Genome-wide association analysis reveals quantitative trait loci and candidate genes involved in yield components under multiple field environments in cotton (Gossypium hirsutum)

Quantitative genomics-enabled selection for simultaneous improvement of lint yield and seed traits in cotton (Gossypium hirsutum L.)

KEY MESSAGE

A Bayesian linkage disequilibrium-based multiple-locus mixed model identified QTLs for fibre, seed and oil traits and predicted breeding worthiness of test lines, enabling their simultaneous improvement in cotton. Improving cotton seed and oil yields has become increasingly important while continuing to breed for higher lint yield. In this study, a novel Bayesian linkage disequilibrium-based multiple-locus mixed model was developed for QTL identification and genomic prediction (GP). A multi-parent population consisting of 256 recombinant inbred lines, derived from four elite cultivars with distinct combinations of traits, was used in the analysis of QTLs for lint percentage, seed index, lint index and seed oil content and their interrelations. All four traits were moderately heritable and correlated but with no large influence of genotype × environment interactions across multiple seasons. Seven to ten major QTLs were identified for each trait with many being adjacent or overlapping for different trait pairs. A fivefold cross-validation of the model indicated prediction accuracies of 0.46-0.62. GP results based on any two-season phenotypes were strongly correlated with phenotypic means of a pooled analysis of three-season experiments (r = 0.83-0.92). When used for selection of improvement in lint, seed and oil yields, GP captured 40-100% of individuals with comparable lint yields of those selected based on the three-season phenotypic results. Thus, this quantitative genomics-enabled approach can not only decipher the genomic variation underlying lint, seed and seed oil traits and their interrelations, but can provide predictions for their simultaneous improvement. We discuss future breeding strategies in cotton that will enhance the entire value of the crop, not just its fibre.

Dissecting the major genetic components underlying cotton lint development

Numerous genetic loci and several functionally characterized genes have been linked to determination of lint percentage (lint%), one of the most important cotton yield components, but we still know little about the major genetic components underlying lint%. Here, we first linked the genetic loci containing MYB25-like_At and HD1_At to the fiberless seed trait of 'SL1-7-1' and found that MYB25-like_At and HD1_At were very lowly expressed in 'SL1-7-1' ovules during fiber initiation. We then dissected the genetic components involved in determination of lint% using segregating populations derived from crosses of fuzzless mutants and intermediate segregants with different lint%, which not only confirmed the HD1_At locus but identified the HD1_Dt locus as being the major genetic components contributing to fiber initiation and lint%. The segregating populations also allowed us to evaluate the relative contributions of MYB25-like_At, MYB25-like_Dt, HD1_At, and HD1_Dt to lint%. Haplotype analysis of an Upland cotton (Gossypium hirsutum) population with 723 accessions (including 81 fuzzless seed accessions) showed that lint% of the accessions with the LP allele (higher lint%) at MYB25-like_At, MYB25-like_Dt, or HD1_At was significantly higher than that with the lp allele (lower lint%). The lint% of the Upland cotton accessions with 3 or 4 LP alleles at MYB25-like and HD1 was significantly higher than that with 2 LP alleles. The results prompted us to propose a strategy for breeding high-yielding cotton varieties, i.e. pyramiding the LP alleles of MYB25-like and HD1 with new lint% LP alleles without negative impact on seed size and fiber quality.

Genome-wide association study for boll weight in Gossypium hirsutum races

High yield has always been an essential target in almost all of the cotton breeding programs. Boll weight (BW) is a key component of cotton yield. Numerous linkage mapping and genome-wide association studies (GWAS) have been performed to understand the genetic mechanism of BW, but information on the markers/genes controlling BW remains limited. In this study, we conducted a GWAS for BW using 51,268 high-quality single-nucleotide polymorphisms (SNPs) and 189 Gossypium hirsutum accessions across five different environments. A total of 55 SNPs significantly associated with BW were detected, of which 29 and 26 were distributed in the A and D subgenomes, respectively. Five SNPs were simultaneously detected in two environments. For TM5655, TM8662, TM36371, and TM50258, the BW grouped by alleles of each SNP was significantly different. The ± 550 kb regions around these four key SNPs contained 262 genes. Of them, Gh_A02G1473, Gh_A10G1765, and Gh_A02G1442 were expressed highly at 0 to 1 days post-anthesis (dpa), - 3 to 0 dpa, and - 3 to 0 dpa in ovule of TM-1, respectively. They were presumed as the candidate genes for fiber cell differentiation, initiation, or elongation based on gene annotation of their homologs. Overall, these results supplemented valuable information for dissecting the genetic architecture of BW and might help to improve cotton yield through molecular marker-assisted selection breeding and molecular design breeding.

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.

Lint percentage and boll weight QTLs in three excellent upland cotton (Gossypium hirsutum): ZR014121, CCRI60, and EZ60

BACKGROUND

Upland cotton (Gossypium hirsutum L.) is the most economically important species in the cotton genus (Gossypium spp.). Enhancing the cotton yield is a major goal in cotton breeding programs. Lint percentage (LP) and boll weight (BW) are the two most important components of cotton lint yield. The identification of stable and effective quantitative trait loci (QTLs) will aid the molecular breeding of cotton cultivars with high yield.

RESULTS

Genotyping by target sequencing (GBTS) and genome-wide association study (GWAS) with 3VmrMLM were used to identify LP and BW related QTLs from two recombinant inbred line (RIL) populations derived from high lint yield and fiber quality lines (ZR014121, CCRI60 and EZ60). The average call rate of a single locus was 94.35%, and the average call rate of an individual was 92.10% in GBTS. A total of 100 QTLs were identified; 22 of them were overlapping with the reported QTLs, and 78 were novel QTLs. Of the 100 QTLs, 51 QTLs were for LP, and they explained 0.29-9.96% of the phenotypic variation; 49 QTLs were for BW, and they explained 0.41-6.31% of the phenotypic variation. One QTL (qBW-E-A10-1, qBW-C-A10-1) was identified in both populations. Six key QTLs were identified in multiple-environments; three were for LP, and three were for BW. A total of 108 candidate genes were identified in the regions of the six key QTLs. Several candidate genes were positively related to the developments of LP and BW, such as genes involved in gene transcription, protein synthesis, calcium signaling, carbon metabolism, and biosynthesis of secondary metabolites. Seven major candidate genes were predicted to form a co-expression network. Six significantly highly expressed candidate genes of the six QTLs after anthesis were the key genes regulating LP and BW and affecting cotton yield formation.

CONCLUSIONS

A total of 100 stable QTLs for LP and BW in upland cotton were identified in this study; these QTLs could be used in cotton molecular breeding programs. Putative candidate genes of the six key QTLs were identified; this result provided clues for future studies on the mechanisms of LP and BW developments.

Status and prospects of genome-wide association studies in cotton

Over the last two decades, the use of high-density SNP arrays and DNA sequencing have allowed scientists to uncover the majority of the genotypic space for various crops, including cotton. Genome-wide association study (GWAS) links the dots between a phenotype and its underlying genetics across the genomes of populations. It was first developed and applied in the field of human disease genetics. Many areas of crop research have incorporated GWAS in plants and considerable literature has been published in the recent decade. Here we will provide a comprehensive review of GWAS studies in cotton crop, which includes case studies on biotic resistance, abiotic tolerance, fiber yield and quality traits, current status, prospects, bottlenecks of GWAS and finally, thought-provoking question. This review will serve as a catalog of GWAS in cotton and suggest new frontiers of the cotton crop to be studied with this important tool.

Genome-wide association study identifies candidate genes and favorable haplotypes for seed yield in Brassica napus

Oilseed rape (Brassica napus L.) is one of the most essential oil crops. Genetic improvement of seed yield (SY) is a major aim of B. napus breeding. Several studies have been reported on the genetic mechanisms of SY of B. napus. Here, a genome-wide association study (GWAS) of SY was conducted using a panel of 403 natural accessions of B. napus, with more than five million high-quality single-nucleotide polymorphisms (SNPs). A total of 1773 significant SNPs were detected associated with SY, and 783 significant SNPs were co-located with previously reported QTLs. The lead SNPs chrA01__8920351 and chrA02__4555979 were jointly detected in Trial 2_2 and Trial 2_mean value, and in Trial 1_2 and Trial 1_mean value, respectively. Subsequently, two candidate genes of BnaA01g17200D and BnaA02g08680D were identified through combining transcriptome, candidate gene association analysis, and haplotype analysis. BnaA09g10430D detected through lead SNP chrA09__5160639 was associated with SY of B. napus. Our results provide valuable information for studying the genetic control of seed yield in B. napus and valuable genes, haplotypes, and cultivars resources for the breeding of high seed yield B. napus cultivars.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01332-6.

SSR-based genome-wide association study in turkish durum wheat germplasms revealed novel QTL of accumulated platinum

BACKGROUND

Durum wheat has a genetic capacity to accumulate toxic metals that can exceed the safety limit of the international standards, which may seriously affect human health. Identifying germplasms with low, nontoxic accumulated metal contents is important to select and develop new varieties. Thus, the objective of this study is to identify the levels of accumulated platinum in durum wheat and detect novel QTL.

METHODS AND RESULTS

Platinum contents were determined using 130 durum genotypes. Results generally showed low values of accumulated Pt and significantly less than the maximum grain's Pt content determined by international standards. Pt contents among genotypes varied from ≤ 0.001 to 0.72 µg/kg with an average of 0.02. Landraces showed the lowest average accumulated Pt. GWAS was then performed with 780 SSR markers. Five QTL were detected and explained 14.4-23.1% of the total phenotypic variation. Chromosomes 3 A, 3B, and 5B appear to be hotspots and may play a crucial role in accumulated Pt and were harbored in 1, 3, and 1 QTL, respectively.

CONCLUSIONS

This assessment of accumulated Pt within a unique panel included accessions mostly from Turkish regions, and GWAS used is the first study regarding accumulated Pt indices to reveal novel QTL. It will allow breeders to accelerate their selection of proper genotypes according to desired alleles and offer an opportunity to apply MAS to minimize Pt toxicity in durum wheat. Results indicated that the significance of genome (B) regions are likely related to the inheritance control of Pt content and may play a pivotal role regarding durum wheat's Pt contents. Nonetheless, these novel QTL should be validated in independent populations in numerous environments.

Detection of Stable Elite Haplotypes and Potential Candidate Genes of Boll Weight Across Multiple Environments via GWAS in Upland Cotton

Boll weight (BW) is a key determinant of yield component traits in cotton, and understanding the genetic mechanism of BW could contribute to the progress of cotton fiber yield. Although many yield-related quantitative trait loci (QTLs) responsible for BW have been determined, knowledge of the genes controlling cotton yield remains limited. Here, association mapping based on 25,169 single-nucleotide polymorphisms (SNPs) and 2,315 insertions/deletions (InDels) was conducted to identify high-quality QTLs responsible for BW in a global collection of 290 diverse accessions, and BW was measured in nine different environments. A total of 19 significant markers were detected, and 225 candidate genes within a 400 kb region (± 200 kb surrounding each locus) were predicted. Of them, two major QTLs with highly phenotypic variation explanation on chromosomes A08 and D13 were identified among multiple environments. Furthermore, we found that two novel candidate genes (Ghir_A08G009110 and Ghir_D13G023010) were associated with BW and that Ghir_D13G023010 was involved in artificial selection during cotton breeding by population genetic analysis. The transcription level analyses showed that these two genes were significantly differentially expressed between high-BW accession and low-BW accession during the ovule development stage. Thus, these results reveal valuable information for clarifying the genetic basics of the control of BW, which are useful for increasing yield by molecular marker-assisted selection (MAS) breeding in cotton.

TIP41L, a putative candidate gene conferring both seed size and boll weight, was fine-mapped in an introgression line of Gossypium hirsutum-Gossypium arboreum

QTLs for yield-related traits in tetraploid cotton have been widely mapped, but QTLs introduced from diploid species into tetraploid cotton background remain uninvolved. Here, a stable introgression line with the traits of small boll and seed on Chr. A12, IL197 derived from Gossypium hirsutum (2n = AADD = 52) × Gossypium arboreum (2n = AA = 26), was employed to construct the F₂ and F₃ secondary populations for fine-mapping QTLs of yield-related traits. QTL analysis showed eight QTLs were detected for three traits, boll weight (BW), seed index (SI, one-hundred-seed weight in g), and lint percentage, with 3.94-28.13 % of the phenotypic variance explained. Of them, a stable major QTL, q(BW + SI)-A12-1 controlling both BW and SI and covering the shortest region in Chr. A12, was further narrowed into a 60.09 kb-interval through substitution mapping. Finally, five candidate genes were detected in the interval. The qRT-PCR analysis revealed only TIP41-like family protein (TIP41L) kept up-regulated expression and significantly lower in TM-1 than that in IL197 from -1 DPA to 15 DPA during cotton boll rapid developmental stage. Therefore, TIP41L gene is speculated as the most likely candidate gene. Comparative analysis with the other four allotetraploid species showed TIP41L gene was probably diverged after the formation of allotetraploid cotton, which may be selected and swept during domestication of modern upland cotton because small boll and seed are detrimental to fibre yield of cotton. This research would lay a solid foundation for further elucidating the molecular mechanism of cotton boll and seed development.

Inheritance, QTLs, and Candidate Genes of Lint Percentage in Upland Cotton

Cotton (Gossypium spp.) is an important natural fiber plant. Lint percentage (LP) is one of the most important determinants of cotton yield and is a typical quantitative trait with high variation and heritability. Many cotton LP genetic linkages and association maps have been reported. This work summarizes the inheritance, quantitative trait loci (QTLs), and candidate genes of LP to facilitate LP genetic study and molecular breeding. More than 1439 QTLs controlling LP have been reported. Excluding replicate QTLs, 417 unique QTLs have been identified on 26 chromosomes, including 243 QTLs identified at LOD >3. More than 60 are stable, major effective QTLs that can be used in marker-assisted selection (MAS). More than 90 candidate genes for LP have been reported. These genes encode MYB, HOX, NET, and other proteins, and most are preferentially expressed during fiber initiation and elongation. A putative molecular regulatory model of LP was constructed and provides the foundation for the genetic study and molecular breeding of LP.