Coevolution reveals a network of human proteins originating with multicellularity.

Protein interaction networks play central roles in biological systems, from simple metabolic pathways through complex programs permitting the development of organisms. Multicellularity could only have arisen from a careful orchestration of cellular and molecular roles and responsibilities, all properly controlled and regulated. Disease reflects a breakdown of this organismal homeostasis. To better understand the evolution of interactions whose dysfunction may be contributing factors to disease, we derived the human protein coevolution network using our MatrixMatchMaker algorithm and using the Orthologous MAtrix project (OMA) database as a source for protein orthologs from 103 eukaryotic genomes. We annotated the coevolution network using protein-protein interaction data, many functional data sources, and we explored the evolutionary rates and dates of emergence of the proteins in our data set. Strikingly, clustering based only on the topology of the coevolution network partitions it into two subnetworks, one generally representing ancient eukaryotic functions and the other functions more recently acquired during animal evolution. That latter subnetwork is enriched for proteins with roles in cell-cell communication, the control of cell division, and related multicellular functions. Further annotation using data from genetic disease databases and cancer genome sequences strongly implicates these proteins in both ciliopathies and cancer. The enrichment for such disease markers in the animal network suggests a functional link between these coevolving proteins. Genetic validation corroborates the recruitment of ancient cilia in the evolution of multicellularity.

A census of human soluble protein complexes.

Cellular processes often depend on stable physical associations between proteins. Despite recent progress, knowledge of the composition of human protein complexes remains limited. To close this gap, we applied an integrative global proteomic profiling approach, based on chromatographic separation of cultured human cell extracts into more than one thousand biochemical fractions that were subsequently analyzed by quantitative tandem mass spectrometry, to systematically identify a network of 13,993 high-confidence physical interactions among 3,006 stably associated soluble human proteins. Most of the 622 putative protein complexes we report are linked to core biological processes and encompass both candidate disease genes and unannotated proteins to inform on mechanism. Strikingly, whereas larger multiprotein assemblies tend to be more extensively annotated and evolutionarily conserved, human protein complexes with five or fewer subunits are far more likely to be functionally unannotated or restricted to vertebrates, suggesting more recent functional innovations.

Using coevolution to predict protein-protein interactions.

Bioinformatic methods to predict protein-protein interactions (PPI) via coevolutionary analysis have -positioned themselves to compete alongside established in vitro methods, despite a lack of understanding for the underlying molecular mechanisms of the coevolutionary process. Investigating the alignment of coevolutionary predictions of PPI with experimental data can focus the effective scope of prediction and lead to better accuracies. A new rate-based coevolutionary method, MMM, preferentially finds obligate interacting proteins that form complexes, conforming to results from studies based on coimmunoprecipitation coupled with mass spectrometry. Using gold-standard databases as a benchmark for accuracy, MMM surpasses methods based on abundance ratios, suggesting that correlated evolutionary rates may yet be better than coexpression at predicting interacting proteins. At the level of protein domains, -coevolution is difficult to detect, even with MMM, except when considering small-scale experimental data involving proteins with multiple domains. Overall, these findings confirm that coevolutionary -methods can be confidently used in predicting PPI, either independently or as drivers of coimmunoprecipitation experiments.

Analysis of site frequency spectra from Arabidopsis with context-dependent corrections for ancestral misinference.

Previous studies have shown that the pattern of single nucleotide polymorphism (SNP) in Arabidopsis (Arabidopsis thaliana) deviates from the distribution expected under a neutral model. Here, we test whether or not ancestral misinference could explain this deviation. We start by showing that there are significant and complex influences of context on mutation dynamics as inferred from SNP frequency, in Arabidopsis, and compare the results to observations about context dependency that have been made on a previous analysis of a maize (Zea mays) SNP dataset. The data concerning heterogeneity across sites are then used to make corrections for ancestral misinference in a context-dependent manner. Using Arabidopsis lyrata to infer the ancestral state for SNPs, we show that the resulting unfolded site frequency spectrum (SFS) in Arabidopsis is skewed toward sites with high frequency derived nucleotides. Sites are also partitioned into two general functional classes, second codon position and 4-fold degenerate sites. These two classes show different SFS; although both show an overrepresentation of high frequency derived sites, low frequency derived sites are vastly overrepresented at the second codon position, but significantly underrepresented at 4-fold degenerate sites. We find that these results are robust to corrections for ancestral misinference, even when context-dependent variation in mutation properties is taken into consideration. The data suggest that, in addition to purifying selection, complex demographic events and/or linked positive selection need to be invoked to explain the SFS, and they highlight the importance of sequence context in analyses of genome-wide variation.

Selection on amino acid substitutions in Arabidopsis.

Studies of nucleotide diversity have found an excess of low-frequency amino acid polymorphisms segregating in Arabidopsis thaliana, suggesting a predominance of weak purifying selection acting on amino acid polymorphism in this inbreeding species. Here, we investigate levels of diversity and divergence at synonymous and nonsynonymous sites in 6 circumpolar populations of the outbreeding Arabidopsis lyrata and compare these results with A. thaliana, to test for differences in mutation and selection parameters across genes, populations, and species. We find that A. lyrata shows an excess of low-frequency nonsynonymous polymorphisms both within populations and species wide, consistent with weak purifying selection similar to the patterns observed in A. thaliana. Furthermore, nonsynonymous polymorphisms tend to be more restricted in their population distribution in A. lyrata, consistent with purifying selection preventing their geographic spread. Highly expressed genes show a reduced ratio of amino acid to synonymous change for both polymorphism and fixed differences, suggesting a general pattern of stronger purifying selection on high-expression proteins.

Effective population size and tests of neutrality at cytoplasmic genes in Arabidopsis.

Cytoplasmic genomes typically lack recombination, implying that genetic hitch-hiking could be a predominant force structuring nucleotide polymorphism in the chloroplast and mitochondria. We test this hypothesis by analysing nucleotide polymorphism data at 28 loci across the chloroplast and mitochondria of the outcrossing plant Arabidopsis lyrata, and compare patterns with multiple nuclear loci, and the highly selfing Arabidopsis thaliana. The maximum likelihood estimate of the ratio of effective population size at cytoplasmic relative to nuclear genes in A. lyrata does not depart from the neutral expectation of 0.5. Similarly, the ratio of effective size in A. thaliana is close to unity, the neutral expectation for a highly selfing species. The results are thus consistent with neutral organelle polymorphism in these species or with comparable effects of hitch-hiking in both cytoplasmic and nuclear genes, in contrast to the results of recent studies on gynodioecious taxa. The four-gamete test and composite likelihood estimation provide evidence for very low levels of recombination in the organelles of A. lyrata, although permutation tests do not suggest that adjacent polymorphic sites are more closely linked than more distant sites across the two genomes, suggesting that mutation hotspots or very low rates of gene conversion could explain the data.