Characteristics of neutral and deleterious protein-coding variation among individuals and populations

Challenges and disparities in the application of personalized genomic medicine to populations with African ancestry

To characterize the extent and impact of ancestry-related biases in precision genomic medicine, we use 642 whole-genome sequences from the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) project to evaluate typical filters and databases. We find significant correlations between estimated African ancestry proportions and the number of variants per individual in all variant classification sets but one. The source of these correlations is highlighted in more detail by looking at the interaction between filtering criteria and the ClinVar and Human Gene Mutation databases. ClinVar's correlation, representing African ancestry-related bias, has changed over time amidst monthly updates, with the most extreme switch happening between March and April of 2014 (r=0.733 to r=-0.683). We identify 68 SNPs as the major drivers of this change in correlation. As long as ancestry-related bias when using these clinical databases is minimally recognized, the genetics community will face challenges with implementation, interpretation and cost-effectiveness when treating minority populations.

A continuum of admixture in the Western Hemisphere revealed by the African Diaspora genome

The African Diaspora in the Western Hemisphere represents one of the largest forced migrations in history and had a profound impact on genetic diversity in modern populations. To date, the fine-scale population structure of descendants of the African Diaspora remains largely uncharacterized. Here we present genetic variation from deeply sequenced genomes of 642 individuals from North and South American, Caribbean and West African populations, substantially increasing the lexicon of human genomic variation and suggesting much variation remains to be discovered in African-admixed populations in the Americas. We summarize genetic variation in these populations, quantifying the postcolonial sex-biased European gene flow across multiple regions. Moreover, we refine estimates on the burden of deleterious variants carried across populations and how this varies with African ancestry. Our data are an important resource for empowering disease mapping studies in African-admixed individuals and will facilitate gene discovery for diseases disproportionately affecting individuals of African ancestry.

Family-Specific Variants and the Limits of Human Genetics

Every single-nucleotide change compatible with life is present in the human population today. Understanding these rare human variants defines an extraordinary challenge for genetics and medicine. The new clinical practice of sequencing many genes for hereditary cancer risk has illustrated the utility of clinical next-generation sequencing in adults, identifying more medically actionable variants than single-gene testing. However, it has also revealed a linear relationship between the length of DNA evaluated and the number of rare 'variants of uncertain significance' reported. We propose that careful approaches to phenotype-genotype inference, distinguishing between diagnostic and screening intent, in conjunction with expanded use of family-scale genetics studies as a source of information on family-specific variants, will reduce variants of uncertain significance reported to patients.

Novel Genetic, Clinical, and Pathomechanistic Insights into TFG-Associated Hereditary Spastic Paraplegia

Hereditary spastic paraplegias (HSPs) are genetically and clinically heterogeneous axonopathies primarily affecting upper motor neurons and, in complex forms, additional neurons. Here, we report two families with distinct recessive mutations in TFG, previously suggested to cause HSP based on findings in a single small family with complex HSP. The first carried a homozygous c.317G>A (p.R106H) variant and presented with pure HSP. The second carried the same homozygous c.316C>T (p.R106C) variant previously reported and displayed a similarly complex phenotype including optic atrophy. Haplotyping and bisulfate sequencing revealed evidence for a c.316C>T founder allele, as well as for a c.316_317 mutation hotspot. Expression of mutant TFG proteins in cultured neurons revealed mitochondrial fragmentation, the extent of which correlated with clinical severity. Our findings confirm the causal nature of bi-allelic TFG mutations for HSP, broaden the clinical and mutational spectra, and suggest mitochondrial impairment to represent a pathomechanistic link to other neurodegenerative conditions.

Genetics of Type 2 Diabetes: the Power of Isolated Populations

Type 2 diabetes (T2D) affects millions of people worldwide. Improving the understanding of the underlying mechanisms and ultimately improving the treatment strategies are, thus, of great interest. To achieve this, identification of genetic variation predisposing to T2D is important. A large number of variants have been identified in large outbred populations, mainly from Europe and Asia. However, to elucidate additional variation, isolated populations have a number of advantageous properties, including increased amounts of linkage disequilibrium, and increased probability for presence of high frequency disease-associated variants due to genetic drift. Collectively, this increases the statistical power to detect association signals in isolated populations compared to large outbred populations. In this review, we elaborate on why isolated populations are a powerful resource for the identification of complex disease variants and describe their contributions to the understanding of the genetics of T2D.

A flexible method for estimating the fraction of fitness influencing mutations from large sequencing data sets

A continuing challenge in the analysis of massively large sequencing data sets is quantifying and interpreting non-neutrally evolving mutations. Here, we describe a flexible and robust approach based on the site frequency spectrum to estimate the fraction of deleterious and adaptive variants from large-scale sequencing data sets. We applied our method to approximately 1 million single nucleotide variants (SNVs) identified in high-coverage exome sequences of 6515 individuals. We estimate that the fraction of deleterious nonsynonymous SNVs is higher than previously reported; quantify the effects of genomic context, codon bias, chromatin accessibility, and number of protein-protein interactions on deleterious protein-coding SNVs; and identify pathways and networks that have likely been influenced by positive selection. Furthermore, we show that the fraction of deleterious nonsynonymous SNVs is significantly higher for Mendelian versus complex disease loci and in exons harboring dominant versus recessive Mendelian mutations. In summary, as genome-scale sequencing data accumulate in progressively larger sample sizes, our method will enable increasingly high-resolution inferences into the characteristics and determinants of non-neutral variation.

Human Knockout Carriers: Dead, Diseased, Healthy, or Improved?

Whole-genome and whole-exome sequence data from large numbers of individuals reveal that we all carry many variants predicted to inactivate genes (knockouts). This discovery raises questions about the phenotypic consequences of these knockouts and potentially allows us to study human gene function through the investigation of homozygous loss-of-function carriers. Here, we discuss strategies, recent results, and future prospects for large-scale human knockout studies. We examine their relevance to studying gene function, population genetics, and importantly, the implications for accurate clinical interpretations.

When Is Selection Effective?

Deleterious alleles can reach high frequency in small populations because of random fluctuations in allele frequency. This may lead, over time, to reduced average fitness. In this sense, selection is more "effective" in larger populations. Recent studies have considered whether the different demographic histories across human populations have resulted in differences in the number, distribution, and severity of deleterious variants, leading to an animated debate. This article first seeks to clarify some terms of the debate by identifying differences in definitions and assumptions used in recent studies. We argue that variants of Morton, Crow, and Muller's "total mutational damage" provide the soundest and most practical basis for such comparisons. Using simulations, analytical calculations, and 1000 Genomes Project data, we provide an intuitive and quantitative explanation for the observed similarity in genetic load across populations. We show that recent demography has likely modulated the effect of selection and still affects it, but the net result of the accumulated differences is small. Direct observation of differential efficacy of selection for specific allele classes is nevertheless possible with contemporary data sets. By contrast, identifying average genome-wide differences in the efficacy of selection across populations will require many modeling assumptions and is unlikely to provide much biological insight about human populations.

The Limits of Natural Selection in a Nonequilibrium World

Evolutionary theory predicts that factors such as a small population size or low recombination rate can limit the action of natural selection. The emerging field of comparative population genomics offers an opportunity to evaluate these hypotheses. However, classical theoretical predictions assume that populations are at demographic equilibrium. This assumption is likely to be violated in the very populations researchers use to evaluate selection's limits: populations that have experienced a recent shift in population size and/or effective recombination rates. Here we highlight theory and data analyses concerning limitations on the action of natural selection in nonequilibrial populations and argue that substantial care is needed to appropriately test whether species and populations show meaningful differences in selection efficacy. A move toward model-based inferences that explicitly incorporate nonequilibrium dynamics provides a promising approach to more accurately contrast selection efficacy across populations and interpret its significance.

Improving performance of multigene panels for genomic analysis of cancer predisposition

PURPOSE

Screening multiple genes for inherited cancer predisposition expands opportunities for cancer prevention; however, reports of variants of uncertain significance (VUS) may limit clinical usefulness. We used an expert-driven approach, exploiting all available information, to evaluate multigene panels for inherited cancer predisposition in a clinical series that included multiple cancer types and complex family histories.

METHODS

For 1,462 sequential patients referred for testing by BROCA or ColoSeq multigene panels, genomic DNA was sequenced and variants were interpreted by multiple experts using International Agency for Research on Cancer guidelines and incorporating evolutionary conservation, known and predicted variant consequences, and personal and family cancer history. Diagnostic yield was evaluated for various presenting conditions and family-history profiles.

RESULTS

Of 1,462 patients, 12% carried damaging mutations in established cancer genes. Diagnostic yield varied by clinical presentation. Actionable results were identified for 13% of breast and colorectal cancer patients and for 4% of cancer-free subjects, based on their family histories of cancer. Incidental findings explaining cancer in neither the patient nor the family were present in 1.7% of subjects. Less than 1% of patients carried VUS in BRCA1 or BRCA2. For all genes combined, initial reports contained VUS for 10.5% of patients, which declined to 7.5% of patients after reclassification based on additional information.

CONCLUSIONS

Individualized interpretation of gene panels is a complex medical activity. Interpretation by multiple experts in the context of personal and family histories maximizes actionable results and minimizes reports of VUS.Genet Med 18 10, 974-981.

Bottlenecks and selective sweeps during domestication have increased deleterious genetic variation in dogs

Population bottlenecks, inbreeding, and artificial selection can all, in principle, influence levels of deleterious genetic variation. However, the relative importance of each of these effects on genome-wide patterns of deleterious variation remains controversial. Domestic and wild canids offer a powerful system to address the role of these factors in influencing deleterious variation because their history is dominated by known bottlenecks and intense artificial selection. Here, we assess genome-wide patterns of deleterious variation in 90 whole-genome sequences from breed dogs, village dogs, and gray wolves. We find that the ratio of amino acid changing heterozygosity to silent heterozygosity is higher in dogs than in wolves and, on average, dogs have 2-3% higher genetic load than gray wolves. Multiple lines of evidence indicate this pattern is driven by less efficient natural selection due to bottlenecks associated with domestication and breed formation, rather than recent inbreeding. Further, we find regions of the genome implicated in selective sweeps are enriched for amino acid changing variants and Mendelian disease genes. To our knowledge, these results provide the first quantitative estimates of the increased burden of deleterious variants directly associated with domestication and have important implications for selective breeding programs and the conservation of rare and endangered species. Specifically, they highlight the costs associated with selective breeding and question the practice favoring the breeding of individuals that best fit breed standards. Our results also suggest that maintaining a large population size, rather than just avoiding inbreeding, is a critical factor for preventing the accumulation of deleterious variants.

Distance from sub-Saharan Africa predicts mutational load in diverse human genomes

The Out-of-Africa (OOA) dispersal ∼ 50,000 y ago is characterized by a series of founder events as modern humans expanded into multiple continents. Population genetics theory predicts an increase of mutational load in populations undergoing serial founder effects during range expansions. To test this hypothesis, we have sequenced full genomes and high-coverage exomes from seven geographically divergent human populations from Namibia, Congo, Algeria, Pakistan, Cambodia, Siberia, and Mexico. We find that individual genomes vary modestly in the overall number of predicted deleterious alleles. We show via spatially explicit simulations that the observed distribution of deleterious allele frequencies is consistent with the OOA dispersal, particularly under a model where deleterious mutations are recessive. We conclude that there is a strong signal of purifying selection at conserved genomic positions within Africa, but that many predicted deleterious mutations have evolved as if they were neutral during the expansion out of Africa. Under a model where selection is inversely related to dominance, we show that OOA populations are likely to have a higher mutation load due to increased allele frequencies of nearly neutral variants that are recessive or partially recessive.

Selective Strolls: Fixation and Extinction in Diploids Are Slower for Weakly Selected Mutations Than for Neutral Ones

In finite populations, an allele disappears or reaches fixation due to two main forces, selection and drift. Selection is generally thought to accelerate the process: a selected mutation will reach fixation faster than a neutral one, and a disadvantageous one will quickly disappear from the population. We show that even in simple diploid populations, this is often not true. Dominance and recessivity unexpectedly slow down the evolutionary process for weakly selected alleles. In particular, slightly advantageous dominant and mildly deleterious recessive mutations reach fixation slightly more slowly than neutral ones (at most 5%). This phenomenon determines genetic signatures opposite to those expected under strong selection, such as increased instead of decreased genetic diversity around the selected site. Furthermore, we characterize a new phenomenon: mildly deleterious recessive alleles, thought to represent a wide fraction of newly arising mutations, on average survive in a population slightly longer than neutral ones, before getting lost. Consequently, these mutations are on average slightly older than neutral ones, in contrast with previous expectations. Furthermore, they slightly increase the amount of weakly deleterious polymorphisms, as a consequence of the longer unconditional sojourn times compared to neutral mutations.

Functional and Structural Consequence of Rare Exonic Single Nucleotide Polymorphisms: One Story, Two Tales

Genetic variation arising from single nucleotide polymorphisms (SNPs) is ubiquitously found among human populations. While disease-causing variants are known in some cases, identifying functional or causative variants for most human diseases remains a challenging task. Rare SNPs, rather than common ones, are thought to be more important in the pathology of most human diseases. We propose that rare SNPs should be divided into two categories dependent on whether the minor alleles are derived or ancestral. Derived alleles are less likely to have been purified by evolutionary processes and may be more likely to induce deleterious effects. We therefore hypothesized that the rare SNPs with derived minor alleles would be more important for human diseases and predicted that these variants would have larger functional or structural consequences relative to the rare variants for which the minor alleles are ancestral. We systematically investigated the consequences of the exonic SNPs on protein function, mRNA structure, and translation. We found that the functional and structural consequences are more significant for the rare exonic variants for which the minor alleles are derived. However, this pattern is reversed when the minor alleles are ancestral. Thus, the rare exonic SNPs with derived minor alleles are more likely to be deleterious. Age estimation of rare SNPs confirms that these potentially deleterious SNPs are recently evolved in the human population. These results have important implications for understanding the function of genetic variations in human exonic regions and for prioritizing functional SNPs in genome-wide association studies of human diseases.

A General Model of the Relationship between the Apportionment of Human Genetic Diversity and the Apportionment of Human Phenotypic Diversity

Models that examine genetic differences between populations alongside a genotype-phenotype map can provide insight about phenotypic variation among groups. We generalize a simple model of a completely heritable, additive, selectively neutral quantitative trait to examine the relationship between single-locus genetic differentiation and phenotypic differentiation on quantitative traits. In agreement with similar efforts using different models, we show that the expected degree to which two groups differ on a neutral quantitative trait is not strongly affected by the number of genetic loci that influence the trait: neutral trait differences are expected to have a magnitude comparable to the genetic differences at a single neutral locus. We discuss this result with respect to population differences in disease phenotypes, arguing that although neutral genetic differences between populations can contribute to specific differences between populations in health outcomes, systematic patterns of difference that run in the same direction for many genetically independent health conditions are unlikely to be explained by neutral genetic differentiation.

Global diversity, population stratification, and selection of human copy-number variation

In order to explore the diversity and selective signatures of duplication and deletion human copy-number variants (CNVs), we sequenced 236 individuals from 125 distinct human populations. We observed that duplications exhibit fundamentally different population genetic and selective signatures than deletions and are more likely to be stratified between human populations. Through reconstruction of the ancestral human genome, we identify megabases of DNA lost in different human lineages and pinpoint large duplications that introgressed from the extinct Denisova lineage now found at high frequency exclusively in Oceanic populations. We find that the proportion of CNV base pairs to single-nucleotide-variant base pairs is greater among non-Africans than it is among African populations, but we conclude that this difference is likely due to unique aspects of non-African population history as opposed to differences in CNV load.

Estimating the mutation load in human genomes

Next-generation sequencing technology has facilitated the discovery of millions of genetic variants in human genomes. A sizeable fraction of these variants are predicted to be deleterious. Here, we review the pattern of deleterious alleles as ascertained in genome sequencing data sets and ask whether human populations differ in their predicted burden of deleterious alleles - a phenomenon known as mutation load. We discuss three demographic models that are predicted to affect mutation load and relate these models to the evidence (or the lack thereof) for variation in the efficacy of purifying selection in diverse human genomes. We also emphasize why accurate estimation of mutation load depends on assumptions regarding the distribution of dominance and selection coefficients - quantities that remain poorly characterized for current genomic data sets.