Reptilian Transcriptomes v2: an extensive resource for Sauropsida genomics and transcriptomics

Despite the remarkable diversity that characterizes the Class Reptilia, in terms of physiology, morphology, ecology or sex-determination, it remains largely under-represented in comparative genomic/transcriptomic studies and major sequence databases. On the other hand, the development of deep-sequencing technologies led to the accumulation of an increasing number of transcriptomic datasets that were analyzed heterogeneously. Aiming to provide a comparative framework that will enhance our understanding of Reptilian evolution, we built the version 2 of the Reptilian Transcriptomes Database. We annotated both available and our newly-sequenced transcriptomic and genomic data from representatives of each of the four extant reptilian orders: (i) six Squamata, including three snakes (Thamnophis elegans, Python molurus bivittatus and Pantherophis guttatus) and three lizards (Chamaeleo chameleon, Chalcides ocellatus and Eublepharis macularis); (ii) the single living Rhynchocephalia (Sphenodon punctatus); (iii) three Crocodilia (Gavialis gangeticus, Crocodylus porosus and Alligator mississippiensis); and (iv) one Testudines (Chrysemys picta). To that end, we improved our annotation pipeline (LANE runner v2) based on iterative BLAST+ searches and Reciprocal Best Hit (RBH) identification. This approach allowed us to annotate 50 to 70% of the sequences per species (a higher percentage than in previous studies and, in the case of the reannotated transcriptomes, higher than in the original publications) and to compare the transcriptomes to each other. We also built phylogenomic trees using large protein alignments (above 500,000 amino acids) that provide support to the position of turtles and the tuatara as sister groups of Archosauria and Squamata, respectively. The Reptilian Transcriptome Database v2 is a new annotation resource that can serve as a reference for differential expression analyses, as well as linkage mapping, comparative genomics and phylogenomics. We made LANE runner v2 versatile for the annotation of any transcriptome dataset