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Mol Biol Evol ; 32(3): 754-66, 2015 Mar.
Article in English | MEDLINE | ID: mdl-25502939

ABSTRACT

Attempts to reconstruct the evolutionary history of snake toxins in the context of their co-option to the venom gland rarely account for nonvenom snake genes that are paralogous to toxins, and which therefore represent important connectors to ancestral genes. In order to reevaluate this process, we conducted a comparative transcriptomic survey on body tissues from a venomous snake. A nonredundant set of 33,000 unigenes (assembled transcripts of reference genes) was independently assembled from six organs of the medically important viperid snake Bothrops jararaca, providing a reference list of 82 full-length toxins from the venom gland and specific products from other tissues, such as pancreatic digestive enzymes. Unigenes were then screened for nontoxin transcripts paralogous to toxins revealing 1) low level coexpression of approximately 20% of toxin genes (e.g., bradykinin-potentiating peptide, C-type lectin, snake venom metalloproteinase, snake venom nerve growth factor) in body tissues, 2) the identity of the closest paralogs to toxin genes in eight classes of toxins, 3) the location and level of paralog expression, indicating that, in general, co-expression occurs in a higher number of tissues and at lower levels than observed for toxin genes, and 4) strong evidence of a toxin gene reverting back to selective expression in a body tissue. In addition, our differential gene expression analyses identify specific cellular processes that make the venom gland a highly specialized secretory tissue. Our results demonstrate that the evolution and production of venom in snakes is a complex process that can only be understood in the context of comparative data from other snake tissues, including the identification of genes paralogous to venom toxins.


Subject(s)
Bothrops/genetics , Crotalid Venoms/genetics , Organ Specificity/genetics , Transcriptome/genetics , Animals , Bothrops/metabolism , Crotalid Venoms/metabolism , Evolution, Molecular , Gene Expression Profiling
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