Homozygous loss-of-function variants in European cosmopolitan and isolate populations

Emerging significance of butyrylcholinesterase

Butyrylcholinesterase (BChE; EC 3.1.1.8), an enzyme structurally related to acetylcholinesterase, is widely distributed in the human body. It plays a role in the detoxification of chemicals such as succinylcholine, a muscle relaxant used in anesthetic practice. BChE is well-known due to variant forms of the enzyme with little or no hydrolytic activity which exist in some endogamous communities and result in prolonged apnea following the administration of succinylcholine. Its other functions include the ability to hydrolyze acetylcholine, the cholinergic neurotransmitter in the brain, when its primary hydrolytic enzyme, acetylcholinesterase, is absent. To assess its potential roles, BChE was studied in relation to insulin resistance, type 2 diabetes mellitus, cognition, hepatic disorders, cardiovascular and cerebrovascular diseases, and inflammatory conditions. Individuals who lack the enzyme activity of BChE are otherwise healthy, until they are given drugs hydrolyzed by this enzyme. Therefore, BChE is a candidate for the study of loss-of-function mutations in humans. Studying individuals with variant forms of BChE can provide insights into whether they are protected against metabolic diseases. The potential utility of the enzyme as a biomarker for Alzheimer's disease and the response to its drug treatment can also be assessed.

The Counteracting Effects of Demography on Functional Genomic Variation: The Roma Paradigm

Demographic history plays a major role in shaping the distribution of genomic variation. Yet the interaction between different demographic forces and their effects in the genomes is not fully resolved in human populations. Here, we focus on the Roma population, the largest transnational ethnic minority in Europe. They have a South Asian origin and their demographic history is characterized by recent dispersals, multiple founder events, and extensive gene flow from non-Roma groups. Through the analyses of new high-coverage whole exome sequences and genome-wide array data for 89 Iberian Roma individuals together with forward simulations, we show that founder effects have reduced their genetic diversity and proportion of rare variants, gene flow has counteracted the increase in mutational load, runs of homozygosity show ancestry-specific patterns of accumulation of deleterious homozygotes, and selection signals primarily derive from preadmixture adaptation in the Roma population sources. The present study shows how two demographic forces, bottlenecks and admixture, act in opposite directions and have long-term balancing effects on the Roma genomes. Understanding how demography and gene flow shape the genome of an admixed population provides an opportunity to elucidate how genomic variation is modeled in human populations.

Less Is More, Natural Loss-of-Function Mutation Is a Strategy for Adaptation

Gene gain and loss are crucial factors that shape the evolutionary success of diverse organisms. In the past two decades, more attention has been paid to the significance of gene gain through gene duplication or de novo genes. However, gene loss through natural loss-of-function (LoF) mutations, which is prevalent in the genomes of diverse organisms, has been largely ignored. With the development of sequencing techniques, many genomes have been sequenced across diverse species and can be used to study the evolutionary patterns of gene loss. In this review, we summarize recent advances in research on various aspects of LoF mutations, including their identification, evolutionary dynamics in natural populations, and functional effects. In particular, we discuss how LoF mutations can provide insights into the minimum gene set (or the essential gene set) of an organism. Furthermore, we emphasize their potential impact on adaptation. At the genome level, although most LoF mutations are neutral or deleterious, at least some of them are under positive selection and may contribute to biodiversity and adaptation. Overall, we highlight the importance of natural LoF mutations as a robust framework for understanding biological questions in general.

Comprehensive genome and transcriptome analyses reveal genetic relationship, selection signature, and transcriptome landscape of small-sized Korean native Jeju horse

The Jeju horse, indigenous to the Jeju Island in Korea may have originated from Mongolian horses. Adaptations to the local harsh environment have conferred Jeju horse with unique traits such as small-sized body, stocky head, and shorter limbs. These characteristics have not been studied previously at the genomic level. Therefore, we sequenced and compared the genome of 41 horses belonging to 6 breeds. We identified numerous breed-specific non-synonymous SNPs and loss-of-function mutants. Demographic and admixture analyses showed that, though Jeju horse is genetically the closest to the Mongolian breeds, its genetic ancestry is independent of that of the Mongolian breeds. Genome wide selection signature analysis revealed that genes such as LCORL, MSTN, HMGA2, ZFAT, LASP1, PDK4, and ACTN2, were positively selected in the Jeju horse. RNAseq analysis showed that several of these genes were also differentially expressed in Jeju horse compared to Thoroughbred horse. Comparative muscle fiber analysis showed that, the type I muscle fibre content was substantially higher in Jeju horse compared to Thoroughbred horse. Our results provide insights about the selection of complex phenotypic traits in the small-sized Jeju horse and the novel SNPs identified will aid in designing high-density SNP chip for studying other native horse breeds.

Increased ultra-rare variant load in an isolated Scottish population impacts exonic and regulatory regions

Human population isolates provide a snapshot of the impact of historical demographic processes on population genetics. Such data facilitate studies of the functional impact of rare sequence variants on biomedical phenotypes, as strong genetic drift can result in higher frequencies of variants that are otherwise rare. We present the first whole genome sequencing (WGS) study of the VIKING cohort, a representative collection of samples from the isolated Shetland population in northern Scotland, and explore how its genetic characteristics compare to a mainland Scottish population. Our analyses reveal the strong contributions played by the founder effect and genetic drift in shaping genomic variation in the VIKING cohort. About one tenth of all high-quality variants discovered are unique to the VIKING cohort or are seen at frequencies at least ten fold higher than in more cosmopolitan control populations. Multiple lines of evidence also suggest relaxation of purifying selection during the evolutionary history of the Shetland isolate. We demonstrate enrichment of ultra-rare VIKING variants in exonic regions and for the first time we also show that ultra-rare variants are enriched within regulatory regions, particularly promoters, suggesting that gene expression patterns may diverge relatively rapidly in human isolates.

An actionable KCNH2 Long QT Syndrome variant detected by sequence and haplotype analysis in a population research cohort

The Viking Health Study Shetland is a population-based research cohort of 2,122 volunteer participants with ancestry from the Shetland Isles in northern Scotland. The high kinship and detailed phenotype data support a range of approaches for associating rare genetic variants, enriched in this isolate population, with quantitative traits and diseases. As an exemplar, the c.1750G > A; p.Gly584Ser variant within the coding sequence of the KCNH2 gene implicated in Long QT Syndrome (LQTS), which occurred once in 500 whole genome sequences from this population, was investigated. Targeted sequencing of the KCNH2 gene in family members of the initial participant confirmed the presence of the sequence variant and identified two further members of the same family pedigree who shared the variant. Investigation of these three related participants for whom single nucleotide polymorphism (SNP) array genotypes were available allowed a unique shared haplotype of 1.22 Mb to be defined around this locus. Searching across the full cohort for this haplotype uncovered two additional apparently unrelated individuals with no known genealogical connection to the original kindred. All five participants with the defined haplotype were shown to share the rare variant by targeted Sanger sequencing. If this result were verified in a healthcare setting, it would be considered clinically actionable, and has been actioned in relatives ascertained independently through clinical presentation. The General Practitioners of four study participants with the rare variant were alerted to the research findings by letters outlining the phenotype (prolonged electrocardiographic QTc interval). A lack of detectable haplotype sharing between c.1750G > A; p.Gly584Ser chromosomes from previously reported individuals from Finland and those in this study from Shetland suggests that this mutation has arisen more than once in human history. This study showcases the potential value of isolate population-based research resources for genomic medicine. It also illustrates some challenges around communication of actionable findings in research participants in this context.

Identifying mouse developmental essential genes using machine learning

The genes that are required for organismal survival are annotated as ‘essential genes’. Identifying all the essential genes of an animal species can reveal critical functions that are needed during the development of the organism. To inform studies on mouse development, we developed a supervised machine learning classifier based on phenotype data from mouse knockout experiments. We used this classifier to predict the essentiality of mouse genes lacking experimental data. Validation of our predictions against a blind test set of recent mouse knockout experimental data indicated a high level of accuracy (>80%). We also validated our predictions for other mouse mutagenesis methodologies, demonstrating that the predictions are accurate for lethal phenotypes isolated in random chemical mutagenesis screens and embryonic stem cell screens. The biological functions that are enriched in essential and non-essential genes have been identified, showing that essential genes tend to encode intracellular proteins that interact with nucleic acids. The genome distribution of predicted essential and non-essential genes was analysed, demonstrating that the density of essential genes varies throughout the genome. A comparison with human essential and non-essential genes was performed, revealing conservation between human and mouse gene essentiality status. Our genome-wide predictions of mouse essential genes will be of value for the planning of mouse knockout experiments and phenotyping assays, for understanding the functional processes required during mouse development, and for the prioritisation of disease candidate genes identified in human genome and exome sequence datasets.

Summary: Here, we used computer-based machine learning methodology to predict which genes in the mouse genome are essential for development, and present a database of mouse essential and non-essential genes.

Mortality patterns in Southern Adriatic islands of Croatia: a registry-based study

Aim

To investigate the mortality patterns on the Southern Adriatic islands of Croatia and compare them with those in two, mainly coastal, mainland counties.

Methods

In this registry-based study we used the official mortality register data to analyze the mortality patterns on seven Croatian islands (Brač, Hvar, Korčula, Lastovo, Mljet, Šolta, and Vis) and Pelješac peninsula in the 1998-2013 period and calculated the average lifespan, life expectancy, and standardized mortality ratios (SMR). We compared the leading causes of death with those in the mainland population of two southernmost Croatian counties.

Results

The average lifespan of the island population was 3-10 years longer for men and 2-7 years longer for women than that on the mainland. All-cause SMRs were significantly lower for both men and women on Korčula, Brač, Mljet, and Pelješac but significantly higher for women on Šolta (1.22; 95% confidence intervals 1.07-1.38). The leading causes of death on the islands were cardiovascular diseases, with higher percentages in men and lower in women in comparison with those on the mainland. There were no substantial differences in the life expectancy at birth.

Conclusions

Despite longer lifespan, lack of differences in life expectancy at birth suggests that the recent generations of islanders no longer show beneficial mortality patterns, possibly due to diminishing adherence to the Mediterranean diet and lifestyle. Restoring the traditional lifestyles is a public health priority, with the ultimate aim of reducing inequalities and improving the health of island inhabitants.

Runs of homozygosity: windows into population history and trait architecture

Long runs of homozygosity (ROH) arise when identical haplotypes are inherited from each parent and thus a long tract of genotypes is homozygous. Cousin marriage or inbreeding gives rise to such autozygosity; however, genome-wide data reveal that ROH are universally common in human genomes even among outbred individuals. The number and length of ROH reflect individual demographic history, while the homozygosity burden can be used to investigate the genetic architecture of complex disease. We discuss how to identify ROH in genome-wide microarray and sequence data, their distribution in human populations and their application to the understanding of inbreeding depression and disease risk.

Slightly deleterious genomic variants and transcriptome perturbations in Down syndrome embryonic selection

The majority of aneuploid fetuses are spontaneously miscarried. Nevertheless, some aneuploid individuals survive despite the strong genetic insult. Here, we investigate if the survival probability of aneuploid fetuses is affected by the genome-wide burden of slightly deleterious variants. We analyzed two cohorts of live-born Down syndrome individuals (388 genotyped samples and 16 fibroblast transcriptomes) and observed a deficit of slightly deleterious variants on Chromosome 21 and decreased transcriptome-wide variation in the expression level of highly constrained genes. We interpret these results as signatures of embryonic selection, and propose a genetic handicap model whereby an individual bearing an extremely severe deleterious variant (such as aneuploidy) could escape embryonic lethality if the genome-wide burden of slightly deleterious variants is sufficiently low. This approach can be used to study the composition and effect of the numerous slightly deleterious variants in humans and model organisms.

Natural Knockouts: Natural Selection Knocked Out

In functional genomics studies, research is dedicated to unveiling the function of genes using gene-knockouts, model organisms in which a gene is artificially inactivated. The idea is that, by knocking out the gene, the provoked phenotype would inform us about the function of the gene. Still, the function of many genes cannot be elucidated, because disruption of conserved sequences, including protein-coding genes, often does not directly affect the phenotype. Since the phenomenon was first observed in the early nineties of the last century, these so-called 'no-phenotype knockouts' have met with great skepticism and resistance by died-in-the-wool selectionists. Still, functional genomics of the late 20th and early 21st centuries has taught us two important lessons. First, two or more unrelated genes can often substitute for each other; and second, some genes are only present in the genome in a silent state. In the laboratory, the disruption of such genes does not negatively influence reproductive success, and does not show measurable fitness effects of the species. The genes are redundant. Genetic redundancy, one of the big surprises of modern biology, can thus be defined as the condition in which the inactivation of a gene is selectively neutral. The no-phenotype knockout is not just a freak of the laboratory. Genetic variants known as homozygous loss-of-function (HLOF) variants are of considerable scientific and clinical interest, as they represent experiments of nature qualifying as "natural knockouts". Such natural knockouts challenge the conventional NeoDarwinian appraisal that genetic information is the result of natural selection acting on random genetic variation.

Settling the score: variant prioritization and Mendelian disease

When investigating Mendelian disease using exome or genome sequencing, distinguishing disease-causing genetic variants from the multitude of candidate variants is a complex, multidimensional task. Many prioritization tools and online interpretation resources exist, and professional organizations have offered clinical guidelines for review and return of prioritization results. In this Review, we describe the strengths and weaknesses of widely used computational approaches, explain their roles in the diagnostic and discovery process and discuss how they can inform (and misinform) expert reviewers. We place variant prioritization in the wider context of gene prioritization, burden testing and genotype-phenotype association, and we discuss opportunities and challenges introduced by whole-genome sequencing.

Forensic genetic analyses in isolated populations with examples of central European Valachs and Roma

Isolated populations present a constant threat to the correctness of forensic genetic casework. In this review article we present several examples of how analyzing samples from isolated populations can bias the results of the forensic statistics and analyses. We select our examples from isolated populations from central and southeastern Europe, namely the Valachs and the European Roma. We also provide the reader with general strategies and principles to improve the laboratory practice (best practice) and reporting of samples from supposedly isolated populations. These include reporting the precise population data used for computing the forensic statistics, using the appropriate θ correction factor for calculating allele frequencies, typing ancestry informative markers in samples of unknown or uncertain ethnicity and establishing ethnic-specific forensic databases.

Intellectual Disability & Rare Disorders: A Diagnostic Challenge

Rare disorders constitute a large and heterogeneous group of diagnoses of which many cause chronic disabilities with significant impact on the lives of affected individuals and their families as well as on the health-care system. Each individual disorder is rare, but when considered as a group, rare disorders are common with a total prevalence of approximately 6-8%. The clinical presentation of these disorders includes a broad diversity of symptoms and signs, often involving the nervous system and resulting in symptoms such as intellectual disability, neuropsychiatric disorders, epilepsy and motor dysfunction. The methods for establishing an etiological diagnosis in patients with rare disorders have improved dramatically during recent years. With the introduction of genomic screening methods, it has been shown that the cause is genetic in the majority of the patients and many will receive an etiological diagnosis in a clinical setting. However, there are a lot of challenges in diagnosing these disorders and despite recent years' advances, a large number of patients with rare disorders still go without an etiological diagnosis. In this chapter we will review the etiology of rare disorders with focus on intellectual disability and what has been learned from massive parallel sequencing studies in deciphering the genetic basis. Furthermore, we will discuss challenges in the etiological diagnostics of these disorders including issues that regard interpretation of the numerous genetic variants detected by genomic screening methods and challenges in the translation of massive parallel sequencing technologies into clinical practice.

The impact of recent population history on the deleterious mutation load in humans and close evolutionary relatives

Over the past decade, there has been both great interest and confusion about whether recent demographic events-notably the Out-of-Africa-bottleneck and recent population growth-have led to differences in mutation load among human populations. The confusion can be traced to the use of different summary statistics to measure load, which lead to apparently conflicting results. We argue, however, that when statistics more directly related to load are used, the results of different studies and data sets consistently reveal little or no difference in the load of non-synonymous mutations among human populations. Theory helps to understand why no such differences are seen, as well as to predict in what settings they are to be expected. In particular, as predicted by modeling, there is evidence for changes in the load of recessive loss of function mutations in founder and inbred human populations. Also as predicted, eastern subspecies of gorilla, Neanderthals and Denisovans, who are thought to have undergone reductions in population sizes that exceed the human Out-of-Africa bottleneck in duration and severity, show evidence for increased load of non-synonymous mutations (relative to western subspecies of gorillas and modern humans, respectively). A coherent picture is thus starting to emerge about the effects of demographic history on the mutation load in populations of humans and close evolutionary relatives.

Translational plasticity facilitates the accumulation of nonsense genetic variants in the human population

Genetic variants that disrupt protein-coding DNA are ubiquitous in the human population, with about 100 such loss-of-function variants per individual. While most loss-of-function variants are rare, a subset have risen to high frequency and occur in a homozygous state in healthy individuals. It is unknown why these common variants are well tolerated, even though some affect essential genes implicated in Mendelian disease. Here, we combine genomic, proteomic, and biochemical data to demonstrate that many common nonsense variants do not ablate protein production from their host genes. We provide computational and experimental evidence for diverse mechanisms of gene rescue, including alternative splicing, stop codon readthrough, alternative translation initiation, and C-terminal truncation. Our results suggest a molecular explanation for the mild fitness costs of many common nonsense variants and indicate that translational plasticity plays a prominent role in shaping human genetic diversity.

Testing the role of predicted gene knockouts in human anthropometric trait variation

Although the role of complete gene inactivation by two loss-of-function mutations inherited in trans is well-established in recessive Mendelian diseases, we have not yet explored how such gene knockouts (KOs) could influence complex human phenotypes. Here, we developed a statistical framework to test the association between gene KOs and quantitative human traits. Our method is flexible, publicly available, and compatible with common genotype format files (e.g. PLINK and vcf). We characterized gene KOs in 4498 participants from the NHLBI Exome Sequence Project (ESP) sequenced at high coverage (>100×), 1976 French Canadians from the Montreal Heart Institute Biobank sequenced at low coverage (5.7×), and >100 000 participants from the Genetic Investigation of ANthropometric Traits (GIANT) Consortium genotyped on an exome array. We tested associations between gene KOs and three anthropometric traits: body mass index (BMI), height and BMI-adjusted waist-to-hip ratio (WHR). Despite our large sample size and multiple datasets available, we could not detect robust associations between specific gene KOs and quantitative anthropometric traits. Our results highlight several limitations and challenges for future gene KO studies in humans, in particular when there is no prior knowledge on the phenotypes that might be affected by the tested gene KOs. They also suggest that gene KOs identified with current DNA sequencing methodologies probably do not strongly influence normal variation in BMI, height, and WHR in the general human population.