Human Genetics Community Research Articles

ERRATUM: Genetic testing for inherited cardiovascular diseases. A position statement of the Polish Cardiac Society endorsed by Polish Society of Human Genetics and Cardiovascular Patient Communities.

According to the latest guidelines of European and American medical societies, genetic testing (GT) is essential in cardiovascular diseases for establishing diagnosis, predicting prognosis, enabling initiation of disease-modifying therapy, and preventing sudden cardiac death. The GT result may be relevant for cascade GT in the patient's relatives, for planning his/her profession and physical activity, and for procreative counseling. This position statement has been prepared due to the scarcity of GT in cardiovascular diseases in Poland and the need to expand its availability. We give a concise description of the genetic background of cardiomyopathies, channelopathies, aortopathies, familial hypercholesterolemia, pheochromocytomas, and paragangliomas. The article discusses various aspects of GT in specific populations, such as children or athletes, and also presents prenatal genetic diagnostics. We propose recommendations for GT and counselling, which take into account Polish needs and capabilities. We give an outline of legal regulations, good clinical practice in GT with respect for patient rights, the role of cardiologists and clinical geneticists in GT planning and post-test counseling, and the requirements for laboratories performing genetic tests. The Polish Cardiac Society and Polish Society of Human Genetics experts speak with one voice with cardiovascular patient communities to underline the need for a law on GT and increasing the availability of GT for cardiovascular patients.

A PLURIPOTENT STEM CELL PLATFORM FOR IN VITRO SYSTEMS GENETICS STUDIES OF MOUSE DEVELOPMENT.

The directed differentiation of pluripotent stem cells (PSCs) from panels of genetically diverse individuals is emerging as a powerful experimental system for characterizing the impact of natural genetic variation on developing cell types and tissues. Here, we establish new PSC lines and experimental approaches for modeling embryonic development in a genetically diverse, outbred mouse stock (Diversity Outbred mice). We show that a range of inbred and outbred PSC lines can be stably maintained in the primed pluripotent state (epiblast stem cells -- EpiSCs) and establish the contribution of genetic variation to phenotypic differences in gene regulation and directed differentiation. Using pooled in vitro fertilization, we generate and characterize a genetic reference panel of Diversity Outbred PSCs (n = 230). Finally, we demonstrate the feasibility of pooled culture of Diversity Outbred EpiSCs as "cell villages", which can facilitate the differentiation of large numbers of EpiSC lines for forward genetic screens. These data can complement and inform similar efforts within the stem cell biology and human genetics communities to model the impact of natural genetic variation on phenotypic variation and disease-risk.

Genetic testing for inherited cardiovascular diseases. A position statement of the Polish Cardiac Society endorsed by Polish Society of Human Genetics and Cardiovascular Patient Communities.

According to the latest guidelines of European and American medical societies, genetic testing (GT) is essential in cardiovascular diseases for establishing diagnosis, predicting prognosis, enabling initiation of disease-modifying therapy, and preventing sudden cardiac death. The GT result may be relevant for cascade GT in the patient's relatives, for planning his/her profession and physical activity, and for procreative counseling. This position statement has been prepared due to the scarcity of GT in cardiovascular diseases in Poland and the need to expand its availability. We give a concise description of the genetic background of cardiomyopathies, channelopathies, aortopathies, familial hypercholesterolemia, pheochromocytomas, and paragangliomas. The article discusses various aspects of GT in specific populations, such as children or athletes, and also presents prenatal genetic diagnostics. We propose recommendations for GT and counselling, which take into account Polish needs and capabilities. We give an outline of legal regulations, good clinical practice in GT with respect for patient rights, the role of cardiologists and clinical geneticists in GT planning and post-test counseling, and the requirements for laboratories performing genetic tests. The Polish Cardiac Society and Polish Society of Human Genetics experts speak with one voice with cardiovascular patient communities to underline the need for a law on GT and increasing the availability of GT for cardiovascular patients.

MbQTL: an R/Bioconductor package for microbial quantitative trait loci (QTL) estimation.

In recent years, significant strides have been made in the field of genomics, with the commencement of large-scale studies aimed at collecting host mutational profiles and microbiome data. The amalgamation of host gene mutational profiles in both healthy and diseased subjects with microbial abundance data holds immense promise in providing insights into several crucial research questions, including the development and progression of diseases, as well as individual responses to therapeutic interventions. With the advent of sequencing methods such as 16s ribosomal RNA (rRNA) sequencing and whole genome sequencing, there is increasing evidence of interplay of human genetics and microbial communities. Quantitative trait loci associated with microbial abundance (mbQTLs), are genetic variants that influence the abundance of microbial populations within the host. Here, we introduce mbQTL, the first R package integrating 16S ribosomal RNA (rRNA) sequencing and single-nucleotide variation (SNV) and single-nucleotide polymorphism (SNP) data. We describe various statistical methods implemented for the identification of microbe-SNV pairs, relevant statistical measures, and plot functionality for interpretation. mbQTL is available on bioconductor at https://bioconductor.org/packages/mbQTL/.

The intersection of genetics and COVID-19 in 2021: preview of the 2021 Rodney Howell Symposium

The intersection of genetics and COVID-19 in 2021: preview of the 2021 Rodney Howell Symposium

"Arte et Labore"-A Blackburn Rovers fan's legacy in human complex trait genetics.

Through his own research contributions on the modelling and genetic analysis of quantitative traits and through his former students and postdocs, Robin Thompson has indirectly left a major legacy in human genetics. In this short note, we highlight examples of the long-lasting relevance and impact of Robin's work in human genetics. A lone early study of marker-assisted selection developed many of the tools and approaches later exploited (often after reinvention) by the human genetics community in GWAS studies and for prediction. Furthermore, a particularly clear example of the pervasive impact of Robin's work is that REML has become the default method to estimate variance components and that genetic predictions exploiting linkage disequilibrium in the population are starting to become used in precision medicine applications.

BrainImageR: spatiotemporal gene set analysis referencing the human brain.

Neuronal analyses such as transcriptomics, epigenetics and genome-wide association studies must be assessed in the context of the human brain to generate biologically meaningful inferences. It is often difficult to access primary human brain tissue; therefore, approximations are made using alternative sources such as peripheral tissues or invitro-derived neurons. Gene sets from these studies are then assessed for their association with the post-mortem human brain. However, most analyses of post-mortem datasets are achieved by building new computational tools each time in-house, which can cause discrepancies from study to study. The field is in need of a user-friendly tool to examine spatiotemporal expression with respect to the postmortem brain. Such a tool will be of use in the molecular interrogation of neurological and psychiatric disorders, with direct advantages for the disease-modeling and human genetics communities. We have developed brainImageR, an R package that calculates both the spatial and temporal association of a dataset with post-mortem human brain. BrainImageR identifies anatomical regions enriched for candidate gene set expression. It further predicts the developmental time point of the sample, a task that has become increasingly important in the field of invitro neuronal modeling. These functionalities of brainImageR enable a quick and efficient characterization of a given dataset across normal human brain development. BrainImageR is released under the Creative Commons CC BY-SA 4.0 license and can be accessed directly at brainimager.salk.edu or the R code can be downloaded through github at https://github.com/saralinker/brainImageR.

From "Personalized" to "Precision" Medicine: The Ethical and Social Implications of Rhetorical Reform in Genomic Medicine.

Since the late 1980s, the human genetics and genomics research community has been promising to usher in a "new paradigm for health care"-one that uses molecular profiling to identify human genetic variants implicated in multifactorial health risks. After the completion of the Human Genome Project in 2003, a wide range of stakeholders became committed to this "paradigm shift," creating a confluence of investment, advocacy, and enthusiasm that bears all the marks of a "scientific/intellectual social movement" within biomedicine. Proponents of this movement usually offer four ways in which their approach to medical diagnosis and health care improves upon current practices, arguing that it is more "personalized," "predictive," "preventive," and "participatory" than the medical status quo. Initially, it was personalization that seemed to best sum up the movement's appeal. By 2012, however, powerful opinion leaders were abandoning "personalized medicine" in favor of a new label: "precision medicine." The new label received a decisive seal of approval when, in January 2015, President Obama unveiled plans for a national "precision medicine initiative" to promote the development and use of genomic tools in health care.

Evaluating Imputation Algorithms for Low-Depth Genotyping-By-Sequencing (GBS) Data.

Well-powered genomic studies require genome-wide marker coverage across many individuals. For non-model species with few genomic resources, high-throughput sequencing (HTS) methods, such as Genotyping-By-Sequencing (GBS), offer an inexpensive alternative to array-based genotyping. Although affordable, datasets derived from HTS methods suffer from sequencing error, alignment errors, and missing data, all of which introduce noise and uncertainty to variant discovery and genotype calling. Under such circumstances, meaningful analysis of the data is difficult. Our primary interest lies in the issue of how one can accurately infer or impute missing genotypes in HTS-derived datasets. Many of the existing genotype imputation algorithms and software packages were primarily developed by and optimized for the human genetics community, a field where a complete and accurate reference genome has been constructed and SNP arrays have, in large part, been the common genotyping platform. We set out to answer two questions: 1) can we use existing imputation methods developed by the human genetics community to impute missing genotypes in datasets derived from non-human species and 2) are these methods, which were developed and optimized to impute ascertained variants, amenable for imputation of missing genotypes at HTS-derived variants? We selected Beagle v.4, a widely used algorithm within the human genetics community with reportedly high accuracy, to serve as our imputation contender. We performed a series of cross-validation experiments, using GBS data collected from the species Manihot esculenta by the Next Generation (NEXTGEN) Cassava Breeding Project. NEXTGEN currently imputes missing genotypes in their datasets using a LASSO-penalized, linear regression method (denoted ‘glmnet’). We selected glmnet to serve as a benchmark imputation method for this reason. We obtained estimates of imputation accuracy by masking a subset of observed genotypes, imputing, and calculating the sample Pearson correlation between observed and imputed genotype dosages at the site and individual level; computation time served as a second metric for comparison. We then set out to examine factors affecting imputation accuracy, such as levels of missing data, read depth, minor allele frequency (MAF), and reference panel composition.

Privacy Risks from Genomic Data-Sharing Beacons

The human genetics community needs robust protocols that enable secure sharing of genomic data from participants in genetic research. Beacons are web servers that answer allele-presence queries—such as “Do you have a genome that has a specific nucleotide (e.g., A) at a specific genomic position (e.g., position 11,272 on chromosome 1)?”—with either “yes” or “no.” Here, we show that individuals in a beacon are susceptible to re-identification even if the only data shared include presence or absence information about alleles in a beacon. Specifically, we propose a likelihood-ratio test of whether a given individual is present in a given genetic beacon. Our test is not dependent on allele frequencies and is the most powerful test for a specified false-positive rate. Through simulations, we showed that in a beacon with 1,000 individuals, re-identification is possible with just 5,000 queries. Relatives can also be identified in the beacon. Re-identification is possible even in the presence of sequencing errors and variant-calling differences. In a beacon constructed with 65 European individuals from the 1000 Genomes Project, we demonstrated that it is possible to detect membership in the beacon with just 250 SNPs. With just 1,000 SNP queries, we were able to detect the presence of an individual genome from the Personal Genome Project in an existing beacon. Our results show that beacons can disclose membership and implied phenotypic information about participants and do not protect privacy a priori. We discuss risk mitigation through policies and standards such as not allowing anonymous pings of genetic beacons and requiring minimum beacon sizes.

Of mice and cats (both calico): Mary F Lyon, FRS (1925-2014).

Of mice and cats (both calico): Mary F Lyon, FRS (1925-2014).

Complex host genetics influence the microbiome in inflammatory bowel disease.

BackgroundHuman genetics and host-associated microbial communities have been associated independently with a wide range of chronic diseases. One of the strongest associations in each case is inflammatory bowel disease (IBD), but disease risk cannot be explained fully by either factor individually. Recent findings point to interactions between host genetics and microbial exposures as important contributors to disease risk in IBD. These include evidence of the partial heritability of the gut microbiota and the conferral of gut mucosal inflammation by microbiome transplant even when the dysbiosis was initially genetically derived. Although there have been several tests for association of individual genetic loci with bacterial taxa, there has been no direct comparison of complex genome-microbiome associations in large cohorts of patients with an immunity-related disease.MethodsWe obtained 16S ribosomal RNA (rRNA) gene sequences from intestinal biopsies as well as host genotype via Immunochip in three independent cohorts totaling 474 individuals. We tested for correlation between relative abundance of bacterial taxa and number of minor alleles at known IBD risk loci, including fine mapping of multiple risk alleles in the Nucleotide-binding oligomerization domain-containing protein 2 (NOD2) gene exon. We identified host polymorphisms whose associations with bacterial taxa were conserved across two or more cohorts, and we tested related genes for enrichment of host functional pathways.ResultsWe identified and confirmed in two cohorts a significant association between NOD2 risk allele count and increased relative abundance of Enterobacteriaceae, with directionality of the effect conserved in the third cohort. Forty-eight additional IBD-related SNPs have directionality of their associations with bacterial taxa significantly conserved across two or three cohorts, implicating genes enriched for regulation of innate immune response, the JAK-STAT cascade, and other immunity-related pathways.ConclusionsThese results suggest complex interactions between genetically altered host functional pathways and the structure of the microbiome. Our findings demonstrate the ability to uncover novel associations from paired genome-microbiome data, and they suggest a complex link between host genetics and microbial dysbiosis in subjects with IBD across independent cohorts.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-014-0107-1) contains supplementary material, which is available to authorized users.

BGMUT Database of Allelic Variants of Genes Encoding Human Blood Group Antigens

The Blood group antigen Gene MUTation (BGMUT) database documents variations in genes of human blood group systems. In March 2014, the database, accessible at www.ncbi.nlm.nih.gov/gv/mhc/xslcgi.cgi?cmd=bgmut, listed 1,545 alleles of 44 genes of 34 blood group systems. Besides allelic information, the BGMUT resource also presents comprehensive and current information on blood group systems. This review describes the database and notes its utility for the transfusion medicine and human genetics communities.

Impact of prenatal technologies on the sex ratio in India: an overview.

The fact that techniques of prenatal diagnosis are used in India and China to selectively eliminate females is widely known. It has been extensively reported in the international media and in scientific publications since the 1990s. The publication of the Census of India 2011 shows that the ratio of girls to boys below the age of 6 years continues to decline at an alarming rate. Following that publication, this topic has again received international attention. The aim of this article is to better inform the human genetics community of the magnitude of this practice and its consequences in India.In this overview, we examine the impact of prenatal technology on the sex ratio in India. We present facts and figures from the Census of India and other publications that show that the practice is wide spread throughout India, in urban and rural areas, among the rich and the poor, and among the educated and the illiterate. We also briefly discuss the possible causes, consequences, and solutions.Genet Med 16 6, 425–432.

A survey of tools for variant analysis of next-generation genome sequencing data

Recent advances in genome sequencing technologies provide unprecedented opportunities to characterize individual genomic landscapes and identify mutations relevant for diagnosis and therapy. Specifically, whole-exome sequencing using next-generation sequencing (NGS) technologies is gaining popularity in the human genetics community due to the moderate costs, manageable data amounts and straightforward interpretation of analysis results. While whole-exome and, in the near future, whole-genome sequencing are becoming commodities, data analysis still poses significant challenges and led to the development of a plethora of tools supporting specific parts of the analysis workflow or providing a complete solution. Here, we surveyed 205 tools for whole-genome/whole-exome sequencing data analysis supporting five distinct analytical steps: quality assessment, alignment, variant identification, variant annotation and visualization. We report an overview of the functionality, features and specific requirements of the individual tools. We then selected 32 programs for variant identification, variant annotation and visualization, which were subjected to hands-on evaluation using four data sets: one set of exome data from two patients with a rare disease for testing identification of germline mutations, two cancer data sets for testing variant callers for somatic mutations, copy number variations and structural variations, and one semi-synthetic data set for testing identification of copy number variations. Our comprehensive survey and evaluation of NGS tools provides a valuable guideline for human geneticists working on Mendelian disorders, complex diseases and cancers.

The Centers for Mendelian Genomics: a new large-scale initiative to identify the genes underlying rare Mendelian conditions.

Next generation exome sequencing (ES) and whole genome sequencing (WGS) are new powerful tools for discovering the gene(s) that underlie Mendelian disorders. To accelerate these discoveries, the National Institutes of Health has established three Centers for Mendelian Genomics (CMGs): the Center for Mendelian Genomics at the University of Washington; the Center for Mendelian Genomics at Yale University; and the Baylor-Johns Hopkins Center for Mendelian Genomics at Baylor College of Medicine and Johns Hopkins University. The CMGs will provide ES/WGS and extensive analysis expertise at no cost to collaborating investigators where the causal gene(s) for a Mendelian phenotype has yet to be uncovered. Over the next few years and in collaboration with the global human genetics community, the CMGs hope to facilitate the identification of the genes underlying a very large fraction of all Mendelian disorders; see http://mendelian.org.

Preface

Preface

Using Biological Knowledge to Uncover the Mystery in the Search for Epistasis in Genome-Wide Association Studies

The search for the missing heritability in genome-wide association studies (GWAS) has become an important focus for the human genetics community. One suspected location of these genetic effects is in gene-gene interactions, or epistasis. The computational burden of exploring gene-gene interactions in the wealth of data generated in GWAS, along with small to moderate sample sizes, have led to epistasis being an afterthought, rather than a primary focus of GWAS analyses. In this review, I discuss some potential approaches to filter a GWAS dataset to a smaller, more manageable dataset where searching for epistasis is considerably more feasible. I describe a number of alternative approaches, but primarily focus on the use of prior biological knowledge from databases in the public domain to guide the search for epistasis. The manner in which prior knowledge is incorporated into a GWA study can be many and these data can be extracted from a variety of database sources. I discuss a number of these approaches and propose that a comprehensive approach will likely be most fruitful for searching for epistasis in large-scale genomic studies of the current state-of-the-art and into the future.

The Biological Coherence of Human Phenome Databases

Disease networks are increasingly explored as a complement to networks centered around interactions between genes and proteins. The quality of disease networks is heavily dependent on the amount and quality of phenotype information in phenotype databases of human genetic diseases. We explored which aspects of phenotype database architecture and content best reflect the underlying biology of disease. We used the OMIM-based HPO, Orphanet, and POSSUM phenotype databases for this purpose and devised a biological coherence score based on the sharing of gene ontology annotation to investigate the degree to which phenotype similarity in these databases reflects related pathobiology. Our analyses support the notion that a fine-grained phenotype ontology enhances the accuracy of phenome representation. In addition, we find that the OMIM database that is most used by the human genetics community is heavily underannotated. We show that this problem can easily be overcome by simply adding data available in the POSSUM database to improve OMIM phenotype representations in the HPO. Also, we find that the use of feature frequency estimates--currently implemented only in the Orphanet database--significantly improves the quality of the phenome representation. Our data suggest that there is much to be gained by improving human phenome databases and that some of the measures needed to achieve this are relatively easy to implement. More generally, we propose that curation and more systematic annotation of human phenome databases can greatly improve the power of the phenotype for genetic disease analysis.

Human and livestock genetics: parallel evolution and horizontal exchange

Human and livestock genetics: parallel evolution and horizontal exchange