Detecting Cotton Leaf Curl Virus Resistance Quantitative Trait Loci in Gossypium hirsutum and iCottonQTL a New R/Shiny App to Streamline Genetic Mapping

Author:

Schoonmaker Ashley N.12ORCID,Hulse-Kemp Amanda M.123ORCID,Youngblood Ramey C.4,Rahmat Zainab56,Atif Iqbal Muhammad6,Rahman Mehboob-ur6ORCID,Kochan Kelli J.7ORCID,Scheffler Brian E.8ORCID,Scheffler Jodi A.9ORCID

Affiliation:

1. Bioinformatics Graduate Program, North Carolina State University, Raleigh, NC 27695, USA

2. Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC 27695, USA

3. USDA Agricultural Research Service, Genomics and Bioinformatics Research Unit, Raleigh, NC 27695, USA

4. Institute for Genomics, Biocomputing and Biotechnology, Mississippi State University, Starkville, MS 39762, USA

5. Plant Genomics and Molecular Breeding Laboratory, National Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences, (NIBGE-C, PIEAS), Faisalabad 38000, Punjab, Pakistan

6. School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia

7. Institute for Genome Sciences and Society, Texas A&M University, College Station, TX 77843, USA

8. USDA Agricultural Research Service, Genomics and Bioinformatics Research Unit, Stoneville, MS 38776, USA

9. USDA Agricultural Research Service, Crop Genetics Research Unit, Stoneville, MS 38776, USA

Abstract

Cotton leaf curl virus (CLCuV) causes devastating losses to fiber production in Central Asia. Viral spread across Asia in the last decade is causing concern that the virus will spread further before resistant varieties can be bred. Current development depends on screening each generation under disease pressure in a country where the disease is endemic. We utilized quantitative trait loci (QTL) mapping in four crosses with different sources of resistance to identify single nucleotide polymorphism (SNP) markers associated with the resistance trait to allow development of varieties without the need for field screening every generation. To assist in the analysis of multiple populations, a new publicly available R/Shiny App was developed to streamline genetic mapping using SNP arrays and to also provide an easy method to convert and deposit genetic data into the CottonGen database. Results identified several QTL from each cross, indicating possible multiple modes of resistance. Multiple sources of resistance would provide several genetic routes to combat the virus as it evolves over time. Kompetitive allele specific PCR (KASP) markers were developed and validated for a subset of QTL, which can be used in further development of CLCuV-resistant cotton lines.

Funder

USDA-ARS research project

USDA Agricultural Research Service

Publisher

MDPI AG

Subject

Plant Science,Ecology,Ecology, Evolution, Behavior and Systematics

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3