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Purifying selection tends to reduce nucleotide and haplotype diversity leading to increased linkage disequilibrium. However, detection of evidence for selection is difficult as the signature is confounded by wide variation in the recombination rate which has a complex relationship with selection. The effective bottleneck time (the ratio of the linkage disequilibrium map to the genetic map in Morgans) controls for variability in the recombination rate. Reduced effective bottleneck times indicate stronger residual linkage disequilibrium, consistent with increased selection. Using whole genome sequence data from one European and three Sub-Saharan African human populations we find, in the African samples, strong correlations between high gene densities and reduced effective bottleneck time for autosomal chromosomes. This suggests that gene-dense autosomes have been subject to increased purifying selection reducing effective bottleneck times compared to gene-poor autosomes. Although previous studies have shown unusually strong linkage disequilibrium for the sex chromosomes variation within the autosomes has not been recognised. The strongest relationship is between effective bottleneck time and the density of essential genes, which are likely targets of greater selective pressure (p = 0.006, for the 22 autosomes). The magnitude of the reduction in chromosome-specific effective bottleneck times from the least to the most gene-dense autosomes is ~17-21% for Sub-Saharan African populations. The effect size is greater in Sub-Saharan African populations, compared to a European sample, consistent with increased efficiency of selection in populations with larger effective population sizes which have not been subject to intense population bottlenecks as experienced by populations of European ancestry. The findings highlight the value of deeper analyses of selection within Sub-Saharan African populations.

Whole-genome sequence data enable construction of high-resolution linkage disequilibrium (LD) maps revealing the LD structure of functional elements within genic and subgenic sequences. The Malecot-Morton model defines LD map distances in linkage disequilibrium units (LDUs), analogous to the centimorgan scale of linkage maps. For whole-genome sequence-derived LD maps, we introduce the ratio of corresponding map lengths kilobases/LDU to describe the extent of LD within genome components. The extent of LD is highly variable across the genome ranging from ~38 kb for intergenic sequences to ~858 kb for centromeric regions. LD is ~16% more extensive in genic, compared with intergenic sequences, reflecting relatively increased selection and/or reduced recombination in genes. The LD profile across 18,268 autosomal genes reveals reduced extent of LD, consistent with elevated recombination, in exonic regions near the 5' end of genes but more extensive LD, compared with intronic sequences, across more centrally located exons. Genes classified as essential and genes linked to Mendelian phenotypes show more extensive LD compared with genes associated with complex traits, perhaps reflecting differences in selective pressure. Significant differences between exonic, intronic and intergenic components demonstrate that fine-scale LD structure provides important insights into genome function, which cannot be revealed by LD analysis of much lower resolution array-based genotyping and conventional linkage maps.

Ca2+-insensitive and -sensitive E1 subunits of the 2-oxoglutarate dehydrogenase complex (OGDHC) regulate tissue-specific NADH and ATP supply by mutually exclusive OGDH exons 4a and 4b. Here we show that their splicing is enforced by distant lariat branch points (dBPs) located near the 5′ splice site of the intervening intron. dBPs restrict the intron length and prevent transposon insertions, which can introduce or eliminate dBP competitors. The size restriction was imposed by a single dominant dBP in anamniotes that expanded into a conserved constellation of four dBP adenines in amniotes. The amniote clusters exhibit taxon-specific usage of individual dBPs, reflecting accessibility of their extended motifs within a stable RNA hairpin rather than U2 snRNA:dBP base-pairing. The dBP expansion took place in early terrestrial species and was followed by a uridine enrichment of large downstream polypyrimidine tracts in mammals. The dBP-protected megatracts permit reciprocal regulation of exon 4a and 4b by uridine-binding proteins, including TIA-1/TIAR and PUF60, which promote U1 and U2 snRNP recruitment to the 5′ splice site and BP, respectively, but do not significantly alter the relative dBP usage. We further show that codons for residues critically contributing to protein binding sites for Ca2+ and other divalent metals confer the exon inclusion order that mirrors the Irving-Williams affinity series, linking the evolution of auxiliary splicing motifs in exons to metallome constraints. Finally, we hypothesize that the dBP-driven selection for Ca2+-dependent ATP provision by E1 facilitated evolution of endothermy by optimizing the aerobic scope in target tissues.

Ciliopathies are a broad range of inherited developmental and degenerative diseases associated with structural or functional defects in motile or primary non-motile cilia. There are around 200 known ciliopathy disease genes and whilst genetic testing can provide an accurate diagnosis, 24–60% of ciliopathy patients who undergo genetic testing do not receive a genetic diagnosis. This is partly because following current guidelines from the American College of Medical Genetics and the Association for Molecular Pathology, it is difficult to provide a confident clinical diagnosis of disease caused by missense or non-coding variants, which account for more than one-third of cases of disease. Mutations in PRPF31 are the second most common cause of the degenerative retinal ciliopathy autosomal dominant retinitis pigmentosa. Here, we present a high-throughput high-content imaging assay providing quantitative measure of effect of missense variants in PRPF31 which meets the recently published criteria for a baseline standard in vitro test for clinical variant interpretation. This assay utilizes a new PRPF31+/– human retinal cell line generated using CRISPR gene editing to provide a stable cell line with significantly fewer cilia in which novel missense variants are expressed and characterised. We show that high-content imaging of cells expressing missense variants in a ciliopathy gene on a null background can allow characterisation of variants according to the cilia phenotype. We hope that this will be a useful tool for clinical characterisation of PRPF31 variants of uncertain significance, and can be extended to variant classification in other ciliopathies.

Mutations in PRPF31 are the second most common cause of the degenerative retinal condition autosomal dominant retinitis pigmentosa. Difficulty in characterising missense variants in this gene presents a significant challenge in providing accurate diagnosis for patients to enable targeted testing of other family members, aid family planning, allow pre-implantation diagnosis and inform eligibility for gene therapy trials. With PRPF31 gene therapy in development, there is an urgent need for tools for accurate molecular diagnosis. Here we present a high-throughput high content imaging assay providing quantitative measure of effect of missense variants in PRPF31 which meets the recently published criteria for a baseline standard in vitro test for clinical variant interpretation. This assay utilizes a new and well-characterized PRPF31+/- human retinal cell line generated using CRISPR gene editing, which allows testing of PRPF31 variants which may be causing disease through either haploinsufficiency or dominant negative effects, or a combination of both. The mutant cells have significantly fewer cilia than wild-type cells, allowing rescue of ciliogenesis with benign or mild variants, but do not totally lack cilia, so dominant negative effects can be observed. The results of the assay provide BS3_supporting evidence to the benign classification of two novel uncharacterized PRPF31 variants and suggest that one novel uncharacterized PRPF31 variant may be pathogenic. We hope that this will be a useful tool for clinical characterisation of PRPF31 variants of unknown significance, and can be extended to variant classification in other ciliopathies.

Quantification of linkage disequilibrium (LD) patterns in the human genome is essential for genome-wide association studies, selection signature mapping and studies of recombination. Whole genome sequence (WGS) data provides optimal source data for this quantification as it is free from biases introduced by the design of array genotyping platforms. The Malécot-Morton model of LD allows the creation of a cumulative map for each choromosome, analogous to an LD form of a linkage map. Here we report LD maps generated from WGS data for a large population of European ancestry, as well as populations of Baganda, Ethiopian and Zulu ancestry. We achieve high average genetic marker densities of 2.3–4.6/kb. These maps show good agreement with prior, low resolution maps and are consistent between populations. Files are provided in BED format to allow researchers to readily utilise this resource., Measurement(s)Linkage DisequilibriumTechnology Type(s)whole genome sequencingFactor Type(s)ethnic groupSample Characteristic - OrganismHomo sapiensSample Characteristic - LocationEurope • Africa Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.9901838

Background Next-generation sequencing is revolutionising diagnosis and treatment of rare diseases, however its application to understanding common disease aetiology is limited. Rare disease applications binarily attribute genetic change(s) at a single locus to a specific phenotype. In common diseases, where multiple genetic variants within and across genes contribute to disease, binary modelling cannot capture the burden of pathogenicity harboured by an individual across a given gene/pathway. We present GenePy, a novel gene-level scoring system for integration and analysis of next-generation sequencing data on a per-individual basis that transforms NGS data interpretation from variant-level to gene-level. This simple and flexible scoring system is intuitive and amenable to integration for machine learning, network and topological approaches, facilitating the investigation of complex phenotypes. Results Whole-exome sequencing data from 508 individuals were used to generate GenePy scores. For each variant a score is calculated incorporating: i) population allele frequency estimates; ii) individual zygosity, determined through standard variant calling pipelines and; iii) any user defined deleteriousness metric to inform on functional impact. GenePy then combines scores generated for all variants observed into a single gene score for each individual. We generated a matrix of ~ 14,000 GenePy scores for all individuals for each of sixteen popular deleteriousness metrics. All per-gene scores are corrected for gene length. The majority of genes generate GenePy scores

Despite the identification of many genetic variants contributing to human disease (the 'disease genome'), establishing reliable molecular diagnoses remain challenging in many cases. The ability to sequence the genomes of patients has been transformative, but difficulty in interpretation of voluminous genetic variation often confounds recognition of underlying causal variants. There are numerous predictors of pathogenicity for individual DNA variants, but their utility is reduced because many plausibly pathogenic variants are probably neutral. The rapidly increasing quantity and quality of information on the properties of genes suggests that gene-specific information might be useful for prediction of causal variation when used alongside variant-specific predictors of pathogenicity. The key to understanding the role of genes in disease relates in part to gene essentiality, which has recently been approximated, for example, by quantifying the degree of intolerance of individual genes to loss-of-function variation. Increasing understanding of the interplay between genetic recombination, selection and mutation and their relationship to gene essentiality suggests that gene-specific information may be useful for the interpretation of sequenced genomes. Considered alongside additional distinctive properties of the disease genome, such as the timing of the evolutionary emergence of genes and the roles of their products in protein networks, the case for using gene-specific measures to guide filtering of sequenced genomes seems strong.

Aarskog-Scott syndrome (AAS) is a rare developmental disorder which primarily affects males and has a relative prevalence of 1 in 25,000 in the general population. AAS patients usually present with developmental complications including short stature and facial, skeletal and urogenital anomalies. The spectrum of genotype-phenotype correlations in AAS is unclear and mutations of the FGD1 gene on the proximal short arm of chromosome X account for only 20% of the incidence of the disorder. Failure to identify pathogenic variants in patients referred for FGD1 screening suggests heterogeneity underlying pathophysiology of the condition. Furthermore, overlapping features of AAS with several other developmental disorders increase the complexity of diagnosis. Cytoskeletal signaling may be involved in the pathophysiology of AAS. The FGD1 protein family has a role in activation of CDC42 (Cell Division Control protein 42 homolog) which has a core function in remodeling of extracellular matrix and the transcriptional activation of many modulators of development. Therefore, mutations in components in the EGFR1 (Epidermal Growth Factor Receptor 1) signaling pathway, to which CDC42 belongs, may contribute to pathophysiology. Parallel sequencing strategies (so-called next generation sequencing or high throughput sequencing) enables simultaneous production of millions of sequencing reads that enormously facilitate cost-effective identification of cryptic mutations in heterogeneous monogenic disorders. Here we review the source of phenotypic and genetic heterogeneity in the context of AAS and discuss the applicability of next generation sequencing for identification of novel mutations underlying AAS.

NGS is a revolutionising diagnosis and treatment of rare diseases. However, its relatively modest application in common diseases is limited by analytical approaches.Instead of variant-level approaches, typical for rare disease or large cohort analyses, contemporary investigation of common polygenic disorders requires the development of tools combining mutational burden and biological impact of a personalised set of mutations into single gene scores. GenePy (https://github.com/UoS-HGIG/GenePy) is a gene score for transforming sequencing data capable of estimating whole-gene pathogenicity on a per-patient basis.GenePy implements known deleteriousness metrics, incorporates allele frequency and individual zygosity information. Individuals harbouring multiple rare highly deleterious mutations accumulate extreme gene scores while the majority of genes usually achieve very low scores. Following correction for gene length, GenePy intuitively prioritises genes within individuals and affords gene/pathway score comparison between groups of individuals. Herein, we generate GenePy scores from whole-exome sequencing data for ∼15,000 genes across a cohort of 508 individuals. We describe score attributes and model behaviour under various biological conditions.We demonstrate proof of concept that GenePy sensitively identifies known causal genes by calculating GenePy scores for NOD2 (an established causal Crohn’s Disease gene), in a modest cohort of patients for comparison against controls. This test of GenePy using a positive control gene demonstrates markedly more significant results (p=1.37 × 10-4) compared to the most commonly applied tool for combining common and rare variation.In addition to increasing the biological information content for each variant, the per gene-per individual nature of GenePy transforms the utility of sequencing data. GenePy scores are intuitive when assessing for individual patients or for comparing between groups. Because GenePy intrinsically reflects pathogenicity at the gene level, this specifically facilitates downstream data integration (e.g. into machine learning, network and topological analyses) with transcriptomic and proteomic data that also report at the gene level.Author SummaryRapid technological advances have made DNA sequencing an effective, economic tool for detecting genomic variation. Detecting rare variation at the individual level is proving very successful in identifying the genetic causes of disease when just single mutations are sufficient to manifest disease. However, interpreting genomic data is much less straightforward for common diseases such as asthma, arthritis or heart disease where many genetic changes across multiple genes combine with the environment to bring about disease symptoms.We have developed a new scoring system called GenePy that generates whole gene pathogenicity scores for indiviual patients. The score corrects for the length of the gene and is intuitive to use. Unlike many mutation deleteriousness metrics, GenePy also takes into account the population frequency of the variant and the number of copies of any given mutation and combines data for as many variants as are present in a given gene for any one individual.In this paper we apply the GenePy scoring system to a cohort of over 500 individuals for whom we have sequencing data across all genomics regions that code for protein. We descibe how GenePy performs and demonstrate superior sensitivity to detect known causal genes in a common autoimmune condition.

Normal sun-exposed skin contains numerous epidermal patches that stain positive for p53 protein (p53 immunopositive patches; PIPs), which are considered potential early precursors of skin cancer. Whilst the TP53 gene is mutated in many PIPs, it is unclear whether PIPs contain any other cancer-related mutations. Here we report that PIPs, predominantly

Next-generation sequencing has catapulted healthcare into a revolutionary genomics era. One such technology, whole-exome sequencing, which targets the protein-coding regions of the genome, has proven success in identifying new causal mutations for diseases of previously unknown etiology. With a successful diagnostic rate approaching 25% for rare disease in recent studies, its clinical utility is becoming increasingly popular. However, the interpretation of whole-exome sequencing data requires expertise in genomic informatics and clinical medicine to ensure the accurate and safe reporting of findings back to the bedside. This is challenged by vast amounts of sequencing data harbouring approximately 25 000 variants per sequenced individual. Computational strategies and fastidious filtering frameworks are thus required to extricate candidate variants in a sea of common polymorphisms. Once prioritized, identified variants require intensive scrutiny at a biological level, and require judicious assessment alongside the clinical phenotype. In the final step, all evidence is collated and documented alongside pathogenicity guidelines to produce an exome report that returns to the clinic. This review provides a practical guide for clinicians and genomic informaticians on the clinical application of whole-exome sequencing. We address sequencing capture and methodology, quality control parameters at different stages of sequencing analysis and propose an exome data filtering strategy that includes primary filtering (for the removal of probable benign variants) and secondary filtering for the prioritization of remaining candidates.

Individuals from three families ascertained in Bogota, Colombia, showing syndromic phenotypes, including cleft lip and/or palate, were exome sequenced. In each case sequencing revealed underlying causal variation confirming or establishing diagnoses. The findings include very rare and novel variants providing insights into genotype and phenotype relationships. These include the molecular diagnosis of an individual with Nager syndrome and a family exhibiting an atypical Incontinentia Pigmenti phenotype with a missense mutation in IKBKG. IKBKG mutations are typically associated with pre-term male death but this variant is associated with survival for 8–15 days. The third family exhibits unusual phenotypic features and the proband received a provisional diagnosis of Pierre Robin Sequence (PRS). Affected individuals share a novel deleterious mutation in IRF6. Mutations in IRF6 cause Van der Woude and Popliteal pterygium syndrome and contribute to nonsyndromic cleft lip phenotypes but have not previously been associated with a PRS phenotype. Exome sequencing followed by in silico screening to identify candidate causal variant(s), and functional assay in some cases, offers a powerful route to establishing molecular diagnoses. This approach is invaluable for conditions showing phenotypic and/or genetic heterogeneity including cleft lip and/or palate phenotypes where many underlying causal genes have not been identified.

Pseudomyxoma peritonei (PMP) is a clinical syndrome characterized by gross mucinous ascites originating from a disseminated intraperitoneal neoplasm. Although typically confined to the abdomen, mortality is high if untreated. Biomarkers, including genetic mutation profiles, may aid treatment selection and decision making. We applied whole-exome sequencing to five patients diagnosed with low-grade appendiceal mucinous neoplasms, using paired tumor and germline samples identify biomarkers. Multiple bioinformatic approaches were applied to these data to assess both somatic mutation profiles and loss of heterozygosity events. Mutation profiles of the tumors were consistent with deamination of methylcytosine being the prevailing mechanism. Pathogenic mutations were identified in both KRAS and GNAS in all samples, and further mutations in genes implicated in PMP, namely FGFR2, APC, SMAD2, and FAT4. No TP53 somatic mutations were identified, matching expectations for low-grade tumors. Four of five samples exhibited clonal loss of heterozygosity; these regions were further examined and found to contain genes harboring pathogenic somatic mutations in some samples. RNF43 was hereby implicated in the pathogenesis of PMP of appendiceal origin, having previously been found to increase sensitivity to Wnt signaling and to have involvement in similar mucinous tumors. In conclusion, we have investigated the mutation profile of PMP of appendiceal origin and provided the first report of RNF43 involvement in its progression.

Next generation sequencing is transforming clinical medicine and genome research, providing a powerful route to establishing molecular diagnoses for genetic conditions; however, challenges remain given the volume and complexity of genetic variation. A number of methods integrate patient phenotype and genotypic data to prioritise variants as potentially causal. Some methods have a clinical focus while others are more research-oriented. With clinical applications in mind we compare results from alternative methods using 21 exomes for which the disease causal variant has been previously established through traditional clinical evaluation. In this case series we find that the PhenIX program is the most effective, ranking the true causal variant at between 1 and 10 in 85% of these cases. This is a significantly higher proportion than the combined results from five alternative methods tested (p = 0.003). The next best method is Exomiser (hiPHIVE), in which the causal variant is ranked 1–10 in 25% of cases. The widely different targets of these methods (more clinical focus, considering known Mendelian genes, in PhenIX, versus gene discovery in Exomiser) is perhaps not fully appreciated but may impact strongly on their utility for molecular diagnosis using clinical exome data.

Background: Over the last 2 decades, there has been an ever-expanding catalog of genetic variants implicated in inflammatory bowel disease (IBD) through genome-wide association studies and next generation sequencing. In this article, we highlight the remarkable developments in understanding the genetic and immunological basis of IBD. The main objective of the study was to perform a systematic review of published literature detailing functional/ immunological studies in patients known to harbor genetic variations in the implicated genes. Methods: A panel of 71 candidate genes implicated in IBD was prioritized using 5 network connectivity in silico methods. An electronic search using MEDLINE and EMBASE from 1996 to February 2014 for each of the selected genes was conducted. Only studies describing genotyped IBD cohorts with concurrent in vivo functional studies were included. Results: Between the reviewers, a total of 35,142 potentially eligible publications were identified. Only 8 genes had publications meeting the inclusion criteria. A total of 67 studies were identified across the selected genes. The NOD2 gene had the most number with 41 studies followed by IL-10 with 11 eligible studies. A meta-analysis was not practical given the heterogeneity of the study design and the number of implicated genes with diverse immunological and physiological functions. Conclusions: There is a clear lack of functional studies in humans to assess the in vivo impact of the various genetic variants implicated. A collaborative approach merging genomics and functional studies will help to unravel the obscure mechanisms involved in IBD. (Inflamm Bowel Dis 2014;20:1813–1819)

Background: Neurodevelopmental disorders have challenged clinical genetics for decades, with over 700 genes implicated and many whose function remains unknown. The application of whole-exome sequencing is proving pivotal in closing the genotype/phenotype gap through the discovery of new genes and variants that help to unravel the pathogenic mechanisms driving neuropathogenesis. One such discovery includes TRIO, a gene recently implicated in neurodevelopmental delay. Trio is a Dbl family guanine nucleotide exchange factor (GEF) and a major regulator of neuronal development, controlling actin cytoskeleton dynamics by activating the GTPase Rac1.Methods: Whole-exome sequencing was undertaken on a family presenting with global developmental delay, microcephaly and mild dysmorphism. Father/daughter exome analysis was performed, followed by confirmatory Sanger sequencing and segregation analysis on four individuals. Three further patients were recruited through the deciphering developmental disorders (DDD) study. Functional studies were undertaken using patient-specific Trio protein mutations.Results: We identified a frameshift deletion in TRIO that segregated autosomal dominantly. By scrutinising data from DDD, we further identified three unrelated children with a similar phenotype who harboured de novo missense mutations in TRIO. Biochemical studies demonstrated that in three out of four families, the Trio mutations led to a markedly reduced Rac1 activation.Conclusions: We describe an inherited global developmental delay phenotype associated with a frameshift deletion in TRIO. Additionally, we identify pathogenic de novo missense mutations in TRIO associated with the same consistent phenotype, intellectual disability, microcephaly and dysmorphism with striking digital features. We further functionally validate the importance of the GEF domain in Trio protein function. Our study demonstrates how genomic technologies are yet again proving prolific in diagnosing and advancing the understanding of neurodevelopmental disorders.

Nonsyndromic Cleft Lip and/or Palate (NSCLP) is regarded as a multifactorial condition in which clefting is an isolated phenotype, distinguished from the largely monogenic, syndromic forms which include clefts among a spectrum of phenotypes. Nonsyndromic clefting has been shown to arise through complex interactions between genetic and environmental factors. However, there is increasing evidence that the broad NSCLP classification may include a proportion of cases showing familial patterns of inheritance and contain highly penetrant deleterious variation in specific genes. Through exome sequencing of multi-case families ascertained in Bogota, Colombia, we identify 28 non-synonymous single nucleotide variants that are considered damaging by at least one predictive score. We discuss the functional impact of candidate variants identified. In one family we find a coding variant in the MSX1 gene which is predicted damaging by multiple scores. This variant is in exon 2, a highly conserved region of the gene. Previous sequencing has suggested that mutations in MSX1 may account for ~2% of NSCLP. Our analysis further supports evidence that a proportion of NSCLP cases arise through monogenic coding mutations, though further work is required to unravel the complex interplay of genetics and environment involved in facial clefting.

The analysis of linkage disequilibrium (LD) underpins the development of effective genotyping technologies, trait mapping and understanding of biological mechanisms such as those driving recombination and the impact of selection. We apply the Malécot-Morton model of LD to create additive LD maps which describe the high-resolution LD landscape of commercial chickens. We investigated LD in chickens (Gallus gallus) at the highest resolution to date for broiler, white egg and brown egg layer commercial lines. There is minimal concordance between breeds of fine scale LD patterns (correlation coefficient < 0.21), and even between discrete broiler lines. Regions of LD breakdown, which may align with recombination hotspots, are enriched near CpG islands and transcription start sites (p < 2.2x10-16), consistent with recent evidence described in finches, but concordance in hotspot locations between commercial breeds is only marginally greater than random. As in other birds functional elements in the chicken genome are associated with recombination, but, unlike evidence from other bird species, the LD landscape is not stable in the populations studied. The development of optimal genotyping panels for genome-led selection programmes will depend on careful analysis of the LD structure of each line of interest. Further study is required to fully elucidate the mechanisms underlying highly divergent LD patterns found in commercial chickens.

CEfrag is a new fragment screening technology based on affinity capillary electrophoresis (ACE). Here we report on the development of a mobility shift competition assay using full-length human heat shock protein 90α (Hsp90α), radicicol as the competitor probe ligand, and successful screening of the Selcia fragment library. The CEfrag assay was able to detect weaker affinity (IC(50) >500 µM) fragments than were detected by a fluorescence polarization competition assay using FITC-labeled geldanamycin. The binding site of selected fragments was determined by co-crystallization with recombinant Hsp90α N-terminal domain and X-ray analysis. The results of this study confirm that CEfrag is a sensitive microscale technique enabling detection of fragments binding to the biological target in near-physiological solution.

Background An understanding of linkage disequilibrium (LD) structures in the human genome underpins much of medical genetics and provides a basis for disease gene mapping and investigating biological mechanisms such as recombination and selection. Whole genome sequencing (WGS) provides the opportunity to determine LD structures at maximal resolution. Results We compare LD maps constructed from WGS data with LD maps produced from the array-based HapMap dataset, for representative European and African populations. WGS provides up to 5.7-fold greater SNP density than array-based data and achieves much greater resolution of LD structure, allowing for identification of up to 2.8-fold more regions of intense recombination. The absence of ascertainment bias in variant genotyping improves the population representativeness of the WGS maps, and highlights the extent of uncaptured variation using array genotyping methodologies. The complete capture of LD patterns using WGS allows for higher genome-wide association study (GWAS) power compared to array-based GWAS, with WGS also allowing for the analysis of rare variation. The impact of marker ascertainment issues in arrays has been greatest for Sub-Saharan African populations where larger sample sizes and substantially higher marker densities are required to fully resolve the LD structure. Conclusions WGS provides the best possible resource for LD mapping due to the maximal marker density and lack of ascertainment bias. WGS LD maps provide a rich resource for medical and population genetics studies. The increasing availability of WGS data for large populations will allow for improved research utilising LD, such as GWAS and recombination biology studies. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1854-0) contains supplementary material, which is available to authorized users.

We report a new family with autosomal dominant inheritance of a late onset rapidly progressive leukodystrophy in which exome sequencing has revealed a novel mutation p.R782G in the Colony-Stimulating Factor 1 Receptor gene (CSF1R). Neuropathology of two affected family members showed cerebral white matter degeneration with axonal swellings and pigmented macrophages. The few recently reported families with CSF1R mutations had been previously labelled “hereditary diffuse leukencephalopathy with axonal spheroids” (HDLS) and “pigmentary orthochromatic leukodystrophy” (POLD), disorders which now appear to form a disease continuum. The term “adult-onset leukoencephalopathy with axonal spheroids and pigmented glia” (ALSP) has been proposed to encompass this spectrum. As CSF1R regulates microglia this mutation implies that dysregulation of microglia is the primary cause of the disease.

Primary immunodeficiencies (PIDs) are rare inborn errors of immunity that have a heterogeneous phenotype that can include severe susceptibility to life-threatening infections from multiple pathogens, unique sensitivity to a single pathogen, autoimmune/inflammatory (AI/I) disease, allergies and/or malignancy. We present a diverse cohort of monogenic PID patients with and without AI/I diseases who underwent clinical, genetic and immunological phenotyping. Novel pathogenic variants were identified in IKBKG, CTLA4, NFKB1, GATA2, CD40LG and TAZ as well as previously reported pathogenic variants in STAT3, PIK3CD, STAT1, NFKB2 and STXBP2. AI/I manifestations were frequently encountered in PIDs, including at presentation. Autoimmunity/inflammation was multisystem in those effected, and regulatory T cell (Treg) percentages were significantly decreased compared with those without AI/I manifestations. Prednisolone was used as the first-line immunosuppressive agent in all cases, however steroid monotherapy failed long-term control of autoimmunity/inflammation in the majority of cases and additional immunosuppression was required. Patients with multisystem autoimmunity/inflammation should be investigated for an underlying PID, and in those with PID early assessment of Tregs may help to assess the risk of autoimmunity/inflammation.

The Saccharomyces species Saccharomyces eubayanus was recently discovered in Patagonia. Genomic, genetic and phylogenetic data all suggest that it is one of the two parents of the hybrid yeast S. pastorianus (S. cerevisiae being the other). Saccharomyces eubayanus genomes can also be found in strains of the hybrid species S. bayanus. Here, we describe a novel pair of PCR primers targeted against the S. eubayanus FSY1 gene that will specifically detect S. eubayanus and hybrids containing this allele of the gene. The primer pair can be used to identify the species using a rapid, inexpensive colony PCR method suitable for a preliminary identification of wild isolates.