Cargando…
Capturing and Selecting Senescence Variation in Wheat
Senescence is a highly quantitative trait, but in wheat the genetics underpinning senescence regulation remain relatively unknown. To select senescence variation and ultimately identify novel genetic regulators, accurate characterization of senescence phenotypes is essential. When investigating sene...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8085557/ https://www.ncbi.nlm.nih.gov/pubmed/33936128 http://dx.doi.org/10.3389/fpls.2021.638738 |
_version_ | 1783686367123865600 |
---|---|
author | Chapman, Elizabeth A. Orford, Simon Lage, Jacob Griffiths, Simon |
author_facet | Chapman, Elizabeth A. Orford, Simon Lage, Jacob Griffiths, Simon |
author_sort | Chapman, Elizabeth A. |
collection | PubMed |
description | Senescence is a highly quantitative trait, but in wheat the genetics underpinning senescence regulation remain relatively unknown. To select senescence variation and ultimately identify novel genetic regulators, accurate characterization of senescence phenotypes is essential. When investigating senescence, phenotyping efforts often focus on, or are limited to, the visual assessment of flag leaves. However, senescence is a whole-plant process, involving remobilization and translocation of resources into the developing grain. Furthermore, the temporal progression of senescence poses challenges regarding trait quantification and description, whereupon the different models and approaches applied result in varying definitions of apparently similar metrics. To gain a holistic understanding of senescence, we phenotyped flag leaf and peduncle senescence progression, alongside grain maturation. Reviewing the literature, we identified techniques commonly applied in quantification of senescence variation and developed simple methods to calculate descriptive and discriminatory metrics. To capture senescence dynamism, we developed the idea of calculating thermal time to different flag leaf senescence scores, for which between-year Spearman’s rank correlations of r ≥ 0.59, P < 4.7 × 10(–5) (TT70), identify as an accurate phenotyping method. Following our experience of senescence trait genetic mapping, we recognized the need for singular metrics capable of discriminating senescence variation, identifying thermal time to flag leaf senescence score of 70 (TT70) and mean peduncle senescence (MeanPed) scores as most informative. Moreover, grain maturity assessments confirmed a previous association between our staygreen traits and grain fill extension, illustrating trait functionality. Here we review different senescence phenotyping approaches and share our experiences of phenotyping two independent recombinant inbred line (RIL) populations segregating for staygreen traits. Together, we direct readers toward senescence phenotyping methods we found most effective, encouraging their use when investigating and discriminating senescence variation of differing genetic bases, and aid trait selection and weighting in breeding and research programs alike. |
format | Online Article Text |
id | pubmed-8085557 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80855572021-05-01 Capturing and Selecting Senescence Variation in Wheat Chapman, Elizabeth A. Orford, Simon Lage, Jacob Griffiths, Simon Front Plant Sci Plant Science Senescence is a highly quantitative trait, but in wheat the genetics underpinning senescence regulation remain relatively unknown. To select senescence variation and ultimately identify novel genetic regulators, accurate characterization of senescence phenotypes is essential. When investigating senescence, phenotyping efforts often focus on, or are limited to, the visual assessment of flag leaves. However, senescence is a whole-plant process, involving remobilization and translocation of resources into the developing grain. Furthermore, the temporal progression of senescence poses challenges regarding trait quantification and description, whereupon the different models and approaches applied result in varying definitions of apparently similar metrics. To gain a holistic understanding of senescence, we phenotyped flag leaf and peduncle senescence progression, alongside grain maturation. Reviewing the literature, we identified techniques commonly applied in quantification of senescence variation and developed simple methods to calculate descriptive and discriminatory metrics. To capture senescence dynamism, we developed the idea of calculating thermal time to different flag leaf senescence scores, for which between-year Spearman’s rank correlations of r ≥ 0.59, P < 4.7 × 10(–5) (TT70), identify as an accurate phenotyping method. Following our experience of senescence trait genetic mapping, we recognized the need for singular metrics capable of discriminating senescence variation, identifying thermal time to flag leaf senescence score of 70 (TT70) and mean peduncle senescence (MeanPed) scores as most informative. Moreover, grain maturity assessments confirmed a previous association between our staygreen traits and grain fill extension, illustrating trait functionality. Here we review different senescence phenotyping approaches and share our experiences of phenotyping two independent recombinant inbred line (RIL) populations segregating for staygreen traits. Together, we direct readers toward senescence phenotyping methods we found most effective, encouraging their use when investigating and discriminating senescence variation of differing genetic bases, and aid trait selection and weighting in breeding and research programs alike. Frontiers Media S.A. 2021-04-16 /pmc/articles/PMC8085557/ /pubmed/33936128 http://dx.doi.org/10.3389/fpls.2021.638738 Text en Copyright © 2021 Chapman, Orford, Lage and Griffiths. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Chapman, Elizabeth A. Orford, Simon Lage, Jacob Griffiths, Simon Capturing and Selecting Senescence Variation in Wheat |
title | Capturing and Selecting Senescence Variation in Wheat |
title_full | Capturing and Selecting Senescence Variation in Wheat |
title_fullStr | Capturing and Selecting Senescence Variation in Wheat |
title_full_unstemmed | Capturing and Selecting Senescence Variation in Wheat |
title_short | Capturing and Selecting Senescence Variation in Wheat |
title_sort | capturing and selecting senescence variation in wheat |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8085557/ https://www.ncbi.nlm.nih.gov/pubmed/33936128 http://dx.doi.org/10.3389/fpls.2021.638738 |
work_keys_str_mv | AT chapmanelizabetha capturingandselectingsenescencevariationinwheat AT orfordsimon capturingandselectingsenescencevariationinwheat AT lagejacob capturingandselectingsenescencevariationinwheat AT griffithssimon capturingandselectingsenescencevariationinwheat |