RESUMEN
We tested 310,605 SNPs for association in 778 individuals with celiac disease and 1,422 controls. Outside the HLA region, the most significant finding (rs13119723; P = 2.0 x 10(-7)) was in the KIAA1109-TENR-IL2-IL21 linkage disequilibrium block. We independently confirmed association in two further collections (strongest association at rs6822844, 24 kb 5' of IL21; meta-analysis P = 1.3 x 10(-14), odds ratio = 0.63), suggesting that genetic variation in this region predisposes to celiac disease.
Asunto(s)
Enfermedad Celíaca/genética , Predisposición Genética a la Enfermedad , Variación Genética , Genoma Humano , Interleucina-2/genética , Interleucinas/genética , Animales , Cromosomas Humanos Par 4/genética , Humanos , Desequilibrio de Ligamiento , Ratones , Polimorfismo de Nucleótido Simple , Factores de RiesgoRESUMEN
A genome-wide association scan in individuals with Crohn's disease by the Wellcome Trust Case Control Consortium detected strong association at four novel loci. We tested 37 SNPs from these and other loci for association in an independent case-control sample. We obtained replication for the autophagy-inducing IRGM gene on chromosome 5q33.1 (replication P = 6.6 x 10(-4), combined P = 2.1 x 10(-10)) and for nine other loci, including NKX2-3, PTPN2 and gene deserts on chromosomes 1q and 5p13.
Asunto(s)
Autofagia/genética , Enfermedad de Crohn/genética , Proteínas de Unión al GTP/genética , Predisposición Genética a la Enfermedad , Variación Genética , Animales , Estudios de Casos y Controles , Humanos , Ratones , Polimorfismo de Nucleótido Simple , Análisis de Secuencia de ADNRESUMEN
We developed a massive-scale RNA sequencing protocol, short quantitative random RNA libraries or SQRL, to survey the complexity, dynamics and sequence content of transcriptomes in a near-complete fashion. This method generates directional, random-primed, linear cDNA libraries that are optimized for next-generation short-tag sequencing. We surveyed the poly(A)(+) transcriptomes of undifferentiated mouse embryonic stem cells (ESCs) and embryoid bodies (EBs) at an unprecedented depth (10 Gb), using the Applied Biosystems SOLiD technology. These libraries capture the genomic landscape of expression, state-specific expression, single-nucleotide polymorphisms (SNPs), the transcriptional activity of repeat elements, and both known and new alternative splicing events. We investigated the impact of transcriptional complexity on current models of key signaling pathways controlling ESC pluripotency and differentiation, highlighting how SQRL can be used to characterize transcriptome content and dynamics in a quantitative and reproducible manner, and suggesting that our understanding of transcriptional complexity is far from complete.
Asunto(s)
Células Madre Embrionarias/metabolismo , Perfilación de la Expresión Génica/métodos , ARN Mensajero/genética , Análisis de Secuencia de ARN/métodos , Animales , Diferenciación Celular , Células Madre Embrionarias/citología , Etiquetas de Secuencia Expresada , Perfilación de la Expresión Génica/estadística & datos numéricos , Biblioteca de Genes , Ratones , Células Madre Pluripotentes/citología , Células Madre Pluripotentes/metabolismo , Polimorfismo de Nucleótido Simple , Sensibilidad y Especificidad , Transducción de SeñalRESUMEN
Complete sets of cloned protein-encoding open reading frames (ORFs), or ORFeomes, are essential tools for large-scale proteomics and systems biology studies. Here we describe human ORFeome version 3.1 (hORFeome v3.1), currently the largest publicly available resource of full-length human ORFs (available at ). Generated by Gateway recombinational cloning, this collection contains 12,212 ORFs, representing 10,214 human genes, and corresponds to a 51% expansion of the original hORFeome v1.1. An online human ORFeome database, hORFDB, was built and serves as the central repository for all cloned human ORFs (http://horfdb.dfci.harvard.edu). This expansion of the original ORFeome resource greatly increases the potential experimental search space for large-scale proteomics studies, which will lead to the generation of more comprehensive datasets.