Jared C. Roach

Analysis of Genetic Inheritance in a Family Quartet by Whole-Genome Sequencing

Runs in the Family The power to detect mutations involved in disease by genome sequencing is enhanced when combined with the ability to discover specific mutations that may have arisen between offspring and parents. Roach et al. (p. 636, published online 10 March) present the sequence of a family with two offspring affected with two genetic disorders: Miller syndrome and primary ciliary dyskinesia. Sequence analysis of the children and their parents not only showed that the intergenerational mutation rate was lower than anticipated but also revealed recombination sites and the occurrence of rare polymorphisms. Genomic sequencing of an entire family reveals the rate of spontaneous mutations in humans and identifies disease genes. We analyzed the whole-genome sequences of a family of four, consisting of two siblings and their parents. Family-based sequencing allowed us to delineate recombination sites precisely, identify 70% of the sequencing errors (resulting in > 99.999% accuracy), and identify very rare single-nucleotide polymorphisms. We also directly estimated a human intergeneration mutation rate of ~1.1 × 10−8 per position per haploid genome. Both offspring in this family have two recessive disorders: Miller syndrome, for which the gene was concurrently identified, and primary ciliary dyskinesia, for which causative genes have been previously identified. Family-based genome analysis enabled us to narrow the candidate genes for both of these Mendelian disorders to only four. Our results demonstrate the value of complete genome sequencing in families.

Uncovering a Macrophage Transcriptional Program by Integrating Evidence from Motif Scanning and Expression Dynamics

Macrophages are versatile immune cells that can detect a variety of pathogen-associated molecular patterns through their Toll-like receptors (TLRs). In response to microbial challenge, the TLR-stimulated macrophage undergoes an activation program controlled by a dynamically inducible transcriptional regulatory network. Mapping a complex mammalian transcriptional network poses significant challenges and requires the integration of multiple experimental data types. In this work, we inferred a transcriptional network underlying TLR-stimulated murine macrophage activation. Microarray-based expression profiling and transcription factor binding site motif scanning were used to infer a network of associations between transcription factor genes and clusters of co-expressed target genes. The time-lagged correlation was used to analyze temporal expression data in order to identify potential causal influences in the network. A novel statistical test was developed to assess the significance of the time-lagged correlation. Several associations in the resulting inferred network were validated using targeted ChIP-on-chip experiments. The network incorporates known regulators and gives insight into the transcriptional control of macrophage activation. Our analysis identified a novel regulator (TGIF1) that may have a role in macrophage activation.

Comparative Genomics of the Human and Mouse T Cell Receptor Loci

The availability of the complete genomic sequences of the human and mouse T cell receptor loci opens up new opportunities for understanding T cell receptors (TCRs) and their genes. The full complement of TCR gene segments is finally known and should prove a valuable resource for supporting functional studies. A rational nomenclature system has been implemented and is widely available through IMGT and other public databases. Systematic comparisons of the genomic sequences within each locus, between loci, and across species enable precise analyses of the various diversification mechanisms and some regulatory signals. The genomic landscape of the TCR loci provides fundamental insights into TCR evolution as highly localized and tightly regulated gene families.

Pairwise end sequencing : a unified approach to genomic mapping and sequencing

Strategies for large-scale genomic DNA sequencing currently require physical mapping, followed by detailed mapping, and finally sequencing. The level of mapping detail determines the amount of effort, or sequence redundancy, required to finish a project. Current strategies attempt to find a balance between mapping and sequencing efforts. One such approach is to employ strategies that use sequence data to build physical maps. Such maps alleviate the need for prior mapping and reduce the final required sequence redundancy. To this end, the utility of correlating pairs of sequence data derived from both ends of subcloned templates is well recognized. However, optimal strategies employing such pairwise data have not been established. In the present work, we simulate and analyze the parameters of pairwise sequencing projects including template length, sequence read length, and total sequence redundancy. One pairwise strategy based on sequencing both ends of plasmid subclones is recommended and illustrated with raw data simulations. We find that pairwise strategies are effective with both small (cosmid) and large (megaYAC) targets and produce ordered sequence data with a high level of mapping completeness. They are ideal for finescale mapping and gene finding and as initial steps for either a high- or a low-redundancy sequencing effort. Such strategies are highly automatable.

The Molecular Evolution of the Vertebrate Trypsinogens

Abstract. We expand the already large number of known trypsinogen nucleotide and amino acid sequences by presenting additional trypsinogen sequences from the tunicate (Boltenia villosa), the lamprey (Petromyzon marinus), the pufferfish (Fugu rubripes), and the frog (Xenopus laevis). The current array of known trypsinogen sequences now spans the entire vertebrate phylogeny. Phylogenetic analysis is made difficult by the presence of multiple isozymes within species and rates of evolution that vary highly between both species and isozymes. We nevertheless present a Fitch-Margoliash phylogeny constructed from pairwise distances. We employ this phylogeny as a vehicle for speculation on the evolution of the trypsinogen gene family as well as the general modes of evolution of multigene families. Unique attributes of the lamprey and tunicate trypsinogens are noted.

Kaviar: an accessible system for testing SNV novelty

SUMMARY With the rapidly expanding availability of data from personal genomes, exomes and transcriptomes, medical researchers will frequently need to test whether observed genomic variants are novel or known. This task requires downloading and handling large and diverse datasets from a variety of sources, and processing them with bioinformatics tools and pipelines. Alternatively, researchers can upload data to online tools, which may conflict with privacy requirements. We present here Kaviar, a tool that greatly simplifies the assessment of novel variants. Kaviar includes: (i) an integrated and growing database of genomic variation from diverse sources, including over 55 million variants from personal genomes, family genomes, transcriptomes, SNV databases and population surveys; and (ii) software for querying the database efficiently.

Rare variants in neuronal excitability genes influence risk for bipolar disorder

Significance Bipolar disorder (BD) is a common, severe, and recurrent psychiatric disorder with no known cure and substantial morbidity and mortality. Heritable causes contribute up to 80% of the lifetime risk for BD. Common genetic variation explains ∼25% of this heritable risk. Rare genetic variants may explain additional risk. We identified contributions of rare variants to BD by sequencing the genomes of 200 individuals from 41 families with BD. The two main findings of this study were as follows: rare risk variants for BD were enriched in genes and pathways that regulate diverse aspects of neuronal excitability; and most of these risk variants were noncoding with predicted regulatory functions. These results highlight specific hypotheses for future research and potential therapeutic targets. We sequenced the genomes of 200 individuals from 41 families multiply affected with bipolar disorder (BD) to identify contributions of rare variants to genetic risk. We initially focused on 3,087 candidate genes with known synaptic functions or prior evidence from genome-wide association studies. BD pedigrees had an increased burden of rare variants in genes encoding neuronal ion channels, including subunits of GABAA receptors and voltage-gated calcium channels. Four uncommon coding and regulatory variants also showed significant association, including a missense variant in GABRA6. Targeted sequencing of 26 of these candidate genes in an additional 3,014 cases and 1,717 controls confirmed rare variant associations in ANK3, CACNA1B, CACNA1C, CACNA1D, CACNG2, CAMK2A, and NGF. Variants in promoters and 5′ and 3′ UTRs contributed more strongly than coding variants to risk for BD, both in pedigrees and in the case-control cohort. The genes and pathways identified in this study regulate diverse aspects of neuronal excitability. We conclude that rare variants in neuronal excitability genes contribute to risk for BD.

A unified test of linkage analysis and rare-variant association for analysis of pedigree sequence data

High-throughput sequencing of related individuals has become an important tool for studying human disease. However, owing to technical complexity and lack of available tools, most pedigree-based sequencing studies rely on an ad hoc combination of suboptimal analyses. Here we present pedigree-VAAST (pVAAST), a disease-gene identification tool designed for high-throughput sequence data in pedigrees. pVAAST uses a sequence-based model to perform variant and gene-based linkage analysis. Linkage information is then combined with functional prediction and rare variant case-control association information in a unified statistical framework. pVAAST outperformed linkage and rare-variant association tests in simulations and identified disease-causing genes from whole-genome sequence data in three human pedigrees with dominant, recessive and de novo inheritance patterns. The approach is robust to incomplete penetrance and locus heterogeneity and is applicable to a wide variety of genetic traits. pVAAST maintains high power across studies of monogenic, high-penetrance phenotypes in a single pedigree to highly polygenic, common phenotypes involving hundreds of pedigrees.

Genetic Mapping at 3-Kilobase Resolution Reveals Inositol 1,4,5-Triphosphate Receptor 3 as a Risk Factor for Type 1 Diabetes in Sweden

We mapped the genetic influences for type 1 diabetes (T1D), using 2,360 single-nucleotide polymorphism (SNP) markers in the 4.4-Mb human major histocompatibility complex (MHC) locus and the adjacent 493 kb centromeric to the MHC, initially in a survey of 363 Swedish T1D cases and controls. We confirmed prior studies showing association with T1D in the MHC, most significantly near HLA-DR/DQ. In the region centromeric to the MHC, we identified a peak of association within the inositol 1,4,5-triphosphate receptor 3 gene (ITPR3; formerly IP3R3). The most significant single SNP in this region was at the center of the ITPR3 peak of association (P=1.7 x 10(-4) for the survey study). For validation, we typed an additional 761 Swedish individuals. The P value for association computed from all 1,124 individuals was 1.30 x 10(-6) (recessive odds ratio 2.5; 95% confidence interval [CI] 1.7-3.9). The estimated population-attributable risk of 21.6% (95% CI 10.0%-31.0%) suggests that variation within ITPR3 reflects an important contribution to T1D in Sweden. Two-locus regression analysis supports an influence of ITPR3 variation on T1D that is distinct from that of any MHC class II gene.

Transcription factor expression in lipopolysaccharide-activated peripheral-blood-derived mononuclear cells

Transcription factors play a key role in integrating and modulating biological information. In this study, we comprehensively measured the changing abundances of mRNAs over a time course of activation of human peripheral-blood-derived mononuclear cells (“macrophages”) with lipopolysaccharide. Global and dynamic analysis of transcription factors in response to a physiological stimulus has yet to be achieved in a human system, and our efforts significantly advanced this goal. We used multiple global high-throughput technologies for measuring mRNA levels, including massively parallel signature sequencing and GeneChip microarrays. We identified 92 of 1,288 known human transcription factors as having significantly measurable changes during our 24-h time course. At least 42 of these changes were previously unidentified in this system. Our data demonstrate that some transcription factors operate in a functional range below 10 transcripts per cell, whereas others operate in a range three orders of magnitude greater. The highly reproducible response of many mRNAs indicates feedback control. A broad range of activation kinetics was observed; thus, combinatorial regulation by small subsets of transcription factors would permit almost any timing input to cis-regulatory elements controlling gene transcription.