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Genome-wide association studies: an intuitive solution for SNP identification and gene mapping in trees

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A Correction to this article was published on 21 September 2023

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Abstract

Analysis of natural diversity in wild/cultivated plants can be used to understand the genetic basis for plant breeding programs. Recent advancements in DNA sequencing have expanded the possibilities for genetically altering essential features. There have been several recently disclosed statistical genetic methods for discovering the genes impacting target qualities. One of these useful methods is the genome-wide association study (GWAS), which effectively identifies candidate genes for a variety of plant properties by examining the relationship between a molecular marker (such as SNP) and a target trait. Conventional QTL mapping with highly structured populations has major limitations. The limited number of recombination events results in poor resolution for quantitative traits. Only two alleles at any given locus can be studied simultaneously. Conventional mapping approach fails to work in perennial plants and vegetatively propagated crops. These limitations are sidestepped by association mapping or GWAS. The flexibility of GWAS comes from the fact that the individuals being examined need not be linked to one another, allowing for the use of all meiotic and recombination events to increase resolution. Phenotyping, genotyping, population structure analysis, kinship analysis, and marker-trait association analysis are the fundamental phases of GWAS. With the rapid development of sequencing technologies and computational methods, GWAS is becoming a potent tool for identifying the natural variations that underlie complex characteristics in crops. The use of high-throughput sequencing technologies along with genotyping approaches like genotyping-by-sequencing (GBS) and restriction site associated DNA (RAD) sequencing may be highly useful in fast-forward mapping approach like GWAS. Breeders may use GWAS to quickly unravel the genomes through QTL and association mapping by taking advantage of natural variances. The drawbacks of conventional linkage mapping can be successfully overcome with the use of high-resolution mapping and the inclusion of multiple alleles in GWAS.

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Authors and Affiliations

  1. Department of Forest Biology and Tree Improvement, Kerala Agricultural University, Thrissur, Kerala, 680 656, India

    M. N. Ashwath, A. V. Santhoshkumar & K. Shiran

  2. Centre for Plant Biotechnology and Molecular Biology, Kerala Agricultural University, Thrissur, Kerala, 680 656, India

    Shivaji Ajinath Lavale

  3. Department of Forest Biology and Tree Improvement, Odisha University of Agriculture and Technology, Bhubaneswar, Odisha, 751 003, India

    Sourav Ranjan Mohapatra

  4. Department of Silviculture and Agroforestry, Kerala Agricultural University, Thrissur, Kerala, 680 656, India

    Ankita Bhardwaj & Umakanta Dash

  5. Institute of Technology, University of Tartu, 50411, Tartu, Estonia

    Kajal Samantara

  6. Mountain Research Center for Field crops, Sher-e-Kashmir University of Agricultural Sciences and Technology Srinagar, Khudwani, Srinagar, Jammu and Kashmir, India

    Shabir Hussain Wani

Authors
  1. M. N. Ashwath
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  2. Shivaji Ajinath Lavale
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  3. A. V. Santhoshkumar
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  4. Sourav Ranjan Mohapatra
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  5. Ankita Bhardwaj
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  6. Umakanta Dash
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  7. K. Shiran
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  8. Kajal Samantara
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  9. Shabir Hussain Wani
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Contributions

Conceptualization: A.M.N., S.A.V., and S.H.W. Writing and original draft preparation: A.M.N., S.A.L., S.R.M., A.B., U.D., S.K., and K.S. Review and editing: A.M.N., S.R.M. Supervision: S.A.V and S.H.W. All authors have read and agreed to the manuscript.

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Correspondence to Sourav Ranjan Mohapatra or Shabir Hussain Wani.

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The original online version of this article was revised: The original version of this article contains an error in author name. The correct spelling should be "Samantara" instead of "Samantra".

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Ashwath, M.N., Lavale, S.A., Santhoshkumar, A.V. et al. Genome-wide association studies: an intuitive solution for SNP identification and gene mapping in trees. Funct Integr Genomics 23, 297 (2023). https://doi.org/10.1007/s10142-023-01224-8

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  • DOI: https://doi.org/10.1007/s10142-023-01224-8

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