Population structure of the Brachypodium species complex and genome wide association of agronomic traits in response to climate

AbstractThe development of model systems requires a detailed assessment of standing genetic variation across natural populations. The Brachypodium species complex has been promoted as a plant model for grass genomics with translational to small grain and biomass crops. To capture the genetic diversity within this species complex, thousands of Brachypodium accessions from around the globe were collected and sequenced using genotyping by sequencing (GBS). Overall, 1,897 samples were classified into two diploid or allopolyploid species and then further grouped into distinct inbred genotypes. A core set of diverse B. distachyon diploid lines were selected for whole genome sequencing and high resolution phenotyping. Genome-wide association studies across simulated seasonal environments was used to identify candidate genes and pathways tied to key life history and agronomic traits under current and future climatic conditions. A total of 8, 22 and 47 QTLs were identified for flowering time, early vigour and energy traits, respectively. Overall, the results highlight the genomic structure of the Brachypodium species complex and allow powerful complex trait dissection within this new grass model species.

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Global Diversity of the Brachypodium Species Complex as a Resource for Genome-Wide Association Studies Demonstrated for Agronomic Traits in Response to Climate

Genetics ◽

10.1534/genetics.118.301589 ◽

2018 ◽

Vol 211 (1) ◽

pp. 317-331 ◽

Cited By ~ 7

Author(s):

Pip B. Wilson ◽

Jared C. Streich ◽

Kevin D. Murray ◽

Steve R. Eichten ◽

Riyan Cheng ◽

...

Keyword(s):

Species Complex ◽

Agronomic Traits ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Global Diversity ◽

Genome Wide

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Genome-wide association studies of 14 agronomic traits in rice landraces

Nature Genetics ◽

10.1038/ng.695 ◽

2010 ◽

Vol 42 (11) ◽

pp. 961-967 ◽

Cited By ~ 1156

Author(s):

Xuehui Huang ◽

Xinghua Wei ◽

Tao Sang ◽

Qiang Zhao ◽

Qi Feng ◽

...

Keyword(s):

Agronomic Traits ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Rice Landraces ◽

Genome Wide

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Genome-wide association study of agronomic traits in bread wheat reveals novel putative alleles for future breeding programs

BMC Plant Biology ◽

10.1186/s12870-019-2165-4 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 11

Author(s):

Yousef Rahimi ◽

Mohammad Reza Bihamta ◽

Alireza Taleei ◽

Hadi Alipour ◽

Pär K. Ingvarsson

Keyword(s):

Bread Wheat ◽

Genome Wide Association Study ◽

Agronomic Traits ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Wheat Varieties ◽

Data Set ◽

Protein Coding ◽

Genome Wide

Abstract Background Identification of loci for agronomic traits and characterization of their genetic architecture are crucial in marker-assisted selection (MAS). Genome-wide association studies (GWAS) have increasingly been used as potent tools in identifying marker-trait associations (MTAs). The introduction of new adaptive alleles in the diverse genetic backgrounds may help to improve grain yield of old or newly developed varieties of wheat to balance supply and demand throughout the world. Landraces collected from different climate zones can be an invaluable resource for such adaptive alleles. Results GWAS was performed using a collection of 298 Iranian bread wheat varieties and landraces to explore the genetic basis of agronomic traits during 2016–2018 cropping seasons under normal (well-watered) and stressed (rain-fed) conditions. A high-quality genotyping by sequencing (GBS) dataset was obtained using either all original single nucleotide polymorphism (SNP, 10938 SNPs) or with additional imputation (46,862 SNPs) based on W7984 reference genome. The results confirm that the B genome carries the highest number of significant marker pairs in both varieties (49,880, 27.37%) and landraces (55,086, 28.99%). The strongest linkage disequilibrium (LD) between pairs of markers was observed on chromosome 2D (0.296). LD decay was lower in the D genome, compared to the A and B genomes. Association mapping under two tested environments yielded a total of 313 and 394 significant (−log10P >3) MTAs for the original and imputed SNP data sets, respectively. Gene ontology results showed that 27 and 27.5% of MTAs of SNPs in the original set were located in protein-coding regions for well-watered and rain-fed conditions, respectively. While, for the imputed data set 22.6 and 16.6% of MTAs represented in protein-coding genes for the well-watered and rain-fed conditions, respectively. Conclusions Our finding suggests that Iranian bread wheat landraces harbor valuable alleles that are adaptive under drought stress conditions. MTAs located within coding genes can be utilized in genome-based breeding of new wheat varieties. Although imputation of missing data increased the number of MTAs, the fraction of these MTAs located in coding genes were decreased across the different sub-genomes.

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Precision Mapping of a Maize MAGIC Population Identified a Candidate Gene for the Senescence-Associated Physiological Traits

Frontiers in Genetics ◽

10.3389/fgene.2021.716821 ◽

2021 ◽

Vol 12 ◽

Author(s):

Marlon Caicedo ◽

Eduardo D. Munaiz ◽

Rosa A. Malvar ◽

José C. Jiménez ◽

Bernardo Ordas

Keyword(s):

Candidate Gene ◽

Defense Mechanism ◽

Agronomic Traits ◽

Association Studies ◽

Recombinant Inbred Lines ◽

Sugar Transport ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Important Trait

Senescence is an important trait in maize (Zea mais L.), a key crop that provides nutrition values and a renewable source of bioenergy worldwide. Genome-wide association studies (GWAS) can be used to identify causative genetic variants that influence the major physiological measures of senescence, which is used by plants as a defense mechanism against abiotic and biotic stresses affecting its performance. We measured four physiological and two agronomic traits that affect senescence. Six hundred seventy-two recombinant inbred lines (RILs) were evaluated in two consecutive years. Thirty-six candidate genes were identified by genome-wide association study (GWAS), and 11 of them were supported by additional evidence for involvement in senescence-related processes including proteolysis, sugar transport, and sink activity. We identified a candidate gene, Zm00001d043586, significantly associated with chlorophyll, and independently studied its transcription expression in an independent panel. Our results showed that Zm00001d043586 affects chlorophyl rate degradation, a key determinant of senescence, at late plant development stages. These results contribute to better understand the genetic relationship of the important trait senescence with physiology related parameters in maize and provide new putative molecular markers that can be used in marker assisted selection for line development.

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Faculty Opinions recommendation of Genome-wide association studies of 14 agronomic traits in rice landraces.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.6138956.6176054 ◽

2010 ◽

Author(s):

Antoni Rafalski ◽

Bailin Li

Keyword(s):

Agronomic Traits ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Rice Landraces ◽

Genome Wide

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Genome-wide Association Studies Reveal the Genetic Basis of Natural Ionomic Variation in Rice Grain Oryza Sativa Subsp. Indica

10.21203/rs.3.rs-582987/v1 ◽

2021 ◽

Author(s):

Suong T. Cu ◽

Nicholas Warnock ◽

Julie Pasuquin ◽

Michael Dingkuhn ◽

James Stangoulis

Keyword(s):

Genetic Basis ◽

Agronomic Traits ◽

Association Studies ◽

Starch Synthesis ◽

Grain Filling ◽

Genome Wide Association ◽

Rice Grain ◽

Genome Wide Association Studies ◽

Potential Candidate ◽

Genome Wide

Abstract 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 (TGW). 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 controlling the variation of Zn and Co concentrations. The effects of starch synthesis and grain filling on TGW and multiple grain elements were elucidated through the 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.

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A high-resolution genome-wide association study of the grain ionome and agronomic traits in rice Oryza sativa subsp. indica

Scientific Reports ◽

10.1038/s41598-021-98573-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Suong T. Cu ◽

Nicholas I. Warnock ◽

Julie Pasuquin ◽

Michael Dingkuhn ◽

James Stangoulis

Keyword(s):

Genome Wide Association Study ◽

Agronomic Traits ◽

Association Studies ◽

Starch Synthesis ◽

Grain Filling ◽

Genome Wide Association ◽

Rice Grain ◽

Genome Wide Association Studies ◽

Potential Candidate ◽

Genome Wide

AbstractThis 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.

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Genome-Wide Association Studies Dissect the G×E Interaction for Agronomic Traits in a Worldwide Collection of Safflower (Carthamus Tinctorius L.)

10.21203/rs.3.rs-926995/v1 ◽

2021 ◽

Author(s):

Huanhuan Zhao ◽

Keith W. Savin ◽

Yongjun Li ◽

Edmond J Breen ◽

Pankaj Maharjan ◽

...

Keyword(s):

Water Stress ◽

Genetic Architecture ◽

Agronomic Traits ◽

Association Studies ◽

Genetic Correlations ◽

Carthamus Tinctorius ◽

Genome Wide Association ◽

Oil Yield ◽

Genome Wide Association Studies ◽

Genome Wide

Abstract Background: Safflower (Carthamus tinctorius L.) has been cultivated worldwide for centuries, originally as a source of textile dyes. Modern safflower breeding has focused on high grain and oil yield and broad adaptability. Here, a genome-wide association study was conducted using a globally diverse Genebank collection of 406 accessions, which included landraces, breeding lines and elite cultivars. We explored the genetic architecture and genotype-by-environment interaction (G × E) patterns of grain yield (YP), days to flowering (DF ), plant height (PH), 500 seed weight (SW), seed oil content (OL), and crude protein content (PR) in four environments (sites) that differed in water availability. Results: Phenotypic variation within the global collection was observed for all traits under differed water stress environments. Two mixed linear models were adopted, and YP exhibited low overall genetic correlations (rGoverall) across sites, while SW and OL had high rGoverall and high pairwise genetic correlations (rGij) across all pairwise sites. Ninety-two marker-trait associations (MTAs) were identified using three methods, single locus genome-wide association studies (GWAS) using a mixed linear model (MLM), the Bayesian multi-locus method (BayesR), and meta-GWAS. MTAs with large effects across all sites were detected for OL, SW, and PR, and MTAs specific for the different water stress sites was identified for all traits. Five MTAs were associated with multiple traits, 4 of 5 MTAs were variously associated with the three traits of SW, OL, and PR and marker effects were consistent with phenotypic observations in different environments. The thresholds of different GWAS methods used in the study affected the number of MTAs identified for complex traits. Conclusions: This study provided insights into the phenotypic variability and genetic architecture of important safflower agronomic traits under different environments. This knowledge is essential to breed for high grain and oil yield and local adaption in safflower.

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