Biology subjects

Swain, M. T.

Publications and source records attributed to Swain, M. T..

3 recordsLinked to original sources

bioRxiv2022

Sequence features do not drive karyotypic evolution: what are the missing correlates of genome evolution?

Genome rearrangements are prevalent across the tree of life and even within species. After two decades of research, various suggestions have been proposed to explain which features of the genome are associated with rearrangements and the breakpoints between rearranged regions. These include: recombination rate, GC content, repetitive DNA content, gene density, and markers of chromatin conformation. Here, we use a set of six aligned rodent genomes to identify regions that have not been rearranged and characterize the breakpoint regions where rearrangements have occurred. We found no strong support for any of the expected correlations between breakpoint regions and a variety of genomic features previously identified. These results call into question the utility and repeatability of identifying chromatin characteristics associated with rearranged regions of the genome and suggest that perhaps a different explanation is in order. We analyzed rates of karyotypic evolution in each of the six lineages and found that the Mongolian gerbil genome has had the most rearrangements. That gerbils exhibit very rapid sequence evolution at a number of key DNA repair genes suggests an alternative hypothesis for patterns of genome rearrangement: karyotypic evolution may be driven by variation at a few genes that control the repair pathway used to fix double-stranded DNA breaks. Such variation may explain the heterogeneity in the rates of karyotypic evolution across species. While currently only supported by circumstantial evidence, a systematic survey of this hypothesis is now warranted.

genomics↗

bioRxiv2021

Identification of the Park Grass Experiment soil metaproteome

The Park Grass Experiment, is an international reference soil with an impressive repository of temperate grassland (meta)data, however, it still lacks documentation of its soil metaproteome. The identification of these proteins is crucial to our understanding of soil ecology and their role in major biogeochemical processes. However, protein extraction can be fraught with technical difficulties including co-extraction of humic material and lack of a compatible databases to identify proteins. To address these issues, we used two compatible soil protein extraction techniques on Park Grass soil, one that removed humic material, namely a modified freeze-dry, heat/thaw/phenol/chloroform (HTPC) method and another which co-extracted humic material, namely an established surfactant method. Proteins were identified by matching mass spectra against a tailored Park Grass metagenome database. We identified a broad range of proteins from Park Grass soil, mainly in "protein metabolism", "membrane transport", "carbohydrate metabolism", "respiration" and "ribosome associated" categories, enabling reconstitution of specific processes active in grassland soil. The soil microbiome was dominated by Proteobacteria, Actinobacteria, Acidobacteria and Firmicutes at phyla level and Bradyrhizobium, Rhizobium, Acidobacteria, Streptomyces and Pseudolabrys at genus level. Further functional enrichment analysis enabled us to identify many proteins in regulatory and signalling networks of key biogeochemical cycles such as the nitrogen cycle. The combined extraction methods connected previous Park Grass metadata with the metaproteome, biogeochemistry and soil ecology. This could provide a base on which future targeted studies of important soil processes and their regulation can be built. HighlightsO_LIParallel protein extraction methods identified 1266 proteins from Park Grass soil C_LIO_LIProteome was enriched in ribosomal and respiration proteins for the surfactant extraction method and nitrogen associated proteins for the modified phenol/chloroform method C_LIO_LIIdentification of regulatory and signalling proteins in key biogeochemical cycles C_LIO_LILinks metaproteome to microbiome, biogeochemical cycles and Park Grass metadata C_LIO_LIProvides baseline for future targeted studies C_LI

biochemistry↗

bioRxiv2019

The Glossina Genome Cluster: Comparative Genomic Analysis of the Vectors of African Trypanosomes

BackgroundTsetse flies (Glossina sp.) are the sole vectors of human and animal trypanosomiasis throughout sub-Saharan Africa. Tsetse are distinguished from other Diptera by unique adaptations, including lactation and the birthing of live young (obligate viviparity), a vertebrate blood specific diet by both sexes and obligate bacterial symbiosis. This work describes comparative analysis of six Glossina genomes representing three sub-genera: Morsitans (G. morsitans morsitans (G.m. morsitans), G. pallidipes, G. austeni), Palpalis (G. palpalis, G. fuscipes) and Fusca (G. brevipalpis) which represent different habitats, host preferences and vectorial capacity. ResultsGenomic analyses validate established evolutionary relationships and sub-genera. Syntenic analysis of Glossina relative to Drosophila melanogaster shows reduced structural conservation across the sex-linked X chromosome. Sex linked scaffolds show increased rates of female specific gene expression and lower evolutionary rates relative to autosome associated genes. Tsetse specific genes are enriched in protease, odorant binding and helicase activities. Lactation associated genes are conserved across all Glossina species while male seminal proteins are rapidly evolving. Olfactory and gustatory genes are reduced across the genus relative to other characterized insects. Vision associated Rhodopsin genes show conservation of motion detection/tracking functions and significant variance in the Rhodopsin detecting colors in the blue wavelength ranges. ConclusionsExpanded genomic discoveries reveal the genetics underlying Glossina biology and provide a rich body of knowledge for basic science and disease control. They also provide insight into the evolutionary biology underlying novel adaptations and are relevant to applied aspects of vector control such as trap design and discovery of novel pest and disease control strategies.

genomics↗