High genomic deleterious mutation rates in hominids

Genetic etiology of truncus arteriosus excluding 22q11.2 deletion syndrome and identification of c.1617del, a prevalent variant in TMEM260, in the Japanese population

Truncus Arteriosus (TA) is a congenital heart disease characterized by a single common blood vessel emerging from the right and left ventricles instead of the main pulmonary artery and aorta. TA accounts for 4% of all critical congenital heart diseases. The most common cause of TA is 22q11.2 deletion syndrome, accounting for 12-35% of all TA cases. However, no major causes of TA other than 22q11.2 deletion have been reported. We performed whole-genome sequencing of 11 Japanese patients having TA without 22q11.2 deletion. Among five patients, we identified pathogenic variants in TMEM260; the biallelic loss-of-function variants of which have recently been associated with structural heart defects and renal anomalies syndrome (SHDRA). In one patient, we identified a de novo pathogenic variant in GATA6, and in another patient, we identified a de novo probably pathogenic variant in NOTCH1. Notably, we identified a prevalent variant in TMEM260 (ENST00000261556.6), c.1617del (p.Trp539Cysfs*9), in 8/22 alleles among the 11 patients. The c.1617del variant was estimated to occur approximately 23 kiloyears ago. Based on the allele frequency of the c.1617del variant in the Japanese population (0.36%), approximately 26% of Japanese patients afflicted with TA could harbor homozygous c.1617del variants. This study highlights TMEM260, especially c.1617del, as a major genetic cause of TA in the Japanese population.

High frequency of transition to transversion ratio in the stem region of RNA secondary structure of untranslated region of SARS-CoV-2

Introduction

The propensity of nucleotide bases to form pairs, causes folding and the formation of secondary structure in the RNA. Therefore, purine (R): pyrimidine (Y) base-pairing is vital to maintain uniform lateral dimension in RNA secondary structure. Transversions or base substitutions between R and Y bases, are more detrimental to the stability of RNA secondary structure, than transitions derived from substitutions between A and G or C and T. The study of transversion and transition base substitutions is important to understand evolutionary mechanisms of RNA secondary structure in the 5'  and 3'  untranslated (UTR) regions of SARS-CoV-2. In this work, we carried out comparative analysis of transition and transversion base substitutions in the stem and loop regions of RNA secondary structure of SARS-CoV-2.

Methods

We have considered the experimentally determined and well documented stem and loop regions of 5' and 3' UTR regions of SARS-CoV-2 for base substitution analysis. The secondary structure comprising of stem and loop regions were visualized using the RNAfold web server. The GISAID repository was used to extract base sequence alignment of the UTR regions. Python scripts were developed for comparative analysis of transversion and transition frequencies in the stem and the loop regions.

Results

The results of base substitution analysis revealed a higher transition (ti) to transversion (tv) ratio (ti/tv) in the stem region of UTR of RNA secondary structure of SARS-CoV-2 reported during the early stage of the pandemic. The higher ti/tv ratio in the stem region suggested the influence of secondary structure in selecting the pattern of base substitutions. This differential pattern of ti/tv values between stem and loop regions was not observed among the Delta and Omicron variants that dominated the later stage of the pandemic. It is noteworthy that the ti/tv values in the stem and loop regions were similar among the later dominant Delta and Omicron variant strains which is to be investigated to understand the rapid evolution and global adaptation of SARS-CoV-2.

Conclusion

Our findings implicate the lower frequency of transversions than the transitions in the stem regions of UTRs of SARS-CoV-2. The RNA secondary structures are associated with replication, translation, and packaging, further investigations are needed to understand these base substitutions across different variants of SARS-CoV-2.

Influence of the mutation load on the genomic composition of hybrids between outcrossing and self-fertilizing species

Hybridization is a natural process whereby two diverging evolutionary lineages reproduce and create offspring of mixed ancestry. Differences in mating systems (e.g., self-fertilization and outcrossing) are expected to affect the direction and extent of hybridization and introgression in hybrid zones. Among other factors, selfers and outcrossers are expected to differ in their mutation loads. This has been studied both theoretically and empirically; however, conflicting predictions have been made on the effects mutation loads of parental species with different mating systems can have on the genomic composition of hybrids. Here, we develop a multi-locus, selective model to study how the different mutation load built up in selfers and outcrossers as a result of selective interference and homozygosity impact the long-term genetic composition of hybrid populations. Notably, our results emphasize that genes from the parental population with lesser mutation load get rapidly overrepresented in hybrid genomes, regardless of the hybrids own mating system. When recombination tends to be more important than mutation, outcrossers' genomes tend to be of higher quality and prevail. When recombination rates are low, however, selfers' genomes may reach higher quality than outcrossers' genomes and prevail in the hybrids. Taken together, these results provide concrete insights into one of the multiple factors influencing hybrid genome ancestry and introgression patterns in hybrid zones containing species with different mating systems.

Genome-wide prediction of disease variant effects with a deep protein language model

Predicting the effects of coding variants is a major challenge. While recent deep-learning models have improved variant effect prediction accuracy, they cannot analyze all coding variants due to dependency on close homologs or software limitations. Here we developed a workflow using ESM1b, a 650-million-parameter protein language model, to predict all ~450 million possible missense variant effects in the human genome, and made all predictions available on a web portal. ESM1b outperformed existing methods in classifying ~150,000 ClinVar/HGMD missense variants as pathogenic or benign and predicting measurements across 28 deep mutational scan datasets. We further annotated ~2 million variants as damaging only in specific protein isoforms, demonstrating the importance of considering all isoforms when predicting variant effects. Our approach also generalizes to more complex coding variants such as in-frame indels and stop-gains. Together, these results establish protein language models as an effective, accurate and general approach to predicting variant effects.

Deleterious mutation load in the admixed mice population

Deleterious mutation loads are known to correlate negatively with effective population size (Ne). Due to this reason, previous studies observed a higher proportion of harmful mutations in small populations than that in large populations. However, the mutational load in an admixed population that derived from introgression between individuals from two populations with vastly different Ne is not known. We investigated this using the whole genome data from two subspecies of the mouse (Mus musculus castaneus and Mus musculus musculus) with significantly different Ne. We used the ratio of diversities at nonsynonymous and synonymous sites (dN/dS) to measure the harmful mutation load. Our results showed that this ratio observed for the admixed population was intermediate between those of the parental populations. The dN/dS ratio of the hybrid population was significantly higher than that of M. m. castaneus but lower than that of M. m. musculus. Our analysis revealed a significant positive correlation between the proportion of M. m. musculus ancestry in admixed individuals and their dN/dS ratio. This suggests that the admixed individuals with high proportions of M. m. musculus ancestry have large dN/dS ratios. We also used the proportion of deleterious nonsynonymous SNVs as a proxy for deleterious mutation load, which also produced similar results. The observed results were in concordance with those expected by theory. We also show a shift in the distribution of fitness effects of nonsynonymous SNVs in the admixed genomes compared to the parental populations. These findings suggest that the deleterious mutation load of the admixed population is determined by the proportion of the ancestries of the subspecies. Therefore, it is important to consider the status and the level of genetic admixture of the populations whilst estimating the mutation loads.

Diffusion approximations in population genetics and the rate of Muller's ratchet

The Wright-Fisher binomial model of allele frequency change is often approximated by a scaling limit in which selection, mutation and drift all decrease at the same 1/N rate. This construction restricts the applicability of the resulting 'Wright-Fisher diffusion equation' to the weak selection, weak mutation regime of evolution. We argue that diffusion approximations of the Wright-Fisher model can be used more generally, for instance in cases where genetic drift is much weaker than selection. One important example of this regime is Muller's ratchet phenomenon, whereby deleterious mutations slowly but irreversibly accumulate through rare stochastic fluctuations. Using a modified diffusion equation we derive improved analytical estimates for the mean click time of the ratchet.

Extreme purifying selection against point mutations in the human genome

Large-scale genome sequencing has enabled the measurement of strong purifying selection in protein-coding genes. Here we describe a new method, called ExtRaINSIGHT, for measuring such selection in noncoding as well as coding regions of the human genome. ExtRaINSIGHT estimates the prevalence of “ultraselection” by the fractional depletion of rare single-nucleotide variants, after controlling for variation in mutation rates. Applying ExtRaINSIGHT to 71,702 whole genome sequences from gnomAD v3, we find abundant ultraselection in evolutionarily ancient miRNAs and neuronal protein-coding genes, as well as at splice sites. By contrast, we find much less ultraselection in other noncoding RNAs and transcription factor binding sites, and only modest levels in ultraconserved elements. We estimate that ~0.4–0.7% of the human genome is ultraselected, implying ~ 0.26–0.51 strongly deleterious mutations per generation. Overall, our study sheds new light on the genome-wide distribution of fitness effects by combining deep sequencing data and classical theory from population genetics.

Previous work has investigated selection in the coding genome, but it is not as well characterized in the non-coding genome. By analyzing rare variants in 70k genome sequences from gnomAD, the authors detect very strong purifying selection ("ultraselection”) across the human genome, finding it in some microRNAs and coding sequences but generally rare in regulatory sequences.

Distinct landscapes of deleterious variants in DNA damage repair system in ethnic human populations

Deleterious variants in the DNA damage repair system can cause genome instability and increase cancer risk. The highly ethnic-specific DDR deleterious variation from this study suggests its potential relationship with different disease susceptibility in ethnic human populations.

Deleterious variants in DNA damage repair (DDR) system can cause genome instability and increase cancer risk. In this study, we analyzed the deleterious variants in DDR system in 16 ethnic human populations. From the genetic variants in 169 DDR genes involved in nine DDR pathways collected from 158,612 individuals of different ethnic background, we identified 1,781 deleterious variants in 81 DDR genes in eight DDR pathways (https://genemutation.fhs.um.edu.mo/dbddr-global/). Our analysis showed although the quantity of deleterious variants was loaded at a similar level, the landscape of the variants differed substantially among different populations that two-third of the variants were present in single ethnic populations, and the rest was mostly shared between the populations with closer geographic and genetic relationship. The highly ethnic-specific DDR deleterious variation suggests its potential relationship with different disease susceptibility in ethnic human populations.

The crucial role of genome-wide genetic variation in conservation

The unprecedented rate of extinction calls for efficient use of genetics to help conserve biodiversity. Several recent genomic and simulation-based studies have argued that the field of conservation biology has placed too much focus on conserving genome-wide genetic variation, and that the field should instead focus on managing the subset of functional genetic variation that is thought to affect fitness. Here, we critically evaluate the feasibility and likely benefits of this approach in conservation. We find that population genetics theory and empirical results show that conserving genome-wide genetic variation is generally the best approach to prevent inbreeding depression and loss of adaptive potential from driving populations toward extinction. Focusing conservation efforts on presumably functional genetic variation will only be feasible occasionally, often misleading, and counterproductive when prioritized over genome-wide genetic variation. Given the increasing rate of habitat loss and other environmental changes, failure to recognize the detrimental effects of lost genome-wide genetic variation on long-term population viability will only worsen the biodiversity crisis.

Middle Pleistocene genome calibrates a revised evolutionary history of extinct cave bears

Palaeogenomes provide the potential to study evolutionary processes in real time, but this potential is limited by our ability to recover genetic data over extended timescales.¹ As a consequence, most studies so far have focused on samples of Late Pleistocene or Holocene age, which covers only a small part of the history of many clades and species. Here, we report the recovery of a low coverage palaeogenome from the petrous bone of a ∼360,000 year old cave bear from Kudaro 1 cave in the Caucasus Mountains. Analysis of this genome alongside those of several Late Pleistocene cave bears reveals widespread mito-nuclear discordance in this group. Using the time interval between Middle and Late Pleistocene cave bear genomes, we directly estimate ursid nuclear and mitochondrial substitution rates to calibrate their respective phylogenies. This reveals post-divergence mitochondrial transfer as the dominant factor explaining their mito-nuclear discordance. Interestingly, these transfer events were not accompanied by large-scale nuclear introgression. However, we do detect additional instances of nuclear admixture among other cave bear lineages, and between cave bears and brown bears, which are not associated with mitochondrial exchange. Genomic data obtained from the Middle Pleistocene cave bear petrous bone has thus facilitated a revised evolutionary history of this extinct megafaunal group. Moreover, it suggests that petrous bones may provide a means of extending both the magnitude and time depth of palaeogenome retrieval over substantial portions of the evolutionary histories of many mammalian clades.

Genetic variation in the Mauritian cynomolgus macaque population reflects variation in the human population

The cynomolgus macaque is an important species for preclinical research, however the extent of genetic variation in this population and its similarity to the human population is not well understood. Exome sequencing was conducted for 101 cynomolgus macaques to characterize genetic variation. The variant distribution frequency was 7.81 variants per kilobase across the sequenced regions, with a total of 2,770,009 single nucleotide variants identified from 2,996,041 loci. A large portion (85.6%) had minor allele frequencies greater than 5%. Enriched pathways for genes with high genetic diversity (≥10 variants per kilobase) were those involving signaling peptides and immune response. Compared to human, the variant distribution frequency and nucleotide diversity in the macaque exome was approximately 4 times greater; however the ratio of non-synonymous to synonymous variants was similar (0.735 and 0.831, respectively). Understanding genetic variability in cynomolgus macaques will enable better interpretation and human translation of phenotypic variability in this species.

Phylogenetic Permulations: A Statistically Rigorous Approach to Measure Confidence in Associations in a Phylogenetic Context

Many evolutionary comparative methods seek to identify associations between phenotypic traits or between traits and genotypes, often with the goal of inferring potential functional relationships between them. Comparative genomics methods aimed at this goal measure the association between evolutionary changes at the genetic level with traits evolving convergently across phylogenetic lineages. However, these methods have complex statistical behaviors that are influenced by nontrivial and oftentimes unknown confounding factors. Consequently, using standard statistical analyses in interpreting the outputs of these methods leads to potentially inaccurate conclusions. Here, we introduce phylogenetic permulations, a novel statistical strategy that combines phylogenetic simulations and permutations to calculate accurate, unbiased P values from phylogenetic methods. Permulations construct the null expectation for P values from a given phylogenetic method by empirically generating null phenotypes. Subsequently, empirical P values that capture the true statistical confidence given the correlation structure in the data are directly calculated based on the empirical null expectation. We examine the performance of permulation methods by analyzing both binary and continuous phenotypes, including marine, subterranean, and long-lived large-bodied mammal phenotypes. Our results reveal that permulations improve the statistical power of phylogenetic analyses and correctly calibrate statements of confidence in rejecting complex null distributions while maintaining or improving the enrichment of known functions related to the phenotype. We also find that permulations refine pathway enrichment analyses by correcting for nonindependence in gene ranks. Our results demonstrate that permulations are a powerful tool for improving statistical confidence in the conclusions of phylogenetic analysis when the parametric null is unknown.

The evolutionary genetics of personality

Genetic influences on personality differences are ubiquitous, but their nature is not well understood. A theoretical framework might help, and can be provided by evolutionary genetics. We assess three evolutionary genetic mechanisms that could explain genetic variance in personality differences: selective neutrality, mutation‐selection balance, and balancing selection. Based on evolutionary genetic theory and empirical results from behaviour genetics and personality psychology, we conclude that selective neutrality is largely irrelevant, that mutation‐selection balance seems best at explaining genetic variance in intelligence, and that balancing selection by environmental heterogeneity seems best at explaining genetic variance in personality traits. We propose a general model of heritable personality differences that conceptualises intelligence as fitness components and personality traits as individual reaction norms of genotypes across environments, with different fitness consequences in different environmental niches. We also discuss the place of mental health in the model. This evolutionary genetic framework highlights the role of gene‐environment interactions in the study of personality, yields new insight into the person‐situation‐debate and the structure of personality, and has practical implications for both quantitative and molecular genetic studies of personality. Copyright © 2007 John Wiley & Sons, Ltd.

Chance, Variation and Shared Ancestry: Population Genetics After the Synthesis

Chance has been a focus of attention ever since the beginning of population genetics, but neutrality has not, as natural selection once appeared to be the only worthwhile issue. Neutral change became a major source of interest during the neutralist-selectionist debate, 1970-1980. It retained interest beyond this period for two reasons that contributed to its becoming foundational for evolutionary reasoning. On the one hand, neutral evolution was the first mathematical prediction to emerge from Mendelian inheritance: until then evolution by natural selection was considered the alternative to the fixity of species; now it appears to be the alternative to continuous change. Second, neutral change generated a set of clear predictions on standing variation. These could be used as a reference for detecting more elusive alternative mechanisms of evolution including natural selection. In the wake of the transition from Mendelism to genomics, the combination of coalescent theory, DNA sequence variation, and numerical analysis made it possible to integrate contingent aspects of the history of species into a new null model, thus opening a new dimension in the concept of population that the Modern Synthesis formerly considered as a mere gene pool.

Rare missense variants in the human cytosolic antibody receptor preserve antiviral function

The genetic basis of most human disease cannot be explained by common variants. One solution to this ‘missing heritability problem’ may be rare missense variants, which are individually scarce but collectively abundant. However, the phenotypic impact of rare variants is under-appreciated as gene function is normally studied in the context of a single ‘wild-type’ sequence. Here, we explore the impact of naturally occurring missense variants in the human population on the cytosolic antibody receptor TRIM21, using volunteer cells with variant haplotypes, CRISPR gene editing and functional reconstitution. In combination with data from a panel of computational predictors, the results suggest that protein robustness and purifying selection ensure that function is remarkably well-maintained despite coding variation.

Removal of alleles by genome editing (RAGE) against deleterious load

BACKGROUND

In this paper, we simulate deleterious load in an animal breeding program, and compare the efficiency of genome editing and selection for decreasing it. Deleterious variants can be identified by bioinformatics screening methods that use sequence conservation and biological prior information about protein function. However, once deleterious variants have been identified, how can they be used in breeding?

RESULTS

We simulated a closed animal breeding population that is subject to both natural selection against deleterious load and artificial selection for a quantitative trait representing the breeding goal. Deleterious load was polygenic and was due to either codominant or recessive variants. We compared strategies for removal of deleterious alleles by genome editing (RAGE) to selection against carriers. When deleterious variants were codominant, the best strategy for prioritizing variants was to prioritize low-frequency variants. When deleterious variants were recessive, the best strategy was to prioritize variants with an intermediate frequency. Selection against carriers was inefficient when variants were codominant, but comparable to editing one variant per sire when variants were recessive.

CONCLUSIONS

Genome editing of deleterious alleles reduces deleterious load, but requires the simultaneous editing of multiple deleterious variants in the same sire to be effective when deleterious variants are recessive. In the short term, selection against carriers is a possible alternative to genome editing when variants are recessive. Our results suggest that, in the future, there is the potential to use RAGE against deleterious load in animal breeding.

Hierarchical Assessment of Mutation Properties in Daphnia magna

Understanding the context-dependence of spontaneous mutations is crucial to predicting evolutionary trajectories. In this experiment, the impact of genetic background and trait-type on mutational susceptibility was investigated. Mutant and non-mutant lines of six unique genotypes from two populations of Daphnia magna were phenotypically assayed using a common-garden experiment. Morphological, life-history, and behavioral traits were measured and estimates of the mutation parameters were generated. The mutation parameters varied between the populations and among genotypes, suggesting differential susceptibility to mutation depending upon genomic background. Traits also varied in their susceptibility to mutation with behavioral traits evolving more rapidly than life-history and morphological traits. These results may reflect the unique selection histories of these populations.

Comparative analysis examining patterns of genomic differentiation across multiple episodes of population divergence in birds

Heterogeneous patterns of genomic differentiation are commonly documented between closely related populations and there is considerable interest in identifying factors that contribute to their formation. These factors could include genomic features (e.g., areas of low recombination) that promote processes like linked selection (positive or purifying selection that affects linked neutral sites) at specific genomic regions. Examinations of repeatable patterns of differentiation across population pairs can provide insight into the role of these factors. Birds are well suited for this work, as genome structure is conserved across this group. Accordingly, we reestimated relative (F_ST ) and absolute (d_XY ) differentiation between eight sister pairs of birds that span a broad taxonomic range using a common pipeline. Across pairs, there were modest but significant correlations in window-based estimates of differentiation (up to 3% of variation explained for F_ST and 26% for d_XY ), supporting a role for processes at conserved genomic features in generating heterogeneous patterns of differentiation; processes specific to each episode of population divergence likely explain the remaining variation. The role genomic features play was reinforced by linear models identifying several genomic variables (e.g., gene densities) as significant predictors of F_ST and d_XY repeatability. F_ST repeatability was higher among pairs that were further along the speciation continuum (i.e., more reproductively isolated) providing further insight into how genomic differentiation changes with population divergence; early stages of speciation may be dominated by positive selection that is different between pairs but becomes integrated with processes acting according to shared genomic features as speciation proceeds.

The invasive MED/Q Bemisia tabaci genome: a tale of gene loss and gene gain

BACKGROUND

Sweetpotato whitefly, Bemisia tabaci MED/Q and MEAM1/B, are two economically important invasive species that cause considerable damages to agriculture crops through direct feeding and indirect vectoring of plant pathogens. Recently, a draft genome of B. tabaci MED/Q has been assembled. In this study, we focus on the genomic comparison between MED/Q and MEAM1/B, with a special interest in MED/Q's genomic signatures that may contribute to the highly invasive nature of this emerging insect pest.

RESULTS

The genomes of both species share similarity in syntenic blocks, but have significant divergence in the gene coding sequence. Expansion of cytochrome P450 monooxygenases and UDP glycosyltransferases in MED/Q and MEAM1/B genome is functionally validated for mediating insecticide resistance in MED/Q using in vivo RNAi. The amino acid biosynthesis pathways in MED/Q genome are partitioned among the host and endosymbiont genomes in a manner distinct from other hemipterans. Evidence of horizontal gene transfer to the host genome may explain their obligate relationship. Putative loss-of-function in the immune deficiency-signaling pathway due to the gene loss is a shared ancestral trait among hemipteran insects.

CONCLUSIONS

The expansion of detoxification genes families, such as P450s, may contribute to the development of insecticide resistance traits and a broad host range in MED/Q and MEAM1/B, and facilitate species' invasions into intensively managed cropping systems. Numerical and compositional changes in multiple gene families (gene loss and gene gain) in the MED/Q genome sets a foundation for future hypothesis testing that will advance our understanding of adaptation, viral transmission, symbiosis, and plant-insect-pathogen tritrophic interactions.

Fitness change in relation to mutation number in spontaneous mutation accumulation lines of Chlamydomonas reinhardtii

Although all genetic variation ultimately stems from mutations, their properties are difficult to study directly. Here, we used multiple mutation accumulation (MA) lines derived from five genetic backgrounds of the green algae Chlamydomonas reinhardtii that have been previously subjected to whole genome sequencing to investigate the relationship between the number of spontaneous mutations and change in fitness from a nonevolved ancestor. MA lines were on average less fit than their ancestors and we detected a significantly negative correlation between the change in fitness and the total number of accumulated mutations in the genome. Likewise, the number of mutations located within coding regions significantly and negatively impacted MA line fitness. We used the fitness data to parameterize a maximum likelihood model to estimate discrete categories of mutational effects, and found that models containing one to two mutational effect categories (one neutral and one deleterious category) fitted the data best. However, the best‐fitting mutational effects models were highly dependent on the genetic background of the ancestral strain.

Living in an adaptive world: Genomic dissection of the genus Homo and its immune response

More than a decade after the sequencing of the human genome, a deluge of genome-wide population data are generating a portrait of human genetic diversity at an unprecedented level of resolution. Genomic studies have provided new insight into the demographic and adaptive history of our species, Homo sapiens, including its interbreeding with other hominins, such as Neanderthals, and the ways in which natural selection, in its various guises, has shaped genome diversity. These studies, combined with functional genomic approaches, such as the mapping of expression quantitative trait loci, have helped to identify genes, functions, and mechanisms of prime importance for host survival and involved in phenotypic variation and differences in disease risk. This review summarizes new findings in this rapidly developing field, focusing on the human immune response. We discuss the importance of defining the genetic and evolutionary determinants driving immune response variation, and highlight the added value of population genomic approaches in settings relevant to immunity and infection.

Direct Determination of the Mutation Rate in the Bumblebee Reveals Evidence for Weak Recombination-Associated Mutation and an Approximate Rate Constancy in Insects

Accurate knowledge of the mutation rate provides a base line for inferring expected rates of evolution, for testing evolutionary hypotheses and for estimation of key parameters. Advances in sequencing technology now permit direct estimates of the mutation rate from sequencing of close relatives. Within insects there have been three prior such estimates, two in nonsocial insects (Drosophila: 2.8 × 10-9 per bp per haploid genome per generation; Heliconius: 2.9 × 10-9) and one in a social species, the honeybee (3.4 × 10-9). Might the honeybee's rate be ∼20% higher because it has an exceptionally high recombination rate and recombination may be directly or indirectly mutagenic? To address this possibility, we provide a direct estimate of the mutation rate in the bumblebee (Bombus terrestris), this being a close relative of the honeybee but with a much lower recombination rate. We confirm that the crossover rate of the bumblebee is indeed much lower than honeybees (8.7 cM/Mb vs. 37 cM/Mb). Importantly, we find no significant difference in the mutation rates: we estimate for bumblebees a rate of 3.6 × 10-9 per haploid genome per generation (95% confidence intervals 2.38 × 10-9 and 5.37 × 10-9) which is just 5% higher than the estimate that of honeybees. Both genomes have approximately one new mutation per haploid genome per generation. While we find evidence for a direct coupling between recombination and mutation (also seen in honeybees), the effect is so weak as to leave almost no footprint on any between-species differences. The similarity in mutation rates suggests an approximate constancy of the mutation rate in insects.

Understanding rare and common diseases in the context of human evolution

The wealth of available genetic information is allowing the reconstruction of human demographic and adaptive history. Demography and purifying selection affect the purge of rare, deleterious mutations from the human population, whereas positive and balancing selection can increase the frequency of advantageous variants, improving survival and reproduction in specific environmental conditions. In this review, I discuss how theoretical and empirical population genetics studies, using both modern and ancient DNA data, are a powerful tool for obtaining new insight into the genetic basis of severe disorders and complex disease phenotypes, rare and common, focusing particularly on infectious disease risk.

Whole-Genome Sequencing Reveals Genetic Variation in the Asian House Rat

Whole-genome sequencing of wild-derived rat species can provide novel genomic resources, which may help decipher the genetics underlying complex phenotypes. As a notorious pest, reservoir of human pathogens, and colonizer, the Asian house rat, Rattus tanezumi, is successfully adapted to its habitat. However, little is known regarding genetic variation in this species. In this study, we identified over 41,000,000 single-nucleotide polymorphisms, plus insertions and deletions, through whole-genome sequencing and bioinformatics analyses. Moreover, we identified over 12,000 structural variants, including 143 chromosomal inversions. Further functional analyses revealed several fixed nonsense mutations associated with infection and immunity-related adaptations, and a number of fixed missense mutations that may be related to anticoagulant resistance. A genome-wide scan for loci under selection identified various genes related to neural activity. Our whole-genome sequencing data provide a genomic resource for future genetic studies of the Asian house rat species and have the potential to facilitate understanding of the molecular adaptations of rats to their ecological niches.

Tempo and mode of genomic mutations unveil human evolutionary history

Mutations that have occurred in human genomes provide insight into various aspects of evolutionary history such as speciation events and degrees of natural selection. Comparing genome sequences between human and great apes or among humans is a feasible approach for inferring human evolutionary history. Recent advances in high-throughput or so-called 'next-generation' DNA sequencing technologies have enabled the sequencing of thousands of individual human genomes, as well as a variety of reference genomes of hominids, many of which are publicly available. These sequence data can help to unveil the detailed demographic history of the lineage leading to humans as well as the explosion of modern human population size in the last several thousand years. In addition, high-throughput sequencing illustrates the tempo and mode of de novo mutations, which are producing human genetic variation at this moment. Pedigree-based human genome sequencing has shown that mutation rates vary significantly across the human genome. These studies have also provided an improved timescale of human evolution, because the mutation rate estimated from pedigree analysis is half that estimated from traditional analyses based on molecular phylogeny. Because of the dramatic reduction in sequencing cost, sequencing on-demand samples designed for specific studies is now also becoming popular. To produce data of sufficient quality to meet the requirements of the study, it is necessary to set an explicit sequencing plan that includes the choice of sample collection methods, sequencing platforms, and number of sequence reads.

The waiting time problem in a model hominin population

Background

Functional information is normally communicated using specific, context-dependent strings of symbolic characters. This is true within the human realm (texts and computer programs), and also within the biological realm (nucleic acids and proteins). In biology, strings of nucleotides encode much of the information within living cells. How do such information-bearing nucleotide strings arise and become established?

Methods

This paper uses comprehensive numerical simulation to understand what types of nucleotide strings can realistically be established via the mutation/selection process, given a reasonable timeframe. The program Mendel’s Accountant realistically simulates the mutation/selection process, and was modified so that a starting string of nucleotides could be specified, and a corresponding target string of nucleotides could be specified. We simulated a classic pre-human hominin population of at least 10,000 individuals, with a generation time of 20 years, and with very strong selection (50 % selective elimination). Random point mutations were generated within the starting string. Whenever an instance of the target string arose, all individuals carrying the target string were assigned a specified reproductive advantage. When natural selection had successfully amplified an instance of the target string to the point of fixation, the experiment was halted, and the waiting time statistics were tabulated. Using this methodology we tested the effect of mutation rate, string length, fitness benefit, and population size on waiting time to fixation.

Results

Biologically realistic numerical simulations revealed that a population of this type required inordinately long waiting times to establish even the shortest nucleotide strings. To establish a string of two nucleotides required on average 84 million years. To establish a string of five nucleotides required on average 2 billion years. We found that waiting times were reduced by higher mutation rates, stronger fitness benefits, and larger population sizes. However, even using the most generous feasible parameters settings, the waiting time required to establish any specific nucleotide string within this type of population was consistently prohibitive.

Conclusion

We show that the waiting time problem is a significant constraint on the macroevolution of the classic hominin population. Routine establishment of specific beneficial strings of two or more nucleotides becomes very problematic.

Germline mutation rates and the long-term phenotypic effects of mutation accumulation in wild-type laboratory mice and mutator mice

The germline mutation rate is an important parameter that affects the amount of genetic variation and the rate of evolution. However, neither the rate of germline mutations in laboratory mice nor the biological significance of the mutation rate in mammalian populations is clear. Here we studied genome-wide mutation rates and the long-term effects of mutation accumulation on phenotype in more than 20 generations of wild-type C57BL/6 mice and mutator mice, which have high DNA replication error rates. We estimated the base-substitution mutation rate to be 5.4 × 10⁻⁹ (95% confidence interval = 4.6 × 10⁻⁹–6.5 × 10⁻⁹) per nucleotide per generation in C57BL/6 laboratory mice, about half the rate reported in humans. The mutation rate in mutator mice was 17 times that in wild-type mice. Abnormal phenotypes were 4.1-fold more frequent in the mutator lines than in the wild-type lines. After several generations, the mutator mice reproduced at substantially lower rates than the controls, exhibiting low pregnancy rates, lower survival rates, and smaller litter sizes, and many of the breeding lines died out. These results provide fundamental information about mouse genetics and reveal the impact of germline mutation rates on phenotypes in a mammalian population.

Dissecting genetic and environmental mutation signatures with model organisms

Deep sequencing has impacted on cancer research by enabling routine sequencing of genomes and exomes to identify genetic changes associated with carcinogenesis. Researchers can now use the frequency, type, and context of all mutations in tumor genomes to extract mutation signatures that reflect the driving mutational processes. Identifying mutation signatures, however, may not immediately suggest a mechanism. Consequently, several recent studies have employed deep sequencing of model organisms exposed to discrete genetic or environmental perturbations. These studies exploit the simpler genomes and availability of powerful genetic tools in model organisms to analyze mutation signatures under controlled conditions, forging mechanistic links between mutational processes and signatures. We discuss the power of this approach and suggest that many such studies may be on the horizon.

Inferring positive selection in humans from genomic data

Adaptation can be described as an evolutionary process that leads to an adjustment of the phenotypes of a population to their environment. In the classical view, new mutations can introduce novel phenotypic features into a population that leave footprints in the genome after fixation, such as selective sweeps. Alternatively, existing genetic variants may become beneficial after an environmental change and increase in frequency. Although they may not reach fixation, they may cause a shift of the optimum of a phenotypic trait controlled by multiple loci. With the availability of polymorphism data from various organisms, including humans and chimpanzees, it has become possible to detect molecular evidence of adaptation and to estimate the strength and target of positive selection. In this review, we discuss the two competing models of adaptation and suitable approaches for detecting the footprints of positive selection on the molecular level.

Maternal onset de novo SH2D1A mutation and lymphocytic choriomeningitis virus infection in a patient with X‑linked lymphoproliferative disease type 1: a case report

X‑linked lymphoproliferative disease type 1 (XLP1) is a rare genetic immunodeficiency disease, which occurs due to germline mutations in the SH2D1A gene. This gene has been reported to encode the adaptor molecule signaling lymphocytic activation molecule‑associated protein XLP1 is generally triggered by the Epstein‑Barr virus (EBV) infection. The present study reported the case of a 4‑year‑old male who presented with a high fever, hypogammaglobulinemia, diffuse lung disease and encephalitis. The patient was infected with the lymphocytic choriomeningitis virus (LCMV), not EBV or any other human herpes virus. The patient was found to carry a SH2D1A c.7G>T/p.A3S mutation, which was inherited from the mother and maternal grandfather, as well as a SH2D1A c.228T>A/p.Y76X mutation, which was identified to be a maternal‑onset de novo mutation at the time of germline development of the patient's mother. To the best of our knowledge, the present study is the first reported case of maternal‑onset XLP1 with a de novo SH2D1A mutation and LCMV infection.

Evolutionary genetic bases of longevity and senescence

Senescence, as a time-dependent developmental process, affects all organisms at every stage in their development and growth. During this process, genetic, epigenetic and environmental factors are known to introduce a wide range of variation for longevity among individuals. As an important life-history trait, longevity shows ontogenetic relationships with other complex traits, and hence may be viewed as a composite trait. Factors that influence the origin and maintenance of diversity of life are ultimately governed by Darwinian processes. Here we review evolutionary genetic mechanisms underlying longevity and senescence in humans from a life-history and genotype-epigenetic-phenotype (G-E-P) map prospective. We suggest that synergistic and cascading effects of cis-ruptive mechanisms in the genome, and epigenetic disruptive processes in relation to environmental factors may lead to sequential slippage in the G-E-P space. These mechanisms accompany age, stage and individual specific senescent processes, influenced by positive pleiotropy of certain genes, superior genome integrity, negative-frequency dependent selection and other factors that universally regulate rarity in nature. Finally we interpret life span as an inherent property of self-organizing systems that, accordingly, maintain species-specific limits for the entire complex of fitness traits. We conclude that Darwinian approaches provide unique opportunities to discover the biological bases of longevity as well as devise individual specific medical or other interventions toward improving health span.

The disparity mutagenesis model predicts rescue of living things from catastrophic errors

In animals including humans, mutation rates per generation exceed a perceived threshold, and excess mutations increase genetic load. Despite this, animals have survived without extinction. This is a perplexing problem for animal and human genetics, arising at the end of the last century, and to date still does not have a fully satisfactory explanation. Shortly after we proposed the disparity theory of evolution in 1992, the disparity mutagenesis model was proposed, which forms the basis for an explanation for an acceleration of evolution and species survival. This model predicts a significant increase of the mutation threshold values if the fidelity difference in replication between the lagging and leading strands is high enough. When applied to biological evolution, the model predicts that living things, including humans, might overcome the lethal effect of accumulated deleterious mutations and be able to survive. Artificially derived mutator strains of microorganisms, in which an enhanced lagging-strand-biased mutagenesis was introduced, showed unexpectedly high adaptability to severe environments. The implications of the striking behaviors shown by these disparity mutators will be discussed in relation to how living things with high mutation rates can avoid the self-defeating risk of excess mutations.

Stochastic simulation in systems biology

Natural systems are, almost by definition, heterogeneous: this can be either a boon or an obstacle to be overcome, depending on the situation. Traditionally, when constructing mathematical models of these systems, heterogeneity has typically been ignored, despite its critical role. However, in recent years, stochastic computational methods have become commonplace in science. They are able to appropriately account for heterogeneity; indeed, they are based around the premise that systems inherently contain at least one source of heterogeneity (namely, intrinsic heterogeneity). In this mini-review, we give a brief introduction to theoretical modelling and simulation in systems biology and discuss the three different sources of heterogeneity in natural systems. Our main topic is an overview of stochastic simulation methods in systems biology. There are many different types of stochastic methods. We focus on one group that has become especially popular in systems biology, biochemistry, chemistry and physics. These discrete-state stochastic methods do not follow individuals over time; rather they track only total populations. They also assume that the volume of interest is spatially homogeneous. We give an overview of these methods, with a discussion of the advantages and disadvantages of each, and suggest when each is more appropriate to use. We also include references to software implementations of them, so that beginners can quickly start using stochastic methods for practical problems of interest.

A nonadaptive origin of a beneficial trait: in silico selection for free energy of folding leads to the neutral emergence of mutational robustness in single domain proteins

Proteins are regarded as being robust to the deleterious effects of mutations. Here, the neutral emergence of mutational robustness in a population of single domain proteins is explored using computer simulations. A pairwise contact model was used to calculate the ΔG of folding (ΔG folding) using the three dimensional protein structure of leech eglin C. A random amino acid sequence with low mutational robustness, defined as the average ΔΔG resulting from a point mutation (ΔΔG average), was threaded onto the structure. A population of 1,000 threaded sequences was evolved under selection for stability, using an upper and lower energy threshold. Under these conditions, mutational robustness increased over time in the most common sequence in the population. In contrast, when the wild type sequence was used it did not show an increase in robustness. This implies that the emergence of mutational robustness is sequence specific and that wild type sequences may be close to maximal robustness. In addition, an inverse relationship between ∆∆G average and protein stability is shown, resulting partly from a larger average effect of point mutations in more stable proteins. The emergence of mutational robustness was also observed in the Escherichia coli colE1 Rop and human CD59 proteins, implying that the property may be common in single domain proteins under certain simulation conditions. The results indicate that at least a portion of mutational robustness in small globular proteins might have arisen by a process of neutral emergence, and could be an example of a beneficial trait that has not been directly selected for, termed a "pseudaptation."

Long runs of homozygosity are enriched for deleterious variation

Exome sequencing offers the potential to study the population-genomic variables that underlie patterns of deleterious variation. Runs of homozygosity (ROH) are long stretches of consecutive homozygous genotypes probably reflecting segments shared identically by descent as the result of processes such as consanguinity, population size reduction, and natural selection. The relationship between ROH and patterns of predicted deleterious variation can provide insight into the way in which these processes contribute to the maintenance of deleterious variants. Here, we use exome sequencing to examine ROH in relation to the distribution of deleterious variation in 27 individuals of varying levels of apparent inbreeding from 6 human populations. A significantly greater fraction of all genome-wide predicted damaging homozygotes fall in ROH than would be expected from the corresponding fraction of nondamaging homozygotes in ROH (p < 0.001). This pattern is strongest for long ROH (p < 0.05). ROH, and especially long ROH, harbor disproportionately more deleterious homozygotes than would be expected on the basis of the total ROH coverage of the genome and the genomic distribution of nondamaging homozygotes. The results accord with a hypothesis that recent inbreeding, which generates long ROH, enables rare deleterious variants to exist in homozygous form. Thus, just as inbreeding can elevate the occurrence of rare recessive diseases that represent homozygotes for strongly deleterious mutations, inbreeding magnifies the occurrence of mildly deleterious variants as well.

Strong purifying selection at synonymous sites in D. melanogaster

Synonymous sites are generally assumed to be subject to weak selective constraint. For this reason, they are often neglected as a possible source of important functional variation. We use site frequency spectra from deep population sequencing data to show that, contrary to this expectation, 22% of four-fold synonymous (4D) sites in Drosophila melanogaster evolve under very strong selective constraint while few, if any, appear to be under weak constraint. Linking polymorphism with divergence data, we further find that the fraction of synonymous sites exposed to strong purifying selection is higher for those positions that show slower evolution on the Drosophila phylogeny. The function underlying the inferred strong constraint appears to be separate from splicing enhancers, nucleosome positioning, and the translational optimization generating canonical codon bias. The fraction of synonymous sites under strong constraint within a gene correlates well with gene expression, particularly in the mid-late embryo, pupae, and adult developmental stages. Genes enriched in strongly constrained synonymous sites tend to be particularly functionally important and are often involved in key developmental pathways. Given that the observed widespread constraint acting on synonymous sites is likely not limited to Drosophila, the role of synonymous sites in genetic disease and adaptation should be reevaluated.

Rare variants in complex traits: novel identification strategies and the role of de novo mutations

Following the limited success of linkage and association studies aimed at identifying the genetic causes of common neurodevelopmental syndromes like autism and schizophrenia, complex traits such as these have recently been considered under the 'common disease-rare variant' hypothesis. Prior to this hypothesis, the study of candidate genes has enabled the discovery of rare variants in complex disorders, and in turn some of these variants have highlighted the genetic contribution of de novo variants. De novo variants belong to a subcategory of spontaneous rare variants that are largely associated with sporadic diseases, which include some complex psychiatric disorders where the affected individuals do not transmit the genetic defects they carry because of their reduced reproductive fitness. Interestingly, recent studies have demonstrated the rate of germline de novo mutations to be higher in individuals with complex psychiatric disorders by comparison to what is seen in unaffected control individuals; moreover, de novo mutations carried by affected individuals have generally been more deleterious than those observed in control individuals. Advanced sequencing technologies have recently enabled the undertaking of massive parallel sequencing projects that can cover the entire coding sequences (exome) or genome of several individuals at once. Such advances have thus fostered the emergence of novel genetic hypotheses and ideas to investigate disease-causative genetic variations. The genetic underpinnings of a number of sporadic complex diseases is now becoming partly explained and more major breakthroughs for complex traits genomics should be expected in the near future.

Implications of fidelity difference between the leading and the lagging strand of DNA for the acceleration of evolution

Without exceptions, genomic DNA of living organisms is replicated using the leading and the lagging strand. In a conventional idea of mutagenesis accompanying DNA replication, mutations are thought to be introduced stochastically and evenly into the two daughter DNAs. Here, however, we hypothesized that the fidelity of the lagging strand is lower than that of the leading strand. Our simulations with a simplified model DNA clearly indicated that, even if mutation rates exceeded the so-called threshold values, an original genotype was guaranteed in the pedigree and, at the same time, the enlargement of diversity was attained with repeated generations. According to our lagging-strand-biased-mutagenesis model, mutator microorganisms were established in which mutations biased to the lagging strand were introduced by deleting the proofreading activity of DNA polymerase. These mutators (“disparity mutators”) grew normally and had a quick and extraordinarily high adaptability against very severe circumstances. From the viewpoint of the fidelity difference between the leading and the lagging strand, the basic conditions for the acceleration of evolution are examined. The plausible molecular mechanism for the faster molecular clocks observed in birds and mammals is discussed, with special reference to the accelerated evolution in the past. Possible applications in different fields are also discussed.

The rhesus macaque is three times as diverse but more closely equivalent in damaging coding variation as compared to the human

Background

As a model organism in biomedicine, the rhesus macaque (Macaca mulatta) is the most widely used nonhuman primate. Although a draft genome sequence was completed in 2007, there has been no systematic genome-wide comparison of genetic variation of this species to humans. Comparative analysis of functional and nonfunctional diversity in this highly abundant and adaptable non-human primate could inform its use as a model for human biology, and could reveal how variation in population history and size alters patterns and levels of sequence variation in primates.

Results

We sequenced the mRNA transcriptome and H3K4me3-marked DNA regions in hippocampus from 14 humans and 14 rhesus macaques. Using equivalent methodology and sampling spaces, we identified 462,802 macaque SNPs, most of which were novel and disproportionately located in the functionally important genomic regions we had targeted in the sequencing. At least one SNP was identified in each of 16,797 annotated macaque genes. Accuracy of macaque SNP identification was conservatively estimated to be >90%. Comparative analyses using SNPs equivalently identified in the two species revealed that rhesus macaque has approximately three times higher SNP density and average nucleotide diversity as compared to the human. Based on this level of diversity, the effective population size of the rhesus macaque is approximately 80,000 which contrasts with an effective population size of less than 10,000 for humans. Across five categories of genomic regions, intergenic regions had the highest SNP density and average nucleotide diversity and CDS (coding sequences) the lowest, in both humans and macaques. Although there are more coding SNPs (cSNPs) per individual in macaques than in humans, the ratio of d_N/d_S is significantly lower in the macaque. Furthermore, the number of damaging nonsynonymous cSNPs (have damaging effects on protein functions from PolyPhen-2 prediction) in the macaque is more closely equivalent to that of the human.

Conclusions

This large panel of newly identified macaque SNPs enriched for functionally significant regions considerably expands our knowledge of genetic variation in the rhesus macaque. Comparative analysis reveals that this widespread, highly adaptable species is approximately three times as diverse as the human but more closely equivalent in damaging variation.

Distortions in genealogies due to purifying selection

Purifying selection can substantially alter patterns of molecular evolution. Its main effect is to reduce overall levels of genetic variation, leading to a reduced effective population size. However, it also distorts genealogies relative to neutral expectations. A structured coalescent method has been used to describe this effect, and forms the basis for numerical methods and simulations. In this study, we extend this approach by making the additional approximation that lineages may be treated independently, which is valid only in the strong selection regime. We show that in this regime, the distortions due to purifying selection can be described by a time-dependent effective population size and mutation rate, confirming earlier intuition. We calculate simple analytical expressions for these functions, N(e)(t) and U(e)(t). These results allow us to describe the structure of genealogies in a population under strong purifying selection as equivalent to a purely neutral population with varying population size and mutation rate, thereby enabling the use of neutral methods of inference and estimation for populations in the strong selection regime.

The effects of contig length and depth on the estimation of SNP frequencies, and the relative abundance of SNPs in protein-coding and non-coding transcripts of tiger salamanders (Ambystoma tigrinum)

BACKGROUND

Next-generation sequencing methods have contributed to rapid progress in the fields of genomics and population genetics. Using this high-throughput and cost-effective technology, a number of studies have estimated single nucleotide polymorphism (SNP) frequency by calculating the mean number of SNPs per unit sequence length (e.g., mean SNPs/kb). However, both read length and contig depth are highly variable and thus raise doubt about simple methods of SNP frequency estimation.

RESULTS

We used 454 pyrosequencing to identify 2,980 putative SNPs in the eastern tiger salamander (Ambystoma tigrinum tigrinum) transcriptome, then constructed analytical models to estimate SNP frequency. The model which considered only contig length (i.e., the method employed in most published papers) was evaluated with very poor likelihood. Our most robust model considered read depth as well as contig length, and was 7.5 × 10⁵⁵ times more likely than the length-only model. Using this novel modeling approach, we estimated SNP frequency in protein-coding (mRNA) and non-coding transcripts (e.g., small RNAs). We found little difference in SNP frequency in the contigs, but we found a trend of a higher frequency of SNPs in long contigs representing non-coding transcripts relative to protein-coding transcripts. These results support the hypothesis that long non-coding transcripts are less conserved than long protein-coding transcripts.

CONCLUSIONS

A modeling approach (i.e., using multiple model construction and model selection approaches) can be a powerful tool for identifying selection on specific functional sequence groups by comparing the frequency and distribution of polymorphisms.

Tandem repeat sequence variation as causative cis-eQTLs for protein-coding gene expression variation: the case of CSTB

Association studies have revealed expression quantitative trait loci (eQTLs) for a large number of genes. However, the causative variants that regulate gene expression levels are generally unknown. We hypothesized that copy-number variation of sequence repeats contribute to the expression variation of some genes. Our laboratory has previously identified that the rare expansion of a repeat c.-174CGGGGCGGGGCG in the promoter region of the CSTB gene causes a silencing of the gene, resulting in progressive myoclonus epilepsy. Here, we genotyped the repeat length and quantified CSTB expression by quantitative real-time polymerase chain reaction in 173 lymphoblastoid cell lines (LCLs) and fibroblast samples from the GenCord collection. The majority of alleles contain either two or three copies of this repeat. Independent analysis revealed that the c.-174CGGGGCGGGGCG repeat length is strongly associated with CSTB expression (P = 3.14 × 10(-11)) in LCLs only. Examination of both genotyped and imputed single-nucleotide polymorphisms (SNPs) within 2 Mb of CSTB revealed that the dodecamer repeat represents the strongest cis-eQTL for CSTB in LCLs. We conclude that the common two or three copy variation is likely the causative cis-eQTL for CSTB expression variation. More broadly, we propose that polymorphic tandem repeats may represent the causative variation of a fraction of cis-eQTLs in the genome.

A resolution of the mutation load paradox in humans

Current information on the rate of mutation and the fraction of sites in the genome that are subject to selection suggests that each human has received, on average, at least two new harmful mutations from its parents. These mutations were subsequently removed by natural selection through reduced survival or fertility. It has been argued that the mutation load, the proportional reduction in population mean fitness relative to the fitness of an idealized mutation-free individual, allows a theoretical prediction of the proportion of individuals in the population that fail to reproduce as a consequence of these harmful mutations. Application of this theory to humans implies that at least 88% of individuals should fail to reproduce and that each female would need to have more than 16 offspring to maintain population size. This prediction is clearly at odds with the low reproductive excess of human populations. Here, we derive expressions for the fraction of individuals that fail to reproduce as a consequence of recurrent deleterious mutation () for a model in which selection occurs via differences in relative fitness, such as would occur through competition between individuals. We show that is much smaller than the value predicted by comparing fitness to that of a mutation-free genotype. Under the relative fitness model, we show that depends jointly on U and the selective effects of new deleterious mutations and that a species could tolerate 10's or even 100's of new deleterious mutations per genome each generation.

A unified framework for detecting rare variant quantitative trait associations in pedigree and unrelated individuals via sequence data

OBJECTIVES

There is great interest to sequence unrelated or pedigree samples for detecting rare variant quantitative trait associations. In order to reduce the cost of sequencing and improve power, many studies sequence selected samples with extreme traits. Existing methods for detecting rare variant associations were developed for unrelated samples. Methods are needed to analyze (selected or randomly ascertained) pedigree samples.

METHODS

We propose a unified framework of modeling extreme trait genetic associations (MEGA) with rare variants. Using MEGA and appropriate permutation algorithms, many rare variant tests can be extended to family data. As an application, we compared study designs using both sib-pairs and unrelated individuals. Extensive simulations were carried out using realistic population genetic and complex trait models.

RESULTS

It is demonstrated that when extreme sampling is implemented within equal-sized cohorts of unrelated individuals or sib-pairs, analyzing unrelated individuals is consistently more powerful than studying sib-pairs. A higher portion of rare variants can be identified through sequencing unrelated samples compared to sibs. Alternatively, if samples are ascertained using fixed thresholds from an infinite-sized population, sequencing one sib with the most extreme trait from each extreme concordant sib-pair is consistently the most powerful design.

CONCLUSIONS

MEGA will play an important role in the analysis of sequence-based genetic association studies.