Protein Amino Acid Composition: A Genomic Signature of Encephalization in Mammals

Large brains relative to body size represent an evolutionarily costly adaptation as they are metabolically expensive and demand substantial amounts of time to reach structural and functional maturity thereby exacerbating offspring mortality while delaying reproductive age. In spite of its cost and adaptive impact, no genomic features linked to brain evolution have been found. By conducting a genome-wide analysis in all 37 fully sequenced mammalian genomes, we show that encephalization is significantly correlated with overall protein amino acid composition. This correlation is not a by-product of changes in nucleotide content, lifespan, body size, absolute brain size or genome size; is independent of phylogenetic effects; and is not restricted to brain expressed genes. This is the first report of a relationship between this fundamental and complex trait and changes in protein AA usage, possibly reflecting the high selective demands imposed by the process of encephalization across mammalian lineages

Increased brain size in mammals is associated with size variations in gene families with cell signalling, chemotaxis and immune-related functions

Genomic determinants underlying increased encephalization across mammalian lineages are unknown. Whole genome comparisons have revealed large and frequent changes in the size of gene families, and it has been proposed that these variations could play a major role in shaping morphological and physiological differences among species. Using a genome-wide comparative approach, we examined changes in gene family size (GFS) and degree of encephalization in 39 fully sequenced mammalian species and found a significant over-representation of GFS variations in line with increased encephalization in mammals. We found that this relationship is not accounted for by known correlates of brain size such as maximum lifespan or body size and is not explained by phylogenetic relatedness. Genes involved in chemotaxis, immune regulation and cell signalling-related functions are significantly over-represented among those gene families most highly correlated with encephalization. Genes within these families are prominently expressed in the human brain, particularly the cortex, and organized in co-expression modules that display distinct temporal patterns of expression in the developing cortex. Our results suggest that changes in GFS associated with encephalization represent an evolutionary response to the specific functional requirements underlying increased brain size in mammals. © 2013 The Authors

Emergence of co-expression in gene regulatory networks.

Transcriptomes are known to organize themselves into gene co-expression clusters or modules where groups of genes display distinct patterns of coordinated or synchronous expression across independent biological samples. The functional significance of these co-expression clusters is suggested by the fact that highly coexpressed groups of genes tend to be enriched in genes involved in common functions and biological processes. While gene co-expression is widely assumed to reflect close regulatory proximity, the validity of this assumption remains unclear. Here we use a simple synthetic gene regulatory network (GRN) model and contrast the resulting co-expression structure produced by these networks with their known regulatory architecture and with the co-expression structure measured in available human expression data. Using randomization tests, we found that the levels of co-expression observed in simulated expression data were, just as with empirical data, significantly higher than expected by chance. When examining the source of correlated expression, we found that individual regulators, both in simulated and experimental data, fail, on average, to display correlated expression with their immediate targets. However, highly correlated gene pairs tend to share at least one common regulator, while most gene pairs sharing common regulators do not necessarily display correlated expression. Our results demonstrate that widespread co-expression naturally emerges in regulatory networks, and that it is a reliable and direct indicator of active co-regulation in a given cellular context

Data from: Optimisation of next generation sequencing transcriptome annotation for species lacking sequenced genomes

Next generation sequencing methods, such as RNA-seq, have permitted the exploration of gene expression in a range of organisms which have been studied in ecological contexts but lack a sequenced genome. However, the efficacy and accuracy of RNA-seq annotation methods using reference genomes from related species have yet to be robustly characterised. Here we conduct a comprehensive power analysis employing RNA-seq data from Drosophila melanogaster in conjunction with 11 additional genomes from related Drosophila species to compare annotation methods and quantify the impact of evolutionary divergence between transcriptome and the reference genome. Our analyses demonstrate that, regardless of the level of sequence divergence, direct genome mapping, where transcript short reads are aligned directly to the reference genome, significantly outperforms the widely used de novo and guided assembly-based methods in both the quantity and accuracy of gene detection. Our analysis also reveals that direct genome mapping recovers a more representative profile of Gene Ontology functional categories, which are often used to interpret emergent patterns in genome-wide expression analyses. Lastly, analysis of available primate RNA-seq data demonstrates the applicability of our observations across diverse taxa. Our quantification of annotation accuracy and reduced gene detection associated with sequence divergence thus provide empirically derived guidelines for the design of future gene expression studies in species without sequenced genomes

dmel_RNA-seq_mapto_dsec_sam

D. melanogaster RNA-seq reads aligned to the D. sechellia genom

dmel_RNA-seq_mapto_dmel_sam

D. melanogaster RNA-seq reads aligned to the D. melanogaster genom

Dmel_denovo_assembly_VelvetOases.fa

D. melanogaster de novo assembly constructed using Velvet Oase

human-RNAseq_mapto_Gorilla-gorilla

Human RNA-seq reads aligned to the G. gorilla genom