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Role of Next Generation Sequencing (NGS) in Genomics-assisted breeding

BY: Mukesh Choudhary | Category: Genetics | Submitted: 2015-10-30 09:06:52
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Article Summary: "The basic philosophy of the Next Generation Sequencing is to generate whole genome sequences for a wide range of crop species. With the cheaper methods of sequencing being available, breeders have begun to utilize NGS technologies in large scale for sequencing, gene/ QTL mapping, allele mining, and whole genome association mappi.."

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Role of Next Generation Sequencing (NGS) in Genomics-assisted breeding
Authors: Mr. Mukesh Choudhary, Dr. Vignesh Muthusamy and Dr. Firoz Hossain

Next generation sequencing (NGS) technologies are being used to generate whole genome sequences for a wide range of crop species. In combination with precise phenotyping methods, it provides a powerful and rapid tool for identifying the genetic basis of agronomically important traits and for predicting the breeding value of individuals in a plant breeding population. Rapid developments in NGS technologies over the last decade have opened up many new opportunities to explore the relationship between genotype and phenotype with greater resolution than ever before. With the decreased cost of sequencing, breeders have begun to utilize NGS technologies in large scale for sequencing, gene/ QTL mapping, allele mining, and whole genome association mapping.

Genomics-assisted breeding

One of the foremost applications of genomics in breeding is the prediction of a phenotype from the genotype and the process is called genomics-assisted breeding (GAB).

Two main types of genomics-assisted breeding are:

(1) Marker-assisted selection (MAS):

MAS includes marker-assisted back-crossing (MABC) which is based on the use of molecular markers that map within specific genes or QTLs known to be associated with target traits or phenotypes to select individuals that carry favorable alleles for traits of interest (and/or to discard those that do not).

(2) Genomic selection (GS):

GS, on the other hand, uses all available marker data for a population as predictors of breeding value. Specifically, GS integrates marker data from a training population with phenotypic and, when available, pedigree data collected on the same population to generate a prediction model. The model outputs genomic estimated breeding values (GEBVs) for all genotyped individuals within a breeding population. The GEBVs serves as a predictor of how well a plant will perform as a parent for crossing and generation advance in a breeding pipeline, based on the similarity of its genomic profile to other plants in the Training Population (TP) that are known to have performed well in the target environment(s). Before the prediction model can be applied to a breeding population, the accuracy of the model is generally tested using cross validation on subsets of the training population. Once validated, the model can be applied to a breeding population where GEBVs are calculated for all lines for which genotypic information is available, and their phenotypic performance is predicted solely on the basis of that genotypic information.

Role of NGS in Crop Improvement

There are various approaches where the use of NGS has enhanced the efficiency and resolution of the mapping process to discover gene and QTL.

(1) Genome-Wide Association Studies (GWAS): It utilize association mapping to map QTLs by taking advantage of historic linkage disequilibrium (LD) to identify statistically significant phenotype-genotype associations. Larger population with high density of markers can be genotyped leading to high resolution in mapping and precise localization of gene.

(2) Sequence based mapping: It requires deep sequencing of two DNA pools derived from individuals from the phenotypic extremes of a segregating population in order to identify candidate genes associated with a phenotype of interest.

(3) Bulked Segregant Analysis (BSA): BSA is widely employed to map the gene(s) of interest and coupling of NGS with BSA will improve the power of it in precise identification of marker-trait relationship.

(4) MutMap: MutMap is a method based on whole genome resequencing of pooled DNA samples from the phenotypic extremes of a segregating population derived from a cross between a mutant of interest and the progenitor wild type line. As compared to previous marker systems, NGS is very efficient for map-based gene discovery because it simultaneously performs SNP discovery, SNP validation, and SNP genotyping in a mapping or mutant population.

(5) TILLING/Eco-TILLING by Sequencing: "TILLING-by-Sequencing," is a new approach in which target genes are amplified from pooled templates (representing natural mutants/ induced mutations) and then sequenced using NGS technology to discover novel rare mutants.

Thus, NGS can be extremely helpful to identify the recombinants in breaking linkage drag and new forms of genetic variation for use in breeding and is also important as a tool for characterizing plant genetic resources globally. Genomics-assisted breeding has dramatically shifted the way breeders are able to work with unadapted genetic resources. The trend for sequence-based genotyping to replace the use of fixed marker arrays seems realistic, particularly as the cost of sequencing continues to fall, and is already happening in many crop species.


1. Varshney, R.K., Terauchi, R. and McCouch, S.R. (2014) Harvesting the promising fruits of genomics: applying genome sequencing technologies to crop breeding.e1001883.
2. Varshney, R.K., Graner, A. and Sorrells, M.E. (2005) Genomics-assisted breeding for crop improvement. Trends in Plant Science10:621-630.

About Author / Additional Info:
I am currently pursuing Ph.D. in Genetics from Indian Agricultural Research Institute.

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