On the allelic spectrum of human disease

Human disease genes show enormous variation in their allelic spectra; that is, in the number and population frequency of the disease-predisposing alleles at the loci. For some genes, there are a few predominant disease alleles. For others, there is a wide range of disease alleles, each relatively rare. The allelic spectrum is important: disease genes with only a few deleterious alleles can be more readily identified and are more amenable to clinical testing. Here, we weave together strands from the human mutation and population genetics literature to provide a framework for understanding and predicting the allelic spectra of disease genes. The theory does a reasonable job for diseases where the genetic etiology is well understood. It also has bearing on the Common Disease/Common Variants (CD/CV) hypothesis, predicting that at loci where the total frequency of disease alleles is not too small, disease loci will have relatively simple spectra.     

Using mouse forward genetics to define novel target space

Rapid advances in genomics technologies have identified a wealth of new therapeutic targets, but typically these targets are weakly validated with only circumstantial evidence to link them to human disease. The next challenge is testing gene-to-disease connections in a relevant animal model, a time-consuming and uncertain process using conventional reverse-genetic approaches such as knockout and transgenic mice. By contrast, forward genetics proceeds by measuring a physiological process that is relevant to disease, then identifying the gene products that impinge on this process. This ‘phenotype-first’ approach solves the bottleneck of target validation by using clinically relevant assays in a mammalian whole-animal system as a discovery platform. As an unbiased approach to gene discovery and validation, forward genetics will identify novel drug targets and increase the success rate of drug development.     

Negative selection on BRCA1 susceptibility alleles sheds light on the population genetics of late-onset diseases and aging theory

The magnitude of negative selection on alleles involved in age-specific mortality decreases with age. This is the foundation of the evolutionary theory of senescence. Because of this decrease in negative selection with age, and because of the absence of reproduction after menopause, alleles involved in women's late-onset diseases are generally considered evolutionarily neutral. Recently, genetic and epidemiological data on alleles involved in late onset-diseases have become available. It is therefore timely to estimate selection on these alleles. Here, we estimate selection on BRCA1 alleles leading to susceptibility to late-onset breast and ovarian cancer. For this, we integrate estimates of the risk of developing a cancer for BRCA1-carriers into population genetics frameworks, and calculate selection coefficients on BRCA1 alleles for different demographic scenarios varying across the extent of human demography. We then explore the magnitude of negative selection on alleles leading to a diverse range of risk patterns, to capture a variety of late-onset diseases. We show that BRCA1 alleles may have been under significant negative selection during human history. Although the mean age of onset of the disease is long after menopause, variance in age of onset means that there are always enough cases occurring before the end of reproductive life to compromise the selective value of women carrying a susceptibility allele in BRCA1. This seems to be the case for an extended range of risk of onset functions varying both in mean and variance. This finding may explain the distribution of BRCA1 alleles' frequency, and also why alleles for many late-onset diseases, like certain familial forms of cancer, coronary artery diseases and Alzheimer dementia, are typically recent and rare. Finally, we discuss why the two most popular evolutionary theories of aging, mutation accumulation and antagonistic pleiotropy, may underestimate the effect of selection on survival at old ages.     

What canCaenorhabditis elegans tell us about nematocides and parasites?

Nematode infections compromise human health and reduce agricultural productivity. Experiments that exploit the powerful molecular genetics of the free-living nematodeCaenorhabditis elegans have contributed to our understanding of how the major classes of anthelmintic nematocides kill worms and how worms might evolve resistance to these drugs. InC. elegans, as in parasites, benzimidizoles interfere with microtubule polymerization, the imidazothiazoles/tetrahydropyrimidines activate nicotinic acetylcholine receptors, and the macrocyclic lactones activate glutamate-gated chloride channels. Mutant alleles of genes that encode drug targets often confer resistance inC. elegans. Preliminary evidence suggests that alleles of homologous genes in parasites will, in many cases, also play a role in resistance. Thus, information acquired fromC. elegans can be usefully applied to understand the mechanisms of drug sensitivity and the genetics of resistance in parasites.     

Unravelling the effects of the environment and host genotype on the gut microbiome

To what extent do host genetics control the composition of the gut microbiome? Studies comparing the gut microbiota in human twins and across inbred mouse lines have yielded inconsistent answers to this question. However, candidate gene approaches, in which one gene is deleted or added to a model host organism, show that a single host gene can have a tremendous effect on the diversity and population structure of the gut microbiota. Now, quantitative genetics is emerging as a highly promising approach that can be used to better understand the overall architecture of host genetic influence on the microbiota, and to discover additional host genes controlling microbial diversity in the gut. In this Review, we describe how host genetics and the environment shape the microbiota, and how these three factors may interact in the context of chronic disease.     

Critical review of NGS analyses for de novo genotyping multigene families

The genotyping of highly polymorphic multigene families across many individuals used to be a particularly challenging task because of methodological limitations associated with traditional approaches. Next‐generation sequencing (NGS) can overcome most of these limitations, and it is increasingly being applied in population genetic studies of multigene families. Here, we critically review NGS bioinformatic approaches that have been used to genotype the major histocompatibility complex (MHC) immune genes, and we discuss how the significant advances made in this field are applicable to population genetic studies of gene families. Increasingly, approaches are introduced that apply thresholds of sequencing depth and sequence similarity to separate alleles from methodological artefacts. We explain why these approaches are particularly sensitive to methodological biases by violating fundamental genotyping assumptions. An alternative strategy that utilizes ultra‐deep sequencing (hundreds to thousands of sequences per amplicon) to reconstruct genotypes and applies statistical methods on the sequencing depth to separate alleles from artefacts appears to be more robust. Importantly, the ‘degree of change’ (DOC) method avoids using arbitrary cut‐off thresholds by looking for statistical boundaries between the sequencing depth for alleles and artefacts, and hence, it is entirely repeatable across studies. Although the advances made in generating NGS data are still far ahead of our ability to perform reliable processing, analysis and interpretation, the community is developing statistically rigorous protocols that will allow us to address novel questions in evolution, ecology and genetics of multigene families. Future developments in third‐generation single molecule sequencing may potentially help overcome problems that still persist in de novo multigene amplicon genotyping when using current second‐generation sequencing approaches.     

Population Growth Inflates the Per-Individual Number of Deleterious Mutations and Reduces Their Mean Effect

This study addresses the question of how purifying selection operates during recent rapid population growth such as has been experienced by human populations. This is not a straightforward problem because the human population is not at equilibrium: population genetics predicts that, on the one hand, the efficacy of natural selection increases as population size increases, eliminating ever more weakly deleterious variants; on the other hand, a larger number of deleterious mutations will be introduced into the population and will be more likely to increase in their number of copies as the population grows. To understand how patterns of human genetic variation have been shaped by the interaction of natural selection and population growth, we examined the trajectories of mutations with varying selection coefficients, using computer simulations. We observed that while population growth dramatically increases the number of deleterious segregating sites in the population, it only mildly increases the number carried by each individual. Our simulations also show an increased efficacy of natural selection, reflected in a higher fraction of deleterious mutations eliminated at each generation and a more efficient elimination of the most deleterious ones. As a consequence, while each individual carries a larger number of deleterious alleles than expected in the absence of growth, the average selection coefficient of each segregating allele is less deleterious. Combined, our results suggest that the genetic risk of complex diseases in growing populations might be distributed across a larger number of more weakly deleterious rare variants.     

The mosquito genome: organization, evolution and manipulation

Apart from the genetic flexibility of the vectors, impediments to the control of vector-borne diseases include the rapid spread of drug resistance throughout parasite populations, the increasing movement of people to and from disease-endemic regions and the limited funds and public health infrastructures of most developing countries. The widely used residual insecticides and antiparasitic drugs have been inadequate solutions to the problem of vector-borne disease control. New approaches are needed. The enormous impact of recent developments in molecular genetics on the understanding of basic biology and human disease has stimulated a re-examination of the prospects for genetic manipulation of vector populations as a means for reducing or eliminating vector-borne diseases, especially malarial. Although control scenarios that exploit this technology may never be realized, Nora Besansky and Frank Collins emphasize that the increase in knowledge of basic mosquito biology on which these ideas depend will inevitably stimulate novel approaches to the control of mosquito-borne diseases.     

Targeting Synaptic Dysfunction in Alzheimer’s Disease Therapy

In the past years, major efforts have been made to understand the genetics and molecular pathogenesis of Alzheimer??s disease (AD), which has been translated into extensive experimental approaches aimed at slowing down or halting disease progression. Advances in transgenic (Tg) technologies allowed the engineering of different mouse models of AD recapitulating a range of AD-like features. These Tg models provided excellent opportunities to analyze the bases for the temporal evolution of the disease. Several lines of evidence point to synaptic dysfunction as a cause of AD and that synapse loss is a pathological correlate associated with cognitive decline. Therefore, the phenotypic characterization of these animals has included electrophysiological studies to analyze hippocampal synaptic transmission and long-term potentiation, a widely recognized cellular model for learning and memory. Transgenic mice, along with non-Tg models derived mainly from exogenous application of A??, have also been useful experimental tools to test the various therapeutic approaches. As a result, numerous pharmacological interventions have been reported to attenuate synaptic dysfunction and improve behavior in the different AD models. To date, however, very few of these findings have resulted in target validation or successful translation into disease-modifying compounds in humans. Here, we will briefly review the synaptic alterations across the different animal models and we will recapitulate the pharmacological strategies aimed at rescuing hippocampal plasticity phenotypes. Finally, we will highlight intrinsic limitations in the use of experimental systems and related challenges in translating preclinical studies into human clinical trials.     

Characterization of microsatellite loci in Festuca gautieri (Poaceae) and transferability to F. eskia and F. xpicoeuropeana

? Premise of the study: Enriched genomic libraries were used to isolate and characterize microsatellite loci in Festuca gautieri, an important plant component of subalpine calcareous grasslands of the eastern Iberian Peninsula, the Pyrenees, and the Cantabrian Mountains. Microsatellites were required to investigate landscape genetics across its distribution range and at a narrower geographical scale within the Ordesa y Monte Perdido, Aigüestortes, and Picos de Europa Spanish national parks. ? Methods and Results: Ten polymorphic microsatellite loci were characterized. They amplified a total of 116 alleles in a sample of 30 individuals of F. gautieri, showing high levels of genetic diversity (expected heterozygosity = 0.821). Cross-species transferability to two other close congeners, F. eskia and F ×picoeuropeana, increased the total number of alleles to 137. These taxa showed lower numbers of alleles but similar levels of genetic diversity to F. gautieri. ? Conclusions: These microsatellite primers will be useful in population and landscape genetics and in establishing conservation strategies for these characteristic elements of subalpine pastures.     

Type 2 diabetes risk alleles demonstrate extreme directional differentiation among human populations, compared to other diseases

Many disease-susceptible SNPs exhibit significant disparity in ancestral and derived allele frequencies across worldwide populations. While previous studies have examined population differentiation of alleles at specific SNPs, global ethnic patterns of ensembles of disease risk alleles across human diseases are unexamined. To examine these patterns, we manually curated ethnic disease association data from 5,065 papers on human genetic studies representing 1,495 diseases, recording the precise risk alleles and their measured population frequencies and estimated effect sizes. We systematically compared the population frequencies of cross-ethnic risk alleles for each disease across 1,397 individuals from 11 HapMap populations, 1,064 individuals from 53 HGDP populations, and 49 individuals with whole-genome sequences from 10 populations. Type 2 diabetes (T2D) demonstrated extreme directional differentiation of risk allele frequencies across human populations, compared with null distributions of European-frequency matched control genomic alleles and risk alleles for other diseases. Most T2D risk alleles share a consistent pattern of decreasing frequencies along human migration into East Asia. Furthermore, we show that these patterns contribute to disparities in predicted genetic risk across 1,397 HapMap individuals, T2D genetic risk being consistently higher for individuals in the African populations and lower in the Asian populations, irrespective of the ethnicity considered in the initial discovery of risk alleles. We observed a similar pattern in the distribution of T2D Genetic Risk Scores, which are associated with an increased risk of developing diabetes in the Diabetes Prevention Program cohort, for the same individuals. This disparity may be attributable to the promotion of energy storage and usage appropriate to environments and inconsistent energy intake. Our results indicate that the differential frequencies of T2D risk alleles may contribute to the observed disparity in T2D incidence rates across ethnic populations.     

Multiple drug resistance genes in malaria -- from epistasis to epidemiology

A decline in our ability to successfully treat patients with malaria infections of the parasitic protozoan Plasmodium falciparum with cheap quinoline drugs has led to a huge escalation in morbidity and mortality in recent years. Many approaches have been taken, including classical genetics, reverse genetics and molecular epidemiology, to identify the molecular determinants underlying this resistance. The contribution of the P. falciparum multidrug resistance gene, pfmdr1, to antimalarial resistance has been a source of controversy for over a decade since it was first identified. In the current issue of Molecular Microbiology, Sidhu and colleagues use powerful reverse genetics to demonstrate the importance of commonly occurring alleles of pfmdr1 in conferring resistance to the second-line drugs quinine and sensitivity to the new alternatives mefloquine and artemisinin. They also elegantly highlight the importance of genetic background and epistasis between pfmdr1 and other potential modulators of drug resistance. Such molecular knowledge will facilitate surveillance/monitoring and aid the development of strategies for the reversal of resistance.     

Human monogenic disorders - a source of novel drug targets

The decrease in new drug applications and approvals over the past several years results from an underlying crisis in drug target identification and validation. Model organisms are being used to address this problem, in combination with novel approaches such as the International HapMap Project. What has been underappreciated is that discovery of new drug targets can also be revived by traditional Mendelian genetics. A large fraction of the human gene repertoire remains phenotypically uncharacterized, and is likely to encode many unanticipated and novel phenotypes that will be of interest to pharmaceutical and biotechnological drug developers.     

New microsatellite loci for Narcissus papyraceus (Amarillydaceae) and cross-amplification in other congeneric species

? Premise of the study: Microsatellite loci from a genomic library of the species Narcissus papyraceus were optimized and characterized for studies of population genetics. ? Methods and Results: Eleven markers that were successfully amplified showed polymorphism when tested on 50 individuals from two populations in southern Spain and northern Morocco. Overall, the number of alleles per locus ranged between 4 and 15. Between 8 and 11 loci successfully amplified in other eight Narcissus species. ? Conclusions: These markers will enable genetic diversity studies of N. papyraceus across its distribution range and conduct paternity analyses among individuals differing in flower morphology.     

Towards the genetic analysis of mulfactorial diseases: the estimation of allele frequency and epistasis

OBJECTIVES: The general aim of this paper is to reactivate the original intention behind the Elston-Stewart algorithm: i.e. physiological characterisation of the effects of individual loci underlying quantitative variation. The specific aim is the estimation of allele frequency and epistasis in multifactorial genetic diseases. METHODS: In a general genetic model, the probability of disease is a sigmoid function of the number of disease alleles summed over all loci. This model has just 4 parameters: the number of loci; the population frequency of disease alleles; a threshold expressed as a proportion of disease alleles; and the slope of the sigmoid curve. Assuming 10 loci, the remaining parameters can be estimated from empirical data: population frequency of the disease, monozygotic twin concordance rates, and disease frequency in sibs of affected probands. RESULTS: For 10 typical multifactorial diseases, the estimates of allele frequency are generally high, of the order of 20%, with strong epistatic interactions between loci. It follows that the frequencies of subphenotypes specific for a single disease locus will also be high, and only about two-fold greater in affected individuals than in normal controls. CONCLUSIONS: Because of allelic heterogeneity, purely genomic approaches are unlikely to succeed in unravelling the genetics of multifactorial diseases; this will rather require articulation with physiology and the identification of biologically meaningful subphenotypes.     

CRISPR: a versatile tool for both forward and reverse genetics research

Human genetics research employs the two opposing approaches of forward and reverse genetics. While forward genetics identifies and links a mutation to an observed disease etiology, reverse genetics induces mutations in model organisms to study their role in disease. In most cases, causality for mutations identified by forward genetics is confirmed by reverse genetics through the development of genetically engineered animal models and an assessment of whether the model can recapitulate the disease. While many technological advances have helped improve these approaches, some gaps still remain. CRISPR/Cas (clustered regularly interspaced short palindromic repeats/CRISPR-associated), which has emerged as a revolutionary genetic engineering tool, holds great promise for closing such gaps. By combining the benefits of forward and reverse genetics, it has dramatically expedited human genetics research. We provide a perspective on the power of CRISPR-based forward and reverse genetics tools in human genetics and discuss its applications using some disease examples.     

Characterization of 10 microsatellite loci in an avian louse, Degeeriella regalis (Phthiraptera: Ischnocera: Philopteridae)

We isolated and characterized 10 polymorphic microsatellite loci in an ischnoceran louse, Degeeriella regalis, which parasitizes the threatened Galápagos hawk (Buteo galapagoensis) and other falconiform birds. The loci were screened across 30 individuals from two island populations in the Galápagos Islands. The number of alleles per locus ranged from two to 28. Polymorphic information content ranged from 0.14 to 0.94 and observed heterozygosity ranged from 0 to 0.67. These markers will be valuable in comparative population genetics studies in this species, which is the focus of a long-term population and disease ecology research program.     

History of genetic disease: the molecular genetics of Huntington disease - a history

The Huntington disease gene was mapped to human chromosome 4p in 1983 and 10 years later the pathogenic mutation was identified as a CAG-repeat expansion. Our current understanding of the molecular pathogenesis of Huntington disease could never have been achieved without the recent progress in the field of molecular genetics. We are now equipped with powerful genetic models that continue to uncover new aspects of the pathogenesis of Huntington disease and will be instrumental for the development of therapeutic approaches for this disease.