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Allele mining and enhanced genetic recombination for rice breeding

Author:
Leung, Hei   Raghavan, Chitra   Zhou, Bo   Oliva, Ricardo   Choi, Il Ryong   Lacorte, Vanica   Jubay, Mona Liza   Cruz, Casiana Vera   Gregorio, Glenn   Singh, Rakesh Kumar   Ulat, Victor Jun   Borja, Frances Nikki   Mauleon, Ramil   Alexandrov, Nickolai N.   McNally, Kenneth L.   Sackville Hamilton, Ruaraidh   


Journal:
Rice


Issue Date:
2015


Abstract(summary):

Traditional rice varieties harbour a large store of genetic diversity with potential to accelerate rice improvement. For a long time, this diversity maintained in the International Rice Genebank has not been fully used because of a lack of genome information. The publication of the first reference genome of Nipponbare by the International Rice Genome Sequencing Project (IRGSP) marked the beginning of a systematic exploration and use of rice diversity for genetic research and breeding. Since then, the Nipponbare genome has served as the reference for the assembly of many additional genomes. The recently completed 3000 Rice Genomes Project together with the public database (SNP-Seek) provides a new genomic and data resource that enables the identification of useful accessions for breeding. Using disease resistance traits as case studies, we demonstrated the power of allele mining in the 3,000 genomes for extracting accessions from the GeneBank for targeted phenotyping. Although potentially useful landraces can now be identified, their use in breeding is often hindered by unfavourable linkages. Efficient breeding designs are much needed to transfer the useful diversity to breeding. Multi-parent Advanced Generation InterCross (MAGIC) is a breeding design to produce highly recombined populations. The MAGIC approach can be used to generate pre-breeding populations with increased genotypic diversity and reduced linkage drag. Allele mining combined with a multi-parent breeding design can help convert useful diversity into breeding-ready genetic resources.


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