Braun, B. A. | bioRxiv Science

bioRxiv2020

D-graph clusters flaviviruses and β-coronaviruses according to their hosts, disease type and human cell receptors

MotivationThere is a need for rapid and easy to use, alignment free methods to cluster large groups of protein sequence data. Commonly used phylogenetic trees based on alignments can be used to visualize only a limited number of protein sequences. DGraph, introduced here, is a dynamic programming application developed to generate 2D-maps based on similarity scores for sequences. The program automatically calculates and graphically displays property distance (PD) scores based on physico-chemical property (PCP) similarities from an unaligned list of FASTA files. Such "PD-graphs" show the interrelatedness of the sequences, whereby clusters can reveal deeper connectivities. ResultsPD-Graphs generated for flavivirus (FV), enterovirus (EV), and coronavirus (CoV) sequences from complete polyproteins or individual proteins are consistent with biological data on vector types, hosts, cellular receptors and disease phenotypes. PD-graphs separate the tick- from the mosquito-borne FV, clusters viruses that infect bats, camels, seabirds and humans separately and the clusters correlate with disease phenotype. The PD method segregates the {beta}-CoV spike proteins of SARS, SARS-CoV-2, and MERS sequences from other human pathogenic CoV, with clustering consistent with cellular receptor usage. The graphs also suggest evolutionary relationships that may be difficult to determine with conventional bootstrapping methods that require postulating an ancestral sequence. Availability and implementationDGraph is written in Java, compatible with the Java 5 runtime or newer. Source code and executable is available from the GitHub website (https://github.com/bjmnbraun/DGraph/releases). Documentation for installation and use of the software is available from the Readme.md file at (https://github.com/bjmnbraun/DGraph). Contactbjmnbraun@gmail.com or webraun@utmb.edu Supplementary informationSupplementary information Table S1 and Fig. S1 are online available.

bioinformatics↗

bioRxiv2017

A novel unbiased test for molecular convergent evolution and discoveries in echolocating, aquatic and high-altitude mammals

Distantly related species entering similar biological niches often adapt by evolving similar morphological and physiological characters. The extent to which genomic molecular convergence, and the extent to which coding mutations underlie this convergent phenotypic evolution remain unknown. Using a novel test, we ask which group of functionally coherent genes is most affected by convergent amino acid substitutions between phenotypically convergent lineages. This most affected sets reveals 75 novel coding convergences in important genes that pattern a highly adapted organ: the cochlea, skin and lung in echolocating, aquatic and high-altitude mammals, respectively. Our test explicitly requires the enriched converged term to not be simultaneously enriched for divergent mutations, and correctly dismisses relaxation-based signals, such as those produced by vision genes in subterranean mammals. This novel test can be readily applied to birds, fish, flies, worms etc., to discover more of the fascinating contribution of protein coding convergence to phenotype convergence.

evolutionary biology↗