scholarly journals Capturing and Selecting Senescence Variation in Wheat

2020 ◽  
Author(s):  
Elizabeth A. Chapman ◽  
Simon Orford ◽  
Jacob Lage ◽  
Simon Griffiths

AbstractSenescence 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 characterisation of senescence phenotypes is essential. When investigating senescence, phenotyping efforts often focus on, or are limited to, visual assessment of the flag leaves. However, senescence is a whole plant process, involving remobilisation 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 recognised 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 RIL populations segregating for staygreen traits. Together, we direct readers towards senescence phenotyping methods we found most effective, encouraging their use when investigating and discriminating senescence variation of differing genetic bases, and to aid trait selection and weighting in breeding and research programs alike.

2021 ◽  
Vol 12 ◽  
Author(s):  
Elizabeth A. Chapman ◽  
Simon Orford ◽  
Jacob Lage ◽  
Simon Griffiths

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 &lt; 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.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Peter E. Moi ◽  
Onesmus M. Kitonyo ◽  
George N. Chemining’wa ◽  
Josiah M. Kinama

Leaf senescence regulates grain yield. However, the modulation of leaf senescence in sorghum under legume-based intercrop systems and nitrogen (N) fertilization is not known. The objective of the study was to investigate the effect of intercropping two sorghum (Gadam and Serena) and cowpea (K80, M66) varieties and sole cropping systems and different fertilizer N rates (0, 40, and 80 kg·N·ha−1) on the time course of postflowering sorghum leaf senescence and understand how senescence modulates grain yield. The experiment was laid out in a randomized complete block design with a split-plot arrangement with three replications. Leaf senescence was assessed from flowering to maturity at (a) whole-plant level by the visual scoring of green leaves and (b) flag leaf scale by measuring leaf greenness with a SPAD 502 chlorophyll meter. A logistic function in SigmaPlot was fitted to estimate four traits of leaf senescence, including minimum and maximum SPAD (SPADmin, SPADmax), time to loss of 50% SPADmax (EC50), and the rate of senescence. Irrespective of the cowpea variety, intercropping reduced sorghum grain yield by 50%. The addition of N increased yield by 27% but no effect was detected between 40 and 80 kg·N ha−1. Intercropping delayed leaf senescence at the whole plant by 0.2 leaves plant−1 day−1 but reduced SPADmax of the flag by 8 SPAD units and rate of senescence by 4 SPAD units day−1 compared with sole crop system. Fertilizer N delayed leaf senescence ( P ≤ 0.05 ) at whole-plant and flag leaf scales. Cropping System × nitrogen modulated senescence at whole-plant and flag leaf scales and sorghum grain yield but marginally influenced other traits. While EC50 did not correlate with grain yield, faster rates of senescence and leaf greenness were associated with high yield under the sole crop system. Overall, N was the main factor in driving sorghum leaf senescence while the intercropping effect on senescence was nonfunctional. Effects of competition in sorghum-legume intercropping and source-sink relationships on the patterns of leaf senescence deserve further investigation.


2014 ◽  
Vol 153 (7) ◽  
pp. 1234-1245 ◽  
Author(s):  
S. WANG ◽  
Z. LIANG ◽  
D. SUN ◽  
F. DONG ◽  
W. CHEN ◽  
...  

SUMMARYDelayed senescence, or stay-green, contributes to a longer grain-filling period and has been regarded as a desirable characteristic for the production of a number of crops including wheat. In the present study, in order to identify quantitative trait loci (QTLs) for traits related to the progression of wheat flag leaf senescence, green leaf area duration (GLAD) of a doubled haploid (DH) population, derived from two winter wheat varieties Hanxuan10 and Lumai14, was visually estimated under two water conditions and was recorded at 3-day intervals from 10 days after anthesis to physiological maturity using a 0–9 scale. According to GLAD, parameters related to the progression of senescence of DH lines and their parents were estimated by the Gompertz statistical model. Based on the model parameters, DH lines were categorized into three groups under drought stress and four groups under well-watered conditions. A total of 24 additive QTLs and 23 pairs of epistatic QTLs for parameters related to the progression of senescence were identified on 18 chromosomes, except for 3B, 1D and 6D. Of the QTLs detected, 14 and 10 additive QTLs were associated with the investigated traits under drought stress and well-watered conditions, respectively. Furthermore, 4, 7, 6, 2 and 2 additive QTLs for traits related to progression of senescence were clustered around the same or similar regions of chromosomes 1A, 1B, 5A, 5B and 7A, respectively. The present data provided the genetic basis for high phenotypic correlations among traits related to the progression of wheat flag leaf senescence. In addition, 17 loci were co-located or linked with previously reported QTLs regulating chlorophyll fluorescence, high-light-induced photo-oxidation, or heat stress and dark-induced senescence. The marker Xwmc336 on chromosome 1A, responsible for the onset and end times of leaf senescence, the time to maximum rate of senescence, the time to reach 75% senescence and chlorophyll content under drought stress may be helpful for marker-assisted selection breeding of wheat.


Euphytica ◽  
2004 ◽  
Vol 135 (3) ◽  
pp. 255-263 ◽  
Author(s):  
V. Verma ◽  
M.J. Foulkes ◽  
A.J. Worland ◽  
R. Sylvester-Bradley ◽  
P.D.S. Caligari ◽  
...  

2013 ◽  
Vol 39 (6) ◽  
pp. 1096 ◽  
Author(s):  
Dong-Qing YANG ◽  
Zhen-Lin WANG ◽  
Yan-Ping YIN ◽  
Ying-Li NI ◽  
Wei-Bing YANG ◽  
...  

Author(s):  
Xiaoping Huang ◽  
Hongyu Zhang ◽  
Qiang Wang ◽  
Rong Guo ◽  
Lingxia Wei ◽  
...  

Abstract Key message This study showed the systematic identification of long non-coding RNAs (lncRNAs) involving in flag leaf senescence of rice, providing the possible lncRNA-mRNA regulatory relationships and lncRNA-miRNA-mRNA ceRNA networks during leaf senescence. Abstract LncRNAs have been reported to play crucial roles in diverse biological processes. However, no systematic identification of lncRNAs associated with leaf senescence in plants has been studied. In this study, a genome-wide high throughput sequencing analysis was performed using rice flag leaves developing from normal to senescence. A total of 3953 lncRNAs and 38757 mRNAs were identified, of which 343 lncRNAs and 9412 mRNAs were differentially expressed. Through weighted gene co-expression network analysis (WGCNA), 22 continuously down-expressed lncRNAs targeting 812 co-expressed mRNAs and 48 continuously up-expressed lncRNAs targeting 1209 co-expressed mRNAs were considered to be significantly associated with flag leaf senescence. Gene Ontology results suggested that the senescence-associated lncRNAs targeted mRNAs involving in many biological processes, including transcription, hormone response, oxidation–reduction process and substance metabolism. Additionally, 43 senescence-associated lncRNAs were predicted to target 111 co-expressed transcription factors. Interestingly, 8 down-expressed lncRNAs and 29 up-expressed lncRNAs were found to separately target 12 and 20 well-studied senescence-associated genes (SAGs). Furthermore, analysis on the competing endogenous RNA (CeRNA) network revealed that 6 down-expressed lncRNAs possibly regulated 51 co-expressed mRNAs through 15 miRNAs, and 14 up-expressed lncRNAs possibly regulated 117 co-expressed mRNAs through 21 miRNAs. Importantly, by expression validation, a conserved miR164-NAC regulatory pathway was found to be possibly involved in leaf senescence, where lncRNA MSTRG.62092.1 may serve as a ceRNA binding with miR164a and miR164e to regulate three transcription factors. And two key lncRNAs MSTRG.31014.21 and MSTRG.31014.36 also could regulate the abscisic-acid biosynthetic gene BGIOSGA025169 (OsNCED4) and BGIOSGA016313 (NAC family) through osa-miR5809. The possible regulation networks of lncRNAs involving in leaf senescence were discussed, and several candidate lncRNAs were recommended for prior transgenic analysis. These findings will extend the understanding on the regulatory roles of lncRNAs in leaf senescence, and lay a foundation for functional research on candidate lncRNAs.


2003 ◽  
Vol 53 (3) ◽  
pp. 255-262 ◽  
Author(s):  
Sohei Kobayashi ◽  
Yoshimichi Fukuta ◽  
Satoshi Morita ◽  
Tadashi Sato ◽  
Mitsuru Osaki ◽  
...  

2010 ◽  
Vol 130 (3) ◽  
pp. 372-382 ◽  
Author(s):  
Arwa Shahin ◽  
Paul Arens ◽  
Adriaan W. Van Heusden ◽  
Gerard Van Der Linden ◽  
Martijn Van Kaauwen ◽  
...  

1986 ◽  
Vol 66 (3) ◽  
pp. 503-508 ◽  
Author(s):  
I. Ma. Martin del Molino ◽  
M. Ulloa ◽  
R. Martinez-Carrasco ◽  
P. Perez

2018 ◽  
Vol 79 (1) ◽  
pp. 26-34 ◽  
Author(s):  
Hélène Hauduc ◽  
Tanush Wadhawan ◽  
Bruce Johnson ◽  
Charles Bott ◽  
Matthew Ward ◽  
...  

Abstract Sulfur causes many adverse effects in wastewater treatment and sewer collection systems, such as corrosion, odours, increased oxygen demand, and precipitate formation. Several of these are often controlled by chemical addition, which will impact the subsequent wastewater treatment processes. Furthermore, the iron reactions, resulting from coagulant addition for chemical P removal, interact with the sulfur cycle, particularly in the digester with precipitate formation and phosphorus release. Despite its importance, there is no integrated sulfur and iron model for whole plant process optimization/design that could be readily used in practice. After a detailed literature review of chemical and biokinetic sulfur and iron reactions, a plant-wide model is upgraded with relevant reactions to predict the sulfur cycle and iron cycle in sewer collection systems, wastewater and sludge treatment. The developed model is applied on different case studies.


Sign in / Sign up

Export Citation Format

Share Document