scispace - formally typeset
Open AccessJournal ArticleDOI

Next generation sequencing technologies for next generation plant breeding.

Reads0
Chats0
TLDR
The next generation plant breeding would demand more efficient technologies to develop low cost, high-throughput genotyping for screening large populations within a smaller time frame.
Abstract
As a term, “next generation plant breeding” is increasingly becoming popular in crop breeding programmes, conferences, scientific fora and social media (Schnable, 2013). Being a frontier area of crop science and business, it is gaining considerable interest among scientific community and policymakers and funds flow from entrepreneurs and research funding agencies. Plant breeding is a continuous attempt to alter genetic architecture of crop plants for efficient utilization as food, fodder, fiber, fuel or other end uses. Although the scientific concepts in plant breeding originated about 100 years ago, domestication and selection of desirable plants from prehistoric periods have contributed tremendously to ensure human food security (Gepts, 2004). During the past few decades, well supported crop improvement programmes for major crops started reaping benefits from cutting edge technologies of biological sciences, particularly in the form of molecular markers and transgenic crop development, which in combination with conventional phenotype based selection, defines the current generation plant breeding practices. Different types of molecular markers have been developed and extensively used during the last three decades for identifying linkage between genes and markers, discovering quantitative trait loci (QTLs), pyramiding desired genes and performing marker assisted foreground and background selections for introgression of desired traits (Varshney and Tuberosa, 2007). However, these markers are based mostly on electrophoretic separation of DNA fragments, which limits detection of genetic polymorphism. In large plant breeding populations, genotyping may take up several months depending on marker system, adding more cost to genotyping. The next generation plant breeding would thus demand more efficient technologies to develop low cost, high-throughput genotyping for screening large populations within a smaller time frame.

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

Genomic Selection in the Era of Next Generation Sequencing for Complex Traits in Plant Breeding.

TL;DR: The NGS-based genotyping have increased genomic-estimated breeding value prediction accuracies over other established marker platform in cereals and other crop species, and made the dream of GS true in crop breeding, but to harness the true benefits from GS, these marker technologies will be combined with high-throughput phenotyping for achieving the valuable genetic gain from complex traits.
Journal ArticleDOI

Mining and Development of Novel SSR Markers Using Next Generation Sequencing (NGS) Data in Plants

TL;DR: An overview of the next generation sequencing is presented, with a focus on the efficient use of de novo transcriptome sequencing (RNA-Seq) and related tools for mining and development of microsatellites in plants.
Journal ArticleDOI

Understanding salinity responses and adopting ‘omics-based’ approaches to generate salinity tolerant cultivars of rice

TL;DR: This review looks into various responses at cellular and whole plant level generated in rice plants toward salinity stress thus, evaluating the suitability of intervention of functional genomics to raise stress tolerant plants.
Journal ArticleDOI

A draft genome of field pennycress (Thlaspi arvense) provides tools for the domestication of a new winter biofuel crop

TL;DR: A comprehensive analysis of pennycress gene homologues involved in glucosinolate biosynthesis, metabolism, and transport pathways revealed high sequence conservation compared with other Brassicaceae species, and helps validate the assembly of the penny cress gene space in this draft genome.
Journal ArticleDOI

Genome-wide SNP discovery and population structure analysis in pepper ( Capsicum annuum ) using genotyping by sequencing

TL;DR: In this article, the authors used the GBS approach for the genome-wide identification of SNPs in a collection of Capsicum spp. accessions and for the assessment of the level of genetic diversity in a subset of 222 cultivated pepper (Capsicum annum) genotypes.
References
More filters
Journal ArticleDOI

A Robust, Simple Genotyping-by-Sequencing (GBS) Approach for High Diversity Species

TL;DR: A procedure for constructing GBS libraries based on reducing genome complexity with restriction enzymes (REs) is reported, which is simple, quick, extremely specific, highly reproducible, and may reach important regions of the genome that are inaccessible to sequence capture approaches.
Journal ArticleDOI

Genome-wide genetic marker discovery and genotyping using next-generation sequencing.

TL;DR: Best practices for several NGS methods for genome-wide genetic marker development and genotyping that use restriction enzyme digestion of target genomes to reduce the complexity of the target.
Journal ArticleDOI

Development of High-Density Genetic Maps for Barley and Wheat Using a Novel Two-Enzyme Genotyping-by-Sequencing Approach

TL;DR: The GBS approach presented here provides a powerful method of developing high-density markers in species without a sequenced genome while providing valuable tools for anchoring and ordering physical maps and whole-genome shotgun sequence.
Journal ArticleDOI

Solution Hybrid Selection with Ultra-long Oligonucleotides for Massively Parallel Targeted Sequencing

TL;DR: A capture method that uses biotinylated RNA 'baits' to fish targets out of a 'pond' of DNA fragments that uniformity was such that ∼60% of target bases in the exonic 'catch', and ∼80% in the regional catch, had at least half the mean coverage.
Journal ArticleDOI

TASSEL-GBS: a high capacity genotyping by sequencing analysis pipeline

TL;DR: The tassel-gbs pipeline, designed for the efficient processing of raw GBS sequence data into SNP genotypes, is described and benchmark it based upon a large scale, species wide analysis in maize, where the average error rate was reduced to 0.0042.
Related Papers (5)