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      Correcting for Differential Transcript Coverage Reveals a Strong Relationship between Alternative Splicing and Organism Complexity

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          Abstract

          What at the genomic level underlies organism complexity? Although several genomic features have been associated with organism complexity, in the case of alternative splicing, which has long been proposed to explain the variation in complexity, no such link has been established. Here, we analyzed over 39 million expressed sequence tags available for 47 eukaryotic species with fully sequenced genomes to obtain a comparable index of alternative splicing estimates, which corrects for the distorting effect of a variable number of transcripts per species—an important obstacle for comparative studies of alternative splicing. We find that alternative splicing has steadily increased over the last 1,400 My of eukaryotic evolution and is strongly associated with organism complexity, assayed as the number of cell types. Importantly, this association is not explained as a by-product of covariance between alternative splicing with other variables previously linked to complexity including gene content, protein length, proteome disorder, and protein interactivity. In addition, we found no evidence to suggest that the relationship of alternative splicing to cell type number is explained by drift due to reduced N e in more complex species. Taken together, our results firmly establish alternative splicing as a significant predictor of organism complexity and are, in principle, consistent with an important role of transcript diversification through alternative splicing as a means of determining a genome’s functional information capacity.

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          Ensembl BioMarts: a hub for data retrieval across taxonomic space

          For a number of years the BioMart data warehousing system has proven to be a valuable resource for scientists seeking a fast and versatile means of accessing the growing volume of genomic data provided by the Ensembl project. The launch of the Ensembl Genomes project in 2009 complemented the Ensembl project by utilizing the same visualization, interactive and programming tools to provide users with a means for accessing genome data from a further five domains: protists, bacteria, metazoa, plants and fungi. The Ensembl and Ensembl Genomes BioMarts provide a point of access to the high-quality gene annotation, variation data, functional and regulatory annotation and evolutionary relationships from genomes spanning the taxonomic space. This article aims to give a comprehensive overview of the Ensembl and Ensembl Genomes BioMarts as well as some useful examples and a description of current data content and future objectives. Database URLs: http://www.ensembl.org/biomart/martview/; http://metazoa.ensembl.org/biomart/martview/; http://plants.ensembl.org/biomart/martview/; http://protists.ensembl.org/biomart/martview/; http://fungi.ensembl.org/biomart/martview/; http://bacteria.ensembl.org/biomart/martview/
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            The origins of genome complexity.

            Complete genomic sequences from diverse phylogenetic lineages reveal notable increases in genome complexity from prokaryotes to multicellular eukaryotes. The changes include gradual increases in gene number, resulting from the retention of duplicate genes, and more abrupt increases in the abundance of spliceosomal introns and mobile genetic elements. We argue that many of these modifications emerged passively in response to the long-term population-size reductions that accompanied increases in organism size. According to this model, much of the restructuring of eukaryotic genomes was initiated by nonadaptive processes, and this in turn provided novel substrates for the secondary evolution of phenotypic complexity by natural selection. The enormous long-term effective population sizes of prokaryotes may impose a substantial barrier to the evolution of complex genomes and morphologies.
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              TimeTree: a public knowledge-base of divergence times among organisms.

              Biologists and other scientists routinely need to know times of divergence between species and to construct phylogenies calibrated to time (timetrees). Published studies reporting time estimates from molecular data have been increasing rapidly, but the data have been largely inaccessible to the greater community of scientists because of their complexity. TimeTree brings these data together in a consistent format and uses a hierarchical structure, corresponding to the tree of life, to maximize their utility. Results are presented and summarized, allowing users to quickly determine the range and robustness of time estimates and the degree of consensus from the published literature. TimeTree is available at http://www.timetree.net
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                Author and article information

                Journal
                Mol Biol Evol
                Mol. Biol. Evol
                molbev
                molbiolevol
                Molecular Biology and Evolution
                Oxford University Press
                0737-4038
                1537-1719
                June 2014
                27 March 2014
                27 March 2014
                : 31
                : 6
                : 1402-1413
                Affiliations
                1Department of Biology and Biochemistry, University of Bath, Bath, United Kingdom
                Author notes

                These authors contributed equally to this work.

                Present address: Human Genetics, Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire, United Kingdom

                Associate editor: Csaba Pal

                *Corresponding author: E-mail: a.urrutia@ 123456bath.ac.uk .
                Article
                msu083
                10.1093/molbev/msu083
                4032128
                24682283
                223bb855-cdb9-4e60-8dd6-b6b8bec89e59
                © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Page count
                Pages: 12
                Categories
                Discoveries

                Molecular biology
                organism complexity,alternative splicing,genome evolution,transcriptome evolution,expressed sequence tags

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