High-resolution and Deep Phylogenetic Reconstruction of Ancestral States from Large Transcriptomic Data Sets.

Phylogenetics is an important area of evolutionary biology that helps to understand the origin and divergence of genes, genomes and species. Building meaningful phylogenetic trees is needed for the accurate reconstruction of the past. To achieve a correct phylogenetic understanding of genes or proteins, reliable and robust methods are needed to construct meaningful trees. With the rapidly increasing availability of genome and transcriptome sequencing data, there is a need for efficient and accurate methodologies for ancestral state reconstruction. Currently available methods are mostly specific for certain gene families, and require substantial adaptation for their application to other gene families. Hence, a generalized framework is essential to utilize large transcriptome resources such as OneKP and MMETSP. Here, we have developed a flexible yet efficient method, based on core strengths such as emphasis on being inclusive in homolog selection, and defining orthologs based on multi-layered inferences. We illustrate how specific steps can be modified to fit the needs of any protein family under consideration. We also demonstrate the success of this protocol by studying and testing the orthologs in various gene families. Taken together, we present a protocol for reconstructing the ancestral states of various domains and proteins across multiple kingdoms of eukaryotes, using thousands of transcriptomes.