Perspectives on the history of evo-devo and the contemporary research landscape in the genomics era

Tickle, Cheryll; Urrutia, Araxi O.

doi:10.1098/rstb.2015.0473

Cited by 17 publications

(12 citation statements)

References 74 publications

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“…While there is some signal of early development adaptive evolution on single genes, the later developmental signal is more consistent at the pathway level. Because pathways link genes to phenotypes ( Müller 2007 ; Wray 2007 ; Tickle and Urrutia 2017 ), this suggests stronger phenotypic adaptation in late development and adult.…”

Section: Resultsmentioning

confidence: 99%

Adaptive Evolution of Animal Proteins over Development: Support for the Darwin Selection Opportunity Hypothesis of Evo-Devo

Liu

Robinson‐Rechavi

2018

Molecular Biology and Evolution

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A driving hypothesis of evolutionary developmental biology is that animal morphological diversity is shaped both by adaptation and by developmental constraints. Here, we have tested Darwin’s “selection opportunity” hypothesis, according to which high evolutionary divergence in late development is due to strong positive selection. We contrasted it to a “developmental constraint” hypothesis, according to which late development is under relaxed negative selection. Indeed, the highest divergence between species, both at the morphological and molecular levels, is observed late in embryogenesis and postembryonically. To distinguish between adaptation and relaxation hypotheses, we investigated the evidence of positive selection on protein-coding genes in relation to their expression over development, in fly Drosophila melanogaster, zebrafish Danio rerio, and mouse Mus musculus. First, we found that genes specifically expressed in late development have stronger signals of positive selection. Second, over the full transcriptome, genes with evidence for positive selection trend to be expressed in late development. Finally, genes involved in pathways with cumulative evidence of positive selection have higher expression in late development. Overall, there is a consistent signal that positive selection mainly affects genes and pathways expressed in late embryonic development and in adult. Our results imply that the evolution of embryogenesis is mostly conservative, with most adaptive evolution affecting some stages of postembryonic gene expression, and thus postembryonic phenotypes. This is consistent with the diversity of environmental challenges to which juveniles and adults are exposed.

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Section: Resultsmentioning

confidence: 99%

Adaptive Evolution of Animal Proteins over Development: Support for the Darwin Selection Opportunity Hypothesis of Evo-Devo

Liu

Robinson‐Rechavi

2018

Molecular Biology and Evolution

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“…Because pathways link genes to phenotypes (Müller 2007;Wray 2007;Tickle and Urrutia 2017), this suggests stronger phenotypic adaptation in late development and adult.…”

Section: Polygenic Selection Analysismentioning

confidence: 99%

Adaptive evolution of animal proteins over development: support for the Darwin selection opportunity hypothesis of Evo-Devo

Liu

Robinson‐Rechavi

2017

Preprint

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Animal morphological diversity is shaped both by adaptation and by developmental constraints. Here we have tested Darwin's "selection opportunity" hypothesis, according to which high evolutionary divergence in late development is due to strong positive selection. We contrasted it to a "developmental constraint" hypothesis, according to which late development is under relaxed negative selection. Indeed, the highest divergence, both at the morphological and molecular levels, is observed late there is a consistent signal that positive selection mainly affects genes and pathways expressed in late embryonic development and in adult. Our results imply that the evolution of embryogenesis is mostly conservative, with most adaptive evolution affecting post-embryonic gene expression, and thus post-embryonic phenotypes. This is consistent with the diversity of environmental challenges to which juveniles and adults are exposed.

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“…Choice of relevant explicative variables is crucial for such purposes. Contrasting with general trends of pathogens distributions [ 27 ], the influence of anthropic pressures on the environment and biodiversity may play significant roles at local geographic scales and can modify the complex interactions between hosts, vectors, and disease agents [ 28 – 30 ]. The BAM framework (biotic, abiotic, movement) was proposed [ 31 ] to identify conditions suitable for disease maintenance and dispersal correctly.…”

Section: Introductionmentioning

confidence: 99%

Spatial epidemiology of yellow fever: Identification of determinants of the 2016-2018 epidemics and at-risk areas in Brazil

et al. 2020

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Optimise control strategies of infectious diseases, identify factors that favour the circulation of pathogens, and propose risk maps are crucial challenges for global health. Ecological niche modelling, once relying on an adequate framework and environmental descriptors can be a helpful tool for such purposes. Despite the existence of a vaccine, yellow fever (YF) is still a public health issue. Brazil faced massive sylvatic YF outbreaks from the end of 2016 up to mid-2018, but cases in human and non-human primates have been recorded until the beginning of 2020. Here we used both human and monkey confirmed YF cases from two epidemic periods (2016/2017 and 2017/2018) to describe the spatial distribution of the cases and explore how biotic and abiotic factors drive their occurrence. The distribution of YF cases largely overlaps for humans and monkeys, and a contraction of the spatial extent associated with a southward displacement is observed during the second period of the epidemics. More contributive variables to the spatiotemporal heterogeneity of cases were related to biotic factors (mammal richness), abiotic factors (temperature and precipitation), and some human-related variables (population density, human footprint, and human vaccination coverage). Both projections of the most favourable conditions showed similar trends with a contraction of the more at-risk areas. Once extrapolated at a large scale, the Amazon basin remains at lower risk, although surrounding forest regions and notably the NorthWest region, would face a higher risk. Spatial projections of infectious diseases often relied on climatic variables only; here for both models, we instead highlighted the importance of considering local biotic conditions, hosts vulnerability, social and epidemiological factors to run the spatial risk analysis correctly: all YF cases occurring later on, in 2019 and 2020, were observed in the predicted at-risk areas.

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Perspectives on the history of evo-devo and the contemporary research landscape in the genomics era

Cited by 17 publications

References 74 publications

Adaptive Evolution of Animal Proteins over Development: Support for the Darwin Selection Opportunity Hypothesis of Evo-Devo

Adaptive Evolution of Animal Proteins over Development: Support for the Darwin Selection Opportunity Hypothesis of Evo-Devo

Adaptive evolution of animal proteins over development: support for the Darwin selection opportunity hypothesis of Evo-Devo

Spatial epidemiology of yellow fever: Identification of determinants of the 2016-2018 epidemics and at-risk areas in Brazil

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