Molecular Biology and Evolution · 2014 · 112 citations · 56 references
Life SciencesBiologyEvolutionary BiologyGene ExpressionGenomicsTranscriptomicsAnimal GenomicsDevelopmental TranscriptomicsPhylogenetic AnalysisTranscriptomic AnalysisVenom BiologyVertebrate EvolutionGene Expression ConservationReptile Venom BiologyVenom EvolutionVenom Gene ExpressionVenom Gland BiologyVenom Gland TranscriptomicsVenom PhylogenyVenom Transcriptomics
Snake venom gene evolution has been studied intensively over the past several decades, yet most previous studies have lacked the context of complete snake genomes and the full context of gene expression across diverse snake tissues. We took a novel approach to studying snake venom evolution by leveraging the complete genome of the Burmese python, including information from tissue-specific patterns of gene expression. We identified the orthologs of snake venom genes in the python genome, and conducted detailed analysis of gene expression of these venom homologs to identify patterns that differ between snake venom gene families and all other genes. We found that venom gene homologs in the python are expressed in many different tissues outside of oral glands, which illustrates the pitfalls of using transcriptomic data alone to define "venom toxins." We hypothesize that the python may represent an ancestral state prior to major venom development, which is supported by our finding that the expansion of venom gene families is largely restricted to highly venomous caenophidian snakes. Therefore, the python provides insight into biases in which genes were recruited for snake venom systems. Python venom homologs are generally expressed at lower levels, have higher variance among tissues, and are expressed in fewer organs compared with all other python genes. We propose a model for the evolution of snake venoms in which venom genes are recruited preferentially from genes with particular expression profile characteristics, which facilitate a nearly neutral transition toward specialized venom system expression.
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MUSCLE: multiple sequence alignment with high accuracy and high throughput
R. C. Edgar · Nucleic Acids Research · 2004 · 46.5K citations · Full text
Paul Flicek, M Ridwan Amode, Daniel Barrell et al. · Nucleic Acids Research · 2013 · 1.3K citations · Full text