Rupali P Patwardhan

Massively parallel functional dissection of mammalian enhancers in vivo

The functional consequences of genetic variation in mammalian regulatory elements are poorly understood. We report the in vivo dissection of three mammalian enhancers at single-nucleotide resolution through a massively parallel reporter assay. For each enhancer, we synthesized a library of >100,000 mutant haplotypes with 2–3% divergence from the wild-type sequence. Each haplotype was linked to a unique sequence tag embedded within a transcriptional cassette. We introduced each enhancer library into mouse liver and measured the relative activities of individual haplotypes en masse by sequencing the transcribed tags. Linear regression analysis yielded highly reproducible estimates of the effect of every possible single-nucleotide change on enhancer activity. The functional consequence of most mutations was modest, with ∼22% affecting activity by >1.2-fold and ∼3% by >2-fold. Several, but not all, positions with higher effects showed evidence for purifying selection, or co-localized with known liver-associated transcription factor binding sites, demonstrating the value of empirical high-resolution functional analysis.

Haplotype-resolved genome sequencing of a Gujarati Indian individual

Haplotype information is essential to the complete description and interpretation of genomes, genetic diversity and genetic ancestry. Although individual human genome sequencing is increasingly routine, nearly all such genomes are unresolved with respect to haplotype. Here we combine the throughput of massively parallel sequencing with the contiguity information provided by large-insert cloning to experimentally determine the haplotype-resolved genome of a South Asian individual. A single fosmid library was split into a modest number of pools, each providing ∼3% physical coverage of the diploid genome. Sequencing of each pool yielded reads overwhelmingly derived from only one homologous chromosome at any given location. These data were combined with whole-genome shotgun sequence to directly phase 94% of ascertained heterozygous single nucleotide polymorphisms (SNPs) into long haplotype blocks (N50 of 386 kilobases (kbp)). This method also facilitates the analysis of structural variation, for example, to anchor novel insertions to specific locations and haplotypes.

Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions

Genomes assembled de novo from short reads are highly fragmented relative to the finished chromosomes of Homo sapiens and key model organisms generated by the Human Genome Project. To address this problem, we need scalable, cost-effective methods to obtain assemblies with chromosome-scale contiguity. Here we show that genome-wide chromatin interaction data sets, such as those generated by Hi-C, are a rich source of long-range information for assigning, ordering and orienting genomic sequences to chromosomes, including across centromeres. To exploit this finding, we developed an algorithm that uses Hi-C data for ultra-long-range scaffolding of de novo genome assemblies. We demonstrate the approach by combining shotgun fragment and short jump mate-pair sequences with Hi-C data to generate chromosome-scale de novo assemblies of the human, mouse and Drosophila genomes, achieving—for the human genome—98% accuracy in assigning scaffolds to chromosome groups and 99% accuracy in ordering and orienting scaffolds within chromosome groups. Hi-C data can also be used to validate chromosomal translocations in cancer genomes.

Parallel, tag-directed assembly of locally derived short sequence reads

We demonstrate subassembly, an in vitro library construction method that extends the utility of short-read sequencing platforms to applications requiring long, accurate reads. A long DNA fragment library is converted to a population of nested sublibraries, and a tag sequence directs grouping of short reads derived from the same long fragment, enabling localized assembly of long fragment sequences. Subassembly may facilitate accurate de novo genome assembly and metagenome sequencing.

Massively parallel decoding of mammalian regulatory sequences supports a flexible organizational model

Despite continual progress in the cataloging of vertebrate regulatory elements, little is known about their organization and regulatory architecture. Here we describe a massively parallel experiment to systematically test the impact of copy number, spacing, combination and order of transcription factor binding sites on gene expression. A complex library of ∼5,000 synthetic regulatory elements containing patterns from 12 liver-specific transcription factor binding sites was assayed in mice and in HepG2 cells. We find that certain transcription factors act as direct drivers of gene expression in homotypic clusters of binding sites, independent of spacing between sites, whereas others function only synergistically. Heterotypic enhancers are stronger than their homotypic analogs and favor specific transcription factor binding site combinations, mimicking putative native enhancers. Exhaustive testing of binding site permutations suggests that there is flexibility in binding site order. Our findings provide quantitative support for a flexible model of regulatory element activity and suggest a framework for the design of synthetic tissue-specific enhancers.

Gene networks in Drosophila melanogaster: integrating experimental data to predict gene function

BackgroundDiscovering the functions of all genes is a central goal of contemporary biomedical research. Despite considerable effort, we are still far from achieving this goal in any metazoan organism. Collectively, the growing body of high-throughput functional genomics data provides evidence of gene function, but remains difficult to interpret.ResultsWe constructed the first network of functional relationships for Drosophila melanogaster by integrating most of the available, comprehensive sets of genetic interaction, protein-protein interaction, and microarray expression data. The complete integrated network covers 85% of the currently known genes, which we refined to a high confidence network that includes 20,000 functional relationships among 5,021 genes. An analysis of the network revealed a remarkable concordance with prior knowledge. Using the network, we were able to infer a set of high-confidence Gene Ontology biological process annotations on 483 of the roughly 5,000 previously unannotated genes. We also show that this approach is a means of inferring annotations on a class of genes that cannot be annotated based solely on sequence similarity. Lastly, we demonstrate the utility of the network through reanalyzing gene expression data to both discover clusters of coregulated genes and compile a list of candidate genes related to specific biological processes.ConclusionsHere we present the the first genome-wide functional gene network in D. melanogaster. The network enables the exploration, mining, and reanalysis of experimental data, as well as the interpretation of new data. The inferred annotations provide testable hypotheses of previously uncharacterized genes.

Systematic Dissection of Coding Exons at Single Nucleotide Resolution Supports an Additional Role in Cell-Specific Transcriptional Regulation

In addition to their protein coding function, exons can also serve as transcriptional enhancers. Mutations in these exonic-enhancers (eExons) could alter both protein function and transcription. However, the functional consequence of eExon mutations is not well known. Here, using massively parallel reporter assays, we dissect the enhancer activity of three liver eExons (SORL1 exon 17, TRAF3IP2 exon 2, PPARG exon 6) at single nucleotide resolution in the mouse liver. We find that both synonymous and non-synonymous mutations have similar effects on enhancer activity and many of the deleterious mutation clusters overlap known liver-associated transcription factor binding sites. Carrying a similar massively parallel reporter assay in HeLa cells with these three eExons found differences in their mutation profiles compared to the liver, suggesting that enhancers could have distinct operating profiles in different tissues. Our results demonstrate that eExon mutations could lead to multiple phenotypes by disrupting both the protein sequence and enhancer activity and that enhancers can have distinct mutation profiles in different cell types.