Genome wide association study of 5 agronomic traits in olive (Olea europaea L.).

Clicks: 374
ID: 78914
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #151 of 1,628 articles by views in Scientific reports

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 1,628 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Olive (Olea europaea L.) is one of the most economically and historically important fruit crops worldwide. Genetic progress for valuable agronomic traits has been slow in olive despite its importance and benefits. Advances in next generation sequencing technologies provide inexpensive and highly reproducible genotyping approaches such as Genotyping by Sequencing, enabling genome wide association study (GWAS). Here we present the first comprehensive GWAS study on olive using GBS. A total of 183 accessions (FULL panel) were genotyped using GBS, 94 from the Turkish Olive GenBank Resource (TOGR panel) and 89 from the USDA-ARS National Clonal Germplasm Repository (NCGR panel) in the USA. After filtering low quality and redundant markers, GWAS was conducted using 24,977 SNPs in FULL, TOGR and NCGR panels. In total, 52 significant associations were detected for leaf length, fruit weight, stone weight and fruit flesh to pit ratio using the MLM_K. Significant GWAS hits were mapped to their positions and 19 candidate genes were identified within a 10-kb distance of the most significant SNP. Our findings provide a framework for the development of markers and identification of candidate genes that could be used in olive breeding programs.
Reference Key
kaya2019genomescientific Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Kaya, Hilal Betul;Akdemir, Deniz;Lozano, Roberto;Cetin, Oznur;Sozer Kaya, Hulya;Sahin, Mustafa;Smith, Jenny L;Tanyolac, Bahattin;Jannink, Jean-Luc;
Journal Scientific reports
Year 2019
DOI
10.1038/s41598-019-55338-w
URL
Keywords
outcome treatment myasthenia gravis refractory disease

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.