Files and links (2)
Published (Version of record)CC BY V4.0, Open Access
Published (Version of record)CC BY V4.0, Open
Journal article
An improved 7K SNP array, the C7AIR, provides a wealth of validated SNP markers for rice breeding and genetics studies
PloS One, Vol.15(5), pp.1-14
14/05/2020
PMCID: PMC7224494
PMID: 32407369
Metrics
3 File views/ downloads
21 Record Views
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Source: InCites
Abstract
Single nucleotide polymorphisms (SNPs) are highly abundant, amendable to high-throughput genotyping, and useful for a number of breeding and genetics applications in crops. SNP frequencies vary depending on the species and populations under study, and therefore target SNPs need to be carefully selected to be informative for each application. While multiple SNP genotyping systems are available for rice (Oryza sativa L. and its relatives), they vary in their informativeness, cost, marker density, speed, flexibility, and data quality. In this study, we report the development and performance of the Cornell-IR LD Rice Array (C7AIR), a second-generation SNP array containing 7,098 markers that improves upon the previously released C6AIR. The C7AIR is designed to detect genome-wide polymorphisms within and between subpopulations of O. sativa, as well as O. glaberrima, O. rufipogon and O. nivara. The C7AIR combines top-performing SNPs from several previous rice arrays, including 4,007 SNPs from the C6AIR, 2,056 SNPs from the High Density Rice Array (HDRA), 910 SNPs from the 384-SNP GoldenGate sets, 189 SNPs from the 44K array selected to add information content for elite U.S. tropical japonica rice varieties, and 8 trait-specific SNPs. To demonstrate its utility, we carried out a genome-wide association analysis for plant height, employing the C7AIR across a diversity panel of 189 rice accessions and identified 20 QTLs contributing to plant height. The C7AIR SNP chip has so far been used for genotyping >10,000 rice samples. It successfully differentiates the five subpopulations of Oryza sativa, identifies introgressions from wild and exotic relatives, and is useful for quantitative trait loci (QTL) and association mapping in diverse materials. Moreover, data from the C7AIR provides valuable information that can be used to select informative and reliable SNP markers for conversion to lower-cost genotyping platforms for genomic selection and other downstream applications in breeding.
Details
- Title
- An improved 7K SNP array, the C7AIR, provides a wealth of validated SNP markers for rice breeding and genetics studies
- Creators
- Karina Y Morales - Texas A&M UniversityNamrata Singh - Cornell UniversityFrancisco Agosto Perez - Cornell UniversityJohn Carlos Ignacio - International Rice Research Institute (Phillipines)Ranjita Thapa - University of Nebraska–LincolnJuan D Arbelaez - University of Illinois Urbana-ChampaignRodante E Tabien - Texas A&M AgriLife Research CenterAdam Famoso - Louisiana State UniversityDiane R Wang - Cornell UniversityEndang M Septiningsih - Texas A&M UniversityYuxin Shi - Cornell UniversityTobias Kretzschmar - International Rice Research InstituteSusan R McCouch - Cornell UniversityMichael J Thomson - Texas A&M University
- Publication Details
- PloS One, Vol.15(5), pp.1-14
- Publisher
- Public Library of Science; San Francisco, CA USA
- Grant note
- Funding was provided by the United States National Science Foundation (NSF-PGRP awards #1026555 and # IOS-1444511 to SMc), the Bill and Melinda Gates Foundation (via AfricaRice: “Rapid mobilization of alleles for rice cultivar improvement in sub-saharan Africa”), the Bill and Melinda Gates Foundation grant "Transforming Rice Breeding" number OPP1076488 (TK, JDA), Texas A&M AgriLife Research (MJT, EMS, RET), and the National Institute of Food and Agriculture, U. S. Department of Agriculture, Hatch projects 1009299 (MJT) and 1009300 (EMS). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
- Identifiers
- 991012925669902368
- Copyright
- © 2020 Morales et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Academic Unit
- Faculty of Science and Engineering; School of Environment, Science and Engineering; Science; Southern Cross Plant Science
- Language
- English
- Resource Type
- Journal article