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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

High-Resolution Inflorescence Phenotyping Using a Novel Image-Analysis Pipeline, PANorama

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Autor(es):
Crowell, Samuel [1] ; Falcao, Alexandre X. [2, 3] ; Shah, Ankur [2] ; Wilson, Zachary [2] ; Greenberg, Anthony J. [2] ; McCouch, Susan R. [1, 2]
Número total de Autores: 6
Afiliação do(s) autor(es):
[1] Cornell Univ, Dept Plant Biol, Ithaca, NY 14853 - USA
[2] Cornell Univ, Dept Plant Breeding & Genet, Ithaca, NY 14853 - USA
[3] Univ Estadual Campinas, Inst Comp, Dept Informat Syst, BR-13083852 Sao Paulo - Brazil
Número total de Afiliações: 3
Tipo de documento: Artigo Científico
Fonte: Plant Physiology; v. 165, n. 2, p. 479-495, JUN 2014.
Citações Web of Science: 22
Resumo

Variation in inflorescence development is an important target of selection for numerous crop species, including many members of the Poaceae (grasses). In Asian rice (Oryza sativa), inflorescence (panicle) architecture is correlated with yield and grain-quality traits. However, many rice breeders continue to use composite phenotypes in selection pipelines, because measuring complex, branched panicles requires a significant investment of resources. We developed an open-source phenotyping platform, PANorama, which measures multiple architectural and branching phenotypes from images simultaneously. PANorama automatically extracts skeletons from images, allows users to subdivide axes into individual internodes, and thresholds away structures, such as awns, that normally interfere with accurate panicle phenotyping. PANorama represents an improvement in both efficiency and accuracy over existing panicle imaging platforms, and flexible implementation makes PANorama capable of measuring a range of organs from other plant species. Using high-resolution phenotypes, a mapping population of recombinant inbred lines, and a dense single-nucleotide polymorphism data set, we identify, to our knowledge, the largest number of quantitative trait loci (QTLs) for panicle traits ever reported in a single study. Several areas of the genome show pleiotropic clusters of panicle QTLs, including a region near the rice Green Revolution gene SEMIDWARF1. We also confirm that multiple panicle phenotypes are distinctly different among a small collection of diverse rice varieties. Taken together, these results suggest that clusters of small-effect QTLs may be responsible for varietal or subpopulation-specific panicle traits, representing a significant opportunity for rice breeders selecting for yield performance across different genetic backgrounds. (AU)

Processo FAPESP: 11/03110-6 - Análise de imagens 3D de raízes de plantas visando associações genótipo-fenótipo
Beneficiário:Alexandre Xavier Falcão
Modalidade de apoio: Bolsas no Exterior - Pesquisa