Whole Genome Wide SSR Markers Identification Based on ddRADseq Data

Gitanjali Tandon; Sarika Jaiswal; Mir Asif Iquebal; Anil Rai; Dinesh Kumar

doi:10.1007/978-1-0716-3024-2_5

Whole Genome Wide SSR Markers Identification Based on ddRADseq Data

Methods Mol Biol. 2023:2638:59-66. doi: 10.1007/978-1-0716-3024-2_5.

Authors

Gitanjali Tandon¹, Sarika Jaiswal¹, Mir Asif Iquebal², Anil Rai¹, Dinesh Kumar^{1

3}

Affiliations

¹ Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India.
² Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India. ma.iquebal@icar.gov.in.
³ Department of Biotechnology, School of Interdisciplinary and Applied Sciences, Central University of Haryana, Mahendergarh, Haryana, India.

PMID: 36781635
DOI: 10.1007/978-1-0716-3024-2_5

Abstract

The advent of advanced NGS technologies have led to the generation of enormous amount of sequence data which further aid in the discovery of the various type of markers such as SSRs, SNPs, InDels, etc. Among all these markers, microsatellite SSR markers can be mined from the ddRADseq data as certain properties of SSR markers make them ideal markers for study. These assist researchers and breeders in diversity analysis and producing new varieties with desired traits. To extract the markers, first, the ddRADseq data is assembled into consensus sequences using STACKS program which are further assembled for mining microsatellites using QDD along with MISA tool.

Keywords: MISA; QDD; SSR markers; STACKS; consensus sequences; ddRADseq.

MeSH terms

Expressed Sequence Tags
Genome, Plant*
Microsatellite Repeats / genetics
Polymorphism, Single Nucleotide*