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Background To identify risk genes whose expression are regulated by the reported risk variants and to explore the potential regulatory mechanism in schizophrenia (SCZ). Methods We systematically integrated three independent brain expression quantitative traits (eQTLs) (CommonMind, GTEx, and BrainSeq Phase 2, a total of 1039 individuals) and GWAS data (56 418 cases and 78 818 controls), with the use of transcriptome-wide association study (TWAS). Diffusion magnetic resonance imaging was utilized to quantify the integrity of white matter bundles and determine whether polygenic risk of novel genes linked to brain structure was present in patients with first-episode antipsychotic SCZ. Results TWAS showed that eight risk genes (CORO7, DDAH2, DDHD2, ELAC2, GLT8D1, PCDHA8, THOC7, and TYW5) reached transcriptome-wide significance (TWS) level. These findings were confirmed by an independent integrative approach (i.e. Sherlock). We further conducted conditional analyses and identified the potential risk genes that driven the TWAS association signal in each locus. Gene expression analysis showed that several TWS genes (including CORO7, DDAH2, DDHD2, ELAC2, GLT8D1, THOC7 and TYW5) were dysregulated in the dorsolateral prefrontal cortex of SCZ cases compared with controls. TWS genes were mainly expressed on the surface of glutamatergic neurons, GABAergic neurons, and microglia. Finally, SCZ cases had a substantially greater TWS genes-based polygenic risk (PRS) compared to controls, and we showed that fractional anisotropy of the cingulum-hippocampus mediates the influence of TWS genes PRS on SCZ. Conclusions Our findings identified novel SCZ risk genes and highlighted the importance of the TWS genes in frontal-limbic dysfunctions in SCZ, indicating possible therapeutic targets.

Merging genetic risk, neurological phenotypes, and clinical presentation is a primary goal for psychiatry. Pursuing this goal, we tested association between phenotypes and overall and pathway-specific polygenic risk in patients with early-stage psychosis. Subjects included 206 demographically diverse cases with a psychotic disorder and 115 matched controls with comprehensive psychiatric and neurological phenotyping. DNA was extracted from blood and genotyped. We calculated polygenic scores (PGSs) for schizophrenia (SZ) and bipolar disorder (BP) using Psychiatric Genomics Consortium GWAS summary statistics. To dissect convergent mechanisms of symptoms, we calculated pathway PGSs (pPGSs) for SZ risk affecting each of four major neurotransmitter systems: glutamate, GABA, dopamine, and serotonin. Psychosis subjects had elevated SZ and BP PGS versus controls; cases with SZ or BP diagnoses had stronger SZ or BP risk, respectively. There was no significant association between individual symptom measures and overall PGS. However, neurotransmitter-specific pPGSs were significantly associated with specific symptoms; most notably, increased glutamatergic pPGS was associated with deficits in cognitive control and altered cortical activation during cognitive control task-based fMRI. Finally, unbiased symptom-driven clustering identified three diagnostically mixed case groups with distinct symptom profiles that separated on primary deficits of positive symptoms, negative symptoms, global functioning, and cognitive control. These clusters had specific genetic risk profiles and differential response to treatment, and outperformed diagnosis in predicting glutamate and GABA pPGS. Our findings suggest pathway-based PGS analysis may be a powerful path forward for identifying convergent mechanisms driving psychotic disorders and linking genetic risk with endophenotypes.

BackgroundThe causal relevance of polyunsaturated fatty acids (PUFAs) for risk of site-specific cancers remains uncertain.MethodsUsing a Mendelian randomization (MR) framework, we assessed the causal relevance of PUFAs for risk of cancer in European and East Asian ancestry individuals. We defined the primary exposure as PUFA desaturase activity, proxied by rs174546 at the FADS locus. Secondary exposures were defined as omega 3 and omega 6 PUFAs that could be proxied by genetic polymorphisms outside the FADS region. Our study used summary genetic data on 10 PUFAs and 67 cancers, corresponding to 562,871 cases and 1,619,465 controls, collected by the Fatty Acids in Cancer Mendelian Randomization Collaboration. We estimated odds ratios (ORs) for cancer per standard deviation increase in genetically proxied PUFA exposures.FindingsGenetically elevated PUFA desaturase activity was associated (P < 0.0007) with higher risk (OR [95% confidence interval]) of colorectal cancer (1.09 [1.07–1.11]), esophageal squamous cell carcinoma (1.16 [1.06–1.26]), lung cancer (1.06 [1.03–1.08]) and basal cell carcinoma (1.05 [1.02–1.07]). There was little evidence for associations with reproductive cancers (OR = 1.00 [95% CI: 0.99–1.01]; Pheterogeneity = 0.25), urinary system cancers (1.03 [0.99–1.06], Pheterogeneity = 0.51), nervous system cancers (0.99 [0.95–1.03], Pheterogeneity = 0.92) or blood cancers (1.01 [0.98–1.04], Pheterogeneity = 0.09). Findings for colorectal cancer and esophageal squamous cell carcinoma remained compatible with causality in sensitivity analyses for violations of assumptions. Secondary MR analyses highlighted higher omega 6 PUFAs (arachidonic acid, gamma-linolenic acid and dihomo-gamma-linolenic acid) as potential mediators. PUFA biosynthesis is known to interact with aspirin, which increases risk of bleeding and inflammatory bowel disease. In a phenome-wide MR study of non-neoplastic diseases, we found that genetic lowering of PUFA desaturase activity, mimicking a hypothetical intervention to reduce cancer risk, was associated (P < 0.0006) with increased risk of inflammatory bowel disease but not bleeding.InterpretationThe PUFA biosynthesis pathway may be an intervention target for prevention of colorectal cancer and esophageal squamous cell carcinoma but with potential for increased risk of inflammatory bowel disease.FundingCancer Resesrch UK (C52724/A20138, C18281/A19169). UK Medical Research Council (MR/P014054/1). National Institute for Health Research (NIHR202411). UK Medical Research Council (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4). National Cancer Institute (R00 CA215360). National Institutes of Health (U01 CA164973, R01 CA60987, R01 CA72520, U01 CA74806, R01 CA55874, U01 CA164973 and U01 CA164973).

BackgroundContrasting the well-described effects of early intervention (EI) services for youth-onset psychosis, the potential benefits of the intervention for adult-onset psychosis are uncertain. This paper aims to examine the effectiveness of EI on functioning and symptomatic improvement in adult-onset psychosis, and the optimal duration of the intervention.Methods360 psychosis patients aged 26–55 years were randomized to receive either standard care (SC, n = 120), or case management for two (2-year EI, n = 120) or 4 years (4-year EI, n = 120) in a 4-year rater-masked, parallel-group, superiority, randomized controlled trial of treatment effectiveness (Clinicaltrials.gov: NCT00919620). Primary (i.e. social and occupational functioning) and secondary outcomes (i.e. positive and negative symptoms, and quality of life) were assessed at baseline, 6-month, and yearly for 4 years.ResultsCompared with SC, patients with 4-year EI had better Role Functioning Scale (RFS) immediate [interaction estimate = 0.008, 95% confidence interval (CI) = 0.001–0.014, p = 0.02] and extended social network (interaction estimate = 0.011, 95% CI = 0.004–0.018, p = 0.003) scores. Specifically, these improvements were observed in the first 2 years. Compared with the 2-year EI group, the 4-year EI group had better RFS total (p = 0.01), immediate (p = 0.01), and extended social network (p = 0.05) scores at the fourth year. Meanwhile, the 4-year (p = 0.02) and 2-year EI (p = 0.004) group had less severe symptoms than the SC group at the first year.ConclusionsSpecialized EI treatment for psychosis patients aged 26–55 should be provided for at least the initial 2 years of illness. Further treatment up to 4 years confers little benefits in this age range over the course of the study.

RNA-Seq is widely used to capture transcriptome dynamics across tissues from different biological entities even across biological conditions, with the aim of understanding the contribution of gene activities to phenotypes of biosamples. However, due to variation from tissues and biological entities (or other biological conditions), joint analysis of bulk RNA expression profiles across multiple tissues from a number of biological entities to achieve the aim is hindered. Moreover, it is crucial to consider interactions between biological variables. For example, different brain disorders may affect brain regions heterogeneously. Thus, modeling the disorder-region interaction can shed light on the heterogeneity. To address these key challenges, we propose a general and flexible statistical framework based on matrix factorization, named INSIDER (https://github.com/kai0511/insider).INSIDER decomposes variation from different biological variables into a shared low-rank latent space. In particular, it considers interactions between biological variables and introduces the elastic net penalty to induce sparsity, thus facilitating interpretation. In the framework, the biological variables and interaction terms can be defined based on the research questions and study design. Besides, it enables us to compute the ‘adjusted’ expression profiles for biological variables that control variation from other biological variables. Lastly, it allows various downstream analyses, such as clustering donors with donor representations, revealing development trajectory in its application to the BrainSpan data, and uncovering mechanisms underlying variables like phenotype and interactions between biological variables (e.g., phenotypes and tissues).

CCCTC-binding factor (CTCF) is a transcription regulator which is involved in many cellular processes. How CTCF recognizes DNA sequence to exert chromosome barrier or enhancer blocking effects remains to be fully interrogated. Despite many computational tools were developed to predict CTCF-mediated loops qualitatively or quantitatively, few could specially evaluate the regulatory potential of DNA sequence at CTCF binding sites (CBSs) and how it affects chromatin loop formation. Here, we developed a deep learning model, DeepAnchor, to precisely characterize the binding patterns for different types of CBSs. By incorporating base-wise genomic/epigenomic features, we revealed distinct chromatin and sequence features for CTCF-mediated insulation and looping at a high resolution, such as two sequence motifs flanking the core CTCF motif at loop-associated CBSs. Besides, we leveraged the predicted anchor score to optimize the loop extrusion model and achieved the best performance in predicting CTCF-anchored loops. We established a compendium of context-specific CTCF-anchored loops across 52 human tissue/cell types and found that genomic disruption of CTCF-anchored loops may represent a general causal mechanism of disease pathogenesis. These computational models, together with the established resource, could facilitate the mechanistic research on how the CTCF-mediatedcis-regulatory elements (CREs) shapes context-specific gene regulation in cell development and disease progression.

Background Grey matter (GM) reduction is a consistent observation in established late stages of schizophrenia, but patients in the untreated early stages of illness display an increase as well as a decrease in GM distribution relative to healthy controls (HC). The relative excess of GM may indicate putative compensatory responses, though to date its relevance is unclear. Methods 343 first-episode treatment-naïve patients with schizophrenia (FES) and 342 HC were recruited. Multivariate source-based morphometry was performed to identify covarying ‘networks' of grey matter concentration (GMC). Neurocognitive scores using the Cambridge Neuropsychological Test Automated Battery (CANTAB) and symptom burden using the Positive and Negative Symptoms Scale (PANSS) were obtained. Bivariate linear relationships between GMC and cognition/symptoms were studied. Results Compared to healthy subjects, FES had prominently lower GMC in two components; the first consists of the anterior insula, inferior frontal gyrus, anterior cingulate and the second component with the superior temporal gyrus, precuneus, inferior/superior parietal lobule, cuneus, and lingual gyrus. Higher GMC was seen in adjacent areas of the middle and superior temporal gyrus, middle frontal gyrus, inferior parietal cortex and putamen. Greater GMC of this component was associated with lower duration of untreated psychosis, less severe positive symptoms and better performance on cognitive tests. Conclusions In untreated stages of schizophrenia, both a distributed lower and higher GMC is observable. While the higher GMC is relatively modest, it occurs across frontoparietal, temporal and subcortical regions in association with reduced illness burden suggesting a compensatory role for higher GMC in the early stages of schizophrenia.

Background Identifying the causal genes at the risk loci and elucidating their roles in schizophrenia (SCZ) pathogenesis remain significant challenges. To explore risk variants associated with gene expression in the human brain and to identify genes whose expression change may contribute to the susceptibility of SCZ, here we report a comprehensive integrative study on SCZ. Methods We systematically integrated the genetic associations from a large-scale SCZ GWAS (N = 56,418) and brain expression quantitative trait loci (eQTL) data (N = 175) using a Bayesian statistical framework (Sherlock) and Summary data-based Mendelian Randomization (SMR). We also measured brain structure of 86 first-episode antipsychotic-naive schizophrenia patients and 152 healthy controls with the structural MRI. Results Both Sherlock (P = 3. 38 × 10−6) and SMR (P = 1. 90 × 10−8) analyses showed that TYW5 mRNA expression was significantly associated with risk of SCZ. Brain-based studies also identified a significant association between TYW5 protein abundance and SCZ. The single-nucleotide polymorphism rs203772 showed significant association with SCZ and the risk allele is associated with higher transcriptional level of TYW5 in the prefrontal cortex. We further found that TYW5 was significantly upregulated in the brain tissues of SCZ cases compared with controls. In addition, TYW5 expression was also significantly higher in neurons induced from pluripotent stem cells of schizophrenia cases compared with controls. Finally, combining analysis of genotyping and MRI data showed that rs203772 was significantly associated with gray matter volume of the right middle frontal gyrus and left precuneus. Conclusions We confirmed that TYW5 is a risk gene for SCZ. Our results provide useful information toward a better understanding of the genetic mechanism of TYW5 in risk of SCZ.

Background: Recent findings indicated a high comorbidity between attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), as well as shared genetic influences on them. The latter might contribute at least partly to the former clinical scenario. This study aimed at investigating whether SHANK genes were potential pleiotropic genes to the two said disorders, underlying their genetic overlap.Methods: This study recruited 298 boys with ADHD (including 256 family trios of 1 ADHD boy and his 2 biological parents), 134 boys with ASD, 109 boys with both ADHD and ASD, and 232 typically developing boys as community controls. They were aged between 6 and 11 years old.Results: There was no significant difference in allele frequency of a number of single nucleotide polymorphisms (SNPs) in SHANK2/SHANK3 between the three clinical groups (ADHD, ASD, and ADHD + ASD) and between the two control groups (community controls and pseudo-controls), respectively. The three clinical groups and the two control groups were thus, respectively, combined. A comparison between the two aggregated samples identified significant evidence of disease association for three SHANK2 SNPs with both ADHD and ASD, even after multiple testing correction: rs11236616 (OR = 0.762, permuted p = 0.0376), rs7106631 (OR = 0.720, permuted p = 0.0034), and rs9888288 (OR = 0.770, permuted p = 0.0407). Comparisons among individual groups pointed to a similar trend of findings.Conclusion:SHANK2 could be considered a potential pleiotropic gene underlying the genetic overlap between ADHD and ASD. This might contribute partly to their high comorbidity in the afflicted children.

Summary Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation., Graphical abstract, Highlights • A multicohort study identifies 52 previously unknown osteoarthritis genetic risk variants • Similarities and differences in osteoarthritis genetic risk depend on joint sites • Osteoarthritis genetic components are associated with pain-related phenotypes • High-confidence effector genes highlight potential targets for drug intervention, A multicohort genome-wide association meta-analysis of osteoarthritis highlights the impact of joint site types on the features of genetic risk variants and the link between osteoarthritis genetics and pain-related phenotypes, pointing toward potential targets for therapeutic intervention.

Genetic effects on the liability scale are informative for describing the genetic architecture of binary traits, typically diseases. However, most genetic association analyses on binary traits are performed by logistic regression, and there is no straightforward method that transforms both effect size estimate and standard error from the logit scale to the liability scale. Here, we derive a simple linear transformation of the log odds ratio and its standard error for a single nucleotide polymorphism (SNP) to an effect size and standard error on the liability scale. We show by analytic calculations and simulations that this approximation is accurate when the disease is common and the SNP effect is small. We also apply this method to estimate the contribution of a SNP near the RET gene to the variance of Hirschsprung disease liability, and the age-specific contributions of APOE4 on the variance of Alzheimer's disease liability. We discuss the approximate linear inter-relationships between genotype and effect sizes on the observed binary, logit, and liability scales, and the potential applications of the linear approximation to statistical power calculation for binary traits.

Identifying rare variants that contribute to complex diseases is challenging because of the low statistical power in current tests comparing cases with controls. Here, we propose a novel and powerful rare variants association test based on the deviation of the observed mutation burden of a gene in cases from a baseline predicted by a weighted recursive truncated negative-binomial regression (RUNNER) on genomic features available from public data. Simulation studies show that RUNNER is substantially more powerful than state-of-the-art rare variant association tests and has reasonable type 1 error rates even for stratified populations or in small samples. Applied to real case-control data, RUNNER recapitulates known genes of Hirschsprung disease and Alzheimer's disease missed by current methods and detects promising new candidate genes for both disorders. In a case-only study, RUNNER successfully detected a known causal gene of amyotrophic lateral sclerosis. The present study provides a powerful and robust method to identify susceptibility genes with rare risk variants for complex diseases.

Additional file 1: Table S1. Unadjusted and age-adjusted Cox regression analysis predicting MACEs in stable CAD patients. Table S2. Competing risks regression models predicting MACEs in stable CAD patients. Table S3. Multivariable Cox regression models predicting MACEs in patients with and without T2DM.

Supplementary methods and figures. (DOC 117 kb)

Supplementary tables. (DOC 541 kb)

Fibroblast growth factor 21 (FGF21) is increasingly recognized as an important metabolic regulator of glucose homeostasis. Here, we conducted an exome-chip association analysis by genotyping 5,169 Chinese individuals from a community-based cohort and two clinic-based cohorts. A custom Asian exome-chip was used to detect genetic determinants influencing circulating FGF21 levels. Single-variant association analysis interrogating 70,444 single nucleotide polymorphisms identified a novel locus

Motivation:The interaction between transcription factor (TF) and transcription factor binding site (TFBS) is essential for gene regulation. Mutation in either the TF or the TFBS may weaken their interaction and thus result in abnormalities. To maintain such vital interaction, a mutation in one of the interacting partners might be compensated by a corresponding mutation in its binding partner during the course of evolution. Confirming this co-evolutionary relationship will guide us in designing protein sequences to target a specific DNA sequence or in predicting TFBS for poorly studied proteins, or even correcting and rescuing disease mutations in clinical applications. Results: Based on six, publicly available, experimentally validated TF–TFBS binding datasets for the basic Helix–Loop–Helix (bHLH) family, Homeo family, High-Mobility Group (HMG) family and Transient Receptor Potential channels (TRP) family, we showed that the evolutions of the TFs and their TFBSs are significantly correlated across eukaryotes. We further developed a mutual information-based method to identify co-evolved protein residues and DNA bases. This research sheds light on the dynamic relationship between TF and TFBS during their evolution. The same principle and strategy can be applied to co-evolutionary studies on protein–DNA interactions in other protein families. Availability: All the datasets, scripts and other related files have been made freely available at: http://jjwanglab.org/co-evo. Contact: junwen@uw.edu Supplementary Information: Supplementary data are available at Bioinformatics online.

Biliary atresia (BA) is characterized by the progressive fibrosclerosing obliteration of the extrahepatic biliary system during the first few weeks of life. Despite early diagnosis and prompt surgical intervention, the disease progresses to cirrhosis in many patients. The current theory for the pathogenesis of BA proposes that during the perinatal period, a still unknown exogenous factor meets the innate immune system of a genetically predisposed individual and induces an uncontrollable and potentially self-limiting immune response, which becomes manifest in liver fibrosis and atresia of the extrahepatic bile ducts. Genetic factors that could account for the disease, let alone for its high incidence in Chinese, are to be investigated. To identify BA susceptibility loci, we carried out a genome-wide association study (GWAS) using the Affymetrix 5.0 and 500 K marker sets. We genotyped nearly 500 000 single-nucleotide polymorphisms (SNPs) in 200 Chinese BA patients and 481 ethnically matched control subjects. The 10 most BA-associated SNPs from the GWAS were genotyped in an independent set of 124 BA and 90 control subjects. The strongest overall association was found for rs17095355 on 10q24, downstream XPNPEP1, a gene involved in the metabolism of inflammatory mediators. Allelic chi-square test P-value for the meta-analysis of the GWAS and replication results was 6.94 x 10(-9). The identification of putative BA susceptibility loci not only opens new fields of investigation into the mechanisms underlying BA but may also provide new clues for the development of preventive and curative strategies.

Human leukocyte antigen (HLA) typing from next generation sequencing (NGS) data has the potential for applications in clinical laboratories and population genetic studies. Here we introduce a novel technique for HLA typing from NGS data based on read-mapping using a comprehensive reference panel containing all known HLA alleles and de novo assembly of the gene-specific short reads. An accurate HLA typing at high-digit resolution was achieved when it was tested on publicly available NGS data, outperforming other newly-developed tools such as HLAminer and PHLAT., {"references":["de Bakker PI, McVean G, Sabeti PC, et al., \"A high-resolution HLA and\nSNP haplotype map for disease association studies in the extended human\nMHC,\" Nat Genet, vol. 38, 2006, pp. 1166–1172.","de Bakker PI, Raychaudhuri S., \"Interrogating the major\nhistocompatibility complex with high-throughput genomics,\" Hum Mol\nGenet, vol. 21, 2012, pp. 29–36.","IMGT/HLA (International immunogenetics project/Human major\nhistocompatibility complex). London: Royal Free Hospital, Anthony\nNolan Research Institute, HLA Informatics Group, 1998.\nhttp://www.ebi.ac.uk/ipd/imgt/hla/.","Bentley G, Higuchi R, Hoglund B, et al. High-resolution, high-throughput\nHLA genotyping by next-generation sequencing. Tissue Antigens, vol. 74,\n2009, pp. 393–403.","Lind C, Ferriola D, Mackiewicz K, et al., \"Next-generation sequencing:\nthe solution for high-resolution, unambiguous human leukocyte antigen\ntyping,\" Hum Immunol, vol. 10, 2010, pp. 1033–1042.","Noble JA, Martin A, Valdes AM, et al., \"Type 1 diabetes risk for\nHLA-DR3 haplotypes depends on genotypic context: Association of\nDPB1 and HLA class I loci among DR3 and DR4 matched Italian patients\nand controls,\" Hum Immunol, vol. 69, 2008, pp. 291–300.","Solberg OD, Mack SJ, Lancastera AK, et al, \"Balancing selection and\nheterogeneity across the classical human leukocyte antigen loci: a\nmeta-analytic review of 497 population studies,\" Hum Immunol, vol.\n69, 2008, pp. 443–464.","Boegel S, Lower M, Schafer M, et al, \"HLA typing from RNA-Seq\nsequence reads,\" Genome Med, vol. 4, 2012, pp. 102–113.","Warren RL, Choe G, Freeman D, et al, \"Derivation of HLA types from\nshotgun sequence datasets,\" Genome Med, vol. 4, 2012, pp. 95–102.\n[10] Gonzalez-Galarza FF, Christmas S, Middleton D, et al., \"Allele frequency\nnet: a database and online repository for immune gene frequencies in\nworldwide populations,\" Nucleic Acids Res, vol. 39, 2011, pp. 913-919.\n[11] Li H, Durbin R, \"Fast and accurate long-read alignment with\nBurrows-Wheeler Transform,\" Bioinformatics, vol. 26, 2010, pp.\n589–595.\n[12] Inflammgen (The laboratory in genetics and genomic medicine of\ninflammation). http://www.inflammgen.org/.\n[13] Erlich RL, Jia X, Anderson S, et al., \"Next-generation sequencing for\nHLA typing of class I loci,\" BMC Genomics, vol. 12, 2011, pp. 42-54.\n[14] Bai Y, Ni M, Cooper B, et al., \"Inference of high resolution HLA types\nusing genome-wide RNA or DNA sequencing reads,\" BMC Genomics,\nvol. 15, 2014, pp. 325-340.\n[15] Stephens M, Smith NJ, Donnelly P, \"A new statistical method for\nhaplotype reconstruction from population data,\" Am J Hum Genet, vol.\n68, 2001, pp. 978–989.\n[16] Major E, Rigo K, Hague T, et al., \"HLA typing from 1000 genomes whole\ngenome and whole exome illumina data,\" PLoS ONE, vol. 8, 2013, pp.\n11–19.\n[17] RefSeq (NCBI reference sequence database). Bethesda: National Library\nof Medicine, National Center for Biotechnology Information, 2002.\nhttp://www.ncbi.nlm.nih.gov/refseq/."]}

Three simple and elegant algorithms involving binary and mixed-radix numbers are presented as C subroutines and applied to gene-counting procedure. The first, a multikey radix-sorting subroutine, is used to tally individuals with similar genetic marker information. The second, a subroutine for N-ary number addition, is used to enumerate all possible phases of a heterozygote. The third, a mixed-radix number subroutine, is used to generate all haplotypes and indexing single array of haplotype frequencies. Examples exposing these algorithms are also given. The sorting algorithm entails broad application while the N-ary and mixed-radix number algorithms are very efficient for generic looping. Implementation of gene-counting using these algorithms avoids use of multilocus genotype identifier and improves its portability to other analysis.

Previous genome-wide association studies (GWAS), which were mainly based on single-variant analysis, have identified many systemic lupus erythematosus (SLE) susceptibility loci. However, the genetic architecture of this complex disease is far from being understood. The aim of this study was to investigate whether using a gene-based analysis may help to identify novel loci, by considering global evidence of association from a gene or a genomic region rather than focusing on evidence for individual variants.Based on the results of a meta-analysis of 2 GWAS of SLE conducted in 2 Asian cohorts, we performed an in-depth gene-based analysis followed by replication in a total of 4,626 patients and 7,466 control subjects of Asian ancestry. Differential allelic expression was measured by pyrosequencing.More than one-half of the reported SLE susceptibility loci showed evidence of independent effects, and this finding is important for understanding the mechanisms of association and explaining disease heritability. ANXA6 was detected as a novel SLE susceptibility gene, with several single-nucleotide polymorphisms (SNPs) contributing independently to the association with disease. The risk allele of rs11960458 correlated significantly with increased expression of ANXA6 in peripheral blood mononuclear cells from heterozygous healthy control subjects. Several other associated SNPs may also regulate ANXA6 expression, according to data obtained from public databases. Higher expression of ANXA6 in patients with SLE was also reported previously.Our study demonstrated the merit of using gene-based analysis to identify novel susceptibility loci, especially those with independent effects, and also demonstrated the widespread presence of loci with independent effects in SLE susceptibility genes.

To adopt an efficient approach of identifying rare variants possibly related to Hirschsprung disease (HSCR), a pilot study was set up to evaluate the performance of a newly designed protocol for next generation targeted resquencing. In total, 20 Chinese HSCR patients and 20 Chinese sex-matched individuals with no HSCR were included, for which coding sequences (CDS) of 62 genes known to be in signaling pathways relevant to enteric nervous system development were selected for capture and sequencing. Blood DNAs from eight pools of five cases or controls were enriched by PCR-based RainDance technology (RDT) and then sequenced on a 454 FLX platform. As technical validation, five patients from case Pool-3 were also independently enriched by RDT, indexed with barcode and sequenced with sufficient coverage. Assessment for CDS single nucleotide variants showed DNA pooling performed well (specificity/sensitivity at 98.4%/83.7%) at the common variant level; but relatively worse (specificity/sensitivity at 65.5%/61.3%) at the rare variant level. Further Sanger sequencing only validated five out of 12 rare damaging variants likely involved in HSCR. Hence more improvement at variant detection and sequencing technology is needed to realize the potential of DNA pooling for large-scale resequencing projects.