Michael W Bevan* and Cristobal Uauy
Corresponding author: Michael W Bevan michael.bevan@jic.ac.uk
The electronic version of this article is the complete one and can be found online at:http://genomebiology.com/2013/14/6/206
| Published: | 24 June 2013 |
© 2013 BioMed Central Ltd
Abstract
The sequencing of large and complex genomes of crop species, facilitated by new sequencing technologies and bioinformatic approaches, has provided new opportunities for crop improvement. Current challenges include understanding how genetic variation translates into phenotypic performance in the field.
Keywords:
Genomics; crop improvement; genomic selection; systems breeding
Background
Genomics, the analysis of an organism's complete DNA sequence, has been one of the most transformative influences on biological studies. The genome sequences of organisms are fundamentally important for understanding the functions of individual genes and their networks, for defining evolutionary relationships and processes, and for revealing previously unknown regulatory mechanisms that coordinate the activities of genes. These genomics-based approaches are having a profound influence on both human disease diagnostics and treatment [1] and, equally importantly, on the improvement of crops for food and fuel production. In this review, we summarize progress in sequencing crop genomes, identify remaining technical challenges, and describe how genomics-based applications can aid crop improvement. We then assess the impact of genomics on plant breeding and crop improvement, showing how it is accelerating the improvement of staple and 'orphan' crops, and facilitating the utilization of untapped allelic variation. Finally, we speculate about the future impacts of genomics on plant biology and crop improvement by developing the concept of systems breeding, which integrates information on gene function, genome states, and regulatory networks across populations and species to create a predictive framework for estimating the contributions of genetic and epigenetic variation to phenotypes and field performance.
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