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1.
Nat Commun ; 10(1): 4448, 2019 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-31575865

RESUMO

Infant and childhood growth are dynamic processes with large changes in BMI during development. By performing genome-wide association studies of BMI at 12 time points from birth to eight years (9286 children, 74,105 measurements) in the Norwegian Mother, Father, and Child Cohort Study, replicated in 5235 children, we identify a transient effect in the leptin receptor (LEPR) locus: no effect at birth, increasing effect in infancy, peaking at 6-12 months (rs2767486, P6m = 2.0 × 10-21, ß6m = 0.16 sd-BMI), and little effect after age five. We identify a similar transient effect near the leptin gene (LEP), peaking at 1.5 years (rs10487505, P1.5y = 1.3 × 10-8, ß1.5y = 0.079 sd-BMI). Both signals are protein quantitative trait loci for soluble-LEPR and LEP in plasma in adults independent from adult traits mapped to the respective genes, suggesting key roles of common variation in the leptin signaling pathway for healthy infant growth.

2.
Hum Mol Genet ; 2019 Jul 05.
Artigo em Inglês | MEDLINE | ID: mdl-31504550

RESUMO

Although hundreds of GWAS-implicated loci have been reported for adult obesity-related traits, less is known about the genetics specific for early-onset obesity, and with only a few studies conducted in non-European populations to date. Searching for additional genetic variants associated with childhood obesity, we performed a trans-ancestral meta-analysis of thirty studies consisting of up to 13,005 cases (≥95th percentile of BMI achieved 2-18 years old) and 15,599 controls (consistently <50th percentile of BMI) of European, African, North/South American and East Asian ancestry. Suggestive loci were taken forward for replication in a sample of 1,888 cases and 4,689 controls from seven cohorts of European and North/South American ancestry. In addition to observing eighteen previously implicated BMI or obesity loci, for both early and late onset, we uncovered one completely novel locus in this trans-ancestral analysis (nearest gene: METTL15). The variant was nominally associated in only the European subgroup analysis but had a consistent direction of effect in other ethnicities. We then utilized trans-ancestral Bayesian analysis to narrow down the location of the probable causal variant at each genome-wide significant signal. Of all the fine-mapped loci, we were able to narrow down the causative variant at four known loci to fewer than ten SNPs (FAIM2, GNPDA2, MC4R and SEC16B loci). In conclusion, an ethnically diverse setting has enabled us to both identify an additional pediatric obesity locus and further fine-map existing loci.

3.
Behav Genet ; 2019 Sep 06.
Artigo em Inglês | MEDLINE | ID: mdl-31493278

RESUMO

There is increasing interest within the genetics community in estimating the relative contribution of parental genetic effects on offspring phenotypes. Here we describe the user-friendly M-GCTA software package used to estimate the proportion of phenotypic variance explained by maternal (or alternatively paternal) and offspring genotypes on offspring phenotypes. The tool requires large studies where genome-wide genotype data are available on mother- (or alternatively father-) offspring pairs. The software includes several options for data cleaning and quality control, including the ability to detect and automatically remove cryptically related pairs of individuals. It also allows users to construct genetic relationship matrices indexing genetic similarity across the genome between parents and offspring, enabling the estimation of variance explained by maternal (or alternatively paternal) and offspring genetic effects. We evaluated the performance of the software using a range of data simulations and estimated the computing time and memory requirements. We demonstrate the use of M-GCTA on previously analyzed birth weight data from two large population based birth cohorts, the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Norwegian Mother and Child Cohort Study (MoBa). We show how genetic variation in birth weight is predominantly explained by fetal genetic rather than maternal genetic sources of variation.

4.
Gigascience ; 8(8)2019 08 01.
Artigo em Inglês | MEDLINE | ID: mdl-31363752

RESUMO

BACKGROUND: Mapping biomedical data to functional knowledge is an essential task in bioinformatics and can be achieved by querying identifiers (e.g., gene sets) in pathway knowledge bases. However, the isoform and posttranslational modification states of proteins are lost when converting input and pathways into gene-centric lists. FINDINGS: Based on the Reactome knowledge base, we built a network of protein-protein interactions accounting for the documented isoform and modification statuses of proteins. We then implemented a command line application called PathwayMatcher (github.com/PathwayAnalysisPlatform/PathwayMatcher) to query this network. PathwayMatcher supports multiple types of omics data as input and outputs the possibly affected biochemical reactions, subnetworks, and pathways. CONCLUSIONS: PathwayMatcher enables refining the network representation of pathways by including proteoforms defined as protein isoforms with posttranslational modifications. The specificity of pathway analyses is hence adapted to different levels of granularity, and it becomes possible to distinguish interactions between different forms of the same protein.

5.
Nat Genet ; 51(5): 804-814, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-31043758

RESUMO

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.


Assuntos
Peso ao Nascer/genética , Adulto , Pressão Sanguínea/genética , Estatura/genética , Diabetes Mellitus Tipo 2/etiologia , Diabetes Mellitus Tipo 2/genética , Feminino , Desenvolvimento Fetal/genética , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Cardiopatias/etiologia , Cardiopatias/genética , Humanos , Recém-Nascido , Masculino , Herança Materna/genética , Troca Materno-Fetal/genética , Doenças Metabólicas/etiologia , Doenças Metabólicas/genética , Modelos Genéticos , Polimorfismo de Nucleotídeo Único , Gravidez , Fatores de Risco
6.
Gigascience ; 8(5)2019 05 01.
Artigo em Inglês | MEDLINE | ID: mdl-31121028

RESUMO

The increasing complexity of data and analysis methods has created an environment where scientists, who may not have formal training, are finding themselves playing the impromptu role of software engineer. While several resources are available for introducing scientists to the basics of programming, researchers have been left with little guidance on approaches needed to advance to the next level for the development of robust, large-scale data analysis tools that are amenable to integration into workflow management systems, tools, and frameworks. The integration into such workflow systems necessitates additional requirements on computational tools, such as adherence to standard conventions for robustness, data input, output, logging, and flow control. Here we provide a set of 10 guidelines to steer the creation of command-line computational tools that are usable, reliable, extensible, and in line with standards of modern coding practices.

8.
Atten Defic Hyperact Disord ; 11(1): 91-105, 2019 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-30927234

RESUMO

Na+/H+ Exchanger 9 (NHE9) is an endosomal membrane protein encoded by the Solute Carrier 9A, member 9 gene (SLC9A9). SLC9A9 has been implicated in attention deficit hyperactivity disorder (ADHD), autism spectrum disorders (ASDs), epilepsy, multiple sclerosis and cancers. To better understand the function of NHE9 and the effects of disease-associated variants on protein-protein interactions, we conducted a quantitative analysis of the NHE9 interactome using co-immunoprecipitation and isobaric labeling-based quantitative mass spectrometry. We identified 100 proteins that interact with NHE9. These proteins were enriched in known functional pathways for NHE9: the endocytosis, protein ubiquitination and phagosome pathways, as well as some novel pathways including oxidative stress, mitochondrial dysfunction, mTOR signaling, cell death and RNA processing pathways. An ADHD-associated mutation (A409P) significantly altered NHE9's interactions with a subset of proteins involved in caveolae-mediated endocytosis and MAP2K2-mediated downstream signaling. An ASD nonsense mutation in SLC9A9, R423X, produced no-detectable amount of NHE9, suggesting the overall loss of NHE9 functional networks. In addition, seven of the NHE9 interactors are products of known autism candidate genes (Simons Foundation Autism Research Initiative, SFARI Gene) and 90% of the NHE9 interactome overlap with SFARI protein interaction network PIN (p < 0.0001), supporting the role of NHE9 interactome in ASDs molecular mechanisms. Our results provide a detailed understanding of the functions of protein NHE9 and its disrupted interactions, possibly underlying ADHD and ASDs. Furthermore, our methodological framework proved useful for functional characterization of disease-associated genetic variants and suggestion of druggable targets.


Assuntos
Transtorno do Deficit de Atenção com Hiperatividade/genética , Transtorno do Espectro Autista/genética , Predisposição Genética para Doença/genética , Mutação , Mapas de Interação de Proteínas/genética , Trocadores de Sódio-Hidrogênio/genética , Humanos
9.
J Proteome Res ; 17(11): 3801-3809, 2018 Nov 02.
Artigo em Inglês | MEDLINE | ID: mdl-30251541

RESUMO

Biochemical pathways are commonly used as a reference to conduct functional analysis on biomedical omics data sets, where experimental results are mapped to knowledgebases comprising known molecular interactions collected from the literature. Due to their central role, the content of the functional knowledgebases directly influences the outcome of pathway analyses. In this study, we investigate the structure of the current pathway knowledge, as exemplified by Reactome, discuss the consequences for biological interpretation, and outline possible improvements in the use of pathway knowledgebases. By providing a view of the underlying protein interaction network, we aim to help pathway analysis users manage their expectations and better identify possible artifacts in the results.

10.
Bioinformatics ; 2018 Aug 30.
Artigo em Inglês | MEDLINE | ID: mdl-30169737

RESUMO

Summary: Data visualization plays critical roles in proteomics studies, ranging from quality control of MS/MS data to validation of peptide identification results. Herein, we present PDV, an integrative proteomics data viewer that can be used to visualize a wide range of proteomics data, including database search results, de novo sequencing results, proteogenomics files, MS/MS data in mzML/mzXML format, and data from public proteomics repositories. PDV is a lightweight visualization tool that enables intuitive and fast exploration of diverse, large-scale proteomics datasets on standard desktop computers in both graphical user interface and command line modes. Availability: PDV software and the user manual are freely available at http://pdv.zhang-lab.org. The source code is available at https://github.com/wenbostar/PDV and is released under the GPL-3 license. Supplementary information: Supplementary data are available at Bioinformatics online.

11.
Proteomics ; 18(18): e1700150, 2018 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-29968278

RESUMO

In shotgun proteomics, peptide and protein identification is most commonly conducted using database search engines, the method of choice when reference protein sequences are available. Despite its widespread use the database-driven approach is limited, mainly because of its static search space. In contrast, de novo sequencing derives peptide sequence information in an unbiased manner, using only the fragment ion information from the tandem mass spectra. In recent years, with the improvements in MS instrumentation, various new methods have been proposed for de novo sequencing. This review article provides an overview of existing de novo sequencing algorithms and software tools ranging from peptide sequencing to sequence-to-protein mapping. Various use cases are described for which de novo sequencing was successfully applied. Finally, limitations of current methods are highlighted and new directions are discussed for a wider acceptance of de novo sequencing in the community.

12.
J Proteomics ; 187: 25-27, 2018 Sep 15.
Artigo em Inglês | MEDLINE | ID: mdl-29864591

RESUMO

The inaugural European Bioinformatics Community (EuBIC) developer's meeting was held from January 9th to January 12th 2018 in Ghent, Belgium. While the meeting kicked off with an interactive keynote session featuring four internationally renowned experts in the field of computational proteomics, its primary focus were the hands-on hackathon sessions which featured six community-proposed projects revolving around three major topics: Here, we present an overview of the scientific program of the EuBIC developer's meeting and provide a starting point for follow-up on the covered projects.

13.
J Proteome Res ; 17(7): 2552-2555, 2018 Jul 06.
Artigo em Inglês | MEDLINE | ID: mdl-29774740

RESUMO

Mass-spectrometry-based proteomics has become the standard approach for identifying and quantifying proteins. A vital step consists of analyzing experimentally generated mass spectra to identify the underlying peptide sequences for later mapping to the originating proteins. We here present the latest developments in SearchGUI, a common open-source interface for the most frequently used freely available proteomics search and de novo engines that has evolved into a central component in numerous bioinformatics workflows.

14.
Artigo em Inglês | MEDLINE | ID: mdl-29437797

RESUMO

Aquaporin-4, encoded by AQP4, is the major water channel in the central nervous system and plays an important role in the brain's water balance, including edema formation and clearance. Using genomic copy-number analysis and trio-exome sequencing, we investigated a male patient with intellectual disability, hearing loss, and progressive gait dysfunction and found a de novo missense change Ser111Thr in AQP4 as the only suspicious finding. Perinatally, signs of brain ischemia were detected in relation to acute collapse 2 h after birth that resolved a few days later. At the age of 3 mo, cardiac hypertrophy was detected that persisted through childhood but was completely resolved by age 16. In theory, this neurodevelopmental disorder with transient cardiomyopathy could be caused by a disturbance of cellular water balance. Ser111 is an extremely conserved residue in the short cytoplasmic loop between AQP4 transmembrane helix 2 and 3, present across all AQP isoforms from plants to mammals, and it does not appear to be a phosphorylation site. We found that the Ser111Thr change does not affect water permeability or protein stability, suggesting another and possibly regulatory role. Although causality remains unproven, this case study draws attention to AQP4 as a candidate gene for a unique developmental disorder and to a specific serine as a residue of possibly great functional importance in many AQPs.

15.
Cancer Res ; 77(21): e43-e46, 2017 11 01.
Artigo em Inglês | MEDLINE | ID: mdl-29092937

RESUMO

Proteogenomics has emerged as a valuable approach in cancer research, which integrates genomic and transcriptomic data with mass spectrometry-based proteomics data to directly identify expressed, variant protein sequences that may have functional roles in cancer. This approach is computationally intensive, requiring integration of disparate software tools into sophisticated workflows, challenging its adoption by nonexpert, bench scientists. To address this need, we have developed an extensible, Galaxy-based resource aimed at providing more researchers access to, and training in, proteogenomic informatics. Our resource brings together software from several leading research groups to address two foundational aspects of proteogenomics: (i) generation of customized, annotated protein sequence databases from RNA-Seq data; and (ii) accurate matching of tandem mass spectrometry data to putative variants, followed by filtering to confirm their novelty. Directions for accessing software tools and workflows, along with instructional documentation, can be found at z.umn.edu/canresgithub. Cancer Res; 77(21); e43-46. ©2017 AACR.


Assuntos
Biologia Computacional/métodos , Genômica/métodos , Neoplasias/genética , Software , Genoma Humano , Humanos , Proteômica/métodos , Espectrometria de Massas em Tandem , Transcriptoma/genética
16.
Mass Spectrom Rev ; 2017 Sep 13.
Artigo em Inglês | MEDLINE | ID: mdl-28902424

RESUMO

Sequence database search engines are bioinformatics algorithms that identify peptides from tandem mass spectra using a reference protein sequence database. Two decades of development, notably driven by advances in mass spectrometry, have provided scientists with more than 30 published search engines, each with its own properties. In this review, we present the common paradigm behind the different implementations, and its limitations for modern mass spectrometry datasets. We also detail how the search engines attempt to alleviate these limitations, and provide an overview of the different software frameworks available to the researcher. Finally, we highlight alternative approaches for the identification of proteomic mass spectrometry datasets, either as a replacement for, or as a complement to, sequence database search engines.

17.
Expert Rev Proteomics ; 14(8): 649-663, 2017 08.
Artigo em Inglês | MEDLINE | ID: mdl-28693350

RESUMO

INTRODUCTION: Mass spectrometry (MS)-based proteomics has become an indispensable tool for the characterization of the proteome and its post-translational modifications (PTM). In addition to standard protein sequence databases, proteogenomics strategies search the spectral data against the theoretical spectra obtained from customized protein sequence databases. Up to date, there are no published proteogenomics studies on acute myeloid leukemia (AML) samples. Areas covered: Proteogenomics involves the understanding of genomic and proteomic data. The intersection of both datatypes requires advanced bioinformatics skills. A standard proteogenomics workflow that could be used for the study of AML samples is described. The generation of customized protein sequence databases as well as bioinformatics tools and pipelines commonly used in proteogenomics are discussed in detail. Expert commentary: Drawing on evidence from recent cancer proteogenomics studies and taking into account the public availability of AML genomic data, the interpretation of present and future MS-based AML proteomic data using AML-specific protein sequence databases could discover new biological mechanisms and targets in AML. However, proteogenomics workflows including bioinformatics guidelines can be challenging for the wide AML research community. It is expected that further automation and simplification of the bioinformatics procedures might attract AML investigators to adopt the proteogenomics strategy.


Assuntos
Biomarcadores Tumorais/metabolismo , Leucemia Mieloide Aguda/genética , Proteogenômica/métodos , Biologia Computacional , Humanos , Espectrometria de Massas
18.
Mol Cell Proteomics ; 16(7): 1275-1285, 2017 07.
Artigo em Inglês | MEDLINE | ID: mdl-28515314

RESUMO

The first stable version of the Proteomics Standards Initiative mzIdentML open data standard (version 1.1) was published in 2012-capturing the outputs of peptide and protein identification software. In the intervening years, the standard has become well-supported in both commercial and open software, as well as a submission and download format for public repositories. Here we report a new release of mzIdentML (version 1.2) that is required to keep pace with emerging practice in proteome informatics. New features have been added to support: (1) scores associated with localization of modifications on peptides; (2) statistics performed at the level of peptides; (3) identification of cross-linked peptides; and (4) support for proteogenomics approaches. In addition, there is now improved support for the encoding of de novo sequencing of peptides, spectral library searches, and protein inference. As a key point, the underlying XML schema has only undergone very minor modifications to simplify as much as possible the transition from version 1.1 to version 1.2 for implementers, but there have been several notable updates to the format specification, implementation guidelines, controlled vocabularies and validation software. mzIdentML 1.2 can be described as backwards compatible, in that reading software designed for mzIdentML 1.1 should function in most cases without adaptation. We anticipate that these developments will provide a continued stable base for software teams working to implement the standard. All the related documentation is accessible at http://www.psidev.info/mzidentml.


Assuntos
Biologia Computacional/normas , Proteômica/normas , Bases de Dados de Proteínas , Software
19.
J Proteomics ; 161: 78-80, 2017 05 24.
Artigo em Inglês | MEDLINE | ID: mdl-28385664

RESUMO

The 2017 EuBIC Winter School was held from January 10th to January 13th 2017 in Semmering, Austria. This meeting gathered international researchers in the fields of bioinformatics and proteomics to discuss current challenges in data analysis and biological interpretation. This article outlines the scientific program and exchanges that took place on this occasion and presents the current challenges of this ever-growing field. BIOLOGICAL SIGNIFICANCE: The EUPA bioinformatics community (EuBIC) organized its first winter school in January 2017. This successful event illustrates the growing need of the bioinformatics community in proteomics to gather and discuss current and future challenges in the field. In addition to the organization of yearly meetings, the young and active EuBIC community aims to develop new collaborative open source projects, spread bioinformatics knowledge in Europe, and actively promote data sharing through public repositories.


Assuntos
Biologia Computacional , Congressos como Assunto , Proteômica , Áustria , Biologia Computacional/educação , Biologia Computacional/métodos , Biologia Computacional/tendências , Congressos como Assunto/organização & administração , Europa (Continente) , Proteômica/educação , Proteômica/métodos , Proteômica/tendências , Sociedades Científicas
20.
Bioinformatics ; 33(16): 2580-2582, 2017 Aug 15.
Artigo em Inglês | MEDLINE | ID: mdl-28379341

RESUMO

Motivation: BioContainers (biocontainers.pro) is an open-source and community-driven framework which provides platform independent executable environments for bioinformatics software. BioContainers allows labs of all sizes to easily install bioinformatics software, maintain multiple versions of the same software and combine tools into powerful analysis pipelines. BioContainers is based on popular open-source projects Docker and rkt frameworks, that allow software to be installed and executed under an isolated and controlled environment. Also, it provides infrastructure and basic guidelines to create, manage and distribute bioinformatics containers with a special focus on omics technologies. These containers can be integrated into more comprehensive bioinformatics pipelines and different architectures (local desktop, cloud environments or HPC clusters). Availability and Implementation: The software is freely available at github.com/BioContainers/. Contact: yperez@ebi.ac.uk.


Assuntos
Biologia Computacional/métodos , Software , Genômica/métodos , Metabolômica/métodos , Proteômica/métodos
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