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Correction for Barua and Mikheyev, an Ancient, Conserved Gene Regulatory Network Led to the Rise of Oral Venom Systems Correction EVOLUTION Correction for “An ancient, conserved gene regulatory network led to the rise of oral venom systems,” by Agneesh Barua and Alexander S. Mikheyev, which was first published March 29, 2021; 10.1073/pnas.2021311118 (Proc. Natl. Acad. Sci. U.S.A. 118, e2021311118). The editors note that, due to a printer’s error, the article in- advertently published with a number of language errors. The article has been updated online to correct these errors. Published under the PNAS license. Published May 24, 2021. www.pnas.org/cgi/doi/10.1073/pnas.2108106118 CORRECTION PNAS 2021 Vol. 118 No. 22 e2108106118 https://doi.org/10.1073/pnas.2108106118 | 1of1 Downloaded by guest on October 1, 2021 An ancient, conserved gene regulatory network led to the rise of oral venom systems Agneesh Baruaa,1 and Alexander S. Mikheyeva,b aEcology and Evolution Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, 904-0495, Japan; and bEvolutionary Genomics Group, Australian National University, Canberra, ACT 0200, Australia Edited by Günter P. Wagner, Yale University, New Haven, CT, and approved February 11, 2021 (received for review October 27, 2020) Oral venom systems evolved multiple times in numerous verte- over time; this diminishes their utility in trying to understand brates, enabling the exploitation of unique predatory niches. Yet events that lead to the rise of venom systems in the nonvenom- how and when they evolved remains poorly understood. Up to ous ancestors of snakes (14, 15). now, most research on venom evolution has focused strictly on A gene coexpression network aims to identify genes that in- toxins. However, using toxins present in modern-day animals to teract with one another based on common expression profiles trace the origin of the venom system is difficult, since they tend to (16). Groups of coexpressed genes that have similar expression evolve rapidly, show complex patterns of expression, and were patterns across samples are identified using hierarchical clustering incorporated into the venom arsenal relatively recently. Here we and are placed in gene “modules” (17). Constructing a network focus on gene regulatory networks associated with the production and comparing expression profiles of modules across taxa can of toxins in snakes, rather than the toxins themselves. We found identify key drivers of phenotypic change and aid in identifying that overall venom gland gene expression was surprisingly well initial genetic targets of natural selection (18, 19). Comparative conserved when compared to salivary glands of other amniotes. analysis using gene coexpression networks allows us to distinguish We characterized the “metavenom network,” a network of ∼3,000 between ancient genetic modules representing core cellular nonsecreted housekeeping genes that are strongly coexpressed processes, evolving modules that give rise to lineage-specific with toxins and are primarily involved in protein folding and mod- differences, and highly flexible modules that have evolved differ- ification. Conserved across amniotes, this network was coopted ently in different taxa (20). Gene coexpression networks are also for venom evolution by exaptation of existing members and the widely used to construct gene regulatory networks (GRNs), owing EVOLUTION recruitment of new toxin genes. For instance, starting from this to their reliability in capturing biologically relevant interactions Heloderma common molecular foundation, lizards, shrews, and between genes as well as their high power in reproducing known solenodon evolved venoms in parallel by overexpression of kalli- protein–protein interactions (21, 22). kreins, which were common in ancestral saliva and induce vasodi- Here we focus on gene coexpression networks involved in the lation when injected, causing circulatory shock. Derived venoms, production of snake venom, rather than the venom toxins them- such as those of snakes, incorporated novel toxins, though they selves. We used a coexpression network to characterize the genes still rely on hypotension for prey immobilization. These similarities associated with venom production, which we term the “meta- suggest repeated cooption of shared molecular machinery for the venom network,” and determined its biological role. We traced evolution of oral venom in mammals and reptiles, blurring the line the origin of this network to the common ancestor of amniotes, between truly venomous animals and their ancestors. which suggests that the venom system originated from a venom | evolution | gene regulatory networks | transcriptomics | complex traits Significance enoms are proteinaceous mixtures that can be traced and Although oral venom systems are ecologically important Vquantified to distinct genomic loci, providing a level of ge- characters, how they originated is still unclear. In this study, we netic tractability that is rare in other traits (1–4). This advantage show that oral venom systems likely originated from a gene regulatory network conserved across amniotes. This network, of venom systems provides insights into processes of molecular “ ” evolution that are otherwise difficult to obtain. For example, which we term the metavenom network, comprises over studies in cnidarians showed that gene duplication is an effective 3,000 housekeeping genes coexpressed with venom and plays a role in protein folding and modification. Comparative tran- way to increase protein dosage in tissues where different eco- scriptomics revealed that the network is conserved between logical roles can give rise to different patterns of gene expression venom glands of snakes and salivary glands of mammals. This (2, 5). Studies of venom in snakes have allowed comparisons of suggests that while these tissues have evolved different the relative importance of sequence evolution vs. gene expres- functions, they share a common regulatory core that persisted sion evolution as well as how a lack of genetic constraint enables from their common ancestor. We propose several evolutionary diversity in complex traits (6, 7). mechanisms that can utilize this common regulatory core to Despite the wealth of knowledge venoms have provided about give rise to venomous animals from their nonvenomous general evolutionary processes, the common molecular basis for ancestors. the evolution of venom systems themselves is unknown. Even in snakes, which have perhaps the best studied venom systems, very Author contributions: A.B. and A.S.M. designed research, performed research, analyzed little is known about the molecular architecture of these systems data, and wrote the paper. at their origin (8, 9). Using toxin families present in modern snakes The authors declare no competing interest. to understand evolution at its origin is difficult because toxins evolve This article is a PNAS Direct Submission. rapidly, in terms of both sequence and gene expression (10, 11). This open access article is distributed under Creative Commons Attribution-NonCommercial- Toxins experience varying degrees of selection and drift, compli- NoDerivatives License 4.0 (CC BY-NC-ND). cating interpretations of evolutionary models (12); estimation of 1To whom correspondence may be addressed. Email: [email protected]. gene family evolution is often inconsistent, varying with which part This article contains supporting information online at https://www.pnas.org/lookup/suppl/ of the gene (exon or intron) is used to construct the phylogeny (13). doi:10.1073/pnas.2021311118/-/DCSupplemental. Most importantly, present-day toxins became a part of venom Published March 29, 2021. PNAS 2021 Vol. 118 No. 14 e2021311118 https://doi.org/10.1073/pnas.2021311118 | 1of10 conserved gene regulatory network. The conserved nature of the 107287553) were the exceptions, which had links with only a few metavenom network across amniotes suggests that oral venom toxin genes and nonvenom genes (namely DLG1, CANX, systems started with a common gene regulatory foundation and HSP90, RPLP0, PDIA4, and LOC8828). underwent lineage-specific changes to give rise to diverse venom Several network characteristics can be used to identify genes systems in snakes, lizards, and even mammals. integral to a network. One of these characteristics is module membership (MM), which represents the connectivity of a gene Results with other genes within a module and is used to define central- The Metavenom Network Is Involved in Toxin Expression in Snakes. ized hub genes (23). MM has values between 0 and 1, where Previously published RNA libraries from Taiwan habu (Proto- values closer to 1 represent high connectivity within a module bothrops mucrosquamatus) were used to construct the network and values closer to 0 represent low connectivity. We estimated (12). Weighted gene coexpression network analysis (WGCNA) the MM of genes in the metavenom network and identified sets was used to construct the coexpression network (23). WGCNA of differentially expressed genes (DEGs) (Dataset S3B). An estimates correlations between genes across samples (libraries) ANOVA-like test for gene expression in the venom gland, heart, and clusters genes with similar profiles into modules (23). This liver, and kidney of habu revealed that out of 3,380 genes that clustering is based solely on similarities in expression levels and make up the metavenom network, 1,295 were significantly dif- does not imply any association based on the ecological roles of ferentially expressed (P < 0.05) (Dataset S3B). To identify genes genes (or toxins). most specific to the venom
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