Genome-wide association identifies candidate genes for drought tolerance in coast redwood and giant sequoia.


Journal

The Plant journal : for cell and molecular biology
ISSN: 1365-313X
Titre abrégé: Plant J
Pays: England
ID NLM: 9207397

Informations de publication

Date de publication:
01 2022
Historique:
revised: 05 11 2021
received: 03 08 2021
accepted: 16 11 2021
pubmed: 21 11 2021
medline: 1 2 2022
entrez: 20 11 2021
Statut: ppublish

Résumé

Drought is a major limitation for survival and growth in plants. With more frequent and severe drought episodes occurring due to climate change, it is imperative to understand the genomic and physiological basis of drought tolerance to be able to predict how species will respond in the future. In this study, univariate and multitrait multivariate genome-wide association study methods were used to identify candidate genes in two iconic and ecosystem-dominating species of the western USA, coast redwood and giant sequoia, using 10 drought-related physiological and anatomical traits and genome-wide sequence-capture single nucleotide polymorphisms. Population-level phenotypic variation was found in carbon isotope discrimination, osmotic pressure at full turgor, xylem hydraulic diameter, and total area of transporting fibers in both species. Our study identified new 78 new marker × trait associations in coast redwood and six in giant sequoia, with genes involved in a range of metabolic, stress, and signaling pathways, among other functions. This study contributes to a better understanding of the genomic basis of drought tolerance in long-generation conifers and helps guide current and future conservation efforts in the species.

Identifiants

pubmed: 34800071
doi: 10.1111/tpj.15592
doi:

Substances chimiques

Carbon Isotopes 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

7-22

Commentaires et corrections

Type : CommentIn

Informations de copyright

© 2021 Society for Experimental Biology and John Wiley & Sons Ltd.

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Auteurs

Amanda R De La Torre (AR)

School of Forestry, Northern Arizona University, 200 E. Pine Knoll, Flagstaff, AZ, 86011, USA.

Manoj K Sekhwal (MK)

School of Forestry, Northern Arizona University, 200 E. Pine Knoll, Flagstaff, AZ, 86011, USA.

Daniela Puiu (D)

Department of Biomedical Engineering, Computer Science and Biostatistics & Center for Computational Biology, John Hopkins University, 3100 Wyman Park Dr, Wyman Park Building, Room S220, Baltimore, MD, 21211, USA.

Steven L Salzberg (SL)

Department of Biomedical Engineering, Computer Science and Biostatistics & Center for Computational Biology, John Hopkins University, 3100 Wyman Park Dr, Wyman Park Building, Room S220, Baltimore, MD, 21211, USA.

Alison D Scott (AD)

Department of Plant Sciences, University of California, Davis, One Shields Avenue, Davis, CA, 95616, USA.

Brian Allen (B)

Department of Plant Sciences, University of California, Davis, One Shields Avenue, Davis, CA, 95616, USA.

David B Neale (DB)

Department of Plant Sciences, University of California, Davis, One Shields Avenue, Davis, CA, 95616, USA.

Alana R O Chin (ARO)

Department of Plant Sciences, University of California, Davis, One Shields Avenue, Davis, CA, 95616, USA.

Thomas N Buckley (TN)

Department of Plant Sciences, University of California, Davis, One Shields Avenue, Davis, CA, 95616, USA.

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