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[National Research Projects] NSFC-Approaches and integrated tools for the efficient use of genetic populations and gene information in plant breeding

Hits:  |  Time:2012-10-19

Supervised by: Jiankang Wang

Project code: 31271798

Period: Jan 2013 to Dec 2016

Abstract:

Most characters that plant breeders wish to improve are quantitative traits, among which are yield and yield components, end-use qualities, adaptation, and various biotic and abiotic resistances or tolerances. Along with the rapid development in molecular biology and biotechnology, more and more genes on these traits have been mapped and cloned. However, most genetic populations and identified gene information have not been efficiently used in plant breeding, especially when considering the large amount of time and efforts spent on developing the genetic populations and conducting the genetic studies. The challenge has been and still remains to convert the ever more plentiful supply of genetic information into an integrated set of markers useful for breeding, and how to integrate such markers into the most efficient breeding scheme. In this project, we will, (1) develop efficient algorithms for high-density genetic linkage map construction, gene by gene interactions, gene by environment interactions, and genotype to phenotypic predictions; (2) enhance the existing genetic analysis and breeding simulation tools, and develop the integrated and decision supported breeding tools; (3) use one CSSL and one RIL population in rice to demonstrate the strategies to integrate the genetic populations and the identified gene information from genetic study into conventional plant breeding. We aim to build a bridge leading from “genetic study” to “field breeding”. This project is designed to take the challenges on the efficient use of genetic population and known gene information in conventional plant breeding.The integrated tools from this project will greatly assist the efficient application of genetic populations and known gene information, and greatly improve the efficiency and predictability of plant breeding.