The UCR Minicore: a valuable resource for cowpea research and breeding

ABSTRACTIncorporation of new sources of genetic diversity into plant breeding programs is crucial for continuing to improve yield and quality, as well as tolerance to abiotic and biotic stresses. A minicore (the “UCR Minicore”) composed of 368 worldwide accessions of cultivated cowpea has been assembled, having been derived from the University of California, Riverside cowpea collection. High-density genotyping with 51,128 SNPs followed by principal component and genetic assignment analyses identified six subpopulations in the UCR Minicore, mainly differentiated by cultivar group and geographic origin. All six subpopulations were present to some extent in West African material, suggesting that West Africa is a center of diversity for cultivated cowpea. Additionally, population structure analyses supported two routes of introduction of cowpea into the U.S.: (1) from Spain to the southwest U.S. through Northern Mexico, and (2) from Africa to the southeast U.S. via the Caribbean. Genome-wide association studies (GWAS) of important agronomic traits including flowering time, resulted in the identification of significant SNPs for all traits and environments. The mapping resolution achieved by high-density genotyping of this diverse minicore collection allowed the identification of strong candidate genes, including orthologs of the Arabidopsis FLOWERING LOCUS T. In summary, this diverse, yet compact cowpea collection constitutes a suitable resource to identify loci controlling complex traits, consequently providing markers to assist with breeding to improve this crop of high relevance to global food and nutritional security.

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Exome resequencing and GWAS for growth, ecophysiology, and chemical and metabolomic composition of wood of Populus trichocarpa

BMC Genomics ◽

10.1186/s12864-019-6160-9 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 1

Author(s):

Fernando P. Guerra ◽

Haktan Suren ◽

Jason Holliday ◽

James H. Richards ◽

Oliver Fiehn ◽

...

Keyword(s):

Biomass Production ◽

Complex Traits ◽

Association Studies ◽

Populus Trichocarpa ◽

Significant Snps ◽

Snp Markers ◽

Exome Capture ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Improvement Programs

Abstract Background Populus trichocarpa is an important forest tree species for the generation of lignocellulosic ethanol. Understanding the genomic basis of biomass production and chemical composition of wood is fundamental in supporting genetic improvement programs. Considerable variation has been observed in this species for complex traits related to growth, phenology, ecophysiology and wood chemistry. Those traits are influenced by both polygenic control and environmental effects, and their genome architecture and regulation are only partially understood. Genome wide association studies (GWAS) represent an approach to advance that aim using thousands of single nucleotide polymorphisms (SNPs). Genotyping using exome capture methodologies represent an efficient approach to identify specific functional regions of genomes underlying phenotypic variation. Results We identified 813 K SNPs, which were utilized for genotyping 461 P. trichocarpa clones, representing 101 provenances collected from Oregon and Washington, and established in California. A GWAS performed on 20 traits, considering single SNP-marker tests identified a variable number of significant SNPs (p-value < 6.1479E-8) in association with diameter, height, leaf carbon and nitrogen contents, and δ15N. The number of significant SNPs ranged from 2 to 220 per trait. Additionally, multiple-marker analyses by sliding-windows tests detected between 6 and 192 significant windows for the analyzed traits. The significant SNPs resided within genes that encode proteins belonging to different functional classes as such protein synthesis, energy/metabolism and DNA/RNA metabolism, among others. Conclusions SNP-markers within genes associated with traits of importance for biomass production were detected. They contribute to characterize the genomic architecture of P. trichocarpa biomass required to support the development and application of marker breeding technologies.

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Genome-wide Identification of Powdery Mildew Resistance in Common Bean

10.21203/rs.3.rs-27731/v2 ◽

2020 ◽

Author(s):

Papias Hongera Binagwa ◽

Sy M. Traore ◽

Marceline Egnin ◽

Gregory C. Bernard ◽

Inocent Ritte ◽

...

Keyword(s):

Disease Resistance ◽

Common Bean ◽

Resistance Genes ◽

Agronomic Traits ◽

Association Studies ◽

Significant Snps ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Disease Resistance Protein ◽

Resistance Protein

Abstract Background: Genome-wide association studies (GWAS) was utilized to detect genetic variations related to the powdery mildew (PM) resistance and several agronomic traits in common bean. However, its application in common bean and the PM interactions to identify genes and their location in the common bean genome has not been fully addressed. Results: Genome-wide association studies (GWAS) through marker-trait association are useful molecular tools for the identification of disease resistance and other agronomic traits. SNP genotyping with a BeadChip containing 5398 SNPs was used to detect genetic variations related to resistance to PM disease in a panel of 206 genotypes grown under field conditions for two consecutive years. Significant SNPs identified on chromosomes 4 and 10 (Pv04 and Pv10) were repeatable, confirming the reliability of the phenotypic data scored from the genotypes grown in two locations within two years. A cluster of resistance genes was revealed on the chromosome 4 of common bean genome among which CNL and TNL like resistance genes were identified. Furthermore, two resistance genes Phavu_010G1320001g and Phavu_010G136800g were also identified on Pv10; further sequence analysis showed that these genes were homologs to the Arabidopsis disease resistance protein (RLM1A-like) and the putative disease resistance protein (At4g11170.1), respectively. Two LRR receptor-like kinases (RLK) were also identified on Pv11 in samples collected in 2018 only. Many genes encoding auxin-responsive protein, TIFY10A protein, growth-regulating factor 5-like, ubiquitin-like protein, cell wall protein RBR3-like protein related to PM resistance were identified nearby significant SNPs. These results suggested that the resistance to PM pathogen involves a network of many genes constitutively co-expressed and may generate several layers of defense barriers or inducible reactions.Conclusion: Our results provide new insights into common bean and PM interactions, and revealed putative resistance genes as well as their location on common bean genome that could be used for marker-assisted selection, functional genomic study approaches to confirm the role of these putative genes; hence, developing common bean resistance lines to the PM disease.

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Quantifying genetic heterogeneity between continental populations for human height and body mass index

Scientific Reports ◽

10.1038/s41598-021-84739-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jing Guo ◽

Andrew Bakshi ◽

Ying Wang ◽

Longda Jiang ◽

Loic Yengo ◽

...

Keyword(s):

Body Mass Index ◽

Body Mass ◽

Complex Traits ◽

Association Studies ◽

Significant Snps ◽

Complex Trait ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Population Difference ◽

Genome Wide

AbstractGenome-wide association studies (GWAS) in samples of European ancestry have identified thousands of genetic variants associated with complex traits in humans. However, it remains largely unclear whether these associations can be used in non-European populations. Here, we seek to quantify the proportion of genetic variation for a complex trait shared between continental populations. We estimated the between-population correlation of genetic effects at all SNPs ($$r_{g}$$ r g ) or genome-wide significant SNPs ($$r_{{g\left( {GWS} \right)}}$$ r g GWS ) for height and body mass index (BMI) in samples of European (EUR; $$n = 49,839$$ n = 49 , 839 ) and African (AFR; $$n = 17,426$$ n = 17 , 426 ) ancestry. The $$\hat{r}_{g}$$ r ^ g between EUR and AFR was 0.75 ($${\text{s}}.{\text{e}}. = 0.035$$ s . e . = 0.035 ) for height and 0.68 ($${\text{s}}.{\text{e}}. = 0.062$$ s . e . = 0.062 ) for BMI, and the corresponding $$\hat{r}_{{g\left( {GWS} \right)}}$$ r ^ g GWS was 0.82 ($${\text{s}}.{\text{e}}. = 0.030$$ s . e . = 0.030 ) for height and 0.87 ($${\text{s}}.{\text{e}}. = 0.064$$ s . e . = 0.064 ) for BMI, suggesting that a large proportion of GWAS findings discovered in Europeans are likely applicable to non-Europeans for height and BMI. There was no evidence that $$\hat{r}_{g}$$ r ^ g differs in SNP groups with different levels of between-population difference in allele frequency or linkage disequilibrium, which, however, can be due to the lack of power.

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Genome-wide Identification of Powdery Mildew Resistance in Common Bean

10.21203/rs.3.rs-27731/v3 ◽

2020 ◽

Author(s):

Papias Hongera Binagwa ◽

Sy M. Traore ◽

Marceline Egnin ◽

Gregory C. Bernard ◽

Inocent Ritte ◽

...

Keyword(s):

Disease Resistance ◽

Common Bean ◽

Resistance Genes ◽

Agronomic Traits ◽

Association Studies ◽

Significant Snps ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Disease Resistance Protein ◽

Resistance Protein

Abstract Background: Genome-wide association studies (GWAS) have been utilized to detect genetic variations related to the powdery mildew (PM) resistance and several agronomic traits in common bean. However, its application in common bean and the PM interactions to identify genes and their location in the common bean genome has not been fully addressed.Results: Genome-wide association studies (GWAS) through marker-trait association are useful molecular tools for the identification of disease resistance and other agronomic traits. SNP genotyping with a BeadChip containing 5398 SNPs was used to detect genetic variations related to resistance to PM disease in a panel of 211 genotypes grown under field conditions for two consecutive years. Significant SNPs identified on chromosomes Pv04 and Pv10 were repeatable, confirming the reliability of the phenotypic data scored from the genotypes grown in two locations within two years. A cluster of resistance genes was revealed on the Pv04 of common bean genome among which CNL and TNL like resistance genes were identified. Furthermore, two resistance genes Phavu_010G1320001g and Phavu_010G136800g were also identified on Pv10; further sequence analysis showed that these genes were homologs to the Arabidopsis disease resistance protein (RLM1A-like) and the putative disease resistance protein (At4g11170.1), respectively. Two LRR receptor-like kinases (RLK) were also identified on Pv11 in samples collected in 2018 only. Many genes encoding auxin-responsive protein, TIFY10A protein, growth-regulating factor 5-like, ubiquitin-like protein, cell wall protein RBR3-like protein related to PM resistance were identified nearby significant SNPs. These results suggested that the resistance to PM pathogen involves a network of many genes constitutively co-expressed and may generate several layers of defense barriers or inducible reactions.Conclusion: Our results provide new insights into common bean and PM interactions, and revealed putative resistance genes as well as their location on common bean genome that could be used for marker-assisted selection, functional genomic study approaches to confirm the role of these putative genes; hence, developing common bean resistance lines to the PM disease.

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Quantifying genetic heterogeneity between continental populations for human height and body mass index

10.1101/839373 ◽

2019 ◽

Cited By ~ 2

Author(s):

Jing Guo ◽

Andrew Bakshi ◽

Ying Wang ◽

Longda Jiang ◽

Loic Yengo ◽

...

Keyword(s):

Body Mass Index ◽

Body Mass ◽

Complex Traits ◽

Association Studies ◽

Significant Snps ◽

Complex Trait ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Population Difference ◽

Genome Wide

AbstractGenome-wide association studies (GWAS) in samples of European ancestry have identified thousands of genetic variants associated with complex traits in humans. However, it remains largely unclear whether these associations can be used in non-European populations. Here, we seek to quantify the proportion of genetic variation for a complex trait shared between continental populations. We estimated the between-population correlation of genetic effects at all SNPs (rg) or genome-wide significant SNPs (rg(GWS)) for height and body mass index (BMI) in samples of European (EUR; n = 49,839) and African (AFR; n = 17,426) ancestry. The between EUR and AFR was 0.75 (s. e. = 0.035) for height and 0.68 (s. e. = 0.062) for BMI, and the corresponding was 0.82 (s. e. = 0.030) for height and 0.87 (s. e. = 0.064) for BMI, suggesting that a large proportion of GWAS findings discovered in Europeans are likely applicable to non-Europeans for height and BMI. There was no evidence that differs in SNP groups with different levels of between-population difference in allele frequency or linkage disequilibrium, which, however, can be due to the lack of power.

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Strategies to Increase Prediction Accuracy in Genomic Selection of Complex Traits in Alfalfa (Medicago sativa L.)

10.20944/preprints202110.0305.v1 ◽

2021 ◽

Author(s):

Cesar A Medina ◽

Harpreet Kaur ◽

Ian Ray ◽

Long-Xi Yu

Keyword(s):

Salt Stress ◽

Abiotic Stress ◽

Genomic Selection ◽

Complex Traits ◽

Prediction Accuracy ◽

Agronomic Traits ◽

Association Studies ◽

Breeding Value ◽

Genome Wide Association Studies ◽

Genome Wide

Agronomic traits such as biomass yield and abiotic stress tolerance are genetically complex and challenging to improve by conventional breeding strategies. Genomic selection (GS) is an alternative approach in which genome-wide markers are used to determine the genomic estimated breeding value (GEBV) of individuals in a population. In alfalfa, previous results indicated that low to moderate prediction accuracy values (<70%) were obtained in complex traits such as yield and abiotic stress resistance. There is a need to increase the prediction value in order to employ GS in breeding programs. In this paper we reviewed different statistic models and their applications in polyploid crops including alfalfa. Specifically, we used empirical data affiliated with alfalfa yield under salt stress to investigate approaches which use DNA marker importance values derived from machine learning models, and genome-wide association studies (GWAS) of marker-trait association scores based on different GWASpoly models, in weighted GBLUP analyses. This approach increased prediction accuracies from 50% to more than 80% for alfalfa yield under salt stress. This is the first report in alfalfa to use variable importance and GWAS-assisted approaches to increase the prediction accuracy of GS, thus helping to select superior alfalfa lines based on their GEBVs.

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A modified forward multiple regression in high-density genome-wide association studies for complex traits

Genetic Epidemiology ◽

10.1002/gepi.20404 ◽

2009 ◽

Vol 33 (6) ◽

pp. 518-525 ◽

Cited By ~ 6

Author(s):

Xiangjun Gu ◽

Ralph F. Frankowski ◽

Gary L. Rosner ◽

Mary Relling ◽

Bo Peng ◽

...

Keyword(s):

Multiple Regression ◽

Complex Traits ◽

Association Studies ◽

High Density ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide

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Genome-level diversification of eight ancient tea populations in the Guizhou and Yunnan regions identifies candidate genes for core agronomic traits

Horticulture Research ◽

10.1038/s41438-021-00617-9 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Litang Lu ◽

Hufang Chen ◽

Xiaojing Wang ◽

Yichen Zhao ◽

Xinzhuan Yao ◽

...

Keyword(s):

Genetic Diversity ◽

Candidate Genes ◽

Agronomic Traits ◽

Association Studies ◽

Functional Characterization ◽

Principal Component ◽

Tea Plant ◽

Guizhou Province ◽

Genome Wide Association Studies ◽

Tea Plants

AbstractThe ancient tea plant, as a precious natural resource and source of tea plant genetic diversity, is of great value for studying the evolutionary mechanism, diversification, and domestication of plants. The overall genetic diversity among ancient tea plants and the genetic changes that occurred during natural selection remain poorly understood. Here, we report the genome resequencing of eight different groups consisting of 120 ancient tea plants: six groups from Guizhou Province and two groups from Yunnan Province. Based on the 8,082,370 identified high-quality SNPs, we constructed phylogenetic relationships, assessed population structure, and performed genome-wide association studies (GWAS). Our phylogenetic analysis showed that the 120 ancient tea plants were mainly clustered into three groups and five single branches, which is consistent with the results of principal component analysis (PCA). Ancient tea plants were further divided into seven subpopulations based on genetic structure analysis. Moreover, it was found that the variation in ancient tea plants was not reduced by pressure from the external natural environment or artificial breeding (nonsynonymous/synonymous = 1.05). By integrating GWAS, selection signals, and gene function prediction, four candidate genes were significantly associated with three leaf traits, and two candidate genes were significantly associated with plant type. These candidate genes can be used for further functional characterization and genetic improvement of tea plants.

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Using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock

10.1101/2020.04.16.044685 ◽

2020 ◽

Author(s):

Biaty Raymond ◽

Loic Yengo ◽

Roy Costilla ◽

Chris Schrooten ◽

Aniek C. Bouwman ◽

...

Keyword(s):

Complex Traits ◽

Prior Information ◽

Genetic Variance ◽

Association Studies ◽

Mammalian Species ◽

Significant Proportion ◽

Significant Snps ◽

Genome Wide Association Studies ◽

Randomized Sampling ◽

Human Height

Genome-Wide Association Studies (GWAS) in large human cohorts have identified thousands of loci associated with complex traits and diseases. For identifying the genes and gene-associated variants that underlie complex traits in livestock, especially where sample sizes are limiting, it may help to integrate the results of GWAS for equivalent traits in humans as prior information. In this study, we sought to investigate the usefulness of results from a GWAS on human height as prior information for identifying the genes and gene-associated variants that affect stature in cattle, using GWAS summary data on samples sizes of 700,000 and 58,265 for humans and cattle, respectively. Using Fisher's exact test, we observed a significant proportion of cattle stature-associated genes (30/77) that are also associated with human height (odds ratio = 5.1, p = 3.1e-10). Result of randomized sampling tests showed that cattle orthologs of human height-associated genes, hereafter referred to as candidate genes (C-genes), were more enriched for cattle stature GWAS signals than random samples of genes in the cattle genome (p=0.01). Randomly sampled SNPs within the C-genes also tend to explain more genetic variance for cattle stature (up to 13.2%) than randomly sampled SNPs within random cattle genes (p=0.09). The most significant SNPs from a cattle GWAS for stature within the C-genes did not explain more genetic variance for cattle stature than the most significant SNPs within random cattle genes (p=0.87). Altogether, our findings support previous studies that suggest a similarity in the genetic regulation of height across mammalian species. However, with the availability of a powerful GWAS for stature that combined data from 8 cattle breeds, prior information from human-height GWAS does not seem to provide any additional benefit with respect to the identification of genes and gene-associated variants that affect stature in cattle.

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VarGoats project: a dataset of 1159 whole-genome sequences to dissect Capra hircus global diversity

Genetics Selection Evolution ◽

10.1186/s12711-021-00659-6 ◽

2021 ◽

Vol 53 (1) ◽

Author(s):

Laure Denoyelle ◽

Estelle Talouarn ◽

Philippe Bardou ◽

Licia Colli ◽

Adriana Alberti ◽

...

Keyword(s):

Complex Traits ◽

Association Studies ◽

Geographic Origin ◽

Genetic Distances ◽

Capra Hircus ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Selection Processes ◽

Genome Wide ◽

Broad Variety

Abstract Background Since their domestication 10,500 years ago, goat populations with distinctive genetic backgrounds have adapted to a broad variety of environments and breeding conditions. The VarGoats project is an international 1000-genome resequencing program designed to understand the consequences of domestication and breeding on the genetic diversity of domestic goats and to elucidate how speciation and hybridization have modeled the genomes of a set of species representative of the genus Capra. Findings A dataset comprising 652 sequenced goats and 507 public goat sequences, including 35 animals representing eight wild species, has been collected worldwide. We identified 74,274,427 single nucleotide polymorphisms (SNPs) and 13,607,850 insertion-deletions (InDels) by aligning these sequences to the latest version of the goat reference genome (ARS1). A Neighbor-joining tree based on Reynolds genetic distances showed that goats from Africa, Asia and Europe tend to group into independent clusters. Because goat breeds from Oceania and Caribbean (Creole) all derive from imported animals, they are distributed along the tree according to their ancestral geographic origin. Conclusions We report on an unprecedented international effort to characterize the genome-wide diversity of domestic goats. This large range of sequenced individuals represents a unique opportunity to ascertain how the demographic and selection processes associated with post-domestication history have shaped the diversity of this species. Data generated for the project will also be extremely useful to identify deleterious mutations and polymorphisms with causal effects on complex traits, and thus will contribute to new knowledge that could be used in genomic prediction and genome-wide association studies.

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