A TILLING by sequencing approach to identify induced mutations in sunflower genes

Abstract The Targeting Induced Local Lesions in Genomes (TILLING) technology is a reverse genetic strategy broadly applicable to every kind of genome and represents an attractive tool for functional genomic and agronomic applications. It consists of chemical random mutagenesis followed by high-throu...

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Autores principales:	Valentina Fanelli, Kathie J. Ngo, Veronica L. Thompson, Brennan R. Silva, Helen Tsai, Wilma Sabetta, Cinzia Montemurro, Luca Comai, Stacey L. Harmer
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/269d8785ed73482ca6d4af804dcf9c0c
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spelling	oai:doaj.org-article:269d8785ed73482ca6d4af804dcf9c0c2021-12-02T16:57:57ZA TILLING by sequencing approach to identify induced mutations in sunflower genes10.1038/s41598-021-89237-w2045-2322https://doaj.org/article/269d8785ed73482ca6d4af804dcf9c0c2021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-89237-whttps://doaj.org/toc/2045-2322Abstract The Targeting Induced Local Lesions in Genomes (TILLING) technology is a reverse genetic strategy broadly applicable to every kind of genome and represents an attractive tool for functional genomic and agronomic applications. It consists of chemical random mutagenesis followed by high-throughput screening of point mutations in targeted genomic regions. Although multiple methods for mutation discovery in amplicons have been described, next-generation sequencing (NGS) is the tool of choice for mutation detection because it quickly allows for the analysis of a large number of amplicons. The aim of the present work was to screen a previously generated sunflower TILLING population and identify alterations in genes involved in several important and complex physiological processes. Twenty-one candidate sunflower genes were chosen as targets for the screening. The TILLING by sequencing strategy allowed us to identify multiple mutations in selected genes and we subsequently validated 16 mutations in 11 different genes through Sanger sequencing. In addition to addressing challenges posed by outcrossing, our detection and validation of mutations in multiple regulatory loci highlights the importance of this sunflower population as a genetic resource.Valentina FanelliKathie J. NgoVeronica L. ThompsonBrennan R. SilvaHelen TsaiWilma SabettaCinzia MontemurroLuca ComaiStacey L. HarmerNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Valentina Fanelli Kathie J. Ngo Veronica L. Thompson Brennan R. Silva Helen Tsai Wilma Sabetta Cinzia Montemurro Luca Comai Stacey L. Harmer A TILLING by sequencing approach to identify induced mutations in sunflower genes
description	Abstract The Targeting Induced Local Lesions in Genomes (TILLING) technology is a reverse genetic strategy broadly applicable to every kind of genome and represents an attractive tool for functional genomic and agronomic applications. It consists of chemical random mutagenesis followed by high-throughput screening of point mutations in targeted genomic regions. Although multiple methods for mutation discovery in amplicons have been described, next-generation sequencing (NGS) is the tool of choice for mutation detection because it quickly allows for the analysis of a large number of amplicons. The aim of the present work was to screen a previously generated sunflower TILLING population and identify alterations in genes involved in several important and complex physiological processes. Twenty-one candidate sunflower genes were chosen as targets for the screening. The TILLING by sequencing strategy allowed us to identify multiple mutations in selected genes and we subsequently validated 16 mutations in 11 different genes through Sanger sequencing. In addition to addressing challenges posed by outcrossing, our detection and validation of mutations in multiple regulatory loci highlights the importance of this sunflower population as a genetic resource.
format	article
author	Valentina Fanelli Kathie J. Ngo Veronica L. Thompson Brennan R. Silva Helen Tsai Wilma Sabetta Cinzia Montemurro Luca Comai Stacey L. Harmer
author_facet	Valentina Fanelli Kathie J. Ngo Veronica L. Thompson Brennan R. Silva Helen Tsai Wilma Sabetta Cinzia Montemurro Luca Comai Stacey L. Harmer
author_sort	Valentina Fanelli
title	A TILLING by sequencing approach to identify induced mutations in sunflower genes
title_short	A TILLING by sequencing approach to identify induced mutations in sunflower genes
title_full	A TILLING by sequencing approach to identify induced mutations in sunflower genes
title_fullStr	A TILLING by sequencing approach to identify induced mutations in sunflower genes
title_full_unstemmed	A TILLING by sequencing approach to identify induced mutations in sunflower genes
title_sort	tilling by sequencing approach to identify induced mutations in sunflower genes
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/269d8785ed73482ca6d4af804dcf9c0c
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A TILLING by sequencing approach to identify induced mutations in sunflower genes

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