Genetic diversity, linkage disequilibrium, and association mapping analyses of Gossypium barbadense L. germplasm

Genome-wide association study of fiber quality traits in US upland cotton (Gossypium hirsutum L.)

KEY MESSAGE

A GWAS in an elite diversity panel, evaluated across 10 environments, identified genomic regions regulating six fiber quality traits, facilitating genomics-assisted breeding and gene discovery in upland cotton. In this study, an elite diversity panel of 348 upland cotton accessions was evaluated in 10 environments across the US Cotton Belt and genotyped with the cottonSNP63K array, for a genome-wide association study of six fiber quality traits. All fiber quality traits, upper half mean length (UHML: mm), fiber strength (FS: g tex-1), fiber uniformity (FU: %), fiber elongation (FE: %), micronaire (MIC) and short fiber content (SFC: %), showed high broad-sense heritability (> 60%). All traits except FE showed high genomic heritability. UHML, FS and FU were all positively correlated with each other and negatively correlated with FE, MIC and SFC. GWAS of these six traits identified 380 significant marker-trait associations (MTAs) including 143 MTAs on 30 genomic regions. These 30 genomic regions included MTAs identified in at least three environments, and 23 of them were novel associations. Phenotypic variation explained for the MTAs in these 30 genomic regions ranged from 6.68 to 11.42%. Most of the fiber quality-associated genomic regions were mapped in the D-subgenome. Further, this study confirmed the pleiotropic region on chromosome D11 (UHML, FS and FU) and identified novel co-localized regions on D04 (FU, SFC), D05 (UHML, FU, and D06 UHML, FU). Marker haplotype analysis identified superior combinations of fiber quality-associated genomic regions with high trait values (UHML = 32.34 mm; FS = 32.73 g tex-1; FE = 6.75%). Genomic analyses of traits, haplotype combinations and candidate gene information described in the current study could help leverage genetic diversity for targeted genetic improvement and gene discovery for fiber quality traits in cotton.

Genome-wide association study of fiber yield-related traits uncovers the novel genomic regions and candidate genes in Indian upland cotton (Gossypium hirsutum L.)

Upland cotton (Gossypium hirsutum L.) is a major fiber crop that is cultivated worldwide and has significant economic importance. India harbors the largest area for cotton cultivation, but its fiber yield is still compromised and ranks 22nd in terms of productivity. Genetic improvement of cotton fiber yield traits is one of the major goals of cotton breeding, but the understanding of the genetic architecture underlying cotton fiber yield traits remains limited and unclear. To better decipher the genetic variation associated with fiber yield traits, we conducted a comprehensive genome-wide association mapping study using 117 Indian cotton germplasm for six yield-related traits. To accomplish this, we generated 2,41,086 high-quality single nucleotide polymorphism (SNP) markers using genotyping-by-sequencing (GBS) methods. Population structure, PCA, kinship, and phylogenetic analyses divided the germplasm into two sub-populations, showing weak relatedness among the germplasms. Through association analysis, 205 SNPs and 134 QTLs were identified to be significantly associated with the six fiber yield traits. In total, 39 novel QTLs were identified in the current study, whereas 95 QTLs overlapped with existing public domain data in a comparative analysis. Eight QTLs, qGhBN_SCY_D6-1, qGhBN_SCY_D6-2, qGhBN_SCY_D6-3, qGhSI_LI_A5, qGhLI_SI_A13, qGhLI_SI_D9, qGhBW_SCY_A10, and qGhLP_BN_A8 were identified. Gene annotation of these fiber yield QTLs revealed 2,509 unique genes. These genes were predominantly enriched for different biological processes, such as plant cell wall synthesis, nutrient metabolism, and vegetative growth development in the gene ontology (GO) enrichment study. Furthermore, gene expression analysis using RNAseq data from 12 diverse cotton tissues identified 40 candidate genes (23 stable and 17 novel genes) to be transcriptionally active in different stages of fiber, ovule, and seed development. These findings have revealed a rich tapestry of genetic elements, including SNPs, QTLs, and candidate genes, and may have a high potential for improving fiber yield in future breeding programs for Indian cotton.

Genome-wide association mapping for wheat morphometric seed traits in Iranian landraces and cultivars under rain-fed and well-watered conditions

Seed traits in bread wheat are valuable to breeders and farmers, thus it is important exploring putative QTLs responsible for key traits to be used in breeding programs. GWAS was carried out using 298 bread wheat landraces and cultivars from Iran to uncover the genetic basis of seed characteristics in both rain-fed and well-watered environments. The analyses of linkage disequilibrium (LD) between marker pairs showed that the largest number of significant LDs in landraces (427,017) and cultivars (370,359) was recorded in genome B, and the strongest LD was identified on chromosome 4A (0.318). LD decay was higher in the B and A genomes, compared to the D genome. Mapping by using mrMLM (LOD > 3) and MLM (0.05/m, Bonferroni) led to 246 and 67 marker-trait associations (MTAs) under rain-fed, as well as 257 and 74 MTAs under well-watered conditions, respectively. The study found that 3VmrMLM correctly detected all types of loci and estimated their effects in an unbiased manner, with high power and accuracy and a low false positive rate, which led to the identification of 140 MTAs (LOD > 3) in all environments. Gene ontology revealed that 10 and 10 MTAs were found in protein-coding regions for rain-fed and well-watered conditions, respectively. The findings suggest that landraces studied in Iranian bread wheat germplasm possess valuable alleles, which are responsive to water-limited conditions. MTAs uncovered in this study can be exploited in the genome-mediated development of novel wheat cultivars.

Genomic and GWAS analyses demonstrate phylogenomic relationships of Gossypium barbadense in China and selection for fibre length, lint percentage and Fusarium wilt resistance

Sea Island cotton (Gossypium barbadense) is the source of the world's finest fibre quality cotton, yet relatively little is understood about genetic variations among diverse germplasms, genes underlying important traits and the effects of pedigree selection. Here, we resequenced 336 G. barbadense accessions and identified 16 million SNPs. Phylogenetic and population structure analyses revealed two major gene pools and a third admixed subgroup derived from geographical dissemination and interbreeding. We conducted a genome-wide association study (GWAS) of 15 traits including fibre quality, yield, disease resistance, maturity and plant architecture. The highest number of associated loci was for fibre quality, followed by disease resistance and yield. Using gene expression analyses and VIGS transgenic experiments, we confirmed the roles of five candidate genes regulating four key traits, that is disease resistance, fibre length, fibre strength and lint percentage. Geographical and temporal considerations demonstrated selection for the superior fibre quality (fibre length and fibre strength), and high lint percentage in improving G. barbadense in China. Pedigree selection breeding increased Fusarium wilt disease resistance and separately improved fibre quality and yield. Our work provides a foundation for understanding genomic variation and selective breeding of Sea Island cotton.

A Calmodulin-Like Gene (GbCML7) for Fiber Strength and Yield Improvement Identified by Resequencing Core Accessions of a Pedigree in Gossypium barbadense

Sea Island cotton (Gossypium barbadense) is world-renowned for its superior natural fiber. Although fiber strength is one of the most important fiber quality traits, genes contributing to fiber strength are poorly understood. Production of sea island cotton also is inextricably linked to improving its relatively low yield, thus enhancing the importance of joint improvement of both fiber quality and yield. We used genomic variation to uncover the genetic evidence of trait improvement resulting from pedigree breeding of Sea Island cotton. This pedigree was aimed at improving fiber strength and yielded an elite cultivar, XH35. Using a combination of genome-wide association study (GWAS) and selection screens, we detected 82 putative fiber-strength-related genes. Expression analysis confirmed a calmodulin-like gene, GbCML7, which enhanced fiber strength in a specific haplotype. This gene is a major-effect gene, which interacts with a minor-effect gene, GbTUA3, facilitating the enhancement of fiber strength in a synergistic fashion. Moreover, GbCML7 participates in the cooperative improvement of fiber strength, fiber length, and fiber uniformity, though a slight compromise exists between the first two of these traits and the latter. Importantly, GbCML7 is shown to boost yield in some backgrounds by increasing multiple yield components to varying degrees, especially boll number. Our work provides valuable genomic evidence and a key genetic factor for the joint improvement of fiber quality and yield in Sea Island cotton.

Identification of Candidate Cotton Genes Associated With Fiber Length Through Quantitative Trait Loci Mapping and RNA-Sequencing Using a Chromosome Segment Substitution Line

Fiber length is an important determinant of fiber quality, and it is a quantitative multi-genic trait. Identifying genes associated with fiber length is of great importance for efforts to improve fiber quality in the context of cotton breeding. Integrating transcriptomic information and details regarding candidate gene regions can aid in candidate gene identification. In the present study, the CCRI45 line and a chromosome segment substitution line (CSSL) with a significantly higher fiber length (MBI7747) were utilized to establish F₂ and F_2:3 populations. Using a high-density genetic map published previously, six quantitative trait loci (QTLs) associated with fiber length and two QTLs associated with fiber strength were identified on four chromosomes. Within these QTLs, qFL-A07-1, qFL-A12-2, qFL-A12-5, and qFL-D02-1 were identified in two or three environments and confirmed by a meta-analysis. By integrating transcriptomic data from the two parental lines and through qPCR analyses, four genes associated with these QTLs including Cellulose synthase-like protein D3 (CSLD3, GH_A12G2259 for qFL-A12-2), expansin-A1 (EXPA1, GH_A12G1972 for qFL-A12-5), plasmodesmata callose-binding protein 3 (PDCB3, GH_A12G2014 for qFL-A12-5), and Polygalacturonase (At1g48100, GH_D02G0616 for qFL-D02-1) were identified as promising candidate genes associated with fiber length. Overall, these results offer a robust foundation for further studies regarding the molecular basis for fiber length and for efforts to improve cotton fiber quality.

Genetic diversity and population structure analysis for morphological traits in upland cotton (Gossypium hirsutum L.)

A total of 96 different genotypes of upland cotton (Gossypium hirsutum) were selected from the breeding material and germplasm available at CCS HAU, India, to find the novel marker-trait associations for morphological traits used for registration of variety in upland cotton. Twenty-three morphological traits of the selected genotypes were recorded in field trials conducted in two replication of randomized block design during Kharif 2018 and 2019. A total of 11 traits showed sufficient variations in the screened germplasm and the same were further used for association mapping. A total of 168 SSRs were used for genotyping, of which 97 SSRs showed polymorphism amplifying 293 different alleles with an average of 3.02 alleles per SSR. Clustering, principal component analysis, and population structure analysis advocated that the current germplasm panel has enough diversity to be considered for association mapping. A total of 20 significant marker-trait associations were identified by the mixed linear model (MLM) and compressed mixed linear model (CMLM), of which 15 were common to both models, hence considered as promising associations. To the best of our knowledge, it is a first attempt to identify the linked markers in relation to morphological traits for the cotton crop. Results of the present study will be highly useful in speeding up variety registration programmes of upland cotton complementing to Distinctiveness, Uniformity, and Stability (DUS) testing.

Identification of Novel Marker-Trait Associations for Lint Yield Contributing Traits in Upland Cotton (Gossypium hirsutum L.) Using SSRs

Improving the yield of lint is the main objective for most of the cotton crop improvement programs throughout the world as it meets the demand of fiber for textile industries. In the current study, 96 genotypes of Gossypium hirsutum were used to find novel simple sequence repeat marker-based associations for lint yield contributing traits by linkage disequilibrium. Extensive phenotyping of 96 genotypes for various agronomic traits was done for two consecutive years (2018 and 2019) in early, normal, and late sown environments. Out of 168 SSR markers screened over the 96 genotypes, a total of 97 polymorphic markers containing 293 alleles were used for analysis. Three different models, i.e., mixed linear model (MLM), compressed mixed linear model (CMLM), and multiple locus mixed linear model (MLMM), were used to detect the significant marker-trait associations for six different environments separately. A total of 38 significant marker-trait associations that were common to at least two environments were considered as promising associations and detailed annotation of the significant markers has been carried out. Twenty-two marker-trait associations were found to be novel in the current study. These results will be very useful for crop improvement programs using marker-assisted cotton breeding.

Detection of candidate genes and development of KASP markers for Verticillium wilt resistance by combining genome-wide association study, QTL-seq and transcriptome sequencing in cotton

Combining GWAS, QTL-seq and transcriptome sequencing detected basal defense-related genes showing gDNA sequence variation and expression difference in diverse cotton lines, which might be the molecular mechanisms of VW resistance in G. hirsutum. Verticillium wilt (VW), which is caused by the soil-borne fungus Verticillium dahliae, is a major disease in cotton (Gossypim hirsutum) worldwide. To facilitate the understanding of the genetic basis for VW resistance in cotton, a genome-wide association study (GWAS), QTL-seq and transcriptome sequencing were performed. The GWAS of VW resistance in a panel of 120 core elite cotton accessions using the Cotton 63K Illumina Infinium SNP array identified 5 QTL from 18 significant SNPs meeting the 5% false discovery rate threshold on 5 chromosomes. All QTL identified through GWAS were found to be overlapped with previously reported QTL. By combining GWAS, QTL-seq and transcriptome sequencing, we identified eight candidate genes showing both gDNA sequence variation and expression difference between resistant and susceptible lines, most related to transcription factors (TFs), flavonoid biosynthesis and those involving in the plant basal defense and broad-spectrum disease resistance. Ten KASP markers were successfully validated in diverse cotton lines and could be deployed in marker-assisted breeding to enhance VW resistance. These results supported our inference that the gDNA sequence variation or expression difference of those genes involving in the basal defense in diverse cotton lines might be the molecular mechanisms of VW resistance in G. hirsutum.

Examining two sets of introgression lines across multiple environments reveals background-independent and stably expressed quantitative trait loci of fiber quality in cotton

Background-independent (BI) and stably expressed (SE) quantitative trait loci (QTLs) were identified using two sets of introgression lines across multiple environments. Genetic background more greatly affected fiber quality traits than environmental factors. Sixty-one SE-QTLs, including two BI-QTLs, were novel and 48 SE-QTLs, including seven BI-QTLs, were previously reported. Cotton fiber quality traits are controlled by QTLs and are susceptible to environmental influence. Fiber quality improvement is an essential goal in cotton breeding but is hindered by limited knowledge of the genetic basis of fiber quality traits. In this study, two sets of introgression lines of Gossypium hirsutum × G. barbadense were used to dissect the QTL stability of three fiber quality traits (fiber length, strength and micronaire) across environments using 551 simple sequence repeat markers selected from our high-density genetic map. A total of 76 and 120 QTLs were detected in the CCRI36 and CCRI45 backgrounds, respectively. Nine BI-QTLs were found, and 78 (41.71%) of the detected QTLs were reported previously. Thirty-nine and 79 QTLs were SE-QTLs in at least two environments in the CCRI36 and CCRI45 backgrounds, respectively. Forty-eight SE-QTLs, including seven BI-QTLs, were confirmed in previous reports, and 61 SE-QTLs, including two BI-QTLs, were considered novel. These results indicate that genetic background more strongly impacts on fiber quality traits than environmental factors. Twenty-three clusters with BI- and/or SE-QTLs were identified, 19 of which harbored favorable alleles from G. barbadense for two or three fiber quality traits. This study is the first report using two sets of introgression lines to identify fiber quality QTLs across environments in cotton, providing insights into the effect of genetic backgrounds and environments on the QTL expression of fiber quality and important information for the genetic basis underlying fiber quality traits toward QTL cloning and molecular breeding.

Genome-wide association study of agronomic traits in bread wheat reveals novel putative alleles for future breeding programs

BACKGROUND

Identification of loci for agronomic traits and characterization of their genetic architecture are crucial in marker-assisted selection (MAS). Genome-wide association studies (GWAS) have increasingly been used as potent tools in identifying marker-trait associations (MTAs). The introduction of new adaptive alleles in the diverse genetic backgrounds may help to improve grain yield of old or newly developed varieties of wheat to balance supply and demand throughout the world. Landraces collected from different climate zones can be an invaluable resource for such adaptive alleles.

RESULTS

GWAS was performed using a collection of 298 Iranian bread wheat varieties and landraces to explore the genetic basis of agronomic traits during 2016-2018 cropping seasons under normal (well-watered) and stressed (rain-fed) conditions. A high-quality genotyping by sequencing (GBS) dataset was obtained using either all original single nucleotide polymorphism (SNP, 10938 SNPs) or with additional imputation (46,862 SNPs) based on W7984 reference genome. The results confirm that the B genome carries the highest number of significant marker pairs in both varieties (49,880, 27.37%) and landraces (55,086, 28.99%). The strongest linkage disequilibrium (LD) between pairs of markers was observed on chromosome 2D (0.296). LD decay was lower in the D genome, compared to the A and B genomes. Association mapping under two tested environments yielded a total of 313 and 394 significant (-log10 P >3) MTAs for the original and imputed SNP data sets, respectively. Gene ontology results showed that 27 and 27.5% of MTAs of SNPs in the original set were located in protein-coding regions for well-watered and rain-fed conditions, respectively. While, for the imputed data set 22.6 and 16.6% of MTAs represented in protein-coding genes for the well-watered and rain-fed conditions, respectively.

CONCLUSIONS

Our finding suggests that Iranian bread wheat landraces harbor valuable alleles that are adaptive under drought stress conditions. MTAs located within coding genes can be utilized in genome-based breeding of new wheat varieties. Although imputation of missing data increased the number of MTAs, the fraction of these MTAs located in coding genes were decreased across the different sub-genomes.