4.7 Article

Genome-Wide Association Study Reveals Candidate Genes for Flowering Time Variation in Common Bean (Phaseolus vulgaris L.)

Journal

FRONTIERS IN PLANT SCIENCE
Volume 10, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fpls.2019.00962

Keywords

Phaseolus vulgaris L.; flowering time control; ddRAD-seq; GWAS; candidate gene analysis

Categories

Funding

  1. European Community [266394, 245058, 774271]
  2. Progetto per l'attuazione delle attivita contenute nel programma triennale 2017-2019 per la conservazione, caratterizzazione, uso e valorizzazione delle risorse genetiche vegetali per l'alimentazione e l'agricoltura (RGV-FAO project) [0011746]
  3. H2020 Societal Challenges Programme [774271] Funding Source: H2020 Societal Challenges Programme

Ask authors/readers for more resources

The common bean is one of the most important staples in many areas of the world. Extensive phenotypic and genetic characterization of unexplored bean germplasm are still needed to unlock the breeding potential of this crop. Dissecting genetic control of flowering time is of pivotal importance to foster common bean breeding and to develop new varieties able to adapt to changing climatic conditions. Indeed, flowering time strongly affects yield and plant adaptation ability. The aim of this study was to investigate the genetic control of days to flowering using a whole genome association approach on a panel of 192 highly homozygous common bean genotypes purposely developed from landraces using Single Seed Descent. The phenotypic characterization was carried out at two experimental sites throughout two growing seasons, using a randomized partially replicated experimental design. The same plant material was genotyped using double digest Restriction-site Associated DNA sequencing producing, after a strict quality control, a dataset of about 50 k Single Nucleotide Polymorphisms (SNPs). The Genome-Wide Association Study revealed significant and meaningful associations between days to flowering and several SNP markers; seven genes are proposed as the best candidates to explain the detected associations.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available