De novo transcriptome assembly and annotation of the brain of common pipistrelle bat (Pipistrellus pipistrellus) - Venkata Rama, Kameswara Sharma Yadavill (2018)
Background: Bats are one of the most important, yet least understood, group of animals in the world. Pipistrelles are the most common and most widespread of all British bat species. In contradiction of the metabolic theory of ageing, bats are an anomaly as they have a high metabolic rate but are exceptionally long-lived, they also exhibit unique features such as flight and echolocation. Humans and other mammals share many common features of brain organization, but the differences in theta waves between bats and rats raises questions about how spatial information is represented in all brains. This study aims to sequence and annotate novel genes and transcripts from the bat brain. Method: In the absence of genome or transcriptome information, transcripts first need to be reconstructed from sequence reads (or read pairs), which is referred to as de novo assembly. Further, counting the reads that fall onto a given transcript provides a digital measurement of transcript abundance, which serves as the starting point for biological inference. For each biological replicate brain sample of bat, de novo assembly was conducted using the software trinity (http://trinityrnaseq.github.io/). High quality transcripts were determined using transrate (https://github.com/Blahah/ transrate, http://hibberdlab.com/transrate). Intersect of the quality transcripts were identified from multiple replicates and used for transcriptome abundance estimation using HISAT (http://www.ccb.jhu.edu/software/hisat/index) and Stringtie (http://www.ccb. jhu.edu/ software/stringtie/). Annotation of novel transcripts used the software tool dammit (https://github.com/camillescott/dammit). Identification of genes homologous with reference genomes was determined using Inparanoid (http://inparanoid.cgb.ki.se/). Novel genes specific to bat brain tissue were identified by Inparanoid-BLAST. These genes were determined by expression abundance (Transcript per Million, > 5X the median) and hierarchical clustering. Phylogenetic trees were constructed for genes of interest involved in echolocation. Adaptive evolution of genes of interest were determined by comparison of selection strength (ω=dN/dS). The functional characterization of novel genes were confirmed by Gene Ontology and KEGG pathway analysis. Results: We report the first full brain transcriptome of common pipistrelle and characterized genes associated with echolocation including Prestin (Slc26a5), Gjb2, Foxp2 which provide a remarkable insight into the bat brain transcriptome. We observed high similarity between the transcripts (within replicates) and orthologues genes were found in closely related species (bat, human, mouse and rat). The ratio of nonsynonymous to synonymous substitutions exemplifies that protein sequence of the genes associated with echolocation evolve in response to ‘purifying selection’. Phylogenetic analysis revealed that these genes are most closely related with the little brown bat (Myotis lucifugus). In addition, this study identifies tissue-specific genes and interactions of classical neural process (Long-term potentiation, Long-term depression and gap junction) in this novel organism. Conclusion: We comprehensively characterized the complete bat brain transcriptome of the common pipistrelle (Pipistrellus pipistrellus). This is the first study of its type and identified novel genes which are prominently involved in regulating the important classical neural processes of brain. This in turn gives profound resource for understanding the evolutionary perspective of these genes and also in brain associated diseases. Potential Outcome and Future Study: Whole-genome assembly and functional genome annotation with RNA have become a realistic goal, and allow the identification of isoform- or allele-specific expression, coexpression and alternative splicing. Extending network analysis to several brain regions is potentially of high interest given the complexity of behavioural phenotypes. Understanding and identifying the adaptive selection of brain transcriptome genes in non-model organisms will provide insight into vertebrate brain evolution and potentially, identify genes involved in multifactorial human diseases. In order to extend this work we have isolated a high quality of RNA from the brain of zebrafish (whole brain tissue and three different regions of brain tissue separately in replicates). Samples have been submitted for NGS and analysis will follow protocols developed here.