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:BACKGROUND: Rye 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. RESULTS: We 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. CONCLUSIONS: QTL 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: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:Wild 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.In 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).Our 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: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.
Project description:The genetic architecture of complex traits underlying physiology and disease in most organisms remains elusive. We still know little about the number of genes that underlie these traits, the magnitude of their effects, or the extent to which they interact. Chromosome substitution strains (CSSs) enable statistically powerful studies based on testing engineered inbred strains that have single, unique, and nonoverlapping genetic differences, thereby providing measures of phenotypic effects that are attributable to individual chromosomes. Here, we report a study of phenotypic effects and gene interactions for 90 blood, bone, and metabolic traits in a mouse CSS panel and 54 traits in a rat CSS panel. Two key observations emerge about the genetic architecture of these traits. First, the traits tend to be highly polygenic: across the genome, many individual chromosome substitutions each had significant phenotypic effects and, within each of the chromosomes studied, multiple distinct loci were found. Second, strong epistasis was found among the individual chromosomes. Specifically, individual chromosome substitutions often conferred surprisingly large effects (often a substantial fraction of the entire phenotypic difference between the parental strains), with the result that the sum of these individual effects often dramatically exceeded the difference between the parental strains. We suggest that strong, pervasive epistasis may reflect the presence of several phenotypically-buffered physiological states. These results have implications for identification of complex trait genes, developmental and physiological studies of phenotypic variation, and opportunities to engineer phenotypic outcomes in complex biological systems.
Project description:BackgroundGastropod snails remain strongly understudied, despite their important role in transmitting parasitic diseases. Knowledge of their distribution and population dynamics increases our understanding of the processes driving disease transmission. We report the first study to use high-throughput sequencing (HTS) to elucidate the population genetic structure of the hermaphroditic snail Bulinus truncatus (Gastropoda, Heterobranchia) on a regional (17-150 km) and inter-regional (1000-5400 km) scale. This snail species acts as an intermediate host of Schistosoma haematobium and Schistosoma bovis, which cause human and animal schistosomiasis respectively.MethodsBulinus truncatus snails were collected in Senegal, Cameroon, Egypt and France and identified through DNA barcoding. A single-end genotyping-by-sequencing (GBS) library, comprising 87 snail specimens from the respective countries, was built and sequenced on an Illumina HiSeq 2000 platform. Reads were mapped against S. bovis and S. haematobium reference genomes to identify schistosome infections, and single nucleotide polymorphisms (SNPs) were scored using the Stacks pipeline. These SNPs were used to estimate genetic diversity, assess population structure and construct phylogenetic trees of B. truncatus.ResultsA total of 10,750 SNPs were scored and used in downstream analyses. The phylogenetic analysis identified five clades, each consisting of snails from a single country but with two distinct clades within Senegal. Genetic diversity was low in all populations, reflecting high selfing rates, but varied between locations due to habitat variability. Significant genetic differentiation and isolation by distance patterns were observed at both spatial scales, indicating that gene flow is not strong enough to counteract the effects of population bottlenecks, high selfing rates and genetic drift. Remarkably, the population genetic differentiation on a regional scale (i.e. within Senegal) was as large as that between populations on an inter-regional scale. The blind GBS technique was able to pick up parasite DNA in snail tissue, demonstrating the potential of HTS techniques to further elucidate the role of snail species in parasite transmission.ConclusionsHTS techniques offer a valuable toolbox to further investigate the population genetic patterns of intermediate schistosome host snails and the role of snail species in parasite transmission.
Project description:Gossypium hirsutum L. represents the largest source of textile fibre, and China is one of the largest cotton-producing and cotton-consuming countries in the world. To investigate the genetic architecture of the agronomic traits of upland cotton in China, a diverse and nationwide population containing 503 G. hirsutum accessions was collected for a genome-wide association study (GWAS) on 16 agronomic traits. The accessions were planted in four places from 2012 to 2013 for phenotyping. The CottonSNP63K array and a published high-density map based on this array were used for genotyping. The 503 G. hirsutum accessions were divided into three subpopulations based on 11 975 quantified polymorphic single-nucleotide polymorphisms (SNPs). By comparing the genetic structure and phenotypic variation among three genetic subpopulations, seven geographic distributions and four breeding periods, we found that geographic distribution and breeding period were not the determinants of genetic structure. In addition, no obvious phenotypic differentiations were found among the three subpopulations, even though they had different genetic backgrounds. A total of 324 SNPs and 160 candidate quantitative trait loci (QTL) regions were identified as significantly associated with the 16 agronomic traits. A network was established for multieffects in QTLs and interassociations among traits. Thirty-eight associated regions had pleiotropic effects controlling more than one trait. One candidate gene, Gh_D08G2376, was speculated to control the lint percentage (LP). This GWAS is the first report using high-resolution SNPs in upland cotton in China to comprehensively investigate agronomic traits, and it provides a fundamental resource for cotton genetic research and breeding.