Significant Quantitative Trait Nucleotides Research Articles

Genome-wide association study provides new insight into the underlying mechanism of drought tolerance during seed germination stage in soybean

Drought is one of the major environmental issues that reduce crop yield. Seed germination is a crucial stage of plant development in all crop plants, including soybean. In soybean breeding, information about genetic mechanism of drought tolerance has great importance. However, at germination stage, there is relatively little knowledge on the genetic basis of soybean drought resistance. The objective of this work was to find the quantitative trait nucleotides (QTNs) linked to drought tolerance related three traits using a genome-wide association study (GWAS), viz., germination rate (GR), root length (RL), and whole seedling length (WSL), using germplasm population of 240 soybean PIs with 34,817 SNPs genotype data having MAF > 0.05. It was observed that heritability (H2) for GR, WSL, and RL across both environments (2020, and 2019) were high in the range of 0.76–0.99, showing that genetic factors play a vital role in drought tolerance as compared to environmental factors. A number of 23 and 27 QTNs were found to be linked to three traits using MLM and mrMLM, respectively. Three significant QTNs, qGR8-1, qWSL13-1, and qRL-8, were identified using both MLM and mrMLM methods among these QTNs. QTN8, located on chromosome 8 was consistently linked to two traits (GR and RL). The area (± 100 Kb) associated with this QTN was screened for drought tolerance based on gene annotation. Fifteen candidate genes were found by this screening. Based on the expression data, four candidate genes i.e. Glyma08g156800, Glyma08g160000, Glyma08g162700, and Glyma13g249600 were found to be linked to drought tolerance regulation in soybean. Hence, the current study provides evidence to understand the genetic constitution of drought tolerance during the germination stage and identified QTNs or genes could be utilized in molecular breeding to enhance the yield under drought stress.

An Improved Expectation–Maximization Bayesian Algorithm for GWAS

Genome-wide association studies (GWASs) are flexible and comprehensive tools for identifying single nucleotide polymorphisms (SNPs) associated with complex traits or diseases. The whole-genome Bayesian models are an effective way of incorporating important prior information into modeling. Bayesian methods have been widely used in association analysis. However, Bayesian analysis is often not feasible due to the high-throughput genotype and large sample sizes involved. In this study, we propose a new Bayesian algorithm under the mixed linear model framework: the expectation and maximization BayesB Improved algorithm (emBBI). The emBBI algorithm corrects polygenic and environmental noise and reduces dimensions; then, it estimates and tests marker effects using emBayesB and the LOD test, respectively. We conducted two simulation experiments and analyzed a real dataset related to flowering time in Arabidopsis to demonstrate the validation of the new algorithm. The results show that the emBBI algorithm is more flexible and accurate in simulation studies compared to established methods, and it performs well under complex genetic backgrounds. The analysis of the Arabidopsis real dataset further illustrates the advantages of the emBBI algorithm for GWAS by detecting known genes. Furthermore, 12 candidate genes are identified in the neighborhood of the significant quantitative trait nucleotides (QTNs) of flowering-related QTNs in Arabidopsis. In addition, we also performed enrichment analysis and tissue expression analysis of candidate genes, which will help us better understand the genetic basis of flowering-related traits in Arabidopsis.

Genome-wide genetic architecture for plant maturity and drought tolerance in diploid potatoes.

Cultivated potato (Solanum tuberosum) is known to be highly susceptible to drought. With climate change and its frequent episodes of drought, potato growers will face increased challenges to achieving their yield goals. Currently, a high proportion of untapped potato germplasm remains within the diploid potato relatives, and the genetic architecture of the drought tolerance and maturity traits of diploid potatoes is still unknown. As such, a panel of 384 ethyl methanesulfonate-mutagenized diploid potato clones were evaluated for drought tolerance and plant maturity under field conditions. Genome-wide association studies (GWAS) were conducted to dissect the genetic architecture of the traits. The results obtained from the genetic structure analysis of the panel showed five main groups and seven subgroups. Using the Genome Association and Prediction Integrated Tool-mixed linear model GWAS statistical model, 34 and 17 significant quantitative trait nucleotides (QTNs) were found associated with maturity and drought traits, respectively. Chromosome 5 carried most of the QTNs, some of which were also detected by using the restricted two-stage multi-locus multi-allele-GWAS haploblock-based model, and two QTNs were found to be pleiotropic for both maturity and drought traits. Using the non-parametric U-test, one and three QTNs, with 5.13%-7.4% phenotypic variations explained, showed favorable allelic effects that increase the maturity and drought trait values. The quantitaive trait loci (QTLs)/QTNs associated with maturity and drought trait were found co-located in narrow (0.5-1kb) genomic regions with 56 candidate genes playing roles in plant development and senescence and in abiotic stress responses. A total of 127 potato clones were found to be late maturing and tolerant to drought, while nine were early to moderate-late maturing and tolerant to drought. Taken together, the data show that the studied germplasm panel and the identified candidate genes are prime genetic resources for breeders and biologists in conventional breeding and targeted gene editing as climate adaptation tools.

Wheat Grains as a Sustainable Source of Protein for Health.

Protein deficiency is recognized among the major global health issues with an underestimation of its importance. Genetic biofortification is a cost-effective and sustainable strategy to overcome global protein malnutrition. This study was designed to focus on protein-dense grains of wheat (Triticum aestivum L.) and identify the genes governing grain protein content (GPC) that improve end-use quality and in turn human health. Genome-wide association was applied using the 90k iSELECT Infinium and 35k Affymetrix arrays with GPC quantified by using a proteomic-based technique in 369 wheat genotypes over three field-year trials. The results showed significant natural variation among bread wheat genotypes that led to detecting 54 significant quantitative trait nucleotides (QTNs) surpassing the false discovery rate (FDR) threshold. These QTNs showed contrasting effects on GPC ranging from -0.50 to +0.54% that can be used for protein content improvement. Further bioinformatics analyses reported that these QTNs are genomically linked with 35 candidate genes showing high expression during grain development. The putative candidate genes have functions in the binding, remobilization, or transport of protein. For instance, the promising QTN AX-94727470 on chromosome 6B increases GPC by +0.47% and is physically located inside the gene TraesCS6B02G384500 annotated as Trehalose 6-phosphate phosphatase (T6P), which can be employed to improve grain protein quality. Our findings are valuable for the enhancement of protein content and end-use quality in one of the major daily food resources that ultimately improve human nutrition.

Genome-wide association analysis provides insights into the genetic basis of photosynthetic responses to low-temperature stress in spring barley.

Low-temperature stress (LTS) is among the major abiotic stresses affecting the geographical distribution and productivity of the most important crops. Understanding the genetic basis of photosynthetic variation under cold stress is necessary for developing more climate-resilient barley cultivars. To that end, we investigated the ability of chlorophyll fluorescence parameters (FVFM, and FVF0) to respond to changes in the maximum quantum yield of Photosystem II photochemistry as an indicator of photosynthetic energy. A panel of 96 barley spring cultivars from different breeding zones of Canada was evaluated for chlorophyll fluorescence-related traits under cold acclimation and freeze shock stresses at different times. Genome-wide association studies (GWAS) were performed using a mixed linear model (MLM). We identified three major and putative genomic regions harboring 52 significant quantitative trait nucleotides (QTNs) on chromosomes 1H, 3H, and 6H for low-temperature tolerance. Functional annotation indicated several QTNs were either within the known or close to genes that play important roles in the photosynthetic metabolites such as abscisic acid (ABA) signaling, hydrolase activity, protein kinase, and transduction of environmental signal transduction at the posttranslational modification levels. These outcomes revealed that barley plants modified their gene expression profile in response to decreasing temperatures resulting in physiological and biochemical modifications. Cold tolerance could influence a long-term adaption of barley in many parts of the world. Since the degree and frequency of LTS vary considerably among production sites. Hence, these results could shed light on potential approaches for improving barley productivity under low-temperature stress.

Multi-Environment Genome-Wide Association Studies of Yield Traits in Common Bean (Phaseolus vulgaris L.) × Tepary Bean (P. acutifolius A. Gray) Interspecific Advanced Lines in Humid and Dry Colombian Caribbean Subregions

Assessing interspecific adaptive genetic variation across environmental gradients offers insight into the scale of habitat-dependent heritable heterotic effects, which may ultimately enable pre-breeding for abiotic stress tolerance and novel climates. However, environmentally dependent allelic effects are often bypassed by intra-specific single-locality genome-wide associations studies (GWAS). Therefore, in order to bridge this gap, this study aimed at coupling an advanced panel of drought/heat susceptible common bean (Phaseolus vulgaris L.) × tolerant tepary bean (P. acutifolius A. Gray) interspecific lines with last-generation multi-environment GWAS algorithms to identify novel sources of heat and drought tolerance to the humid and dry subregions of the Caribbean coast of Colombia, where the common bean typically exhibits maladaptation to extreme weather. A total of 87 advanced lines with interspecific ancestries were genotyped by sequencing (GBS), leading to the discovery of 15,645 single-nucleotide polymorphism (SNP) markers. Five yield traits were recorded for each genotype and inputted in modern GWAS algorithms (i.e., FarmCPU and BLINK) to identify the putative associated loci across four localities in coastal Colombia. Best-fit models revealed 47 significant quantitative trait nucleotides (QTNs) distributed in all 11 common bean chromosomes. A total of 90 flanking candidate genes were identified using 1-kb genomic windows centered in each associated SNP marker. Pathway-enriched analyses were done using the mapped output of the GWAS for each yield trait. Some genes were directly linked to the drought tolerance response; morphological, physiological, and metabolic regulation; signal transduction; and fatty acid and phospholipid metabolism. We conclude that habitat-dependent interspecific polygenic effects are likely sufficient to boost common bean adaptation to the severe climate in coastal Colombia via introgression breeding. Environmental-dependent polygenic adaptation may be due to contrasting levels of selection and the deleterious load across localities. This work offers putative associated loci for marker-assisted and genomic selection targeting the common bean’s neo-tropical lowland adaptation to drought and heat.

Multi-locus genome-wide association study of chickpea reference set identifies genetic determinants of Pratylenchus thornei resistance.

Pratylenchus thornei is an economically important species of root-lesion nematode adversely affecting chickpea (Cicer arietinum) yields globally. Integration of resistant crops in farming systems is recognised as the most effective and sustainable management strategy for plant-parasitic nematodes. However, breeding for P. thornei resistance in chickpea is limited by the lack of genetic diversity. We deployed a genome-wide association approach to identify genomic regions and candidate genes associated with P. thornei resistance in 285 genetically diverse chickpea accessions. Chickpea accessions were phenotyped for P. thornei resistance in replicated glasshouse experiments performed for two years (2018 and 2020). Whole genome sequencing data comprising 492,849 SNPs were used to implement six multi-locus GWAS models. Fourteen chickpea genotypes were found to be resistant to P. thornei. Of the six multi-locus GWAS methods deployed, FASTmrMLM was found to be the best performing model. In all, 24 significant quantitative trait nucleotides (QTNs) were identified, of which 13 QTNs were associated with lower nematode population density and 11 QTNs with higher nematode population density. These QTNs were distributed across all of the chickpea chromosomes, except chromosome 8. We identified, receptor-linked kinases (RLKs) on chromosomes 1, 4 and 6, GDSL-like Lipase/Acylhydrolase on chromosome 3, Aspartic proteinase-like and Thaumatin-like protein on chromosome 4, AT-hook DNA-binding and HSPRO2 on chromosome 6 as candidate genes for P. thornei resistance in the chickpea reference set. New sources of P. thornei resistant genotypes were identified that can be harnessed into breeding programs and putative candidate P. thornei resistant genes were identified that can be explored further to develop molecular markers and accelerate the incorporation of improved P. thornei resistance into elite chickpea cultivars.

Elucidating the patterns of pleiotropy and its biological relevance in maize.

Pleiotropy-when a single gene controls two or more seemingly unrelated traits-has been shown to impact genes with effects on flowering time, leaf architecture, and inflorescence morphology in maize. However, the genome-wide impact of biological pleiotropy across all maize phenotypes is largely unknown. Here, we investigate the extent to which biological pleiotropy impacts phenotypes within maize using GWAS summary statistics reanalyzed from previously published metabolite, field, and expression phenotypes across the Nested Association Mapping population and Goodman Association Panel. Through phenotypic saturation of 120,597 traits, we obtain over 480 million significant quantitative trait nucleotides. We estimate that only 1.56-32.3% of intervals show some degree of pleiotropy. We then assess the relationship between pleiotropy and various biological features such as gene expression, chromatin accessibility, sequence conservation, and enrichment for gene ontology terms. We find very little relationship between pleiotropy and these variables when compared to permuted pleiotropy. We hypothesize that biological pleiotropy of common alleles is not widespread in maize and is highly impacted by nuisance terms such as population structure and linkage disequilibrium. Natural selection on large standing natural variation in maize populations may target wide and large effect variants, leaving the prevalence of detectable pleiotropy relatively low.

Genetic Dissection of Epistatic Interactions Contributing Yield-Related Agronomic Traits in Rice Using the Compressed Mixed Model.

Rice (Oryza sativa) is one of the most important cereal crops in the world, and yield-related agronomic traits, including plant height (PH), panicle length (PL), and protein content (PC), are prerequisites for attaining the desired yield and quality in breeding programs. Meanwhile, the main effects and epistatic effects of quantitative trait nucleotides (QTNs) are all important genetic components for yield-related quantitative traits. In this study, we conducted genome-wide association studies (GWAS) for 413 rice germplasm resources, with 36,901 single nucleotide polymorphisms (SNPs), to identify QTNs, QTN-by-QTN interaction (QQI), and their candidate genes, using a multi-locus compressed variance component mixed model, 3VmrMLM. As a result, two significant QTNs and 56 paired QQIs were detected, amongst 5219 genes of these QTNs, and 26 genes were identified as the yield-related confirmed genes, such as LCRN1, OsSPL3, and OsVOZ1 for PH, and LOG and QsBZR1 for PL. To reveal the substantial contributions related to the variation of yield-related agronomic traits in rice, we further implemented an enrichment analysis and expression analysis. As the results showed, 114 genes, nearly all significant QQIs, were involved in 37 GO terms; for example, the macromolecule metabolic process (GO:0043170), intracellular part (GO:0044424), and binding (GO:0005488). It was revealed that most of the QQIs and the candidate genes were significantly involved in the biological process, molecular function, and cellular component of the target traits. The demonstrated genetic interactions play a critical role in yield-related agronomic traits of rice, and such epistatic interactions contributed to large portions of the missing heritability in GWAS. These results help us to understand the genetic basis underlying the inheritance of the three yield-related agronomic traits and provide implications for rice improvement.

Uncovering Novel Genomic Regions and Candidate Genes for Senescence-Related Traits by Genome-Wide Association Studies in Upland Cotton (Gossypium hirsutum L.).

Senescence in plants is a complex trait, which is controlled by both genetic and environmental factors and can affect the yield and quality of cotton. However, the genetic basis of cotton senescence remains relatively unknown. In this study, we reported genome-wide association studies (GWAS) based on 185 accessions of upland cotton and 26,999 high-quality single-nucleotide polymorphisms (SNPs) to reveal the genetic basis of cotton senescence. To determine cotton senescence, we evaluated eight traits/indices. Our results revealed a high positive correlation (r>0.5) among SPAD value 20 days after topping (SPAD20d), relative difference of SPAD (RSPAD), nodes above white flower on topping day (NAWF0d), nodes above white flower 7 days after topping (NAWF7d), and number of open bolls on the upper four branches (NB), and genetic analysis revealed that all traits had medium or high heritability ranging from 0.53 to 0.86. Based on a multi-locus method (FASTmrMLM), a total of 63 stable and significant quantitative trait nucleotides (QTNs) were detected, which represented 50 genomic regions (GWAS risk loci) associated with cotton senescence. We observed three reliable loci located on chromosomes A02 (A02_105891088_107196428), D03 (D03_37952328_38393621) and D13 (D13_59408561_60730103) because of their high repeatability. One candidate gene (Ghir_D03G011060) was found in the locus D03_37952328_38393621, and its Arabidopsis thaliana homologous gene (AT5G23040) encodes a cell growth defect factor-like protein (CDF1), which might be involved in chlorophyll synthesis and cell death. Moreover, qRT-PCR showed that the transcript level of Ghir_D03G011060 was down-regulated in old cotton leaves, and virus-induced gene silencing (VIGS) indicated that silencing of Ghir_D03G011060 resulted in leaf chlorosis and promoted leaf senescence. In addition, two candidate genes (Ghir_A02G017660 and Ghir_D13G021720) were identified in loci A02_105891088_107196428 and D13_59408561_60730103, respectively. These results provide new insights into the genetic basis of cotton senescence and will serve as an important reference for the development and implementation of strategies to prevent premature senescence in cotton breeding programs.

Multi-locus genome-wide association studies for five yield-related traits in rice

BackgroundImproving the overall production of rice with high quality is a major target of breeders. Mining potential yield-related loci have been geared towards developing efficient rice breeding strategies. In this study, one single-locus genome-wide association studies (SL-GWAS) method (MLM) in conjunction with five multi-locus genome-wide association studies (ML-GWAS) approaches (mrMLM, FASTmrMLM, pLARmEB, pKWmEB, and ISIS EM-BLASSO) were conducted in a panel consisting of 529 rice core varieties with 607,201 SNPs.ResultsA total of 152, 106, 12, 111, and 64 SNPs were detected by the MLM model associated with the five yield-related traits, namely grain length (GL), grain width (GW), grain thickness (GT), thousand-grain weight (TGW), and yield per plant (YPP), respectively. Furthermore, 74 significant quantitative trait nucleotides (QTNs) were presented across at least two ML-GWAS methods to be associated with the above five traits successively. Finally, 20 common QTNs were simultaneously discovered by both SL-GWAS and ML-GWAS methods. Based on genome annotation, gene expression analysis, and previous studies, two candidate key genes (LOC_Os09g02830 and LOC_Os07g31450) were characterized to affect GW and TGW, separately.ConclusionsThese outcomes will provide an indication for breeding high-yielding rice varieties in the immediate future.

Genetic Dissection of Seedling Root System Architectural Traits in a Diverse Panel of Hexaploid Wheat through Multi-Locus Genome-Wide Association Mapping for Improving Drought Tolerance.

Cultivars with efficient root systems play a major role in enhancing resource use efficiency, particularly water absorption, and thus in drought tolerance. In this study, a diverse wheat association panel of 136 wheat accessions including mini core subset was genotyped using Axiom 35k Breeders’ Array to identify genomic regions associated with seedling stage root architecture and shoot traits using multi-locus genome-wide association studies (ML-GWAS). The association panel revealed a wide variation of 1.5- to 50-fold and were grouped into six clusters based on 15 traits. Six different ML-GWAS models revealed 456 significant quantitative trait nucleotides (QTNs) for various traits with phenotypic variance in the range of 0.12–38.60%. Of these, 87 QTNs were repeatedly detected by two or more models and were considered reliable genomic regions for the respective traits. Among these QTNs, eleven were associated with average diameter and nine each for second order lateral root number (SOLRN), root volume (RV) and root length density (RLD). A total of eleven genomic regions were pleiotropic and each controlled two or three traits. Some important candidate genes such as Formin homology 1, Ubiquitin-like domain superfamily and ATP-dependent 6-phosphofructokinase were identified from the associated genomic regions. The genomic regions/genes identified in this study could potentially be targeted for improving root traits and drought tolerance in wheat.

Genetic variability assessment of 127 Triticum turgidum L. accessions for mycorrhizal susceptibility-related traits detection

Positive effects of arbuscular mycorrhizal fungi (AMF)—wheat plant symbiosis have been well discussed by research, while the actual role of the single wheat genotype in establishing this type of association is still poorly investigated. In this work, the genetic diversity of Triticum turgidum wheats was exploited to detect roots susceptibility to AMF and to identify genetic markers in linkage with chromosome regions involved in this symbiosis. A tetraploid wheat collection of 127 accessions was genotyped using 35K single-nucleotide polymorphism (SNP) array and inoculated with the AMF species Funneliformis mosseae (F. mosseae) and Rhizoglomus irregulare (R. irregulare), and a genome‐wide association study (GWAS) was conducted. Six clusters of genetically related accessions were identified, showing a different mycorrhizal colonization among them. GWAS revealed four significant quantitative trait nucleotides (QTNs) involved in mycorrhizal symbiosis, located on chromosomes 1A, 2A, 2B and 6A. The results of this work enrich future breeding activities aimed at developing new grains on the basis of genetic diversity on low or high susceptibility to mycorrhization, and, possibly, maximizing the symbiotic effects.

Genome-Wide Association Studies of Seed Performance Traits in Response to Heat Stress in Medicago truncatula Uncover MIEL1 as a Regulator of Seed Germination Plasticity.

Legume seeds are an important source of proteins, minerals, and vitamins for human and animal diets and represent a keystone for food security. With climate change and global warming, the production of grain legumes faces new challenges concerning seed vigor traits that allow the fast and homogenous establishment of the crop in a wide range of environments. These seed performance traits are regulated during seed maturation and are under the strong influence of the maternal environment. In this study, we used 200 natural Medicago truncatula accessions, a model species of legumes grown in optimal conditions and under moderate heat stress (26°C) during seed development and maturation. This moderate stress applied at flowering onwards impacted seed weight and germination capacity. Genome-wide association studies (GWAS) were performed to identify putative loci or genes involved in regulating seed traits and their plasticity in response to heat stress. We identified numerous significant quantitative trait nucleotides and potential candidate genes involved in regulating these traits under heat stress by using post-GWAS analyses combined with transcriptomic data. Out of them, MtMIEL1, a RING-type zinc finger family gene, was shown to be highly associated with germination speed in heat-stressed seeds. In Medicago, we highlighted that MtMIEL1 was transcriptionally regulated in heat-stressed seed production and that its expression profile was associated with germination speed in different Medicago accessions. Finally, a loss-of-function analysis of the Arabidopsis MIEL1 ortholog revealed its role as a regulator of germination plasticity of seeds in response to heat stress.

Identification of New Leaf Rust Resistance Loci in Wheat and Wild Relatives by Array-Based SNP Genotyping and Association Genetics.

Leaf rust caused by Puccinia triticina is the most widespread rust disease of wheat. As pathogen populations are constantly evolving, identification of novel sources of resistance is necessary to maintain disease resistance and stay ahead of this plant-pathogen evolutionary arms race. The wild genepool of wheat is a rich source of genetic diversity, accounting for 44% of the Lr genes identified. Here we performed a genome-wide association study (GWAS) on a diverse germplasm of 385 accessions, including 27 different Triticum and Aegilops species. Genetic characterization using the wheat 90 K array and subsequent filtering identified a set of 20,501 single nucleotide polymorphic (SNP) markers. Of those, 9,570 were validated using exome capture and mapped onto the Chinese Spring reference sequence v1.0. Phylogenetic analyses illustrated four major clades, clearly separating the wild species from the T. aestivum and T. turgidum species. GWAS was conducted using eight statistical models for infection types against six leaf rust isolates and leaf rust severity rated in field trials for 3–4 years at 2–3 locations in Canada. Functional annotation of genes containing significant quantitative trait nucleotides (QTNs) identified 96 disease-related loci associated with leaf rust resistance. A total of 21 QTNs were in haplotype blocks or within flanking markers of at least 16 known Lr genes. The remaining significant QTNs were considered loci that putatively harbor new Lr resistance genes. Isolation of these candidate genes will contribute to the elucidation of their role in leaf rust resistance and promote their usefulness in marker-assisted selection and introgression.

Genome-wide association studies and whole-genome prediction reveal the genetic architecture of KRN in maize

BackgroundKernel row number (KRN) is an important trait for the domestication and improvement of maize. Exploring the genetic basis of KRN has great research significance and can provide valuable information for molecular assisted selection.ResultsIn this study, one single-locus method (MLM) and six multilocus methods (mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB and ISIS EM-BLASSO) of genome-wide association studies (GWASs) were used to identify significant quantitative trait nucleotides (QTNs) for KRN in an association panel including 639 maize inbred lines that were genotyped by the MaizeSNP50 BeadChip. In three phenotyping environments and with best linear unbiased prediction (BLUP) values, the seven GWAS methods revealed different numbers of KRN-associated QTNs, ranging from 11 to 177. Based on these results, seven important regions for KRN located on chromosomes 1, 2, 3, 5, 9, and 10 were identified by at least three methods and in at least two environments. Moreover, 49 genes from the seven regions were expressed in different maize tissues. Among the 49 genes, ARF29 (Zm00001d026540, encoding auxin response factor 29) and CKO4 (Zm00001d043293, encoding cytokinin oxidase protein) were significantly related to KRN, based on expression analysis and candidate gene association mapping. Whole-genome prediction (WGP) of KRN was also performed, and we found that the KRN-associated tagSNPs achieved a high prediction accuracy. The best strategy was to integrate all of the KRN-associated tagSNPs identified by all GWAS models.ConclusionsThese results aid in our understanding of the genetic architecture of KRN and provide useful information for genomic selection for KRN in maize breeding.

Genome-wide association study of agronomic and quality traits in a world collection of the wild wheat relative Triticum urartu.

Triticum urartu (2n=2x=14, subgenome Au Au ), a wild diploid wheat progenitor, features broad allelic diversity for a number of traits of agronomic relevance. A thorough characterization of the diversity of T.urartu natural accessions may provide wheat breeders with new alleles potentially contributing to wheat improvement. In this study, we performed an extensive genotypic and phenotypic characterization of a world collection of 299 T.urartu ex situ accessions, developing 441327 single nucleotide polymorphisms and recording trait values for agronomic and quality traits. The collection was highly diverse, with broad variation in phenology and plant architecture traits. Seed features were also varied, and analyses of flour quality reported 18 distinct patterns of glutenins, and carotenoid concentrations and sedimentation volumes in some cases surpassing those of cultivated materials. The genome-wide molecular markers developed on the collection were used to conduct a genome-wide association study reporting 25 highly significant quantitative trait nucleotides for the traits under examination, only partially overlapping loci already reported in wheat. Our data show that T.urartu may be considered a valuable allele pool to support the improvement of wheat agronomy and quality.

Genetic dissection of 2-heptenal content in soybean (Glycine max) seed through genome-wide association study

Association analysis is an alternative to conventional, family-based methods for detecting the location of gene(s) or quantitative trait loci (QTLs), and provides relatively high resolution in terms of defining the genome position of a gene or QTL. Flavour is an essential quality characteristic of soymilk; however, soymilk contains volatile compounds unacceptable to consumers. One of main constituents in the volatiles of normal soymilk is 2-heptenal, which is thought to be a degradative oxidation product of polyunsaturated acids. In this study, a genome-wide association study using 24651 single-nucleotide polymorphisms (SNPs) was performed to identify quantitative trait nucleotides (QTNs) controlling 2-heptenal content in soybean (Glycine max (L.) Merr.) seed from a natural population of 110 soybean germplasm accessions. We detected 62 significant QTNs located on 18 different chromosomes that are significantly associated with 2-heptenal content in soybean seed. Among these, 17 QTNs co-localised with QTLs previously found to be related to protein, oil and/or fatty acid content in soybean seed. We also identified some candidate genes involved in lipid metabolism. These findings further our understanding of the genetic basis of 2-heptenal content in soybean seed and the improvement of marker-assisted breeding efficiency, which will be important for breeding soybean cultivars with low 2-heptenal content.

Genetic Detection of Lint Percentage Applying Single-Locus and Multi-Locus Genome-Wide Association Studies in Chinese Early-Maturity Upland Cotton.

Upland cotton (Gossypium hirsutum L.) is the most important source of natural fiber in the world. Early-maturity upland cotton varieties are commonly planted in China. Nevertheless, lint yield of early-maturity upland cotton varieties is strikingly lower than that of middle- and late-maturity ones. How to effectively improve lint yield of early maturing cotton, becomes a focus of cotton research. Here, based on 72,792 high-quality single nucleotide polymorphisms of 160 early-maturing upland cotton accessions, we performed genome-wide association studies (GWASs) for lint percentage (LP), one of the most lint-yield component traits, applying one single-locus method and six multi-locus methods. A total of 4 and 45 significant quantitative trait nucleotides (QTNs) were respectively identified to be associated with LP. Interestingly, in two of four planting environments, two of these QTNs (A02_74713290 and A02_75551547) were simultaneously detected via both one single-locus and three or more multi-locus GWAS methods. Among the 42 genes within a genomic region (A02: 74.31–75.95 Mbp) containing the above two peak QTNs, Gh_A02G1269, Gh_A02G1280, and Gh_A02G1295 had the highest expression levels in ovules during seed development from 20 to 25 days post anthesis, whereas Gh_A02G1278 was preferentially expressed in the fibers rather than other organs. These results imply that the four potential candidate genes might be closely related to cotton LP by regulating the proportion of seed weight and fiber yield. The QTNs and potential candidate genes for LP, identified in this study, provide valuable resource for cultivating novel cotton varieties with earliness and high lint yield in the future.

Multi-Locus Genome-Wide Association Studies of Fiber-Quality Related Traits in Chinese Early-Maturity Upland Cotton.

Early-maturity varieties of upland cotton are becoming increasingly important for farmers to improve their economic benefits through double cropping practices and mechanical harvesting production in China. However, fiber qualities of early-maturing varieties are relatively poor compared with those of middle- and late- maturing ones. Therefore, it is crucial for researchers to elucidate the genetic bases controlling fiber-quality related traits in early-maturity cultivars, and to improve synergistically cotton earliness and fiber quality. Here, multi-locus genome-wide association studies (ML-GWAS) were conducted in a panel consisting of 160 early-maturing cotton accessions. Each accession was genotyped by 72,792 high-quality single nucleotide polymorphisms (SNPs) using specific-locus amplified fragment sequencing (SLAF-seq) approach, and fiber quality-related traits under four environmental conditions were measured. Applying at least three ML-GWAS methods, a total of 70 significant quantitative trait nucleotides (QTNs) were identified to be associated with five objective traits, including fiber length (FL), fiber strength (FS), fiber micronaire (FM), fiber uniformity (FU) and fiber elongation (FE). Among these QTNs, D11_21619830, A05_28352019 and D03_34920546 were found to be significantly associated with FL, FS, and FM, respectively, across at least two environments. Among 96 genes located in the three target genomic regions (A05: 27.95 28.75, D03: 34.52 35.32, and D11: 21.22 22.02 Mbp), six genes (Gh_A05G2325, Gh_A05G2329, Gh_A05G2334, Gh_D11G1853, Gh_D11G1876, and Gh_D11G1879) were detected to be highly expressed in fibers relative to other eight tissues by transcriptome sequencing method in 12 cotton tissues. Together, multiple favorable QTN alleles and six candidate key genes were characterized to regulate fiber development in early-maturity cotton. This will lay a solid foundation for breeding novel cotton varieties with earliness and excellent fiber-quality in the future.