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Sahito JH, Zhang H, Gishkori ZGN, Ma C, Wang Z, Ding D, Zhang X, Tang J. Advancements and Prospects of Genome-Wide Association Studies (GWAS) in Maize. Int J Mol Sci 2024; 25:1918. [PMID: 38339196 PMCID: PMC10855973 DOI: 10.3390/ijms25031918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/30/2024] [Accepted: 02/02/2024] [Indexed: 02/12/2024] Open
Abstract
Genome-wide association studies (GWAS) have emerged as a powerful tool for unraveling intricate genotype-phenotype association across various species. Maize (Zea mays L.), renowned for its extensive genetic diversity and rapid linkage disequilibrium (LD), stands as an exemplary candidate for GWAS. In maize, GWAS has made significant advancements by pinpointing numerous genetic loci and potential genes associated with complex traits, including responses to both abiotic and biotic stress. These discoveries hold the promise of enhancing adaptability and yield through effective breeding strategies. Nevertheless, the impact of environmental stress on crop growth and yield is evident in various agronomic traits. Therefore, understanding the complex genetic basis of these traits becomes paramount. This review delves into current and future prospectives aimed at yield, quality, and environmental stress resilience in maize and also addresses the challenges encountered during genomic selection and molecular breeding, all facilitated by the utilization of GWAS. Furthermore, the integration of omics, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics has enriched our understanding of intricate traits in maize, thereby enhancing environmental stress tolerance and boosting maize production. Collectively, these insights not only advance our understanding of the genetic mechanism regulating complex traits but also propel the utilization of marker-assisted selection in maize molecular breeding programs, where GWAS plays a pivotal role. Therefore, GWAS provides robust support for delving into the genetic mechanism underlying complex traits in maize and enhancing breeding strategies.
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Affiliation(s)
- Javed Hussain Sahito
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Hao Zhang
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Zeeshan Ghulam Nabi Gishkori
- Institute of Biotechnology, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
| | - Chenhui Ma
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Zhihao Wang
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Dong Ding
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Xuehai Zhang
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Jihua Tang
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
- The Shennong Laboratory, Zhengzhou 450002, China
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Yuan G, He D, Shi J, Li Y, Yang Y, Du J, Zou C, Ma L, Gao S, Pan G, Shen Y. Genome-Wide Association Study Discovers Novel Germplasm Resources and Genetic Loci with Resistance to Gibberella Ear Rot Caused by Fusarium graminearum. PHYTOPATHOLOGY 2023; 113:1317-1324. [PMID: 36721376 DOI: 10.1094/phyto-09-22-0336-r] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Gibberella ear rot (GER) in maize caused by Fusarium graminearum is one of the most devastating maize diseases reducing grain yield and quality worldwide. The genetic bases of maize GER resistance remain largely unknown. Using artificial inoculation across multiple environments, the GER severity of an association panel consisting of 316 diverse inbred lines was observed with wide phenotypic variation. In the association panel, a genome-wide association study using a general linear model identified 69 single-nucleotide polymorphisms (SNPs) significantly associated with GER resistance at the threshold of 2.04 × 10-5, and the average phenotypic variation explained (PVE) of these SNPs was 5.09%. We also conducted a genome-wide association study analysis using a mixed linear model at a threshold of 1.0 × 10-4, and 16 significantly associated SNPs with an average PVE of 4.73% were detected. A combined general linear model and mixed linear model method obtained 10 co-localized significantly associated SNPs linked to GER resistance, including the most significant SNP (PZE-105079915) with the greatest PVE value, 9.07%, at bin 5.05 following 10 candidate genes. These findings are significant for the exploration of the complicated genetic variations in maize GER resistance. The regions and genes identified herein provide a list of candidate targets for further investigation, in addition to the elite germplasm resources that can be used for breeding GER resistance in maize.
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Affiliation(s)
- Guangsheng Yuan
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Dandan He
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Jiaxin Shi
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Youliang Li
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Yan Yang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Juan Du
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Chaoying Zou
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Langlang Ma
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Shibin Gao
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Guangtang Pan
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Yaou Shen
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
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Warburton ML, Woolfolk SW, Smith JS, Hawkins LK, Castano-Duque L, Lebar MD, Williams WP. Genes and genetic mechanisms contributing to fall armyworm resistance in maize. THE PLANT GENOME 2023; 16:e20311. [PMID: 36866429 DOI: 10.1002/tpg2.20311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 01/18/2023] [Indexed: 06/20/2023]
Abstract
Maize (Zea mays L.) is a crop of major economic and food security importance globally. The fall armyworm (FAW), Spodoptera frugiperda, can devastate entire maize crops, especially in countries or markets that do not allow the use of transgenic crops. Host-plant insect resistance is an economical and environmentally benign way to control FAW, and this study sought to identify maize lines, genes, and pathways that contribute to resistance to FAW. Of the 289 maize lines phenotyped for FAW damage in artificially infested, replicated field trials over 3 years, 31 were identified with good levels of resistance that could donate FAW resistance into elite but susceptible hybrid parents. The 289 lines were genotyped by sequencing to provide single nucleotide polymorphism (SNP) markers for a genome-wide association study (GWAS), followed by a metabolic pathway analysis using the Pathway Association Study Tool (PAST). GWAS identified 15 SNPs linked to 7 genes, and PAST identified multiple pathways, associated with FAW damage. Top pathways, and thus useful resistance mechanisms for further study, include hormone signaling pathways and the biosynthesis of carotenoids (particularly zeaxanthin), chlorophyll compounds, cuticular wax, known antibiosis agents, and 1,4-dihydroxy-2-naphthoate. Targeted metabolite analysis confirmed that maize genotypes with lower levels of FAW damage tend to have higher levels of chlorophyll a than genotypes with high FAW damage, which tend to have lower levels of pheophytin, lutein, chlorophyll b and β-carotene. The list of resistant genotypes, and the results from the genetic, pathway, and metabolic study, can all contribute to efficient creation of FAW resistant cultivars.
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Affiliation(s)
- Marilyn L Warburton
- USDA ARS Plant Germplasm Introduction and Testing Research Unit, Pullman, WA, USA
| | - Sandra W Woolfolk
- USDA ARS Corn Host Plant Resistance Research Unit, Mississippi State, MS, USA
| | - J Spencer Smith
- USDA ARS Corn Host Plant Resistance Research Unit, Mississippi State, MS, USA
| | - Leigh K Hawkins
- USDA ARS Corn Host Plant Resistance Research Unit, Mississippi State, MS, USA
| | | | - Matthew D Lebar
- USDA ARS Food and Feed Safety Research Unit, New Orleans, LA, USA
| | - W Paul Williams
- USDA ARS Corn Host Plant Resistance Research Unit, Mississippi State, MS, USA
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Khanal A, Adhikari P, Kaiser C, Lipka AE, Jamann TM, Mideros SX. Genetic mapping of sorghum resistance to an Illinois isolate of Colletotrichum sublineola. THE PLANT GENOME 2022; 15:e20243. [PMID: 35822435 DOI: 10.1002/tpg2.20243] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 06/03/2022] [Indexed: 06/15/2023]
Abstract
Anthracnose leaf blight (ALB) is an economically important disease of sorghum [Sorghum bicolor (L.) Moench] caused by the fungal pathogen Colletotrichum sublineola Henn. ex Sacc. & Trotter. Although qualitative and quantitative resistance have been identified for ALB, the usefulness of resistance loci differs depending on the pathogen pathotype. Identifying resistance effective against unique pathogen pathotypes is critical to managing ALB, as the disease is managed primarily through the deployment of host resistance. We isolated C. sublineola from ALB-infected leaves collected in Illinois and found that the strain was a novel pathotype, as it produced a unique combination of virulence against a set of differential lines. Using this isolate, we inoculated 579 temperate-adapted sorghum conversion lines in 2019 and 2020. We then conducted a genome-wide association study (GWAS) and a metabolic pathway analysis using the Pathway Associated Study Tool (PAST). We identified 47 significant markers distributed across all chromosomes except chromosome 8. We identified 32 candidate genes based on physical proximity with significant markers, some of which have a known role in host defense. We identified 47 pathways associated with ALB resistance, indicating a role for secondary metabolism in defense to ALB. Our results are important to improve the understanding of the genetic basis of ALB resistance in sorghum and highlight the importance of developing durable resistance to ALB.
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Affiliation(s)
- Ashmita Khanal
- Dep. of Crop Sciences, Univ. of Illinois at Urbana-Champaign, Urbana, IL, 61802, USA
| | - Pragya Adhikari
- Dep. of Crop Sciences, Univ. of Illinois at Urbana-Champaign, Urbana, IL, 61802, USA
| | - Christopher Kaiser
- Dep. of Crop Sciences, Univ. of Illinois at Urbana-Champaign, Urbana, IL, 61802, USA
| | - Alexander E Lipka
- Dep. of Crop Sciences, Univ. of Illinois at Urbana-Champaign, Urbana, IL, 61802, USA
| | - Tiffany M Jamann
- Dep. of Crop Sciences, Univ. of Illinois at Urbana-Champaign, Urbana, IL, 61802, USA
| | - Santiago X Mideros
- Dep. of Crop Sciences, Univ. of Illinois at Urbana-Champaign, Urbana, IL, 61802, USA
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Development of Novel Markers for Yield in Hevea brasiliensis Muell. Arg. Based on Candidate Genes from Biosynthetic Pathways Associated with Latex Production. Biochem Genet 2022; 60:2171-2199. [PMID: 35296963 DOI: 10.1007/s10528-022-10211-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 02/24/2022] [Indexed: 12/22/2022]
Abstract
Scarcity of functional genetic markers associated with candidate genes (CGs) is a serious constraint for marker-assisted selection in the natural rubber producing tree, Hevea brasiliensis. In order to develop markers associated with rubber yield, five CGs involved in latex biosynthesis were characterized from 16 popular Hevea varieties. Novel SNPs and indels were identified and developed into markers using simple genotyping techniques like allele-specific PCR, CAPS, etc. A progeny population was genotyped using these markers to validate them, to understand their segregation pattern and to map them to a genetic linkage map. Parent-specific maps were constructed using pseudo-test cross strategy with the help of additional markers. The sequence structure information generated will be useful for future studies on gene mapping, functional relevance of coding SNPs and evolution of rubber biosynthesis genes in Hevea. Concurrently, the markers developed may serve as powerful tools for yield-based selection and for genetic diversity and pedigree studies in Hevea. Above all, the marker assays designed for genotyping could be economically carried out in any laboratory having basic molecular biology infrastructure and expertise.
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Back to the wild: mining maize (Zea mays L.) disease resistance using advanced breeding tools. Mol Biol Rep 2022; 49:5787-5803. [PMID: 35064401 DOI: 10.1007/s11033-021-06815-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 10/06/2021] [Indexed: 10/19/2022]
Abstract
Cultivated modern maize (Zea mays L.) originated through the continuous process of domestication from its wild progenitors. Today, maize is considered as the most important cereal crop which is extensively cultivated in all parts of the world. Maize shows remarkable genotypic and phenotypic diversity which makes it an ideal model species for crop genetic research. However, intensive breeding and artificial selection of desired agronomic traits greatly narrow down the genetic bases of maize. This reduction in genetic diversity among cultivated maize led to increase the chance of more attack of biotic stress as climate changes hampering the maize grain production globally. Maize germplasm requires to integrate both durable multiple-diseases and multiple insect-pathogen resistance through tapping the unexplored resources of maize landraces. Revisiting the landraces seed banks will provide effective opportunities to transfer the resistant genes into the modern cultivars. Here, we describe the maize domestication process and discuss the unique genes from wild progenitors which potentially can be utilized for disease resistant in maize. We also focus on the genetics and disease resistance mechanism of various genes against maize biotic stresses and then considered the different molecular breeding tools for gene transfer and advanced high resolution mapping for gene pyramiding in maize lines. At last, we provide an insight for targeting identified key genes through CRISPR/Cas9 genome editing system to enhance the maize resilience towards biotic stress.
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Liu L, Jiang LG, Luo JH, Xia AA, Chen LQ, He Y. Genome-wide association study reveals the genetic architecture of root hair length in maize. BMC Genomics 2021; 22:664. [PMID: 34521344 PMCID: PMC8442424 DOI: 10.1186/s12864-021-07961-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 08/28/2021] [Indexed: 12/05/2022] Open
Abstract
Background Root hair, a special type of tubular-shaped cell, outgrows from root epidermal cell and plays important roles in the acquisition of nutrients and water, as well as interactions with biotic and abiotic stress. Although many genes involved in root hair development have been identified, genetic basis of natural variation in root hair growth has never been explored. Results Here, we utilized a maize association panel including 281 inbred lines with tropical, subtropical, and temperate origins to decipher the phenotypic diversity and genetic basis of root hair length. We demonstrated significant associations of root hair length with many metabolic pathways and other agronomic traits. Combining root hair phenotypes with 1.25 million single nucleotide polymorphisms (SNPs) via genome-wide association study (GWAS) revealed several candidate genes implicated in cellular signaling, polar growth, disease resistance and various metabolic pathways. Conclusions These results illustrate the genetic basis of root hair length in maize, offering a list of candidate genes predictably contributing to root hair growth, which are invaluable resource for the future functional investigation. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-07961-z.
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Affiliation(s)
- Lin Liu
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing, 100193, China
| | - Lu-Guang Jiang
- MOE Key Laboratory of Crop Heterosis and Utilization, National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China
| | - Jin-Hong Luo
- MOE Key Laboratory of Crop Heterosis and Utilization, National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China
| | - Ai-Ai Xia
- MOE Key Laboratory of Crop Heterosis and Utilization, National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China
| | - Li-Qun Chen
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing, 100193, China.
| | - Yan He
- MOE Key Laboratory of Crop Heterosis and Utilization, National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China.
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Medeiros DB, Brotman Y, Fernie AR. The utility of metabolomics as a tool to inform maize biology. PLANT COMMUNICATIONS 2021; 2:100187. [PMID: 34327322 PMCID: PMC8299083 DOI: 10.1016/j.xplc.2021.100187] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 03/26/2021] [Accepted: 04/19/2021] [Indexed: 05/04/2023]
Abstract
With the rise of high-throughput omics tools and the importance of maize and its products as food and bioethanol, maize metabolism has been extensively explored. Modern maize is still rich in genetic and phenotypic variation, yielding a wide range of structurally and functionally diverse metabolites. The maize metabolome is also incredibly dynamic in terms of topology and subcellular compartmentalization. In this review, we examine a broad range of studies that cover recent developments in maize metabolism. Particular attention is given to current methodologies and to the use of metabolomics as a tool to define biosynthetic pathways and address biological questions. We also touch upon the use of metabolomics to understand maize natural variation and evolution, with a special focus on research that has used metabolite-based genome-wide association studies (mGWASs).
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Affiliation(s)
- David B. Medeiros
- Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany
| | - Yariv Brotman
- Department of Life Sciences, Ben-Gurion University of the Negev, Beersheva, Israel
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Shikha K, Shahi JP, Vinayan MT, Zaidi PH, Singh AK, Sinha B. Genome-wide association mapping in maize: status and prospects. 3 Biotech 2021; 11:244. [PMID: 33968587 PMCID: PMC8085158 DOI: 10.1007/s13205-021-02799-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 04/19/2021] [Indexed: 12/11/2022] Open
Abstract
Genome-wide association study (GWAS) provides a robust and potent tool to retrieve complex phenotypic traits back to their underlying genetics. Maize is an excellent crop for performing GWAS due to diverse genetic variability, rapid decay of linkage disequilibrium, availability of distinct sub-populations and abundant SNP information. The application of GWAS in maize has resulted in successful identification of thousands of genomic regions associated with many abiotic and biotic stresses. Many agronomic and quality traits of maize are severely affected by such stresses and, significantly affecting its growth and productivity. To improve productivity of maize crop in countries like India which contribute only 2% to the world's total production in 2019-2020, it is essential to understand genetic complexity of underlying traits. Various DNA markers and trait associations have been revealed using conventional linkage mapping methods. However, it has achieved limited success in improving polygenic complex traits due to lower resolution of trait mapping. The present review explores the prospects of GWAS in improving yield, quality and stress tolerance in maize besides, strengths and challenges of using GWAS for molecular breeding and genomic selection. The information gathered will facilitate elucidation of genetic mechanisms of complex traits and improve efficiency of marker-assisted selection in maize breeding. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s13205-021-02799-4.
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Affiliation(s)
- Kumari Shikha
- Department of Genetics and Plant Breeding, Institute of Agriculltural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh India
| | - J. P. Shahi
- Department of Genetics and Plant Breeding, Institute of Agriculltural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh India
| | - M. T. Vinayan
- International Maize and Wheat Improvement Centre (CIMMYT)-Asia, ICRISAT Campus, Patancheru, Hyderabad, Telangana India
| | - P. H. Zaidi
- International Maize and Wheat Improvement Centre (CIMMYT)-Asia, ICRISAT Campus, Patancheru, Hyderabad, Telangana India
| | - A. K. Singh
- Department of Genetics and Plant Breeding, Institute of Agriculltural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh India
| | - B. Sinha
- Department of Genetics and Plant Breeding, Institute of Agriculltural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh India
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PAST: The Pathway Association Studies Tool to Infer Biological Meaning from GWAS Datasets. PLANTS 2020; 9:plants9010058. [PMID: 31906457 PMCID: PMC7020396 DOI: 10.3390/plants9010058] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 12/27/2019] [Accepted: 12/30/2019] [Indexed: 01/23/2023]
Abstract
In recent years, a bioinformatics method for interpreting genome-wide association study (GWAS) data using metabolic pathway analysis has been developed and successfully used to find significant pathways and mechanisms explaining phenotypic traits of interest in plants. However, the many scripts implementing this method were not straightforward to use, had to be customized for each project, required user supervision, and took more than 24 h to process data. PAST (Pathway Association Study Tool), a new implementation of this method, has been developed to address these concerns. PAST has been implemented as a package for the R language. Two user-interfaces are provided; PAST can be run by loading the package in R and calling its methods, or by using an R Shiny guided user interface. In testing, PAST completed analyses in approximately half an hour to one hour by processing data in parallel and produced the same results as the previously developed method. PAST has many user-specified options for maximum customization. Thus, to promote a powerful new pathway analysis methodology that interprets GWAS data to find biological mechanisms associated with traits of interest, we developed a more accessible, efficient, and user-friendly tool. These attributes make PAST accessible to researchers interested in associating metabolic pathways with GWAS datasets to better understand the genetic architecture and mechanisms affecting phenotypes.
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