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Genome-wide association study of 12 agronomic traits in peach.

ABSTRACT: Peach (Prunus persica L.) is a highly valuable crop species and is recognized by molecular researchers as a model fruit for the Rosaceae family. Using whole-genome sequencing data generated from 129 peach accessions, here we perform a comprehensive genome-wide association study for 12 key agronomic traits. We show that among the 10 qualitative traits investigated, nine exhibit consistent and more precise association signals than previously identified by linkage analysis. For two of the qualitative traits, we describe candidate genes, one potentially involved in cell death and another predicted to encode an auxin-efflux carrier, that are highly associated with fruit shape and non-acidity, respectively. Furthermore, we find that several genomic regions harbouring association signals for fruit weight and soluble solid content overlapped with predicted selective sweeps that occurred during peach domestication and improvement. Our findings contribute to the large-scale characterization of genes controlling agronomic traits in peach.

SUBMITTER: Cao K

PROVIDER: S-EPMC5105138 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Genome-wide association study of 12 agronomic traits in peach.

Cao Ke K Zhou Zhengkui Z Wang Qi Q Guo Jian J Zhao Pei P Zhu Gengrui G Fang Weichao W Chen Changwen C Wang Xinwei X Wang Xiaoli X Tian Zhixi Z Wang Lirong L

Nature communications 20161108

Peach (Prunus persica L.) is a highly valuable crop species and is recognized by molecular researchers as a model fruit for the Rosaceae family. Using whole-genome sequencing data generated from 129 peach accessions, here we perform a comprehensive genome-wide association study for 12 key agronomic traits. We show that among the 10 qualitative traits investigated, nine exhibit consistent and more precise association signals than previously identified by linkage analysis. For two of the qualitati ...[more]

PMID: 27824331

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Project description:Prunus species include many important perennial fruit crops, such as peach, plum, apricot, and related wild species. Here, we report de novo genome assemblies for five species, including the cultivated species peach (Prunus persica), plum (Prunus salicina), and apricot (Prunus armeniaca), and the wild peach species Tibetan peach (Prunus mira) and Chinese wild peach (Prunus davidiana). The genomes ranged from 240 to 276 Mb in size, with contig N50 values of 2.27-8.30 Mb and 25,333-27,826 protein-coding gene models. As the phylogenetic tree shows, plum diverged from its common ancestor with peach, wild peach species, and apricot ~7 million years ago (MYA). We analyzed whole-genome resequencing data of 417 peach accessions, called 3,749,618 high-quality SNPs, 577,154 small indels, 31,800 deletions, duplications, and inversions, and 32,338 insertions, and performed a structural variant-based genome-wide association study (GWAS) of key agricultural traits. From our GWAS data, we identified a locus associated with a fruit shape corresponding to the OVATE transcription factor, where a large inversion event correlates with higher OVATE expression in flat-shaped accessions. Furthermore, a GWAS revealed a NAC transcription factor associated with fruit developmental timing that is linked to a tandem repeat variant and elevated NAC expression in early-ripening accessions. We also identified a locus encoding microRNA172d, where insertion of a transposable element into its promoter was found in double-flower accessions. Thus, our efforts have suggested roles for OVATE, a NAC transcription factor, and microRNA172d in fruit shape, fruit development period, and floral morphology, respectively, that can be connected to traits in other crops, thereby demonstrating the importance of parallel evolution in the diversification of several commercially important domesticated species. In general, these genomic resources will facilitate functional genomics, evolutionary research, and agronomic improvement of these five and other Prunus species. We believe that structural variant-based GWASs can also be used in other plants, animal species, and humans and be combined with deep sequencing GWASs to precisely identify candidate genes and genetic architecture components.

Project description:The population growth trend in recent decades has resulted in continuing efforts to guarantee food security in which leguminous plants, such as the common bean (Phaseolus vulgaris L.), play a particularly important role as they are relatively cheap and have high nutritional value. To meet this demand for food, the main target for genetic improvement programs is to increase productivity, which is a complex quantitative trait influenced by many component traits. This research aims to identify Quantitative Trait Nucleotides (QTNs) associated with productivity and its components using multi-locus genome-wide association studies. Ten morpho-agronomic traits [plant height (PH), first pod insertion height (FPIH), number of nodules (NN), pod length (PL), total number of pods per plant (NPP), number of locules per pod (LP), number of seeds per pod (SP), total seed weight per plant (TSW), 100-seed weight (W100), and grain yield (YLD)] were evaluated in four environments for 178 Mesoamerican common bean domesticated accessions belonging to the Brazilian Diversity Panel. In order to identify stable QTNs, only those identified by multiple methods (mrMLM, FASTmrMLM, pLARmEB, and ISIS EM-BLASSO) or in multiple environments were selected. Among the identified QTNs, 64 were detected at least thrice by different methods or in different environments, and 39 showed significant phenotypic differences between their corresponding alleles. The alleles that positively increased the corresponding traits, except PH (for which lower values are desired), were considered favorable alleles. The most influenced trait by the accumulation of favorable alleles was PH, showing a 51.7% reduction, while NN, TSW, YLD, FPIH, and NPP increased between 18 and 34%. Identifying QTNs in several environments (four environments and overall adjusted mean) and by multiple methods reinforces the reliability of the associations obtained and the importance of conducting these studies in multiple environments. Using these QTNs through molecular techniques for genetic improvement, such as marker-assisted selection or genomic selection, can be a strategy to increase common bean production.

Dataset Information

Genome-wide association study of 12 agronomic traits in peach.

Publications

Genome-wide association study of 12 agronomic traits in peach.

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