*Application of Onsager and Prigozhin Variational Principles of Nonequilibrium… DOI: http://dx.doi.org/10.5772/intechopen.103116*

impossible in the mechanics of continuous media to take into account the fluctuations of the hydrodynamic functions formed due to the molecular structure of the medium. At this level of description, taking into account the atomic-molecular structure leads to the Langevin equation, in which the parameters of the medium are described by

random sources. These sources are responsible for fluctuations *ρ*,*V* , *T* and being unavoidable properties of the medium, cannot be excluded. Therefore, postulating Langevin sources in hydrodynamics brings the corresponding equations as close as possible to describing the behavior of a real medium.

In turn, the possibility of taking into account the structure of a physically infinitesimal plasma element in this work was achieved, on the one hand, by using the variational methods of Prigogine and Onsager, combined by Gyarmati, and making it possible to obtain a completely self-consistent equation with the accuracy of the chosen drift approximation. On the other hand, this approximation, being singleparticle, initially takes into account the discreteness of the considered ionized medium ("atomic-molecular" structure). In addition, it admits small perturbations within the limits of its accuracy, that is, within the limits of the constancy of the first adiabatic invariant *μ*.

larger than the distance between collisions on fluctuations. For example, in the problem of plasma flow around the solar wind of the Earth's magnetosphere, the characteristic size of the latter is much less than the mean free path corresponding to Coulomb collisions. This, proceeding from rigorous considerations, indicates the inadmissibility of using the hydrodynamic approximation to describe the processes in this problem. However, the experimental data are in good agreement with the results that follow for this problem from the solution of hydrodynamic equations, which indicates the presence of an effective particle scattering mechanism, which leads to a significant decrease in the mean free path in comparison with Coulomb collisions [12].


**5. Molecular markers for germplasm characterisation**

Molecular markers are DNA tags or sequence differences (polymorphisms) that provide the ability to quickly track the presence of specific DNA regions associated with a trait, through a segregating population. They are widely used for basic research in plant biology and genetics and are now essential to the CSIRO cotton breeding program for selecting homozygous transgenic lines on a large scale, monitoring the purity of transgenic breeding lines, and stacking traits by marker assisted selection. Upland cotton has limited intra-specific genetic polymorphism compared to other crops as revealed by a number of molecular marker and genetic diversity analyses [76-78], due to the relatively recent polyploidisation (estimated 1-2 mya) [79, 80] that created the species as well as domestication and selection. This has hindered application of molecular markers to breeding, as to obtain large numbers of polymorphic markers for detailed mapping required crossing *G. hirsutum* to *G. barbadense* (inter-specific), which are largely unsuitable for cultivar improvement in breeding programs.

Two major technological breakthroughs have occurred in the marker field since ~2010 that have removed many limitations associated with marker technology and its application in cotton.

#### **5.1. SNP discovery in germplasm important for Australia**

cotton. The CSIRO derived sub-clover duplicated stunt7 viral promoter was deregulated in 2008 as a commercial event in cotton (T304-40) driving the *Cry1Ab* insect resistance gene and forms part of Bayer CropScience's TwinLink product. A cotton rubisco small subunit promoter has also been shown to be expressed at high levels in green photosynthetic tissues throughout the development of cotton in the field and hence a useful promoter for expressing transgenes

Molecular markers are DNA tags or sequence differences (polymorphisms) that provide the ability to quickly track the presence of specific DNA regions associated with a trait, through a segregating population. They are widely used for basic research in plant biology and genetics and are now essential to the CSIRO cotton breeding program for selecting homozygous transgenic lines on a large scale, monitoring the purity of transgenic breeding lines, and stacking traits by marker assisted selection. Upland cotton has limited intra-specific genetic polymorphism compared to other crops as revealed by a number of molecular marker and genetic diversity analyses [76-78], due to the relatively recent polyploidisation (estimated 1-2 mya) [79, 80] that created the species as well as domestication and selection. This has hindered application of molecular markers to breeding, as to obtain large numbers of polymorphic markers for detailed mapping required crossing *G. hirsutum* to *G. barbadense* (inter-specific),

Two major technological breakthroughs have occurred in the marker field since ~2010 that have removed many limitations associated with marker technology and its application in

**1.** Next-generation sequencing (NGS) can sequence DNA millions of more times than previous methods [81]. This has opened up the possibility to discover a larger number of single nucleotide polymorphisms (SNP, single DNA base changes) in cotton that are the most common form of difference between individuals or cultivars, and should be sufficiently abundant to discriminate between any two *G. hirsutum* lines. NGS has also enabled the completion of the genome sequence of the diploid cotton *Gossypium raimon‐ dii* [82] that is related to the D-genome present in Upland cotton. The genome sequence of a diploid A-genome containing cotton species is likely to be publicly available in the near future, and will make it easy to compare and align any short sequence reads from NGS to find large numbers of widely distributed nucleotide differences between cultivars

**2.** New high-throughput genotyping (HTG) platforms based on SNPs have been developed that can accurately call millions of SNPs in large populations [83, 84]. These technologies enable complete genome coverage of markers between *G. hirsutum* cultivars in a fraction

**5. Molecular markers for germplasm characterisation**

which are largely unsuitable for cultivar improvement in breeding programs.

that can be used for mapping and breeding.

of the time required by conventional marker approaches.

in leaves [75].

16 World Cotton Germplasm Resources

cotton.

To ensure that SNPs are informative to the breeding populations being developed in Australia, it is essential to find SNPs among cotton cultivars that constitute the major germplasm sources of the elite cultivars we are developing. The most straightforward method to identifying SNPs, in the absence of the Upland cotton genome sequence, is to sequence expressed gene transcripts (RNA-seq) by isolating mRNA and converting it into cDNA for sequencing. This method has been used successfully for many other plants such as maize and wheat [85]. RNA-seq targets SNP discovery to genes that are actively transcribed and therefore more likely to be associated with conferring trait differences. The disadvantage is that cDNA is likely to have lower SNP frequencies than non-expressed regions as they are constrained by the genes function. CSIRO RNA-seq data was generated on a set of 18 cultivars that represented significant genetic variation present within current Australian commercial cultivars were selected; containing old Australian and US cultivars, as well as cultivars from China and India. Over 50 million reads (of ~90 bp) for each Upland cotton sample was obtained. We found the key to identifications of varietal SNPs confidently was when a sub-genome-specific SNP was also found in close proximity to the varietal SNP (Figure 2). This enabled representative sequences from both genomes in each cultivar to be identified and compared. From the 18 cultivars ~38,000 varietal SNPs were identified. A selected subset of >1,500 of these putative SNPs were analysed using a combination of SNP platforms (GoldenGate and Sequenom) and it was found that these SNP could be validated at a rate >90% [Zhu, Q-H, pers comm.]. the Upland cotton genome sequence, is to sequence expressed gene transcripts (RNA-seq) by isolating mRNA and converting it into cDNA for sequencing. This method has been used successfully for many other plants such as maize and wheat [85]. RNA-seq targets SNP discovery to genes that are actively transcribed and therefore more likely to be associated with conferring trait differences. The disadvantage is that cDNA is likely to have lower SNP frequencies than non-expressed regions as they are constrained by the genes function. CSIRO RNA-seq data was generated on a set of 18 cultivars that represented significant genetic variation present within current Australian commercial cultivars were selected; containing old Australian and US cultivars, as well as cultivars from China and India. Over 50 million reads (of ~90 bp) for each Upland cotton sample was obtained. We found the key to identifications of varietal SNPs confidently was when a sub-genome-specific SNP was also found in close proximity to the varietal SNP (Figure 2). This enabled representative sequences from both genomes in each cultivar to be identified and compared. From the 18 cultivars ~38,000 varietal SNPs were identified. A selected subset of >1,500 of these putative SNPs were analysed using a combination of SNP platforms (GoldenGate and Sequenom) and it was found that these SNP could be validated at a rate >90% [Zhu, Q-H, pers comm.].

Figure 2. Stretch of DNA sequence from two cultivars showing the sequences for both the A and D genomes. SNPs with the best validation rates are where a varietal SNP (in red) is in close proximity to a sub-genome-specific SNP (in blue) that allows determination of which genome the specific short reads sequences are derived from. **Figure 2.** Stretch of DNA sequence from two cultivars showing the sequences for both the A and D genomes. SNPs with the best validation rates are where a varietal SNP (in red) is in close proximity to a sub-genome-specific SNP (in blue) that allows determination of which genome the specific short reads sequences are derived from.

Although RNASeq data has allowed us to progress towards being able to effectively use SNPs for genotyping in breeding projects, the protein coding regions of genomes have been found to have a significantly lower level of DNA polymorphism than non-coding regions, so polymorphisms within genes between closely related cultivars are going to be less frequent and hence less useful. With the availability of the assembled *G. raimondii* genome and possibly of the *G. arboreum* genome soon, to serve as a framework for short read sequence alignment, our SNP identification will in future be performed using genomic DNA sources. **5.2. International cotton SNP consortium**  Although RNASeq data has allowed us to progress towards being able to effectively use SNPs for genotyping in breeding projects, the protein coding regions of genomes have been found to have a significantly lower level of DNA polymorphism than non-coding regions, so polymorphisms within genes between closely related cultivars are going to be less frequent and hence less useful. With the availability of the assembled *G. raimondii* genome and possibly of the *G. arboreum* genome soon, to serve as a framework for short read sequence alignment, our SNP identification will in future be performed using genomic DNA sources.

#### SNP Chips enable high throughput parallel analysis (millions at a time) whereas older markers like **5.2. International cotton SNP consortium**

significant improvement over older technologies for large-scale genotyping. Recently an international cotton consortium was formed to create a 70,000 public Illumina Infinium SNP array for cotton. This array was made available for purchase in late 2013 and contains ~ 50,000 SNP Chips enable high throughput parallel analysis (millions at a time) whereas older markers like SSR markers tend to be performed only one or a few at a time. Therefore SNP Chips represent a significant improvement over older technologies for large-scale genotyping.

SSR markers tend to be performed only one or a few at a time. Therefore SNP Chips represent a

intra‐specific *G. hirsutum* SNPs, *~*16,000 inter-specific SNPs predominantly from *G. barbadense* but also *G. tomentosum* and *G. mustelinum*, and small numbers (~4,000) of SNPs from two diploids *G. longicalyx*  and *G. armourianum*. The publicly available SNPs were provided by a number of international groups including; CSIRO, Texas A&M, University of California-Davis, Cotton Incorporated, Brigham Young University and United States Department of Agriculture-Agricultural Research Service, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), Council of Scientific and Industrial Research- National Botanical Research Institute (CSIR-NBRI), and Dow Recently an international cotton consortium was formed to create a 70,000 public Illumina Infinium SNP array for cotton. This array was made available for purchase in late 2013 and contains ~ 50,000 intra‐specific *G. hirsutum* SNPs, *~*16,000 inter-specific SNPs predominantly from *G. barbadense* but also *G. tomentosum* and *G. mustelinum*, and small numbers (~4,000) of SNPs from two diploids *G. longicalyx* and *G. armourianum*. The publicly available SNPs were provided by a number of international groups including; CSIRO, Texas A&M, University of California-Davis, Cotton Incorporated, Brigham Young University and United States Depart‐ ment of Agriculture-Agricultural Research Service, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), Council of Scientific and Industrial Research-National Botanical Research Institute (CSIR-NBRI), and Dow AgroSciences. These arrays will provide unprecedented numbers of makers to be screened across cotton germplasm and will likely be the genotyping method of choice for a number of years.

#### **5.3. Genotype-by-sequencing**

SNP Chips represent a major advance in genotyping of cotton. However, SNP Chip platforms still possess limitations. Since cultivated cotton is an allotetraploid it is often difficult for these platforms to differentiate between the two cotton sub-genomes, and from our experience only ~34% of the polymorphic SNP markers act as co-dominant markers (can discriminate between both homozygous alleles and their heterozygote class, see Figure 3A) on a GoldenGate or Fluidigm platform, whereas the majority act as dominant markers (can only differentiate accurately between both homozygote classes but the heterozygote class cannot be differenti‐ ated from one of the homozygote classes, see Figure 3B). Dominant markers reduce the amount of information that can be obtained from an individual, but they are still very useful for mapping (eg., commonly used AFLP markers are all dominant markers). In addition SNP platforms can only interrogate the SNPs that have already been indentified and placed on the chip, and once manufactured, new SNP Chips are unlikely to be remade for several years, so any newly discovered SNPs will be unable to be included and assayed.

**Figure 3.** Typical *G. hirsutum* varietal SNP profiles using the Sequenom platform. Each spot represents a different culti‐ var being assessed for the presence of a specific SNP. A) Co-dominant example, a particular polymorphic nucleotide is scored either as homozygous A (Green) or C (Blue) or heterozygous for C and A (Yellow). B) Dominant example, a par‐ ticular polymorphic nucleotide can only be scored either as homozygous A (Blue) or heterozygous CA (Yellow), homo‐

Australian Cotton Germplasm Resources http://dx.doi.org/10.5772/58414 19

Possessing significant genetic diversity within a breeding program is extremely important for future crop improvement. Where detailed pedigree information is known, breeders can specifically select parents for crossing based on their trait package and degree of relatedness. However, it is often the case that detailed knowledge about the pedigrees of cultivars is lacking, especially for imported cultivars, and this may hamper their use in cotton improvement. Molecular markers provide an alternative means of determining levels of relatedness and ancestry between cultivars. Many studies have used markers to determine the diversity levels with cotton populations [88], however most have suffered from insufficient numbers of marker required to generate accurate estimates. The first major use of a large public cotton SNP chip and other high throughput genotyping technologies by CSIRO will be to enable more accurate diversity estimates within breeding populations and seed repositories. Breeders should be quickly able to determine diversity estimates and phylogenies between cultivars, as well as identify shared genetic regions between members of the same pedigree. This data will enable the use of more diverse germplasm which may contain unique traits to be effectively integrated

zygous C (blue) cannot be scored due to tetraploid nature [Zhu, Q-H, pers comm.].

**5.4. Genetic diversity analysis**

into the breeding program.

We are investigating genotyping using NGS alone, which is called Genotype-by-Sequencing (GBS). GBS uses an amplified subset of genome from individual lines or plants to identify base differences between them [86, 87]. Using bioinformatic analyses the SNPs are found on-the-go when comparing the two sets of sequences, so no prior information about the genotypes is required. The SNPs found are then analysed as separate markers. The advantage of GBS is that SNPs are found in the analysis of the DNA fragments compared, and so informative SNPs linked to a trait are more likely to be identified. Also SNPs from different genomes can be easily separated based on the presence/absence of specific sub-genome related SNPs (which are much more common than varietal SNPs) and so most markers can be selected to be co-dominant (i.e., heterozygous alleles can be scored). This makes this genotyping technology especially suitable for polyploids such as cotton, and is becoming the genotyping method of choice in, for example, wheat which has three similar genomes (A, B and D) [86].

**Figure 3.** Typical *G. hirsutum* varietal SNP profiles using the Sequenom platform. Each spot represents a different culti‐ var being assessed for the presence of a specific SNP. A) Co-dominant example, a particular polymorphic nucleotide is scored either as homozygous A (Green) or C (Blue) or heterozygous for C and A (Yellow). B) Dominant example, a par‐ ticular polymorphic nucleotide can only be scored either as homozygous A (Blue) or heterozygous CA (Yellow), homo‐ zygous C (blue) cannot be scored due to tetraploid nature [Zhu, Q-H, pers comm.].

#### **5.4. Genetic diversity analysis**

Recently an international cotton consortium was formed to create a 70,000 public Illumina Infinium SNP array for cotton. This array was made available for purchase in late 2013 and contains ~ 50,000 intra‐specific *G. hirsutum* SNPs, *~*16,000 inter-specific SNPs predominantly from *G. barbadense* but also *G. tomentosum* and *G. mustelinum*, and small numbers (~4,000) of SNPs from two diploids *G. longicalyx* and *G. armourianum*. The publicly available SNPs were provided by a number of international groups including; CSIRO, Texas A&M, University of California-Davis, Cotton Incorporated, Brigham Young University and United States Depart‐ ment of Agriculture-Agricultural Research Service, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), Council of Scientific and Industrial Research-National Botanical Research Institute (CSIR-NBRI), and Dow AgroSciences. These arrays will provide unprecedented numbers of makers to be screened across cotton germplasm

SNP Chips represent a major advance in genotyping of cotton. However, SNP Chip platforms still possess limitations. Since cultivated cotton is an allotetraploid it is often difficult for these platforms to differentiate between the two cotton sub-genomes, and from our experience only ~34% of the polymorphic SNP markers act as co-dominant markers (can discriminate between both homozygous alleles and their heterozygote class, see Figure 3A) on a GoldenGate or Fluidigm platform, whereas the majority act as dominant markers (can only differentiate accurately between both homozygote classes but the heterozygote class cannot be differenti‐ ated from one of the homozygote classes, see Figure 3B). Dominant markers reduce the amount of information that can be obtained from an individual, but they are still very useful for mapping (eg., commonly used AFLP markers are all dominant markers). In addition SNP platforms can only interrogate the SNPs that have already been indentified and placed on the chip, and once manufactured, new SNP Chips are unlikely to be remade for several years, so

We are investigating genotyping using NGS alone, which is called Genotype-by-Sequencing (GBS). GBS uses an amplified subset of genome from individual lines or plants to identify base differences between them [86, 87]. Using bioinformatic analyses the SNPs are found on-the-go when comparing the two sets of sequences, so no prior information about the genotypes is required. The SNPs found are then analysed as separate markers. The advantage of GBS is that SNPs are found in the analysis of the DNA fragments compared, and so informative SNPs linked to a trait are more likely to be identified. Also SNPs from different genomes can be easily separated based on the presence/absence of specific sub-genome related SNPs (which are much more common than varietal SNPs) and so most markers can be selected to be co-dominant (i.e., heterozygous alleles can be scored). This makes this genotyping technology especially suitable for polyploids such as cotton, and is becoming the genotyping method of choice in, for

and will likely be the genotyping method of choice for a number of years.

any newly discovered SNPs will be unable to be included and assayed.

example, wheat which has three similar genomes (A, B and D) [86].

**5.3. Genotype-by-sequencing**

18 World Cotton Germplasm Resources

Possessing significant genetic diversity within a breeding program is extremely important for future crop improvement. Where detailed pedigree information is known, breeders can specifically select parents for crossing based on their trait package and degree of relatedness. However, it is often the case that detailed knowledge about the pedigrees of cultivars is lacking, especially for imported cultivars, and this may hamper their use in cotton improvement. Molecular markers provide an alternative means of determining levels of relatedness and ancestry between cultivars. Many studies have used markers to determine the diversity levels with cotton populations [88], however most have suffered from insufficient numbers of marker required to generate accurate estimates. The first major use of a large public cotton SNP chip and other high throughput genotyping technologies by CSIRO will be to enable more accurate diversity estimates within breeding populations and seed repositories. Breeders should be quickly able to determine diversity estimates and phylogenies between cultivars, as well as identify shared genetic regions between members of the same pedigree. This data will enable the use of more diverse germplasm which may contain unique traits to be effectively integrated into the breeding program.

#### **5.5. Linking SNPs to traits**

With improvements in SNP identification and the availability of large scale public cotton SNP chip, the availability of molecular makers will no longer be a limiting issue in cotton research and the main task will be linking markers to important traits that will aid in their introgression into elite varieties. Most of our initial focus will be to link SNPs to disease resistance traits, as increased disease resistance has been responsible for a significant amount of our variety based yield improvements. Common methods for linking markers to traits involve the creation of bi-parental crosses that segregate for the trait of interest, followed by selfing, genotyping and trait assessment in the F2 or F3 populations. Where possible immortal genetic populations, in which each line is inbred and can be propagated simply by self-pollination, such as recombi‐ nant inbred populations or inbred backcross (IBC) populations are used as phenotyping is much simpler (only looking at homozygote classes) and repeatable. These immortals lines have been very helpful when assaying for disease resistance (Verticillium wilt, Fusarium wilt and black root rot) as disease phenotypes are often environmentally affected and difficult to score. The new high-throughput marker technology should greatly accelerate these traditional genetic studies in cotton. However, such populations require significant amounts of time and labor invested in their creation. With the availability of high throughput SNP genotyping between *G. hirsutum* cultivars, other approaches consistent with conventional breeding strategies can now be routinely performed. One such method involves locating chromosomal segment substitutions derived by repeated backcrossing of the trait into an elite cultivar. Backcrossing is used by breeders to transfer a limited number of desirable traits from one parent (possibly poor agronomically) to an elite parent, and involves multiple rounds of crossing back to a recurring elite line; with each backcross reducing the amount of donor DNA present in the offspring. This methodology can be used to find markers linked to the trait(s) after as little as 3 cycles of backcrossing and then selfing, as individuals with the desired trait can now be compared using whole genome SNP analysis to reveal which genomic regions are associated with the donor parent. The markers in the donor regions can be confirmed as being linked to the trait in a further cycle of backcrossing, selfing and selection. Once the marker linkage has been verified, marker-assisted backcrossing can then eliminate the need for further trait phenotyping until the desired elite cultivar is obtained. We are using this system to find linked markers for disease and fibre traits and for introgression of traits from other cotton species.

**5.6. Genome wide association mapping**

cotton germplasm cultivars.

**5.7. Mining diversity in other cotton species**

Upland cotton by genetic modification.

Large scale genotyping of cotton at an economical price enables genotyping large diverse collections of *G. hirsutum* lines. To link SNP markers to important traits in cotton the most manageable route is to perform genome wide association studies on elite cultivars and their pedigrees, avoiding the time and energy required in the creation of specialised genetic populations examining small numbers of traits. Association genetic analysis is a method for linking specific markers with phenotypes using established populations of individuals, and has been extensively used in human/animal genetic analyses where defined genetic crosses are often difficult to generate [89]. The extent of genome-wide allelic association (linkage disequilibrium: LD) is the key starting point for association mapping. The extent of LD has been quantified and association mapping has been successfully applied for many plant species (e.g., [90]) including cotton [91, 92]. The application of LD-based association mapping for cotton will facilitate comprehensive utilization of existing genetic diversity conserved within

Australian Cotton Germplasm Resources http://dx.doi.org/10.5772/58414 21

CSIRO is interested in using association analysis on a large number of well defined cotton varieties to find markers linked to disease resistance, fibre quality and yield component traits. The bottleneck for this type of research is the difficulty in adequately phenotyping a large number of cultivars for agronomically important traits. To obtain an accurate measurement of the most important trait, yield, requires significant replication both within a field, across geographical regions and over multiple seasons. This restricts the numbers of varieties that can be tested lowering the power of the analyses. It is also possible to model genetic/environ‐ mental (GxE) interactions for specific traits using association analysis, but that requires a magnitude larger level of replication under different management conditions, as well as significant knowledge about the environmental conditions in which the traits were measured

(and therefore is unlikely to be undertaken by our research teams in the near future).

The cotton genus (*Gossypium*) contains ~50 species that are widely geographically distributed from arid to tropical regions and morphologically diverse ranging from herbaceous perennials to small trees. These species are usually divided into three gene pools with regard to their use for genetic improvement of Upland cotton though only a few sources have been extensively used. The primary gene pool consists of *G. barbadense, G. tomentosum*, *G. mustelinum* and *G. darwinii* which are tetraploid species with the same A and D genome complement that are sexually compatible with Upland cotton. The secondary gene pool is represented by diploids with A, D, B or F genomes that require synthetic tetraploid formation or a synthetic hexaploid bridging species for traits to be introgressed into Upland cotton [39, 44]. The tertiary gene pool consists of other diploid species with a completely different genome type such as C, E, G or K that show relatively poor or no recombination with the A or D-genome and thus traits from these species are likely to require isolation of the causal genes and transfer into cultivated

Once a representative A-genome diploid sequence is completed, and its information added to the already published D genome, it will be possible to use this information as a scaffold to

The ability to scan the whole genome quickly and identify regions from the donor plant makes this strategy practical in cotton and is limited only by reliability and robustness of the trait and the time it takes to cycle through multiple generations. An added advantage of this method to find markers is that the germplasm produced at the end of the process is already partly introgressed into an elite cultivar and can be a parent for more advanced crosses with other elite material. A SNP Chip can also be used to identify backcrossed individuals with the lowest levels of donor DNA at each backcrossing step, reducing the number of backcrosses required to produce an elite cultivar with the trait of interest. This is especially useful to separate the trait of interest from regions nearby that may carry genes that result in poor yield (linkage drag), such as Okra leaf trait.

#### **5.6. Genome wide association mapping**

**5.5. Linking SNPs to traits**

20 World Cotton Germplasm Resources

species.

drag), such as Okra leaf trait.

With improvements in SNP identification and the availability of large scale public cotton SNP chip, the availability of molecular makers will no longer be a limiting issue in cotton research and the main task will be linking markers to important traits that will aid in their introgression into elite varieties. Most of our initial focus will be to link SNPs to disease resistance traits, as increased disease resistance has been responsible for a significant amount of our variety based yield improvements. Common methods for linking markers to traits involve the creation of bi-parental crosses that segregate for the trait of interest, followed by selfing, genotyping and trait assessment in the F2 or F3 populations. Where possible immortal genetic populations, in which each line is inbred and can be propagated simply by self-pollination, such as recombi‐ nant inbred populations or inbred backcross (IBC) populations are used as phenotyping is much simpler (only looking at homozygote classes) and repeatable. These immortals lines have been very helpful when assaying for disease resistance (Verticillium wilt, Fusarium wilt and black root rot) as disease phenotypes are often environmentally affected and difficult to score. The new high-throughput marker technology should greatly accelerate these traditional genetic studies in cotton. However, such populations require significant amounts of time and labor invested in their creation. With the availability of high throughput SNP genotyping between *G. hirsutum* cultivars, other approaches consistent with conventional breeding strategies can now be routinely performed. One such method involves locating chromosomal segment substitutions derived by repeated backcrossing of the trait into an elite cultivar. Backcrossing is used by breeders to transfer a limited number of desirable traits from one parent (possibly poor agronomically) to an elite parent, and involves multiple rounds of crossing back to a recurring elite line; with each backcross reducing the amount of donor DNA present in the offspring. This methodology can be used to find markers linked to the trait(s) after as little as 3 cycles of backcrossing and then selfing, as individuals with the desired trait can now be compared using whole genome SNP analysis to reveal which genomic regions are associated with the donor parent. The markers in the donor regions can be confirmed as being linked to the trait in a further cycle of backcrossing, selfing and selection. Once the marker linkage has been verified, marker-assisted backcrossing can then eliminate the need for further trait phenotyping until the desired elite cultivar is obtained. We are using this system to find linked markers for disease and fibre traits and for introgression of traits from other cotton

The ability to scan the whole genome quickly and identify regions from the donor plant makes this strategy practical in cotton and is limited only by reliability and robustness of the trait and the time it takes to cycle through multiple generations. An added advantage of this method to find markers is that the germplasm produced at the end of the process is already partly introgressed into an elite cultivar and can be a parent for more advanced crosses with other elite material. A SNP Chip can also be used to identify backcrossed individuals with the lowest levels of donor DNA at each backcrossing step, reducing the number of backcrosses required to produce an elite cultivar with the trait of interest. This is especially useful to separate the trait of interest from regions nearby that may carry genes that result in poor yield (linkage

Large scale genotyping of cotton at an economical price enables genotyping large diverse collections of *G. hirsutum* lines. To link SNP markers to important traits in cotton the most manageable route is to perform genome wide association studies on elite cultivars and their pedigrees, avoiding the time and energy required in the creation of specialised genetic populations examining small numbers of traits. Association genetic analysis is a method for linking specific markers with phenotypes using established populations of individuals, and has been extensively used in human/animal genetic analyses where defined genetic crosses are often difficult to generate [89]. The extent of genome-wide allelic association (linkage disequilibrium: LD) is the key starting point for association mapping. The extent of LD has been quantified and association mapping has been successfully applied for many plant species (e.g., [90]) including cotton [91, 92]. The application of LD-based association mapping for cotton will facilitate comprehensive utilization of existing genetic diversity conserved within cotton germplasm cultivars.

CSIRO is interested in using association analysis on a large number of well defined cotton varieties to find markers linked to disease resistance, fibre quality and yield component traits. The bottleneck for this type of research is the difficulty in adequately phenotyping a large number of cultivars for agronomically important traits. To obtain an accurate measurement of the most important trait, yield, requires significant replication both within a field, across geographical regions and over multiple seasons. This restricts the numbers of varieties that can be tested lowering the power of the analyses. It is also possible to model genetic/environ‐ mental (GxE) interactions for specific traits using association analysis, but that requires a magnitude larger level of replication under different management conditions, as well as significant knowledge about the environmental conditions in which the traits were measured (and therefore is unlikely to be undertaken by our research teams in the near future).

#### **5.7. Mining diversity in other cotton species**

The cotton genus (*Gossypium*) contains ~50 species that are widely geographically distributed from arid to tropical regions and morphologically diverse ranging from herbaceous perennials to small trees. These species are usually divided into three gene pools with regard to their use for genetic improvement of Upland cotton though only a few sources have been extensively used. The primary gene pool consists of *G. barbadense, G. tomentosum*, *G. mustelinum* and *G. darwinii* which are tetraploid species with the same A and D genome complement that are sexually compatible with Upland cotton. The secondary gene pool is represented by diploids with A, D, B or F genomes that require synthetic tetraploid formation or a synthetic hexaploid bridging species for traits to be introgressed into Upland cotton [39, 44]. The tertiary gene pool consists of other diploid species with a completely different genome type such as C, E, G or K that show relatively poor or no recombination with the A or D-genome and thus traits from these species are likely to require isolation of the causal genes and transfer into cultivated Upland cotton by genetic modification.

Once a representative A-genome diploid sequence is completed, and its information added to the already published D genome, it will be possible to use this information as a scaffold to determine the gene coding regions for different *Gossypium* species. The coding sequences from these genomes will identify new diversity within genes already associated with disease and stress that could be targets for introgression. Traditionally the work required to introgress traits from anything other than *G. hirsutum* or *G. barbadense* has been prohibitive. However the ability to identify important genes via re-sequencing of other *Gossypium* species means that markers for these traits can be found rapidly and used in marker assisted backcrossing strategies as mentioned above. Therefore, in future we will be able to access much more diverse germplasm for unique traits with potential targets for introgression including glandless seeds (in a glanded plant) and Fusarium wilt resistance that are present in indigenous Australian *Gossypium* species [47, 48].

phenotype of these plants would then be compared to homozygous wild-type plants at this

Australian Cotton Germplasm Resources http://dx.doi.org/10.5772/58414 23

The availability of mutant lines in most or all of the cotton genes would provide the cotton community with the means of testing gene function in a large number of genes at an unpre‐ cedented rate. Lines with mutations in a particular gene would need to be found in both subgenomes, then crossed and progeny selected that were mutated for both copies of the genes in order to categorically define its function. Once a gene has been confirmed as being associated with an important trait, the sequence of this gene could be sequenced from many different cotton cultivars and related species to identify variants that may possess superior qualities for targeted introgression. Currently, large mutagenic populations of *G. arboreum* and *G. hirsu‐ tum* are being established at CSIRO in order to locate genes involved in fibre formation and

NGS and high throughput genotyping will enable large numbers of specific traits to be linked to specific markers, thus increasing the importance of marker assisted selection in the breeding of cotton. However the ability to easily stack a moderate number of traits becomes quickly impractical in the field, where extremely large population would need to be grown to identify plants carrying all the correct combination of markers. To overcome this problem a number of companies have developed non-destructive seed based screening methodologies to screen markers. 'Seed chippers' [96] use complicated robotics and liquid handling equipment to remove small portions of embryo, extracting DNA and performing genotyping. This technol‐ ogy was first demonstrated in maize and then soybean but is beginning to be adapted to work in cotton. Seed-based screening will play an essential role in future transgenic trait stacking and marker-assisted breeding of disease and fibre traits in cotton as it will allow the very small proportion of plants with the favorable allele combination to be identified. Seeds selected that contain the correct marker combinations will be planted in the field and selections for fibre and yield traits performed normally, with the knowledge that other desired traits are already

**6. Success stories of germplasm utilization in Australian cotton**

As mentioned previously, bacterial blight was the most important disease in Australian cotton when the modern Industry first started with estimated yield losses up to 20%. Bacterial blight resistance was introduced to the CSIRO breeding program from Tamcot SP37, which supplied the B2, B3 and B7 genes [97]. The first blight resistant cultivar was released in 1985 and had rapid adoption. Importantly, this cultivar also had high yield, high gin turnout, wide adapta‐ tion and the okra leaf trait. This cultivar was selected from a large breeding population that

location from the same seed lot.

disease and insect resistance.

**5.9. Seed genotyping**

present.

**improvement**

**6.1. Disease resistance**

#### **5.8. Exploiting mutant collections of cotton**

As previously mentioned, induced mutations can produce novel variation that can be directly used for crop improvement and aid in identifying which genes are important for specific traits. Now that a genome sequence is available for cotton, the major basic research challenge is to uncover the genes responsible for major agronomic traits from the more than 50,000 genes present in this species. The advent of NGS technology and the completed *G. raimondii* genome sequence has opened up practical ways of achieving this via a reverse genetics approach; where a mutation in a specific gene sequence is first identified in a plant by sequencing and the phenotype of this plant is then compared against the not mutated or wild-type plant to identify the physiological, morphological or agronomic consequences of the disruption of that gene and hence its possible function. Traditionally mutated plants with interesting phenotypes are selected from large populations of mutagenised plants, and researchers work back to find where the mutation that caused the novel trait is located within the genome (forward genetic approach). However the space/land required in order to select for interesting mutants is substantial for a large plant like cotton, and the tetraploid nature of Upland cotton, potentially makes finding valuable mutants more difficult (as for some traits both the A and D genome genes would need to be simultaneously mutated to result in a phenotype). The reverse genetics approach, is to first obtain a large collection of plants carrying chemically or radiation induced mutations spread throughout the genome that are identified through NGS. Since NGS can rapidly re-sequence a genome as long as an existing reference genome is known, sequencing the randomly mutated plants will identify single base changes in gene sequences caused by chemical mutagenesis similar to how SNPs are already identified between cultivars. Using specialised DNA capture technologies that only isolate DNA from expressed regions of the genome to reduce the sequence complexity [93, 94], this procedure would be cost effective. A large library of plants harbouring these known mutations, would be made by subjecting cotton seeds to induced mutagenesis and plants (M1 generation) grown and allowed to self seed. The M2 seeds would then be planted, leaf material isolated and the gene sequences of these plants sequenced and the multiple mutations in each plant identified. By collecting seeds from the M2 plants, a database of the sequence changes would be identified and associated with specific seed lots and mutations causing loss of gene function of any selected gene could be identified. The M3 seeds from that plant would be planted and using markers specific for the mutation (a type of SNP marker), plants selected that were homozygous for the mutation [95]. The phenotype of these plants would then be compared to homozygous wild-type plants at this location from the same seed lot.

The availability of mutant lines in most or all of the cotton genes would provide the cotton community with the means of testing gene function in a large number of genes at an unpre‐ cedented rate. Lines with mutations in a particular gene would need to be found in both subgenomes, then crossed and progeny selected that were mutated for both copies of the genes in order to categorically define its function. Once a gene has been confirmed as being associated with an important trait, the sequence of this gene could be sequenced from many different cotton cultivars and related species to identify variants that may possess superior qualities for targeted introgression. Currently, large mutagenic populations of *G. arboreum* and *G. hirsu‐ tum* are being established at CSIRO in order to locate genes involved in fibre formation and disease and insect resistance.

#### **5.9. Seed genotyping**

determine the gene coding regions for different *Gossypium* species. The coding sequences from these genomes will identify new diversity within genes already associated with disease and stress that could be targets for introgression. Traditionally the work required to introgress traits from anything other than *G. hirsutum* or *G. barbadense* has been prohibitive. However the ability to identify important genes via re-sequencing of other *Gossypium* species means that markers for these traits can be found rapidly and used in marker assisted backcrossing strategies as mentioned above. Therefore, in future we will be able to access much more diverse germplasm for unique traits with potential targets for introgression including glandless seeds (in a glanded plant) and Fusarium wilt resistance that are present in indigenous Australian

As previously mentioned, induced mutations can produce novel variation that can be directly used for crop improvement and aid in identifying which genes are important for specific traits. Now that a genome sequence is available for cotton, the major basic research challenge is to uncover the genes responsible for major agronomic traits from the more than 50,000 genes present in this species. The advent of NGS technology and the completed *G. raimondii* genome sequence has opened up practical ways of achieving this via a reverse genetics approach; where a mutation in a specific gene sequence is first identified in a plant by sequencing and the phenotype of this plant is then compared against the not mutated or wild-type plant to identify the physiological, morphological or agronomic consequences of the disruption of that gene and hence its possible function. Traditionally mutated plants with interesting phenotypes are selected from large populations of mutagenised plants, and researchers work back to find where the mutation that caused the novel trait is located within the genome (forward genetic approach). However the space/land required in order to select for interesting mutants is substantial for a large plant like cotton, and the tetraploid nature of Upland cotton, potentially makes finding valuable mutants more difficult (as for some traits both the A and D genome genes would need to be simultaneously mutated to result in a phenotype). The reverse genetics approach, is to first obtain a large collection of plants carrying chemically or radiation induced mutations spread throughout the genome that are identified through NGS. Since NGS can rapidly re-sequence a genome as long as an existing reference genome is known, sequencing the randomly mutated plants will identify single base changes in gene sequences caused by chemical mutagenesis similar to how SNPs are already identified between cultivars. Using specialised DNA capture technologies that only isolate DNA from expressed regions of the genome to reduce the sequence complexity [93, 94], this procedure would be cost effective. A large library of plants harbouring these known mutations, would be made by subjecting cotton seeds to induced mutagenesis and plants (M1 generation) grown and allowed to self seed. The M2 seeds would then be planted, leaf material isolated and the gene sequences of these plants sequenced and the multiple mutations in each plant identified. By collecting seeds from the M2 plants, a database of the sequence changes would be identified and associated with specific seed lots and mutations causing loss of gene function of any selected gene could be identified. The M3 seeds from that plant would be planted and using markers specific for the mutation (a type of SNP marker), plants selected that were homozygous for the mutation [95]. The

*Gossypium* species [47, 48].

22 World Cotton Germplasm Resources

**5.8. Exploiting mutant collections of cotton**

NGS and high throughput genotyping will enable large numbers of specific traits to be linked to specific markers, thus increasing the importance of marker assisted selection in the breeding of cotton. However the ability to easily stack a moderate number of traits becomes quickly impractical in the field, where extremely large population would need to be grown to identify plants carrying all the correct combination of markers. To overcome this problem a number of companies have developed non-destructive seed based screening methodologies to screen markers. 'Seed chippers' [96] use complicated robotics and liquid handling equipment to remove small portions of embryo, extracting DNA and performing genotyping. This technol‐ ogy was first demonstrated in maize and then soybean but is beginning to be adapted to work in cotton. Seed-based screening will play an essential role in future transgenic trait stacking and marker-assisted breeding of disease and fibre traits in cotton as it will allow the very small proportion of plants with the favorable allele combination to be identified. Seeds selected that contain the correct marker combinations will be planted in the field and selections for fibre and yield traits performed normally, with the knowledge that other desired traits are already present.


3.2.2. Algae

The total overall algae cover across the entire site increased significantly from 42.9 ± 3.1% in 2000 to 56.8 ± 3.2% in 2018 (*p* = 0.0009) (Figures 4 and 5). *Dictyosphaeria* spp. (*D. cavernosa* and *D. versluyii*) decreased significantly from 16.7 ± 1.5% in 2000 to 1.1 ± 0.3% 2018 (*p* < 0.0001). *Gracilaria salicornia* and *Kappaphycus alvarezii* were both present in 2000 (2.8 ± 2.4%, and 0.33 ± 0.3% respectively) and absent from the 2018 survey (*p* = 0.0002, 0.045). Non-coral substrate (turf, crustose coralline algae) increased significantly from 23.1 ± 2.1% in 2000 to 55.6 ± 3.2% in 2018 (*p* < 0.0001).


**6. ECV impact on the reduction of caesarean deliveries and breech presentation at birth**

The Cochrane, in a systematic review, assessed the external cephalic version at term effects. The results proved a clinically and statistically significant reduction of breech babies as well as of caesareans deliveries when the external cephalic version was used. No significant effects on perinatal mortality were observed. No significant differences in the incidence on Apgar score were observed (7 at the first minute or at the fifth minute, low umbilical artery PH level or perinatal death.

In fact, the Cochrane Foundation recommended offering the external version to every woman with normal pregnancies and breeching presentation at term (37th-42nd week) (level of recommendation A).

The cephalic version at term reduces the incidence of breech presentation (risk difference 52%, NNT 2) as well as the caesarean rate (risk difference 17%, NNT 6) at birth. In daily

The External Version in Modern Obstetrics 195

Secondly, the baby's must be move by palpating the backbone. This can be achieved by using both hands simultaneously. While with one hand, the babies feet are moved upwards, with the other hand the baby's head must be moved to the opposite side and towards the pelvis. The rotation must continue until achieving the optimal vertex position

It must not be performed any sudden manoeuvres, but moderate and sustained pressure, trying that the fetus make the rest of the movement. Basically, the purpose is that the fetus

Fig. 2. Maneuvers to secure the cephalic presentation in fetuses with breech presentation.

During the maneuver the fetal presentation must be monitored with the ultrasound scan and the fetal cardiac frequency with continuous cardiotocography. Transitional fetal bradycardia commonly occurs. It is spontaneously solved in most of cases. However, the version must be stopped if it is sustained and still continues after relieving the pressure. It will also be stopped if it does not succeed after a short period of time or in case of severe pain. The benefit of performing the version without anesthesia is that the pain suffered is an indicator of the limit of pressure in the maneuver. Furthermore, the use of epidural analgesia has not proved neither a greater success in the maneuver, nor a reduction in subsequent caesarean rate (Hofmeyr, 2003). After the procedure, the tocolytics perfusion will be stopped and the success of the manoeuvre will be confirmed by ultrasound

Regardless of the success or the failure of the version, the fetal status must be evaluated again after performing the procedure. The fetus must be monitored for at least 45 minutes. If the cardiotocographic record is normal and there is no vaginal bleeding or pain, the patient can be discharged, although a 24 hour relative rest will be

itself finds a more comfortable position than the one that it has under pressure.

(SEGO, 2001).

scanning.

recommended.

clinical practice, most of breech babies are born by elective caesarean, without considering the vaginal delivery possibility. That is why the number of caesarians has a further increase in daily clinical practice that in the projects. This reduction in the number of caesareans continues in spite of the increase of intrapartum caesareans (which has been observed in cephalic babies after a successful version in comparison to babies with spontaneous cephalic presentation). Furthermore, this increase is regardless of a higher induction rate and it is caused by both maternal and fetal indications.

Table 1. Definitions of Grade of Recommendation.

With respect to the external cephalic version effect on the perinatal outcome, the Cochrane data base indicates that, even though no statistically significant differences on perinatal mortality were observed, there is not enough evidence to precisely evaluate the risks related to the process. More projects must be carried out to determine the adverse effects as well as on the external version practice at birth or on the foetuses in non-longitudinal situation. with to


*4.3. 3D Bioprinted Heart Tissue Patches for Drug Screening*

An increasingly widespread opinion believes that 3D printing can offer great potential also in pharmaceutics for the discovery and development of new drugs, as well as for advances in drug delivery strategies [94]. Drug discovery represents the preclinical phase of the entire process, and it consists in testing thousands of compounds to select few candidates with possible beneficial effects against the clinical target diseases. The drug development phase involves further validation of the selected drug in terms of absorption, distribution, metabolism, excretion (ADME), toxicity, dosage, and treatment modalities, as well as interaction with other molecular compounds [110]. Drug development is a multistep process that involves phase I-III clinical trials, review and approval by the Food and Drug Administration (FDA), phase IV clinical trials, followed by launch in the market, and post-market surveillance by FDA.

About 94% of the drugs that passed the preclinical trials fail in the clinical phase [111]. It is believed that this is mainly attributable to inadequate screening in preclinical trials, most of which are still performed on traditional 2D monolayer culture systems that miss the native 3D extracellular microenvironment [112]. Furthermore, the efficacy and toxicity of drugs evaluated in animal studies do not always predict the response in human patients [113]. For example, during both the preclinical and clinical stages of drug development, cardiotoxicity remains a major cause of failure, thus representing the primary reason for the retraction of pharmaceuticals from the market [114]. The use of 3D engineered tissue platforms could overcome these problems, and 3D bioprinting, in particular, could play a key role in both the drug discovery and development phases. 3D bioprinted tissues could produce results similar to those obtained in in vivo tests, thus representing valuable platforms for conducting drug toxicity analysis in vitro.

In the cardiovascular field, most of the efforts toward developing drug discovery and screening platforms have focused on recreating microtissues of the left ventricular myocardium, the site of most cardiac pathologies and the primary pumping chamber of the heart [115]. For example, Zhang and colleagues developed a novel hybrid strategy based on 3D bioprinting to engineer endothelialized myocardial tissues [116]. In their work, the authors directly encapsulated ECs (1 × 107 cells/mL) within an alginate/GelMA bioink through a combination of extrusion and photocuring processes (Figure 9A). In approximatively 2 weeks of culture, the ECs gradually migrated toward the microfiber peripheries, organizing in a confluent layer of endothelium, and formed a pattern resembling the blood vessel walls (Figure 9B). This bioprinted microfiber scaffold was then seeded with rat-derived CMs (1 × 106 cells/mL) (Figure 9C). The CMs adhered and spread on the surface of the microfibers across the entire thickness of the scaffolds, and strongly expressed the contractile Actn1 protein and the intercellular conductive connexin-43, as demonstrated by immunostaining analysis. In addition, the CMs-populated constructs started beating spontaneously and synchronously after 48 hours of culture. In order to construct the endothelialized-heart-on-a-chip device and evaluate cardiovascular drug toxicity, a microfluidic perfusion bioreactor was generated. The endothelialized microtissue was tested with the common anti-cancer drug doxorubicin, which demonstrated dose-dependent effects towards both CMs and ECs. In particular, the beating rate of the CMs decreased to 70.5% and 1.62%, and the levels of von Willebrand factor (vWF) secreted by the ECs were reduced to 76.0% and 35.3% 6 days after exposure to 10 μM and 100 μM doxorubicin, respectively (Figure 9D,E). In the same study, the authors adopted a similar fabrication method and drug toxicity test on endothelialized human iPSCs-derived CMs microtissue, with results that were comparable to those observed in the rat-derived microtissue, thus suggesting potential translational for personalized drug screening.

**Figure 9.** Example of 3D bioprinted heart tissue patches used for drug screening. (**A**) Schematic representation of the extrusion-based 3D bioprinting system used to generate microfibrous alginate/gelatin methacrylate (GelMA) scaffolds encapsulating endothelial cells (ECs), that (**B**) in approximatively 2 weeks form a vascular bed through migration of cells to the peripheries of the microfibers. (**C**) Cardiomyocytes (CMs) are then seeded into the interstitial space of the endothelialized scaffold. The doxorubicin dose-concentration response is evaluated as (**D**) relative beating rate of CMs and (**E**) relative expression levels of von Willebrand factor (vWF) in ECs. Reprinted from Zhang et al. [116]. Copyright © 2020 Elsevier Ltd.

More recently, Lind and coworkers designed cardiac microphysiological devices via multi-material 3D bioprinting by sequentially using six functional bioinks based on highly conductance, piezoresistive, and biocompatible soft materials [117]. After printing, the devices were seeded with human iPSCs-CMs (220 K/cm2), which self-assembled into laminar tissues mimicking the structure of the native heart.  In particular, the L-type calcium channel blocker verapamil and the β-adrenergic agonist isoproterenol were investigated. The engineered microtissue displayed inotropic responses to verapamil and isoproterenol, comparable to data obtained from engineered 3D neonatal rat ventricular myocardial tissues and isolated postnatal whole rat hearts, therefore demonstrating the potential of this model as a drug screening platform.

In another study, Wang and colleagues 3D bioprinted a functional cardiac tissue mimicking the structural, physiological, and functional features of native myocardium [118]. The authors used a fibrin-based composite hydrogel as bioink to print primary CMs (10 × 106 cells/mL) isolated from infant rat hearts. Bioprinted cardiac tissue constructs exhibited spontaneous synchronous contraction in culture, and positivity to Actn1 and connexin 43, indicating the generation of uniformly aligned and electromechanically coupled cardiac cells. The authors then evaluated physiologic responses of these bioprinted cardiac tissues to known cardiac drugs, the androgen agonist epinephrine and the androgen antagonist carbachol after 3 weeks of culture. Calcium imaging analysis was used to quantify spontaneous beating of bioprinted cardiac tissues, revealing that epinephrine increased the beating frequency from 80 to 110 beats per minute (BPM), whereas carbachol decreased the beating frequency to 40 BPM. Interestingly, the authors demonstrated the reversible effects of these drugs when these were removed from the bioprinted cardiac tissues, thus indicating their effectiveness in testing the physiological response of cardiac drugs.

As mentioned above, 3D bioprinting could be useful also for the development of drug delivery strategies [94]. Some current applications of 3D printing in drug delivery systems include implant

surfaces (i.e., orthopedic implants) modified with drug-eluting solutions [119,120], medical devices (i.e., stent or catheter) containing and eluting drugs [121], and 3D printed delivery devices providing personalized drug release profiles [122]. 3D bioprinting applications for drug screening discussed in this paragraph are summarized in Table 3.

**Table 3.** Applications of 3D bioprinting for drug screening.

1 gelatin methacrylated; 2 endothelial cells; 3 cardiomyocytes; smooth muscle cells; 4 von Willebrand factor; 5 thermoplastic polyurethane; 6 carbon black nanoparticles; 7 silver particle-filled, polyamide; 8 polydimethylsiloxane;

9 cardiomyocytes derived from human induced pluripotent stem cells; 10 hyaluronic acid.

#### **5. 3D Printing for Testing and Realizing New Heart Devices**

Another important application of 3D printing is the development and testing of medical devices. With regard to the cardiovascular field, one of the first studies was the one of Kalejs and von Segesser, who created an aortic root model made of common house-hold silicone, then started to use this model in in-vitro valved stents testing, integrating the aortic root in an artificial circulatory loop [123]. Biglino and coworkers, instead, imaged a tract of descending aorta of a 29-year-old volunteer 50 mm in length with MRI, then used the polyjet technique for printing models having different wall thickness (0.6, 0.7, 0.8, 1.0, and 1.5 mm) but constant internal diameter (15.5 mm) [124]. These models of descending aorta were then subjected to compliance tests through gradual increase and decrease of the internal volume in order to track pressure variations. Two critical cases of vascular anatomies were then selected for evaluating the practicability of the method, after the identification of a range of material's distensibility. The first case concerned an adult patient affected by severe pulmonary regurgitation and dilated right ventricular outflow tract (RVOT), whereas the second case was about a pediatric patient with hypoplastic left heart syndrome (HLHS) and aortic coarctation (2.7 mm narrowing). Good anatomical finishing was qualitatively obtained for both models, suggesting their usefulness for device implantation and testing (Figure 10A). Later, Mashari and colleagues acquired TEE images of a patient subjected to a percutaneous MitraClip® operation, which is a minimally invasive procedure to reduce the mitral regurgitation, for creating a 3D MV model [125]. Hemodynamic tests were then carried out on this 3D model by insertion in a pulse duplicator chamber loaded with a fluid mimicking the blood (Figure 10B). Paulsen and colleagues used a 3D printed left heart simulator to compare two different conduits for valve-spearing aortic root replacement [126]. The simulator was efficient to show the comparability of straight tubular and Valsalva grafts in terms of gross hemodynamic and coronary blood flow, however it revealed that the two conduits differ considerably in terms of biomechanics. 3D printing also resulted effective in realizing personalized occluders for the treatment

of CHD using new biodegradable materials. As an example, Sun and coworkers produced a 3D printed biodegradable occluder made of a copolimer composed by poly-L lactic acid, trimethylene carbonate and glycolide [127]. Such a 3D printed model was then tested both in vitro and in vivo in a rabbit model, demonstrating good results in terms of safety, reliability and biocompatibility.

**Figure 10.** Examples of 3D printed models for device testing. (**A**) 3D printed right ventricular outflow tract (RVOT) model used for physical insertion of a stent-graft for assessing patient's suitability for the device. Reprinted from Biglino et al. [124]. Copyright © 2020, Springer Nature. (**B**) Silicone 3D printed mitral valve (MV) incorporated into (**C**) a pulse-duplicator chamber filled with a blood mimicking fluid for hemodynamic testing. Reprinted from Mashari et al. [125]. Copyright © 2020 Elsevier Inc.

### **6. Regulatory Considerations and Commercialization of 3D Printed and 3D Bioprinted Products**

The 3D printing industry is a rapidly expanding field, and it has been estimated that the global market for 3D printed devices will reach around \$34.8 billion with a compound annual growth rate (CAGR) of 23.2% during the forecast period 2019–2024, while that of 3D bioprinting will be near \$1.647 million with a CAGR of 20.4% by the end of 2024 [128,129]. For this reason, it is necessary that regulatory agencies around the world will soon try to establish quality standards before devices manufactured with 3D printing technologies become part of common clinical practice.

Worldwide, the regulatory requirements for a given type of medicinal product depend strictly on its classification. In the USA, medicinal products are categorized as drugs, biologics, or medical devices [130]. Each type of product is regulated by a different center within the FDA: The center for drug evaluation and research (CDER), the center for biologics evaluation and research (CBER), or the center for devices and radiological health (CDRH), respectively. The FDA regulatory agency in the USA considers 3D printed devices in the same way to traditional medical devices, and therefore subject them to the same regulatory requirements and submission information [131]. The CDRH classifies medical devices into three classes, on the basis of the intended use of the device, the indications for use, and the risk level to patient or user (Figure 11) [131]. Medical devices of Class I have a minimal harm potential to the patient or user, require general controls without clinical trials and are exempt from the regulatory process, meaning there is no need for proof of safety or efficacy. Medical devices of Class II have a moderate risk to the patient or user, require both general and special controls, and most of them need also filing a premarket notification, known as 510 (k), for notifying the FDA the intent of marketing. A 510 (k) is obtained when the device proves to be safe, effective, and substantially equivalent to a device already legally marketed that is not subjected to premarket approval [131]. Finally, Class III includes those medical devices that support or sustain human life, are generally implanted, and thus require clinical trials or other evidences before the most rigorous premarket approval. If a Class III device presents only minor changes from an already approved device, named predicate device, it may not need the stringent premarket approval; on the contrary, all novel devices that do not have a predicate device are automatically classified as Class III devices [130,132].

**Figure 11.** Classification of medical devices in the USA and in the EU.

In the EU, products are categorized as medicinal products (drugs or biologics) or medical devices, and they have their own unique regulatory processes [133]. With establishment of the EU, approval processes for medical devices followed a path of harmonization; nevertheless, medical device regulation does not fall solely to any one agency. Indeed, national competent authorities (NCAs) are responsible to designate and audit notified bodies (NBs), which are independent commercial organizations that contract with device manufacturers to supply these certifications for a fee [134]. NBs assess and assure conformity with requirements of the relevant European commission (EU) directives. Once NBs demonstrate the device meets requirements for conformity, the NBs issue a conformité européenne (CE) mark, and the device can be marketed in any EU member state [135]. Differently from the USA, medical devices in the EU are classified into four classes: class I, class IIa, class IIb, and class III (Figure 11) [136]. Class I are low risk medical devices, and only require a self-declaration of conformity by manufacturers without the involvement of NBs. In contrast, and similarly to what happens in the USA, medical devices of Classes IIa, IIb, and III require clinical and/or nonclinical evidence to support their approval.

In December 2017, the FDA released a guidance document entitled "Technical Considerations for Additive Manufactured Medical Devices", with the aim to outline technical considerations for manufacturing 3D printed devices, and containing recommendations for testing and characterizing such devices [137]. As already discussed in a dedicated section of this review, the technical workflow for manufacturing 3D medical devices involve several steps (Figure 12). The aspects of 3D printing addressed in the guidance document focused on device design, materials control, printing and post-printing validation; examination of printing parameters; assessment of physical and mechanical characteristics of final devices; and biological and safety considerations of final devices in terms of cleaning, sterility, and biocompatibility [137]. It has to be remembered that 3D printed medical devices, like those traditionally manufactured, must meet quality system requirements across all the production process.

**Figure 12.** Technical workflow for manufacturing 3D printed medical devices.

Over the years, more than 80 3D printed medical devices have been approved by the FDA's center CDRH through 510(k) process [138]. Most of these devices are used in dental, orthopedic and cranio-maxillofacial fields (i.e., dental crowns, hearing aids, bone tether plates, skull plates, hip cups, spinal cages, facial implants, and screws), and are produced using powder bed fusion techniques (83%), stereolithography (12%), extrusion (3%), and jetting (2%) [138,139]. A postmarket analysis of the FDA's approved devices, conducted on the manufacturer and user facility device experience (MAUDE) database, evidenced that the principal reasons for product-related adverse events were improper size or incompatibility with other components of the device (46%), device fracture or shaving (45%), incorrect device size for the patient (5%), implant wear (2%) and incorrect device implanted (2%) [138]. To be fair, we have to say that many of these adverse events are common to medical devices manufactured with the traditional techniques.

As for 3D printed products containing biological components, no defined regulations currently exist, since these products cannot be simply classified as medical device, biologic, or drug, but can rather be considered both medical devices and biologics [140]. Indeed, combination products are products comprising two or more regulated components, that is drug-device, device-biologic, drug-biologic or drug-device-biologic [141]. A combination product is for example one in which living cells (biologics) are combined with a synthetic scaffold matrix (medical device) that provides physically support for the growth of new tissue [133]. The legislation applied to these products depends on their classification, which is determined by several factors, mainly by the way in which the finished product achieves its intended medical purpose and by its primary mode of action (PMOA) [133]. In the USA, the office of combination product (OPC) assigns combination products to the most appropriate FDA center [142]. If the PMOA of a cell-based medicinal product is provided by the biological cellular constituent, then the product is regulated as biologics by CBER in the USA, and as combined advanced-therapy medicinal products (ATMPs) in the EU [140,142]. On the other hand, if the therapeutic effect derives from the device component, the combination product is considered a Class III medical device in the EU. Regarding 3D bioprinted products, their classification mainly depends on whether these devices are

mass-produced or custom-made. In current practice, custom-made devices, which are manufactured in accordance with a specific prescription for a specific individual, are exempt from normal quality system requirements or conformity assessment requirements by most regulatory bodies in both in the USA and in the EU [143,144].

The technical workflow for 3D bioprinting medical device is similar to that seen for 3D printing, although additional steps are included in the manufacturing process, such as selection of a design approach, cell type, and biological material [138]. Consequently, additional technical considerations need to be taken into account respect to 3D printed medical devices. These include, for example, printing parameters (printing temperature, resolution, and speed) or material selection. Mechanical and physicochemical properties, biocompatibility, as well as vascularization and biological function of the finished product are other parameters to be evaluated. Although 3D bioprinting technologies are largely still in the research and development stage, urgent regulatory and manufacturing process considerations are required to meet the growing global interest and needs of such 3D printed products.

#### **7. Current Limitations, Future Perspectives, and Conclusions**

3D printing attracted remarkable attention of the scientific community due to its high versatility, and in recent years the technology has considerably expanded also to the cardiovascular medicine. 3D printing allows the complex cardiac anatomy to be accurately replicated using materials resembling human heart tissues. For this reason, 3D printed heart models could serve as an excellent tool in facilitating medical education, pre-operative planning, and communication between doctor and patients or their family. Nevertheless, cardiac surgeons and cardiologists agree with the fact that these 3D printed heart models should only be used to complement the current diagnostic tools. This is particularly true when creating a model for cardiovascular pre-surgical planning, where an error made during segmentation of an image data set could have devastating consequences. In addition, there is still no statistical data currently available to demonstrate the real clinical value of these 3D printed models. Another obstacle that limits diffusion and routine application of 3D printing in clinical practice is related to its high cost. Further investigations are needed to analyze the cost-benefit of 3D printing for creating anatomical models. Interestingly, a recent work demonstrated that 3D printed heart models produced with low cost materials (A\$50) show efficiency and precision similar to models created with high cost materials (A\$300) [6]. Another limitation to overcome in a near future is the availability of the 3D printing technology in situ; most research hospitals, indeed, have access to facilities through academic collaborators. Building a 3D printing laboratory would require planning in hardware, software and dedicated staff [145].

Currently, the most advanced application of 3D printing is 3D bioprinting, which has the great potential to engineer highly organized functional tissues and/or organs with complex geometries and tailored components for widespread applications, including transplantation, drug discovery and development, and disease modelling. The most ambitious goal of the 3D bioprinting technology, however, is the realization of customized devices for clinical applications. In the cardiovascular field, fabrication of 3D bioprinted functional tissues greatly depends on the availability of biomimetic materials recapitulating native heart ECM and electrical conductivity properties. Although several specialized 3D bioprinters have been developed to fabricate various types of 3D heart tissues, such as myocardium and heart valves, bioprinting technology still faces many technical challenges. Some of the main efforts focus on obtaining high resolution distribution of cells, while minimizing their loss and maximizing cell–cell interactions. The ideal bioprinter should have resolution in the submicron range to allow bioprinting of a matrix with an orientation able to direct the alignment of cardiovascular cells [146]. Achieving the proper cellular composition is another issue in cardiovascular 3D bioprinting [62]. As emerged in different studies discussed in the manuscript, alteration of the composition of nonmyocyte cells, such as FBs and ECs, strongly influences the function, vascularization and vitality of the 3D bioprinted cardiac tissue.

Another crucial aspect to consider in 3D bioprinting relates the development of an ideal cardiac bioink, possessing appropriate stiffness and cell microenvironment, and controllable degradation rate. At the time of this writing, hydrogels are among the most used bioprintable materials for cardiovascular applications, as they provide good support for cells. Nevertheless, hydrogels do not contain specific ECM proteins for certain cell types, thus not fully reflecting the native environment of the heart. In addition, although hydrogels encapsulate and confine cells, they limit cell–cell interactions, and do not allow to obtain the same high cell density as native tissues. Another important shortcoming is the instability of hydrogels during the bioprinting process: Increasing hydrogel concentration improves its mechanical properties, but simultaneously limits biological activities [147]. Use of decellularized heart ECM as bioink material represents an alternative solution in 3D bioprinting, although further optimization is still needed. Besides the fact that decellularization is a tedious process, the native ECM loses its mechanical integrity and some of the biochemical properties when homogenized, and toxic residues can remain after the decellularization process. In addition, cells seeded on the decellularized ECM produce MMPs that rapid degrade the bioink [147]. Despite the advancements in scaffold-free techniques, limitations still exist also in the use of tissue spheroids for 3D bioprinting. Some are technical difficulties related to the printing process: The nozzle used to load tissue spheroids should be large enough to hold the spheroids inside and allow extrusion without clogging, since these structures do not have a homogeneous size and can be easily deformed or broken. Furthermore, necrosis can occur in the core of tissue spheroids, but this can be overcome by proper vascularization. Considering that each type of bioink has its own advantages and disadvantages over others, a future winning strategy could involve the combination of bioinks composed of multiple and complementary biomaterials. This in turn would require the development of hybrid systems integrating different but compatible bioprinting technologies. At present, the majority of the 3D bioprinting techniques require post-processing of the printed product through crosslinking. In most cases, this step complicates the workflow and leads to a potential deterioration in the quality of the final product [148]. For these reasons, there is an urgent need to improve material design or the printing technology itself for preventing the post-printing step.

As discussed in the manuscript, another challenge in 3D bioprinting is the achievement of early vascularization of tissue constructs, which is fundamental for exchange of materials and oxygen supply, and consequently for improving vascular integration with the host cardiovascular system. Supply of oxygen to 3D printed tissue constructs could be addressed by generation of oxygen biomaterials that, together with conductive elastomers, could be the future of 3D bioprinted cardiac tissues. In addition, the development of 3D printed bioreactors that can integrate electrical and mechanical stimulation could represent another potential area for generating functional heart tissues [149].Advancements in 3D bioprinting technologies will also be dependent on the capability to accelerate large-scale tissue constructs production in a rapid manner. At the moment, only extrusion-based bioprinting has the potential to produce volumetric human-scale tissues but this method lacks speed and resolution. A final challenge in this field is the conduction of long-term studies for evaluating cell viability after printing, cell phenotypic changes and their biological functionality, as many works published so far are short-term studies. Long-term studies could better assess the biological safety and fidelity of constructs before clinical trials. In this context, immunogenicity of the 3D bioprinted construct is an issue that has to be addressed as well.

A future area of research is undoubtedly 4D printing, which essentially combines a 3D printing technique with smart materials that can respond to external stimuli, thereby reshaping or changing their function over time [150]. To do this, 4D printing employs hydrogels responsive to, i.e., temperature, pH, light, electric or magnetic field, or shape-memory polymers [151]. The most intriguing aspect of 4D bioprinting is the possibility to create sophisticated high resolution dynamic and animated structures, otherwise inaccessible with the current static 3D bioprinting techniques. Nonetheless, an aspect that should be carefully considered in 4D printing is the presence of a stimulus that may have a negative effect on living cells. At the moment, 4D printing of cardiac tissue is still in its early stages, but we believe that it can give the opportunity to generate dynamic structures better mimicking the types of tissue structures in vivo. It is hoped that in a near future these important major challenges and regulatory issues could be addressed to enable the translation of the technology to personalized therapeutic and pharmaceutical applications.

**Author Contributions:** C.G., writing—original draft preparation and visualization; L.F., C.L., B.Z., J.C.C. and D.M. writing—review and editing. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Acknowledgments:** The authors would like to acknowledge networking support by the COST Action CA16122—Bioneca. D.M. work is co-financed by the Scientific Centre of Excellence for Basic, Clinical and Translational Neuroscience (project "Experimental and clinical research of hypoxic-ischemic damage in perinatal and adult brain"; GA KK<IP_ADDRESS>.0007 funded by the European Union through the European Regional Development Fund).

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

#### **References**

© 2020 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 (http://creativecommons.org/licenses/by/4.0/).


**Author details**

Wael I. Ibraheem\* and Reghunathan S. Preethanath College of Dentistry, Jazan University, Jazan, Kingdom of Saudi Arabia

\*Address all correspondence to<EMAIL_ADDRESS><EMAIL_ADDRESS>
© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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