Genome-wide association study of agronomic traits in rice cultivated in temperate regions.
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ABSTRACT: Rice plants are sensitive to the agro-climate conditions, being photoperiod one of main factor contributing to their adaptation to the region where they are grown. Dissecting the genetic bases underlying diversity in rice populations adapted to specific environmental conditions is a fundamental resource for breeding. In this study we have analysed a collection of japonica varieties adapted to temperate regions to perform association studies with traits of high agronomical interest such as heading date, plant height, number of panicles, panicle length and number of grains per panicle.We have performed a genome wide association study using a panel of 1713 SNPs that, based on previous linkage disequilibrium estimations, provides a full coverage of the whole genome. We have found a total of 43 SNPs associated with variations in the different traits. The identified SNPs were distributed across the genome except in chromosome 12, where no associated SNPs were found. The inspection of the vicinity of these markers also revealed a set of genes associated with physiological functions strongly linked to agronomic traits. Of special relevance are two genes involved in gibberellin homeostasis that are associated with plant height and panicle length. We also detected novel associated sites with heading date, panicle length and number of grain per panicle.We have identified loci associated with important agronomic traits among cultivars adapted to temperate conditions. Some of these markers co-localized with already known genes or QTLs, but the association also provided novel molecular markers that can be of help to elucidate the complicated genetic mechanism controlling important agronomic traits, as flowering regulation in the non-dependent photoperiod pathway. The detected associated markers may provide important tools for the genetic improvement of rice cultivars in temperate regions.
<h4>Background</h4>Rice plants are sensitive to the agro-climate conditions, being photoperiod one of main factor contributing to their adaptation to the region where they are grown. Dissecting the genetic bases underlying diversity in rice populations adapted to specific environmental conditions is a fundamental resource for breeding. In this study we have analysed a collection of japonica varieties adapted to temperate regions to perform association studies with traits of high agronomical inte ...[more]
Project description:The population growth trend in recent decades has resulted in continuing efforts to guarantee food security in which leguminous plants, such as the common bean (Phaseolus vulgaris L.), play a particularly important role as they are relatively cheap and have high nutritional value. To meet this demand for food, the main target for genetic improvement programs is to increase productivity, which is a complex quantitative trait influenced by many component traits. This research aims to identify Quantitative Trait Nucleotides (QTNs) associated with productivity and its components using multi-locus genome-wide association studies. Ten morpho-agronomic traits [plant height (PH), first pod insertion height (FPIH), number of nodules (NN), pod length (PL), total number of pods per plant (NPP), number of locules per pod (LP), number of seeds per pod (SP), total seed weight per plant (TSW), 100-seed weight (W100), and grain yield (YLD)] were evaluated in four environments for 178 Mesoamerican common bean domesticated accessions belonging to the Brazilian Diversity Panel. In order to identify stable QTNs, only those identified by multiple methods (mrMLM, FASTmrMLM, pLARmEB, and ISIS EM-BLASSO) or in multiple environments were selected. Among the identified QTNs, 64 were detected at least thrice by different methods or in different environments, and 39 showed significant phenotypic differences between their corresponding alleles. The alleles that positively increased the corresponding traits, except PH (for which lower values are desired), were considered favorable alleles. The most influenced trait by the accumulation of favorable alleles was PH, showing a 51.7% reduction, while NN, TSW, YLD, FPIH, and NPP increased between 18 and 34%. Identifying QTNs in several environments (four environments and overall adjusted mean) and by multiple methods reinforces the reliability of the associations obtained and the importance of conducting these studies in multiple environments. Using these QTNs through molecular techniques for genetic improvement, such as marker-assisted selection or genomic selection, can be a strategy to increase common bean production.
Project description:Identification of trait-associated metabolites will advance the knowledge and understanding of the biosynthetic and catabolic pathways that are relevant to the complex traits of interest. In the past, the association between metabolites (treated as quantitative traits) and genetic variants (e.g., SNPs) has been extensively studied using metabolomic quantitative trait locus (mQTL) mapping. Nevertheless, the research on the association between metabolites with agronomic traits has been inadequate. In practice, the regular approaches for QTL mapping analysis may be adopted for metabolites-phenotypes association analysis due to the similarity in data structure of these two types of researches. In the study, we compared four regular QTL mapping approaches, i.e., simple linear regression (LR), linear mixed model (LMM), Bayesian analysis with spike-slab priors (Bayes B) and least absolute shrinkage and selection operator (LASSO), by testing their performances on the analysis of metabolome-phenotype associations. Simulation studies showed that LASSO had the higher power and lower false positive rate than the other three methods. We investigated the associations of 839 metobolites with five agronomic traits in a collection of 533 rice varieties. The results implied that a total of 25 metabolites were significantly associated with five agronomic traits. Literature search and bioinformatics analysis indicated that the identified 25 metabolites are significantly involved in some growth and development processes potentially related to agronomic traits. We also explored the predictability of agronomic traits based on the 839 metabolites through cross-validation, which showed that metabolomic prediction was efficient and its application in plant breeding has been justified.
Project description:Peach (Prunus persica L.) is a highly valuable crop species and is recognized by molecular researchers as a model fruit for the Rosaceae family. Using whole-genome sequencing data generated from 129 peach accessions, here we perform a comprehensive genome-wide association study for 12 key agronomic traits. We show that among the 10 qualitative traits investigated, nine exhibit consistent and more precise association signals than previously identified by linkage analysis. For two of the qualitative traits, we describe candidate genes, one potentially involved in cell death and another predicted to encode an auxin-efflux carrier, that are highly associated with fruit shape and non-acidity, respectively. Furthermore, we find that several genomic regions harbouring association signals for fruit weight and soluble solid content overlapped with predicted selective sweeps that occurred during peach domestication and improvement. Our findings contribute to the large-scale characterization of genes controlling agronomic traits in peach.
Project description:BACKGROUND:Cultivated rice (Oryza sativa L.) is one of the staple food for over half of the world's population. Thus, improvement of cultivated rice is important for the development of the world. It has been shown that abundant elite genes exist in rice landraces in previous studies. RESULTS:A genome-wide association study (GWAS) performed with EMMAX for 12 agronomic traits measured in both Guangzhou and Hangzhou was carried out using 150 accessions of Ting's core collection selected based on 48 phenotypic traits from 2262 accessions of Ting's collection, the GWAS included more than 3.8 million SNPs. Within Ting's core collection, which has a simple population structure, low relatedness, and rapid linkage disequilibrium (LD) decay, we found 32 peaks located closely to previously cloned genes such as Hd1, SD1, Ghd7, GW8, and GL7 or mapped QTL, and these loci might be natural variations in the cloned genes or QTL which influence potentially agronomic traits. Furthermore, we also detected 32 regions where new genes might be located, and some peaks of these new candidate genes such as the signal on chromosome 11 for heading days were even higher than that of Hd1. Detailed annotation of these significant loci were shown in this study. Moreover, according to the estimated LD decay distance of 100 to 350?kb on the 12 chromosomes in this study, we found 13 identical significant regions in the two locations. CONCLUSIONS:This research provided important information for further mining these elite genes within Ting's core collection and using them for rice breeding.
Project description:Olive (Olea europaea L.) is one of the most economically and historically important fruit crops worldwide. Genetic progress for valuable agronomic traits has been slow in olive despite its importance and benefits. Advances in next generation sequencing technologies provide inexpensive and highly reproducible genotyping approaches such as Genotyping by Sequencing, enabling genome wide association study (GWAS). Here we present the first comprehensive GWAS study on olive using GBS. A total of 183 accessions (FULL panel) were genotyped using GBS, 94 from the Turkish Olive GenBank Resource (TOGR panel) and 89 from the USDA-ARS National Clonal Germplasm Repository (NCGR panel) in the USA. After filtering low quality and redundant markers, GWAS was conducted using 24,977 SNPs in FULL, TOGR and NCGR panels. In total, 52 significant associations were detected for leaf length, fruit weight, stone weight and fruit flesh to pit ratio using the MLM_K. Significant GWAS hits were mapped to their positions and 19 candidate genes were identified within a 10-kb distance of the most significant SNP. Our findings provide a framework for the development of markers and identification of candidate genes that could be used in olive breeding programs.
Project description:Peanut (Arachis hypogaea) consists of two subspecies, hypogaea and fastigiata, and has been cultivated worldwide for hundreds of years. Here, 158 peanut accessions were selected to dissect the molecular footprint of agronomic traits related to domestication using specific-locus amplified fragment sequencing (SLAF-seq method). Then, a total of 17,338 high-quality single nucleotide polymorphisms (SNPs) in the whole peanut genome were revealed. Eleven agronomic traits in 158 peanut accessions were subsequently analyzed using genome-wide association studies (GWAS). Candidate genes responsible for corresponding traits were then analyzed in genomic regions surrounding the peak SNPs, and 1,429 genes were found within 200 kb windows centerd on GWAS-identified peak SNPs related to domestication. Highly differentiated genomic regions were observed between hypogaea and fastigiata accessions using FST values and sequence diversity (π) ratios. Among the 1,429 genes, 662 were located on chromosome A3, suggesting the presence of major selective sweeps caused by artificial selection during long domestication. These findings provide a promising insight into the complicated genetic architecture of domestication-related traits in peanut, and reveal whole-genome SNP markers of beneficial candidate genes for marker-assisted selection (MAS) in future breeding programs.
Project description:Uncovering the genetic basis of key agronomic traits, and particularly of drought tolerance, addresses an important priority for durum wheat improvement. Here, a genome-wide association study (GWAS) in 493 durum wheat accessions representing a worldwide collection was employed to address the genetic basis of 17 agronomically important traits and a drought wilting score. Using a linear mixed model with 4 inferred subpopulations and a kinship matrix, we identified 90 marker-trait-associations (MTAs) defined by 78 markers. These markers could be merged into 44 genomic loci by linkage disequilibrium (r 2 > 0.2). Based on sequence alignment of the markers to the reference genome of bread wheat, we identified 14 putative candidate genes involved in enzymes, hormone-response, and transcription factors. The GWAS in durum wheat and a previous quantitative trait locus (QTL) analysis in bread wheat identified a consensus QTL locus.4B.1 conferring drought tolerance, which was further scanned for the presence of potential candidate genes. A haplotype analysis of this region revealed that two minor haplotypes were associated with both drought tolerance and reduced plant stature, thought to be the effect of linkage with the semi-dwarfing gene Rht-B1. Haplotype variants in the key chromosome 4B region were informative regarding evolutionary divergence among durum, emmer and bread wheat. Over all, the data are relevant in the context of durum wheat improvement and the isolation of genes underlying variation in some important quantitative traits.
Project description:BackgroundAfrican rice, Oryza glaberrima, is an invaluable resource for rice cultivation and for the improvement of biotic and abiotic resistance properties. Since its domestication in the inner Niger delta ca. 2500?years BP, African rice has colonized a variety of ecologically and climatically diverse regions. However, little is known about the genetic basis of quantitative traits and adaptive variation of agricultural interest for this species.ResultsUsing a reference set of 163 fully re-sequenced accessions, we report the results of a Genome Wide Association Study carried out for African rice. We investigated a diverse panel of traits, including flowering date, panicle architecture and resistance to Rice yellow mottle virus. For this, we devised a pipeline using complementary statistical association methods. First, using flowering time as a target trait, we found several association peaks, one of which co-localised with a well described gene in the Asian rice flowering pathway, OsGi, and identified new genomic regions that would deserve more study. Then we applied our pipeline to panicle- and resistance-related traits, highlighting some interesting genomic regions and candidate genes. Lastly, using a high-resolution climate database, we performed an association analysis based on climatic variables, searching for genomic regions that might be involved in adaptation to climatic variations.ConclusionOur results collectively provide insights into the extent to which adaptive variation is governed by sequence diversity within the O. glaberrima genome, paving the way for in-depth studies of the genetic basis of traits of interest that might be useful to the rice breeding community.
Project description:This study presents a comprehensive study of the genetic bases controlling variation in the rice ionome employing genome-wide association studies (GWAS) with a diverse panel of indica accessions, each genotyped with 5.2 million markers. GWAS was performed for twelve elements including B, Ca, Co, Cu, Fe, K, Mg, Mn, Mo, Na, P, and Zn and four agronomic traits including days to 50% flowering, grain yield, plant height and thousand grain weight. GWAS identified 128 loci associated with the grain elements and 57 associated with the agronomic traits. There were sixteen co-localization regions containing QTL for two or more traits. Fourteen grain element quantitative trait loci were stable across growing environments, which can be strong candidates to be used in marker-assisted selection to improve the concentrations of nutritive elements in rice grain. Potential candidate genes were revealed including OsNAS3 linked to the locus that controls the variation of Zn and Co concentrations. The effects of starch synthesis and grain filling on multiple grain elements were elucidated through the likely involvement of OsSUS1 and OsGSSB1 genes. Overall, our study provides crucial insights into the genetic basis of ionomic variations in rice and will facilitate improvement in breeding for trace mineral content.
Project description:BackgroundIn this study we carried out a genome-wide association analysis for plant and grain morphology and root architecture in a unique panel of temperate rice accessions adapted to European pedo-climatic conditions. This is the first study to assess the association of selected phenotypic traits to specific genomic regions in the narrow genetic pool of temperate japonica. A set of 391 rice accessions were GBS-genotyped yielding-after data editing-57000 polymorphic and informative SNPS, among which 54% were in genic regions.ResultsIn total, 42 significant genotype-phenotype associations were detected: 21 for plant morphology traits, 11 for grain quality traits, 10 for root architecture traits. The FDR of detected associations ranged from 3 · 10-7 to 0.92 (median: 0.25). In most cases, the significant detected associations co-localised with QTLs and candidate genes controlling the phenotypic variation of single or multiple traits. The most significant associations were those for flag leaf width on chromosome 4 (FDR = 3 · 10-7) and for plant height on chromosome 6 (FDR = 0.011).ConclusionsWe demonstrate the effectiveness and resolution of the developed platform for high-throughput phenotyping, genotyping and GWAS in detecting major QTLs for relevant traits in rice. We identified strong associations that may be used for selection in temperate irrigated rice breeding: e.g. associations for flag leaf width, plant height, root volume and length, grain length, grain width and their ratio. Our findings pave the way to successfully exploit the narrow genetic pool of European temperate rice and to pinpoint the most relevant genetic components contributing to the adaptability and high yield of this germplasm. The generated data could be of direct use in genomic-assisted breeding strategies.
