Christopher E. Mason

RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays

Ultra-high-throughput sequencing is emerging as an attractive alternative to microarrays for genotyping, analysis of methylation patterns, and identification of transcription factor binding sites. Here, we describe an application of the Illumina sequencing (formerly Solexa sequencing) platform to study mRNA expression levels. Our goals were to estimate technical variance associated with Illumina sequencing in this context and to compare its ability to identify differentially expressed genes with existing array technologies. To do so, we estimated gene expression differences between liver and kidney RNA samples using multiple sequencing replicates, and compared the sequencing data to results obtained from Affymetrix arrays using the same RNA samples. We find that the Illumina sequencing data are highly replicable, with relatively little technical variation, and thus, for many purposes, it may suffice to sequence each mRNA sample only once (i.e., using one lane). The information in a single lane of Illumina sequencing data appears comparable to that in a single array in enabling identification of differentially expressed genes, while allowing for additional analyses such as detection of low-expressed genes, alternative splice variants, and novel transcripts. Based on our observations, we propose an empirical protocol and a statistical framework for the analysis of gene expression using ultra-high-throughput sequencing technology.

Multiple Recurrent De Novo CNVs, Including Duplications of the 7q11.23 Williams Syndrome Region, Are Strongly Associated with Autism

We have undertaken a genome-wide analysis of rare copy-number variation (CNV) in 1124 autism spectrum disorder (ASD) families, each comprised of a single proband, unaffected parents, and, in most kindreds, an unaffected sibling. We find significant association of ASD with de novo duplications of 7q11.23, where the reciprocal deletion causes Williams-Beuren syndrome, characterized by a highly social personality. We identify rare recurrent de novo CNVs at five additional regions, including 16p13.2 (encompassing genes USP7 and C16orf72) and Cadherin 13, and implement a rigorous approach to evaluating the statistical significance of these observations. Overall, large de novo CNVs, particularly those encompassing multiple genes, confer substantial risks (OR = 5.6; CI = 2.6-12.0, p = 2.4 × 10(-7)). We estimate there are 130-234 ASD-related CNV regions in the human genome and present compelling evidence, based on cumulative data, for association of rare de novo events at 7q11.23, 15q11.2-13.1, 16p11.2, and Neurexin 1.

An integrated map of structural variation in 2,504 human genomes

Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis

Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. A whole-genome, exon-level expression analysis of 13 regions from left and right sides of the mid-fetal human brain revealed that 76% of genes are expressed, and 44% of these are differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as coexpression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. We show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. These data provide a wealth of biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.

Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data

A large number of computational methods have been developed for analyzing differential gene expression in RNA-seq data. We describe a comprehensive evaluation of common methods using the SEQC benchmark dataset and ENCODE data. We consider a number of key features, including normalization, accuracy of differential expression detection and differential expression analysis when one condition has no detectable expression. We find significant differences among the methods, but note that array-based methods adapted to RNA-seq data perform comparably to methods designed for RNA-seq. Our results demonstrate that increasing the number of replicate samples significantly improves detection power over increased sequencing depth.

Recurrent somatic TET2 mutations in normal elderly individuals with clonal hematopoiesis

Aging is characterized by clonal expansion of myeloid-biased hematopoietic stem cells and by increased risk of myeloid malignancies. Exome sequencing of three elderly females with clonal hematopoiesis, demonstrated by X-inactivation analysis, identified somatic TET2 mutations. Recurrence testing identified TET2 mutations in 10 out of 182 individuals with X-inactivation skewing. TET2 mutations were specific to individuals with clonal hematopoiesis without hematological malignancies and were associated with alterations in DNA methylation.

methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles

DNA methylation is a chemical modification of cytosine bases that is pivotal for gene regulation,cellular specification and cancer development. Here, we describe an R package, methylKit, thatrapidly analyzes genome-wide cytosine epigenetic profiles from high-throughput methylation andhydroxymethylation sequencing experiments. methylKit includes functions for clustering, samplequality visualization, differential methylation analysis and annotation features, thus automatingand simplifying many of the steps for discerning statistically significant bases or regions of DNAmethylation. Finally, we demonstrate methylKit on breast cancer data, in which we find statisticallysignificant regions of differential methylation and stratify tumor subtypes. methylKit is availableat http://code.google.com/p/methylkit.

L-Histidine Decarboxylase and Tourette's Syndrome

Tourettes syndrome is a common developmental neuropsychiatric disorder characterized by chronic motor and vocal tics. Despite a strong genetic contribution, inheritance is complex, and risk alleles have proven difficult to identify. Here, we describe an analysis of linkage in a two-generation pedigree leading to the identification of a rare functional mutation in the HDC gene encoding L-histidine decarboxylase, the rate-limiting enzyme in histamine biosynthesis. Our findings, together with previously published data from model systems, point to a role for histaminergic neurotransmission in the mechanism and modulation of Tourettes syndrome and tics.

Susceptibility loci for intracranial aneurysm in European and Japanese populations

Stroke is the worlds third leading cause of death. One cause of stroke, intracranial aneurysm, affects ∼2% of the population and accounts for 500,000 hemorrhagic strokes annually in mid-life (median age 50), most often resulting in death or severe neurological impairment. The pathogenesis of intracranial aneurysm is unknown, and because catastrophic hemorrhage is commonly the first sign of disease, early identification is essential. We carried out a multistage genome-wide association study (GWAS) of Finnish, Dutch and Japanese cohorts including over 2,100 intracranial aneurysm cases and 8,000 controls. Genome-wide genotyping of the European cohorts and replication studies in the Japanese cohort identified common SNPs on chromosomes 2q, 8q and 9p that show significant association with intracranial aneurysm with odds ratios 1.24–1.36. The loci on 2q and 8q are new, whereas the 9p locus was previously found to be associated with arterial diseases, including intracranial aneurysm. Associated SNPs on 8q likely act via SOX17, which is required for formation and maintenance of endothelial cells, suggesting a role in development and repair of the vasculature; CDKN2A at 9p may have a similar role. These findings have implications for the pathophysiology, diagnosis and therapy of intracranial aneurysm.

Assembly and diploid architecture of an individual human genome via single-molecule technologies

We present the first comprehensive analysis of a diploid human genome that combines single-molecule sequencing with single-molecule genome maps. Our hybrid assembly markedly improves upon the contiguity observed from traditional shotgun sequencing approaches, with scaffold N50 values approaching 30 Mb, and we identified complex structural variants (SVs) missed by other high-throughput approaches. Furthermore, by combining Illumina short-read data with long reads, we phased both single-nucleotide variants and SVs, generating haplotypes with over 99% consistency with previous trio-based studies. Our work shows that it is now possible to integrate single-molecule and high-throughput sequence data to generate de novo assembled genomes that approach reference quality.