2020
DOI: 10.1101/2020.08.06.240747
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An ancient, conserved gene regulatory network led to the rise of oral venom systems

Abstract: Oral venom systems evolved multiple times in numerous vertebrates enabling exploitation of unique predatory niches. Yet how and when they evolved remains poorly understood. Up to now, most research on venom evolution has focussed strictly on the toxins. However, using toxins present in modern day animals to trace the origin of the venom system is difficult, since they tend to evolve rapidly, show complex patterns of expression, and were incorporated into the venom arsenal relatively recently. Here we focus on … Show more

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Cited by 5 publications
(8 citation statements)
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References 98 publications
(109 reference statements)
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“…Setting up venom production requires novel specialized tissues and glands, in which a set of genes originally not related to the venomous function is recruited and modified to encode potent toxins. Most animal toxins represent rather few broad classes of proteins [54], but being broadly distributed across unrelated venomous animal taxa, they expectedly have been recruited from very different genomic backgrounds [57]. This general trend to convergent evolution provides a unique opportunity to disentangle the interplay of conserved and lineage-specific mechanisms that govern recruitment and evolution of venom peptides.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Setting up venom production requires novel specialized tissues and glands, in which a set of genes originally not related to the venomous function is recruited and modified to encode potent toxins. Most animal toxins represent rather few broad classes of proteins [54], but being broadly distributed across unrelated venomous animal taxa, they expectedly have been recruited from very different genomic backgrounds [57]. This general trend to convergent evolution provides a unique opportunity to disentangle the interplay of conserved and lineage-specific mechanisms that govern recruitment and evolution of venom peptides.…”
Section: Discussionmentioning
confidence: 99%
“…Currently, most efforts to this end focus on the well-characterized taxa of venomous animals, mainly on snakes (e.g. [57,58]), and extending such studies to new system(s) will greatly magnify the power of comparative analysis. Essentially such system can be seeded by a pair of distantly related taxa that have independently acquired venoms.…”
Section: Discussionmentioning
confidence: 99%
“…Setting up venom production requires novel specialized tissues and glands, in which a set of genes originally not related to the venomous function is recruited and modified to encode potent toxins. Most animal toxins represent rather few broad classes of proteins, such as cysteine rich secretory peptides (CRISPs), hyaluronidases, kunitz-phospholipase and serine-type proteases (Zancolli & Casewell 2020), but being broadly distributed across unrelated venomous animal taxa, they have been recruited from very different genomic backgrounds (Barua & Mikheyev 2021). This general trend to convergent evolution provides a unique opportunity to disentangle the interplay of lineage-specific and conserved mechanisms that govern recruitment and evolution of venom peptides.…”
Section: Discussionmentioning
confidence: 99%
“…Currently, most efforts to this end focus on the well characterized taxa of venomous animals, mainly on snakes (e.g. Barua & Mikheyev 2019, 2021), and extending such studies to new system(s) will greatly magnify the power of comparative analysis. Essentially, such system can be seeded by a pair of distantly related taxa that have independently acquired venom function, and cone snails and Vexillum representing unrelated evolutionary successful radiations of venomous neogastropods are thus a perfect system.…”
Section: Discussionmentioning
confidence: 99%
“…To remove these batch effects and identify any existing patterns in expression between tissues and species, we used an empirical Bayes method implemented via the ComBat function in sva R package (72). This approach has been successfully implemented in previous studies (28, 73, 74).…”
Section: Methodsmentioning
confidence: 99%