Harvesting the Promising Fruits of Genomics: Applying Genome Sequencing Technologies to Crop Breeding

Title 
Harvesting the Promising Fruits of Genomics: Applying Genome Sequencing Technologies to Crop Breeding 
Publication Type 
Journal Article 
Authors 
Varshney RK, Terauchi R, McCouch SR 
Year of Publication 
2014 
Volume 
12 
Journal 
PLoS Biology 
Issue 
Pagination 
e1001883 
Date Published 
6/2014 
Keywords 
association studies, Beans, bi-parental mapping population, breeding value, Cassava, Chickpea, Cowpea, Data mgmt, gene function analysis, Genetic Variation, genomic selection, Groundnut, high throughput phenotyping, immortalized recombinant lines, Maize, mapping, marker-assisted selection, MAS, multi-parent mapping population, mutant population, Next generation sequencing, NGS, parental selection, QTL, quantitative trait locus, Rice, Sorghum, Soya Bean, training population, Wheat 
URL 
http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001883 
DOI 
10.1371/journal.pbio.1001883.g001 
Abstract 

Abstract

Next generation sequencing (NGS) technologies are being used to generate whole genome sequences for a wide range of crop species. When combined with precise phenotyping methods, these technologies provide a powerful and rapid tool for identifying the genetic basis of agriculturally important traits and for predicting the breeding value of individuals in a plant breeding population. Here we summarize current trends and future prospects for utilizing NGS-based technologies to develop crops with improved trait performance and increase the efficiency of modern plant breeding. It is our hope that the application of NGS technologies to plant breeding will help us to meet the challenge of feeding a growing world population.

Introduction

In 2012, the world population exceeded 7 billion people and is expected to continue growing. To feed this growing population and meet rising expectations regarding food quality, food production must increase by an estimated 70% by 2050. Recent abrupt climatic changes make stable food production even more difficult and put pressure on fragile environments. There is, therefore, an urgent need to accelerate crop breeding improvements and to implement new management strategies that together can achieve sustainable yield increases without further expanding farmland or damaging the environment.

To meet these challenges, scientists are developing new and more efficient breeding strategies that integrate genomic technologies and high throughput phenotyping to better utilize natural and induced genetic variation. Rapid developments in next generation sequencing (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. As the cost of sequencing has decreased, breeders have begun to utilize NGS with increasing regularity to sequence large populations of plants, increasing the resolution of gene and quantitative trait locus (QTL) discovery and providing the basis for modeling complex genotype-phenotype relationships at the whole-genome level.

Specialized plant genetic stocks, such as bi-parental and multi-parent mapping populations, mutant populations, and immortalized collections of recombinant lines, have been generated to facilitate mapping and gene function analysis via association studies and QTL mapping in several crop species. Knowledge about the identity and map location of agriculturally important genes and QTL provides the basis for parental selection and marker-assisted selection (MAS) in plant breeding. Alternatively, genotypic and phenotypic datasets on training populations can be used to develop models to predict the breeding value of lines in an approach called genomic selection (GS). We discuss both approaches later in this Essay.

 

 
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