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SNP Identification and Discovery

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Bioinformatics in Rice Research

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Abstract

The global climate change has a negative influence on the quality of crop production and has been considered a threat in recent years. Henceforth, there is a need for advancement in technology to overcome the issue and improve both the quality and quantity of the crop plants by exploiting their genome. The various single nucleotide polymorphism (SNP) markers have been extensively used in crop breedings as molecular markers with advances in NGS (Next-generation sequencing) technology. These SNP markers are cost-effective for variety identification. SNPs have a deterministic role in protein expression. Thereby sequencing and genotyping have enabled crop improvement based on genomics with significant advances in NGS technologies which have also assisted in overcoming the drawbacks in detecting new functional SNPs associated with diverse traits. While SNP markers are found to be highly abundant and prevalent across the genome, functional SNPs are known to have a crucial impact on the phenotypes of plants. Besides, it was also known that SNP markers can be widely used and implemented in genotyping for the identification of structural variants due to their codominance, low cost, flexibility, speed, and ease of automation than other markers. Even in the genome-wide association study (GWAS), SNP markers were considered a significant tool in developing genome-wide haplotypes. Identified SNP patterns from GWAS are useful for understanding plant evolution. Genetic variations derived from the SNP patterns may execute desired phenotypes in the plant that benefits plant breeding and crop improvements. Even though SNPs widely use, technical advancements are needed to overcome the challenges in plant SNPs identification, to understand speciation and evolution through genomic divergence of plants, and to identify associate genomic variations of phenotypic traits.

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Abbreviations

ASO:

Allele-specific oligonucleotide

OLA:

Oligonucleotide ligation assay

QTLs :

Quantitative trait loci

RAPD:

Random amplification of polymorphic DNA

RFLP:

Restriction fragment length polymorphism

SNP:

Single nucleotide polymorphism

SSCP:

Single-strand conformation polymorphism

SSRs:

Simple sequence repeats

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Acknowledgements

The authors thank the Centre for Bioinformatics for providing the necessary facility for the work.

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There is no conflict of interest to declare.

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Authors and Affiliations

  1. Centre for Bioinformatics, Pondicherry University, Pondicherry, India

    Christian Bharathi Antony Raj, Hemavathy Nagarajan & Mohamed Hameed Aslam

  2. Department of Biotechnology, Karpagam Academy of Higher Education, Coimbatore, India

    Santhiya Panchalingam

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  1. Christian Bharathi Antony Raj
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  2. Hemavathy Nagarajan
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  3. Mohamed Hameed Aslam
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  4. Santhiya Panchalingam
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Editors and Affiliations

  1. Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, Odisha, India

    Manoj Kumar Gupta

  2. Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, Odisha, India

    Lambodar Behera

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Antony Raj, C.B., Nagarajan, H., Aslam, M.H., Panchalingam, S. (2021). SNP Identification and Discovery. In: Gupta, M.K., Behera, L. (eds) Bioinformatics in Rice Research. Springer, Singapore. https://doi.org/10.1007/978-981-16-3993-7_17

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