Gene expression profiling of placentae from women with obesity and obstructive sleep apnoea.

INTRODUCTION: Obstructive sleep apnoea (OSA), a condition characterised by intermittent hypoxia and reoxygenation during sleep, is associated with an increased risk of adverse pregnancy outcomes including gestational diabetes and hypertensive disorders of pregnancy. The biological mechanisms of these associations are poorly understood. The impact of OSA on placental function has not been well characterised. METHODS: We performed 3' mRNA sequencing on placenta from women with obesity and OSA (n = 11) and women with obesity and no OSA (n = 9). RESULTS: After correcting for multiple testing, there were no statistically significant differences in gene expression between OSA and no OSA groups (adjusted p < 0.05). In unadjusted analyses, 101 genes were differentially expressed in OSA compared to no OSA placentae (p < 0.01). In Reactome pathway and GO term analysis, this included downregulation of genes involved in O-linked glycosylation (B3GNT5 and B3GNT8) and Wnt signalling (TRABD2B and FRZB) pathways. In gene set enrichment analysis, genes within 24 pathways had a non-random distribution in OSA compared to no OSA placentae (adjusted p < 0.05). This included an increase in genes relating to the reversible hydration of carbon dioxide in OSA placentae, a potential novel mechanism contributing to the development of adverse pregnancy outcomes in women with OSA. DISCUSSION: There is overall similarity in the placental transcriptome of women with obesity who do and do not have OSA during pregnancy. Alterations in the reversible hydration of carbon dioxide are a potential mechanism contributing to the development of adverse pregnancy outcomes in maternal OSA, however this finding requires validation in larger cohorts.

Tumor Fusion Burden as a Hallmark of Immune Infiltration in Prostate Cancer.

Prostate cancer is the second leading cause of cancer-related death in men. Despite having a relatively lower tumor mutational burden than most tumor types, multiple gene fusions such as TMPRSS2:ERG have been characterized and linked to more aggressive disease. Individual tumor samples have been found to contain multiple fusions, and it remains unknown whether these fusions increase tumor immunogenicity. Here, we investigated the role of fusion burden on the prevalence and expression of key molecular and immune effectors in prostate cancer tissue specimens that represented the different stages of disease progression and androgen sensitivity, including hormone-sensitive and castration-resistant prostate cancer. We found that tumor fusion burden was inversely correlated with tumor mutational burden and not associated with disease stage. High fusion burden correlated with high immune infiltration, PD-L1 expression on immune cells, and immune signatures, representing activation of T cells and M1 macrophages. High fusion burden inversely correlated with immune-suppressive signatures. Our findings suggest that high tumor fusion burden may be a more appropriate biomarker than tumor mutational burden in prostate cancer, as it more closely associates with immunogenicity, and suggests that tumors with high fusion burden could be potential candidates for immunotherapeutic agents.

Comprehensive Profiling of Poor-Risk Paired Primary and Recurrent Triple-Negative Breast Cancers Reveals Immune Phenotype Shifts.

PURPOSE: Emerging data suggest immune checkpoint inhibitors have reduced efficacy in heavily pretreated triple-negative breast cancers (TNBC), but underlying mechanisms are poorly understood. To better understand the phenotypic evolution of TNBCs, we studied the genomic and transcriptomic profiles of paired tumors from patients with TNBC. EXPERIMENTAL DESIGN: We collected paired primary and metastatic TNBC specimens from 43 patients and performed targeted exome sequencing and whole-transcriptome sequencing. From these efforts, we ascertained somatic mutation profiles, tumor mutational burden (TMB), TNBC molecular subtypes, and immune-related gene expression patterns. Stromal tumor-infiltrating lymphocytes (stromal TIL), recurrence-free survival, and overall survival were also analyzed. RESULTS: We observed a typical TNBC mutational landscape with minimal shifts in copy number or TMB over time. However, there were notable TNBC molecular subtype shifts, including increases in the Lehmann/Pietenpol-defined basal-like 1 (BL1, 11.4%-22.6%) and mesenchymal (M, 11.4%-22.6%) phenotypes, and a decrease in the immunomodulatory phenotype (IM, 31.4%-3.2%). The Burstein-defined basal-like immune-activated phenotype was also decreased (BLIA, 42.2%-17.2%). Among downregulated genes from metastases, we saw enrichment of immune-related Kyoto Encyclopedia of Genes and Genomes pathways and gene ontology (GO) terms, and decreased expression of immunomodulatory gene signatures (P < 0.03) and percent stromal TILs (P = 0.03). There was no clear association between stromal TILs and survival. CONCLUSIONS: We observed few mutational shifts, but largely consistent transcriptomic shifts in longitudinally paired TNBCs. Transcriptomic and IHC analyses revealed significantly reduced immune-activating gene expression signatures and TILs in recurrent TNBCs. These data may explain the observed lack of efficacy of immunotherapeutic agents in heavily pretreated TNBCs. Further studies are ongoing to better understand these initial observations.See related commentary by Savas and Loi, p. 526.

Survival prediction in mesothelioma using a scalable Lasso regression model: instructions for use and initial performance using clinical predictors.

INTRODUCTION: Accurate prognostication is difficult in malignant pleural mesothelioma (MPM). We developed a set of robust computational models to quantify the prognostic value of routinely available clinical data, which form the basis of published MPM prognostic models. METHODS: Data regarding 269 patients with MPM were allocated to balanced training (n=169) and validation sets (n=100). Prognostic signatures (minimal length best performing multivariate trained models) were generated by least absolute shrinkage and selection operator regression for overall survival (OS), OS <6 months and OS <12 months. OS prediction was quantified using Somers DXY statistic, which varies from 0 to 1, with increasing concordance between observed and predicted outcomes. 6-month survival and 12-month survival were described by area under the curve (AUC) scores. RESULTS: Median OS was 270 (IQR 140-450) days. The primary OS model assigned high weights to four predictors: age, performance status, white cell count and serum albumin, and after cross-validation performed significantly better than would be expected by chance (mean DXY0.332 (±0.019)). However, validation set DXY was only 0.221 (0.0935-0.346), equating to a 22% improvement in survival prediction than would be expected by chance. The 6-month and 12-month OS signatures included the same four predictors, in addition to epithelioid histology plus platelets and epithelioid histology plus C-reactive protein (mean AUC 0.758 (±0.022) and 0.737 (±0.012), respectively). The <6-month OS model demonstrated 74% sensitivity and 68% specificity. The <12-month OS model demonstrated 63% sensitivity and 79% specificity. Model content and performance were generally comparable with previous studies. CONCLUSIONS: The prognostic value of the basic clinical information contained in these, and previously published models, is fundamentally of limited value in accurately predicting MPM prognosis. The methods described are suitable for expansion using emerging predictors, including tumour genomics and volumetric staging.

TGFß attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells.

Therapeutic antibodies that block the programmed death-1 (PD-1)-programmed death-ligand 1 (PD-L1) pathway can induce robust and durable responses in patients with various cancers, including metastatic urothelial cancer. However, these responses only occur in a subset of patients. Elucidating the determinants of response and resistance is key to improving outcomes and developing new treatment strategies. Here we examined tumours from a large cohort of patients with metastatic urothelial cancer who were treated with an anti-PD-L1 agent (atezolizumab) and identified major determinants of clinical outcome. Response to treatment was associated with CD8+ T-effector cell phenotype and, to an even greater extent, high neoantigen or tumour mutation burden. Lack of response was associated with a signature of transforming growth factor ß (TGFß) signalling in fibroblasts. This occurred particularly in patients with tumours, which showed exclusion of CD8+ T cells from the tumour parenchyma that were instead found in the fibroblast- and collagen-rich peritumoural stroma; a common phenotype among patients with metastatic urothelial cancer. Using a mouse model that recapitulates this immune-excluded phenotype, we found that therapeutic co-administration of TGFß-blocking and anti-PD-L1 antibodies reduced TGFß signalling in stromal cells, facilitated T-cell penetration into the centre of tumours, and provoked vigorous anti-tumour immunity and tumour regression. Integration of these three independent biological features provides the best basis for understanding patient outcome in this setting and suggests that TGFß shapes the tumour microenvironment to restrain anti-tumour immunity by restricting T-cell infiltration.

Assessing Recent Selection and Functionality at Long Noncoding RNA Loci in the Mouse Genome.

Long noncoding RNAs (lncRNAs) are one of the most intensively studied groups of noncoding elements. Debate continues over what proportion of lncRNAs are functional or merely represent transcriptional noise. Although characterization of individual lncRNAs has identified approximately 200 functional loci across the Eukarya, general surveys have found only modest or no evidence of long-term evolutionary conservation. Although this lack of conservation suggests that most lncRNAs are nonfunctional, the possibility remains that some represent recent evolutionary innovations. We examine recent selection pressures acting on lncRNAs in mouse populations. We compare patterns of within-species nucleotide variation at approximately 10,000 lncRNA loci in a cohort of the wild house mouse, Mus musculus castaneus, with between-species nucleotide divergence from the rat (Rattus norvegicus). Loci under selective constraint are expected to show reduced nucleotide diversity and divergence. We find limited evidence of sequence conservation compared with putatively neutrally evolving ancestral repeats (ARs). Comparisons of sequence diversity and divergence between ARs, protein-coding (PC) exons and lncRNAs, and the associated flanking regions, show weak, but significantly lower levels of sequence diversity and divergence at lncRNAs compared with ARs. lncRNAs conserved deep in the vertebrate phylogeny show lower within-species sequence diversity than lncRNAs in general. A set of 74 functionally characterized lncRNAs show levels of diversity and divergence comparable to PC exons, suggesting that these lncRNAs are under substantial selective constraints. Our results suggest that, in mouse populations, most lncRNA loci evolve at rates similar to ARs, whereas older lncRNAs tend to show signals of selection similar to PC genes.

Recent Evolution in Rattus norvegicus Is Shaped by Declining Effective Population Size.

The brown rat, Rattus norvegicus, is both a notorious pest and a frequently used model in biomedical research. By analyzing genome sequences of 12 wild-caught brown rats from their presumed ancestral range in NE China, along with the sequence of a black rat, Rattus rattus, we investigate the selective and demographic forces shaping variation in the genome. We estimate that the recent effective population size (Ne) of this species = [Formula: see text], based on silent site diversity. We compare patterns of diversity in these genomes with patterns in multiple genome sequences of the house mouse (Mus musculus castaneus), which has a much larger Ne. This reveals an important role for variation in the strength of genetic drift in mammalian genome evolution. By a Pairwise Sequentially Markovian Coalescent analysis of demographic history, we infer that there has been a recent population size bottleneck in wild rats, which we date to approximately 20,000 years ago. Consistent with this, wild rat populations have experienced an increased flux of mildly deleterious mutations, which segregate at higher frequencies in protein-coding genes and conserved noncoding elements. This leads to negative estimates of the rate of adaptive evolution (α) in proteins and conserved noncoding elements, a result which we discuss in relation to the strongly positive estimates observed in wild house mice. As a consequence of the population bottleneck, wild rats also show a markedly slower decay of linkage disequilibrium with physical distance than wild house mice.

Analysis of Five Gene Sets in Chimpanzees Suggests Decoupling between the Action of Selection on Protein-Coding and on Noncoding Elements.

We set out to investigate potential differences and similarities between the selective forces acting upon the coding and noncoding regions of five different sets of genes defined according to functional and evolutionary criteria: 1) two reference gene sets presenting accelerated and slow rates of protein evolution (the Complement and Actin pathways); 2) a set of genes with evidence of accelerated evolution in at least one of their introns; and 3) two gene sets related to neurological function (Parkinson's and Alzheimer's diseases). To that effect, we combine human-chimpanzee divergence patterns with polymorphism data obtained from target resequencing 20 central chimpanzees, our closest relatives with largest long-term effective population size. By using the distribution of fitness effect-alpha extension of the McDonald-Kreitman test, we reproduce inferences of rates of evolution previously based only on divergence data on both coding and intronic sequences and also obtain inferences for other classes of genomic elements (untranslated regions, promoters, and conserved noncoding sequences). Our results suggest that 1) the distribution of fitness effect-alpha method successfully helps distinguishing different scenarios of accelerated divergence (adaptation or relaxed selective constraints) and 2) the adaptive history of coding and noncoding sequences within the gene sets analyzed is decoupled.

The relation between recombination rate and patterns of molecular evolution and variation in Drosophila melanogaster.

Genetic recombination associated with sexual reproduction increases the efficiency of natural selection by reducing the strength of Hill-Robertson interference. Such interference can be caused either by selective sweeps of positively selected alleles or by background selection (BGS) against deleterious mutations. Its consequences can be studied by comparing patterns of molecular evolution and variation in genomic regions with different rates of crossing over. We carried out a comprehensive study of the benefits of recombination in Drosophila melanogaster, both by contrasting five independent genomic regions that lack crossing over with the rest of the genome and by comparing regions with different rates of crossing over, using data on DNA sequence polymorphisms from an African population that is geographically close to the putatively ancestral population for the species, and on sequence divergence from a related species. We observed reductions in sequence diversity in noncrossover (NC) regions that are inconsistent with the effects of hard selective sweeps in the absence of recombination. Overall, the observed patterns suggest that the recombination rate experienced by a gene is positively related to an increase in the efficiency of both positive and purifying selection. The results are consistent with a BGS model with interference among selected sites in NC regions, and joint effects of BGS, selective sweeps, and a past population expansion on variability in regions of the genome that experience crossing over. In such crossover regions, the X chromosome exhibits a higher rate of adaptive protein sequence evolution than the autosomes, implying a Faster-X effect.

Estimation of the spontaneous mutation rate per nucleotide site in a Drosophila melanogaster full-sib family.

We employed deep genome sequencing of two parents and 12 of their offspring to estimate the mutation rate per site per generation in a full-sib family of Drosophila melanogaster recently sampled from a natural population. Sites that were homozygous for the same allele in the parents and heterozygous in one or more offspring were categorized as candidate mutations and subjected to detailed analysis. In 1.23 × 10(9) callable sites from 12 individuals, we confirmed six single nucleotide mutations. We estimated the false negative rate in the experiment by generating synthetic mutations using the empirical distributions of numbers of nonreference bases at heterozygous sites in the offspring. The proportion of synthetic mutations at callable sites that we failed to detect was <1%, implying that the false negative rate was extremely low. Our estimate of the point mutation rate is 2.8 × 10(-9) (95% confidence interval = 1.0 × 10(-9) - 6.1 × 10(-9)) per site per generation, which is at the low end of the range of previous estimates, and suggests an effective population size for the species of ∼1.4 × 10(6). At one site, point mutations were present in two individuals, indicating that there had been a premeiotic mutation cluster, although surprisingly one individual had a G→A transition and the other a G→T transversion, possibly associated with error-prone mismatch repair. We also detected three short deletion mutations and no insertions, giving a deletion mutation rate of 1.2 × 10(-9) (95% confidence interval = 0.7 × 10(-9) - 11 × 10(-9)).

Faster-X adaptive protein evolution in house mice.

The causes of the large effect of the X chromosome in reproductive isolation and speciation have long been debated. The faster-X hypothesis predicts that X-linked loci are expected to have higher rates of adaptive evolution than autosomal loci if new beneficial mutations are on average recessive. Reproductive isolation should therefore evolve faster when contributing loci are located on the X chromosome. In this study, we have analyzed genome-wide nucleotide polymorphism data from the house mouse subspecies Mus musculus castaneus and nucleotide divergence from Mus famulus and Rattus norvegicus to compare rates of adaptive evolution for autosomal and X-linked protein-coding genes. We found significantly faster adaptive evolution for X-linked loci, particularly for genes with expression in male-specific tissues, but autosomal and X-linked genes with expression in female-specific tissues evolve at similar rates. We also estimated rates of adaptive evolution for genes expressed during spermatogenesis and found that X-linked genes that escape meiotic sex chromosome inactivation (MSCI) show rapid adaptive evolution. Our results suggest that faster-X adaptive evolution is either due to net recessivity of new advantageous mutations or due to a special gene content of the X chromosome, which regulates male function and spermatogenesis. We discuss how our results help to explain the large effect of the X chromosome in speciation.

Processing genome scale tabular data with wormtable.

BACKGROUND: Modern biological science generates a vast amount of data, the analysis of which presents a major challenge to researchers. Data are commonly represented in tables stored as plain text files and require line-by-line parsing for analysis, which is time consuming and error prone. Furthermore, there is no simple means of indexing these files so that rows containing particular values can be quickly found. RESULTS: We introduce a new data format and software library called wormtable, which provides efficient access to tabular data in Python. Wormtable stores data in a compact binary format, provides random access to rows, and enables sophisticated indexing on columns within these tables. Files written in existing formats can be easily converted to wormtable format, and we provide conversion utilities for the VCF and GTF formats. CONCLUSIONS: Wormtable's simple API allows users to process large tables orders of magnitude more quickly than is possible when parsing text. Furthermore, the indexing facilities provide efficient access to subsets of the data along with providing useful methods of summarising columns. Since third-party libraries or custom code are no longer needed to parse complex plain text formats, analysis code can also be substantially simpler as well as being uniform across different data formats. These benefits of reduced code complexity and greatly increased performance allow users much greater freedom to explore their data.

Contributions of protein-coding and regulatory change to adaptive molecular evolution in murid rodents.

The contribution of regulatory versus protein change to adaptive evolution has long been controversial. In principle, the rate and strength of adaptation within functional genetic elements can be quantified on the basis of an excess of nucleotide substitutions between species compared to the neutral expectation or from effects of recent substitutions on nucleotide diversity at linked sites. Here, we infer the nature of selective forces acting in proteins, their UTRs and conserved noncoding elements (CNEs) using genome-wide patterns of diversity in wild house mice and divergence to related species. By applying an extension of the McDonald-Kreitman test, we infer that adaptive substitutions are widespread in protein-coding genes, UTRs and CNEs, and we estimate that there are at least four times as many adaptive substitutions in CNEs and UTRs as in proteins. We observe pronounced reductions in mean diversity around nonsynonymous sites (whether or not they have experienced a recent substitution). This can be explained by selection on multiple, linked CNEs and exons. We also observe substantial dips in mean diversity (after controlling for divergence) around protein-coding exons and CNEs, which can also be explained by the combined effects of many linked exons and CNEs. A model of background selection (BGS) can adequately explain the reduction in mean diversity observed around CNEs. However, BGS fails to explain the wide reductions in mean diversity surrounding exons (encompassing ~100 Kb, on average), implying that there is a substantial role for adaptation within exons or closely linked sites. The wide dips in diversity around exons, which are hard to explain by BGS, suggest that the fitness effects of adaptive amino acid substitutions could be substantially larger than substitutions in CNEs. We conclude that although there appear to be many more adaptive noncoding changes, substitutions in proteins may dominate phenotypic evolution.

Inference of site frequency spectra from high-throughput sequence data: quantification of selection on nonsynonymous and synonymous sites in humans.

Sequencing errors and random sampling of nucleotide types among sequencing reads at heterozygous sites present challenges for accurate, unbiased inference of single-nucleotide polymorphism genotypes from high-throughput sequence data. Here, we develop a maximum-likelihood approach to estimate the frequency distribution of the number of alleles in a sample of individuals (the site frequency spectrum), using high-throughput sequence data. Our method assumes binomial sampling of nucleotide types in heterozygotes and random sequencing error. By simulations, we show that close to unbiased estimates of the site frequency spectrum can be obtained if the error rate per base read does not exceed the population nucleotide diversity. We also show that these estimates are reasonably robust if errors are nonrandom. We then apply the method to infer site frequency spectra for zerofold degenerate, fourfold degenerate, and intronic sites of protein-coding genes using the low coverage human sequence data produced by the 1000 Genomes Project phase-one pilot. By fitting a model to the inferred site frequency spectra that estimates parameters of the distribution of fitness effects of new mutations, we find evidence for significant natural selection operating on fourfold sites. We also find that a model with variable effects of mutations at synonymous sites fits the data significantly better than a model with equal mutational effects. Under the variable effects model, we infer that 11% of synonymous mutations are subject to strong purifying selection.

Positive and negative selection in murine ultraconserved noncoding elements.

There are many more selectively constrained noncoding than coding nucleotides in the mammalian genome, but most mammalian noncoding DNA is subject to weak selection, on average. One of the most striking discoveries to have emerged from comparisons among mammalian genomes is the hundreds of noncoding elements of more than 200 bp in length that show absolute conservation among mammalian orders. These elements represent the tip of the iceberg of a much larger class of conserved noncoding elements (CNEs). Much evidence suggests that CNEs are selectively constrained and not mutational cold-spots, and there is evidence that some CNEs play a role in the regulation of development. Here, we quantify negative and positive selection acting in murine CNEs by analyzing within-species nucleotide variation and between-species divergence of CNEs that we identified using a phylogenetically independent comparison. The distribution of fitness effects of new mutations in CNEs, inferred from within-species polymorphism, suggests that CNEs receive a higher number of strongly selected deleterious mutations and many fewer nearly neutral mutations than amino acid sites of protein-coding genes or regulatory elements close to genes. However, we also show that CNEs experience a far higher proportion of adaptive substitutions than any known category of genomic sites in murids. The absolute rate of adaptation of CNEs is similar to that of amino acid sites of proteins. This result suggests that there is widespread adaptation in mammalian conserved noncoding DNA elements, some of which have been implicated in the regulation of crucially important processes, including development.

Inference of mutation parameters and selective constraint in mammalian coding sequences by approximate Bayesian computation.

We develop an inference method that uses approximate Bayesian computation (ABC) to simultaneously estimate mutational parameters and selective constraint on the basis of nucleotide divergence for protein-coding genes between pairs of species. Our simulations explicitly model CpG hypermutability and transition vs. transversion mutational biases along with negative and positive selection operating on synonymous and nonsynonymous sites. We evaluate the method by simulations in which true mean parameter values are known and show that it produces reasonably unbiased parameter estimates as long as sequences are not too short and sequence divergence is not too low. We show that the use of quadratic regression within ABC offers an improvement over linear regression, but that weighted regression has little impact on the efficiency of the procedure. We apply the method to estimate mutational and selective constraint parameters in data sets of protein-coding genes extracted from the genome sequences of primates, murids, and carnivores. Estimates of CpG hypermutability are substantially higher in primates than murids and carnivores. Nonsynonymous site selective constraint is substantially higher in murids and carnivores than primates, and autosomal nonsynonymous constraint is higher than X-chromsome constraint in all taxa. We detect significant selective constraint at synonymous sites in primates, carnivores, and murid rodents. Synonymous site selective constraint is weakest in murids, a surprising result, considering that murid effective population sizes are likely to be considerably higher than the other two taxa.

Positive and negative selection on noncoding DNA close to protein-coding genes in wild house mice.

During the past two decades, evidence has accumulated of adaptive evolution within protein-coding genes in a variety of species. However, with the exception of Drosophila and humans, little is known about the extent of adaptive evolution in noncoding DNA. Here, we study regions upstream and downstream of protein-coding genes in the house mouse Mus musculus castaneus, a species that has a much larger effective population size (N(e)) than humans. We analyze polymorphism data for 78 genes from 15 wild-caught M. m. castaneus individuals and divergence to a closely related species, Mus famulus. We find high levels of nucleotide diversity and moderate levels of selective constraint in upstream and downstream regions compared with nonsynonymous sites of protein-coding genes. From the polymorphism data, we estimate the distribution of fitness effects (DFE) of new mutations and infer that most new mutations in upstream and downstream regions behave as effectively neutral and that only a small fraction is strongly negatively selected. We also estimate the fraction of substitutions that have been driven to fixation by positive selection (α) and the ratio of adaptive to neutral divergence (ω(α)). We find that α for upstream and downstream regions (∼ 10%) is much lower than α for nonsynonymous sites (∼ 50%). However, ω(α) estimates are very similar for nonsynonymous sites (∼ 10%) and upstream and downstream regions (∼ 5%). We conclude that negative selection operating in upstream and downstream regions of M. m. castaneus is weak and that the low values of α for upstream and downstream regions relative to nonsynonymous sites are most likely due to the presence of a higher proportion of neutrally evolving sites and not due to lower absolute rates of adaptive substitution.

Evidence for pervasive adaptive protein evolution in wild mice.

The relative contributions of neutral and adaptive substitutions to molecular evolution has been one of the most controversial issues in evolutionary biology for more than 40 years. The analysis of within-species nucleotide polymorphism and between-species divergence data supports a widespread role for adaptive protein evolution in certain taxa. For example, estimates of the proportion of adaptive amino acid substitutions (alpha) are 50% or more in enteric bacteria and Drosophila. In contrast, recent estimates of alpha for hominids have been at most 13%. Here, we estimate alpha for protein sequences of murid rodents based on nucleotide polymorphism data from multiple genes in a population of the house mouse subspecies Mus musculus castaneus, which inhabits the ancestral range of the Mus species complex and nucleotide divergence between M. m. castaneus and M. famulus or the rat. We estimate that 57% of amino acid substitutions in murids have been driven by positive selection. Hominids, therefore, are exceptional in having low apparent levels of adaptive protein evolution. The high frequency of adaptive amino acid substitutions in wild mice is consistent with their large effective population size, leading to effective natural selection at the molecular level. Effective natural selection also manifests itself as a paucity of effectively neutral nonsynonymous mutations in M. m. castaneus compared to humans.

Distributions of selectively constrained sites and deleterious mutation rates in the hominid and murid genomes.

Protein-coding sequences make up only about 1% of the mammalian genome. Much of the remaining 99% has been long assumed to be junk DNA, with little or no functional significance. Here, we show that in hominids, a group with historically low effective population sizes, all classes of noncoding DNA evolve more slowly than ancestral transposable elements and so appear to be subject to significant evolutionary constraints. Under the nearly neutral theory, we expected to see lower levels of selective constraints on most sequence types in hominids than murids, a group that is thought to have a higher effective population size. We found that this is the case for many sequence types examined, the most extreme example being 5'UTRs, for which constraint in hominids is only about one-third that of murids. Surprisingly, however, we observed higher constraints for some sequence types in hominids, notably 4-fold sites, where constraint is more than twice as high as in murids. This implies that more than about one-fifth of mutations at 4-fold sites are effectively selected against in hominids. The higher constraint at 4-fold sites in hominids suggests a more complex protein-coding gene structure than murids and indicates that methods for detecting selection on protein-coding sequences (e.g., using the d(N)/d(S) ratio), with 4-fold sites as a neutral standard, may lead to biased estimates, particularly in hominids. Our constraint estimates imply that 5.4% of nucleotide sites in the human genome are subject to effective negative selection and that there are three times as many constrained sites within noncoding sequences as within protein-coding sequences. Including coding and noncoding sites, we estimate that the genomic deleterious mutation rate U = 4.2. The mutational load predicted under a multiplicative model is therefore about 99% in hominids.

Patterns of DNA-sequence divergence between Drosophila miranda and D. pseudoobscura.

Contrary to the classical view, a large amount of non-coding DNA seems to be selectively constrained in Drosophila and other species. Here, using Drosophila miranda BAC sequences and the Drosophila pseudoobscura genome sequence, we aligned coding and non-coding sequences between D. pseudoobscura and D. miranda, and investigated their patterns of evolution. We found two patterns that have previously been observed in comparisons between Drosophila melanogaster and its relatives. First, there is a negative correlation between intron divergence and intron length, suggesting that longer non-coding sequences may contain more regulatory elements than shorter sequences. Our other main finding is a negative correlation between the rate of non-synonymous substitutions (d(N)) and codon usage bias (F(op)), showing that fast-evolving genes have a lower codon usage bias, consistent with strong positive selection interfering with weak selection for codon usage.