Computational efforts to identify functional elements within genomes leverage comparative sequence information by looking for regions that exhibit evidence of selective constraint. One way of detecting constrained elements is to follow a bottom-up approach by computing constraint scores for individual positions of a multiple alignment and then defining constrained elements as segments of contiguous, highly scoring nucleotide positions. Here we present GERP++, a new tool that uses maximum likelihood evolutionary rate estimation for position-specific scoring and, in contrast to previous bottom-up methods, a novel dynamic programming approach to subsequently define constrained elements. GERP++ evaluates a richer set of candidate element breakpoints and ranks them based on statistical significance, eliminating the need for biased heuristic extension techniques. Using GERP++ we identify over 1.3 million constrained elements spanning over 7% of the human genome. We predict a higher fraction than earlier estimates largely due to the annotation of longer constrained elements, which improves one to one correspondence between predicted elements with known functional sequences. GERP++ is an efficient and effective tool to provide both nucleotide- and element-level constraint scores within deep multiple sequence alignments. There are millions of sequences in the human genome that perform essential functions, such as protein-coding exons, noncoding RNAs, and regulatory sequences that control the transcription of genes. However, these functional sequences are embedded in a background of DNA that serves no discernible function. Thus, a major challenge in the field of genomics is the accurate identification of functional sequences in the human genome. One approach to identify functional sequences is to align the genome sequences of many divergent species and search for sequences whose similarity has been maintained during evolution. We have developed GERP++, a software tool that utilizes this “comparative genomics” approach to identify putatively functional sequences. Given a multiple sequence alignment, GERP++ identifies sites under evolutionary constraint, i.e., sites that show fewer substitutions than would be expected to occur during neutral evolution. GERP++ then aggregates these sites into longer, potentially functional sequences called constrained elements. Using GERP++ results in improved resolution of functional sequence elements in the human genome and reveals that a higher proportion of the human genome is under evolutionary constraint (∼7%) than was previously estimated.

Bacterial pathogenicity islands (PAI) often encode both effector molecules responsible for disease and secretion systems that deliver these effectors to host cells. Human enterohemorrhagic Escherichia coli (EHEC), enteropathogenic E. coli , and the mouse pathogen Citrobacter rodentium (CR) possess the locus of enterocyte effacement (LEE) PAI. We systematically mutagenized all 41 CR LEE genes and functionally characterized these mutants in vitro and in a murine infection model. We identified 33 virulence factors, including two virulence regulators and a hierarchical switch for type III secretion. In addition, 7 potential type III effectors encoded outside the LEE were identified by using a proteomics approach. These non-LEE effectors are encoded by three uncharacterized PAIs in EHEC O157, suggesting that these PAIs act cooperatively with the LEE in pathogenesis. Our findings provide significant insights into bacterial virulence mechanisms and disease.

Short insertions and deletions (indels) are the second most abundant form of human genetic variation, but our understanding of their origins and functional effects lags behind that of other types of variants. Using population-scale sequencing, we have identified a high-quality set of 1.6 million indels from 179 individuals representing three diverse human populations. We show that rates of indel mutagenesis are highly heterogeneous, with 43%–48% of indels occurring in 4.03% of the genome, whereas in the remaining 96% their prevalence is 16 times lower than SNPs. Polymerase slippage can explain upwards of three-fourths of all indels, with the remainder being mostly simple deletions in complex sequence. However, insertions do occur and are significantly associated with pseudo-palindromic sequence features compatible with the fork stalling and template switching (FoSTeS) mechanism more commonly associated with large structural variations. We introduce a quantitative model of polymerase slippage, which enables us to identify indel-hypermutagenic protein-coding genes, some of which are associated with recurrent mutations leading to disease. Accounting for mutational rate heterogeneity due to sequence context, we find that indels across functional sequence are generally subject to stronger purifying selection than SNPs. We find that indel length modulates selection strength, and that indels affecting multiple functionally constrained nucleotides undergo stronger purifying selection. We further find that indels are enriched in associations with gene expression and find evidence for a contribution of nonsense-mediated decay. Finally, we show that indels can be integrated in existing genome-wide association studies (GWAS); although we do not find direct evidence that potentially causal protein-coding indels are enriched with associations to known disease-associated SNPs, our findings suggest that the causal variant underlying some of these associations may be indels.

Significance: Cancer represents a breakdown of molecular mechanisms evolved by multicellular life to impose constraints on cell growth, resulting in more “primitive” proliferative cellular phenotypes. This suggests interpreting the activity of genes in cancer according to their evolutionary origins may provide insights into common mechanisms driving tumorigenesis. We incorporated phylogenetic and interaction data into expression analysis of seven solid tumors, revealing universal strong preferential expression of genes shared with unicellular species in tumors, alongside widespread disruption of links between unicellular and multicellular components of gene regulatory networks. Considering how the constraints imposed on these networks by evolution were altered in tumors identified molecular processes that could be manipulated for therapeutic benefit in cancer and uncovered several promising drug targets.

Summary: Enterohaemorrhagic Escherichia coli (EHEC) O157:H7 uses a specialized protein translocation apparatus, the type III secretion system (TTSS), to deliver bacterial effector proteins into host cells. These effectors interfere with host cytoskeletal pathways and signalling cascades to facilitate bacterial survival and replication and promote disease. The genes encoding the TTSS and all known type III secreted effectors in EHEC are localized in a single pathogenicity island on the bacterial chromosome known as the locus for enterocyte effacement (LEE). In this study, we performed a proteomic analysis of proteins secreted by the LEE‐encoded TTSS of EHEC. In addition to known LEE‐encoded type III secreted proteins, such as EspA, EspB and Tir, a novel protein, NleA (non‐LEE‐encoded effector A), was identified. NleA is encoded in a prophage‐associated pathogenicity island within the EHEC genome, distinct from the LEE. The LEE‐encoded TTSS directs translocation of NleA into host cells, where it localizes to the Golgi apparatus. In a panel of strains examined by Southern blot and database analyses, nleA was found to be present in all other LEE‐containing pathogens examined, including enteropathogenic E. coli and Citrobacter rodentium, and was absent from non‐pathogenic strains of E. coli and non‐LEE‐containing pathogens. NleA was determined to play a key role in virulence of C. rodentium in a mouse infection model.