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

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 disea...

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Autores principales: Schoonmaker, Ashley N., Hulse-Kemp, Amanda M., Youngblood, Ramey C., Rahmat, Zainab, Atif Iqbal, Muhammad, Rahman, Mehboob-ur, Kochan, Kelli J., Scheffler, Brian E., Scheffler, Jodi A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10005503/
https://www.ncbi.nlm.nih.gov/pubmed/36904013
http://dx.doi.org/10.3390/plants12051153
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author Schoonmaker, Ashley N.
Hulse-Kemp, Amanda M.
Youngblood, Ramey C.
Rahmat, Zainab
Atif Iqbal, Muhammad
Rahman, Mehboob-ur
Kochan, Kelli J.
Scheffler, Brian E.
Scheffler, Jodi A.
author_facet Schoonmaker, Ashley N.
Hulse-Kemp, Amanda M.
Youngblood, Ramey C.
Rahmat, Zainab
Atif Iqbal, Muhammad
Rahman, Mehboob-ur
Kochan, Kelli J.
Scheffler, Brian E.
Scheffler, Jodi A.
author_sort Schoonmaker, Ashley N.
collection PubMed
description 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.
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spelling pubmed-100055032023-03-11 Detecting Cotton Leaf Curl Virus Resistance Quantitative Trait Loci in Gossypium hirsutum and iCottonQTL a New R/Shiny App to Streamline Genetic Mapping Schoonmaker, Ashley N. Hulse-Kemp, Amanda M. Youngblood, Ramey C. Rahmat, Zainab Atif Iqbal, Muhammad Rahman, Mehboob-ur Kochan, Kelli J. Scheffler, Brian E. Scheffler, Jodi A. Plants (Basel) Article 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. MDPI 2023-03-03 /pmc/articles/PMC10005503/ /pubmed/36904013 http://dx.doi.org/10.3390/plants12051153 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Schoonmaker, Ashley N.
Hulse-Kemp, Amanda M.
Youngblood, Ramey C.
Rahmat, Zainab
Atif Iqbal, Muhammad
Rahman, Mehboob-ur
Kochan, Kelli J.
Scheffler, Brian E.
Scheffler, Jodi A.
Detecting Cotton Leaf Curl Virus Resistance Quantitative Trait Loci in Gossypium hirsutum and iCottonQTL a New R/Shiny App to Streamline Genetic Mapping
title Detecting Cotton Leaf Curl Virus Resistance Quantitative Trait Loci in Gossypium hirsutum and iCottonQTL a New R/Shiny App to Streamline Genetic Mapping
title_full Detecting Cotton Leaf Curl Virus Resistance Quantitative Trait Loci in Gossypium hirsutum and iCottonQTL a New R/Shiny App to Streamline Genetic Mapping
title_fullStr Detecting Cotton Leaf Curl Virus Resistance Quantitative Trait Loci in Gossypium hirsutum and iCottonQTL a New R/Shiny App to Streamline Genetic Mapping
title_full_unstemmed Detecting Cotton Leaf Curl Virus Resistance Quantitative Trait Loci in Gossypium hirsutum and iCottonQTL a New R/Shiny App to Streamline Genetic Mapping
title_short Detecting Cotton Leaf Curl Virus Resistance Quantitative Trait Loci in Gossypium hirsutum and iCottonQTL a New R/Shiny App to Streamline Genetic Mapping
title_sort detecting cotton leaf curl virus resistance quantitative trait loci in gossypium hirsutum and icottonqtl a new r/shiny app to streamline genetic mapping
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10005503/
https://www.ncbi.nlm.nih.gov/pubmed/36904013
http://dx.doi.org/10.3390/plants12051153
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