Autoria: MCCOUCH, S. R.; WRIGHT, M. H.; TUNG, C.-W.; MARON, L. G.; MCNALLY, K. L.; FITZGERALD, M.; DECLERCK, G.; AGOSTO-PEREZ, F.; KORNILIEV, P.; GREENBERG, A. J.; NAREDO, M. E. B.; MERCADO, S. M. Q.; HARRINGTON, S. E.; SHI, Y.; BRANCHINI, D. A.; FALCAO, P. R. K.; LEUNG, H.; EBANA, K.; YANO, M.; EIZENGA, G.; SINGH, N.; MCCLUNG, A.; MEZEY, J.

Resumo: Increasing food production is essential to meet the demands of a growing human population, with its rising income levels and nutritional expectations. To address the demand, plant breeders seek new sources of genetic variation to enhance the productivity, sustainability and resilience of crop varieties. Here we launch a high-resolution, open-access research platform to facilitate genome-wide association mapping in rice, a staple food crop. The platform provides an immortal collection of diverse germplasm, a high-density single-nucleotide polymorphism data set tailored for gene discovery, well-documented analytical strategies, and a suite of bioinformatics resources to facilitate biological interpretation. Using grain length, we demonstrate the power and resolution of our new high-density rice array, the accompanying genotypic data set, and an expanded diversity panel for detecting major and minor effect QTLs and subpopulation-specific alleles, with immediate implications for rice improvement.

Ano de publicação: 2016

Tipo de publicação: Artigo de periódico

Unidade: Embrapa Agricultura Digital

Palavras-chave: Biologia computacional, Dados genótipicos, Genoma