Biology subjects

Shendure, J.

Publications and source records attributed to Shendure, J..

At least 91 records · Page 5Linked to original sources

bioRxiv2019

Trans- and cis-acting effects of the lncRNA Firre on epigenetic and structural features of the inactive X chromosome

Firre encodes a lncRNA involved in nuclear organization in mammals. Here we find that Firre RNA is transcribed from the active X chromosome (Xa) and exerts trans-acting effects on the inactive X chromosome (Xi). Allelic deletion of Firre on the Xa in a mouse hybrid fibroblast cell line results in a dramatic loss of the histone modification H3K27me3 and of components of the PRC2 complex on the Xi as well as the disruption of the perinucleolar location of the Xi. These features are measurably rescued by ectopic expression of a mouse or human Firre/FIRRE cDNA transgene, strongly supporting a conserved trans-acting role of the Firre transcript in maintaining the Xi heterochromatin environment. Surprisingly, CTCF occupancy is decreased on the Xi upon loss of Firre RNA, but is partially recovered by ectopic transgene expression, suggesting a functional link between Firre RNA and CTCF in maintenance of epigenetic features and/or location of the Xi. Loss of Firre RNA results in dysregulation of genes implicated in cell division and development, but not in reactivation of genes on the Xi, which retains its bipartite structure despite some changes in chromatin contact distribution. Allelic deletion or inversion of Firre on the Xi causes localized redistribution of chromatin contacts, apparently dependent on the orientation of CTCF binding sites clustered at the locus. Thus, the Firre locus and its RNA have roles in the maintenance of epigenetic features and structure of the Xi.

genomics↗

bioRxiv2019

Concurrent Genome and Epigenome Editing by CRISPR-Mediated Sequence Replacement

Recent advances in genome editing have facilitated the direct manipulation of not only the genome, but also the epigenome. Genome editing is typically performed by introducing a single CRISPR/Cas9-mediated double stranded break (DSB), followed by NHEJ or HDR mediated repair. Epigenome editing, and in particular methylation of CpG dinucleotides, can be performed using catalytically inactive Cas9 (dCas) fused to a methyltransferase domain. However, for investigations of the role of methylation in gene silencing, studies based on dCas9-methyltransferase have limited resolution and are potentially confounded by the effects of binding of the fusion protein. As an alternative strategy for epigenome editing, we tested CRISPR/Cas9 dual cutting of the genome in the presence of in vitro methylated exogenous DNA, i.e. to drive replacement of the DNA sequence intervening the dual cuts via NHEJ. In a proof-of-concept at the HPRT1 promoter, successful replacement events with heavily methylated alleles of a CpG island resulted in functional silencing of the HPRT1 gene. Although still limited in efficiency, our study demonstrates concurrent epigenome and genome editing in a single event, and opens the door to investigations of the functional consequences of methylation patterns at single CpG dinucleotide resolution. Our results furthermore support the conclusion that promoter methylation is sufficient to functionally silence gene expression.

genomics↗

bioRxiv2019

Characterizing the temporal dynamics of gene expression in single cells with sci-fate

Gene expression programs are dynamic, e.g. the cell cycle, response to stimuli, normal differentiation and development, etc. However, nearly all techniques for profiling gene expression in single cells fail to directly capture the dynamics of transcriptional programs, which limits the scope of biology that can be effectively investigated. Towards addressing this, we developed sci-fate, a new technique that combines S4U labeling of newly synthesized mRNA with single cell combinatorial indexing (sci-), in order to concurrently profile the whole and newly synthesized transcriptome in each of many single cells. As a proof-of-concept, we applied sci-fate to a model system of cortisol response and characterized expression dynamics in over 6,000 single cells. From these data, we quantify the dynamics of the cell cycle and glucocorticoid receptor activation, while also exploring their intersection. We furthermore use these data to develop a framework for inferring the distribution of cell state transitions. We anticipate sci-fate will be broadly applicable to quantitatively characterize transcriptional dynamics in diverse systems.

genomics↗

bioRxiv2019

Sci-Hi-C: a single-cell Hi-C method for mapping 3D genome organization in large number of single cells

The highly dynamic nature of chromosome conformation and three-dimensional (3D) genome organization leads to cell-to-cell variability in chromatin interactions within a cell population, even if the cells of the population appear to be functionally homogeneous. Hence, although Hi-C is a powerful tool for mapping 3D genome organization, this heterogeneity of chromosome higher order structure among individual cells limits the interpretive power of population based bulk Hi-C assays. Moreover, single-cell studies have the potential to enable the identification and characterization of rare cell populations or cell subtypes in a heterogeneous population. However, it may require surveying relatively large numbers of single cells to achieve statistically meaningful observations in single-cell studies. By applying combinatorial cellular indexing to chromosome conformation capture, we developed single-cell combinatorial indexed Hi-C (sci-Hi-C), a high throughput method that enables mapping chromatin interactomes in large number of single cells. We demonstrated the use of sci-Hi-C data to separate cells by karytoypic and cell-cycle state differences and to identify cellular variability in mammalian chromosomal conformation. Here, we provide a detailed description of method design and step-by-step working protocols for sci-Hi-C.

genomics↗

bioRxiv2019

A systematic evaluation of the design, orientation, and sequence context dependencies of massively parallel reporter assays

Massively parallel reporter assays (MPRAs) functionally screen thousands of sequences for regulatory activity in parallel. Although MPRAs have been applied to address diverse questions in gene regulation, there has been no systematic comparison of how differences in experimental design influence findings. Here, we screen a library of 2,440 sequences, representing candidate liver enhancers and controls, in HepG2 cells for regulatory activity using nine different approaches (including conventional episomal, STARR-seq, and lentiviral MPRA designs). We identify subtle but significant differences in the resulting measurements that correlate with epigenetic and sequence-level features. We also test this library in both orientations with respect to the promoter, validating en masse that enhancer activity is robustly independent of orientation. Finally, we develop and apply a novel method to assemble and functionally test libraries of the same putative enhancers as 192-mers, 354-mers, and 678-mers, and observe surprisingly large differences in functional activity. This work provides a framework for the experimental design of high-throughput reporter assays, suggesting that the extended sequence context of tested elements, and to a lesser degree the precise assay, influence MPRA results.

genomics↗

bioRxiv2019

An open-source platform to distribute and interpret data from multiplexed assays of variant effect

Multiplex Assays of Variant Effect (MAVEs), such as deep mutational scans and massively parallel reporter assays, test thousands of sequence variants in a single experiment. Despite the importance of MAVE data for basic and clinical research, there is no standard resource for their discovery and distribution. Here we present MaveDB, a public repository for large-scale measurements of sequence variant impact, designed for interoperability with applications to interpret these datasets. We also describe the first of these applications, MaveVis, which retrieves, visualizes, and contextualizes variant effect maps. Together, the database and applications will empower the community to mine these powerful datasets.

genomics↗

bioRxiv2019

Chromatin compartment dynamics in a haploinsufficient model of cardiac laminopathy

Pathogenic mutations in A-type nuclear lamins cause dilated cardiomyopathy, which is postulated to result from dysregulated gene expression due to changes in chromatin organization into active and inactive compartments. To test this, we performed genome-wide chromosome conformation analyses (Hi-C) in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) with a haploinsufficient mutation for lamin A/C. Compared to gene-corrected cells, mutant hiPSC-CMs have marked electrophysiological and contractile alterations, with modest gene expression changes. While large-scale changes in chromosomal topology are evident, differences in chromatin compartmentalization are limited to a few hotspots that escape inactivation during cardiogenesis. These regions exhibit upregulation of multiple non-cardiac genes including CACNA1A, encoding for neuronal P/Q-type calcium channels. Pharmacological inhibition of the resulting current partially mitigates the electrical alterations. On the other hand, A/B compartment changes do not explain most gene expression alterations in mutant hiPSC-CMs. We conclude that global errors in chromosomal compartmentation are not the primary pathogenic mechanism in heart failure due to lamin A/C haploinsufficiency. SummaryBertero et al. observe that lamin A/C haploinsufficiency in human cardiomyocytes markedly alters electrophysiology, contractility, gene expression, and chromosomal topology. Contrary to expectations, however, changes in chromatin compartments involve just few regions, and most dysregulated genes lie outside these hotspots. Condensed titleGenomic effects of lamin A/C haploinsufficiency

genomics↗

bioRxiv2019

Supervised classification enables rapid annotation of cell atlases

Single cell technologies for profiling tissues or even entire organisms are rapidly being adopted. However, the manual process by which cell types are typically annotated in the resulting data is labor-intensive and increasingly rate-limiting for the field. Here we describe Garnett, an algorithm and accompanying software for rapidly annotating cell types in scRNA-seq and scATAC-seq datasets, based on an interpretable, hierarchical markup language of cell type-specific genes. Garnett successfully classifies cell types in tissue and whole organism datasets, as well as across species.

genomics↗

bioRxiv2019

Capturing cell type-specific chromatin structural patterns by applying topic modeling to single-cell Hi-C data

Single-cell Hi-C (scHi-C) interrogates genome-wide chromatin interaction in individual cells, allowing us to gain insights into 3D genome organization. However, the extremely sparse nature of scHi-C data poses a significant barrier to analysis, limiting our ability to tease out hidden biological information. In this work, we approach this problem by applying topic modeling to scHi-C data. Topic modeling is well-suited for discovering latent topics in a collection of discrete data. For our analysis, we generate twelve different single-cell combinatorial indexed Hi-C (sciHi-C) libraries from five human cell lines (GM12878, H1Esc, HFF, IMR90, and HAP1), consisting over 25,000 cells. We demonstrate that topic modeling is able to successfully capture cell type differences from sciHi-C data in the form of "chromatin topics." We further show enrichment of particular compartment structures associated with locus pairs in these topics.

genomics↗

bioRxiv2018

Saturation mutagenesis of disease-associated regulatory elements

The majority of common variants associated with common diseases, as well as an unknown proportion of causal mutations for rare diseases, fall in noncoding regions of the genome. Although catalogs of noncoding regulatory elements are steadily improving, we have a limited understanding of the functional effects of mutations within them. Here, we performed saturation mutagenesis in conjunction with massively parallel reporter assays on 20 disease-associated gene promoters and enhancers, generating functional measurements for over 30,000 single nucleotide substitution and deletion mutations. We find that the density of putative transcription factor binding sites varies widely between regulatory elements, as does the extent to which evolutionary conservation or various integrative scores predict functional effects. These data provide a powerful resource for interpreting the pathogenicity of clinically observed mutations in these disease-associated regulatory elements, and also comprise a gold-standard dataset for the further development of algorithms that aim to predict the regulatory effects of noncoding mutations.

genetics↗

bioRxiv2018

Massively parallel profiling and predictive modeling of the outcomes of CRISPR/Cas9-mediated double-strand break repair

Non-homologous end-joining (NHEJ) plays an important role in double-strand break (DSB) repair of DNA. Recent studies have shown that the error patterns of NHEJ are strongly biased by sequence context, but these studies were based on relatively few templates. To investigate this more thoroughly, we systematically profiled [~]1.16 million independent mutational events resulting from CRISPR/Cas9-mediated cleavage and NHEJ-mediated DSB repair of 6,872 synthetic target sequences, introduced into a human cell line via lentiviral infection. We find that: 1) insertions are dominated by 1 bp events templated by sequence immediately upstream of the cleavage site, 2) deletions are predominantly associated with microhomology, and 3) targets exhibit variable but reproducible diversity with respect to the number and relative frequency of the mutational outcomes to which they give rise. From these data, we trained a model that uses local sequence context to predict the distribution of mutational outcomes. Exploiting the bias of NHEJ outcomes towards microhomology mediated events, we demonstrate the programming of deletion patterns by introducing microhomology to specific locations in the vicinity of the DSB site. We anticipate that our results will inform investigations of DSB repair mechanisms as well as the design of CRISPR/Cas9 experiments for diverse applications including genome-wide screens, gene therapy, lineage tracing and molecular recording.

genomics↗

bioRxiv2018

Genome wide association with quantitative resistance phenotypes in Mycobacterium tuberculosis reveals novel resistance genes and regulatory regions

Drug resistance is threatening attempts at tuberculosis epidemic control. Molecular diagnostics for drug resistance that rely on the detection of resistance-related mutations could expedite patient care and accelerate progress in TB eradication. We performed minimum inhibitory concentration testing for 12 anti-TB drugs together with Illumina whole genome sequencing on 1452 clinical Mycobacterium tuberculosis (MTB) isolates. We then used a linear mixed model to evaluate genome wide associations between mutations in MTB genes or noncoding regions and drug resistance, followed by validation of our findings in an independent dataset of 792 patient isolates. Novel associations at 13 genomic loci were confirmed in the validation set, with 2 involving noncoding regions. We found promoter mutations to have smaller average effects on resistance levels than gene body mutations in genes where both can contribute to resistance. Enabled by a quantitative measure of resistance, we estimated the heritability of the resistance phenotype to 11 anti-TB drugs and identify a lower than expected contribution from known resistance genes. We also report the proportion of variation in resistance levels explained by the novel loci identified here. This study highlights the complexity of the genomic mechanisms associated with the MTB resistance phenotype, including the relatively large number of potentially causative or compensatory loci, and emphasizes the contribution of the noncoding portion of the genome.

evolutionary biology↗

bioRxiv2018

Predicting mRNA abundance directly from genomic sequence using deep convolutional neural networks

Algorithms that accurately predict gene structure from primary sequence alone were transformative for annotating the human genome. Can we also predict the expression levels of genes based solely on genome sequence? Here we sought to apply deep convolutional neural networks towards this goal. Surprisingly, a model that includes only promoter sequences and features associated with mRNA stability explains 59% and 71% of variation in steady-state mRNA levels in human and mouse, respectively. This model, which we call Xpresso, more than doubles the accuracy of alternative sequence-based models, and isolates rules as predictive as models relying on ChIP-seq data. Xpresso recapitulates genome-wide patterns of transcriptional activity and predicts the influence of enhancers, heterochromatic domains, and microRNAs. Model interpretation reveals that promoter-proximal CpG dinucleotides strongly predict transcriptional activity. Looking forward, we propose the accurate prediction of cell type-specific gene expression based solely on primary sequence as a grand challenge for the field.

genomics↗

bioRxiv2018

A combination of transcription factors mediates inducible interchromosomal pairing

Remodeling of the three-dimensional organization of a genome has been previously described (e.g. condition-specific pairing or looping), but it remains unknown which factors specify and mediate such shifts in chromosome conformation. Here we describe an assay, MAP-C (Mutation Analysis in Pools by Chromosome conformation capture), that enables the simultaneous characterization of hundreds of cis or trans-acting mutations for their effects on a chromosomal contact or loop. As a proof of concept, we applied MAP-C to systematically dissect the molecular mechanism of inducible interchromosomal pairing between HAS1pr-TDA1pr alleles in Saccharomyces yeast. We identified three transcription factors, Leu3, Sdd4 (Ypr022c), and Rgt1, whose collective binding to nearby DNA sequences is necessary and sufficient for inducible pairing between binding site clusters. Rgt1 contributes to the regulation of pairing, both through changes in expression level and through its interactions with the Tup1/Ssn6 repressor complex. HAS1pr-TDA1pr is the only locus with a cluster of binding site motifs for all three factors in both S. cerevisiae and S. uvarum genomes, but the promoter for HXT3, which contains Leu3 and Rgt1 motifs, also exhibits inducible homolog pairing. Altogether, our results demonstrate that specific combinations of transcription factors can mediate condition-specific interchromosomal contacts, and reveal a molecular mechanism for interchromosomal contacts and mitotic homolog pairing.

genomics↗

bioRxiv2018

Functional Testing of Thousands of Osteoarthritis-Associated Variants for Regulatory Activity

To date, genome-wide association studies have implicated at least 35 loci in osteoarthritis, but due to linkage disequilibrium, we have yet to pinpoint the specific variants that underlie these associations, nor the mechanisms by which they contribute to disease risk. Here we functionally tested 1,605 single nucleotide variants associated with osteoarthritis for regulatory activity using a massively parallel reporter assay. We identified six single nucleotide polymorphisms (SNPs) with differential regulatory activity between the major and minor alleles. We show that our most significant hit, rs4730222, drives increased expression of an alternative isoform of HBP1 in a heterozygote chondrosarcoma cell line, a CRISPR-edited osteosarcoma cell line, and in chondrocytes derived from osteoarthritis patients.

genomics↗

bioRxiv2018

crisprQTL mapping as a genome-wide association framework for cellular genetic screens

Expression quantitative trait locus (eQTL) and genome-wide association studies (GWAS) are powerful paradigms for mapping the determinants of gene expression and organismal phenotypes, respectively. However, eQTL mapping and GWAS are limited in scope (to naturally occurring, common genetic variants) and resolution (by linkage disequilibrium). Here, we present crisprQTL mapping, a framework in which large numbers of CRISPR/Cas9 perturbations are introduced to each cell on an isogenic background, followed by single-cell RNA-seq (scRNA-seq). crisprQTL mapping is analogous to conventional human eQTL studies, but with individual humans replaced by individual cells; genetic variants replaced by unique combinations of unlinked guide RNA (gRNA)-programmed perturbations per cell; and tissue-level RNA-seq of many individuals replaced by scRNA-seq of many cells. By randomly introducing gRNAs, a single population of cells can be leveraged to test for association between each perturbation and the expression of any potential target gene, analogous to how eQTL studies leverage populations of humans to test millions of genetic variants for associations with expression in a genome-wide manner. However, crisprQTL mapping is neither limited to naturally occurring, common genetic variants nor by linkage disequilibrium. As a proof-of-concept, we applied crisprQTL mapping to evaluate 1,119 candidate enhancers with no strong a priori hypothesis as to their target gene(s). Perturbations were made by a nuclease-dead Cas9 (dCas9) tethered to KRAB, and introduced at a mean allele frequency of 1.1% into a population of 47,650 profiled human K562 cells (median of 15 gRNAs identified per cell). We tested for differential expression of all genes within 1 megabase (Mb) of each candidate enhancer, effectively evaluating 17,584 potential enhancer-target gene relationships within a single experiment. At an empirical false discovery rate (FDR) of 10%, we identify 128 cis crisprQTLs (11%) whose targeting resulted in downregulation of 105 nearby genes. crisprQTLs were strongly enriched for proximity to their target genes (median 34.3 kilobases (Kb)) and the strength of H3K27ac, p300, and lineage-specific transcription factor (TF) ChIP-seq peaks. Our results establish the power of the eQTL mapping paradigm as applied to programmed variation in populations of cells, rather than natural variation in populations of individuals. We anticipate that crisprQTL mapping will facilitate the comprehensive elucidation of the cis-regulatory architecture of the human genome.

genomics↗

bioRxiv2018

Accurate functional classification of thousands of BRCA1 variants with saturation genome editing

Variants of uncertain significance (VUS) fundamentally limit the utility of genetic information in a clinical setting. The challenge of VUS is epitomized by BRCA1, a tumor suppressor gene integral to DNA repair and genomic stability. Germline BRCA1 loss-of-function (LOF) variants predispose women to early-onset breast and ovarian cancers. Although BRCA1 has been sequenced in millions of women, the risk associated with most newly observed variants cannot be definitively assigned. Data sharing attenuates this problem but it is unlikely to solve it, as most newly observed variants are exceedingly rare. In lieu of genetic evidence, experimental approaches can be used to functionally characterize VUS. However, to date, functional studies of BRCA1 VUS have been conducted in a post hoc, piecemeal fashion. Here we employ saturation genome editing to assay 96.5% of all possible single nucleotide variants (SNVs) in 13 exons that encode functionally critical domains of BRCA1. Our assay measures cellular fitness in a haploid human cell line whose survival is dependent on intact BRCA1 function. The resulting function scores for nearly 4,000 SNVs are bimodally distributed and almost perfectly concordant with established assessments of pathogenicity. Sequence-function maps enhanced by parallel measurements of variant effects on mRNA levels reveal mechanisms by which loss-of-function SNVs arise. Hundreds of missense SNVs critical for protein function are identified, as well as dozens of exonic and intronic SNVs that compromise BRCA1 function by disrupting splicing or transcript stability. We predict that these function scores will be directly useful for the clinical interpretation of cancer risk based on BRCA1 sequencing. Furthermore, we propose that this paradigm can be extended to overcome the challenge of VUS in other genes in which genetic variation is clinically actionable.

genomics↗

bioRxiv2018

A multiplexed homology-directed DNA repair assay reveals the impact of ~1,700 BRCA1 variants on protein function

Loss-of-function mutations in BRCA1 confer a predisposition to breast and ovarian cancer. Genetic testing for mutations in the BRCA1 gene frequently reveals a missense variant for which the impact on the molecular function of the BRCA1 protein is unknown. Functional BRCA1 is required for homology directed repair (HDR) of double-strand DNA breaks, a key activity for maintaining genome integrity and tumor suppression. Here we describe a multiplex HDR reporter assay to simultaneously measure the effect of hundreds of variants of BRCA1 on its role in DNA repair. Using this assay, we measured the effects of ~1,700 amino acid substitutions in the first 302 residues of BRCA1. Benchmarking these results against variants with known effects, we demonstrate accurate discrimination of loss-of-function versus benign variants. We anticipate that this assay can be used to functionally characterize BRCA1 missense variants at scale, even before the variants are observed in results from genetic testing.

genomics↗