87 results found
Elliott AG, Ganesamoorthy D, Coin L, et al., 2016, Complete Genome Sequence of Klebsiella quasipneumoniae subsp. similipneumoniae Strain ATCC 700603, Genome Announcements, Vol: 4, ISSN: 2169-8287
Klebsiella quasipneumoniae subsp. similipneumoniae strain ATCC 700603, formerly known as K. pneumoniae K6, is known for producing extended-spectrum β-lactamase (ESBL) enzymes that can hydrolyze oxyimino-β-lactams, resulting in resistance to these drugs. We herein report the complete genome of strain ATCC 700603 and show that the ESBL genes are plasmid-encoded.
Poznik GD, Xue Y, Mendez FL, et al., 2016, Punctuated bursts in human male demography inferred from 1,244 worldwide Y-chromosome sequences, Nature Genetics, Vol: 48, Pages: 593-599, ISSN: 1546-1718
We report the sequences of 1,244 human Y chromosomes randomly ascertained from 26 worldwide populations by the 1000 Genomes Project. We discovered more than 65,000 variants, including single-nucleotide variants, multiple-nucleotide variants, insertions and deletions, short tandem repeats, and copy number variants. Of these, copy number variants contribute the greatest predicted functional impact. We constructed a calibrated phylogenetic tree on the basis of binary single-nucleotide variants and projected the more complex variants onto it, estimating the number of mutations for each class. Our phylogeny shows bursts of extreme expansion in male numbers that have occurred independently among each of the five continental superpopulations examined, at times of known migrations and technological innovations.
Li J, Woods SL, Healey S, et al., 2016, Point Mutations in Exon 1B of APC Reveal Gastric Adenocarcinoma and Proximal Polyposis of the Stomach as a Familial Adenomatous Polyposis Variant, American Journal of Human Genetics, Vol: 98, Pages: 830-842, ISSN: 1537-6605
Gastric adenocarcinoma and proximal polyposis of the stomach (GAPPS) is an autosomal-dominant cancer-predisposition syndrome with a significant risk of gastric, but not colorectal, adenocarcinoma. We mapped the gene to 5q22 and found loss of the wild-type allele on 5q in fundic gland polyps from affected individuals. Whole-exome and -genome sequencing failed to find causal mutations but, through Sanger sequencing, we identified point mutations in APC promoter 1B that co-segregated with disease in all six families. The mutations reduced binding of the YY1 transcription factor and impaired activity of the APC promoter 1B in luciferase assays. Analysis of blood and saliva from carriers showed allelic imbalance of APC, suggesting that these mutations lead to decreased allele-specific expression in vivo. Similar mutations in APC promoter 1B occur in rare families with familial adenomatous polyposis (FAP). Promoter 1A is methylated in GAPPS and sporadic FGPs and in normal stomach, which suggests that 1B transcripts are more important than 1A in gastric mucosa. This might explain why all known GAPPS-affected families carry promoter 1B point mutations but only rare FAP-affected families carry similar mutations, the colonic cells usually being protected by the expression of the 1A isoform. Gastric polyposis and cancer have been previously described in some FAP-affected individuals with large deletions around promoter 1B. Our finding that GAPPS is caused by point mutations in the same promoter suggests that families with mutations affecting the promoter 1B are at risk of gastric adenocarcinoma, regardless of whether or not colorectal polyps are present.
Minh DC, Ganesamoorthy D, Cooper MA, et al., 2015, Realtime analysis and visualization of MinION sequencing data with npReader, Bioinformatics, Vol: 32, Pages: 764-766, ISSN: 1367-4803
Motivation: The recently released Oxford Nanopore MinION sequencing platform presents many innovative features opening up potential for a range of applications not previously possible. Among these features, the ability to sequence in real-time provides a unique opportunity for many time-critical applications. While many software packages have been developed to analyze its data, there is still a lack of toolkits that support the streaming and real-time analysis of MinION sequencing data.Results: We developed npReader, an open-source software package to facilitate real-time analysis of MinION sequencing data. npReader can simultaneously extract sequence reads and stream them to downstream analysis pipelines while the samples are being sequenced on the MinION device. It provides a command line interface for easy integration into a bioinformatics work flow, as well as a graphical user interface which concurrently displays the statistics of the run. It also provides an application programming interface for development of streaming algorithms in order to fully utilize the extent of nanopore sequencing potential.Availability and implementation: npReader is written in Java and is freely available at https://github.com/mdcao/npReader.
The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
Ramasamy A, Trabzuni D, Guelfi S, et al., 2014, Genetic variability in the regulation of gene expression in ten regions of the human brain, NATURE NEUROSCIENCE, Vol: 17, Pages: 1418-1428, ISSN: 1097-6256
Bellos E, Kumar V, Lin C, et al., 2014, cnvCapSeq : detecting copy number variation in long-range targeted resequencing data, Nucleic Acids Research, ISSN: 0305-1048
Bellos E, Coin LJM, 2014, cnvOffSeq: detecting intergenic copy number variation using off-target exome sequencing data, BIOINFORMATICS, Vol: 30, Pages: I639-I645, ISSN: 1367-4803
Anderson ST, Kaforou M, Brent AJ, et al., 2014, Diagnosis of Childhood Tuberculosis and Host RNA Expression in Africa, New England Journal of Medicine, Vol: 370, Pages: 1712-1723, ISSN: 1533-4406
White HD, Held C, Stewart R, et al., 2014, Darapladib for Preventing Ischemic Events in Stable Coronary Heart Disease, New England Journal of Medicine, Vol: 370, Pages: 1702-1711, ISSN: 1533-4406
Zhang F, Chen R, Liu D, et al., 2013, YHap: a population model for probabilistic assignment of Y haplogroups from re-sequencing data, BMC BIOINFORMATICS, Vol: 14, ISSN: 1471-2105
Kaforou M, Wright VJ, Oni T, et al., 2013, Detection of Tuberculosis in HIV-Infected and -Uninfected African Adults Using Whole Blood RNA Expression Signatures: A Case-Control Study., Plos Medicine, Vol: 10
Background: A major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB),particularly in the context of HIV infection. We hypothesized that a unique host blood RNA transcriptional signature woulddistinguish TB from other diseases (OD) in HIV-infected and -uninfected patients, and that this could be the basis of a simplediagnostic test.Methods and Findings: Adult case-control cohorts were established in South Africa and Malawi of HIV-infected or -uninfected individuals consisting of 584 patients with either TB (confirmed by culture of Mycobacterium tuberculosis [M.TB]from sputum or tissue sample in a patient under investigation for TB), OD (i.e., TB was considered in the differentialdiagnosis but then excluded), or healthy individuals with latent TB infection (LTBI). Individuals were randomized intotraining (80%) and test (20%) cohorts. Blood transcriptional profiles were assessed and minimal sets of significantlydifferentially expressed transcripts distinguishing TB from LTBI and OD were identified in the training cohort. A 27 transcriptsignature distinguished TB from LTBI and a 44 transcript signature distinguished TB from OD. To evaluate our signatures, weused a novel computational method to calculate a disease risk score (DRS) for each patient. The classification based on thisscore was first evaluated in the test cohort, and then validated in an independent publically available dataset(GSE19491). In our test cohort, the DRS classified TB from LTBI (sensitivity 95%, 95% CI [87–100]; specificity 90%, 95% CI[80–97]) and TB from OD (sensitivity 93%, 95% CI [83–100]; specificity 88%, 95% CI [74–97]). In the independent validationcohort, TB patients were distinguished both from LTBI individuals (sensitivity 95%, 95% CI [85–100]; specificity 94%, 95% CI[84–100]) and OD patients (sensitivity 100%, 95% CI [100–100]; specificity 96%, 95% CI [93–100]). Limitations of our studyin
Alves AC, Bruhn S, Ramasamy A, et al., 2013, Dysregulation of Complement System and CD4+T Cell Activation Pathways Implicated in Allergic Response, PLOS ONE, Vol: 8, ISSN: 1932-6203
Levin M, Kaforou M, Herberg J, et al., 2013, METHOD FOR CALCULATING A DISEASE RISK SCORE, PCT/GB2013/050225
The present disclosure relates to a general method for converting complex gene expression data into a simple, composite disease risk score which can be used for the development of rapid diagnostic tests suitable for clinical use for the determination of the presence of an infection or disease in a host.
Munhoz RP, Teive HA, Eleftherohorinou H, et al., 2013, Demographic and motor features associated with the occurrence of neuropsychiatric and sleep complications of Parkinson's disease, JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY, Vol: 84, Pages: 883-887, ISSN: 0022-3050
Bonnelykke K, Matheson MC, Pers TH, et al., 2013, Meta-analysis of genome-wide association studies identifies ten loci influencing allergic sensitization, NATURE GENETICS, Vol: 45, Pages: 902-U290, ISSN: 1061-4036
Ikram MA, Fornage M, Smith AV, et al., 2013, Common variants at 6q22 and 17q21 are associated with intracranial volume (vol 44, pg 539, 2012), NATURE GENETICS, Vol: 45, Pages: 713-713, ISSN: 1061-4036
Taal HR, St Pourcain B, Thiering E, et al., 2013, Common variants at 12q15 and 12q24 are associated with infant head circumference (vol 44, pg 532, 2012), NATURE GENETICS, Vol: 45, Pages: 713-713, ISSN: 1061-4036
Walters RG, Coin LJ, Ruokonen A, et al., 2013, Rare genomic structural variants in complex disease: lessons from the replication of associations with obesity, PLoS One, Vol: 8, ISSN: 1932-6203
The limited ability of common variants to account for the genetic contribution to complex disease has prompted searches for rare variants of large effect, to partly explain the 'missing heritability'. Analyses of genome-wide genotyping data have identified genomic structural variants (GSVs) as a source of such rare causal variants. Recent studies have reported multiple GSV loci associated with risk of obesity. We attempted to replicate these associations by similar analysis of two familial-obesity case-control cohorts and a population cohort, and detected GSVs at 11 out of 18 loci, at frequencies similar to those previously reported. Based on their reported frequencies and effect sizes (OR>/=25), we had sufficient statistical power to detect the large majority (80%) of genuine associations at these loci. However, only one obesity association was replicated. Deletion of a 220 kb region on chromosome 16p11.2 has a carrier population frequency of 2x10(-4) (95% confidence interval [9.6x10(-5)-3.1x10(-4)]); accounts overall for 0.5% [0.19%-0.82%] of severe childhood obesity cases (P = 3.8x10(-10); odds ratio = 25.0 [9.9-60.6]); and results in a mean body mass index (BMI) increase of 5.8 kg.m(-2) [1.8-10.3] in adults from the general population. We also attempted replication using BMI as a quantitative trait in our population cohort; associations with BMI at or near nominal significance were detected at two further loci near KIF2B and within FOXP2, but these did not survive correction for multiple testing. These findings emphasise several issues of importance when conducting rare GSV association, including the need for careful cohort selection and replication strategy, accurate GSV identification, and appropriate correction for multiple testing and/or control of false discovery rate. Moreover, they highlight the potential difficulty in replicating rare CNV associations across different populations. Nevertheless, we show that such studies are potentially valuable for th
Shao H, Bellos E, Yin H, et al., 2013, A population model for genotyping indels from next-generation sequence data, NUCLEIC ACIDS RESEARCH, Vol: 41, ISSN: 0305-1048
al Basatena N-KS, Hoggart CJ, Coin LJ, et al., 2013, The Effect of Genomic Inversions on Estimation of Population Genetic Parameters from SNP Data, GENETICS, Vol: 193, Pages: 243-253, ISSN: 0016-6731
Couto-Alves A, Wright VJ, Perumal K, et al., 2013, A new scoring system derived from base excess and platelet count at presentation predicts mortality in paediatric meningococcal sepsis, CRITICAL CARE, Vol: 17, ISSN: 1466-609X
Bellos E, Johnson MR, Coin LJ, 2012, cnvHiTSeq: integrative models for high-resolution copy number variation detection and genotyping using population sequencing data, Genome Biology, Vol: 13, ISSN: 1474-7596
Recent advances in sequencing technologies provide the means for identifying copy number variation (CNV) at an unprecedented resolution. A single next-generation sequencing experiment offers several features that can be used to detect CNV, yet current methods do not incorporate all available signatures into a unified model. cnvHiTSeq is an integrative probabilistic method for CNV discovery and genotyping that jointly analyzes multiple features at the population level. By combining evidence from complementary sources, cnvHiTSeq achieves high genotyping accuracy and a substantial improvement in CNV detection sensitivity over existing methods, while maintaining a low false discovery rate. cnvHiTSeq is available at http://sourceforge.net/projects/cnvhitseq
Ramasamy A, Kuokkanen M, Vedantam S, et al., 2012, Genome-Wide Association Studies of Asthma in Population-Based Cohorts Confirm Known and Suggested Loci and Identify an Additional Association near HLA, PLOS ONE, Vol: 7, ISSN: 1932-6203
Coin LJM, Cao D, Ren J, et al., 2012, An exome sequencing pipeline for identifying and genotyping common CNVs associated with disease with application to psoriasis, BIOINFORMATICS, Vol: 28, Pages: I370-I374, ISSN: 1367-4803
O'Reilly PF, Hoggart CJ, Pomyen Y, et al., 2012, MultiPhen: Joint Model of Multiple Phenotypes Can Increase Discovery in GWAS, PLOS One, Vol: 7, ISSN: 1932-6203
The genome-wide association study (GWAS) approach has discovered hundreds of genetic variants associated with diseasesand quantitative traits. However, despite clinical overlap and statistical correlation between many phenotypes, GWAS aregenerally performed one-phenotype-at-a-time. Here we compare the performance of modelling multiple phenotypes jointlywith that of the standard univariate approach. We introduce a new method and software, MultiPhen, that models multiplephenotypes simultaneously in a fast and interpretable way. By performing ordinal regression, MultiPhen tests the linearcombination of phenotypes most associated with the genotypes at each SNP, and thus potentially captures effects hiddento single phenotype GWAS. We demonstrate via simulation that this approach provides a dramatic increase in power inmany scenarios. There is a boost in power for variants that affect multiple phenotypes and for those that affect only onephenotype. While other multivariate methods have similar power gains, we describe several benefits of MultiPhen overthese. In particular, we demonstrate that other multivariate methods that assume the genotypes are normally distributed,such as canonical correlation analysis (CCA) and MANOVA, can have highly inflated type-1 error rates when testing casecontrolor non-normal continuous phenotypes, while MultiPhen produces no such inflation. To test the performance ofMultiPhen on real data we applied it to lipid traits in the Northern Finland Birth Cohort 1966 (NFBC1966). In these dataMultiPhen discovers 21% more independent SNPs with known associations than the standard univariate GWAS approach,while applying MultiPhen in addition to the standard approach provides 37% increased discovery. The most associatedlinear combinations of the lipids estimated by MultiPhen at the leading SNPs accurately reflect the Friedewald Formula,suggesting that MultiPhen could be used to refine the definition of existing phenotypes or uncover novel heritablepheno
Taal HR, St Pourcain B, Thiering E, et al., 2012, Common variants at 12q15 and 12q24 are associated with infant head circumference, Nat Genet, Vol: 44, Pages: 532-538, ISSN: 1061-4036
Dastani Z, Hivert M-F, Timpson N, et al., 2012, Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits: A Multi-Ethnic Meta-Analysis of 45,891 Individuals, PLOS Genetics, Vol: 8, ISSN: 1553-7390
Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inverselyassociated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wideassociation studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. Weidentified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.561028–1.2610243). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, andN = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samplesrevealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations afteraccounting for multiple testing (p,361024). We next developed a multi-SNP genotypic risk score to test the associationof adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This riskscore was associated with increased risk of T2D (p = 4.361023, n = 22,044), increased triglycerides (p = 2.6610214,n = 93,440), increased waist-to-hip ratio (p = 1.861025, n = 77,167), increased glucose two hours post oral glucosetolerance testing (p = 4.461023, n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDLcholesterolconcentrations (p = 4.5610213, n = 96,748) and decreased BMI (p = 1.461024, n = 121,335). These findingsidentify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers ofinsulin resistance.
Hoggart CJ, O'Reilly PF, Kaakinen M, et al., 2012, Fine-Scale Estimation of Location of Birth from Genome-Wide Single-Nucleotide Polymorphism Data, GENETICS, Vol: 190, Pages: 669-U583, ISSN: 0016-6731
Bellos E, Coin LJM, Kaforou M, 2012, Bioinformatics: living on the edge, GENOME BIOLOGY, Vol: 13, ISSN: 1465-6906
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