Under the traditional mutation load model based on multiplicative fitness effects, the load in a population is 1−e−U, where U is the genomic deleterious mutation rate. Because this load becomes high under large U, synergistic epistasis has been proposed as one possible means of reducing the load. However, experiments on model organisms attempting to detect synergistic epistasis have often focused on a quadratic fitness model, with the resulting general conclusion being that epistasis is neither common nor strong. Here, I present a model of additive fitness effects and show that, unlike multiplicative effects, the equilibrium frequency of an allele under additivity is dependent on the average absolute fitness of the population. The additive model then results in a load of U/(U +1), which is much lower than 1−e−U for large U. Numerical iterations demonstrate that this analytic derivation holds as a good approximation under biologically relevant values of selection coefficients and U. Additionally, regressions onto Drosophila mutation accumulation data suggest that the common method of inferring epistasis by detecting large quadratic terms from regressions is not always necessary, as the additive model fits the data well and results in synergistic epistasis. Furthermore, the additive model gives a much larger reduction in load than the quadratic model when predicted from the same data, indicating that it is important to consider this additive model in addition to the quadratic model when inferring epistasis from mutation accumulation data.

Background: Paraganglioma syndrome type 1 (PGL1) is a rare autosomal dominant syndrome associated with multiple, overwhelmingly benign, pheochromocytomas and paragangliomas, attributed to SDHD gene mutations. Objective: Clinically and molecularly characterize a family with uncommon malignant phenotype of paragangliomas attributed to two seemingly pathogenic SDHD germline mutations. Materials & methods: The proband presented with large bilateral carotid body tumours and family history of cervical masses in his five siblings. All family members underwent clinical examination, imaging studies (18F-FDG PET/CT) and genotyping of relevant genes. The proband was diagnosed with locally advanced paraganglioma; his hypertensive, otherwise asymptomatic father, had locally advanced pheochromocytoma and his three siblings showed multiple head and neck masses, confirmed to be paragangliomas with local metastasis. All affected patients carried two germline mutations in the SDHD gene; a previously reported nonsense mutation in exon 1 (p.Trp5X) and a novel missense mutation in exon 2 (p.Pro53Leu), highly deleterious by in silico analysis. Allelic loss at the SDHD locus was not shown for any of the analysed tumours. Conclusions: This is a rare case of malignant PGL1 with seemingly double pathogenic mutations in the SDHD gene, highlighting the possibility that the presence of both mutations is associated with the more aggressive phenotype.

Next-generation sequencing (NGS) technologies have played a central role in the genetic revolution. These technologies, especially whole-exome sequencing, have become the primary tool of geneticists to identify the causative DNA variants in Mendelian disorders, including hereditary deafness. Current research estimates that 1% of all human genes have a function in hearing. To date, mutations in over 80 genes have been reported to cause nonsyndromic hearing loss (NSHL). Strikingly, more than a quarter of all known genes related to NSHL were discovered in the past 5 years via NGS technologies. In this article, we review recent developments in the usage of NGS for hereditary deafness, with an emphasis on whole-exome sequencing.

Development of mammalian lung involves reiterative outgrowth and branching of an epithelial tube into the surrounding mesenchymal bed. Each coordinated growth and branching cycle is driven by reciprocal signalling between epithelial and adjacent mesenchymal cells. This signalling network includes FGF, SHH, BMP4 and other pathways. We have characterized lung defects in 36Pub mice carrying a deletion that removes an antagonist of FGF signalling, Spry2. Spry2 deficient mice show an enlarged cystic structure located in the terminus of each lobes. Our study shows that Spry2 deficient lungs have reduced lung branching and the cystic structure forms in the early lung development stage. Furthermore, mice carrying a targeted disruption of Spry2 fail to complement the lung phenotype characterized in 36Pub mice. A Spry2-BAC transgene rescues the defect. Interestingly, cystic structure growth is accompanied by the reduced and spatially disorganized expression of Fgf10 and elevated expression of Shh and Bmp4. Altered signalling balance due to the loss of Spry2 causes a delayed branch cycle and cystic growth. Our data underscores the importance of restricting cellular responsiveness to signalling and highlights the interplay between morphogenesis events and spatial localization of gene expression.

Bayesian shrinkage analysis estimates all QTLs effects simultaneously, which shrinks the effect of “insignificant” QTLs close to zero so that it does not need special model selection. Bayesian shrinkage estimation usually has an excellent performance on multiple QTLs mapping, but it could not give a probabilistic explanation of how often a QTLs is included in the model, also called posterior inclusion probability, which is important to assess the importance of a QTL. In this research, two methods, FitMix and SimMix, are proposed to approximate the posterior probabilities. Under the assumption of mixture distribution of the estimated QTL effect, FitMix and SimMix mathematically and intuitively fit mixture distribution, respectively. The simulation results showed that both methods gave very reasonable estimates for posterior probabilities. We also applied the two methods to map QTLs for the North American Barley Genome Mapping Project data.

Codon 72 is a hotspot of polymorphisms in the TP53 gene, which encodes a hub protein in the protein–protein interaction network of p53. It is thus a central player in the apoptotic pathway, preventing cancer. A large number of articles have been published exploring its association with an increased susceptibility to most common cancers. However, these studies have produced inconclusive results, which may be due to their small sample sizes or study designs. To comprehensively evaluate the potential correlation between the TP53 Pro72Arg polymorphism and cancer risk and to better characterize the Pro72Arg polymorphism, we performed a systematic HuGE review and meta-analysis of candidate studies through online resources, according to the proposal of MOOSE and the PRISMA statement. The identified articles were carefully examined according to the inclusion criteria. Pooled odds ratios were calculated on the basis of different genetic models, while heterogeneity was assessed through a chi-based Q-test and I2. After applying the inclusion filters, we obtained a pool of 54 eligible studies, representing 18 718 cases and 21 261 controls. Overall, non-significant cancer risk was observed in all the genetic models but their observed heterogeneity was extremely significant. In subgroup analysis, an increased susceptibility was observed in the case of colorectal cancer, while in cancers of the female reproductive system, significantly increased risk was detected in all the genetic models except the dominant model. In another subgroup analysis, significantly increased cancer risk was observed among Asians in homozygous and recessive models, while in Americans increased cancer risk was observed only in dominant and recessive models. No association was observed in the rest of the populations. In conclusion, pooled subgroup analysis on the basis of ethnicity proved that the TP53 Arg72Pro polymorphism is associated with an increased risk of cancer in Asians and Americans only and is not associated in other populations. It can therefore be concluded that this meta-analysis of available data suggests partial confirmation of the association between the TP53 Arg72Pro polymorphism and cancer risk susceptibility.

Studies of complex genetic diseases have revealed many risk factors of small effect, but the combined amount of heritability explained is still low. Genome-wide association studies are often underpowered to identify true effects because of the very large number of parallel tests. There is, therefore, a great need to generate data sets that are enriched for those markers that have an increased a priori chance of being functional, such as markers in genomic regions involved in gene regulation. ReMo-SNPs is a computational program developed to aid researchers in the process of selecting functional SNPs for association analyses in user-specified regions and/or motifs genome-wide. The useful feature of automatic selection of genotyped markers in the user-provided material makes the output data ready to be used in a following association study. In this article we describe the program and its functions. We also validate the program by including an example study on three different transcription factors and results from an association study on two psychiatric phenotypes. The flexibility of the ReMo-SNPs program enables the user to study any region or sequence of interest, without limitation to transcription factor binding regions and motifs. The program is freely available at: http://www.neuro.ki.se/ReMo-SNPs/

With a large number of quantitative trait loci being identified in genome-wide association studies, researchers have become more interested in detecting interactions among genes or single nucleotide polymorphisms (SNPs). In this research, we carried out a two-stage model selection procedure to detect interacting gene pairs or SNP pairs associated with four important traits of outbred mice, including glucose, high-density lipoprotein cholesterol, diastolic blood pressure and triglyceride. In the first stage, a variance heterogeneity test was used to screen for candidate SNPs. In the second stage, the Lasso method and single pair analysis were used to select two-way interactions. Moreover, the shared Gene Ontology information about the selected interacting gene pairs was considered to study the interactions auxiliarily. Based on this method, we not only replicated the identification of important SNPs associated with each trait of outbred mice, but also found some SNP pairs and gene pairs with significant interaction effects on each trait. Simulation studies were also conducted to evaluate the performance of the two-stage method in different situations.

As a whole neurogenetic diseases are a common group of neurological disorders. However, the recognition and molecular diagnosis of these disorders is not always straightforward. Besides, there is a paucity of information regarding the diagnostic yield that specialized neurogenetic clinics could obtain. We performed a prospective, observational, analytical study of the patients seen in a neurogenetic clinic at a tertiary medical centre to assess the diagnostic yield of a comprehensive diagnostic evaluation that included a personalized clinical assessment along with traditional and next-generation sequencing diagnostic tests. We included a cohort of 387 patients from May 2008 to June 2014. For sub-group analysis we selected a sample of patients whose main complaint was the presence of progressive ataxia, to whom we applied a systematic molecular diagnostic algorithm. Overall, a diagnostic mutation was identified in 27·4% of our cohort. However, if we only considered those patients where a molecular test could be performed, the success rate rises to 45%. We obtained diagnostic yields of 23·5 and 57·5% in the global group of ataxic patients and in the subset of ataxic patients with a positive family history, respectively. Thus, about a third of patients evaluated in a neurogenetic clinic could be successfully diagnosed.

Background: A 40 kb ancestral germline duplication upstream of the GREM1 gene was reported in Ashkenazi families with hereditary mixed polyposis syndrome (HMPS). Objective: Assess the contribution of the GREM1 mutation to familial colorectal cancer (CRC) in Ashkenazim. Methods: Jewish Ashkenazi individuals (n = 472 155 males, 317 females) were genotyped for the GREM1 duplication, 194 with CRC, 131 had other cancer types (endometrial, pancreatic and ovarian) that show a syndromic association with CRC, and 147 were cancer-free with a suggestive family history of CRC. Results: One mutation carrier was found who fulfills the Amsterdam criteria for Lynch Syndrome (LS). The prevalence of this mutation amongst LS Ashkenazim is 0·7%. Conclusion: If validated in additional studies it seems rational to recommend to look for the GREM1 founder mutation in Ashkenazi individuals with multiple colorectal polyps and/or fulfill the criteria for LS.

Pharmacogenetic/pharmacogenomic (PGx) testing is currently available for a wide range of health problems including cardiovascular disease, cancer, diabetes, autoimmune disorders, mental health disorders and infectious diseases. PGx contributes important information to the field of precision medicine by clarifying appropriate treatments for specific disease subtypes. Tangible benefits to patients including improved outcomes and reduced total health care costs have been observed. However, PGx-guided therapy faces many barriers to full integration into clinical practice and acceptance by stakeholders, whether practitioner, patient or payer. Each stakeholder has a unique perspective on the role of PGx testing, although all are similarly challenged with demonstrating or appraising its cost-to-benefit value. Coverage by insurers is a critical step in achieving widespread adoption of PGx testing. The acceleration of adoption of precision medicine in general and for PGx testing in particular will be determined by how quickly robust evidence can be accumulated that shows a return on investment for payers in terms of real dollars, for clinicians in terms of patient clinical responses, and for patients in terms of economic, health and quality of life outcomes. Trends in PGx testing utilization and uptake by payers in real-world practice are discussed; the role of pharmacoeconomics in assessing cost-effectiveness is highlighted using a case study in psychiatric care, and several issues that will affect adoption of PGx testing in the United States (US) over the next few years are reviewed.

Several lines of evidence implicate abnormalities in glutamatergic neural transmission in major depressive disorder (MDD) and treatment response. A high percentage of MDD patients do not respond adequately to antidepressants and are classified as having treatment-resistant depression (TRD). In this study we investigated five GRIK4 variants, previously associated with antidepressants response, in an Italian cohort of 247 MDD no-TRD and 380 TRD patients. We found an association between rs11218030 G allele and TRD. Moreover, significant associations between rs11218030 and rs1954787 and the presence of psychotic symptoms were observed. In conclusion, our data support the involvement of GRIK4 in TRD and in the risk of developing psychotic symptoms during depressive episodes.

There are an estimated 6000–8000 rare Mendelian diseases that collectively affect 30 million individuals in the United States. The low incidence and prevalence of these diseases present significant challenges to improving diagnostics and treatments. Next-generation sequencing (NGS) technologies have revolutionized research of rare diseases. This article will first comment on the effectiveness of NGS through the lens of long-tailed economics. We then provide an overview of recent developments and challenges of NGS-based research on rare diseases. As the quality of NGS studies improve and the cost of sequencing decreases, NGS will continue to make a significant impact on the study of rare diseases moving forward.

Genome-wide association studies (GWAS) have revealed association of a locus approximately 25b downstream of the TMEM18 gene with body mass and obesity. We utilized targeted re-sequencing of the body mass associated locus in proximity of TMEM18 in a case-control population of severely obese children and adolescents from the Stockholm area. We expanded our study to include the TMEM18 gene itself, with the aim of identifying body mass associated genetic variants. Sequencing was performed on the SOLiD platform, on long-range PCR fragments generated through targeted amplification of the regions of interest. Candidate single nucleotide polymorphisms (SNPs) were validated by TaqMan genotyping. We were able to observe 131 SNPs across the re-sequenced regions. Chi squared tests comparing the allele frequencies between cases and controls revealed 57 SNPs as candidates for association with obesity. Validation and replication genotyping revealed robust associations for SNPs within the haplotype block region located downstream from the TMEM18 gene. This study provides a high resolution map of the genetic variation pattern in the TMEM18 gene, as well as the associated haplotype block, and further strengthens the association of variants within the proximal haplotype block with obesity and body mass.

Screening programs for asymptomatic newborns (newborn screening – NBS) have increasingly been implemented in many westernized countries since the end of the 20th century (Wilson et al., 2010). The major goal of these programs is to unselectively screen all newborns for a well defined group of severe, rare, clearly identifiable and actionable conditions. These conditions should be diagnosed and treated in a timely fashion to ensure short and long term health of the newborn as an infant and an adult. As such, NBS programs are one of the pivotal public health achievements of the past decade (Centers for Disease Control and Prevention, 2011) that have led to the saving of lives and improving quality of life as well as posing less financial burden on the health care system. Technically the currently practiced screening process is performed 48 hours after birth, using a minute amount of blood collected on a dried blood spot card, which is subsequently subjected to biochemical analysis predominantly using mass spectrometry assays.

Global patterns of copy number variations (CNVs) in chromosomes are required to understand the dynamics of genome organization and complexity. For this study, analysis was performed using the Affymetrix Genome-Wide Human SNP Array 6.0 chip and CytoScan High-Density arrays. We identified a total of 44 109 CNVs from 1715 genomes with a mean of 25 CNVs in an individual, which established the first drafts of population-specific CNV maps providing a rationale for prioritizing chromosomal regions. About 19 905 ancient CNVs were identified across all chromosomes and populations at varying frequencies. CNV count, and sometimes CNV size, contributed to the bulk CNV size of the chromosome. Population specific lengthening and shortening of chromosomal length was observed. Sex bias for CNV presence was largely dependent on ethnicity. Lower CNV inheritance rate was observed for India, compared to YRI and CEU. A total of 33 candidate CNV hotspots from 5382 copy number (CN) variable region (CNVR) clusters were identified. Population specific CNV distribution patterns in p and q arms disturbed the assumption that CNV counts in the p arm are less common compared to long arms, and the CNV occurrence and distribution in chromosomes is length independent. This study unraveled the force of independent evolutionary dynamics on genome organization and complexity across chromosomes and populations.

This report is regarding a Dutch female with microcephaly, mild intellectual disability (ID), gonadal dysgenesis and dysmorphic facial features with synophrys. Upon genotyping, an ~455 kb de novo deletion encompassing the first exon of NRXN1 was found. Bidirectional sequencing of the coding exons of the NRXN1 alpha isoform was subsequently performed to investigate the possibility of a pathogenic mutation on the other allele, but we could not find any other mutation. Previously, many heterozygous mutations as well as microdeletions in NRXN1 were shown to be associated with ID, autism, schizophrenia, and other psychiatric and psychotic disorders. Our results are in agreement with other reports that show that NRXN1 deletions can lead to ID, microcephaly and mild dysmorphic features. However, this is the first report of gonadal dysgenesis being associated with such deletions. It is not clear whether there is a causal relationship between the NRXN1 deletion and gonadal dysgenesis, but it is of interest that the FSHR gene, which encodes the follicle-stimulating hormone receptor causative correlation that is mutated in ovarian dysgenesis, is located proximal to the NRXN1 gene. Given that most of the females carrying NRXN1 deletions have been diagnosed at a prepubertal age, gynecologic screening of female carriers of a NRXN1 deletion is warranted.

Genome-wide association studies (GWAS) can detect common variants associated with diseases. Next generation sequencing technology has made it possible to detect rare variants. Most of association tests, including burden tests and nonburden tests, mainly target rare variants by upweighting rare variant effects and downweighting common variant effects. But there is increasing evidence that complex diseases are caused by both common and rare variants. In this paper, we extend the ADA method (adaptive combination of P-values; Lin et al., 2014) for rare variants only and propose a RC-ADA method (common and rare variants by adaptive combination of P-values). Our proposed method combines the per-site P-values with the weights based on minor allele frequencies (MAFs). The RC-ADA is robust to directions of effects of causal variants and inclusion of a high proportion of neutral variants. The performance of the RC-ADA method is compared with several other association methods. Extensive simulation studies show that the RC-ADA method is more powerful than other association methods over a wide range of models.