The genomic distribution and local context of coincident SNPs in human and chimpanzee

Comparative Investigation of Coincident Single Nucleotide Polymorphisms Underlying Avian Influenza Viruses in Chickens and Ducks

Avian influenza is a severe viral infection that has the potential to cause human pandemics. In particular, chickens are susceptible to many highly pathogenic strains of the virus, resulting in significant losses. In contrast, ducks have been reported to exhibit rapid and effective innate immune responses to most avian influenza virus (AIV) infections. To explore the distinct genetic programs that potentially distinguish the susceptibility/resistance of both species to AIV, the investigation of coincident SNPs (coSNPs) and their differing causal effects on gene functions in both species is important to gain novel insight into the varying immune-related responses of chickens and ducks. By conducting a pairwise genome alignment between these species, we identified coSNPs and their respective effect on AIV-related differentially expressed genes (DEGs) in this study. The examination of these genes (e.g., CD74, RUBCN, and SHTN1 for chickens and ABCA3, MAP2K6, and VIPR2 for ducks) reveals their high relevance to AIV. Further analysis of these genes provides promising effector molecules (such as IκBα, STAT1/STAT3, GSK-3β, or p53) and related key signaling pathways (such as NF-κB, JAK/STAT, or Wnt) to elucidate the complex mechanisms of immune responses to AIV infections in both chickens and ducks.

Mutation bias reflects natural selection in Arabidopsis thaliana

Since the first half of the twentieth century, evolutionary theory has been dominated by the idea that mutations occur randomly with respect to their consequences1. Here we test this assumption with large surveys of de novo mutations in the plant Arabidopsis thaliana. In contrast to expectations, we find that mutations occur less often in functionally constrained regions of the genome-mutation frequency is reduced by half inside gene bodies and by two-thirds in essential genes. With independent genomic mutation datasets, including from the largest Arabidopsis mutation accumulation experiment conducted to date, we demonstrate that epigenomic and physical features explain over 90% of variance in the genome-wide pattern of mutation bias surrounding genes. Observed mutation frequencies around genes in turn accurately predict patterns of genetic polymorphisms in natural Arabidopsis accessions (r = 0.96). That mutation bias is the primary force behind patterns of sequence evolution around genes in natural accessions is supported by analyses of allele frequencies. Finally, we find that genes subject to stronger purifying selection have a lower mutation rate. We conclude that epigenome-associated mutation bias2 reduces the occurrence of deleterious mutations in Arabidopsis, challenging the prevailing paradigm that mutation is a directionless force in evolution.

Passenger hotspot mutations in cancer driven by APOBEC3A and mesoscale genomic features

Cancer drivers require statistical modeling to distinguish them from passenger events, which accumulate during tumorigenesis but provide no fitness advantage to cancer cells. The discovery of driver genes and mutations relies on the assumption that exact positional recurrence is unlikely by chance; thus, the precise sharing of mutations across patients identifies drivers. Examining the mutation landscape in cancer genomes, we found that many recurrent cancer mutations previously designated as drivers are likely passengers. Our integrated bioinformatic and biochemical analyses revealed that these passenger hotspot mutations arise from the preference of APOBEC3A, a cytidine deaminase, for DNA stem-loops. Conversely, recurrent APOBEC-signature mutations not in stem-loops are enriched in well-characterized driver genes and may predict new drivers. This demonstrates that mesoscale genomic features need to be integrated into computational models aimed at identifying mutations linked to diseases.

A new heterozygous compound mutation in the CTSA gene in galactosialidosis

Galactosialidosis is an autosomal recessive lysosomal storage disease caused by the combined deficiency of lysosomal β-galactosidase and neuraminidase due to a defect in the protective protein/cathepsin A. Patients present with various clinical manifestations and are classified into three types according to the age of onset: the early infantile type, the late infantile type, and the juvenile/adult type. We report a Japanese female case of juvenile/adult type galactosialidosis. Clinically, she presented with short stature, coarse facies, angiokeratoma, remarkable action myoclonus, and cerebellar ataxia. The patient was diagnosed with galactosialidosis with confirmation of impaired β-galactosidase and neuraminidase function in cultured skin fibroblasts. Sanger sequencing for CTSA identified a compound heterozygous mutation consisting of NM_00308.3(CTSA):c.746 + 3A>G and c.655-1G>A. Additional analysis of her mother’s DNA sequence indicated that the former mutation originated from her mother, and therefore the latter was estimated to be from the father or was a de novo mutation. Both mutations are considered pathogenic owing to possible splicing abnormalities. One of them (c.655-1G>A) is novel because it has never been reported previously.

ShRangeSim: Simulation of Single Nucleotide Polymorphism Clusters in Next-Generation Sequencing Data

Genomic variations are in the focus of research to uncover mechanisms of host-pathogen interactions and diseases such as cancer. Nowadays, next-generation sequencing (NGS) data are analyzed through dedicated pipelines to detect them. Surrogate NGS data in conjunction with genomic variations help to evaluate pipelines and validate their outcomes, fostering selection of proper tools for a given scientific question. I describe how existing approaches for simulating NGS data in conjunction with genomic variations fail to model local enrichments of single nucleotide polymorphisms (SNPs), so called SNP clusters. Two distributions for count data are applied to publicly available collections of genomic variations. The results suggest modeling of SNP cluster sizes by overdispersion-aware distributions.

Purifying selection shapes the coincident SNP distribution of primate coding sequences

Genome-wide analysis has observed an excess of coincident single nucleotide polymorphisms (coSNPs) at human-chimpanzee orthologous positions, and suggested that this is due to cryptic variation in the mutation rate. While this phenomenon primarily corresponds with non-coding coSNPs, the situation in coding sequences remains unclear. Here we calculate the observed-to-expected ratio of coSNPs (coSNP_O/E) to estimate the prevalence of human-chimpanzee coSNPs, and show that the excess of coSNPs is also present in coding regions. Intriguingly, coSNP_O/E is much higher at zero-fold than at nonzero-fold degenerate sites; such a difference is due to an elevation of coSNP_O/E at zero-fold degenerate sites, rather than a reduction at nonzero-fold degenerate ones. These trends are independent of chimpanzee subpopulation, population size, or sequencing techniques; and hold in broad generality across primates. We find that this discrepancy cannot fully explained by sequence contexts, shared ancestral polymorphisms, SNP density, and recombination rate, and that coSNP_O/E in coding sequences is significantly influenced by purifying selection. We also show that selection and mutation rate affect coSNP_O/E independently, and coSNPs tend to be less damaging and more correlated with human diseases than non-coSNPs. These suggest that coSNPs may represent a “signature” during primate protein evolution.

Concurrent nucleotide substitution mutations in the human genome are characterized by a significantly decreased transition/transversion ratio

There is accumulating evidence that the number of multiple-nucleotide substitutions (MNS) occurring in closely spaced sites in eukaryotic genomes is significantly higher than would be predicted from the random accumulation of independently generated single-nucleotide substitutions (SNS). Although this excess can in principle be accounted for by the concept of transient hypermutability, a general mutational signature of concurrent MNS mutations has not so far been evident. Employing a dataset (N = 449) of "concurrent" double MNS mutations causing human inherited disease, we have identified just such a mutational signature: concurrently generated double MNS mutations exhibit a >twofold lower transition/transversion ratio (termed RTs/Tv ) than independently generated de novo SNS mutations (<0.80 vs. 2.10; P = 2.69 × 10(-14) ). We replicated this novel finding through a similar analysis employing two double MNS variant datasets with differing abundances of concurrent events (150,521 variants with both substitutions on the same haplotypic lineage vs. 94,875 variants whose component substitutions were on different haplotypic lineages) plus 5,430,874 SNS variants, all being derived from the whole-genome sequencing of seven Chinese individuals. Evaluation of the newly observed mutational signature in diverse contexts provides solid support for the postulated role of translesion synthesis DNA polymerases in transient hypermutability.

SNP Formation Bias in the Murine Genome Provides Evidence for Parallel Evolution

In this study, we show novel DNA motifs that promote single nucleotide polymorphism (SNP) formation and are conserved among exons, introns, and intergenic DNA from mice (Sanger Mouse Genomes Project), human genes (1000 Genomes), and tumor-specific somatic mutations (data from TCGA). We further characterize SNPs likely to be very recent in origin (i.e., formed in otherwise congenic mice) and show enrichment for both synonymous and parallel DNA variants occurring under circumstances not attributable to purifying selection. The findings provide insight regarding SNP contextual bias and eukaryotic codon usage as strategies that favor long-term exonic stability. The study also furnishes new information concerning rates of murine genomic evolution and features of DNA mutagenesis (at the time of SNP formation) that should be viewed as "adaptive."

Genotype-Frequency Estimation from High-Throughput Sequencing Data

Rapidly improving high-throughput sequencing technologies provide unprecedented opportunities for carrying out population-genomic studies with various organisms. To take full advantage of these methods, it is essential to correctly estimate allele and genotype frequencies, and here we present a maximum-likelihood method that accomplishes these tasks. The proposed method fully accounts for uncertainties resulting from sequencing errors and biparental chromosome sampling and yields essentially unbiased estimates with minimal sampling variances with moderately high depths of coverage regardless of a mating system and structure of the population. Moreover, we have developed statistical tests for examining the significance of polymorphisms and their genotypic deviations from Hardy-Weinberg equilibrium. We examine the performance of the proposed method by computer simulations and apply it to low-coverage human data generated by high-throughput sequencing. The results show that the proposed method improves our ability to carry out population-genomic analyses in important ways. The software package of the proposed method is freely available from https://github.com/Takahiro-Maruki/Package-GFE.

Long-Term Balancing Selection in LAD1 Maintains a Missense Trans-Species Polymorphism in Humans, Chimpanzees, and Bonobos

Balancing selection maintains advantageous genetic and phenotypic diversity in populations. When selection acts for long evolutionary periods selected polymorphisms may survive species splits and segregate in present-day populations of different species. Here, we investigate the role of long-term balancing selection in the evolution of protein-coding sequences in the Homo-Pan clade. We sequenced the exome of 20 humans, 20 chimpanzees, and 20 bonobos and detected eight coding trans-species polymorphisms (trSNPs) that are shared among the three species and have segregated for approximately 14 My of independent evolution. Although the majority of these trSNPs were found in three genes of the major histocompatibility locus cluster, we also uncovered one coding trSNP (rs12088790) in the gene LAD1. All these trSNPs show clustering of sequences by allele rather than by species and also exhibit other signatures of long-term balancing selection, such as segregating at intermediate frequency and lying in a locus with high genetic diversity. Here, we focus on the trSNP in LAD1, a gene that encodes for Ladinin-1, a collagenous anchoring filament protein of basement membrane that is responsible for maintaining cohesion at the dermal-epidermal junction; the gene is also an autoantigen responsible for linear IgA disease. This trSNP results in a missense change (Leucine257Proline) and, besides altering the protein sequence, is associated with changes in gene expression of LAD1.

Longevity and plasticity of CFTR provide an argument for noncanonical SNP organization in hominid DNA

Like many other ancient genes, the cystic fibrosis transmembrane conductance regulator (CFTR) has survived for hundreds of millions of years. In this report, we consider whether such prodigious longevity of an individual gene – as opposed to an entire genome or species – should be considered surprising in the face of eons of relentless DNA replication errors, mutagenesis, and other causes of sequence polymorphism. The conventions that modern human SNP patterns result either from purifying selection or random (neutral) drift were not well supported, since extant models account rather poorly for the known plasticity and function (or the established SNP distributions) found in a multitude of genes such as CFTR. Instead, our analysis can be taken as a polemic indicating that SNPs in CFTR and many other mammalian genes may have been generated—and continue to accrue—in a fundamentally more organized manner than would otherwise have been expected. The resulting viewpoint contradicts earlier claims of ‘directional’ or ‘intelligent design-type’ SNP formation, and has important implications regarding the pace of DNA adaptation, the genesis of conserved non-coding DNA, and the extent to which eukaryotic SNP formation should be viewed as adaptive.

Nonhuman primate models in the genomic era: a paradigm shift

Because of their strong similarities to humans across physiologic, developmental, behavioral, immunologic, and genetic levels, nonhuman primates are essential models for a wide spectrum of biomedical research. But unlike other animal models, nonhuman primates possess substantial outbred genetic variation, reducing statistical power and potentially confounding interpretation of results in research studies. Although unknown genetic variation is a hindrance in studies that allocate animals randomly, taking genetic variation into account in study design affords an opportunity to transform the way that nonhuman primates are used in biomedical research. New understandings of how the function of individual genes in rhesus macaques mimics that seen in humans are greatly advancing the rhesus macaques utility as research models, but epistatic interaction, epigenetic regulatory mechanisms, and the intricacies of gene networks limit model development. We are now entering a new era of nonhuman primate research, brought on by the proliferation and rapid expansion of genomic data. Already the cost of a rhesus macaque genome is dwarfed by its purchase and husbandry costs, and complete genomic datasets will inevitably encompass each rhesus macaque used in biomedical research. Advancing this outcome is paramount. It represents an opportunity to transform the way animals are assigned and used in biomedical research and to develop new models of human disease. The genetic and genomic revolution brings with it a paradigm shift for nonhuman primates and new mandates on how nonhuman primates are used in biomedical research.

Genome-wide inference of ancestral recombination graphs

The complex correlation structure of a collection of orthologous DNA sequences is uniquely captured by the "ancestral recombination graph" (ARG), a complete record of coalescence and recombination events in the history of the sample. However, existing methods for ARG inference are computationally intensive, highly approximate, or limited to small numbers of sequences, and, as a consequence, explicit ARG inference is rarely used in applied population genomics. Here, we introduce a new algorithm for ARG inference that is efficient enough to apply to dozens of complete mammalian genomes. The key idea of our approach is to sample an ARG of [Formula: see text] chromosomes conditional on an ARG of [Formula: see text] chromosomes, an operation we call "threading." Using techniques based on hidden Markov models, we can perform this threading operation exactly, up to the assumptions of the sequentially Markov coalescent and a discretization of time. An extension allows for threading of subtrees instead of individual sequences. Repeated application of these threading operations results in highly efficient Markov chain Monte Carlo samplers for ARGs. We have implemented these methods in a computer program called ARGweaver. Experiments with simulated data indicate that ARGweaver converges rapidly to the posterior distribution over ARGs and is effective in recovering various features of the ARG for dozens of sequences generated under realistic parameters for human populations. In applications of ARGweaver to 54 human genome sequences from Complete Genomics, we find clear signatures of natural selection, including regions of unusually ancient ancestry associated with balancing selection and reductions in allele age in sites under directional selection. The patterns we observe near protein-coding genes are consistent with a primary influence from background selection rather than hitchhiking, although we cannot rule out a contribution from recurrent selective sweeps.

Interaction-based evolution: how natural selection and nonrandom mutation work together

BACKGROUND

The modern evolutionary synthesis leaves unresolved some of the most fundamental, long-standing questions in evolutionary biology: What is the role of sex in evolution? How does complex adaptation evolve? How can selection operate effectively on genetic interactions? More recently, the molecular biology and genomics revolutions have raised a host of critical new questions, through empirical findings that the modern synthesis fails to explain: for example, the discovery of de novo genes; the immense constructive role of transposable elements in evolution; genetic variance and biochemical activity that go far beyond what traditional natural selection can maintain; perplexing cases of molecular parallelism; and more.

PRESENTATION OF THE HYPOTHESIS

Here I address these questions from a unified perspective, by means of a new mechanistic view of evolution that offers a novel connection between selection on the phenotype and genetic evolutionary change (while relying, like the traditional theory, on natural selection as the only source of feedback on the fit between an organism and its environment). I hypothesize that the mutation that is of relevance for the evolution of complex adaptation-while not Lamarckian, or "directed" to increase fitness-is not random, but is instead the outcome of a complex and continually evolving biological process that combines information from multiple loci into one. This allows selection on a fleeting combination of interacting alleles at different loci to have a hereditary effect according to the combination's fitness.

TESTING AND IMPLICATIONS OF THE HYPOTHESIS

This proposed mechanism addresses the problem of how beneficial genetic interactions can evolve under selection, and also offers an intuitive explanation for the role of sex in evolution, which focuses on sex as the generator of genetic combinations. Importantly, it also implies that genetic variation that has appeared neutral through the lens of traditional theory can actually experience selection on interactions and thus has a much greater adaptive potential than previously considered. Empirical evidence for the proposed mechanism from both molecular evolution and evolution at the organismal level is discussed, and multiple predictions are offered by which it may be tested.

REVIEWERS

This article was reviewed by Nigel Goldenfeld (nominated by Eugene V. Koonin), Jürgen Brosius and W. Ford Doolittle.

Galactosialidosis: review and analysis of CTSA gene mutations

Background

Mutations in the CTSA gene, that encodes the protective protein/cathepsin A or PPCA, lead to the secondary deficiency of β-galactosidase (GLB1) and neuraminidase 1 (NEU1), causing the lysosomal storage disorder galactosialidosis (GS). Few clinical cases of GS have been reported in the literature, the majority of them belonging to the juvenile/adult group of patients.

Methods

The correct nomenclature of mutations for this gene is discussed through the analysis of the three PPCA/CTSA isoforms available in the GenBank database. Phenotype-genotype correlation has been assessed by computational analysis and review of previously reported single amino acid substitutions.

Results

We report the clinical and mutational analyses of four cases with the rare infantile form of GS. We identified three novel nucleotide changes, two of them resulting in the missense mutations, c.347A>G (p.His116Arg), c.775T>C (p.Cys259Arg), and the third, c.1216C>T, resulting in the p.Gln406* stop codon, a type of mutation identified for the first time in GS. An Italian founder effect of the c.114delG mutation can be suggested according to the origin of the only three patients carrying this mutation reported here and in the literature.

Conclusions

In early reports mutations nomenclature was selected according to all CTSA isoforms (three different isoforms), thus generating a lot of confusion. In order to assist physicians in the interpretation of detected mutations, we mark the correct nomenclature for CTSA mutations. The complexity of pathology caused by the multifunctions of CTSA, and the very low numbers of mutations (only 23 overall) in relation to the length of the CTSA gene are discussed.

In addition, the in silico functional predictions of all reported missense mutations allowed us to closely predict the early infantile, late infantile and juvenile phenotypes, also disclosing different degrees of severity in the juvenile phenotype.

Origins of shared genetic variation in African cichlids

Cichlid fishes have evolved tremendous morphological and behavioral diversity in the waters of East Africa. Within each of the Great Lakes Tanganyika, Malawi, and Victoria, the phenomena of hybridization and retention of ancestral polymorphism explain allele sharing across species. Here, we explore the sharing of single nucleotide polymorphisms (SNPs) between the major East African cichlid assemblages. A set of approximately 200 genic and nongenic SNPs was ascertained in five Lake Malawi species and genotyped in a diverse collection of ∼160 species from across Africa. We observed segregating polymorphism outside of the Malawi lineage for more than 50% of these loci; this holds similarly for genic versus nongenic SNPs, as well as for SNPs at putative CpG versus non-CpG sites. Bayesian and principal component analyses of genetic structure in the data demonstrate that the Lake Malawi endemic flock is not monophyletic and that river species have likely contributed significantly to Malawi genomes. Coalescent simulations support the hypothesis that river cichlids have transported polymorphism between lake assemblages. We observed strong genetic differentiation between Malawi lineages for approximately 8% of loci, with contributions from both genic and nongenic SNPs. Notably, more than half of these outlier loci between Malawi groups are polymorphic outside of the lake. Cichlid fishes have evolved diversity in Lake Malawi as new mutations combined with standing genetic variation shared across East Africa.

Lack of genomic imprinting of DNA primase, polypeptide 2 (PRIM2) in human term placenta and white blood cells

PRIM2, encoding a subunit of primase involved in DNA replication and transcription, is expressed in the placenta and is crucial for mammalian development and growth. Its role in placental function is not well understood. Recently, PRIM2 was reported as imprinted in human white blood cells (WBC). We report here our failure to confirm imprinting of the PRIM2 locus in human placenta or WBC. The discordance between our results and those of others are likely due to an incorrectly annotated PRIM2 pseudogene found in the human genome database.

Paternal age effect mutations and selfish spermatogonial selection: causes and consequences for human disease

Advanced paternal age has been associated with an increased risk for spontaneous congenital disorders and common complex diseases (such as some cancers, schizophrenia, and autism), but the mechanisms that mediate this effect have been poorly understood. A small group of disorders, including Apert syndrome (caused by FGFR2 mutations), achondroplasia, and thanatophoric dysplasia (FGFR3), and Costello syndrome (HRAS), which we collectively term "paternal age effect" (PAE) disorders, provides a good model to study the biological and molecular basis of this phenomenon. Recent evidence from direct quantification of PAE mutations in sperm and testes suggests that the common factor in the paternal age effect lies in the dysregulation of spermatogonial cell behavior, an effect mediated molecularly through the growth factor receptor-RAS signal transduction pathway. The data show that PAE mutations, although arising rarely, are positively selected and expand clonally in normal testes through a process akin to oncogenesis. This clonal expansion, which is likely to take place in the testes of all men, leads to the relative enrichment of mutant sperm over time-explaining the observed paternal age effect associated with these disorders-and in rare cases to the formation of testicular tumors. As regulation of RAS and other mediators of cellular proliferation and survival is important in many different biological contexts, for example during tumorigenesis, organ homeostasis and neurogenesis, the consequences of selfish mutations that hijack this process within the testis are likely to extend far beyond congenital skeletal disorders to include complex diseases, such as neurocognitive disorders and cancer predisposition.

Long-term balancing selection at the antiviral gene OAS1 in Central African chimpanzees

Oligoadenylate synthetases (OAS) are interferon-induced enzymes that participate in the first line of defense against a wide range of viral infection in animals. Upon activation by viral double-stranded RNA, OAS synthesizes (2-5) oligoadenylates, which activate RNase L, leading to the nonspecific degradation of cellular and viral RNA. Some association studies in humans suggest that variation at one of the OAS genes, OAS1, could be influencing host susceptibility to viral infection. We assessed the diversity of OAS1 in hominoid primates with a focus on chimpanzees. We found that the OAS1 gene is extremely polymorphic in Central African chimpanzee and exhibits levels of silent and replacement diversity much higher than neutral regions of the chimpanzee genome. This level of variation strongly suggests that balancing selection is acting on OAS1, and indeed, this conclusion was validated by several tests of neutrality. We further demonstrated that balancing selection has been acting at this locus since the split between chimpanzees, humans, and gorillas (~8.6 Ma) and caused the persistence of two deeply divergent allelic lineages in Central African chimpanzees. These two groups of OAS1 alleles differ by a large number of amino acids (a.a.), including several a.a. putatively involved in RNA binding. It is therefore very likely that variation at the OAS1 locus affects the innate immune response of individuals to specific viral infection. Our data strongly suggest that interactions between viral RNA and OAS1 are responsible for the maintenance of ancestral polymorphisms at this locus for at least 13.2 My.

Variation in the mutation rate across mammalian genomes

It has been known for many years that the mutation rate varies across the genome. However, only with the advent of large genomic data sets is the full extent of this variation becoming apparent. The mutation rate varies over many different scales, from adjacent sites to whole chromosomes, with the strongest variation seen at the smallest scales. Some of these patterns have clear mechanistic bases, but much of the rate variation remains unexplained, and some of it is deeply perplexing. Variation in the mutation rate has important implications in evolutionary biology and underexplored implications for our understanding of hereditary disease and cancer.

Mutation rate distribution inferred from coincident SNPs and coincident substitutions

Mutation rate variation has the potential to bias evolutionary inference, particularly when rates become much higher than the mean. We first confirm prior work that inferred the existence of cryptic, site-specific rate variation on the basis of coincident polymorphisms—sites that are segregating in both humans and chimpanzees. Then we extend this observation to a longer evolutionary timescale by identifying sites of coincident substitutions using four species. From these data, we develop analytic theory to infer the variance and skewness of the distribution of mutation rates. Even excluding CpG dinucleotides, we find a relatively large coefficient of variation and positive skew, which suggests that, although most sites in the genome have mutation rates near the mean, the distribution contains a long right-hand tail with a small number of sites having high mutation rates. At least for primates, these quickly mutating sites are few enough that the infinite sites model in population genetics remains appropriate.