Cohesive versus Flexible Evolution of Functional Modules in Eukaryotes

Although functionally related proteins can be reliably predicted from phylogenetic profiles, many functional modules do not seem to evolve cohesively according to case studies and systematic analyses in prokaryotes. In this study we quantify the extent of evolutionary cohesiveness of functional modules in eukaryotes and probe the biological and methodological factors influencing our estimates. We have collected various datasets of protein complexes and pathways in Saccheromyces cerevisiae. We define orthologous groups on 34 eukaryotic genomes and measure the extent of cohesive evolution of sets of orthologous groups of which members constitute a known complex or pathway. Within this framework it appears that most functional modules evolve flexibly rather than cohesively. Even after correcting for uncertain module definitions and potentially problematic orthologous groups, only 46% of pathways and complexes evolve more cohesively than random modules. This flexibility seems partly coupled to the nature of the functional module because biochemical pathways are generally more cohesively evolving than complexes

Enrichment of homologs in insignificant BLAST hits by co-complex network alignment

<p>Abstract</p> <p>Background</p> <p>Homology is a crucial concept in comparative genomics. The algorithm probably most widely used for homology detection in comparative genomics, is BLAST. Usually a stringent score cutoff is applied to distinguish putative homologs from possible false positive hits. As a consequence, some BLAST hits are discarded that are in fact homologous.</p> <p>Results</p> <p>Analogous to the use of the genomics context in genome alignments, we test whether conserved functional context can be used to select candidate homologs from insignificant BLAST hits. We make a co-complex network alignment between complex subunits in yeast and human and find that proteins with an insignificant BLAST hit that are part of homologous complexes, are likely to be homologous themselves. Further analysis of the distant homologs we recovered using the co-complex network alignment, shows that a large majority of these distant homologs are in fact ancient paralogs.</p> <p>Conclusions</p> <p>Our results show that, even though evolution takes place at the sequence and genome level, co-complex networks can be used as circumstantial evidence to improve confidence in the homology of distantly related sequences.</p

A methodology for detecting the orthology signal in a PPI network at a functional complex level

Contains fulltext : 93730.pdf (preprint version ) (Open Access)13 p

Describing the orthology signal in a PPI network at a functional, complex level

In recent work, stable evolutionary signal induced by orthologous proteins has been observed in a Yeast protein-protein interaction (PPI) network. This finding suggests more connected subgraphs of a PPI network to be potential mediators of evolutionary information. Because protein complexes are also likely to be present in such subgraphs, it is interesting to characterize the bias of the orthology signal on the detection of putative protein complexes. To this aim, we propose a novel methodology for quantifying the functionality of the orthology signal in a PPI network at a protein complex level. The methodology performs a differential analysis between the functions of those complexes detected by clustering a PPI network using only proteins with orthologs in another given species, and the functions of complexes detected using the entire network or sub-networks generated by random sampling of proteins. We applied the proposed methodology to a Yeast PPI network using orthology information from a number of different organisms. The results indicated that the proposed method is capable to isolate functional categories that can be clearly attributed to the presence of an evolutionary (orthology) signal and quantify their distribution at a fine-grained protein level

Bacterial genes and genome dynamics in the environment

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2013Cataloged from PDF version of thesis.Includes bibliographical references (p. 143-158).One of the most marvelous features of microbial life is its ability to thrive in such diverse and dynamic environments. My scientific interest lies in the variety of modes by which microbial life accomplishes this feat. In the first half of this thesis I present tools to leverage high throughput sequencing for the study of environmental genomes. In the second half of this thesis, I describe modes of environmental adaptation by bacteria via gene content or gene expression evolution. Associating genes' usage and evolution to adaptation in various environments is a cornerstone of microbiology. New technologies and approaches have revolutionized this pursuit, and I begin by describing the computational challenges I resolved in order to bring these technologies to bear on microbial genomics. In Chapter 1, I describe SHE-RA, an algorithm that increases the useable read length of ultra-high throughput sequencing technologies, thus extending their range of applications to include environmental sequencing. In Chapter 2, I design a new hybrid assembly approach for short reads and assemble 82 Vibrio genomes. Using the ecologically defined groups of this bacterial family, I investigate the genomic and metabolic correlates of habitat and differentiation, and evaluate a neutral model of gene content. In Chapter 3, I report the extent to which orthologous genes in bacteria exhibit the same transcriptional response to the same change in environment, and describe the features and functions of bacterial transcriptional networks that are conserved. I conclude this thesis with a summary of my tools and results, their use in other studies, and their relevance to future work. In particular, I discuss the future experiments and analytical strategies that I am eager to see applied to compelling open questions in microbial ecology and evolution.by Sonia C. Timberlake.Ph.D

Application of high-resolution metagenomics to study symbiont population structure across individual mussels

Eukaryotes are habitats for bacterial organisms where the host colonization and dispersal among individual hosts have consequences for bacterial ecology and evolution. Vertical symbiont transmission leads to geographic isolation of the microbial population and consequently to genetic isolation of microbiotas from individual hosts. In contrast, the extent of geographic and genetic isolation of horizontally transmitted microbiota and its consequences in shaping population pangenomes is poorly characterized. Here we show that chemosynthetic symbionts (Sulfur-oxidizing or SOX and Methane-oxidizing or MOX) of individual Bathymodiolus brooksi mussels constitute genetically isolated subpopulations. The reconstruction of core genome-wide strain sequences from high-resolution metagenomes revealed distinct phylogenetic clades. Nucleotide diversity and strain composition vary along the mussel lifespan, and individual hosts show a high degree of genetic isolation. By additionally reconstructing population pan genomes, we reveal that gene content differences between mussel symbiont communities reflect the differences in strain composition; thus, strains belonging to the same monophyletic group share most of their genes. Furthermore, for both symbionts, the accessory gene content is over-represented in functions related to genome integrity. Compared to SOX, the MOX pan-genome is larger and has a smaller fraction of accessory genes. We find that MOX contains more genes related to cell motility and mobile genetic elements. Altogether, our results suggest that the uptake of environmental bacteria is a restricted process in B. brooksi, where self-infection of the gill tissue results in serial founder effects during symbiont evolution. We suggest that this geographic isolation among symbiont populations from individual mussels limits the exposure of symbionts to mobile genetic elements. In addition, the differences between both species suggest that the two symbionts have different ecological traits, where the association of MOX with the host occurred more recently and has a more facultative character that may involve an active free-living phase. We conclude that bacterial colonization dynamics over the host life cycle are an important determinant of population structure and genome evolution of horizontally transmitted symbionts