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Mol Ecol. 2016 Sep;25(17):4177-96. doi: 10.1111/mec.13768.

Extreme QTL mapping of germination speed in Arabidopsis thaliana.

Author information

1
Department of Biology, Center for Genomics and Systems Biology, New York University, 12 Waverly Place, New York, NY, 10003, USA.
2
Center for Genomics and Systems Biology, NYU Abu Dhabi Research Institute, New York University Abu Dhabi, Saadiyat Island, Abu Dhabi, United Arab Emirates.
3
Molecular and Computational Biology Section, University of Southern California, Ray R. Irani Hall 201, Los Angeles, CA, 90089-2910, USA.

Abstract

Seed germination is a key life history transition for annual plants and partly determines lifetime performance and fitness. Germination speed, the elapsed time for a nondormant seed to germinate, is a poorly understood trait important for plants' competitiveness and fitness in fluctuating environments. Germination speed varied by 30% among 18 Arabidopsis thaliana populations measured, and exhibited weak negative correlation with flowering time and seed weight, with significant genotype effect (P < 0.005). To dissect the genetic architecture of germination speed, we developed the extreme QTL (X-QTL) mapping method in A. thaliana. The method has been shown in yeast to increase QTL mapping power by integrating selective screening and bulk-segregant analysis in a very large mapping population. By pooled genotyping of top 5% of rapid germinants from ~100 000 F3 individuals, three X-QTL regions were identified on chromosomes 1, 3 and 4. All regions were confirmed as QTL regions by sequencing 192 rapid germinants from an independent F3 selection experiment. Positional overlaps were found between X-QTLs and previously identified seed, life history and fitness QTLs. Our method provides a rapid mapping platform in A. thaliana with potentially greater power. One can also relate identified X-QTLs to the A. thaliana physical map, facilitating candidate gene identification.

KEYWORDS:

bulk-segregant analysis; life history; quantitative genomics; seed ecology

PMID:
27454560
DOI:
10.1111/mec.13768
[Indexed for MEDLINE]

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