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...

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Main Authors: Elizabeth A. Chapman, Simon Orford, Jacob Lage, Simon Griffiths
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-04-01
Series:Frontiers in Plant Science
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2021.638738/full
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spelling doaj-17f9aa0cc19445ff816682eef06044b52021-04-16T05:43:29ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2021-04-011210.3389/fpls.2021.638738638738Capturing and Selecting Senescence Variation in WheatElizabeth A. Chapman0Simon Orford1Jacob Lage2Simon Griffiths3Department of Crop Genetics, John Innes Centre, Norwich Research Park, Norwich, United KingdomDepartment of Crop Genetics, John Innes Centre, Norwich Research Park, Norwich, United KingdomKWS UK Ltd., Thriplow, United KingdomDepartment of Crop Genetics, John Innes Centre, Norwich Research Park, Norwich, United KingdomSenescence 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.https://www.frontiersin.org/articles/10.3389/fpls.2021.638738/fullsenescencephenotypingselectionstaygreengrain developmentpeduncle
collection DOAJ
language English
format Article
sources DOAJ
author Elizabeth A. Chapman
Simon Orford
Jacob Lage
Simon Griffiths
spellingShingle Elizabeth A. Chapman
Simon Orford
Jacob Lage
Simon Griffiths
Capturing and Selecting Senescence Variation in Wheat
Frontiers in Plant Science
senescence
phenotyping
selection
staygreen
grain development
peduncle
author_facet Elizabeth A. Chapman
Simon Orford
Jacob Lage
Simon Griffiths
author_sort Elizabeth A. Chapman
title Capturing and Selecting Senescence Variation in Wheat
title_short 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_sort capturing and selecting senescence variation in wheat
publisher Frontiers Media S.A.
series Frontiers in Plant Science
issn 1664-462X
publishDate 2021-04-01
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.
topic senescence
phenotyping
selection
staygreen
grain development
peduncle
url https://www.frontiersin.org/articles/10.3389/fpls.2021.638738/full
work_keys_str_mv AT elizabethachapman capturingandselectingsenescencevariationinwheat
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AT jacoblage capturingandselectingsenescencevariationinwheat
AT simongriffiths capturingandselectingsenescencevariationinwheat
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