Development in the Wild: Phenotypic Plasticity

Donohue, Kathleen

doi:10.1002/9781118305881.ch10

Cited by 11 publications

(7 citation statements)

References 128 publications

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“…For example, juvenile Bromeliaceae plants have narrow leaves to conserve water, whereas adults have larger flat leaves that support an increased transpiration (Benzing, 2000). Unlike studies on phenotypic plasticity, which is a mechanism by which plants develop adaptive traits (Donohue, 2013), investigations of heterophylly allow us to better understand both leaf development and phase change regulation (Jones, 1999;Nakayama et al, 2012). To date, such studies have contributed greatly to elucidating the mechanisms involved in the ecology, evolution, and development of leaf functions.…”

Section: Introductionmentioning

confidence: 99%

Heterophylly Quantitative Trait Loci Respond to Salt Stress in the Desert Tree Populus euphratica

et al. 2021

Front. Plant Sci.

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Heterophylly, or leaf morphological changes along plant shoot axes, is an important indicator of plant eco-adaptation to heterogeneous microenvironments. Despite extensive studies on the genetic control of leaf shape, the genetic architecture of heterophylly remains elusive. To identify genes related to heterophylly and their associations with plant saline tolerance, we conducted a leaf shape mapping experiment using leaves from a natural population of Populus euphratica. We included 106 genotypes grown under salt stress and salt-free (control) conditions using clonal seedling replicates. We developed a shape tracking method to monitor and analyze the leaf shape using principal component (PC) analysis. PC1 explained 42.18% of the shape variation, indicating that shape variation is mainly determined by the leaf length. Using leaf length along shoot axes as a dynamic trait, we implemented a functional mapping-assisted genome-wide association study (GWAS) for heterophylly. We identified 171 and 134 significant quantitative trait loci (QTLs) in control and stressed plants, respectively, which were annotated as candidate genes for stress resistance, auxin, shape, and disease resistance. Functions of the stress resistance genes ABSCISIC ACIS-INSENSITIVE 5-like (ABI5), WRKY72, and MAPK3 were found to be related to many tolerance responses. The detection of AUXIN RESPONSE FACTOR17-LIKE (ARF17) suggests a balance between auxin-regulated leaf growth and stress resistance within the genome, which led to the development of heterophylly via evolution. Differentially expressed genes between control and stressed plants included several factors with similar functions affecting stress-mediated heterophylly, such as the stress-related genes ABC transporter C family member 2 (ABCC2) and ABC transporter F family member (ABCF), and the stomata-regulating and reactive oxygen species (ROS) signaling gene RESPIRATORY BURST OXIDASE HOMOLOG (RBOH). A comparison of the genetic architecture of control and salt-stressed plants revealed a potential link between heterophylly and saline tolerance in P. euphratica, which will provide new avenues for research on saline resistance-related genetic mechanisms.

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Section: Introductionmentioning

confidence: 99%

Heterophylly Quantitative Trait Loci Respond to Salt Stress in the Desert Tree Populus euphratica

et al. 2021

Front. Plant Sci.

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“…Plants are sessile, and thus in order to survive and reproduce under varying levels of moisture, temperature, light, and pathogens, they often modify metabolic, morphological, defensive, and phenological traits ( Sultan 2000 ; Des Marais et al. 2013 ; Donohue 2013 ). The differential performance responses of a genotype across environmental gradients is depicted as phenotypic plasticity, as a joint result of overall environmental effect and the sensitivity of gene effects across environments ( Bradshaw 1965 ; Des Marais et al.…”

Section: Introductionmentioning

confidence: 99%

Phenotypic Plasticity Contributes to Maize Adaptation and Heterosis

Liu

Warburton

et al. 2020

Molecular Biology and Evolution

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Plant phenotypic plasticity describes altered phenotypic performance of an individual when grown in different environments. Exploring genetic architecture underlying plant plasticity variation may help mitigate the detrimental effects of a rapidly changing climate on agriculture, but little research has been done in this area to date. In the present study, we established a population of 976 maize F1 hybrids by crossing 488 diverse inbred lines with two elite testers. Genome-wide association study (GWAS) identified hundreds of quantitative trait loci (QTLs) associated with phenotypic plasticity variation across diverse F1 hybrids, the majority of which contributed very little variance, in accordance with the polygenic nature of these traits. We identified several QTL regions that may have been selected during the tropical-temperate adaptation process. We also observed heterosis in terms of phenotypic plasticity, in addition to the traditional genetic value differences measured between hybrid and inbred lines, and the pattern of which was affected by genetic background. Our results demonstrate a landscape of phenotypic plasticity in maize, which will aid in the understanding of its genetic architecture, its contribution to adaptation and heterosis, and how it may be exploited for future maize breeding in a rapidly changing environment.

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“…The fraction of vegetation (VF) is a key trait that drives the partitioning of radiation between the background and the vegetation. It is used in several studies as a proxy of crop state [1] and yield [2, 3]. The complement to unity of VF is the gap fraction that is used to estimate the plant area index.…”

Section: Introductionmentioning

confidence: 99%

SegVeg: Segmenting RGB images into green and senescent vegetation by combining deep and shallow methods

Serouart

Madec

David

et al. 2022

Preprint

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The pixels segmentation of high resolution RGB images into background, green vegetation and senescent vegetation classes is a first step often required before estimating key traits of interest including the vegetation fraction, the green area index, or to characterize the sanitary state of the crop. We developed the SegVeg model for semantic segmentation of RGB images into the three classes of interest. It is based on a U-net model that separates the vegetation from the background. It was trained over a very large and diverse dataset. The vegetation pixels are then classified using a SVM shallow machine learning technique trained over pixels extracted from grids applied to images. Results show that the SegVeg model allows to segment accurately the three classes, with however some confusion mainly between the background and the senescent vegetation, particularly over the dark and bright parts of the images. The use of the components of several color spaces allows to better classify the vegetation pixels into green and senescent ones. Finally, the model is used to predict the fraction of the three classes over the grids pixels or the whole images. Results show that the green fraction is very well estimated (R_squared=0.94), while the senescent and background fractions show slightly degraded performances (R_squared=0.70 and 0.73, respectively). We made SegVeg publicly available as a ready-to-use script, as well as the entire dataset, rendering segmentation accessible to a broad audience by requiring neither manual annotation nor knowledge, or at least, a pre-trained model to more specific use.

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Development in the Wild: Phenotypic Plasticity

Cited by 11 publications

References 128 publications

Heterophylly Quantitative Trait Loci Respond to Salt Stress in the Desert Tree Populus euphratica

Heterophylly Quantitative Trait Loci Respond to Salt Stress in the Desert Tree Populus euphratica

Phenotypic Plasticity Contributes to Maize Adaptation and Heterosis

SegVeg: Segmenting RGB images into green and senescent vegetation by combining deep and shallow methods

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