*2.7. Cytotoxicity Test*

The cytotoxicity test of hydrogels was performed as previous method using U87-MG glioblastoma cells (ATCC HTB-14) cultured by Eagle's Minimum Essential Medium (EMEM) with 10% fetal bovine serum (FBS) and 100 IU ml−1 penicillin and streptomycin [13,36]. The hydrogels were soaked in DI water for 8 days, followed by being immersed in the cell cultural medium for 3 days to remove residual monomer and chemicals. After that, the washed hydrogels were put into another cell cultural medium again for 3 days to achieve conditioned cell cultural medium. Following this, 2 × 104 U87-MG cells were seeded onto a 24-well plate and cultured in fresh cell cultural for 3 days. Then the conditioned cell cultural medium was used to culture the cells for another 24 h or 48 h. To evaluate the cytotoxicity of hydrogels, a crystal violet staining method was used. First, cells were fixed by 1 mL of 2% glutaraldehyde in triplicate for 10 min. Then the medium was aspirated and the cells were washed with phosphate-bu ffered saline (PBS) twice. Then, 1 mL of 0.1% crystal violet was added into the plate and the cells were stained for 40 min. Crystal violet was then washed away by water. Crystal violet was present only in the stained cells. The plate was further drained inversely overnight. The cytotoxicity was evaluated by reading the absorbance at 590 nm of the crystal violet.

In addition, Trypan blue was used to show the cell viability by the previous method [13,36]. Specifically, old media in the 24 well plate were aspirated and 1 mL of Dulbecco's phosphate-bu ffered saline (DPBS) was added to wash the adherent cells. Then, DPBS was added into the counting chamber, and the chamber was inserted into a Cellometer Vision Image Cytometry for counting and imaging.


**3. Evidence of the need for investment in the cultivation of medicinal plants from the African perspective**

The COVID-19 pandemic commenced and most nations of the world swung into action for the search for the cure of the viral infection through several means which include: synthesizing of new drugs, testing already existing drugs and search of new drugs from natural sources. Although, the African countries could not go on to search for cures from other sources; it looked at what is readily available on her continent and made a giant stride towards the utilization of medicinal plants to combat the ravaging COVID-19 pandemic. This effort is evidenced by Madagascar's research institute who developed the Covid-Organics (medicinal plant preparation) derived mainly from *Artemisia annua* and other plants indigenous to Madagascar. Many other African countries including Nigeria have made effort in that regard. As demonstrated from the above, this calls for aggressive pharmaceutical research as it has demonstrated the therapeutic potentials of the medicinal plants of African origin towards the fight against the deadly viral disease (COVID-19). Africa needs to invest in the cultivation of medicinal plants for pharmaceutical research towards the development of drugs. Medicinal plants may be the latent savior for the Africans against present and future pandemics. Africa needs to prepare a head and not wait for other pandemics before it starts searching for a cure. This shows Africa's late response to COVID-19 because it was not prepared. Africa has a great advantage as it houses huge varieties of medicinal plants resources and it is in best position to search for the cure of the future diseases from medicinal plants. Professor Albert Rakoto Ratsimamanga the pioneer of Science in Madagascar stated and declared that "*we (Africa) must move forward at our own pace, we must above all have confidence in ourselves and in the therapeutic virtues of nature. For nature and man are one*" [17].


**Author details**

244 The Complex World of Polysaccharides

electrostatic potential at their molecular surfaces.

These contributions should be examined only as relative values as there are no experimental data for calibration or comparison of the calculated values. The apolar contribution remained nearly unaffected by the presence of water, while the electrostatic contribution is dominant even for insoluble chitin (100% acetylation). This finding suggests that hydrogen bond interactions, either intra-chains or between polymer chains and water molecules, play far a more important role in the solubility of chitin and chitosan than hydrophobic interactions. These results have further shown that fine tuning the electrostatic contributions in chitosan can be used to promote remodeling of its the physical state. Additional simulations have shown that the overall net charge and solubility of chitosan can be altered by changes in the pH. Comparison of the electrostatic response of a chitosan and chitin chains to pH changes shows a rather distinct surface charge profile for the two polymers. The electrostatic similarity between chitin and chitosan in basic pH aids to explain the loss of solubility of chitosan at high pH values (Figure 7). The positively charged character of chitosan chains in acid pH is shown by patches in blue (Figure 7D). On the other hand, chitin (Figure 7A) and chitosan chains in basic medium (Figure 7B) show a similar

**Figure 7.** Electrostatic potential represented at the molecular surface of chitin (A) and chitosan (B-D) chains. Molecular structures were obtained from 20-ns molecular dynamics simulations. The different Richard A. Cunha and Eduardo F. Franca\* *Institute of Chemistry, Federal University of Uberlândia, Uberlândia, MG, Brazil*

Thereza A. Soares, Victor H. Rusu, Frederico J.S. Pontes and Roberto D. Lins\* *Department of Fundamental Chemistry, Federal University of Pernambuco, Recife, PE, Brazil*


**Xue Xia, Claudio Persello \* and Mila Koeva**

Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7522 NB Enschede, The Netherlands

**\*** Correspondence<EMAIL_ADDRESS>
Received: 12 June 2019; Accepted: 18 July 2019; Published: 20 July 2019

**Abstract:** There is a growing demand for cheap and fast cadastral mapping methods to face the challenge of 70% global unregistered land rights. As traditional on-site field surveying is time-consuming and labor intensive, imagery-based cadastral mapping has in recent years been advocated by fit-for-purpose (FFP) land administration. However, owing to the semantic gap between the high-level cadastral boundary concept and low-level visual cues in the imagery, improving the accuracy of automatic boundary delineation remains a major challenge. In this research, we use imageries acquired by Unmanned Aerial Vehicles (UAV) to explore the potential of deep Fully Convolutional Networks (FCNs) for cadastral boundary detection in urban and semi-urban areas. We test the performance of FCNs against other state-of-the-art techniques, including Multi-Resolution Segmentation (MRS) and Globalized Probability of Boundary (gPb) in two case study sites in Rwanda. Experimental results show that FCNs outperformed MRS and gPb in both study areas and achieved an average accuracy of 0.79 in precision, 0.37 in recall and 0.50 in F-score. In conclusion, FCNs are able to effectively extract cadastral boundaries, especially when a large proportion of cadastral boundaries are visible. This automated method could minimize manual digitization and reduce field work, thus facilitating the current cadastral mapping and updating practices.

**Keywords:** deep learning; fully convolutional networks; cadaster boundaries; contour detection; unmanned aerial vehicles


**1. Introduction**

*Helicobacter pylori* is one of the most common human infections [1–3]. Infected patients develop chronic active gastritis in all cases, which can lead to peptic ulcer, atrophic gastritis, gastric cancer and gastric MALT-lymphoma [4–7]. Eradication of *H. pylori* can prevent longterm complications, or relapses of the disease. The treatment the infection is recognized as the primary prevention of gastric cancer.

The prevalence of *H. pylori* infection in the population has geographical distribution characteristics, determined by the level of hygiene, and can reach 80% [8]. According to a meta-analysis published in 2017, the number of people infected with *H. pylori* in the Russian Federation was estimated at 78.5% [9]. At the same time, the prevalence of infection in developed countries is decreasing. Thus, a recently published study showed, that about 40% of the population in Russia is infected, while the prevalence of *H. pylori* increases with age [10].

The recently published Maastricht VI Consensus proposed two strategies for selecting eradication therapy: individualized, based on antibacterial susceptibility, and empirical, in which data regarding local resistance of *H. pylori* to clarithromycin (<15% or >15%) are taken into account when choosing a treatment regimen and monitoring the effectiveness of schemes used in the particular region [4]. Therefore, the determination of *H. pylori* resistance

**Citation:** Medakina, I.; Tsapkova, L.; Polyakova, V.; Nikolaev, S.; Yanova, T.; Dekhnich, N.; Khatkov, I.; Bordin, D.; Bodunova, N. *Helicobacter pylori* Antibiotic Resistance: Molecular Basis and Diagnostic Methods. *Int. J. Mol. Sci.* **2023**, *24*, 9433. https:// doi.org/10.3390/ijms24119433

Academic Editors: Jean-Christophe Marvaud and Maria Teresa Mascellino

Received: 30 March 2023 Revised: 10 May 2023 Accepted: 19 May 2023 Published: 29 May 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

to antibiotics, primarily to clarithromycin, is extremely important for the implementation of these treatment strategies.

The efficacy of antibacterial drugs depends on the sensitivity of the bacteria to them. Currently, a major problem is the decreasing efficacy of therapy regimens, which is associated with the rise of antibiotic resistance in *H. pylori* strains. The prevalence of *H. pylori* resistance varies in different countries and depends on the overall frequency of antibiotic use.

The main objective of this study was to provide a comprehensive analysis of current state of research on the study of antibiotic resistance in *H. pylori*, the molecular mechanisms underlying its emergence, as well as an overview and comparison of methods used for resistance evaluation.

The structure of this article is presented in a diagram (Figure 1).

**Figure 1.** The structure of this article.


**2.2 PTTH regulates of ecdysone levels**

146 Steroids – Basic Science

Thummel 1997; Yin and Thummel 2005), the relationship between ecdysone and cell cycle is a relatively unexplored field. Here we review the evidence that the ecdysone pulse is critical

In *Drosophila*, cell growth and cell cycle progression are regulated by a number of key genes, which have been shown to control the cell cycle in an analogous manner in all multicellular organisms. These include the *Drosophila* orthologue of the mammalian *c-myc* transcription factor and oncogene, dMyc, which drives growth and progression through G1 to S-phase (Johnston et al. 1999), the essential G1 to S-phase Cyclin complex, Cyclin E (CycE) and its Cyclin-dependent-kinase (Cdk) partner Cdk2, which triggers S-phase by promoting DNA replication (Knoblich et al. 1994; Neufeld et al. 1998; Richardson et al. 1995), and the *Drosophila* orthologue of the Cdc25 phosphatase, String (Stg), which is required for G2/M progression and promotes mitotic entry by activating the Cdk1/Cyclin B complex (Edgar and Datar 1996). CycE and Stg are the rate limiting factors for S-phase and mitosis, respectively, and both are activated by the *Drosophila* orthologue of human E2F1 protein, dE2F1 (Neufeld et al. 1998). dE2F1 responds to the relevant Cdk-Cyclin complex (CycE/Cdk2 for S-phase and CycB/Cdk1 for mitosis) to coordinate cell cycle progression

During metamorphosis, following removal of the obsolete larval structures, proliferation of the remaining tissue occurs in an ecdysone-dependent manner to produce adult structures. For example, during pupal development the larval midgut is removed by apoptosis and is replaced through proliferation of the remaining tissue to form the adult midgut (Jiang, Baehrecke, and Thummel 1997). Microarray analysis has revealed that the ecdysone signal is associated with the activation of key cell cycle genes, including *Cyclin B, Cdc2* and *Cyclin D*, during the initiation of midgut metamorphosis (Li and White 2003). Analysis of *EcR* null mutants also revealed that EcR function was necessary for the cell cycle and growth genes to be activated in the larval midgut, suggesting that the ecdysone pathway is required for cell division control. The body of this chapter will discuss how the ecdysone pulse achieves changes to cell growth and cell cycle progression. First we will describe how ecdysone levels dictate body size cell extrinsically by controlling developmental timing. Then we will discuss how ecdysone works with its receptors, in a tissue autonomous manner to control transcription of cell cycle genes, which most likely occurs indirectly by modifying the

**2. Cell extrinsic effects of ecdysone on larval growth and body size**

The ecdysone pulse can act indirectly to affect larval growth as a consequence of the link between the ecdysone titre and developmental timing. Here we will discuss how cell extrinsic effects of the ecdysone pathway control *Drosophila* larval growth and final body size non-autonomously, at least in part, through interactions between the ecdysone and insulin pathways (King-Jones and Thummel 2005; Shingleton 2005; Mirth and Riddiford

The prothoracic gland (PG) is tightly associated with the developmental timing of all holometabolous insects, including *Drosophila*, as it produces the ecdysone pulse that dictates

for controlling cell growth and division in *Drosophila*.

from G1 to S-phase and G2 into mitosis (Reis and Edgar 2004).

activity of developmental signalling pathways.

**2.1 The prothoracic gland directs body size**

2007; Nijhout 2008).

**1.4 Linking the Ecdysone pulse to cell cycle**

In insects, the production and release of ecdysone is responsive to the prothoracicotropic hormone (PTTH), a small, secreted peptide. PTTH is thought to induce the transcription of ecdysone biosynthetic genes that encode enzymes driving the series of dehydrogenation and hydroxylation reactions required to synthesise the active metabolite 20E from the cholesterol precursor (Marchal et al. 2010). In *Drosophila* PTTH is produced by a pair of bilateral neurosecretory cells in the brain, which innervate the prothoracic gland (PG) ((Figure 2; (McBrayer et al. 2007)). PTTH is expressed throughout 3rd instar in an 8 hour cyclic pattern, with upregulation noticed around 12 hours before pupariation (McBrayer et al. 2007). Ablation of the neurons that produce PTTH results in a 5-day developmental delay in the onset of pupariation, larger 3rd instar larvae and pupae, and adults with larger wings due to increased cell number. In line with the predicted role for PTTH in modulating ecdysone synthesis and release, larvae lacking PTTH producing neurons have reduced ecdysone titres. This suggests PTTH normally modulates ecdysone levels to coordinate larval growth with the onset of metamorphosis. However, as the ecdysone levels still eventually peak in larvae with ablated neurons, PTTH may not be the sole factor required for increasing ecdysone titres (McBrayer et al. 2007). Thus PTTH might be required in addition to the insulin-dependent growth pathways discussed above, to coordinate larval growth with ecdysone-induced moulting and metamorphosis (Figure 2-3).


*Article* **Natural Variation of** *OsHd8* **Regulates Heading Date in Rice**

**Huanran Yuan 1,†, Ruihua Wang 1,†, Mingxing Cheng 1,†, Xiao Wei 1 , Wei Wang 1 , Fengfeng Fan 1 , Licheng Zhang 1 , Zhikai Wang 2 , Zhihong Tian 2 and Shaoqing Li 1,\***

**Abstract:** Heading date, as one of the most important agronomic traits, is a fundamental factor determining crop yield. Although diverse genes related to heading date have already been reported in rice, the key gene that regulates heading date is still poorly understood. Here, we identified a heading date regulator, heading date 8 (*OsHd8*), which promoted the heading date under long-day conditions and encoded a putative HAP3 subunit of the CCAAT-box-binding transcription factor. It is localized in the nucleus and expressed in various tissues. Sequence analysis revealed that there were four SNPs and one InDel in the promoter region of *OsHd8*, which was involved in the regulation of some floral regulators including *GHD7.1*, *SDG718*, *OsGI* and *HDT1*. Further evolutionary analysis showed that *OsHd8* presents divergence between *indica* and *japonica*, showing natural selection during the domestication of cultivated rice. These results indicate that *OsHd8* plays an important role in the regulation of heading date, and may be an important target for rice breeding programs.

**Keywords:** heading date; *Heading date 8* (*OsHd8*); promoter; natural variation; rice

**Citation:** Yuan, H.; Wang, R.; Cheng, M.; Wei, X.; Wang, W.; Fan, F.; Zhang, L.; Wang, Z.; Tian, Z.; Li, S. Natural Variation of *OsHd8* Regulates Heading Date in Rice. *Agronomy* **2022**, *12*, 2260. https://doi.org/10.3390/ agronomy12102260

Academic Editor: Argelia Lorence

Received: 22 August 2022 Accepted: 16 September 2022 Published: 21 September 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

**1. Introduction**

Flowering is an important process in plant transition from vegetative to reproductive growth [1,2]. Rice flowering is often affected by the external environment, including light, temperature, and nutritional conditions [3]. Appropriate flowering time is not only beneficial to the reproductive development of rice but also affects the yield of rice [4].

To date, many flowering-related genes have been identified in plants [5–10]. *Ghd7* encodes a protein with a CCT (CO, CO-LIKE and TIMING OF CAB1) domain that delays the heading date, increases the plant height and promotes panicle size development [5]. In *Arabidopsis thaliana*, *CO* (*CONSTANS*), as a key factor in the photoperiod pathway, promotes flowering under long-day (LD) conditions [11]. FT (FLOWERING LOCUS T) is a member of the *PEBP* gene family that shares homology with RAF kinase inhibitor proteins (RKIPs; these are activated by CO to regulate flowering [12–14]. *Hd1* and *Hd3a*, a rice ortholog of the *Arabidopsis CO* and *FT* gene, respectively, have been identified to promote heading under short day (SD) conditions [6,9]. However, the regulation of *Hd1* and *Hd3a* in rice is different from that in *Arabidopsis thaliana*. *PhyB* (*phytochromes B*) is involved in the post-translation regulation of *Hd1* to regulate *Hd3a* expression, while overexpression of *Hd1* inhibits *Hd3a* expression and delays flowering depending on phyB under SD conditions [15]. *RFT1* (*RICE FLOWERING LOCUS T 1*), encoding the mobile flowering signal, is the closest homolog of Hd3a. In *Hd3a*-RNAi transgenic plants, the *RFT1* gene is activated to promote flowering under SD conditions [10,16]. *Ehd1* (*Early heading date 1*) encodes a B-type response regulator, which can promote the flowering of rice under SD conditions by regulating expression of the *FT-like* gene [8]. *Ehd1*, as a unique

floral activation pathway in rice, regulates the heading date by the protein complex of Ghd7-Hd1 and OsRE1-OsRIP1 [17–19]. PPS (Peter Pan syndrome) is a homolog of the photomorphogenic gene *COP1* (*CONSTITUTIVE PHOTOMORPHOGENIC1*) in *Arabidopsis thaliana* and promotes flowering by regulating the GA biosynthesis and suppressing the *miR156/miR172* expression [8]. In addition, MADS-box genes have been shown to play a vital role in the flowering time, of which, *OsMADS50* is an important flowering activator, controlling various downstream floral regulators in rice, including *OsMADS1*, *OsMADS4*, *OsMADS15*, *OsMADS18* and *Hd3a* [20–23].

The HAP (heterotrimeric heme activator protein) family, a class of CCAAT box factor (CBF) or nuclear factor Y (NF-Y), have been identified as important regulators in rice [24]. The HAP complex consists of three subunits, namely HAP2 (NF-YA; CBF-B), HAP3 (NF-YB; CBF-A) and HAP5 (NF-YC; CBF-C) [25,26]. A total of 10 *HAP2* (*OsHAP2A*–*J*) genes, 11 *HAP3* (*OsHAP3A*–*K*) genes and 7 *HAP5* (*OsHAP5A*–*G*) genes have been identified in rice, and recent studies revealed that *HAP* gene members play a vital role in the rice heading date [25]. HAP5B and HAP5D, as flowering inhibitory factors, directly interact with HAP3D, HAP3F and HAP3H protein to regulate the photoperiodic flowering response of rice under LD [27]. *DHD1* (*DELAYED HEADING DATE1*) is involved in the flowering development through binding to their target *HAP5* family genes *HAP5C* and *HAP5D* [28]. *OsHAPL1* (*Heme Activator Protein like 1*), as a flowering repressor, can physically interact with the DTH8/HAP3H and Hd1, and repress the heading date in rice [4].

Transcriptional regulation is largely controlled through gene promoters and their contributing cis-acting elements (CREs) [29]. The diversity of cis-regulatory elements including auxin response elements (AuxREs), the abscisic acid response element (ABRE), A-box (TACGTA), C-box (GACGTC), and G-box (CACGTG) are associated with auxin response in *Arabidopsis thaliana* [30]. Introducing new or disrupting existing upstream CREs, including single-nucleotide polymorphisms (SNPs), segmental deletions, insertion of transposable elements, and copy number variations, often leads to changes in many agronomic characters, resulting in crop improvement [31–34]. 3-bp InDel in the promoter region of *Sl-ALMT9* (*Al-ACTIVATED MALATE TRANSPORTER9*) disrupts a W-box binding site, which prevents binding of the transcription repressor WRKY42, and promotes the accumulation of malic acid in fruits [35]. *OsREM20* (*Oryza sativa REPRODUCTIVE MERISTEM 20*) encodes a B3 domain transcription factor and controls the grain number per panicle in rice by affecting the binding efficiency of *OsMADS34* to the CArG box in the promoter [33].

In this study, we identified an early-flowering gene *OsHd8* in the early-flowering rice JiaHong2B (JH2B) through map-based cloning, which encodes a putative HAP3 subunit of the CCAAT-box-binding transcription factor, and regulates the expression of *OsGI*, *OsSDG718*, *OsHDT1* and *OsGHD7.1* to promote rice heading under long-day conditions

#### **2. Materials and Methods**

#### *2.1. Plant Materials and Cultivation*

To clone *OsHd8*, a F2 population of 4500 individuals was generated from the cross of 1880/JH2B. A set of germplasms, including 101 rice varieties (59 *indica* (*IND*), 9 *temperate japonica* (*TEJ*), 9 *tropical japonica* (*TRJ*), 12 *aus* (*AUS*), 2 *aromatic* (*ARO*) and 10 *admix* (*ADM*)), were used for genotyping of *OsHd8* (Supplementary Table S1). All the rice plants were grown in the ErZhou experimental field (30◦400 N, 114◦880 E) of Wuhan University.

#### *2.2. Heading Date Investigation Map-Based Cloning*

The 1880, JH2B two parents and F2 population were investigated for the heading date. Each plant recorded the heading date when the rice plant began to head with a single spike. A total of 606 F2 plants with extreme phenotypes, which defined as the first 15% of heading in the whole F2 population, derived from the cross of 1880/JH2B were used for mapping of *OsHd8.* Firstly, it was primarily located in the 3.3~6.53 Mb region of the chromosome 8 by BSA-Seq (bulked segregant sequencing), and then we used the F2 population of the target

QTL and mapped *OsHd8* between the marker SNP7730 and SSR-1 (Supplementary Table S2) using a chromosome fragment substitution analysis.

#### *2.3. BSA-Seq and Analysis of the Seq-BSA Data*

For the BSA-seq, two DNA pools were developed by selecting the extreme early heading date plants and extreme late heading date plants from the F2 population. The extreme phenotype of the early growth period was defined as the first 15% of heading in the whole F2 population, and the extreme phenotype of the late growth period was defined as the last 15% of the heading in the whole F2 population. The early heading date pool (Z-pool) was made by mixing equal amounts of DNA from 50 extreme early heading date plats, and the late heading date pool (W-pool) was made by mixing equal amounts of DNA from 50 extreme late heading date plats. The DNA isolated from the two DNA pools were prepared for BSA sequencing.

Libraries for all the DNA pools were prepared according to the Illumina TruSeq Library Construction Kit. The DNA libraries were sequenced on Illumina Hiseq Xten PE15 (Illumina Inc., San Diego, CA, USA). The short reads from the two DNA pools were aligned to a *Nipponbare* reference genome (MSU Rice Genome Annotation Project Release 7) using the BWA software [36]. Reads of the Z-pool and W-pool were separately aligned to a *Nipponbare* reference genome and consensus sequence reads to call SNPs with the SAM tools software [36]. The SNP loci between the test samples and reference genome were obtained using the GATK software [37]. The Euclidean distance (ED) and SNP-index were calculated to identify the candidate regions of the genome associated with the heading date [38].

#### *2.4. RNA Isolation and Quantitative Reverse Transcription-PCR (qRT-PCR) Analysis*

Total RNAs were extracted from young rice leaves of 3-week-old seedlings using the TRIzol Reagent according to the manufacturer's protocol (Invitrogen, Carlsbad, CA, USA). Total RNA was used for synthesizing the cDNA with a reverse transcription kit (Vazyme, Nanjing, China). Quantitative reverse transcriptase (qRT-PCR) was performed on a Roche LightCyclerr480II instrument using the Hieff qPCR SYBR Green Master Mix (No Rox) following the manufacturer's instructions (Yeasen, Shanghai, China). The actin gene was used as the internal control. All assays were performed with three biological replicates and the relative expression level was analyzed with the 2−∆∆CT method [39].

#### *2.5. Vector Constructions and Plant Transformation*

In order to construct a complementary vector, the upstream 2 kb promoter region of the ATG, gene coding region, and downstream 1 kb region of the *OsHd8* gene, were amplified from the genomic DNA of 1880 and then constructed into the complementary vector pCAMBIA1301. To prepare the construction of the Hd8 overexpression vector, the CDS of *OsHd8* was amplified from 1880 and was introduced into the vector pCAMBIA1301-Ubi. All the constructed vector plasmids were transformed into an *Agrobacterium tumefactions* strain EHA105 and transferred by *Agrobacterium*-mediated transformation into JH2B.

#### *2.6. Dual Luciferase (LUC) Analysis*

The promoter regions were amplified from 1880 and JH2B, then cloned into the pGreenII 0800-LUC vector. Subsequently, the vectors co-transformed with GV3101 (pSoup-p19) chemically competent cells. Overnight, *A. tumefaciens* were cultured at 28 ◦C and collected by centrifugation and re-suspended in the MS medium with OD600 = 1.5, and incubated at 28 ◦C and 200 rpm for 3 h. The strains were infiltrated into tobacco (*Nicotiana benthamiana*) leaves and tested after 3 days (long day/white light). Leaves were infiltrated with 1 mM D-luciferin solution and images were captured using a Tanon 5200 Multi imaging system. Quantification was performed using the Dual-Luciferase Reporter Assay System (Promega, Madison, WI, USA). All the assays were performed on three biological replicates.

#### *2.7. Evolutionary Analysis*

The genome sequences of 3024 cultivars and 32 wild rice accessions were obtained from the Rice Functional Genomics and Breeding Database (RFGB, http://www.rmbreeding. cn/Snp3k, accessed on 20 April 2022) and OryzaGenome (http://viewer.shigen.info/ oryzagenome/, accessed on 22 April 2022) [40,41]. The geographic information of cultivated rice populations was obtained from the MKBASE (http://www.mbkbase.org/rice/ germplasm, accessed on 28 April 2022) and marked on the map using R software. The PopGenome package in the R software was used to calculate the parameters of genetic divergence for *OsHd8* and its flanking regions between *indica* and *japonica* subspecies, including haplotype and nucleotide FST, Nei's GST, Hudson's GST and HST [42]. A phylogenetic tree of *OsHd8* was constructed using the UPGMA method with MEGA7.0 [43], and a haplotype network was constructed using the pegas package in the R software [44].

#### *2.8. Statistical Analysis*

All the assays were performed on three biological replicates. The data were analyzed using the GraphPad Prism 9 software (https://www.graphpad.com/, accessed on 28 January 2022) and the means were compared by Student's *t*-test, the \*, \*\* and \*\*\* mean *p* < 0.05, 0.01 and 0.001, respectively. The primers used for genetic mapping, vector construction, PCR and qRT-PCR analysis were all listed in Supplementary Table S4.

#### **3. Results**

#### *3.1. Genetic Analysis and Mapping of OsHd8 for Heading Date*

In the breeding practice, we found that the heading date of the *O. longistaminata* introgression line 1880 and an early flowering variety JiaHong2B (JH2B), was about 92 days and 65 days (Figure 1A,B), respectively, showing a great difference. To explore the genetic basis for the heading date in 1880, genetic linkage analysis of 1147 F2 individuals derived from the cross of 1880/JH2B displayed a continuous distribution with an apparent valley bottom between 62 and 92 days (Figure 1C). These plants were then used for the short and long heading date pools. The two pools were then subjected to whole-genome sequencing up to >121× coverage, and 835,204 high-quality single-nucleotide polymorphisms (SNPs) were identified. SNP-index analysis showed that there was only one obvious single peak on the short arm 3.3~6.53 Mb of chromosome 8 (Supplementary Figure S1), meaning that the candidate gene controlling heading date is possibly located in this region, and named as *Hd8*.

A total of 660 plants with extreme phenotypes were then selected from a 4500 F2 population of 1880/JH2B cross and were used for fine mapping; the *OsHd8* successfully narrowed the locus to a 31.8 kb region between the marker SNP7730 and SSR-1 (Figure 2A). According to the information from the RGAP (Rice Genome Annotation Project), four predicted genes were present in this region, namely, *LOC\_Os08g07730*, *LOC\_Os08g07740*, *LOC\_Os08g07760*, and *LOC\_Os08g07774* (Figure 2A). qRT-PCR showed that the *LOC\_Os08g07740*, encoding a histone-like transcription factor and archaeal histone, had a large expressional difference between 1880 and JH2B (Figure 2B–E). And it was reported a flowering suppressor named *EF8*/*LHD1* [45,46], we deduced that the *LOC\_Os08g07740* was responsible for *OsHd8*.

**Figure 1.** Genetic analysis of heading date in 1880 and JH2B. (**A**) The phenotype of the 1880 and JH2B for heading date. Scale bars = 5cm; (**B**) Statistics on the heading date of 1880 and JH2B; Values are means ± SD (n = 5), \*\*\* indicates a significant difference at *p* < 0.001 by t-test;(**C**) Distribution of heading date in the F2 population derived from 1880 × JH2B. A total of 660 plants with extreme phenotypes were then selected from a 4500 F2 pop-**Figure 1.** Genetic analysis of heading date in 1880 and JH2B. (**A**) The phenotype of the 1880 and JH2B for heading date. Scale bars = 5 cm; (**B**) Statistics on the heading date of 1880 and JH2B; Values are means ± SD (n = 5), \*\*\* indicates a significant difference at *p* < 0.001 by *t*-test;(**C**) Distribution of heading date in the F2 population derived from 1880 × JH2B. *Agronomy* **2022**, *12*, 2260 6 of 17

**Figure 2.** Identification of candidate heading date gene for *OsHd8*. (**A**) Fine mapping of *OsHd8*. The *OsHd8* locus was detected on chromosome 8. Positional cloning narrowed to a 31.8 kb region between marker SNP7730 and SSR-1. The red colors marked gene *LOC\_Os08g7740* was the candidate **Figure 2.** Identification of candidate heading date gene for *OsHd8*. (**A**) Fine mapping of *OsHd8*. The *OsHd8* locus was detected on chromosome 8. Positional cloning narrowed to a 31.8 kb region between

about one week and showed an increased expression level (Figure 3A–C).

< 0.01; Student's t-test).

gene; (**B**–**E**) Comparison of the relative expression levels of four candidate genes among 1880 and JH2B. Values are means ± SEM (n = 3), The asterisks indicate significant differences (\*, *p* < 0.05; \*\*, *p*

4.7 kb genomic fragment, including a 2 kb upstream regulatory sequence, a 1.7 kb gene coding region, and a 1 kb downstream fragment of *OsHd8* from 1880, was cloned into the vector pCAMBIA1301, and introduced into JH2B, through *agrobacterium-*mediated transformation. Compared to JH2B, the heading date of transgenic complementary plants was delayed by marker SNP7730 and SSR-1. The red colors marked gene *LOC\_Os08g7740* was the candidate gene; (**B**–**E**) Comparison of the relative expression levels of four candidate genes among 1880 and JH2B. Values are means ± SEM (n = 3), The asterisks indicate significant differences (\*, *p* < 0.05; \*\*, *p* < 0.01; ns means no significance; Student's *t*-test).

#### *3.2. OsHd8 Encodes a Transcriptional Repressor*

To investigate whether *LOC\_Os08g07740* was responsible for the phenotypic changes, a 4.7 kb genomic fragment, including a 2 kb upstream regulatory sequence, a 1.7 kb gene coding region, and a 1 kb downstream fragment of *OsHd8* from 1880, was cloned into the vector pCAMBIA1301, and introduced into JH2B, through *agrobacterium-*mediated transformation. Compared to JH2B, the heading date of transgenic complementary plants was delayed by about one week and showed an increased expression level (Figure 3A–C). *Agronomy* **2022**, *12*, 2260 7 of 17

**Figure 3.** Effect of *OsHd8* on heading date in rice**.** (**A**) and (**D**) Comparison of heading date of JH2B, *OsHd8* complemented transgenic plants (Com-1-Com-3) and *OsHd8* overexpression transgenic plants (OEHd8-1-OEHd8-3). Scale bars = 5 cm; (**B**) and (**E**) Statistical analysis of heading date of JH2B, *OsHd8* complemented transgenic plants and *OsHd8* overexpression transgenic plants. Values are means ± SD (n = 5), The asterisks indicate significant differences (\*\*, *p* < 0.01; \*\*\*, *p* < 0.00; Student's t-test); (**C**) and (**F**) Expression levels of *OsHd8* in the JH2B, *OsHd8* complemented transgenic plants and *OsHd8* overexpression transgenic plants. Values are means ± SEM (n = 3), The asterisks indicate significant differences (\*\*, *p* < 0.01; \*\*\*, *p* < 0.00; Student's t-test). **Figure 3.** Effect of *OsHd8* on heading date in rice. (**A**) and (**D**) Comparison of heading date of JH2B, *OsHd8* complemented transgenic plants (Com-1-Com-3) and *OsHd8* overexpression transgenic plants (OEHd8-1-OEHd8-3). Scale bars = 5 cm; (**B**) and (**E**) Statistical analysis of heading date of JH2B, *OsHd8* complemented transgenic plants and *OsHd8* overexpression transgenic plants. Values are means ± SD (n = 5), The asterisks indicate significant differences (\*\*, *p* < 0.01; \*\*\*, *p* < 0.00; Student's *t*-test); (**C**) and (**F**) Expression levels of *OsHd8* in the JH2B, *OsHd8* complemented transgenic plants and *OsHd8* overexpression transgenic plants. Values are means ± SEM (n = 3), The asterisks indicate significant differences (\*\*, *p* < 0.01; \*\*\*, *p* < 0.00; Student's *t*-test).

To further validate the function of *LOC\_Os08g0774*0, an overexpression construct was transformed into JH2B. The *OsHd8* transcript level increased by about fivefold, and the heading date was delayed by 15 to 35 days compared with control plants (Figure 3D,E). These results demonstrated that *LOC\_Os08g07740* is *OsHd8*, which is essential for

showed that *OsHd8* was expressed in all tissues, including the roots, young leaves, culms, and panicle (Figure 4B), corresponding to the A protein-BLAST(BLASTp) at NCBI online. Gene identification by MSU-RGAP revealed that *OsHd8* encodes a CBFD\_NFYB\_HMF domain nuclear transcription factor belonging to the HAP3 subunit [46]. The transcriptional activity assays were then performed in rice protoplasts. The luciferase reporter gene contained five copies of binding sites for GAL4, and the Renilla luciferase gene was used as the internal reference. Compared with the transactivator control constructs GALBD-

regulating the heading date in rice.

To further validate the function of *LOC\_Os08g07740*, an overexpression construct was transformed into JH2B. The *OsHd8* transcript level increased by about fivefold, and the heading date was delayed by 15 to 35 days compared with control plants (Figure 3D,E). These results demonstrated that *LOC\_Os08g07740* is *OsHd8*, which is essential for regulating the heading date in rice.

To further investigate the function of *OsHd8*, protein subcellular localization was performed and found that it was located in the nucleus (Figure 4A); spatiotemporal analysis showed that *OsHd8* was expressed in all tissues, including the roots, young leaves, culms, and panicle (Figure 4B), corresponding to the A protein-BLAST(BLASTp) at NCBI online revealed that *OsHd8* encodes a CBFD\_NFYB\_HMF domain nuclear transcription factor belonging to the HAP3 subunit [46]. The transcriptional activity assays were then performed in rice protoplasts. The luciferase reporter gene contained five copies of binding sites for GAL4, and the Renilla luciferase gene was used as the internal reference. Compared with the transactivator control constructs GALBD-VP16, GALBD-VP16 fused with *OsHd8* induced significantly less LUC activity in rice protoplasts (Figure 4C,D), indicating that OsHd8 functions as a transcriptional repressor. *Agronomy* **2022**, *12*, 2260 8 of 17 VP16, GALBD-VP16 fused with *OsHd8* induced significantly less LUC activity in rice protoplasts (Figure 4C,D), indicating that OsHd8 functions as a transcriptional repressor.

**Figure 4.** Molecular characterization of *OsHd8*. (**A**) Subcellular localization of OsHd8 (35S:: OsHd8 sGFP) in rice protoplasts. Scale bar = 10 μm; (**B**) *OsHd8* expression levels in various organs revealed by qRT–PCR, including roots (R), Flag leaf (FL), stem node (St) and young panicles of different lengths (YP1: 0.5-1 cm young panicle, YP2: 1-2 cm young panicle, YP3: 2-3 cm young panicle, YP4: 3-4 cm young panicle, YP5: 4-5 cm young panicle). Values are means ± SEM (n = 3), \*\* indicates a significant difference at *p* < 0.01 by t-test;(**C**) The main structure of vectors of transcriptional activity assays; (**D**) The transcription activity in rice protoplasts by co-transformation of different effector vectors with the reporter plasmids and internal control vectors. **Figure 4.** Molecular characterization of *OsHd8*. (**A**) Subcellular localization of OsHd8 (35S: OsHd8 sGFP) in rice protoplasts. Scale bar = 10 µm; (**B**) *OsHd8* expression levels in various organs revealed by qRT–PCR, including roots (R), Flag leaf (FL), stem node (St) and young panicles of different lengths (YP1: 0.5–1 cm young panicle, YP2: 1–2 cm young panicle, YP3: 2–3 cm young panicle, YP4: 3–4 cm young panicle, YP5: 4–5 cm young panicle). Values are means ± SEM (n = 3), \*\* indicates a significant difference at *p* < 0.01 by *t*-test; (**C**) The main structure of vectors of transcriptional activity assays; (**D**) The transcription activity in rice protoplasts by co-transformation of different effector vectors with the reporter plasmids and internal control vectors.

To illustrate how *OsHd8* regulates the heading date, we compared the genomic se-

one 8-bp InDel were found in the promoters of the two parent lines (Figure 5A).

*3.3. Expression Level of OsHd8 Affects Heading Date*

#### *3.3. Expression Level of OsHd8 Affects Heading Date*

To illustrate how *OsHd8* regulates the heading date, we compared the genomic sequence of *OsHd8* between 1880 and JH2B; no nucleotide difference was detected in the coding regions of *OsHd8* (Supplementary Figure S2). Instead, four polymorphisms and one 8-bp InDel were found in the promoters of the two parent lines (Figure 5A).

To verify whether the 8-bp InDel or 4 SNPs in the *OsHd8* promoter affect the *OsHd8* expression, we generated constructs by installing two type promoter fragments into the pGreenII0800-LUC vector and then introduced the constructs into rice protoplasts for transient expression assays. Results showed that 1880 promoter activity was much stronger than that of JH2 (Figure 5B). Furthermore, to validate the promoter activation capacity between 1880 and JH2B, a Dual-LUC assay was carried out in tobacco leaves and found that the 1880 promoter had a greater LUC/REN value than JH2B (Figure 5C), meaning that the sequence variations in the promoter of 1880 led to a high expression of *OsHd8*, and hence the delayed heading date. *Agronomy* **2022**, *12*, 2260 9 of 17

**Figure 5.** Sequence variations in the *OsHd8* promoter. (**A**) Schematic representation of the two major variations of the *OsHd8* promoter region. CT repeats are labeled in blue; red represents an InDel; (**B**) Transient expression assays of the two *OsHd8* promoter types in rice protoplasts. Values are means ± SEM (*n* = 6), \*\*\* indicates a significant difference at *p* < 0.001 by t-test; (**C**) Image of the Dual-LUC assay in tobacco leaves. **Figure 5.** Sequence variations in the *OsHd8* promoter. (**A**) Schematic representation of the two major variations of the *OsHd8* promoter region. CT repeats are labeled in blue; red represents an InDel; (**B**) Transient expression assays of the two *OsHd8* promoter types in rice protoplasts. Values are means ± SEM (*n* = 6), \*\*\* indicates a significant difference at *p* < 0.001 by *t*-test; (**C**) Image of the Dual-LUC assay in tobacco leaves.

#### To verify whether the 8-bp InDel or 4 SNPs in the *OsHd8* promoter affect the *OsHd8 3.4. Comparative Transcriptome Analysis of JH2B and OE-OsHd8*

expression, we generated constructs by installing two type promoter fragments into the pGreenII0800-LUC vector and then introduced the constructs into rice protoplasts for transient expression assays. Results showed that 1880 promoter activity was much stronger than that of JH2 (Figure 5B). Furthermore, to validate the promoter activation capacity between 1880 and JH2B, a Dual-LUC assay was carried out in tobacco leaves and found that the 1880 promoter had a greater LUC/REN value than JH2B (Figure 5C), meaning that the sequence variations in the promoter of 1880 led to a high expression of *OsHd8*, and hence the delayed heading date. *3.4. Comparative Transcriptome Analysis of JH2B and OE-OsHd8* To further explore the regulatory network underlying the *OsHd8* function, we performed RNA-sequencing analysis with young leaves from JH2B and OE-*Hd8*. A total of 1198 differentially expressed genes (DEGs) were identified, of which 825 genes were upregulated and 373 genes were downregulated in the OE-*OsHd8* plants. Gene Ontology (GO) assay showed that these DEGs were significantly enriched in terms of the metabolic process, binding and transcription regulator activity (Figure 6A). Further analysis of transcription factors of DEGs revealed that transcription factors associated with flowering were enriched in the *OsHd8* pathway, such as the MADS family, HAP2 family, bZIP family and WRKY family (Supplementary Figure S3) [25,47–49]. In particular, several genes controlling the rice heading date, such as *GHD7.1*, *SDG718*, *OsGI* and *HDT1* [2,50–52], were differen-

To further explore the regulatory network underlying the *OsHd8* function, we performed RNA-sequencing analysis with young leaves from JH2B and OE-*Hd8*. A total of 1198 differentially expressed genes (DEGs) were identified, of which 825 genes were up-

process, binding and transcription regulator activity (Figure 6A). Further analysis of transcription factors of DEGs revealed that transcription factors associated with flowering were enriched in the *OsHd8* pathway, such as the MADS family, HAP2 family, bZIP family and WRKY family (Supplementary Figure S3) [25,47–49]. In particular, several genes controlling the rice heading date, such as *GHD7.1*, *SDG718*, *OsGI* and *HDT1* [2,50–52], were differentially expressed in OE-OsHd8 plants just as confirmed with qRT–PCR analysis (Figure 6B). These results demonstrated that *OsHd8* could be involved in complicated

transcriptional regulation processes governing the rice heading date.

tially expressed in OE-OsHd8 plants just as confirmed with qRT–PCR analysis (Figure 6B). These results demonstrated that *OsHd8* could be involved in complicated transcriptional regulation processes governing the rice heading date.

*Agronomy* **2022**, *12*, 2260 10 of 17

**Figure 6.** Transcriptome analysis of the DEGs from RNA-sequencing data in heading date between JH2B and OE-OsHd8. (**A**) Gene ontology (GO) annotation of differentially expressed genes (DEG) in heading date between JH2B and OE-OsHd8. The enriched GO terms of molecular function, biological process and cellular component were listed, and ranged from large to small according to log10Pvalue; (**B**) Comparison of transcriptional expression levels of OsHd8 related genes in heading date between JH2B and OE-OsHd8. Values are means ± SEM (n = 3), The asterisks indicate significant differences (\*, *p* < 0.05; \*\*, *p* < 0.01; Student's t-test). **Figure 6.** Transcriptome analysis of the DEGs from RNA-sequencing data in heading date between JH2B and OE-OsHd8. (**A**) Gene ontology (GO) annotation of differentially expressed genes (DEG) in heading date between JH2B and OE-OsHd8. The enriched GO terms of molecular function, biological process and cellular component were listed, and ranged from large to small according to -log10 *p*value; (**B**) Comparison of transcriptional expression levels of OsHd8 related genes in heading date between JH2B and OE-OsHd8. Values are means ± SEM (n = 3), The asterisks indicate significant differences (\*, *p* < 0.05; \*\*, *p* < 0.01; ns means no significance; Student's *t*-test).

#### *3.5. Variations in the OsHd8 Promoter Affect its Expression and Heading Date* In order to understand the effects of the promoter variation on the expression of *OsHd8*, we then selected 101 rice accessions, including 59 *indica* (*IND*), 9 *temperate japonica*

*3.5. Variations in the OsHd8 Promoter Affect its Expression and Heading Date*

*Agronomy* **2022**, *12*, 2260 11 of 17

In order to understand the effects of the promoter variation on the expression of *OsHd8*, we then selected 101 rice accessions, including 59 *indica* (*IND*), 9 *temperate japonica* (*TEJ*), 9 *tropical japonica* (*TRJ*), 12 *aus* (*AUS*), 2 *aromatic* (*ARO*) and 10 *admix* (*ADM*) lines from different countries for clustering analysis (Figure 7A). Results showed that *OsHd8* diverges into six haplotypes (Figure 7A), of which the haplotype 2 (Hap2), belonging to JH2B, showed the shortest heading date. 1880 belongs to Hap1, which showed the longest heading date, while Hap3, Hap4 and Hap5 were derived from Hap1 by single-base mutations and had a heading date between the Hap1 and Hap2 (Figure 7B). Further transcriptional analysis of *OsHd8* in rice leaves showed that the Hap2 expression was significantly lower than the other five haplotypes (Figure 7C), consistent with the phenotype of the haplotypes. These results indicate that the promoter sequence variation seems significantly correlated with the gene expression and heading date of rice. (*TEJ*), 9 *tropical japonica* (*TRJ*), 12 *aus* (*AUS*), 2 *aromatic* (*ARO*) and 10 *admix* (*ADM*) lines from different countries for clustering analysis (Figure 7A). Results showed that *OsHd8* diverges into six haplotypes (Figure 7A), of which the haplotype 2 (Hap2), belonging to JH2B, showed the shortest heading date. 1880 belongs to Hap1, which showed the longest heading date, while Hap3, Hap4 and Hap5 were derived from Hap1 by single-base mutations and had a heading date between the Hap1 and Hap2 (Figure 7B). Further transcriptional analysis of *OsHd8* in rice leaves showed that the Hap2 expression was significantly lower than the other five haplotypes (Figure 7C), consistent with the phenotype of the haplotypes. These results indicate that the promoter sequence variation seems significantly correlated with the gene expression and heading date of rice.

**Figure 7.** Haplotype analysis of *OsHd8*. (**A**) Haplotype analysis of *OsHd8* from 101 rice varieties; *IND* means *indica*, *TEJ* means *temperate japonica*, *TRJ* means *tropical japonica*, *AUS* means *aus*, *ARO*  means *aromatic*, *ADM* means *admixed*; (**B**) Analysis of heading date in representative varieties with six haplotypes. n = 11 in Hap1, n = 42 in Hap2, n = 27 in Hap3, n = 10 in Hap4, n = 8 in Hap5, and n = 3 in Hap6; (**C**) The relative expression level of the six haplotypes. Values are means ± SEM (n = 3), The asterisks indicate significant differences (\*, *p* < 0.05; \*\*\*, *p* < 0.001; Student's t-test). **Figure 7.** Haplotype analysis of *OsHd8*. (**A**) Haplotype analysis of *OsHd8* from 101 rice varieties; *IND* means *indica*, *TEJ* means *temperate japonica*, *TRJ* means *tropical japonica*, *AUS* means *aus*, *ARO* means *aromatic*, *ADM* means *admixed*; (**B**) Analysis of heading date in representative varieties with six haplotypes. n = 11 in Hap1, n = 42 in Hap2, n = 27 in Hap3, n = 10 in Hap4, n = 8 in Hap5, and n = 3 in Hap6; (**C**) The relative expression level of the six haplotypes. Values are means ± SEM (n = 3), The asterisks indicate significant differences (\*, *p* < 0.05; \*\*\*, *p* < 0.001; Student's *t*-test).

#### *3.6. OsHd8 Is Subjected to Selection in Cultivated Rice*

*3.6. OsHd8 is Subjected to Selection in Cultivated Rice* To investigate the genetic relationship of *OsHd8* variations, a total of 3024 cultivated rice from the 3k database (http://www.rmbreeding.cn/Index/, accessed on 20 April 2022) and 32 *O. rufipogon* accessions (http://viewer.shigen.info/oryzagenome/, accessed on 20 April 2022) were selected to analyze the genetic diversity of this gene and its flanking region. The nucleotide diversity value (π) of *OsHd8* is lower than its flanking regions in To investigate the genetic relationship of *OsHd8* variations, a total of 3024 cultivated rice from the 3k database (http://www.rmbreeding.cn/Index/, accessed on 20 April 2022) and 32 *O. rufipogon* accessions (http://viewer.shigen.info/oryzagenome/, accessed on 20 April 2022) were selected to analyze the genetic diversity of this gene and its flanking region. The nucleotide diversity value (π) of *OsHd8* is lower than its flanking regions in both cultivated and *O. rufipogon* accessions (Figure 8A, Supplementary Table S3), suggesting that *OsHd8* might be subjected to natural selection.

ing that *OsHd8* might be subjected to natural selection.

**Figure 8.** Phylogenetic relationship and genetic variation analysis of *OsHd8*. (**A**) Nucleotide diversity and selection analysis of *OsHd8* and its flanking region (~200 kb). From Rice SNPS-Seek Database (https://snp-seek.irri.org/\_snp.zul, accessed on 20 April 2022) and OryzaGenome (http://viewer.shigen.info/oryzagenome/, accessed on 22 April 2022), Genomic sequences of 3024 cultivated germplasm and 32 wild germplasm were obtained. *ADM* means *admixed*, *ARO* means *aromatic*, *AUS* means *aus*, *IND* means *indica*, *JAP* means unclassified *japonica*, *TEJ* means *temperate japonica*, *TRJ* means *tropical japonica*; (**B**) The parameters of genetic difference between *indica* and *japonica* ecotypes for *OsHd8* and its flanking genomic regions; (**C**) Haplotype network of *OsHd8*. The size of the circle is proportional to the number of samples given to the order. The black dots on the lines indicate the mutation steps between haplotypes; (**D**) Phylogenetic relationship of *OsHd8* generated between 3024 cultivated rice and 32 wild rice accessions. The orange and blue rectangles represent the types of *Hd8*1880 and *Hd8*JH2B, respectively. **Figure 8.** Phylogenetic relationship and genetic variation analysis of *OsHd8*. (**A**) Nucleotide diversity and selection analysis of *OsHd8* and its flanking region (~200 kb). From Rice SNPS-Seek Database (https://snp-seek.irri.org/\_snp.zul, accessed on 20 April 2022) and OryzaGenome (http://viewer. shigen.info/oryzagenome/, accessed on 22 April 2022), Genomic sequences of 3024 cultivated germplasm and 32 wild germplasm were obtained. *ADM* means *admixed*, *ARO* means *aromatic*, *AUS* means *aus*, *IND* means *indica*, *JAP* means unclassified *japonica*, *TEJ* means *temperate japonica*, *TRJ* means *tropical japonica*; (**B**) The parameters of genetic difference between *indica* and *japonica* ecotypes for *OsHd8* and its flanking genomic regions; (**C**) Haplotype network of *OsHd8*. The size of the circle is proportional to the number of samples given to the order. The black dots on the lines indicate the mutation steps between haplotypes; (**D**) Phylogenetic relationship of *OsHd8* generated between 3024 cultivated rice and 32 wild rice accessions. The orange and blue rectangles represent the types of *Hd8*1880 and *Hd8*JH2B, respectively.

both cultivated and *O. rufipogon* accessions (Figure 8A, Supplementary Table S3), suggest-

We further analyzed the parameters of genetic divergence in the *OsHd8* locus between *indica* and *japonica* subspecies from 3024 cultivated accessions, including the estimates of haplotype and nucleotide FST, Nei's GST, and Hudson's GST and HST. Genetic analysis showed that the five parameters in the *OsHd8* locus were all greater than 0.25 between *indica* and *japonica* subspecies, and the haplotype and nucleotide FST reached to 0.549 and 0.764, respectively, (Figure 8B), suggesting strong genetic differentiation between *indica* and *japonica* subspecies at the *OsHd8* locus [53]. Phylogenetic analysis with the coding sequence indicated that the *OsHd8* could be We further analyzed the parameters of genetic divergence in the *OsHd8* locus between *indica* and *japonica* subspecies from 3024 cultivated accessions, including the estimates of haplotype and nucleotide FST, Nei's GST, and Hudson's GST and HST. Genetic analysis showed that the five parameters in the *OsHd8* locus were all greater than 0.25 between *indica* and *japonica* subspecies, and the haplotype and nucleotide FST reached to 0.549 and 0.764, respectively, (Figure 8B), suggesting strong genetic differentiation between *indica* and *japonica* subspecies at the *OsHd8* locus [53].

categorized into 86 haplotypes, and that the *indica* rice was closer to the wild rice haplotypes (Figure 8C). Meanwhile, 1880 was clustered together with the wild rice, meaning Phylogenetic analysis with the coding sequence indicated that the *OsHd8* could be categorized into 86 haplotypes, and that the *indica* rice was closer to the wild rice haplotypes (Figure 8C). Meanwhile, 1880 was clustered together with the wild rice, meaning *Hd8*1880 evolved from wild rice *O. rufipogon* (Figure 8D). These results suggest that *Hd8*1880

originated from wild rice and that at least one mutational event was involved in the origin of *Hd8*1880 in *indica* rice.

#### **4. Discussion**

Flowering is an important trait of plants, and the appropriate flowering time is responsible for the growth and successful sexual reproduction in flowering plants [45]. How to accurately control the flowering time in rice is of great practical significance for the improvement of rice yield. In the present study, we found an elite allele of *EF8/LHD1/DTH8/Ghd8* from indica 1880, which delays the heading date by about 27 days, compared to the JH2B (Figure 1) [45,46,54,55]. Previously, the functional *DTH8* allele from *cv. Asominori* delays the heading date by about 13 days compared to CSSL61 (1-bp deletion in the exon that carries the nonfunctional DTH8) [55]. In our study, the newly identified mutations in the promoter reduced the expression level of *OsHd8* in JH2B, leading to a shorter heading date (Figure 3). Furthermore, the *DTH8* allele from *japonica cv. Asominori* could down-regulate the transcription of *Ehd1* and *Hd3a* to regulate the heading date, and another *EF8* functional allele delays the heading date by regulating the *Hd3a* and *RFT1*. However, our results indicated that *EF8* could alter the expression patterns of the other genes, *GHD7.1*, *SDG718*, *OsGI* and *HDT1* (Figure 3). Therefore, we speculate that different alleles of a gene may have different regulatory roles and target genes, resulting in different regulatory mechanisms and phenotypes. Whether differences in gene sequences or genetic backgrounds lead to different allelic effects is an interesting question that deserves further investigation.

The promoter is located in the upstream of the gene coding region and contains many cis-acting elements (CRE), and transcriptional regulation is mainly determined by the promoter CREs [29]. In our study, the promoter activity of 1880 is much higher than that of JH2B (Figure 4B,C) because of the SNP and InDel variations in the JH2B promoter (Figure 4A), of which one SNP at -335 bp (G/A) is located in the ABRE cis-acting element in the JH2B promoter (Figure 7). It has been well characterized that ABRE, as an important response element of abscisic acid (ABA), plays an important role in the regulation of the ABA signal network [56]. When encountered with drought stress, plants may accelerate the initiation of the flowering transformation to shorten their growth cycle through the RCN1 mediated ABA signal process [57]. Interestingly, we found that the ABA response element in the *OsHd8* promoter of the *japonica* variety *Nipponbare* with a short heading date was the same as that of JH2B. Haplotype analysis based on the promoter sequence showed that the JH2B haplotype had the shortest heading date and the lowest expression level (Figure 7). This reminds us that the mutation of the ABA-responsive element of *OsHd8* in JH2B may lead to the change in the growth period of rice. However, how ABA response elements regulate the expression of *OsHd8* needs to be further validated.

During the evolution of rice, the regional adaptability of cultivated rice is affected by the response to the length of daylight [58]. The heading date is determined by a variety of internal and external signals, including light time, temperature, and hormones [59]. The difference in sensitivity of rice to the photocycle and temperature makes the rice vary greatly in different areas. Many rice lines and wild rice in tropical and subtropical regions, such as *O. rufipogon*, have strong photoperiod sensitivity to flowering. This strong photoperiod sensitivity completely inhibits heading in long-day conditions, allowing it to induce heading only in short daylight conditions [60]. The *Hd8*JH2B allele cloned in this study may be a potential genetic resource. This genotype promotes flowering in long-day conditions and is widely present in the 3K database (Figure 8). With further analysis of the regional distribution map of *Hd8*1880 and *Hd8*JH2B haplotypes, we can see that the *Hd8*JH2B haplotype distributes mainly in the higher latitude area (Figure 9), meaning that this haplotype rice may be less sensitive to photoperiod and have expanded more greatly than the other haplotype rice.

#### **5. Conclusions 5. Conclusions**

This study identified and mapped a heading date gene, *OsHd8*, from an early-flowering rice JiaHong2B (JH2B). Four SNPs and one InDel in the promoter region of *OsHd8*  led to the advance of the JH2B heading date. Comparative transcriptome analysis revealed *OsHd8* to be involved in regulation of some floral regulators including *GHD7.1*, *SDG718*, *OsGI* and *HDT1*. *OsHd8* presents strong genetic differentiation between *indica* and *japonica* subspecies and shows artificial selection during the domestication of cultivated rice. Our work will provide a valuable heading date gene for rice breeding programs This study identified and mapped a heading date gene, *OsHd8*, from an early-flowering rice JiaHong2B (JH2B). Four SNPs and one InDel in the promoter region of *OsHd8* led to the advance of the JH2B heading date. Comparative transcriptome analysis revealed *OsHd8* to be involved in regulation of some floral regulators including *GHD7.1*, *SDG718*, *OsGI* and *HDT1*. *OsHd8* presents strong genetic differentiation between *indica* and *japonica* subspecies and shows artificial selection during the domestication of cultivated rice. Our work will provide a valuable heading date gene for rice breeding programs

**Supplementary Materials:** The supplementary figures and tables are available online at https://www.mdpi.com/article/10.3390/agronomy12102260/s1. Supplementary Figure S1: ED association analysis of candidate genes in heading date. Supplementary Figure S2: Comparison of CDS sequences of *OsHd8* gene in 1880, JH2B and *Nipponbare*. Supplementary Figure S3: Analysis of transcription factors belonging to differentially expressed genes in JH2B and OE-*OsHd8* expression profile by MAPMAN software. Supplementary Table S1: *OsHd8* haplotypes in the 101 rice cultivars. Supplementary Table S2: Recombination events between OsHd8 and molecular markers. Supplementary Table S3: The estimated parameters of nucleotide diversity (π) of *OsHd8* and its flanking regions. Supplementary Table S4: Primers used in this study. **Supplementary Materials:** The supplementary figures and tables are available online at https: //www.mdpi.com/article/10.3390/agronomy12102260/s1. Supplementary Figure S1: ED association analysis of candidate genes in heading date. Supplementary Figure S2: Comparison of CDS sequences of *OsHd8* gene in 1880, JH2B and *Nipponbare*. Supplementary Figure S3: Analysis of transcription factors belonging to differentially expressed genes in JH2B and OE-*OsHd8* expression profile by MAPMAN software. Supplementary Table S1: *OsHd8* haplotypes in the 101 rice cultivars. Supplementary Table S2: Recombination events between OsHd8 and molecular markers. Supplementary Table S3: The estimated parameters of nucleotide diversity (π) of *OsHd8* and its flanking regions. Supplementary Table S4: Primers used in this study.

**Author Contributions:** Conceptualization, S.L. and H.Y.; methodology, S.L.; software, M.C.; validation, R.W.; formal analysis, H.Y. and R.W.; investigation, X.W. and W.W.; resources, S.L. and F.F.; data curation, L.Z. and Z.W.; writing—original draft preparation, H.Y., R.W. and M.C.; writing—review and editing, H.Y. and S.L.; visualization, Z.T.; supervision, S.L.; project administration, S.L.; funding acquisition, S.L. All authors have read and agreed to the published version of the manuscript. **Author Contributions:** Conceptualization, S.L. and H.Y.; methodology, S.L.; software, M.C.; validation, R.W.; formal analysis, H.Y. and R.W.; investigation, X.W. and W.W.; resources, S.L. and F.F.; data curation, L.Z. and Z.W.; writing—original draft preparation, H.Y., R.W. and M.C.; writing—review and editing, H.Y. and S.L.; visualization, Z.T.; supervision, S.L.; project administration, S.L.; funding acquisition, S.L. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by the National Natural Science Foundation of China (U20A2023, 31870322), Hubei Hongshan Laboratory (2021hszd010). **Funding:** This work was supported by the National Natural Science Foundation of China (U20A2023, 31870322), Hubei Hongshan Laboratory (2021hszd010).

**Institutional Review Board Statement:** Not applicable. **Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable. **Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The datasets generated during the current study are available from the corresponding author on reasonable request. **Data Availability Statement:** The datasets generated during the current study are available from the corresponding author on reasonable request.

**Acknowledgments:** We thank IRRI for kindly providing the rice cultivars. **Acknowledgments:** We thank IRRI for kindly providing the rice cultivars.

**Conflicts of interest:** The authors declare no conflict of interest. **Conflicts of Interest:** The authors declare no conflict of interest.

### **References**


*Article* **Maze Solving by a Quantum Walk with Sinks and Self-Loops: Numerical Analysis**

**Leo Matsuoka 1,\*, Kenta Yuki 2, Hynek Laviˇcka 3 and Etsuo Segawa 4**

> 2

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	- Yokohama 240-8501, Japan<EMAIL_ADDRESS>	- Correspondence<EMAIL_ADDRESS>
**Abstract:** Maze-solving by natural phenomena is a symbolic result of the autonomous optimization induced by a natural system. We present a method for finding the shortest path on a maze consisting of a bipartite graph using a discrete-time quantum walk, which is a toy model of many kinds of quantum systems. By evolving the amplitude distribution according to the quantum walk on a kind of network with sinks, which is the exit of the amplitude, the amplitude distribution remains eternally on the paths between two self-loops indicating the start and the goal of the maze. We performed a numerical analysis of some simple cases and found that the shortest paths were detected by the chain of the maximum trapped densities in most cases of bipartite graphs. The counterintuitive dependence of the convergence steps on the size of the structure of the network was observed in some cases, implying that the asymmetry of the network accelerates or decelerates the convergence process. The relation between the amplitude remaining and distance of the path is also discussed briefly.

**Keywords:** discrete-time quantum walk; scattering quantum random walk; Grover walk; pathfinding; network