concerning how drought affects the symbiotic relationship between nitrogen fixing soil rhizobia and the host plant (Ferguson et al., 2010). This unique symbiotic relationship is initiated by the plant through release of root flavonoids into the rhizosphere, recognized by compatible Rhizobium sp. Flavonoid signaling results in bacterial production of specific lipochito-oligosaccharides (Nod factors) secreted by rhizobia (Kondorosi et al., 2013). Nod factors are in turn recognized by specific LysM receptor-like kinases located on root epidermal cells. Nod factor binding results in genetic and metabolic signaling cascades that are mediated, at least in part, by cell specific nuclear Ca2+ oscillations (Charpentier and Oldroyd, 2013). The signaling cascade results in increased division of cortical cells within the root infection area with formation of composite structures derived from the two symbiotic partners (Gage, 2004). This bacterial infection thread allows rhizobia penetrating deep into the dividing cellular profile resulting in a new organ, the N-fixing 'nodule,' housing infected rhizobia replicating within nodule cells (Oldroyd et al., 2011; Oldroyd, 2013). Inside infected cells, rhizobia are encapsulated with a plant-derived membrane forming the facultative organelle, the symbiosome (Oldroyd, 2013). The symbiosome provides strict plant control on movement of nutrients from bacteria and regulates rhizobial activity and persistence. The symbiosis is facultative and initiated by nitrogen starvation of the host plant (Maróti and Kondorosi, 2014). Within the symbiosome, bacteria differentiate into an endosymbiotic form (bacteroids) for fixing N2 into ammonium. This energyrequiring process is dependent on photosynthate supplied by the shoots. Fixation is catalyzed by the bacterial enzyme nitrogenase requiring a low, but stable, oxygen environment achieved in part through activity of a nodule localized oxygen diffusion barrier. Continual oxygen flux to support bacteroid respiration is finally ensured by the nodule expressed protein leghaemoglobin.

The purpose of this mini-review is to provide an update on the recent developments that have enhanced our understanding of how drought influences soybean roots/nodules, with a particular focus on root and nodule phenome and symbiotic nitrogen fixation. Effects of drought on the soybean root/nodule transcriptome, proteome and metabolome are also outlined as illustrated in **Figures 1** and **2**.

### DROUGHT-INDUCED CHANGES TO THE ROOT PHENOME

Soybean has an allorhizic root system consisting of a primary root (tap root) and lateral (basal) roots (Ao et al., 2010; Fenta et al., 2014). Decreased root lengths and dry biomass accumulation have been reported in many soybean accessions under drought conditions (Thu et al., 2014). Drought not only changes root architecture (root depth, root branching density, and root angle) but also partitioning of root to shoot biomass with an increase in root mass (Franco et al., 2011; Fenta et al., 2014). Several studies have provided strong evidence that root types either penetrating deep into the soil and attaining greater

FIGURE 1 | Below-ground plant organs affected by drought that can be analyzed using omics technologies, including the rhizobia that form symbiotic relationships with soybean roots.

"root mass at depth" (Lopes et al., 2011; Ali et al., 2016) or roots with large xylem diameters and/or larger lateral root systems with more root hairs are advantageous under drought conditions (Tanaka et al., 2014; Vadez, 2014). Such roots tend to have a greater total surface area, which facilitate maximal moisture and nutrient extraction to maintain photosynthesis (Blum, 2011; Lopes et al., 2011; Comas et al., 2013). The soybean cultivar Jackson is an excellent example possessing this type of root system with long roots growing deep into the soil allowing better water uptake than other more droughtsensitive cultivars (Serraj et al., 1997; Fenta et al., 2014). However, identification of soybean cultivars with improved root architecture characteristics still remains challenging. Classic root phenotyping approaches including analysis of soil cores and applying standard excavation techniques to determine root traits are still the methods of choice (Fenta et al., 2014). Future more accurate non-destructive methods under development are transparent tubes (mini-rhizotrons), to measure with a camera various root characteristics around the outside walls of the tubes, or in situ tomographic measurements of the root system with X-rays (Mooney et al., 2012; Eberbach et al., 2013).

# CHANGES IN THE ROOT TRANSCRIPTOME AND PROTEOME

Transcriptome analysis and Next-Generation Sequencing (NGS) are current strategies to particularly study plant responses to abiotic stress (Fan et al., 2013). Identification of genes underpinning root traits and related drought responses have recently received intensive interest (Manavalan et al., 2009; Libault et al., 2010; Comas et al., 2013; Thao et al., 2013; Satbhai et al., 2015). Among 3,000 genes strongly up-regulated in roots by drought were several transcription factors, receptorlike kinases, calcium signaling components as well as jasmonate and abscisic acid biosynthetic genes (Tripathi et al., 2016). Transcriptome responses to drought are also highly dependent on stress intensity and duration as well as species and organs investigated. In the case of soybean roots, 145 root genes were for example differentially expressed due to drought. Identified gene functions demonstrated a complex drought response with genes involved in different multiple biochemical pathways related to drought adaptation (Stolf-Moreira et al., 2011). Applying the deep SuperSAGE method, increased expression of 1,127 unitags in a stress-tolerant soybean accession were associated with responses to hormone stimuli, water stress, as well as oxidative stresses (Neto et al., 2013). Other transcriptome studies were carried out with soybean cultivars W82 and DT2008. The genome of W82, often used as a model cultivar, was sequenced several years ago (Schmutz et al., 2010). DT2008, an economically important soybean cultivar and widely grown in Vietnam (Vinh et al., 2010; Sulieman et al., 2015), has high drought tolerance (Ha et al., 2013; Sulieman et al., 2015) and better nodule development under drought when compared to W82 (Sulieman et al., 2015). By comparing the root transcriptomes of DT2008 and W82, seedlings under normal and dehydration conditions (2 and 10 h treatment), 38172 soybean genes, which changed in expression, could be annotated with high confidence (Ha et al., 2015). Data suggested that higher drought tolerability of DT2008 roots, when compared to W82, might be attributed to a higher number of root genes induced by early dehydration than by prolonged dehydration. The higher drought tolerability of DT2008 vs. W82 might be further attributed to differential expression of genes associated in osmo-protectant biosynthesis, detoxification, cell wall-related proteins, kinases, transcription factors as well as phosphatase 2C proteins (Ha et al., 2015). In particular, the levels of transcripts encoding the auxin responsive factors (ARFs) GmARF33 and GmARF50 were greatly increased in shoots and roots. For example, GmARF50 transcripts were rapidly increased by 15- and 30-fold after 2 and 10 h of dehydration, respectively (Ha et al., 2013). Further, subjecting Williams 82 to increasing drought conditions caused the total differential expression of 6609 transcripts including many genes involved in hormone (auxin/ethylene), carbohydrate, cell wall-related secondary metabolism as well as transcription factors controlling root growth (Song et al., 2016). However, a more in-depth functional characterization is still required to determine how these transcripts will lead to better drought tolerance.

Several proteomics study have also been carried out to unravel the abiotic stress response mechanism in soybean (Hossain et al., 2013) and root proteins, changed in abundance due to drought, were involved in osmotic-stress responses (Toorchi et al., 2009). These proteomics studies also highlighted again the key role of root genes involved in osmo-protection and encoding kinases and transcription factors in the drought response. Interestingly, decreased amounts of methionine synthase were also found as a response to drought (Mohammadi et al., 2012; Oh and Komatsu, 2015). This enzyme catalyzes the conversion of cysteine into methionine in sulfur metabolism. This protein, of central importance in sulfur metabolism, might therefore be a drought responsive protein underpinning possible epigenetic controls that are triggered in drought response. Lower methionine synthase activity under drought might further negatively affect soybean growth due to less available methionine for protein biosynthesis. Furthermore, a great number of root metabolites, such as coumestrol, also change during drought (Tripathi et al., 2016). Coumestrol possibly stimulates mycorrhizal colonization and there is emerging evidence that mycorrhizal plants have improved drought tolerance (Armada et al., 2016).

### EXPLORING THE NODULE PHENOME

Soybean has determinate nodules formed by the symbiotic interaction of a soybean plant with Bradyrhizobium (Herridge et al., 2008). Despite symbiotic N2 fixation is adequate to meet the nitrogen needs of the soybean crop, high-yielding soybeans benefit from supplemental N applications, since N2 fixation capacities are not always sufficient to produce high yields. However, nodule numbers are only decreased when soybean plants are subjected to severe drought conditions (Fernandez-Luquen et al., 2008; Márquez-García et al., 2015). Nodule drought tolerance has been linked to the ability to sustain a supply of photosynthate to the nodules during drought and to greater nodule biomass (King and Purcell, 2001). The relationships between the frequency and intensity of nodulation and root growth and architecture are, however, still poorly understood, particularly the factors that control nodule density per unit root length in the absence and presence of stress. Furthermore, although nitrate is required for root development, it has a negative impact on nodulation (Ferguson et al., 2010). Therefore, improving root and nodule development under drought requires in the future a better understanding of the consequences of the signaling of nitrate and related nutrients, such as phosphate, on root development together with the impact of drought-induced changes on nutrient availability on symbiotic nitrogen fixation.

Exposure to severe drought also impairs nitrogenase activity. This may be caused by several factors including impairment of the supply of photosynthate to the nodules to drive symbiotic nitrogen fixation and breakdown of the oxygen diffusion barrier or loss of leghemoglobin (King and Purcell, 2006; Arrese-Igor et al., 2011). In exchange for photosynthate, soybean nodules deliver reduced nitrogen in form of ureides (allantoin and allantonic acid), mediated by UPS1 transporter proteins (Collier and Tegeder, 2012), to the plant, providing the nitrogen that

is required for biomass production and finally seed protein production. However, the molecular mechanisms that support ureide export to the plant via the xylem have so far not been fully characterized.

# EXPLORING THE NODULE TRANSCRIPTOME AND PROTEOME

Studies on nodule transcriptome profiles have largely focused on the early stages of nodule development. The release of the complete soybean genome (Schmutz et al., 2010) and the RNAseq atlas of genes expressed in fourteen different soybean tissues, including nodules, (Severin et al., 2010) provide currently a useful genetic resource to also study single nodule genes, or gene networks, after drought exposure with automated bioinformatics methods predicting also gene regulatory networks (Zhu et al., 2013). A recently predicted soybean nodulationrelated regulatory gene network, consisting of 10 regulatory modules, might be also applicable to investigate drought effects on nodule gene expression. Transcriptome studies have been generally limited by poor genome annotation, but the situation is gradually improving with the growing annotated soybean genome database (Severin et al., 2010). The previous application of Suppression Subtractive Hybridisation (SSH) technology on soybean nodules, in the absence and presence of drought, largely identified sequences with unknown functions. Only relatively few drought-responsive transcripts had known functions applying this technology including ferritins and metallothionins involved in metal detoxification, particularly in response to oxidative stress (Clement et al., 2008). We recently also explored the nodule cysteine protease transcriptome during developmental nodule senescence. Several papain-like and legumain-like cysteine proteases, also called vacuolar processing enzymes (VPEs), were identified to be strongly expressed during nodule senescence (Van Wyk et al., 2014). In nodules, papain-like cysteine proteases have known functions in the regulation of bacterial symbiosis and nitrogen fixation, they target for example leghemoglobin (Van de Velde et al., 2006; Li et al., 2008). We have recently also found that inhibition of papain-like cysteine protease activity can improve soybean tolerance to drought and favors increased nodulation (Quain et al., 2014, 2015). VPEs are involved in developmental senescence and activation of pre-proteases. With their caspaselike activity, they further play an important role in programmed cell death (PCD) (Hara-Nishimura et al., 2005; Roberts et al., 2012). Other such identified cysteine proteases with caspase-1 like activity include the 20S proteasome beta subunit 1 (PBA1; casapase-3 like activity), DEVDase (Hatsugai et al., 2009; Gu et al., 2010; Han et al., 2012), YVADase (Hara-Nishimura et al., 2005), VKMDase (Bonneau et al., 2008), VEIDase, and TATDase (Chichkova et al., 2010). Cathepsin B, also with caspase-3 activity and responsible for PCD, is normally bound to an endogenous cysteine protease inhibitor but is released upon perception of PCD triggers (Ge et al., 2016). An interesting aspect would be therefore to investigate in the future if exposure to drought may compromise such protease-inhibitor interactions and hence lead to PCD.

Proteome analyses on legume nodules have not only been carried out to better understand the soybean symbiosome (Clarke et al., 2015), but also to find drought-induced proteome changes. The nodule proteomes of Medicago truncatula and Glycine max were recently compared under drought and drought caused the down-regulation of the entire nodule proteome. Particular proteins down-regulated were lipoxygenases and proteins involved in carbon, nitrogen and sulfur metabolism, similar to the root proteome, and proteins involved in protein turnover (Gil-Quintana et al., 2015). The study also highlighted a high degree of similarity between both legume proteomes. Research carried out on M. truncatula might be, therefore, also directly applicable to other economically important legume crops, such as soybean. Applicable findings include that drought induces a major change in the metabolic profile of M. truncatula nodules with accumulation of amino acids (Pro, His, and Trp) and carbohydrates (sucrose, galactinol, raffinose, and trehalose) associated with a decline of bacteroid proteins involved in C-metabolism (Larrainzar et al., 2009). Further applicable findings are that in M. truncatula nodules methionine biosynthesis is particularly affected by drought and that, despite sufficient S-availability, the nitrogen fixation rate in response to drought declines. Such decline is associated with a down-regulation of proteins involved in biosynthesis of methionine and S-adenosyl-L-methionine (SAM), a precursor in ethylene biosynthesis, as well as ethylene biosynthesis (Larrainzar et al., 2014). These results provide strong evidence for a central importance of sulfur metabolism in the drought response. Also, the recent finding of significant delay in drought-induced leaf senescence in nodulated M. truncatula plants with nodulated plants recovering more effectively from drought, relative to non-nodulated plants, might also be applicable to soybean (Staudinger et al., 2016).

## FOCUS AREAS FOR INTENSIVE EXPLORATION

Technology development is key to future progress. In particular, a major focus must be more accurate, non-invasive monitoring of root architecture and nodulation in the field. Extraction of the entire root system from field-grown plants ("shovelomics") to determine drought-induced changes in root architecture is often laborious and requires destructive root excavation (Fenta et al., 2014). Scientists are often reluctant to work in the field with such system. High throughput root and nodule phenotyping under field conditions by direct screening of root and nodule systems in the soil, without the need for excavation, is therefore very likely crucial for any future soybean improvement.

An exciting future task will also be the development of root and nodule transcriptome, proteome as well as metabolome maps in relation to drought (Nguyen, 2016). However, this should also include more in-depth functional characterization of transcripts/proteins/metabolites and how they lead to better drought tolerance. Transcriptomic and proteomics studies

already indicate that up-regulation of genes involved in osmoprotection and coding for kinases and transcription factors are playing a key role in the drought response in addition to down-regulation of genes coding for proteins involved in nitrogen and sulfur metabolism. Deeper understanding of drought-induced changes in gene/protein/metabolite expression patterns will provide information on gene/protein/metabolite networks underpinning phenotypic traits relevant to stress tolerance and also how they ultimately link to phenome changes allowing new insights into changes required for drought recovery.

Improving the soybean-rhizobia symbiosis might also contribute to better drought tolerance. More robust rhizobia with better osmo-tolerance of rhizobia to persist for longer in droughted soils might thereby be a contributor (Mhadhbi et al., 2013). Recent research has also provided evidence that plant growth-promoting rhizobacterium (PGPR) improve plant adaptation to drought by stimulating lateral root formation and increasing shoot growth (Rolli et al., 2015) with stimulation partly caused by bacterium-produced volatile organic compounds (Wintermans et al., 2016). Also, salicylic acid to assemble a better root microbiome might play a role, since salicylic acid can modulate colonization of the root by specific bacterial families (Lebeis et al., 2015). Pyrrolizidine alkaloids (PAs), involved in plant cell re-programming for micro-symbiont entry, might be further a contributor and a target for investigation. A plant-homo-spermidine synthase (HSS), the first pathwayspecific enzyme of PA biosynthesis, is exclusively localized in nodules (Irmer et al., 2015) suggesting that the plant is the main PA producer. Investigation how drought affects expression of soybean nodule HSS (Glyma.06g126700) might be therefore interesting.

Drought might finally also affect expression of nodule specific cysteine-rich antimicrobial peptides (NCR AMPs) essential for bacteroid development and found in legumes with indeterminate nodules (Mergaert et al., 2003; Horváth et al., 2015). In

### REFERENCES

M. truncatula nodules, the bacteria undergo an irreversible differentiation process producing elongated polyploid bacteroids that cannot resume cell division. This differentiation process is controlled by nodule specific NCRs (Van de Velde et al., 2010; Haag et al., 2011, 2012; Frendo et al., 2013; Horváth et al., 2015). Although 138 NCRs were recently detected in M. truncatula bacteroids (Durgo et al., 2015) such NCRs, or peptides with similar antimicrobial functions, have so far not been found in soybean. Search for similar peptides in soybean and characterizing them under drought might be therefore an interesting future task.

### AUTHOR CONTRIBUTIONS

KK has overall organized the paper and has written the draft paper. BV contributed with knowledge about proteolytic events in nodules and transcriptome analysis. BF contributed with his knowledge about root architecture, nodule characterization and recent developments in root and nodule screening. TK contributed with her knowledge about rhizobia screening for drought tolerance. GD contributed with his knowledge about legumains. CF contributed with her knowledge about nodule biology and and was involved in final writing of the paper.

### ACKNOWLEDGMENTS

This work was funded by the International Foundation of Science (IFS grant C/5151-1), the NRF Incentive funding for rated researchers (90779) and the NRF National Bioinformatics Functional Genomics program (86947). Funding received from the Genomic Research Institute (GRI), University of Pretoria, is also acknowledged. TK thanks the NRF/DST in South Africa for a bursary. CF thanks BBSRC (UK) for financial support (BB/K501839/1).

lowest leaves in soybean (Glycine max Merr.). Annals Bot. 116, 497–510. doi: 10.1093/aob/mcv030

drought stress response strategy in Medicago truncatula. J. Proteomics 136, 202–213. doi: 10.1016/j.jprot.2016.01.006

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Kunert, Vorster, Fenta, Kibido, Dionisio and Foyer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Effective Use of Water and Increased Dry Matter Partitioned to Grain Contribute to Yield of Common Bean Improved for Drought Resistance

Jose A. Polania1, 2 \*, Charlotte Poschenrieder 2 , Stephen Beebe1 and Idupulapati M. Rao1 \*

1 Centro Internacional de Agricultura Tropical, Santiago de Cali, Colombia, 2 Lab Fisiología Vegetal, Facultad de Biociencias, Universidad Autónoma de Barcelona, Bellaterra, Spain

Edited by: Urs Feller, University of Bern, Switzerland

### Reviewed by:

Bingcheng Xu, Chinese Academy of Sciences and Ministry of Water Resources, China Jorge Alberto Acosta-Gallegos, Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, Mexico James Kelly, Michigan State University, USA

### \*Correspondence:

Jose A. Polania<EMAIL_ADDRESS>Idupulapati M. Rao<EMAIL_ADDRESS>
### Specialty section:

This article was submitted to Agroecology and Land Use Systems, a section of the journal Frontiers in Plant Science

> Received: 30 March 2016 Accepted: 29 April 2016 Published: 12 May 2016

### Citation:

Polania JA, Poschenrieder C, Beebe S and Rao IM (2016) Effective Use of Water and Increased Dry Matter Partitioned to Grain Contribute to Yield of Common Bean Improved for Drought Resistance. Front. Plant Sci. 7:660. doi: 10.3389/fpls.2016.00660 Common bean (Phaseolus vulgaris L.) is the most important food legume in the diet of poor people in the tropics. Drought causes severe yield loss in this crop. Identification of traits associated with drought resistance contributes to improving the process of generating bean genotypes adapted to these conditions. Field studies were conducted at the International Center for Tropical Agriculture (CIAT), Palmira, Colombia, to determine the relationship between grain yield and different parameters such as effective use of water (EUW), canopy biomass, and dry partitioning indices (pod partitioning index, harvest index, and pod harvest index) in elite lines selected for drought resistance over the past decade. Carbon isotope discrimination (CID) was used for estimation of water use efficiency (WUE). The main objectives were: (i) to identify specific morpho-physiological traits that contribute to improved resistance to drought in lines developed over several cycles of breeding and that could be useful as selection criteria in breeding; and (ii) to identify genotypes with desirable traits that could serve as parents in the corresponding breeding programs. A set of 36 bean genotypes belonging to the Middle American gene pool were evaluated under field conditions with two levels of water supply (irrigated and drought) over two seasons. Eight bean lines (NCB 280, NCB 226, SEN 56, SCR 2, SCR 16, SMC 141, RCB 593, and BFS 67) were identified as resistant to drought stress. Resistance to terminal drought stress was positively associated with EUW combined with increased dry matter partitioned to pod and seed production and negatively associated with days to flowering and days to physiological maturity. Differences in genotypic response were observed between grain CID and grain yield under irrigated and drought stress. Based on phenotypic differences in CID, leaf stomatal conductance, canopy biomass, and grain yield under drought stress, the lines tested were classified into two groups, water savers and water spenders. Pod harvest index could be a useful selection criterion in breeding programs to select for drought resistance in common bean.

Keywords: canopy biomass, carbon isotope discrimination, pod harvest index, terminal drought stress, water use efficiency

### INTRODUCTION

Common bean (Phaseolus vulgaris L.) is the most important food legume in the tropics of Latin America and eastern and southern Africa.  The yield of beans is affected by various constraints (Thung and Rao, 1999). Among those drought is responsible for losses between 10 and 100%. About 60% of the bean-producing regions have prolonged periods of water shortage and drought is the second most important factor in yield reduction after diseases (Thung and Rao, 1999; Rao, 2014). The development of bean varieties resistant to drought stress conditions through breeding is a useful strategy to increase food security in marginal areas. Breeding programs for improving resistance to drought usually select the best genotypes based on grain yield under drought stress (Rosales et al., 2012). A physiological approach using morpho-physiological traits as selection criteria can increase the possibility of combining parents with complementary traits, provided the germplasm is characterized more thoroughly than just testing for yield (Reynolds and Trethowan, 2007; Mir et al., 2012). A useful trait must exhibit higher heritability, enough genetic variability, correlation with yield, and its evaluation must be fast, easy and cheap (Jackson et al., 1996; Araus et al., 2002; Beebe et al., 2013).

Three key processes, among others, have been related to improved drought resistance: (i) acquiring greater amount of water by the root system from the soil profile to facilitate transpiration, (ii) acquiring more carbon (biomass) in relation to water transpired, and (iii) increased mobilization of accumulated carbon to the harvestable economic product (Condon et al., 2004). Previous research identified several traits that contribute to improved resistance of common bean to drought and these include earliness, deep rooting, and greater ability to partition dry matter to grain production (Hall, 2004; Beebe et al., 2013; Rao et al., 2013; Rao, 2014). Water use efficiency (WUE), or "more crop per drop" is considered as an important component of drought resistance in different crops (Blum, 2009; Sinclair, 2012; Vadez et al., 2014). Increased WUE reduces the rate of transpiration and crop water use, processes that are crucial for carbon assimilation, biomass production, and yield (Blum, 2009; Sinclair, 2012). However, the reduction in water use is generally achieved by plant traits and environmental responses that could also reduce yield potential (Blum, 2005). WUE is a complex trait and difficult to phenotype, preventing many breeding programs from using WUE directly (Araus et al., 2002; Easlon et al., 2014). In contrast to WUE, effective use of water (EUW) implies maximal soil moisture capture for transpiration, and also involves decreased non-stomatal transpiration and minimal water loss by soil evaporation (Blum, 2009). EUW is relevant when there is still soil water available at maturity or when deeprooted genotypes access water deep in the soil profile that is not normally available (Araus et al., 2002). Ideotypes of plants have been proposed by Blum (2015) for targeting in plant breeding according to agro-ecological zones and types of drought such as, the isohydric ("water saving") plant model and the anisohydric

One plant attribute that has been associated with WUE is carbon isotope discrimination (CID), based on the inverse relationship between CID and WUE (greater 13C discrimination being associated with lower values of WUE, or conversely, more water use and transpiration). Selection for low 13C discrimination has been proposed as a screening method to improve WUE in breeding C3 crops (Araus et al., 2002; Khan et al., 2007; Easlon et al., 2014). Use of CID presented some advantages by reflecting integration over long periods of gas exchange during crop development, high throughput sampling, relatively low cost, and high heritability (Easlon et al., 2014). In bush bean under moderate droughts or non-arid environments, it has been observed that there is a positive relationship between CID, root length density and grain yield (Sponchiado et al., 1989; White et al., 1990; White, 1993; Hall, 2004; Polania et al., 2012). Increased water use is associated with increased accumulation of carbon and plant growth. However, improved harvest index (HI) or enhanced mobilization of photosynthates to grain production plays an essential role in increase of yield under stress. In most environments with drought, water deficit occurs during reproductive development, reducing HI (Blum, 2009). Several studies in common bean have shown that increased dry matter partitioned to pod and seed formation contributes to better grain yield under drought as well as low soil fertility stress (Rao, 2014). Therefore, assimilate partitioning is an important attribute to evaluate adaptation to abiotic stress in common bean (Rosales-Serna et al., 2004; Beebe et al., 2008, 2013; Klaedtke et al., 2012; Polania et al., 2012, 2016; Rosales et al., 2012; Assefa et al., 2013; Rao et al., 2013; Rao, 2014).

The main objectives of this study were: (i) to identify specific morpho-physiological traits that contribute to improved resistance to drought in lines developed over several cycles of breeding and that could be useful as selection criteria in breeding beans for drought resistance; and (ii) to identify genotypes with desirable traits that could serve as parents in breeding programs that are aimed to improve drought resistance.

### MATERIALS AND METHODS

### Experimental Site and Meteorological Conditions

Two field trials were conducted during the dry season (from June to September in both 2012 and 2013), at the main experiment station of the International Center for Tropical Agriculture (CIAT) in Palmira, Colombia, located at 3◦ 29′′ N latitude, 76◦ 21′′ W longitude and at an altitude of 965 m. Basic characteristics of this field site were described previously (Beebe et al., 2008). The soil is a Mollisol (Aquic Hapludoll) with adequate nutrient supply and is estimated to permit storage of 100 mm of available water (assuming 1.0 m of effective root growth with −0.03 and −1.5 MPa as upper and lower limits for soil matric potential). During the crop-growing season, maximum and minimum air temperatures in 2012 were 31.0 and 19.0◦C, and in 2013 were 30.2 and 19.2◦C, respectively. Total rainfall during the active crop growth was 85.8 mm in 2012 and 87.7 mm in 2013. The potential pan evaporation was of 385.2 mm in 2012 and 351.0 mm in 2013. Two levels of water supply (irrigated and rainfed) were applied to simulate well-watered (control) and drought stress treatments respectively. Trials were furrow irrigated (∼35 mm of water per irrigation). The drought stress treatment under rainfed conditions in 2012 received three irrigations (at 3 days before planting and at 5 and 23 days after planting) and in 2013 also received three irrigations (at 3 days before planting and at 4 and 15 days after planting). In both years, irrigation was suspended after the third irrigation to induce terminal drought stress conditions. The irrigated control treatment received five irrigations in 2012 and six irrigations in 2013 to ensure adequate soil moisture for crop growth and development.

### Plant Material and Experimental Design

For this study 36 bush bean genotypes belonging to the Middle American gene pool were selected: 22 elite lines of common bean (BFS 10, BFS 29, BFS 32, BFS 67, MIB 778, NCB 226, NCB 280, RCB 273, RCB 593, SCR 16, SCR 2, SCR 9, SEN 56, SER 118, SER 119, SER 125, SER 16, SER 48, SER 78, SMC 141, SMC 43, and SXB 412); five interspecific lines between elite line SER 16 and Phaseolus coccineus (ALB 6, ALB 60, ALB 74, ALB 88, and ALB 213); one landrace of tepary bean (Phaseolus acutifolius) G40001 from Veracruz-Mexico, and two interspecific lines between tepary bean and common bean (INB 841 and INB 827 developed from five cycles of congruity backcrossing of tepary with ICA Pijao). BFS (small red) lines were developed to improve adaptation to low soil fertility and drought. SER and SCR (small red), SEN (small black), and NCB (small black) lines were developed for improved adaptation to drought. ALB (small red) lines were developed for improved adaptation to drought and aluminum toxicity. RCB (small red) lines were developed for improved yield potential, disease resistance, and commercial grain. SEA 15 and BAT 477 were included as drought resistant checks, and three commercial cultivars of common bean (DOR 390, Pérola and Tio Canela) as drought sensitive materials. BAT 477 NN was included as a non-nodulating bean genotype. In the 2 years, a 6 × 6 partially balanced lattice design with three replications was used. Experimental units consisted of 4 rows with 3.72 m row length with a row-to-row distance of 0.6 m and plant-toplant spacing of 7 cm (equivalent to 24 plants m−2 ). Trials were managed by controlling weeds with application of herbicides (Fomesafen, Fluazifop-p-butil, and Bentazon) and pests and diseases by spraying with insecticides (Thiametoxam, Clorpirifos, Imidacloprid, Abamectina, Cyromazine, and Milbemectin) and fungicides (Benomil and Carboxin) as needed.

### Yield Measurements and Phenological Assessment

Grain was harvested from two central rows after discarding end plants in both the irrigated and drought plots. Mean yields per hectare were corrected for 0% moisture in grain. Days to flowering (DF) and days to physiological maturity (DPM) were recorded for each plot. DF is defined as the number of days after planting until 50% of the plants have at least one open flower. DPM is the number of days after planting until 50% of plants have at least one pod losing its green pigmentation. The geometric mean (GM) of grain yield was determined as (NS × DS)1/2 where NS is no stress (irrigated) and DS is drought stress. The drought response index (DRI) was calculated as indicator of drought resistance as described before (Bidinger et al., 1987; Krishnamurthy et al., 2010), using DF under rainfed conditions for every individual plot and yield potential as arithmetic mean of grain yield under irrigated conditions across replications.

### Physiological Measurements

At mid-pod filling, a 50 cm segment of the row (equivalent to an area of 0.3 m2 ) from each plot with about seven plants was used for destructive sampling to measure total canopy biomass (CB) and leaf area index (LAI). Leaf area was measured using a leaf area meter (model LI-3000, LI-COR, NE, USA) and the LAI was calculated as leaf area per unit land area. Also, at mid-pod filling the stomatal conductance was measured with a portable leaf porometer (Decagon SC-1) on a fully expanded young leaf of one plant within each replication. Measurements were made late in the morning \$(10 a.m.–12 noon) on clear, sunny days with minimal wind. At the time of harvest, plants in 50 cm of a row from each plot were cut and dry weights of stem, pod, seed, and pod wall, seed number per area (SNA), and pod number per area (PNA) were recorded. The following attributes were determined according to Beebe et al. (2013): harvest index (HI) (%): seed biomass dry weight at harvest/total shoot biomass dry weight at mid-pod filling × 100; pod harvest index (PHI) (%): seed biomass dry weight at harvest/pod biomass dry weight at harvest × 100; pod partitioning index (PPI) (%): pod biomass dry weight at harvest/total canopy biomass dry weight at mid-pod filling × 100. HI and PPI were estimated using the CB value at mid-pod filling growth stage which is assumed to be the time that reflects the maximum vigor of the genotype. It is assumed that from this time common bean begins to lose canopy biomass through leaf fall, especially under terminal drought stress. Shoot and seed total nonstructural carbohydrates (TNC) concentrations were determined according to the method described by Kang and Bringk (1995).

One plant of each genotype from each plot (irrigated and drought) was selected for destructive sampling at mid-pod filling. A random sample of grain per experimental unit was selected, washed thoroughly and ground. The ground samples of plants at mid-pod filling and grain at harvest were sent to UC Davis Stable Isotope Facility in USA for 13C analysis. CID (113C in ‰) was calculated according to the following equation, where δ 13Cs and δ 13Ca are sample and atmospheric concentrations of 13C, respectively, and carbon isotope composition of atmosphere is assumed to be −8.0‰(Farquhar et al., 1989). Isotopic discrimination between 13C and 12C (1) in shoot and grain was related to whole plant water use (Farquhar et al., 1989).

$$\Delta \text{ 13C (CID) } = \frac{[\\$13 \text{Ca} - \\$13 \text{Cs}]}{[1 + (\\$13 \text{Cs}/1000)]}$$

### Statistical Analysis

All data were analyzed using the SAS (v 9.0) PROC MIXED and PROC CORR (SAS Institute Inc., 2008). The adjusted means for each genotype and the environment (irrigated and rainfed) were obtained using the mixed models theory together with the MIXED procedure considering the effects of the replications and blocks within replications as random and genotypes as fixed. Correlation coefficients were calculated by the PROC CORR. Values reported with ∗ , ∗∗, or ∗∗∗ are statistically significant at probability levels of 5, 1, and 0.1%, respectively.

# RESULTS

### Grain Yield

The data on rainfall distribution, water applied through irrigation, and pan evaporation in both trials indicated that the crop suffered terminal drought stress during crop development under rainfed treatment conditions. The mean value of grain yield under drought conditions decreased by 56% compared with irrigated conditions (**Table 1**). Under drought conditions the grain yield of 36 genotypes ranged from 59 to 1526 kg ha−1 (**Table 1**). Among the genotypes tested, the lines BFS 29, NCB 280, SEN 56, BFS 10, SEA 15, and NCB 226 were superior in their resistance to drought stress. The relationship between grain yield of drought and irrigated treatments indicated that BFS 29, NCB 280, SEN 56, BFS 10, and NCB 226 were not only drought resistant but were also responsive to irrigation (**Table 1**). Among the 36 genotypes tested, the biofortified line MIB 778, was the most sensitive to drought stress. MIB 778 is an interspecific progeny of common bean and P. dumosus, which may explain its extreme sensitivity to drought. The genotypes Pérola, DOR 390, SMC 43, and ALB 88 were also sensitive to drought stress (**Table 1**).

### Leaf Stomatal Conductance and Carbon Isotope Discrimination

Leaf stomatal conductance presented a significant positive correlation with grain yield under both irrigated (0.24∗∗) and drought stress (0.31∗∗∗) conditions (**Table 3**). The lines NCB 280, SEN 56, SCR 16, SMC 141, NCB 226, SEA 15, and BFS 10, combined higher values of leaf stomatal conductance with better grain yield under drought stress (**Tables 1, 2**). The lines MIB 778, Pérola, SMC 43, and DOR 390 presented lower values of stomatal conductance combined with lower grain yield under drought stress (**Tables 1, 2**). Similarly correlations and differences in genotypic response were observed between grain CID and grain yield under irrigated and drought stress conditions (**Table 3**). The accession of P. acutifolius G 40001 and the lines SER 16, ALB 6, and ALB 60 presented lower values of leaf stomatal conductance and grain CID (lower use of water) combined with moderate plant growth and grain yield under drought stress (**Tables 1, 2**).

# Canopy Biomass (CB), Pod Partitioning Index (PPI), and Pod Harvest Index (PHI)

A positive and significant correlation was observed between CB and grain yield under both irrigated and drought conditions, 0.39∗∗∗ and 0.59∗∗∗, respectively (**Table 3**). The drought resistant lines combined higher CB production with higher grain yield under drought stress conditions. The drought susceptible lines presented lower values of both CB and grain yield under drought conditions (**Table 1**). It is important to note that the sampled area to determine CB at mid-pod filling was small and this could overestimate the total CB values per hectare. This small area was selected to facilitate comparison of large number of genotypes. Lines with superior grain yield showed higher values of LAI under drought stress (**Table 3**). The PPI reflects the biomass partitioned to pods at harvest as a proportion of the total CB at mid-pod filling growth stage. This ratio and HI may be overestimated because we used the CB values at midpod filling growth stage with the assumption that this growth stage reflects the maximum vigor. The values of CB may be underestimated if vegetative growth continues between mid-pod filling to physiological maturity due to irrigation or intermittent rainfall. Correlation coefficients between grain yield and PPI were positive and highly significant under drought conditions (**Table 3**). Also, the drought resistant lines combined higher value of PPI and grain yield under drought stress conditions while the drought susceptible lines showed lower ability in partitioning of dry matter to pod production under drought conditions (**Table 1**). The lines SMC 141 and SER 118 were outstanding in dry matter partitioning to pod production, but the CB values of these lines were lower under drought stress (**Table 1**).

The PHI value reflects the biomass partitioned to seed as a proportion of total pod biomass. A positive and highly significant correlation of PHI with grain yield was observed under both irrigated and drought conditions (**Table 3**). The lines identified as drought resistant were superior in PHI, resulting in a higher grain yield under drought conditions. The drought susceptible lines described previously showed lower ability in partitioning of dry matter from plant structures to pod production (PPI) and from podwall to seed production (PHI) resulting in poor performance under drought stress (**Figure 2**, **Table 1**). The accession of P. acutifolius (G 40001) and the lines INB 841 and SER 118 likewise presented higher values of PHI under drought stress. A weak positive correlation between grain yield and seed TNC was observed under both irrigated and drought stress conditions (**Table 3**). The drought resistant lines combined higher seed TNC concentration with higher grain yield under drought stress. The drought susceptible lines presented lower seed TNC concentration and grain yield under drought stress.

### Days to Flowering (DF), Days to Physiological Maturity (DPM), Pod Number Per Area (PNA), Seed Number Per Area (SNA), and 100 Seed Weight

Results on the analysis of DRI showed that the lines SMC 141, BFS 10, BAT 477, NCB 280, SEA 15, SCR 16, BFS 67, NCB 226, SEN 56, and SER 78 were drought resistant with higher values of DRI, while Pérola, RCB 273, ALB 74, BFS 32, DOR 390, SMC 43, ALB 88, INB 841, and MIB 778 were highly drought sensitive with lower values of DRI (**Table 1**). A negative and significant correlation was observed between DF and grain yield under both irrigated and drought conditions, −0.51∗∗∗ and

TABLE 1 | Phenotypic differences in canopy biomass, pod partitioning index, grain yield and drought response index (DRI) of 36 genotypes of common bean grown under irrigated and drought conditions in 2012 and 2013 at Palmira, Colombia.

Values reported are mean for two seasons. GM = geometric mean. \*Significant difference at 0.05 level as estimated from the MIXED procedure.

−0.53∗∗∗, respectively (**Table 3**). The lines identified as drought resistant described previously combined shorter DF with higher grain yield under drought stress conditions (**Tables 1, 2**). The drought susceptible checks Tío Canela, Pérola, and DOR 390 and the lines MIB 778 and SMC 43 showed sensitivity to drought stress with greater DF under drought conditions (**Table 2**). The same response was observed in DPM (**Table 2**), that showed a negative and highly significant correlation with grain yield under both irrigated and drought treatments (**Table 3**). The drought resistant lines with shorter DF also showed shorter DPM with superior grain yield than the other genotypes under drought stress (**Tables 1, 2**). A negative and significant correlation was observed between DF and CB (r = −0.18∗∗ and r = −0.35∗∗∗) and DPM and CB (r = −0.13∗ and r = −0.20∗∗) under irrigated and drought conditions, respectively. The PNA, SNA, and 100 seed weight showed a positive and highly significant correlation with grain yield under both irrigated and drought treatments (**Table 3**). The lines BFS 29, BFS 10, NCB 280, SEN 56, SCR 16, SCR 2, and NCB 226 showed higher values of PNA than the other genotypes under drought stress conditions (data not

Values reported are mean for two seasons. \*Significant difference at 0.05 level as estimated from the MIXED procedure.

shown). These lines also presented higher values of SNA. The line SEA 15 showed the highest value of 100 seed weight under drought stress followed by NCB 226, SCR 2, SCR 16, NCB 280, and BFS 10. The genotypes ALB 88, DOR 390, SMC 43, Pérola, and MIB 778 produced less pods and seeds under drought stress.

### DISCUSSION

This study permitted evaluating a diverse set of elite common bean breeding lines recently developed for improving resistance to drought stress. It was conducted in the light of past experience with shoot traits such as CID, stomatal conductance, canopy biomass, and indices of dry matter partitioning such as PPI, PHI, and HI. The lines were derived from crosses among bean races (Beebe et al., 2008), as well as interspecific crosses with introgression from P. coccineus (Butare et al., 2012) or P. acutifolius (Beebe, 2012). The lines NCB 280, NCB 226, SEN 56, SCR 2, SCR 16, SMC 141, RCB 593, BFS 67, SER 16, ALB 60, ALB 6, BFS 10, and BFS 29 developed over several cycles of breeding to drought limitation were found to be remarkably drought resistant. These lines also showed values of grain yield that doubles the values under drought stress of three leading commercial cultivars in Latin America:

Polania et al. Traits Contributing to Drought Resistance

TABLE 3 | Correlation coefficients (r) between final grain yield (kg ha−1) and other shoot attributes of 36 genotypes of common bean grown under irrigated and drought stress conditions in 2012 and 2013 at Palmira, Colombia.

Mean values of two seasons were used for correlation analysis.\* , \*\* , \*\*\* Significant at the 0.05, 0.01, and 0.001 probability levels, respectively.

DOR 390, Perola, and Tío Canela. We removed the effects of drought escape (early flowering) and yield potential (optimally irrigated yield) by estimating DRI through analysis. We found a relationship between genotypes with higher values of grain yield under drought stress and higher values of DRI. This positive relationship indicates that genotypes with higher values of grain yield under drought stress are physiologically responsive to drought stress. This analysis also allowed us to examine drought resistance that can be explained by physiological measurements made in this study and discussed below.

### Grain Yield and Carbon Isotope Discrimination (CID)

The relationship between different tissues sampled for CID and grain yield, showed that using grain sample is more relevant than CB sample at mid-pod filling in the determination of CID for common bean under drought conditions. We consider that the use of grain sample for CID determination makes more sense in the case of common bean under terminal drought stress. This is because it is taken at maturity, and it would reflect an integrated effect of gas exchange during a critical and important crop growth stage which is grain filling. In our experimental conditions the effect of terminal drought is stronger at harvest than at mid-pod filling. A relationship was observed between stomatal conductance and grain CID under rainfed conditions, with differences in performance among some genotypes (**Figure 1**, **Table 2**). Stomatal conductance and CID are useful measurements to track plant responses to drought but these depend on different processes. CID depends on variation in photosynthetic biochemistry, conductance of CO2 to the leaf interior and the chloroplasts, or a combination of these (Seibt et al., 2008; Easlon et al., 2014). After evaluating 36 advanced lines

over two seasons, several drought resistant genotypes showed a clear evidence of superior access to soil moisture, and a few drought resistant genotypes showed a contrasting pattern for using less water. These results allowed us to classify the genotypes into two groups: water savers (isohydric plants) and water spenders (anisohydric) and this could facilitate targeting genotypes suitable to different agro-ecological zones (Blum, 2015). We classify NCB 280, SMC 141, SCR 16, SEN 56, BFS 67, and NCB 226 as water spenders that are able to access more water and show better water status during their canopy growth and grain development, resulting in higher grain yield. Our results also indicate that these lines maximize their capture of soil water for transpiration and maintain adequate gas exchange rates thus contributing to improved growth and greater proportion of biomass partitioned to grain (**Figure 1**, **Tables 1**, **2**). We consider that these lines were drought resistant through EUW as proposed by Blum (2009). These genotypes should be useful for cultivation in areas exposed to intermittent drought stress in Central America, South America, and Africa, particularly in agroecological regions where rainfall is intermittent during the season and soils that can store greater amount of available water deep in the soil profile.

We also identified a few genotypes that are combining lower values of grain CID and stomatal conductance with better grain yield under rainfed conditions, and we classified these genotypes as water savers, which are BFS 10, SER 16, ALB 6, ALB 60, and G 40001 (**Figure 1**, **Tables 1**, **2**). The line G 40001 (P. acutifolius) of tepary bean presents different traits related to drought resistance confirming its behavior as water saver with a combination of morpho-physiological characteristics such as greater ability for partitioning dry matter to grain, fine roots, smaller leaves for reduced water use, and reduced stomatal conductance (Mohamed et al., 2005; Butare et al., 2011; Rao et al., 2013; Beebe et al., 2014). Our classification of the line SER

16 as water saver is consistent with a previous study conducted under greenhouse conditions where this line was characterized as responsive to soil drying by closing its stomata sooner than the other genotypes during progressive soil drying (Devi et al., 2013). The water savers could be more suitable to bean farmers in semiarid to dry environments, dominated by terminal type of drought stress in Central America, Africa, northern Mexico, and north-east Brazil.

We also identified a group of genotypes (BFS 29, SEA 15, SER 125, and RCB 593) with intermediate response in terms of either as water spenders or as water savers with higher grain yield and these genotypes may be suitable for improving yield stability in drought-prone areas. The correlation between grain CID and grain yield under drought stress was weak but positive (**Table 3**). This is because of a few water saving genotypes that influenced the correlation. The values of grain CID are useful to classify genotypes as either water spenders or water savers together with other morpho-physiological attributes such as leaf stomatal conductance.

### Grain Yield, Canopy Biomass, and Indices of Dry Matter Partitioning

Total shoot biomass or CB can be understood in a physiological sense as the result of accumulated net photosynthesis of the crop, and it is shown to be related to yield in several crops (Araus et al., 2002). Several drought resistant lines were outstanding in CB production and grain yield under drought stress. Also these lines were superior in leaf area development under drought stress. These lines were able to access more water, as reflected in the values of grain CID. This, combined with increased dry matter partitioned to grain (HI and PHI), resulted in improved resistance to drought (Muñoz-Perea et al., 2007; Polania et al., 2012, 2016; Assefa et al., 2013; Rao et al., 2013; Beebe et al., 2014; Rao, 2014). Compared with the drought-sensitive checks DOR 390, Pérola, and Tio Canela, most of the bred lines showed a higher accumulation of CB at mid-pod filling growth stage. These results show significant progress in breeding for improved CB accumulation and enhanced dry matter partitioning toward pod and grain production. Previous research suggested that the drought resistance in common bean is associated with a more efficient dry matter partitioning to pod formation and grain production (Hall, 2004; Rosales-Serna et al., 2004; Cuellar-Ortiz et al., 2008; Klaedtke et al., 2012; Rosales et al., 2012; Assefa et al., 2013; Beebe et al., 2013, 2014; Rao et al., 2013; Rao, 2014). The positive and significant correlations between grain yield and biomass partitioning indices (PPI, HI, and PHI) under drought stress (**Table 3**) highlight the importance of improved dry matter partitioning from plant biomass to pod formation (PPI) and grain production (PHI). Genotypes that increased the proportion of dry matter partitioned to grain also showed higher values of TNC in seed (results not shown). The lines BFS 29, SEA 15, BFS 10, NCB 280, SEN 56, SCR 16, and SMC 141 showed greater grain yield under drought and were superior in their ability to partition greater proportion of biomass to pod and grain production (**Figure 2**, **Table 1**). The lines INB 841 and SER 118 showed especially higher values of PPI and PHI across years under stress, and both are excellent parents. Breeding programs should focus on the selection of best-performing materials that combine greater values of CB as a result of EUW with greater ability to partition dry matter toward pod development and grain filling. PHI could serve as a useful selection criterion for improving drought resistance because of its simplicity in measurement and its significant correlation with grain yield under both irrigated and drought conditions (Assefa et al., 2013).

### Grain Yield, Phenology, and Yield Components

Early maturing genotypes were more adapted to drought stress and responsive to irrigation. Farmers have multiple reasons for preferring short season varieties, one of them is to minimize exposure to drought (White and Singh, 1991; Beebe, 2012). Early maturity has been a standard mechanism to confront drought in breeding programs, and it is a trait that may be more useful where terminal drought predominates (Beebe et al., 2014). However, previous results indicated that a shorter growth cycle can reduce grain yield potential per day by an estimated 74 kg ha−1 (White and Singh, 1991). In contrast, recent results show that early maturing genotypes with increased dry matter partitioned to grain can compensate this effect, indicating that high yielding lines had higher grain yield per day compared with low yielding genotypes under drought (Klaedtke et al., 2012; Rao et al., 2013; Beebe et al., 2014). We also observed a negative and significant correlation between phenology (DF and DPM) and CB and phenology and SNA under both irrigated and drought stress conditions. These phenotypic correlations suggest that a rapid accumulation of CB due to EUW, combined with an efficient remobilization of these reserves to the pod and grain formation (higher values of grain yield per day and SNA), is an important adaptive strategy of early maturing and drought resistant genotypes. Significant positive associations between grain yield and PPI, PHI and 100 seed weight under both irrigated and drought conditions suggest that increased dry matter partitioning toward grain, or sink strength, is an important factor in determining grain yield under drought stress (Polania et al., 2016). Greater values of SNA and PNA likewise are consistent with the hypothesis that drought resistant lines have greater sink strength.

An important role for EUW in drought resistance implies that the understanding of the factors controlling the deep rooting and water status of the plant would be of great importance to improve drought resistance. In this scenario, traits such as grain CID related with EUW, CB, PPI, PHI, PNA, and SNA should be also considered as useful plant traits to be included in bean breeding programs aimed for improving drought resistance. Some of these traits are easier to implement in a breeding program due to their simplicity and relatively low analytical cost: PHI, grain CID, PNA, and SNA. Since these parameters could be determined at harvest time, it may be easier for breeders to integrate into on-going breeding efforts.

### CONCLUSIONS

Our results demonstrate that drought resistance in common bean is related to EUW to produce greater canopy biomass, combined with an increased dry matter partitioned from vegetative structures to the pods and subsequently to grain production resulting in higher values of pod and SNA. Several lines (BFS 29, SEA 15, BFS 10, NCB 280, SEN 56, SCR 16, and SMC 141) expressed this desirable combination of traits. Resistance

### REFERENCES

to terminal drought stress was found to be positively associated with EUW combined with superior ability to partition greater proportion of dry matter toward pod and seed production and negatively associated with days to flowering and DPM. Based on phenotypic differences in grain CID, leaf stomatal conductance, canopy biomass and grain yield under drought stress, the lines tested were classified into two groups, water savers and water spenders. We suggest that pod harvest index could be a useful selection criterion in breeding programs to select for drought resistance in common bean.

### AUTHOR CONTRIBUTIONS

JP, CP, SB, and IR designed the experiments and contributed to data interpretation. JP collected and analyzed the data. JP, CP, SB, and IR wrote the paper. All authors read and approved the final manuscript.

### ACKNOWLEDGMENTS

The authors acknowledge the support of the Bill and Melinda Gates Foundation (BMGF), and the CGIAR research program on grain legumes for financial support of research on improving drought resistance in common bean. We also thank Miguel Grajales, Cesar Cajiao, Mariela Rivera, and bean breeding and physiology teams at CIAT, Colombia for their contribution.

common bean (Phaseolus vulgaris L.) cultivars uncovers characteristics related to terminal drought resistance. Plant Physiol. Biochem. 56, 24–34. doi: 10.1016/j.plaphy.2012.04.007

Rosales-Serna, R., Kohashi-Shibata, J., Acosta-Gallegos, J. A., Trejo-López, C., Ortiz-Cereceres, J., and Kelly, J. D. (2004). Biomass distribution, maturity acceleration and yield in drought-stressed common bean cultivars. Field Crops Res. 85, 203–211. doi: 10.1016/S0378-4290(03) 00161-8

SAS Institute Inc. (2008). SAS/STAT R 9.2. Cary, NC: SAS Institute Inc.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Polania, Poschenrieder, Beebe and Rao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Grape Ripening Is Regulated by Deficit Irrigation/Elevated Temperatures According to Cluster Position in the Canopy

Olfa Zarrouk 1 \*, Cecilia Brunetti 2, 3, Ricardo Egipto4 , Carla Pinheiro1, 5 \*, Tânia Genebra1 , Antonella Gori 2, 3, Carlos M. Lopes 4 , Massimiliano Tattini 6 and M. Manuela Chaves 1, 4

1 Instituto de Tecnologia Química e Biológica, Universidade NOVA de Lisboa, Oeiras, Portugal, 2 Trees and Timber Institute, The National Research Council of Italy, Florence, Italy, 3 Department of Plant, Soil and Environmental Sciences, University of Florence, Florence, Italy, 4 Linking Landscape, Environment, Agriculture and Food (LEAF), Instituto Superior de Agronomia, Universidade de Lisboa, Lisboa, Portugal, 5 Faculdade de Ciências e Tecnologia, Universidade NOVA de Lisboa, Caparica, Portugal, 6 Department of Biology, Agriculture and Food Sciences, Institute for Sustainable Plant Protection, The National Research Council of Italy, Florence, Italy

### Edited by:

Urs Feller, University of Bern, Switzerland

### Reviewed by:

Claudio Lovisolo, University of Turin, Italy Amarendra Narayan Misra, Central University of Jharkhand, India

\*Correspondence:

Olfa Zarrouk<EMAIL_ADDRESS>Carla Pinheiro<EMAIL_ADDRESS>
### Specialty section:

This article was submitted to Agroecology and Land Use Systems, a section of the journal Frontiers in Plant Science

> Received: 17 June 2016 Accepted: 18 October 2016 Published: 15 November 2016

### Citation:

Zarrouk O, Brunetti C, Egipto R, Pinheiro C, Genebra T, Gori A, Lopes CM, Tattini M and Chaves MM (2016) Grape Ripening Is Regulated by Deficit Irrigation/Elevated Temperatures According to Cluster Position in the Canopy. Front. Plant Sci. 7:1640. doi: 10.3389/fpls.2016.01640 The impact of water deficit on berry quality has been extensively investigated during the last decades. Nonetheless, there is a scarcity of knowledge on the performance of varieties exposed to a combination of high temperatures/water stress during the growing season and under vineyard conditions. The objective of this research was to investigate the effects of two irrigation regimes, sustained deficit irrigation (SDI, 30% ETc) and regulated deficit irrigation (RDI, 15% ETc) and of two cluster positions within the canopy (east- and west-exposed sides) on berry ripening in red Aragonez (Tempranillo) grapevines. The study was undertaken for two successive years in a commercial vineyard in South Portugal, monitoring the following parameters: pre-dawn leaf water potential, berry temperature, sugars, polyphenols, abscisic acid (ABA) and related metabolites. Additionally, expression patterns for different transcripts encoding for enzymes responsible for anthocyanin and ABA biosynthesis (VviUFGT, VvNCED1, VvβG1, VviHyd1, VviHyd2) were analyzed. In both years anthocyanin concentration was lower in RDI at the west side (RDIW- the hottest one) from véraison onwards, suggesting that the most severe water stress conditions exacerbated the negative impact of high temperature on anthocyanin. The down-regulation of VviUFGT expression revealed a repression of the anthocyanin synthesis in berries of RDIW, at early stages of berry ripening. At full-maturation, anthocyanin degradation products were detected, being highest at RDIW. This suggests that the negative impact of water stress and high temperature on anthocyanins results from the repression of biosynthesis at the onset of ripening and from degradation at later stages. On the other hand, berries grown under SDI displayed a higher content in phenolics than those under RDI, pointing out for the attenuation of the negative temperature effects under SDI. Irrigation regime and berry position had small effect on free-ABA concentration. However, ABA catabolism/conjugation process and ABA biosynthetic pathway were affected by water and heat stresses. This indicates the role of ABA-GE and catabolites in berry ABA homeostasis under abiotic stresses. Principal component analysis (PCA) showed that the strongest influence in berry ripening is the deficit irrigation regime, while temperature is an important variable determining the improvement or impairment of berry quality by the deficit irrigation regime. In summary, this work shows the interaction between irrigation regime and high temperature on the control of berry ripening.

Keywords: ABA metabolism, anthocyanins, flavonols, heat stress Vitis vinifera, water stress

### INTRODUCTION

The effect of water stress on grape berry ripening and quality has been extensively investigated during the last decades (for reviews, see Chaves et al., 2010; Kuhn et al., 2013). Overall, berry quality benefits from mild to moderate water deficit (Chaves et al., 2010) and the reduction in berry development was early proposed as mostly responsible for the improvement of berry quality by water deficits (Matthews and Anderson, 1988). However, more recently water deficit was shown to profoundly alter berry secondary metabolism, particularly of flavonoids, thus greatly regulating the ripening process (development and composition) (Castellarin et al., 2007a,b). The regulation of genes and proteins of the various metabolic pathways is either the consequence of a direct effect of water shortage and/or indirect via the changing of the light environment around grape clusters due to the impairment of vine vegetative growth.

The matter is far from being conclusively addressed, two major causes can be highlighted: the experimental set-ups adopted in the majority of experiments, namely the water stress timing and conditions; the diversity of varieties (Zarrouk et al., 2016). It was shown that pre-véraison water stress promotes the accumulation of anthocyanins, as a consequence of both reduced berry development and enhanced expression of flavonoid genes, thus leading (Basile et al., 2011; Intrigliolo et al., 2012; Romero et al., 2013) to earlier grape ripening (Castellarin et al., 2007a,b). In contrast, water stress imposed at post-véraison just increased the proportion of seeds and skin relative to whole-berry fresh mass, without significant effects on secondary metabolism (Roby and Matthews, 2004).

On the other hand, several reports (Deluc et al., 2009; Girona et al., 2009; Niculcea et al., 2014) have shown that the effect of water deficit on the biosynthesis of phenolics and berry growth is strongly cultivar dependent. The differential increase of anthocyanin compounds in berries under preor post-véraison deficit irrigation was primarily attributed to large differences in abscisic acid (ABA) sensitivity displayed by different varieties (Ferrandino and Lovisolo, 2013). Grape varieties may have either isohydric or anisohydric strategy to cope with water stress, as a consequence of large differences in the ability to regulate water losses through chemical (i.e., ABA) signaling (Deluc et al., 2009; Lovisolo et al., 2010; Balint and Reynolds, 2013; Niculcea et al., 2014). In addition, ABA was reported to strongly control key events of grape ripening through regulation of primary (sugars) and secondary metabolite biosynthesis (e.g., anthocyanins) (Davies et al., 1997; Peppi and Fidelibus, 2008).  These findings support the idea that ripening of non-climacteric grapes is, to a certain extent, ABA-regulated (Davies et al., 1997; Jia et al., 2011; Niculcea et al., 2014). Nonetheless, the expression of 9 cis-epoxycarotenoid dioxygenase (NCED), the enzyme involved in the first committed step of ABA (Qin and Zeevaart, 2002) is not always correlated with the concentration of free-ABA in berries (Deluc et al., 2009; Wheeler et al., 2009). This suggests that products of ABA catabolism/conjugation (Nambara and Marion-Poll, 2003) may be also involved in berry ripening. Free-ABA, the active form of this hormone, may be oxidized by ABA 8′ hydroxylase to phaseic (PA) and dihydrophaseic acids (DPA) or conjugated with glucose to form ABA-glucosylester (ABA-GE), through the action of ABA glucosyltransferase (ABA-GTase). ABA-GE plays an important role in the regulation of ABA content since it releases free-ABA through β-D-glucosidase and it has been proposed to be involved in long-distance transport of ABA.

Several reports showed the impact of water shortage on the hormonal balance of grape berry during ripening (Deluc et al., 2009; Niculcea et al., 2013) and on the ABA catabolites concentrations (Balint and Reynolds, 2013). Zarrouk et al. (2012) showed that both free ABA and ABA-GE are involved in the enhancement of ripening process in stressed berries.

In this context, Coombe (1989) attributes the promotion of sugar accumulation in water stressed berries to a direct effect of ABA signaling on fruit ripening. More recently, Niculcea et al. (2014) observed that the imposition of both types of deficit irrigation (pre- and post-véraison), altered the pattern of ABA accumulation, and relates the improvement of sugar concentration, phenolic substances and anthocyanins to the persistence of ABA production over time in post-véraisonstressed berries. Nonetheless, the enhancement of berry ABA content by water stress is not always accompanied by an increase in sugars or in secondary metabolites. In our previous investigation (Zarrouk et al., 2012), a negative effect of moderate deficit irrigation on grape berry anthocyanin concentration was observed, despite the increase in ABA concentration at véraison, suggesting a decoupling on the ripening process parameters due to other external factor than water deficit. Climate condition, namely high temperature along the growing season is considered a putative constraint to the implementation and success of the deficit irrigation regime (Shellie, 2011). Also, the interaction between elevated temperature and water deficit is considered the main cause of variability in field experiments results (Bonada et al., 2015) namely in what concerns the ripening of wine grapes (Real et al., 2015).

In this context, Fernandes de Oliveira and Nieddu (2013) showed that high temperature at mid-ripening coupled with moderate deficit irrigation (25% of Etc) reduced total anthocyanin content, possibly by degrading these compounds or/and inhibiting their biosynthesis. Bonada et al. (2015) related an advance of the onset of berry net water loss by elevated temperature under water deficit, which hastened berry ripening and altered the balance of sensory traits.

The effect of temperature on berry composition has been studied extensively and the negative impact of high temperature on anthocyanin content was reported (Spayd et al., 2002; Mori et al., 2007; Sadras and Moran, 2012; Bonada and Sadras, 2014; Bonada et al., 2015). Nonetheless, to date, there appears to be a scarcity of knowledge of the performance of different varieties exposed to a combination of high temperatures and water stress during the growing seasons and under vineyard conditions (Greer and Weedon, 2013).

Portugal is the 11th highest wine-producing country worldwide (OIV, 2016), with strong influence of wine industry on the economic stability and development of the country (Fraga et al., 2016). Recent climate studies in Portugal highlight an increase in the temperature during grape growing season (Fraga et al., 2012), with increase in minimum temperature during the ripening period (Malheiro et al., 2010; Fraga et al., 2012) and an acute dryness in summer (Santos et al., 2012). This compromise the optimal climatic conditions to grow most current varieties particularly in southern Portugal (Real et al., 2015), with likely negative impact in wine characteristics. Irrigation is being used to maintain winegrape yield and overcome the negative impact of water stress incidence during the grapevine reproductive season, but the effects of different kinds of irrigation systems on berry and wine quality are still largely unknown.

In this investigation we analyzed the combined effect of water and heat stress in grape berry ripening process. Our experiments with Aragonez variety (syn. Tempranillo) over two consecutive seasons aimed at the revelation of the existence of differences in the accumulation and the biosynthesis of different parameters that define ripening in relation to the cluster position within the canopy and the irrigation regime applied. For this, the effect of two different irrigation regimes on grape berry skin during development was examined. The study focused on sugar accumulation in the berry, anthocyanin and flavonol accumulation in skin, endogenous ABA and ABA metabolites, as well as expression patterns for different transcripts encoding for enzymes responsible for anthocyanin and ABA biosynthesis (VviUFGT, VvNCED1, VvβG1, VviHyd1, VviHyd2).

### MATERIALS AND METHODS

### Vineyard Site, Experimental Design, and Berry Temperature Measurements

Experiments were conducted over 2013-2014 in a commercial vineyard (Herdade do Esporão), located at Reguengos de Monsaraz, Alentejo winegrowing region, Southern Portugal (lat. 38◦ 23′ 55.00′′ N; long. 7◦ 32′ 46.00′′ W). The climate is of Mediterranean type, with hot and dry summers and mild rainy winters. Soil texture is a sandy-loam to silty-clay-loam, with a pH of 7.0–7.6, a low content in organic matter (10.5 g kg−1 ) and high P2O5 and K2O values (110 and 173 mg kg−1 , respectively). The 11-year-old grapevines of the red variety Aragonez (syn. Tempranillo) were grafted on 1103 Paulsen rootstock.  All vines were uniformly pruned with 15–16 nodes per vine. The experimental layout was a randomized complete block design with two treatments and four replications per treatment. The elemental plot comprised three adjacent rows (two buffer rows and a central one for data collection) of 10 vines each. Climate data (air temperature and precipitation) were obtained from an automatic meteorological station located in the experimental orchard, near the vineyard (at ∼900 m).

Two irrigation treatments were applied: Sustained Deficit Irrigation (SDI), usually applied by winegrower, and Regulated Deficit Irrigation (RDI). The drip line was positioned along the row close to the vine trunks and consisted of pressure compensating 2.2 L/h drip emitters with 1.0 m spacing. Irrigation started on June, 14th and was ended at September, 6th in 2013; in 2014 it started on June, 12th and stopped on August, 23th. Watering was applied according to the crop evapotranspiration (ETc) and soil water content. ETc was estimated from the reference evapotranspiration (ET0) using the crop coefficients proposed by Allen et al. (1998). During irrigation, the average fraction of ETc applied was ca 0.3 in SDI and 0.15 in RDI. Water was applied 1–2 times a week. The total amount of water supplied until commercial harvest to SDI plants was 111 and 57 mm in 2013 and 2014 respectively (∼30% ETc), while the supply on RDI was 53 mm in 2013 and 38 mm in 2014 (∼15% ETc) (Supplementary Table 1). Standard cultural practices in the region were applied to all treatments. To characterize the vine water status, pre-dawn leaf water potential (9pd) was measured before each sampling date. Measurements were carried out on an adult leaf from eight replicate plants from each treatment, using a Scholander pressure chamber (Model 1000; PMS instrument Co., Corvallis, OR, USA). In order to estimate accumulated water stress, pre-dawn water stress integral (S9pd) was determined for each phenological stage accordingly to Myers (1988), using a −0.2 MPa maximum threshold. Berry temperature was monitored continuously (at 30-minintervals) using a dual channel temperature data logger to which a two-junction, fine wires copper-constantan thermocouples were attached. These probes were positioned on berry surface (avoiding direct sun exposure) of a sample of clusters located in different canopy positions (exposed and internal; facing east and west) of 2 vines per treatment.

In order to quantify the incidence of berry temperature on anthocyanin accumulation at each side of the canopy (east and west), the Rustioni et al. (2011) approach was used. Berry temperature was averaged each hour and then converted into normal heat hours (NHH) and cumulated per phenological period. NHH computing procedure was done as described by Rustioni et al. (2011), based on a function that varies from 0 to 1 and gives 0 for temperatures outside minimum and maximum cardinals (Tmin = 10◦C and Tmax = 35◦C) and 1 for temperatures at optimum (Topt = 25◦C).

### Grape Berry Analysis

Berries were collected at different developmental stages during summer (from June to August). Four stages were considered: end of pea size (PS, 5–6 weeks after anthesis), véraison (V, 9–10 weeks after anthesis), mid-ripening (MR, 12 weeks after anthesis) and full maturation (FM, 14 weeks after anthesis). During 2013, only three stages were sampled (pea size, véraison and full maturation) as a consequence of unusual early berry maturation and an acceleration of sugar accumulation and acid breakdown. At each sampling date a representative sample of 50 bunches per treatment from 10 vines per replicate (30-40 plants per treatment) was randomly collected from the experimental vineyard. Bunches from each east side and west side of the vine (East side and West side) were collected separately. Four sample groups were generated: SDI east (SDIE), SDI west (SDIW), RDI east (RDIE), and RDI west (RDIW). A sub-sample of 20 bunches was collected and stored at 4◦C. Three independent replicates of 50 berries each were weighed to determine berry weight and diameter, and the juice was extracted to determine total soluble solids (TSS, ◦Brix) and titratable acidity (TA, g tartaric acid L −1 ). The concentration of TSS was measured using a manual refractometer (ITREF 32, Instrutemp). The TA was assessed according to Office International de la Vigne et du Vin (OIV, 1990) procedure. The second sub-sample of 30 bunches was immediately frozen in liquid nitrogen from which three to four independent pools of 30-40 frozen berries were carefully selected, peeled and the seeds removed. Skins were removed, weighted and ground in liquid nitrogen to a fine powder and stored at −80◦C until successive analysis.

### ABA and Related Metabolites Analysis

ABA, ABA-GE, PA, and DPA concentrations in berry skin were simultaneously analyzed by HPLC MS/MS. Before starting the extraction procedure, 40 ng of each deuterium-labeled internal standards were added (ABA-d6, ABA-GE-d5, PA-d3, DPA-d3, all from National Research Council of Canada, Saskatoon, SK, Canada) per 300 mg of freeze dried skin powder. The tissue was extracted with 3 mL of CH3OH:H2O (50:50 adjusted to pH 2.5 with HCOOH) for 30 min at 4◦C. The supernatant was partitioned three times with 3 mL of n-exane. The methanolic fraction was purified using Sep-Pak C18 cartridges (Waters, Massachusetts, USA), and the eluate was dried under nitrogen and rinsed with 250µL of CH3OH:H2O acidified at pH 2.5. Identification and quantification of free-ABA, ABA-GE, PA and DPA was performed through the injection of 3µL of sample solution in a LC-ESI-MS/MS equipment, consisting of a LC-MS-8030 triple quadrupole mass spectrometer operating in negative ion mode equipped with electrospray ionization source (ESI) and coupled with a Nexera HPLC system (all from Shimadzu, Kyoto, Japan). Compounds were separated in an Agilent Poroshell C18 column (3.0 × 100 mm, 2.7µm) eluted with a linear gradient solvent, at a flow rate of 0.3 mL min-1, from 95% H2O (with the addition of 0.1% of HCOOH, solvent A) to 100% CH3CN/MeOH (50/50, with the addition of 0.1% of HCOOH, solvent B) over a 30-min run. Quantification of free-ABA, ABA-GE, PA, and DPA was conducted in multiple reaction monitoring (MRM) with the corresponding transitions for each analyte (ABA: 263/153; d6-ABA: 269/159; ABA-GE: 425/263; d5-ABA-GE: 430/268; PA: 279/139; d3-PA: 282/142; DPA: 281/171; d3-DPA: 284/174).

### Phenylpropanoids Analysis

Freeze dried skins (300–350 mg) were ground in a mortar under liquid nitrogen and the obtained powder was extracted with 70% of aqueous ethanol acidified to pH 2 by HCOOH (3 × 5 mL) and sonicated for 30 min. The supernatant was partitioned with 3 × 5 mL of n-Hexane, reduced to dryness under vacuum and rinsed with CH3OH/H2O (50/50, pH 2). Aliquots of 5µL were injected into Perkin Elmer Flexar HPLC equipped with a quaternary 200Q/410 pump and a LC 200 photodiode array detector (Perkin Elmer, Bradford, CT, USA). Metabolites were separated in a 4.6 × 250 mm Hypersil SB-C18 column (5µm) (Agilent Technologies, Milan, Italy), operating at 30◦C and eluted at a flow rate of 1 mL min−1 . Anthocyanins were separated using a gradient solvent system consisting of H2O (plus 5% HCOOH) (A), CH3OH (plus 5% HCOOH) (B), CH3CN (plus 5% HCOOH (C), during a 47 min run: 0–2 min 80% A, 15% B, 5% C; 2–17 min to 70% A, 20% B, 10% C; 17–32 min to 55% A, 30% B, 15% C; 32–37 min 55% A, 30% B, 15% C; 37–42 min to 20% A, 40% B, 40% C; 42–47 min 20% A, 40% B, 40% C. Flavonoids and hydroxycinnamic acids were separated using a linear gradient solvent system consisting of solvent A (90% H2O with the addition of 0.1% formic acid, 10% CH3CN) and solvent B (90% CH3CN and 10% of H2O with the addition of 0.1% formic acid). The chromatographic run lasted 45 min starting from 100% solvent A and arriving to 100% solvent B. Individual metabolites were identified on the basis of their retention times, UV-spectral characteristics and mass-spectrometric data. HPLC-MS-MS analysis was performed with a LC-MS-8030 triple quadrupole mass spectrometer operating in the electrospray ionization (ESI) mode and a Nexera HPLC system (all from Shimadzu, Kyoto, Japan). The mass spectrometer operated in negative ion scan mode for hydroxycinnamic derivatives and flavonoids detection, and in positive ion scan mode for anthocyanin detection. Product ion spectra were obtained using Argon as collision gas at a pressure of 230 kPa. Quantification of anthocyanins was performed at 530 nm using calibration curves of cyanidin 3-O-glucoside chloride, delphinidin 3-O-glucoside chloride, petunidin 3-O-glucoside chloride, malvidin 3-Oglucoside chloride (Extrasynthese). Quantification of flavonoids and hydroxycinnamic acid derivatives was performed at 350 and 330 nm respectively using the calibration curve of quercetin 3-Oglucoside, rutin, myricetin 3-O-glucoside, trans-caftaric acid and trans-coutaric acid; gallic acid, protocatechuic acid, vanillic acid and syringic acidwere quantified at 280 nm.

# Analysis of Degradation Products of Anthocyanins

Degradation products of anthocyanins were quantified on the samples extracted for phenylpropanoids analysis following the protocol reported in Seeram et al. (2001) and Sadilova et al. (2007) with some modifications. Aliquots of 20µL were injected into Perkin Elmer Flexar HPLC reported above and analyzed on a 4.6 × 250 mm Hypersil SB-C18 column (5µm) (Agilent Technologies, Milan, Italy), operating at 30◦C and eluted at a flow rate of 1 mL min−1 . Degradation products of anthocyanins were detected at 235 nm and quantified using authentic standards of protocatechuic acid and phloroglucinaldehyde (Sigma Aldrich, Milan, Italy).

## RNA Extraction and cDNA Synthesis

Total RNA extractions were performed in 1.5 mL tube, using the method of Reid et al. (2006). Briefly, skin tissue of 20 berries was ground to a fine powder in liquid nitrogen using a mortar and pestle. The extraction buffer, pre-warmed (65◦C) (300 mM Tris HCl pH 8.0, 25 mM EDTA, 2 M NaCl, 2% (w/v) CTAB, 2% (w/v) PVPP, 0.05% (w/v) spermidine trihydrochloride and 2% (v/v) β-mercaptoethanol just prior use) was added to powder and shaken vigorously. Tubes were subsequently incubated at 65◦C with shaking for 10 min. Mixtures were extracted twice with equal volumes of chloroform:isoamyl alcohol (24:1) and centrifuged at 16,100 g for 10 min at 4◦C. To the supernatant add 100µl 3 M NaOAc (pH 5.2) and 600µl isopropanol were added, mixed, and stored at −80 ◦C for 25 min. Nucleic acid pellets were collected by centrifugation at 16,100 g for 30 min at 4◦C. The pellet was dissolved in 250µL TE (pH 7.5) and adds 94µL of 8 M LiCl and stored at 4◦C overnight. RNA was pelleted by centrifugation at 16,100 g for 30 min at 4◦C, then washed with 1µl of ice cold 70% ethanol, air dried, and dissolved in RNase-free water. Total RNA was purified using an RNeasy R Mini kit (Qiagen) with the addition of an on-column DNAse I digestion (RNase-Free DNase Set; Qiagen). RNA concentration was determined before and after DNase I digestion using a Nanodrop ND-1000 spectrophotometer (Nanodrop Technologies) in 260/280 nm ratio. RNA integrity was evaluated by 1% (w/v) agarose gel electrophoresis. First-strand cDNA was synthesized using the Omniscript R Reverse Transcription kit (Qiagen) according to the manufacture's instructions. The cDNA was prepared from 1000 ng of total RNA and synthesized at 37◦C for 60 min and the cDNA stored at −80◦C.

### Quantitative Real-Time PCR Analysis

Quantitative real-time PCR was performed in the iQ5 2.0 Standard Edition (Bio-Rad), sequence detection system in a 96 well reaction plate. Each reaction (20µl) contained 250 nM of each primer, 5µL of 1/50 diluted cDNA, and 10µl of Power SYBR Green Master Mix (Bio-Rad). Thermal cycling conditions were 95◦C for 10 min followed by 95◦C for 10 s, 60◦C for 10 s, and 72◦C for 10 s for 40 cycles. Dissociation curves for each amplicon were then analyzed to verify the specificity of each amplification reaction; the dissociation curve was obtained by heating the amplicon from 55 to 95◦C. Each PCR was run in triplicate within the same plate, and the cycle threshold (Ct) values obtained from the technical replicates were averaged. Gene transcripts were quantified by comparing the Ct of the target gene with that of actin (Reid et al., 2006). Gene expression was expressed as mean and standard error calculated from the three biological replicates. Primer pairs for VviUFGT were retrieved from Jeong et al. (2004), VviNCED1 and VviβG1 from Sun et al. (2010), VviHyd1 and VviHyd2 from Speirs et al. (2013).

# Data Analysis

Measurements were conducted of four biological replicates. Data of each season were subjected to analysis of variance (ANOVA) using SPSS 12.0 (SPSS Inc., Chicago, USA). Means were separated by Duncan's multiple range test (p ≤ 0.05). Principal component analysis (PCA) was also performed on all measured skin parameters, using the R software (version 3.2.5, R Development Core Team 2011) and the ade4 package (Culhane et al., 2002; Chessel et al., 2004; Thioulouse and Dray, 2009).

# RESULTS

## Vine Water Status and Cluster Zone Microclimate

Water applied in RDI treatment from pea-size berry to full maturation was similar in both years, while SDI treated-plants in 2014 received ∼65% of water than in 2013 (Supplementary Table 1). The cumulative pre-dawn water stress (S9pd) was higher in 2014. In RDI and SDI treatments, accumulated stress from peasize berry to véraison was 2–13 times higher in 2014 than in 2013, respectively (**Table 1**). The accumulated stress from véraison to full maturation was similar in both years in RDI treatment, while accumulated stress in SDI treatment in 2014 was 1.5 times higher than in 2013 (**Table 1**). Berry temperature (Tberry) on westexposed clusters was always higher than in east-exposed berries, irrespective of the phenological stage, irrigation treatment and year (**Table 2**; Supplementary Figure 1). Air temperature (Tair) measured from véraison to full maturity was, on average, 2◦C higher in 2013 than in 2014 (Supplementary Table 2). In the same period, maximum Tair was 0.4◦C higher in 2014, while minimum temperature in 2013 was 1.0 ◦C higher than in 2014. In both years, the Tair never went below 10 ◦C. In 2013, an accumulated period of 121 h with Tair above 35◦C was observed, whereas in 2014 only 83 h had Tair above 35◦C. Though accumulated hours with Tair > 35◦C in 2013 was higher, the duration of Tberry > 35◦C observed in 2013 was lower than in 2014, irrespective of irrigation and cluster exposure.

Slight differences were observed between irrigation treatments in Tberry from clusters from the same canopy side in both years (**Table 2**). While the west-exposed clusters displayed maximum

TABLE 1 | Pre-dawn water stress integral (S9pd), according to Myers (1988) in sustained deficit irrigation (SDI) and regulated deficit irrigation (RDI) treatments during the periods pea size -véraison (PS-V), véraison-mid-ripening (V-MR), mid-ripening-full maturation (MR-FM) and véraison-full maturation (V-FM) in 2013 and 2014 growing seasons.

DOY: day of the year.

Tberry higher than the east exposed clusters, the amplitude was larger in the RDI treatment (Tberry 5–8◦C and 2.5–9◦C higher in SDI and RDI, respectively). Regarding for the number of hours with Tberry > 35◦C, the berries of the RDI treatment were shown to accumulate more hours with Tberry > 35◦C than the berries of the SDI treatment. Although in 2014, the accumulated hours of berry temperature above 35◦C was lower than the observed in 2013 (**Table 2**).

### Berry Composition

The trend of the TSS and TA accumulation both in 2013 and 2014 is presented in **Figure 1**. There was a significant season effect (P < 0.01) on both TSS and TA. TSS was higher in 2013 (25◦Brix) than in 2014 (22◦Brix), the reverse being observed for TA (∼3.4 g L −1 in 2013 vs. ∼4.9 g L−1 in 2014). In 2013, no significant TSS differences between irrigation treatments and side of the canopy were observed.

In 2014, differences between treatments and side of the canopy started to be observed at véraison. TSS starts to accumulate at véraison in berries from east-side followed by the west side both in SDI and RDI. This trend was also observed at mid-ripening, and at full maturation in SDI. At full maturation RDI presents higher TSS as compared with SDI, being highest at RDIW. The breakdown of TA was observed since véraison stage, especially in RDI. Differences in TA content were not observed between east and west berries at both pea size and véraison stages. On the contrary, from mid-ripening to full maturation, west side berries had lower TA content east side berries, in both SDI and RDI.

### Grape Skin Anthocyanin Composition and Accumulation

A wide range of cyanidin, delphinidin, malvidin, petunidin, and peonidin derivatives were identified in either years of experimentation (**Table 3**), but their concentration was higher in 2014 than in 2013. Irrespective of the year, the concentration of anthocyanins increased since véraison to reach maximum levels at full maturation in all treatments (**Figure 2**). Anthocyanin levels were lower in RDI than SDI. West-exposed berries displayed lower anthocyanin concentration than east-exposed berries, irrespective of irrigation. In 2013, no differences in the trend of accumulation of anthocyanin were observed at véraison, except for RDIE which was significantly higher as compared with all other treatments. In contrast, at full maturation SDIE showed higher anthocyanin concentration as compared to SDIW and RDIW. Methoxylated anthocyanins (peonidin, petunidin, and malvidin) were highest in east exposed clusters in both irrigation regimes at full maturation (**Figure 2**). The ratio of methoxylated to non-methoxylated anthocyanins was the highest in RDIE, as well as in east sided than in west sided berries (**Table 3**).

In 2014 the level of anthocyanins since véraison stage was higher in east than in west-exposed barriers, irrespective of irrigation regime (**Figure 2**). This trend was even more evident at mid-ripening and at full maturation. Differences in anthocyanin concentration were not recorded between SDI and RDI at mid-ripening stage, whereas at full maturation RDI had lower anthocyanin content than SDI, irrespective of canopy position (**Figure 2**). The ratio of methoxylated

 42.8

 9.8

 23.8

 153

 below 10

◦C (Tberry < 10

◦C) were null. For SDIE regime in 2014 it was 1 at PS-V.

 47.1

 10.7

 23.9

 172

 40.8

 10.9

 23.7

 113

 46.5

 11

 23.7

 169

PS-FM

\*Except for SDIE regime in 2014 the number of hours with temperature

to non-methoxylated anthocyanin ratio in SDI exceeded that in RDI at véraison, the reverse being observed at mid-ripening.

# Grape Skin Phenylpropanoids Composition and Accumulation

Different derivatives of hydroxycinnamic acid, such as caftaric and coutaric acid, and of quercetin and myricetin were identified in berry skin (**Table 4**). Traces of benzoic acids, e.g., gallic acid, protocatechuic acid, vanillic acid and syringic acid were also detected in 2013, but not in 2014. In general, phenolic acids (hydrocinnamic acids and benzoic acids) concentrations decreased along berry development and were higher in SDI as compared with RDI at all studied phenological stages, and in both seasons. In addition, phenolic acids were higher at west side than the east side at pea-size and véraison. The flavonol content was higher at west side than the east side (independent on irrigation treatment) since the pea size stage. The concentration of phenylpropanoids was greater in 2014 than in 2013.

# Grape Skin Anthocyanin Degradation Products

Products of anthocyanin degradation, such as protocatechuic acid and phloroglucinaldehyde were only detected at full maturation (**Figure 3**), the concentration of which in west-exposed berries exceeded that in east-exposed berries. The degradation of anthocyanins was higher in berries under RDI.

# Free ABA and Related Metabolites Accumulation in Grape Skin

Free-ABA concentration sharply increased at véraison in both years (**Figure 4**). There were no significant differences at pea size and véraison in ABA skin concentration in 2014. In 2013, ABA was highest at west side independently from irrigation at pea size stage, and lowest in RDIE at véraison. In 2013, SDI treatment presented highest free ABA at full maturation stage, where east side presents highest values. In 2014, SDI treatment presented higher ABA both at mid-ripening and full maturation stages. In contrast with 2013, in 2014 west side presented the highest free ABA at mid-ripening and full maturation stages. DPA was the pre-dominant ABA catabolite present while PA concentration was significantly lower. PA and DPA concentrations showed the same trend of accumulation and decreased along berry ripening. During 2013, PA and DPA were highest at pea size and decreases thereafter. At this stage, RDI was higher than SDI and west side presented highest content. During 2014, no differences were observed at pea size, and PA and DPA showed a sharp increase at véraison stage in SDIW and RDIW while decreases at east side in both irrigation treatments. This highest content at west side was maintained at mid-ripening being SDIW with higher content than RDIW (**Figure 4**). Contrarily to PA and DPA, the ABA-GE increased along berry development in both

 ≥

years and its concentration was lower in RDI and at the west side.

# Expression of VviUFGT, VviNCED1, VviβG1, VviHyd1, and VviHyd2 Genes in Grape Berry Skin

The expression profile of VviUFGT was transiently up-regulated in all treatments at véraison stage during skin development (**Figure 5**). This increase in VviUFGT expression coincides with the onset of anthocyanin accumulation. Differences among treatments in the expression were observed from véraison until full maturation, where VviUFGT showed the maximum expression under SDI when compared with RDI. VviUFGT expression was also repressed at the west side both in SDI and RDI at véraison. However, at full maturation, VviUFGT was highest at SDIE while no differences due to the side were observed in RDI. VviNCED1, was studied at different phenological stages (**Figure 6**). A peak of expression was detected at véraison in both irrigation treatments. The expression of VviNCED1 decreases from véraison onward, being more expressed at the west side of both irrigation treatments at mid-ripeningand at full maturation stages. In skin, VviβG1 peaked at véraison stage. VviβG1 expression was up-regulated at the west side of the canopy at pea size stage and in RDI at mid-ripening. Although no significant differences were recorded, a tendency in highest expression of VviβG1 in RDI and at the west side of the canopy was recorded at véraison. The trend of expression of two genes encoding ABA 8 ′ -hydroxylases (VviHyd1 and VviHyd2) was studied along berry ripening (**Figure 6**). VviHyd1 expression was higher at pea size stage but no statistical differences were recorded between east and west side of the canopy. Although, VviHyd1 expression decreased thereafter, it maintained a statistical high expression level both in SDIW and RDIW at véraison coincident with high PA and

DPA concentrations at this stage. VviHyd2 presented a similar trend of expression than VviHyd1. However, VviHyd2 was higherexpressed at the west side of the canopy at all phenological stages studied and in RDI treatment since véraison stage.

### Interaction between Deficit Irrigation and Cluster Position with Berry Ripening and Quality Traits

PCA performed on cumulative water stress (S9pd), NHH and AEBT at véraison and full maturation separated the SDI from RDI as well as cluster position in both years (Supplementary Figure 2). In order to decipher the "vintage effect," PCA was performed combining all data from both years (**Figure 7A**). This analysis showed that most traits contribute to the separation along the first axis and explain 67% of the variability (Supplementary Table 3), contributing thereby to a strong "vintage effect." In addition, both deficit irrigation regime and cluster position, were discriminated along the 2nd and 3rd axis (13 and 11% respectively) in the 2 years (**Figure 7A**). Nonetheless, PCA showed difference between both studied years, being the impact of deficit irrigation regime greater in 2013, while in 2014 the cluster position had more influence (**Figure 7A**). ABA-GE parameter contributed for the separation along the 2nd and 3rd axis (Supplementary Table 3). Taking into consideration the data from **Figure 7B** (PCA for 2013) and 7C (PCA for 2014), we could further indicate that ABA-GE discriminated between deficit irrigation systems (**Figure 7B**, along 1st axis; **Figure 7C**, along 2nd axis) (Supplementary Table 3). In both cases, ABA-GE contributed for the separation SDI vs. RDI. However, only in 2014 it discriminates east vs. west cluster position. A distinctive response of ABA and ABA metabolism to both the irrigation treatment and the cluster position is observed in 2014 (**Figure 8**). It is important to note, that the first and the second axis explain 68–69% of observed variability and that the second axis contributes with at least a ½ to 3/4 of the first axis.

Also for 2014, PCA shows (**Figure 7C**), that the parameters associated with cluster position discrimination (east vs. west) were the different chemical forms of malvidin (Malvidin-3-O-glucoside, Malvidin-3-O-acetylglucoside, and Peonidin-3-O-(6′′-O-coumaroyl)glucoside + Malvidin-3-O-(6′′-O-coumaroyl)glucoside), flavonols (rutin and quercetin-3-O-glucoside and myricetin), and degradation products of anthocyanins. These molecules, in a year with low water availability (high S9pd), were able to discriminate east-west position and responded to the berry temperature. In contrast, in 2013, the separation according to cluster position was only achieved along the 4th axis (7%) and none of above mentioned parameters contributed significantly for such separation (Supplementary Table 3). This indicates that in 2013, other factors in addition to water stress and Tberry are impacting on berry skin metabolism. It appears that in wet years, vines could cope with high Tair in a way that made difficult to separate the effects of irrigation from cluster position.

In order to explain the effect of water stress and/or cluster position on berry ripening and composition, we explore for the existence of correlations. To our surprise, neither anthocyanins

nd, non-detected;

 Values presented are mean ± SD (n ≥ 3).

TABLE 4 | Flavonol

concentration

 in berry skins (µmol g

−1 dry weight) of east- and

west-exposed

 clusters under sustained

 deficit irrigation (SDI) and regulated

 deficit irrigation (RDI) along the

nor ABA correlated with S9pd in both years. Nonetheless, a highly significant and negative correlation between free-ABA and total anthocyanins was observed for both irrigation treatments (r = −0.76, p ≤ 0.0001) in the 2 years. Interestingly, a weaker correlation was observed on the west side as compared with the east side (east r = −0.84, p ≤ 0.001 vs. west r = −0.67, p ≤ 0.05) indicating that high temperature affect negatively ripening process, namely anthocyanin accumulation. In addition, a thermal disruption of the anthocyanins/ABA relationship among the different irrigations and cluster positions was observed, being the RDIW showing the larger difference, suggesting the higher susceptibility of RDI to high temperature as compared with SDI.

### DISCUSSION

Ripening is a complex process leading to several physiological and metabolic changes including softening, and sugar and anthocyanin accumulation. In contrast to climacteric fruits in which the control of ripening is well established, in nonclimacteric grape berries, ripening is, still, poorly understood.

Hormones, particularly ABA, are long known to participate in the ripening process of grape berry (Jeong et al., 2004; Symons et al., 2006; Wheeler et al., 2009; Koyama et al., 2010; Sun et al., 2010; Böttcher and Davies, 2012). Deficit irrigation has been proposed as suitable viticultural practice to influence berry ripening, through the stimulation of sugar and anthocyanin biosynthesis under a mild to moderate water deficits (Castellarin et al., 2007a; Gambetta et al., 2010). However, deficit irrigation has been shown to increase (Basile et al., 2011; Santesteban et al., 2011) decrease (Intrigliolo et al., 2012; Zarrouk et al., 2012) or to have negligibly affect (Castellarin et al., 2007a,b; Girona et al., 2009) on anthocyanin biosynthesis. Mechanisms through which water deficit affects berry ripening require further elucidation, mostly because increases in sugars and anthocyanins in berries exposed to pre- or post-véraison deficit irrigation depends greatly on the sensitivity of berry developmental growth and cultivar's sensitivity to ABA signaling (Ferrandino and Lovisolo, 2013).

Air temperature, namely high temperatures, may also have a strong impact on berry quality, leading to a drop in berry acidity and an increase in sugar content (Keller, 2010), while reducing anthocyanin content (Mori et al., 2007; Tarara et al., 2008; Greer and Weedon, 2013) and varietal aroma (Jones and Goodrich, 2008; Bonada et al., 2015). Our study aimed at evaluating the combined effect of changes in water availability and berry temperature (by sampling berries located on different sides in the canopy) on grape berry ripening and composition.

### Interactive Effects of Irrigation Regime and Berry Temperature on the Biosynthesis, Accumulation, and Degradation of Anthocyanins

Water deficit has been considered to impact on the accumulation of anthocyanins through the stimulation of anthocyanin hydroxylation (Castellarin et al., 2007b), which converts hydroxylated anthocyanins (cyanidin and delphinidin) into their methoxylated derivates (peonidin, petunidin, and malvidin) (Kennedy et al., 2002; Castellarin et al., 2007a,b). In contrast, high temperature was shown to reduce anthocyanin hydroxylation in grape berries (Tarara et al., 2008). Our study shows that methoxylated anthocyanins accumulated from mid-ripening to full maturation stages in berries located on the east canopy side, irrespective of year and irrigation regime. The ratio of methoxylated to non-methoxylated anthocyanin was higher in RDI than SDI vines, as reported previously (Castellarin et al., 2007a,b; Deluc et al., 2009). On the other hand, the ratio of methoxylated to non-methoxylated anthocyanins was higher in berries located at the west than at the east side, confirming previous findings of high temperature influence on the anthocyanin forms (Tarara et al., 2008).

Methoxylation of anthocyanins greatly affects berry color and stability (Jackman and Smith, 1996). Our data suggests that anthocyanin methoxylation might represent a strategy adopted by grapes to cope with the combined effects of water shortage and heat stress. Increasing anthocyanin stability

through methoxylation may partly compensate for reduced anthocyanin biosynthesis when carbon assimilation is severely constrained under severe stress (i.e., the combined effect of water deficit and heat stress). The concentration of anthocyanins was significantly repressed in west-exposed berries, both in SDI and RDI during ripening in 2013. In 2014, no differences in anthocyanin concentrations between sides were observed in SDI at full maturation suggesting that more irrigated SDI vines are less sensitive to high temperatures during ripening in coolest years or/and years with less hours of extreme temperature which corroborates recent studies of Romero et al. (2016). In contrast, RDI showed statistically lower concentration at the west side than at the east side and lower than SDI. Our findings suggest that the most severe stress conditions, i.e., RDI treatment, exacerbated the negative impact of high temperature on anthocyanin biosynthesis and/or degradation. Our hypothesis is further corroborated by the observation that the expression of VviUFGT, which is involved in late steps of anthocyanin biosynthesis, was downregulated in RDI as compared to SDI at the onset of ripening. This also supports the negative effect of higher pre-véraison S9pd on anthocyanin biosynthesis. The expression of VviUFGT was also repressed at the west side in both irrigation treatments, possibly due to greater heat stress incidence in this side (**Table 2**). In contrast, VviUFGT expression was higher at west side than in east side in both treatments at full maturation, suggesting the possibility of an enhancement of anthocyanin biosynthesis at this stage. However, this enhancement was not translated into higher anthocyanin concentrations in the berries located at the west side. This may be due to the highest rate of degradation registered on the west side of the canopy in both irrigation treatments (**Figure 4**). Our results suggest that the negative impact of water stress and high temperature on anthocyanin content likely results from the repression of anthocyanin biosynthesis at the onset of ripening. We also provide evidence that accumulation

of anthocyanins at full maturation is negatively affected by water/heat stress possibly because of the higher degradation rate of these compounds at later stages of berry ripening.

Interactive effects of water deficit and side of the canopy on berry quality are clearly exposed in our study. There is compelling evidence that the negative impact of water deficit on berry quality greatly depends on temperature (Tarara et al., 2008; Bonada et al., 2013; Fernandes de Oliveira and Nieddu, 2013). In our experiment, an annual effect on anthocyanin accumulation was observed, 2013 exhibiting lower concentrations than in 2014, in spite of 2013 showing lower accumulated water stress (S9pd). The high temperatures observed in the growing season of 2013 (2◦C higher than 2014) could explain these results. On the other hand, in 2013, berries accumulated more hours with Tair above the threshold of >35◦C during the ripening period, as compared with 2014. This could explain the acceleration of sugar accumulation (TSS) and acid breakdown (TA) observed in 2013 with regards to 2014. While TSS was higher in 2013 than in 2014 at full maturation, anthocyanins were lower in 2013. This result corroborates the fact that high temperature promotes sugar concentration in detriments of other quality attributes of berries, leading to poorly balanced wines with reduced varietal characteristics (Mira de Orduña, 2010). Sugar accumulation was reported to be required for anthocyanin biosynthesis in grape berries (Gollop et al., 2002; Castellarin et al., 2007a). Although no differences were observed in TSS due to irrigation treatments and cluster position in 2013, anthocyanins were repressed at the west side of the canopy. In 2014, TSS was lower at west side at véraison, which corroborates with low anthocyanin concentration results. However, at full maturation, TSS was higher in RDI (both sides of the canopy) as compared with SDI, while anthocyanins were lower in RDI treatments (east and west). Taking into account the more stressful temperature conditions in 2013, and higher cumulative heat stress from pea size to full maturation at west exposure in 2014, these results suggest a decoupling of anthocyanin/sugar as a consequence of high temperature (Sadras and Moran, 2012; Bonada et al., 2013).

### Differential Regulation of Flavonol and Other Phenylpropanoid Accumulation during Berry Development by Irrigation and Cluster Position

The influence of water and heat stress on flavonol profile in grapes is still unclear, in contrast with compelling evidence reported for anthocyanin biosynthesis (Ferrandino and Lovisolo, 2013). Our study offers the first evidence that the combined effect of water and temperatures stress is distinct from those reported for water- or heat stressed grapes alone (Spayd et al., 2002; Castellarin et al., 2007a,b; Azuma et al., 2012; Zarrouk et al., 2012).

Deficit irrigation did not enhance the concentration of flavonol compounds, and no differences were observed between SDI and RDI berries. The data corroborates Deluc et al. (2009), which showed that flavonol content is not affected by water stress in a red grapevine variety but it is in a white one. Nevertheless, flavonols were higher at the west side of both SDI and RDI treatments, suggesting an enhancement of their accumulation/biosynthesis under heat stress. The results suggest that the same climactic conditions that influence anthocyanin biosynthesis/accumulation at west side of the canopy may also affect flavonols since they share the same biosynthetic pathway. In this sense, the present study may suggest that the increase of flavonol concentration is promoted by the decrease in the UDPglucose:flavonoid 3-O-glucosyltransferase activity by heat stress. We found that the transcript of this enzyme (VviUFGT) is downregulated, suggesting that more substrate is available for flavonol biosynthesis via flavonol synthase activity. The competition for substrates (that both enzymes share) supports it. These results show also the differential impact of irrigation is dependent upon the stage of berry growth and the year, and suggest the multiple roles of flavonols during development, as previously reported by Cohen et al. (2008). In addition, the accumulation of phenolic acids at west side, may account for a protective effect against oxidative stress thanks to their chemical structures. Phenolic acids are able to scavenge free radicals (Blokhina et al., 2003), which are expected to be generated by high temperatures.

# Water Deficit and Cluster Position Modulate ABA Metabolism in the Berry

ABA is a key signal in the trigger of berry ripening, as suggested by the increase of berry ABA content around véraison (Wheeler et al., 2009; Giribaldi et al., 2010; Sun et al., 2010; Zifkin et al., 2012; Karppinen et al., 2013; Niculcea et al., 2013). However, the effect of water stress on ABA concentration in grape berries is far from being conclusively addressed (Deluc et al., 2009; Balint and Reynolds, 2013; Niculcea et al., 2013, 2014). In addition, contrasting findings have been reported in studies exploring the effect of heat stress on ABA metabolism (Azuma et al., 2012; Carbonell-Bejerano et al., 2013; Rienth et al., 2014) which appear to be particularly dependent on grape berry phenology.

In this sense, Rienth et al. (2014) showed that ABA synthesis was repressed by heat stress at the beginning of véraison and enhanced at the end of this developmental stage.

In our study, free-ABA concentration increased at véraison in both years, concomitantly with the sharp increase in transcripts of ABA biosynthesis genes, VviNCED1 and VviβG1. This enhancement of ABA-biosynthetic genes coincided with a steep increase in berry sugars and anthocyanins. Irrigation regime and berry position had little effect on free-ABA levels at véraison, in contrast with their effects on sugar and anthocyanin. Additionally, although the strong correlation found between free-ABA and total anthocyanins on both sides of the canopy, the west side showed a weaker correlation as compared with the east side. We hypothesize that high temperature account for the differential modulation of these metabolites, since it was demonstrated to uncouple some ripening-related traits (Sadras and Moran, 2012; Carbonell-Bejerano et al., 2013; Sadras et al., 2013).

The biological function of ABA in grape ripening requires a transient increase at véraison as well as the subsequent decrease, which seems to be under developmental control (Wheeler et al., 2009). This hypothesis is reinforced by our study since ABA concentration in skins was found to not respond to vine water status (S9pd). On the other hand, the ABA increase coincides with the decrease in the PA and DPA, suggesting that this increase is caused by a decreased catabolism rate (Castellarin et al., 2015) and increased biosynthesis. Our results also point out to the effect of environmental conditions on ABA catabolism, since effects of irrigation and cluster position on PA and DPA were recorded. The molecular regulation of PA and DPA shows a complex pattern. The genes encoding ABA 8′ -hydroxylases (VviHyd1 and VviHyd2) were expressed equally in berry skin, but only VviHyd2 was modulated by water stress, being up-regulated under RDI treatment.

The decrease of ABA after véraison may be due to several processes of degradation and oxidation. ABA-GE increased from pea size, reaching maximum content at full maturation, being higher in SDI treatment and repressed in west side of the canopy. This suggests that ABA-GE responds negatively to high temperatures and water stress intensity, contrasting with previous reports analysing ABA-GE under water stress (Deluc et al., 2009; Zarrouk et al., 2012; Balint and Reynolds, 2013). This highlights the need to carefully monitor water stress imposition and progression in order to be able to compare data sets originated from distinct experimental setups.

Grape berry can also modulate it ABA concentration via the release of ABA-GE by β-glucosidase (Lee et al., 2006; Sun et al., 2010; Zhang et al., 2013). VvβG1 transcript increased around véraison, coincident with ABA accumulation, which indicates that β-glucosidase might play a role in regulating the level of ABA during the ripening at this stage. At mid-ripening, VvβG1 transcript was up-regulated in RDI skins, suggesting a high

release of free ABA from ABA-GE in this treatment. This latter result may also explain in part the lower ABA-GE concentrations at full maturation in RDI. Altogether, these results indicate that ABA found in skin along berry development may be also derived from the de-conjugation process of ABA-GE at later stages of berry development. These findings support a role for β-glucosidase in the modulation of ABA content during grape berries development and in response to dehydration.

The accumulation pattern of the different ABA related products provided evidence that endogenous ABA content is modulated by a dynamic balance between biosynthesis and catabolism. It appears that in grape berry, the ABA homeostasis is achieved by degradation before véraison, while after véraison ABA homeostasis is realized by conjugation. In addition, changes in ABA catabolism/conjugation along berry development were affected by water stress particularly when also submitted to heat stress, indicating that ABA-GE and ABA catabolites play an essential role in ABA homeostasis under environmental constraints.

### CONCLUSION

Our work shows that the impact of irrigation regime and high temperature interaction in the control of berry ripening is quite complex and dynamic. Multivariate analysis showed that the strongest parameter influencing the berry ripening is the deficit irrigation system, in spite of some differences observed between the 2 years. Nonetheless, berry temperature is an important variable conditioning the deficit irrigation effect

on berry quality. Deficit irrigation has a positive effect on berry composition only when the high temperature is not a limiting factor. Seasons with increased water stress, lead to a larger impact of high temperatures on the berry ripening and composition. Our results also show that the negative impact of water stress and high temperature on anthocyanins results from the repression of biosynthesis at the onset of ripening and from degradation at later stages Independently from the effect of water stress and cluster position, the increase in free ABA took place at the same stage as anthocyanin and sugar accumulation in the skin. Water and heat stresses do not affect free ABA, but do alter ABA catabolism/conjugation. This suggests that the homeostasis of berry ABA under abiotic stresses is mostly controlled by of catabolism/oxidation processes. Besides the observed season-specific effect on the accumulation and biosynthesis of different metabolites in the grape berry, and in general, SDI gives rise to berries with greater concentrations of phenolics than RDI, with the additional advantage of attenuating heat incidence at the west side of the canopy.

# AUTHOR CONTRIBUTIONS

OZ and MC conceived and planned the study. CB, AG, and MT performed the HPLC analysis of flavonoids and ABA. CB and MT performed the data integration and processing for the above compounds. RE and CL implemented and maintained the viticultural treatments and monitored the vineyard. RE did the climatic and irrigation data processing and analysis. CP performed PCAs data analysis. OZ and TG did the sampling and the processing and analysis of the berry samples. OZ and CP performed data analysis. OZ, CP, and MC drafted the initial manuscript, all authors contributed to the final manuscript.

## ACKNOWLEDGMENTS

This work was supported by the European Community's Seventh Framework Programme (FP7/2007-2013) under the grant agreement n◦ FP7-311775, Project INNOVINE and was

### REFERENCES

integrated into the COST (European Cooperation in Science and Technology) Action FA1106 "Quality fruit." This work was also supported by the Ministero dell'Istruzione, dell'Università e della Ricerca of Italy: PRIN 2010–2011 "PRO-ROOT" and Progetto Premiale 2012 "Aqua." RE had a scholarship from INNOVINE. OZ was supported by postdoctoral fellowships from INNOVINE and FCT (SFRH/BPD/111693/2015). This work was supported by FCT, through R&D Unit, UID/Multi/04551/2013 (GreenIT). Authors acknowledge Herdade do Esporão (Reguengos de Monsaraz, Alentejo, Portugal) for the experimental vineyard facilities and Agri-Ciência-Consultores de Engenharia, Lda for providing berry temperature data.

### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fpls.2016. 01640/full#supplementary-material

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Zarrouk, Brunetti, Egipto, Pinheiro, Genebra, Gori, Lopes, Tattini and Chaves. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Identification of Rapeseed MicroRNAs Involved in Early Stage Seed Germination under Salt and Drought Stresses

### Hongju Jian † , Jia Wang † , Tengyue Wang, Lijuan Wei, Jiana Li and Liezhao Liu\*

*Chongqing Engineering Research Center for Rapeseed, College of Agronomy and Biotechnology, Southwest University, Chongqing, China*

### *Edited by:*

*Alison Kingston-Smith, Aberystwyth University, UK*

### *Reviewed by:*

*Shirish Anand Ranade, CSIR-National Botanical Research Institute, India Anyela Valentina Camargo Rodriguez, Aberystwyth University, UK*

### *\*Correspondence:*

*Liezhao Liu<EMAIL_ADDRESS>
*† These authors have contributed equally to this work.*

### *Specialty section:*

*This article was submitted to Agroecology and Land Use Systems, a section of the journal Frontiers in Plant Science*

> *Received: 14 October 2015 Accepted: 29 April 2016 Published: 13 May 2016*

### *Citation:*

*Jian H, Wang J, Wang T, Wei L, Li J and Liu L (2016) Identification of Rapeseed MicroRNAs Involved in Early Stage Seed Germination under Salt and Drought Stresses. Front. Plant Sci. 7:658. doi: 10.3389/fpls.2016.00658* Drought and salinity are severe and wide-ranging abiotic stresses that substantially affect crop germination, development and productivity, and seed germination is the first critical step in plant growth and development. To comprehensively investigate small-RNA targets and improve our understanding of miRNA-mediated post-transcriptional regulation networks during *Brassica napus* seed imbibition under drought and salt stresses, we constructed three small-RNA libraries from *B. napus* variety ZS11 embryos exposed to salt (200 mM NaCl, denoted "S"), drought (200 g L−1 PEG-6000, denoted "D"), and distilled water (denoted "CK") during imbibition and sequenced them using an Illumina Genome Analyzer. A total of 11,528,557, 12,080,081, and 12,315,608 raw reads were obtained from the CK, D, and S libraries, respectively. Further analysis identified 85 known miRNAs belonging to 31 miRNA families and 882 novel miRNAs among the three libraries. Comparison of the D and CK libraries revealed significant down-regulation of six miRNA families, miR156, miR169, miR860, miR399, miR171, and miR395, whereas only miR172 was significantly up-regulated. In contrast, comparison of the S library with the CK library showed significant down-regulation of only two miRNA families: miRNA393 and miRNA399. Putative targets for 336, 376, and 340 novel miRNAs were successfully predicted in the CK, D, and S libraries, respectively, and 271 miRNA families and 20 target gene families [including disease resistance protein (DIRP), drought-responsive family protein (DRRP), early responsive to dehydration stress protein (ERD), stress-responsive alpha-beta barrel domain protein (SRAP), and salt tolerance homolog2 (STH2)] were confirmed as being core miRNAs and genes involved in the seed imbibition response to salt and drought stresses. The sequencing results were partially validated by quantitative RT-PCR for both conserved and novel miRNAs as well as the predicted target genes. Our data suggest that diverse and complex miRNAs are involved in seed imbibition, indicating that miRNAs are involved in plant hormone regulation, and may play important roles during seed germination under salt- or drought-stress conditions.

Keywords: drought stress, salt stress, microRNA, *Brassica napus*, seed germination

## INTRODUCTION

Drought and salinity are severe and wide-ranging abiotic stresses that substantially affect the germination, development, and productivity of crops. Unlike most animals, plants are sessile organisms that have evolved mechanisms to cope with a wide range of changes in the environment and climate through the regulation of gene expression (Sunkar, 2010). These mechanisms involve complicated biological processes that finely coordinate molecular signaling pathways. To prevent cellular damage and to aid in recovery, specific genes, or proteins are activated at the molecular level by various stresses (Chinnusamy et al., 2007; Shinozaki and Yamaguchi-Shinozaki, 2007). Although there are specific pathways for each stress, certain key genes, or proteins act as nodal components that are integral in stress responsive signal transduction pathways (Knight and Knight, 2001; Fujita et al., 2006). Much effort has been devoted to elucidating gene expression in plants exposed to dry and brackish conditions; however, the mechanisms underlying the regulation of gene expression under these conditions remain largely unknown.