Genome-wide association analysis of root system architecture features and agronomic traits in durum wheat

2020 ◽  
Vol 40 (6) ◽  
Author(s):  
Ali Ashraf Mehrabi ◽  
Alireza Pour-Aboughadareh ◽  
Sajjad Mansouri ◽  
Alireza Hosseini
Keyword(s):  
Durum Wheat ◽  
Root System ◽  
Association Analysis ◽  
System Architecture ◽  
Agronomic Traits ◽  
Root System Architecture ◽  
Genome Wide Association ◽  
Genome Wide Association Analysis ◽  
Genome Wide

scholarly journals Comprehensive Genome-Wide Association Analysis Reveals the Genetic Basis of Root System Architecture in Soybean

2020 ◽  
Vol 11 ◽  
Author(s):  
Waldiodio Seck ◽  
Davoud Torkamaneh ◽  
François Belzile
Keyword(s):  
Root System ◽  
System Architecture ◽  
Phenotypic Variation ◽  
Genetic Basis ◽  
Genome Wide Association Study ◽  
Primary Root ◽  
Root System Architecture ◽  
Genome Wide Association ◽  
Nucleotide Polymorphisms ◽  
Genome Wide

Increasing the understanding genetic basis of the variability in root system architecture (RSA) is essential to improve resource-use efficiency in agriculture systems and to develop climate-resilient crop cultivars. Roots being underground, their direct observation and detailed characterization are challenging. Here, were characterized twelve RSA-related traits in a panel of 137 early maturing soybean lines (Canadian soybean core collection) using rhizoboxes and two-dimensional imaging. Significant phenotypic variation (P < 0.001) was observed among these lines for different RSA-related traits. This panel was genotyped with 2.18 million genome-wide single-nucleotide polymorphisms (SNPs) using a combination of genotyping-by-sequencing and whole-genome sequencing. A total of 10 quantitative trait locus (QTL) regions were detected for root total length and primary root diameter through a comprehensive genome-wide association study. These QTL regions explained from 15 to 25% of the phenotypic variation and contained two putative candidate genes with homology to genes previously reported to play a role in RSA in other species. These genes can serve to accelerate future efforts aimed to dissect genetic architecture of RSA and breed more resilient varieties.

scholarly journals Genome-wide association analysis of agronomic traits in wheat under drought-stressed and non-stressed conditions

PLoS ONE ◽  
2017 ◽  
Vol 12 (2) ◽  
pp. e0171692 ◽  
Author(s):  
Learnmore Mwadzingeni ◽  
Hussein Shimelis ◽  
D. Jasper G. Rees ◽  
Toi J. Tsilo
Keyword(s):  
Association Analysis ◽  
Agronomic Traits ◽  
Genome Wide Association ◽  
Genome Wide Association Analysis ◽  
Genome Wide

Genome-wide association analysis for nine agronomic traits in maize under well-watered and water-stressed conditions

2013 ◽  
Vol 126 (10) ◽  
pp. 2587-2596 ◽  
Author(s):  
Yadong Xue ◽  
Marilyn L. Warburton ◽  
Mark Sawkins ◽  
Xuehai Zhang ◽  
Tim Setter ◽  
...  
Keyword(s):  
Association Analysis ◽  
Agronomic Traits ◽  
Genome Wide Association ◽  
Genome Wide Association Analysis ◽  
Genome Wide

scholarly journals Exploiting natural variation in crown root traits via genome-wide association studies in maize

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Houmiao Wang ◽  
Xiao Tang ◽  
Xiaoyi Yang ◽  
Yingying Fan ◽  
Yang Xu ◽  
...  
Keyword(s):  
Root System ◽  
Candidate Genes ◽  
System Architecture ◽  
Root Traits ◽  
Root System Architecture ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Crown Root ◽  
Genome Wide ◽  
Maize Varieties

Abstract Background Root system architecture (RSA), which is determined by the crown root angle (CRA), crown root diameter (CRD), and crown root number (CRN), is an important factor affecting the ability of plants to obtain nutrients and water from the soil. However, the genetic mechanisms regulating crown root traits in the field remain unclear. Methods In this study, the CRA, CRD, and CRN of 316 diverse maize inbred lines were analysed in three field trials. Substantial phenotypic variations were observed for the three crown root traits in all environments. A genome-wide association study was conducted using two single-locus methods (GLM and MLM) and three multi-locus methods (FarmCPU, FASTmrMLM, and FASTmrEMMA) with 140,421 SNP. Results A total of 38 QTL including 126 SNPs were detected for CRA, CRD, and CRN. Additionally, 113 candidate genes within 50 kb of the significant SNPs were identified. Combining the gene annotation information and the expression profiles, 3 genes including GRMZM2G141205 (IAA), GRMZM2G138511 (HSP) and GRMZM2G175910 (cytokinin-O-glucosyltransferase) were selected as potentially candidate genes related to crown root development. Moreover, GRMZM2G141205, encoding an AUX/IAA transcriptional regulator, was resequenced in all tested lines. Five variants were identified as significantly associated with CRN in different environments. Four haplotypes were detected based on these significant variants, and Hap1 has more CRN. Conclusions These findings may be useful for clarifying the genetic basis of maize root system architecture. Furthermore, the identified candidate genes and variants may be relevant for breeding new maize varieties with root traits suitable for diverse environmental conditions.

scholarly journals Exploiting natural variation in root system architecture via genome-wide association studies

2020 ◽  
Vol 71 (8) ◽  
pp. 2379-2389 ◽  
Author(s):  
Agnieszka Deja-Muylle ◽  
Boris Parizot ◽  
Hans Motte ◽  
Tom Beeckman
Keyword(s):  
Root System ◽  
System Architecture ◽  
Association Studies ◽  
Root Traits ◽  
Root System Architecture ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Important Research Topic ◽  
Root Growth And Development

Abstract Root growth and development has become an important research topic for breeders and researchers based on a growing need to adapt plants to changing and more demanding environmental conditions worldwide. Over the last few years, genome-wide association studies (GWASs) became an important tool to identify the link between traits in the field and their genetic background. Here we give an overview of the current literature concerning GWASs performed on root system architecture (RSA) in plants. We summarize which root traits and approaches have been used for GWAS, mentioning their respective success rate towards a successful gene discovery. Furthermore, we zoom in on the current technical hurdles in root phenotyping and GWAS, and discuss future possibilities in this field of research.

Exploiting Natural Variation in Crown Root Traits via Genome-Wide Association Studies in Maize

2021 ◽  
Author(s):  
Houmiao Wang ◽  
Xiao Tang ◽  
Xiaoyi Yang ◽  
Yingying Fan ◽  
Yang Xu ◽  
...  
Keyword(s):  
Root System ◽  
Candidate Genes ◽  
System Architecture ◽  
Root Traits ◽  
Root System Architecture ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Crown Root ◽  
Genome Wide ◽  
Maize Varieties

Abstract Background: Root system architecture (RSA), which is determined by the crown root angle (CRA), crown root diameter (CRD), and crown root number (CRN), is an important factor affecting the ability of plants to obtain nutrients and water from the soil. However, the genetic mechanisms regulating crown root traits in the field remain unclear. Methods: In this study, the CRA, CRD, and CRN of 348 diverse maize inbred lines were analysed in three field trials. Substantial phenotypic variations were observed for the three crown root traits in all environments. A genome-wide association study was conducted using three multi-locus methods (FarmCPU, FASTmrMLM, and FASTmrEMMA).Results: A total of 91, 116, and 117 marker–trait associations were identified for CRA, CRD, and CRN, respectively. Additionally, 683 candidate genes within 50 kb of the significant SNPs were identified. A combined analysis of gene annotations and expression profiles revealed 20 promising genes related to auxin synthesis and signal transduction, cytokinin oxidase/dehydrogenase, and transcription factors. These candidate genes may be associated with crown root development. Moreover, GRMZM2G141205, encoding an AUX/IAA transcriptional regulator, was resequenced in all tested lines. Five variants were identified as significantly associated with CRN based on the data for 16SY and 17SY as well as the average values for the three environments. Four haplotypes were detected based on these significant variants, and Hap1 was the optimal haplotype for CRN. Conclusions: These findings may be useful for clarifying the genetic basis of maize root system architecture. Furthermore, the identified candidate genes and variants may be relevant for breeding new maize varieties with root traits suitable for diverse environmental conditions.

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