Project description:Soybean is the world's leading source of vegetable protein and demand for its seed continues to grow. Breeders have successfully increased soybean yield, but the genetic architecture of yield and key agronomic traits is poorly understood. We developed a 40-mating soybean nested association mapping (NAM) population of 5,600 inbred lines that were characterized by single nucleotide polymorphism (SNP) markers and six agronomic traits in field trials in 22 environments. Analysis of the yield, agronomic, and SNP data revealed 23 significant marker-trait associations for yield, 19 for maturity, 15 for plant height, 17 for plant lodging, and 29 for seed mass. A higher frequency of estimated positive yield alleles was evident from elite founder parents than from exotic founders, although unique desirable alleles from the exotic group were identified, demonstrating the value of expanding the genetic base of US soybean breeding.
Project description:Comparative and evolutionary genomics analyses are the powerful tools to provide mechanistic insights into important agronomic traits. Here, we completed a chromosome-scale assembly of the "neglected" but vital melon subspecies Cucumis melo ssp. agrestis using single-molecule real-time sequencing, Hi-C, and an ultra-dense genetic map. Comparative genomics analyses identified two targeted genes, UDP-sugar pyrophosphorylase and α-galactosidase, that were selected during evolution for specific phloem transport of oligosaccharides in Cucurbitaceae. Association analysis of transcriptome and the DNA methylation patterns revealed the epigenetic regulation of sucrose accumulation in developing fruits. We constructed the melon recombinant inbred lines to uncover Alkaline/Neutral Invertase (CINV), Sucrose-Phosphatase 2 (SPP2), α-galactosidase, and β-galactosidase loci related to sucrose accumulation and an LRR receptor-like serine/threonine-protein kinase associated with gummy stem blight resistance. This study provides essential genomic resources enabling functional genomics studies and the genomics-informed breeding pipelines for improving the fruit quality and disease resistance traits.
Project description:Phenotypic plasticity is the ability of a given genotype to produce multiple phenotypes in response to changing environmental conditions. Understanding the genetic basis of phenotypic plasticity and establishing a predictive model is highly relevant to future agriculture under a changing climate. Here we report findings on the genetic basis of phenotypic plasticity for 23 complex traits using a diverse maize population planted at five sites with distinct environmental conditions. We found that latitude-related environmental factors were the main drivers of across-site variation in flowering time traits but not in plant architecture or yield traits. For the 23 traits, we detected 109 quantitative trait loci (QTLs), 29 for mean values, 66 for plasticity, and 14 for both parameters, and 80% of the QTLs interacted with latitude. The effects of several QTLs changed in magnitude or sign, driving variation in phenotypic plasticity. We experimentally validated one plastic gene, ZmTPS14.1, whose effect was likely mediated by the compensation effect of ZmSPL6 from a downstream pathway. By integrating genetic diversity, environmental variation, and their interaction into a joint model, we could provide site-specific predictions with increased accuracy by as much as 9.9%, 2.2%, and 2.6% for days to tassel, plant height, and ear weight, respectively. This study revealed a complex genetic architecture involving multiple alleles, pleiotropy, and genotype-by-environment interaction that underlies variation in the mean and plasticity of maize complex traits. It provides novel insights into the dynamic genetic architecture of agronomic traits in response to changing environments, paving a practical way toward precision agriculture.
Project description:Flowering Chinese cabbage is a type of leafy vegetable that belongs to the Brassica genus. Originally native to South China, it is now widely cultivated and consumed across the globe, particularly in Asian countries. The recent cultivation and regional expansion of flowering Chinese cabbage provides a valuable opportunity to elucidate the genomic basis underlying environmental adaptation and desired traits during a short-term artificial selection process. Here, we investigate the genetic variation, population structure, and diversity of a diverse germplasm collection of 403 flowering Chinese cabbage accessions. Our investigation seeks to elucidate the genomic basis that guides the selection of adaptability, yield, and pivotal agronomic traits. We further investigated breeding improvement associated with stem development by integrating transcriptome data. Genome-wide association analysis identified 642 loci and corresponding candidate genes associated with 11 essential agronomic traits, including plant architecture and yield. Furthermore, we uncovered a significant disparity in the allele frequency distribution of nonsynonymous mutations in these candidate genes throughout the improvement stages. Our results shed light on the genetic basis of improvement and crucial agronomic traits in flowering Chinese cabbage, offering invaluable resources for upcoming genomics-assisted breeding endeavors.
Project description:Dioscorea bulbifera is an edible yam specie with aerial bulbils. Assessing the genetic diversity of D. bulbifera accession for cultivation and breeding purposes is essential for it genetic improvement, especially where the crop faces minimal attention. The aims of this study was to assess the genetic diversity of Dioscorea bulbifera accessions collected from Nigeria and accessions maintained at the genebank of International Institute of Tropical Agriculture (IITA) Ibadan. Accessions were profiled using quatitative and qualitative phenotypic traits and Diversity Array Technology SNP-markers. Multivariate analysis based phenotypic traits revealed high variability among the evaluated accessions and all phenotypic traits assessed were useful in discriminating the aerial yam accessions. Clustering analysis based phenotypic traits revealed the presence of two well defined clusters. Using DArT-Seq marker, the 94 accessions were classified into three genetic group through the admixture and the phylogeny analysis. The comparision of phenotypic and genotypic clustering revealed inconsistency membership across the two clustering methods. The study established a baseline for the selection of parental lines from the genetic groups for genetic improvement of the D. bulbifera.
Project description:A growing number of studies clearly demonstrate a substantial link between metabolic dysfunction and the risk of Alzheimer's disease (AD), especially glucose-related dysfunction; one hypothesis for this comorbidity is the presence of a common genetic etiology. We conducted a large-scale cross-trait GWAS to investigate the genetic overlap between AD and ten metabolic traits. Among all the metabolic traits, fasting glucose, fasting insulin and HDL were found to be genetically associated with AD. Local genetic covariance analysis found that 19q13 region had strong local genetic correlation between AD and T2D (P = 6.78 × 10- 22), LDL (P = 1.74 × 10- 253) and HDL (P = 7.94 × 10- 18). Cross-trait meta-analysis identified 4 loci that were associated with AD and fasting glucose, 3 loci that were associated with AD and fasting insulin, and 20 loci that were associated with AD and HDL (Pmeta < 1.6 × 10- 8, single trait P < 0.05). Functional analysis revealed that the shared genes are enriched in amyloid metabolic process, lipoprotein remodeling and other related biological pathways; also in pancreas, liver, blood and other tissues. Our work identifies common genetic architectures shared between AD and fasting glucose, fasting insulin and HDL, and sheds light on molecular mechanisms underlying the association between metabolic dysregulation and AD.
Project description:Dissection of the genetic loci controlling drought tolerance traits with a complex genetic inheritance is important for drought-tolerant sugarcane improvement. In this study, we conducted a large-scale candidate gene association study of 649 candidate genes in a sugarcane diversity panel to identify genetic variants underlying agronomic traits and drought tolerance indices evaluated in plant cane and ratoon cane under water-stressed (WS) and non-stressed (NS) environments. We identified 197 significant marker-trait associations (MTAs) in 141 candidate genes associated with 18 evaluated traits with the Bonferroni correction threshold (α = 0.05). Out of the total, 95 MTAs in 78 candidate genes and 62 MTAs in 58 candidate genes were detected under NS and WS conditions, respectively. Most MTAs were found only in specific water regimes and crop seasons. These MTAs explained 7.93-30.52% of phenotypic variation. Association mapping results revealed that 34, 59, and 104 MTAs involved physiological and molecular adaptation, phytohormone metabolism, and drought-inducible genes. They identified 19 pleiotropic genes associated with more than one trait and many genes related to drought tolerance indices. The genetic and genomic resources identified in this study will enable the combining of yield-related traits and sugar-related traits with agronomic value to optimize the yield of sugarcane cultivars grown under drought-stressed and non-stressed environments.
Project description:BackgroundWild diploid wheat, Triticum urartu (T. urartu) is the progenitor of bread wheat, and understanding its genetic diversity and genome function will provide considerable reference for dissecting genomic information of common wheat.ResultsIn this study, we investigated the morphological and genetic diversity and population structure of 238 T. urartu accessions collected from different geographic regions. This collection had 19.37 alleles per SSR locus and its polymorphic information content (PIC) value was 0.76, and the PIC and Nei's gene diversity (GD) of high-molecular-weight glutenin subunits (HMW-GSs) were 0.86 and 0.88, respectively. UPGMA clustering analysis indicated that the 238 T. urartu accessions could be classified into two subpopulations, of which Cluster I contained accessions from Eastern Mediterranean coast and those from Mesopotamia and Transcaucasia belonged to Cluster II. The wide range of genetic diversity along with the manageable number of accessions makes it one of the best collections for mining valuable genes based on marker-trait association. Significant associations were observed between simple sequence repeats (SSR) or HMW-GSs and six morphological traits: heading date (HD), plant height (PH), spike length (SPL), spikelet number per spike (SPLN), tiller angle (TA) and grain length (GL).ConclusionsOur data demonstrated that SSRs and HMW-GSs were useful markers for identification of beneficial genes controlling important traits in T. urartu, and subsequently for their conservation and future utilization, which may be useful for genetic improvement of the cultivated hexaploid wheat.
Project description:BackgroundRye is an important European crop used for food, feed, and bioenergy. Several quality and yield-related traits are of agronomic relevance for rye breeding programs. Profound knowledge of the genetic architecture of these traits is needed to successfully implement marker-assisted selection programs. Nevertheless, little is known on quantitative loci underlying important agronomic traits in rye.ResultsWe used 440 F(3:4) inbred lines from two biparental populations (Pop-A, Pop-B) fingerprinted with about 800 to 900 SNP, SSR and/or DArT markers and outcrossed them to a tester for phenotyping. The resulting hybrids and their parents were evaluated for grain yield, single-ear weight, test weight, plant height, thousand-kernel weight, falling number, protein, starch, soluble and total pentosan contents in up to ten environments in Central Europe. The quality of the phenotypic data was high reflected by moderate to high heritability estimates. QTL analyses revealed a total of 31 QTL for Pop-A and 52 for Pop-B. QTL x environment interactions were significant (P < 0.01) in most cases but variance of QTL main effect was more prominent.ConclusionsQTL mapping was successfully applied based on two segregating rye populations. QTL underlying grain yield and several quality traits had small effects. In contrast, thousand-kernel weight, test weight, falling number and starch content were affected by several major QTL with a high frequency of occurrence in cross validation. These QTL explaining a large proportion of the genotypic variance can be exploited in marker-assisted selection programs and are candidates for further genetic dissection.
Project description:Individual variations of white matter (WM) tracts are known to be associated with various cognitive and neuropsychiatric traits. Diffusion tensor imaging (DTI) and genome-wide single-nucleotide polymorphism (SNP) data from 17,706 UK Biobank participants offer the opportunity to identify novel genetic variants of WM tracts and explore the genetic overlap with other brain-related complex traits. We analyzed the genetic architecture of 110 tract-based DTI parameters, carried out genome-wide association studies (GWAS), and performed post-GWAS analyses, including association lookups, gene-based association analysis, functional gene mapping, and genetic correlation estimation. We found that DTI parameters are substantially heritable for all WM tracts (mean heritability 48.7%). We observed a highly polygenic architecture of genetic influence across the genome (p value = 1.67 × 10-05) as well as the enrichment of genetic effects for active SNPs annotated by central nervous system cells (p value = 8.95 × 10-12). GWAS identified 213 independent significant SNPs associated with 90 DTI parameters (696 SNP-level and 205 locus-level associations; p value < 4.5 × 10-10, adjusted for testing multiple phenotypes). Gene-based association study prioritized 112 significant genes, most of which are novel. More importantly, association lookups found that many of the novel SNPs and genes of DTI parameters have previously been implicated with cognitive and mental health traits. In conclusion, the present study identifies many new genetic variants at SNP, locus and gene levels for integrity of brain WM tracts and provides the overview of pleiotropy with cognitive and mental health traits.