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GWAS hints at pleiotropic roles for FLOWERING LOCUS T in flowering time and yield-related traits in canola

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posted on 2024-11-15, 18:02 authored by Harsh Raman, Rosy Raman, Yu Qiu, Avilash Yadav, Sridevi Sureshkumar, Lauren Borg, Maheswaran Rohan, David Wheeler, Oliver Owen, Ian Menz, Sureshkumar Balasubramanian
Background: Transition to flowering at the right time is critical for local adaptation and to maximize grain yield in crops. Canola is an important oilseed crop with extensive variation in flowering time among varieties. However, our understanding of underlying genes and their role in canola productivity is limited. Results: We report our analyses of a diverse GWAS panel (300-368 accessions) of canola and identify SNPs that are significantly associated with variation in flowering time and response to photoperiod across multiple locations. We show that several of these associations map in the vicinity of FLOWERING LOCUS T (FT) paralogs and its known transcriptional regulators. Complementary QTL and eQTL mapping studies, conducted in an Australian doubled haploid population, also detected consistent genomic regions close to the FT paralogs associated with flowering time and yield-related traits. FT sequences vary between accessions. Expression levels of FT in plants grown in field (or under controlled environment cabinets) correlated with flowering time. We show that markers linked to the FT paralogs display association with variation in multiple traits including flowering time, plant emergence, shoot biomass and grain yield. Conclusions: Our findings suggest that FT paralogs not only control flowering time but also modulate yield-related productivity traits in canola.

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Citation

Raman, H., Raman, R., Qiu, Y., Yadav, A., Sureshkumar, S., Borg, L., Rohan, M., Wheeler, D., Owen, O., Menz, I. & Balasubramanian, S. (2019). GWAS hints at pleiotropic roles for FLOWERING LOCUS T in flowering time and yield-related traits in canola. BMC Genomics, 20 (1), 636-1-636-18.

Journal title

BMC Genomics

Volume

20

Issue

1

Language

English

RIS ID

138103

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