Abstract: Most phenotype-associated genetic variants map to non-coding regulatory regions of the human genome. Moreover, variants associated with blood cell phenotypes are enriched in regulatory regions active during hematopoiesis. To systematically explore the nature of these regions, we developed a highly efficient strategy, Perturb-multiome, that makes it possible to simultaneously profile both chromatin accessibility and gene expression in single cells with CRISPR-mediated perturbation of a range of master transcription factors (TFs). This approach allowed us to examine the connection between TFs, accessible regions, and gene expression across the genome throughout hematopoietic differentiation. We discovered that variants within the TF-sensitive accessible chromatin regions, while representing less than 0.3% of the genome, show a ~100-fold enrichment in heritability across certain blood cell phenotypes; this enrichment is strikingly higher than for other accessible chromatin regions. Our approach facilitates large-scale mechanistic understanding of phenotype-associated genetic variants by connecting key cis-regulatory elements and their target genes within gene regulatory networks.


Cohesin-mediated 3D contacts tune enhancer-promoter regulation

Abstract: Enhancers are key drivers of gene regulation thought to act via 3D physical interactions with the promoters of their target genes. However, genome-wide depletions of architectural proteins such as cohesin result in only limited changes in gene expression, despite a loss of contact domains and loops. Consequently, the role of cohesin and 3D contacts in enhancer function remains debated. Here, we developed CRISPRi of regulatory elements upon degron operation (CRUDO), a novel approach to measure how changes in contact frequency impact enhancer effects on target genes by perturbing enhancers with CRISPRi and measuring gene expression in the presence or absence of cohesin. We systematically perturbed all 1,039 candidate enhancers near five cohesin-dependent genes and identified 34 enhancer-gene regulatory interactions. Of 26 regulatory interactions with sufficient statistical power to evaluate cohesin dependence, 18 show cohesin-dependent effects. A decrease in enhancer-promoter contact frequency upon removal of cohesin is frequently accompanied by a decrease in the regulatory effect of the enhancer on gene expression, consistent with a contact-based model for enhancer function. However, changes in contact frequency and regulatory effects on gene expression vary as a function of distance, with distal enhancers (e.g., >50Kb) experiencing much larger changes than proximal ones (e.g., <50Kb). Because most enhancers are located close to their target genes, these observations can explain how only a small subset of genes - those with strong distal enhancers - are sensitive to cohesin. Together, our results illuminate how 3D contacts, influenced by both cohesin and genomic distance, tune enhancer effects on gene expression.

bioRxiv : the preprint server for biology

Guckelberger P
Doughty BR
Munson G
Rao SSP
Tan Y
Cai XS
Fulco CP
Nasser J
Mualim KS
Bergman DT
Ray J
Jagoda E
Munger CJ
Gschwind AR
Sheth MU
Tan AS
Pulido SG
Mitra N
Weisz D
Shamim MS
Durand NC
Mahajan R
Khan R
Steinmetz LM
Kanemaki MT
Lander ES
Meissner A
Aiden EL
Engreitz JM


Three-dimensional genome architecture persists in a 52,000-year-old woolly mammoth skin sample

Abstract: Analyses of ancient DNA typically involve sequencing the surviving short oligonucleotides and aligning to genome assemblies from related, modern species. Here, we report that skin from a female woolly mammoth (†Mammuthus primigenius) that died 52,000 years ago retained its ancient genome architecture. We use PaleoHi-C to map chromatin contacts and assemble its genome, yielding 28 chromosome-length scaffolds. Chromosome territories, compartments, loops, Barr bodies, and inactive X chromosome (Xi) superdomains persist. The active and inactive genome compartments in mammoth skin more closely resemble Asian elephant skin than other elephant tissues. Our analyses uncover new biology. Differences in compartmentalization reveal genes whose transcription was potentially altered in mammoths vs. elephants. Mammoth Xi has a tetradic architecture, not bipartite like human and mouse. We hypothesize that, shortly after this mammoth's death, the sample spontaneously freeze-dried in the Siberian cold, leading to a glass transition that preserved subfossils of ancient chromosomes at nanometer scale.

Sandoval-Velasco M
Dudchenko O
Rodríguez JA
Pérez Estrada C
Dehasque M
Fontsere C
Mak SST
Khan R
Contessoto VG
Oliveira Junior AB
Kalluchi A
Zubillaga Herrera BJ
Jeong J
Roy RP
Christopher I
Weisz D
Omer AD
Batra SS
Shamim MS
Durand NC
O'Connell B
Roca AL
Plikus MV
Kusliy MA
Romanenko SA
Lemskaya NA
Serdyukova NA
Modina SA
Perelman PL
Kizilova EA
Baiborodin SI
Rubtsov NB
Machol G
Rath K
Mahajan R
Kaur P
Gnirke A
Garcia-Treviño I
Coke R
Flanagan JP
Pletch K
Ruiz-Herrera A
Plotnikov V
Pavlov IS
Pavlova NI
Protopopov AV
Di Pierro M
Graphodatsky AS
Lander ES
Rowley MJ
Wolynes PG
Onuchic JN
Dalén L
Marti-Renom MA
Gilbert MTP
Aiden EL

Animals
Mammoths
Genome
Female
Skin
Elephants
Chromatin
Fossils
DNA, Ancient
Mice
Humans
X Chromosome


Functional dissection of complex and molecular trait variants at single nucleotide resolution

Abstract: Identifying the causal variants and mechanisms that drive complex traits and diseases remains a core problem in human genetics. The majority of these variants have individually weak effects and lie in non-coding gene-regulatory elements where we lack a complete understanding of how single nucleotide alterations modulate transcriptional processes to affect human phenotypes. To address this, we measured the activity of 221,412 trait-associated variants that had been statistically fine-mapped using a Massively Parallel Reporter Assay (MPRA) in 5 diverse cell-types. We show that MPRA is able to discriminate between likely causal variants and controls, identifying 12,025 regulatory variants with high precision. Although the effects of these variants largely agree with orthogonal measures of function, only 69% can plausibly be explained by the disruption of a known transcription factor (TF) binding motif. We dissect the mechanisms of 136 variants using saturation mutagenesis and assign impacted TFs for 91% of variants without a clear canonical mechanism. Finally, we provide evidence that epistasis is prevalent for variants in close proximity and identify multiple functional variants on the same haplotype at a small, but important, subset of trait-associated loci. Overall, our study provides a systematic functional characterization of likely causal common variants underlying complex and molecular human traits, enabling new insights into the regulatory grammar underlying disease risk.

Siraj L
Castro RI
Dewey H
Kales S
Nguyen TTL
Kanai M
Berenzy D
Mouri K
Wang QS
McCaw ZR
Gosai SJ
Aguet F
Cui R
Vockley CM
Lareau CA
Okada Y
Gusev A
Jones TR
Lander ES
Sabeti PC
Finucane HK
Reilly SK
Ulirsch JC
Tewhey R


Convergence of coronary artery disease genes onto endothelial cell programs

Abstract: Linking variants from genome-wide association studies (GWAS) to underlying mechanisms of disease remains a challenge1-3. For some diseases, a successful strategy has been to look for cases in which multiple GWAS loci contain genes that act in the same biological pathway1-6. However, our knowledge of which genes act in which pathways is incomplete, particularly for cell-type-specific pathways or understudied genes. Here we introduce a method to connect GWAS variants to functions. This method links variants to genes using epigenomics data, links genes to pathways de novo using Perturb-seq and integrates these data to identify convergence of GWAS loci onto pathways. We apply this approach to study the role of endothelial cells in genetic risk for coronary artery disease (CAD), and discover 43 CAD GWAS signals that converge on the cerebral cavernous malformation (CCM) signalling pathway. Two regulators of this pathway, CCM2 and TLNRD1, are each linked to a CAD risk variant, regulate other CAD risk genes and affect atheroprotective processes in endothelial cells. These results suggest a model whereby CAD risk is driven in part by the convergence of causal genes onto a particular transcriptional pathway in endothelial cells. They highlight shared genes between common and rare vascular diseases (CAD and CCM), and identify TLNRD1 as a new, previously uncharacterized member of the CCM signalling pathway. This approach will be widely useful for linking variants to functions for other common polygenic diseases.

Schnitzler GR
Kang H
Fang S
Angom RS
Lee-Kim VS
Ma XR
Zhou R
Zeng T
Guo K
Taylor MS
Vellarikkal SK
Barry AE
Sias-Garcia O
Bloemendal A
Munson G
Guckelberger P
Nguyen TH
Bergman DT
Hinshaw S
Cheng N
Cleary B
Aragam K
Lander ES
Finucane HK
Mukhopadhyay D
Gupta RM
Engreitz JM

Hemangioma, Cavernous, Central Nervous System

Journal Article
Research Support, N.I.H., Extramural


Genome-wide association study identifies human genetic variants associated with fatal outcome from Lassa fever

Abstract: Infection with Lassa virus (LASV) can cause Lassa fever, a haemorrhagic illness with an estimated fatality rate of 29.7%, but causes no or mild symptoms in many individuals. Here, to investigate whether human genetic variation underlies the heterogeneity of LASV infection, we carried out genome-wide association studies (GWAS) as well as seroprevalence surveys, human leukocyte antigen typing and high-throughput variant functional characterization assays. We analysed Lassa fever susceptibility and fatal outcomes in 533 cases of Lassa fever and 1,986 population controls recruited over a 7 year period in Nigeria and Sierra Leone. We detected genome-wide significant variant associations with Lassa fever fatal outcomes near GRM7 and LIF in the Nigerian cohort. We also show that a haplotype bearing signatures of positive selection and overlapping LARGE1, a required LASV entry factor, is associated with decreased risk of Lassa fever in the Nigerian cohort but not in the Sierra Leone cohort. Overall, we identified variants and genes that may impact the risk of severe Lassa fever, demonstrating how GWAS can provide insight into viral pathogenesis.

Kotliar D
Raju S
Tabrizi S
Odia I
Goba A
Momoh M
Sandi JD
Nair P
Phelan E
Tariyal R
Eromon PE
Mehta S
Robles-Sikisaka R
Siddle KJ
Stremlau M
Jalloh S
Gire SK
Winnicki S
Chak B
Schaffner SF
Pauthner M
Karlsson EK
Chapin SR
Kennedy SG
Branco LM
Kanneh L
Vitti JJ
Broodie N
Gladden-Young A
Omoniwa O
Jiang PP
Yozwiak N
Heuklom S
Moses LM
Akpede GO
Asogun DA
Rubins K
Kales S
Happi AN
Iruolagbe CO
Dic-Ijiewere M
Iraoyah K
Osazuwa OO
Okonkwo AK
Kunz S
McCormick JB
Khan SH
Honko AN
Lander ES
Oldstone MBA
Hensley L
Folarin OA
Okogbenin SA
Günther S
Ollila HM
Tewhey R
Okokhere PO
Schieffelin JS
Andersen KG
Reilly SK
Grant DS
Garry RF
Barnes KG
Happi CT
Sabeti PC

Humans
Lassa Fever
Genome-Wide Association Study
Seroepidemiologic Studies
Lassa virus
Fever
Human Genetics


Rewriting regulatory DNA to dissect and reprogram gene expression

Abstract: Regulatory DNA sequences within enhancers and promoters bind transcription factors to encode cell type-specific patterns of gene expression. However, the regulatory effects and programmability of such DNA sequences remain difficult to map or predict because we have lacked scalable methods to precisely edit regulatory DNA and quantify the effects in an endogenous genomic context. Here we present an approach to measure the quantitative effects of hundreds of designed DNA sequence variants on gene expression, by combining pooled CRISPR prime editing with RNA fluorescence in situ hybridization and cell sorting (Variant-FlowFISH). We apply this method to mutagenize and rewrite regulatory DNA sequences in an enhancer and the promoter of PPIF in two immune cell lines. Of 672 variant-cell type pairs, we identify 497 that affect PPIF expression. These variants appear to act through a variety of mechanisms including disruption or optimization of existing transcription factor binding sites, as well as creation of de novo sites. Disrupting a single endogenous transcription factor binding site often led to large changes in expression (up to -40% in the enhancer, and -50% in the promoter). The same variant often had different effects across cell types and states, demonstrating a highly tunable regulatory landscape. We use these data to benchmark performance of sequence-based predictive models of gene regulation, and find that certain types of variants are not accurately predicted by existing models. Finally, we computationally design 185 small sequence variants (≤10 bp) and optimize them for specific effects on expression in silico. 84% of these rationally designed edits showed the intended direction of effect, and some had dramatic effects on expression (-100% to +202%). Variant-FlowFISH thus provides a powerful tool to map the effects of variants and transcription factor binding sites on gene expression, test and improve computational models of gene regulation, and reprogram regulatory DNA.

Martyn GE
Montgomery MT
Jones H
Guo K
Doughty BR
Linder J
Chen Z
Cochran K
Lawrence KA
Munson G
Pampari A
Fulco CP
Kelley DR
Lander ES
Kundaje A
Engreitz JM


Extremely sparse models of linkage disequilibrium in ancestrally diverse association studies

Abstract: Linkage disequilibrium (LD) is the correlation among nearby genetic variants. In genetic association studies, LD is often modeled using large correlation matrices, but this approach is inefficient, especially in ancestrally diverse studies. In the present study, we introduce LD graphical models (LDGMs), which are an extremely sparse and efficient representation of LD. LDGMs are derived from genome-wide genealogies; statistical relationships among alleles in the LDGM correspond to genealogical relationships among haplotypes. We published LDGMs and ancestry-specific LDGM precision matrices for 18 million common variants (minor allele frequency >1%) in five ancestry groups, validated their accuracy and demonstrated order-of-magnitude improvements in runtime for commonly used LD matrix computations. We implemented an extremely fast multiancestry polygenic prediction method, BLUPx-ldgm, which performs better than a similar method based on the reference LD correlation matrix. LDGMs will enable sophisticated methods that scale to ancestrally diverse genetic association data across millions of variants and individuals.

Salehi Nowbandegani P
Wohns AW
Ballard JL
Lander ES
Bloemendal A
Neale BM
O'Connor LJ

Humans
Linkage Disequilibrium
Alleles
Gene Frequency
Genetic Association Studies
Haplotypes


Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases

Abstract: Genome-wide association studies (GWASs) are a valuable tool for understanding the biology of complex human traits and diseases, but associated variants rarely point directly to causal genes. In the present study, we introduce a new method, polygenic priority score (PoPS), that learns trait-relevant gene features, such as cell-type-specific expression, to prioritize genes at GWAS loci. Using a large evaluation set of genes with fine-mapped coding variants, we show that PoPS and the closest gene individually outperform other gene prioritization methods, but observe the best overall performance by combining PoPS with orthogonal methods. Using this combined approach, we prioritize 10,642 unique gene-trait pairs across 113 complex traits and diseases with high precision, finding not only well-established gene-trait relationships but nominating new genes at unresolved loci, such as LGR4 for estimated glomerular filtration rate and CCR7 for deep vein thrombosis. Overall, we demonstrate that PoPS provides a powerful addition to the gene prioritization toolbox.

Weeks EM
Ulirsch JC
Cheng NY
Trippe BL
Fine RS
Miao J
Patwardhan TA
Kanai M
Nasser J
Fulco CP
Tashman KC
Aguet F
Li T
Ordovas-Montanes J
Smillie CS
Biton M
Shalek AK
Ananthakrishnan AN
Xavier RJ
Regev A
Gupta RM
Lage K
Ardlie KG
Hirschhorn JN
Lander ES
Engreitz JM
Finucane HK

Humans
Multifactorial Inheritance
Quantitative Trait Loci
Genome-Wide Association Study
Genetic Predisposition to Disease
Phenotype
Polymorphism, Single Nucleotide

Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't


Massively parallel base editing to map variant effects in human hematopoiesis

Abstract: Systematic evaluation of the impact of genetic variants is critical for the study and treatment of human physiology and disease. While specific mutations can be introduced by genome engineering, we still lack scalable approaches that are applicable to the important setting of primary cells, such as blood and immune cells. Here, we describe the development of massively parallel base-editing screens in human hematopoietic stem and progenitor cells. Such approaches enable functional screens for variant effects across any hematopoietic differentiation state. Moreover, they allow for rich phenotyping through single-cell RNA sequencing readouts and separately for characterization of editing outcomes through pooled single-cell genotyping. We efficiently design improved leukemia immunotherapy approaches, comprehensively identify non-coding variants modulating fetal hemoglobin expression, define mechanisms regulating hematopoietic differentiation, and probe the pathogenicity of uncharacterized disease-associated variants. These strategies will advance effective and high-throughput variant-to-function mapping in human hematopoiesis to identify the causes of diverse diseases.

Martin-Rufino JD
Castano N
Pang M
Grody EI
Joubran S
Caulier A
Wahlster L
Li T
Qiu X
Riera-Escandell AM
Newby GA
Al'Khafaji A
Chaudhary S
Black S
Weng C
Munson G
Liu DR
Wlodarski MW
Sims K
Oakley JH
Fasano RM
Xavier RJ
Lander ES
Klein DE
Sankaran VG

Humans
Cell Differentiation
CRISPR-Cas Systems
Gene Editing
Genome
Hematopoiesis
Hematopoietic Stem Cells
Genetic Engineering
Single-Cell Analysis


Gene Sequencing Identifies Perturbation in Nitric Oxide Signaling as a Nonlipid Molecular Subtype of Coronary Artery Disease

Abstract: A key goal of precision medicine is to disaggregate common, complex diseases into discrete molecular subtypes. Rare coding variants in the low-density lipoprotein receptor gene (LDLR) are identified in 1% to 2% of coronary artery disease (CAD) patients, defining a molecular subtype with risk driven by hypercholesterolemia. To search for additional subtypes, we compared the frequency of rare, predicted loss-of-function and damaging missense variants aggregated within a given gene in 41 081 CAD cases versus 217 115 controls. Rare variants in LDLR were most strongly associated with CAD, present in 1% of cases and associated with 4.4-fold increased CAD risk. A second subtype was characterized by variants in endothelial nitric oxide synthase gene (NOS3), a key enzyme regulating vascular tone, endothelial function, and platelet aggregation. A rare predicted loss-of-function or damaging missense variants in NOS3 was present in 0.6% of cases and associated with 2.42-fold increased risk of CAD (95% CI, 1.80-3.26; P=5.50×10-9). These variants were associated with higher systolic blood pressure (+3.25 mm Hg; [95% CI, 1.86-4.65]; P=5.00×10-6) and increased risk of hypertension (adjusted odds ratio 1.31; [95% CI, 1.14-1.51]; P=2.00×10-4) but not circulating cholesterol concentrations, suggesting that, beyond lipid pathways, nitric oxide synthesis is a key nonlipid driver of CAD risk. Beyond LDLR, we identified an additional nonlipid molecular subtype of CAD characterized by rare variants in the NOS3 gene.

Circulation. Genomic and precision medicine

Khera AV
Wang M
Chaffin M
Emdin CA
Samani NJ
Schunkert H
Watkins H
McPherson R
Erdmann J
Elosua R
Boerwinkle E
Ardissino D
Butterworth AS
Di Angelantonio E
Naheed A
Danesh J
Chowdhury R
Krumholz HM
Sheu WH
Rich SS
Rotter JI
Chen YI
Gabriel S
Lander ES
Saleheen D
Kathiresan S

Humans
Coronary Artery Disease
Polymorphism, Genetic
Nitric Oxide
Cholesterol
Hypercholesterolemia


A patient-driven clinicogenomic partnership for metastatic prostate cancer

Abstract: Molecular profiling studies have enabled discoveries for metastatic prostate cancer (MPC) but have predominantly occurred in academic medical institutions and involved non-representative patient populations. We established the Metastatic Prostate Cancer Project (MPCproject, mpcproject.org), a patient-partnered initiative to involve patients with MPC living anywhere in the US and Canada in molecular research. Here, we present results from our partnership with the first 706 MPCproject participants. While 41% of patient partners live in rural, physician-shortage, or medically underserved areas, the MPCproject has not yet achieved racial diversity, a disparity that demands new initiatives detailed herein. Among molecular data from 333 patient partners (572 samples), exome sequencing of 63 tumor and 19 cell-free DNA (cfDNA) samples recapitulated known findings in MPC, while inexpensive ultra-low-coverage sequencing of 318 cfDNA samples revealed clinically relevant AR amplifications. This study illustrates the power of a growing, longitudinal partnership with patients to generate a more representative understanding of MPC.

Crowdis J
Balch S
Sterlin L
Thomas BS
Camp SY
Dunphy M
Anastasio E
Shah S
Damon AL
Ramos R
Sosa DM
Small IK
Tomson BN
Nguyen CM
McGillicuddy M
Chastain PS
He MX
Cheung ATM
Wankowicz S
Tewari AK
Kim D
AlDubayan SH
Dowdye A
Zola B
Nowak J
Manarite J
Gunn IH
Olson B
Lander ES
Painter CA
Wagle N
Van Allen EM


Neurocognitive trajectory and proteomic signature of inherited risk for Alzheimer's disease

Abstract: For Alzheimer's disease-a leading cause of dementia and global morbidity-improved identification of presymptomatic high-risk individuals and identification of new circulating biomarkers are key public health needs. Here, we tested the hypothesis that a polygenic predictor of risk for Alzheimer's disease would identify a subset of the population with increased risk of clinically diagnosed dementia, subclinical neurocognitive dysfunction, and a differing circulating proteomic profile. Using summary association statistics from a recent genome-wide association study, we first developed a polygenic predictor of Alzheimer's disease comprised of 7.1 million common DNA variants. We noted a 7.3-fold (95% CI 4.8 to 11.0; p < 0.001) gradient in risk across deciles of the score among 288,289 middle-aged participants of the UK Biobank study. In cross-sectional analyses stratified by age, minimal differences in risk of Alzheimer's disease and performance on a digit recall test were present according to polygenic score decile at age 50 years, but significant gradients emerged by age 65. Similarly, among 30,541 participants of the Mass General Brigham Biobank, we again noted no significant differences in Alzheimer's disease diagnosis at younger ages across deciles of the score, but for those over 65 years we noted an odds ratio of 2.0 (95% CI 1.3 to 3.2; p = 0.002) in the top versus bottom decile of the polygenic score. To understand the proteomic signature of inherited risk, we performed aptamer-based profiling in 636 blood donors (mean age 43 years) with very high or low polygenic scores. In addition to the well-known apolipoprotein E biomarker, this analysis identified 27 additional proteins, several of which have known roles related to disease pathogenesis. Differences in protein concentrations were consistent even among the youngest subset of blood donors (mean age 33 years). Of these 28 proteins, 7 of the 8 proteins with concentrations available were similarly associated with the polygenic score in participants of the Multi-Ethnic Study of Atherosclerosis. These data highlight the potential for a DNA-based score to identify high-risk individuals during the prolonged presymptomatic phase of Alzheimer's disease and to enable biomarker discovery based on profiling of young individuals in the extremes of the score distribution.

Paranjpe MD
Chaffin M
Zahid S
Ritchie S
Rotter JI
Rich SS
Gerszten R
Guo X
Heckbert S
Tracy R
Danesh J
Lander ES
Inouye M
Kathiresan S
Butterworth AS
Khera AV

Adult
Aged
Alzheimer Disease
Biomarkers
Cross-Sectional Studies
Genome-Wide Association Study
Humans
Middle Aged
Proteomics


Inferring gene regulation from stochastic transcriptional variation across single cells at steady state

Abstract: Regulatory relationships between transcription factors (TFs) and their target genes lie at the heart of cellular identity and function; however, uncovering these relationships is often labor-intensive and requires perturbations. Here, we propose a principled framework to systematically infer gene regulation for all TFs simultaneously in cells at steady state by leveraging the intrinsic variation in the transcriptional abundance across single cells. Through modeling and simulations, we characterize how transcriptional bursts of a TF gene are propagated to its target genes, including the expected ranges of time delay and magnitude of maximum covariation. We distinguish these temporal trends from the time-invariant covariation arising from cell states, and we delineate the experimental and technical requirements for leveraging these small but meaningful cofluctuations in the presence of measurement noise. While current technology does not yet allow adequate power for definitively detecting regulatory relationships for all TFs simultaneously in cells at steady state, we investigate a small-scale dataset to inform future experimental design. This study supports the potential value of mapping regulatory connections through stochastic variation, and it motivates further technological development to achieve its full potential.

Proceedings of the National Academy of Sciences of the United States of America

Gupta A
Martin-Rufino JD
Jones TR
Subramanian V
Qiu X
Grody EI
Bloemendal A
Weng C
Niu SY
Min KH
Mehta A
Zhang K
Siraj L
Al' Khafaji A
Sankaran VG
Raychaudhuri S
Cleary B
Grossman S
Lander ES

Computer Simulation
Gene Expression Regulation
Gene Regulatory Networks
Models, Biological
Transcription Factors

Journal Article
Research Support, Non-U.S. Gov't


Compatibility rules of human enhancer and promoter sequences

Abstract: Gene regulation in the human genome is controlled by distal enhancers that activate specific nearby promoters1. A proposed model for this specificity is that promoters have sequence-encoded preferences for certain enhancers, for example, mediated by interacting sets of transcription factors or cofactors2. This 'biochemical compatibility' model has been supported by observations at individual human promoters and by genome-wide measurements in Drosophila3-9. However, the degree to which human enhancers and promoters are intrinsically compatible has not yet been systematically measured, and how their activities combine to control RNA expression remains unclear. Here we design a high-throughput reporter assay called enhancer × promoter self-transcribing active regulatory region sequencing (ExP STARR-seq) and applied it to examine the combinatorial compatibilities of 1,000 enhancer and 1,000 promoter sequences in human K562 cells. We identify simple rules for enhancer-promoter compatibility, whereby most enhancers activate all promoters by similar amounts, and intrinsic enhancer and promoter activities multiplicatively combine to determine RNA output (R2 = 0.82). In addition, two classes of enhancers and promoters show subtle preferential effects. Promoters of housekeeping genes contain built-in activating motifs for factors such as GABPA and YY1, which decrease the responsiveness of promoters to distal enhancers. Promoters of variably expressed genes lack these motifs and show stronger responsiveness to enhancers. Together, this systematic assessment of enhancer-promoter compatibility suggests a multiplicative model tuned by enhancer and promoter class to control gene transcription in the human genome.

Bergman DT
Jones TR
Liu V
Ray J
Jagoda E
Siraj L
Kang HY
Nasser J
Kane M
Rios A
Nguyen TH
Grossman SR
Fulco CP
Lander ES
Engreitz JM

Enhancer Elements, Genetic
Humans
Promoter Regions, Genetic
RNA
Transcription Factors


Mapping transcriptomic vector fields of single cells

Abstract: Single-cell (sc)RNA-seq, together with RNA velocity and metabolic labeling, reveals cellular states and transitions at unprecedented resolution. Fully exploiting these data, however, requires kinetic models capable of unveiling governing regulatory functions. Here, we introduce an analytical framework dynamo (https://github.com/aristoteleo/dynamo-release), which infers absolute RNA velocity, reconstructs continuous vector fields that predict cell fates, employs differential geometry to extract underlying regulations, and ultimately predicts optimal reprogramming paths and perturbation outcomes. We highlight dynamo's power to overcome fundamental limitations of conventional splicing-based RNA velocity analyses to enable accurate velocity estimations on a metabolically labeled human hematopoiesis scRNA-seq dataset. Furthermore, differential geometry analyses reveal mechanisms driving early megakaryocyte appearance and elucidate asymmetrical regulation within the PU.1-GATA1 circuit. Leveraging the least-action-path method, dynamo accurately predicts drivers of numerous hematopoietic transitions. Finally, in silico perturbations predict cell-fate diversions induced by gene perturbations. Dynamo, thus, represents an important step in advancing quantitative and predictive theories of cell-state transitions.

Qiu X
Zhang Y
Martin-Rufino JD
Weng C
Hosseinzadeh S
Yang D
Pogson AN
Hein MY
Hoi Joseph Min K
Wang L
Grody EI
Shurtleff MJ
Yuan R
Xu S
Ma Y
Replogle JM
Lander ES
Darmanis S
Bahar I
Sankaran VG
Xing J
Weissman JS

Algorithms
Female
Gene Expression Regulation
HL-60 Cells
Hematopoiesis
Hematopoietic Stem Cells
Humans
Kinetics
Models, Biological
RNA, Messenger
Single-Cell Analysis
Staining and Labeling
Transcriptome

Research Support, U.S. Gov't, Non-P.H.S.


Cross-Sectional Assessment of SARS-CoV-2 Viral Load by Symptom Status in Massachusetts Congregate Living Facilities

Abstract: Transmission of coronavirus disease 2019 (COVID-19) from people without symptoms confounds societal mitigation strategies. From April to June 2020, we tested nasopharyngeal swabs by reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) from 15 514 staff and 16 966 residents of nursing homes and assisted living facilities in Massachusetts. Cycle threshold (Ct) distributions were very similar between populations with (n = 739) and without (n = 2179) symptoms at the time of sampling (mean Ct, 25.7 vs 26.4; ranges 12-38). However, as local cases waned, those without symptoms shifted towards higher Ct. With such similar viral load distributions, existing testing modalities should perform comparably regardless of symptoms, contingent upon time since infection.

Lennon NJ
Bhattacharyya RP
Mina MJ
Rehm HL
Hung DT
Smole S
Woolley A
Lander ES
Gabriel SB

Reverse Transcriptase Polymerase Chain Reaction


ARPA-H: Accelerating biomedical breakthroughs

Collins FS
Schwetz TA
Tabak LA
Lander ES


Compressed sensing for highly efficient imaging transcriptomics

Abstract: Recent methods for spatial imaging of tissue samples can identify up to ~100 individual proteins1-3 or RNAs4-10 at single-cell resolution. However, the number of proteins or genes that can be studied in these approaches is limited by long imaging times. Here we introduce Composite In Situ Imaging (CISI), a method that leverages structure in gene expression across both cells and tissues to limit the number of imaging cycles needed to obtain spatially resolved gene expression maps. CISI defines gene modules that can be detected using composite measurements from imaging probes for subsets of genes. The data are then decompressed to recover expression values for individual genes. CISI further reduces imaging time by not relying on spot-level resolution, enabling lower magnification acquisition, and is overall about 500-fold more efficient than current methods. Applying CISI to 12 mouse brain sections, we accurately recovered the spatial abundance of 37 individual genes from 11 composite measurements covering 180 mm2 and 476,276 cells.

Cleary B
Simonton B
Bezney J
Murray E
Alam S
Sinha A
Habibi E
Marshall J
Lander ES
Chen F
Regev A

Animals
Brain
Brain Chemistry
Gene Expression Profiling
Mice
Mice, Inbred C57BL
Molecular Imaging
Signal Processing, Computer-Assisted
Transcriptome


Genome-wide enhancer maps link risk variants to disease genes

Abstract: Genome-wide association studies (GWAS) have identified thousands of noncoding loci that are associated with human diseases and complex traits, each of which could reveal insights into the mechanisms of disease1. Many of the underlying causal variants may affect enhancers2,3, but we lack accurate maps of enhancers and their target genes to interpret such variants. We recently developed the activity-by-contact (ABC) model to predict which enhancers regulate which genes and validated the model using CRISPR perturbations in several cell types4. Here we apply this ABC model to create enhancer-gene maps in 131 human cell types and tissues, and use these maps to interpret the functions of GWAS variants. Across 72 diseases and complex traits, ABC links 5,036 GWAS signals to 2,249 unique genes, including a class of 577 genes that appear to influence multiple phenotypes through variants in enhancers that act in different cell types. In inflammatory bowel disease (IBD), causal variants are enriched in predicted enhancers by more than 20-fold in particular cell types such as dendritic cells, and ABC achieves higher precision than other regulatory methods at connecting noncoding variants to target genes. These variant-to-function maps reveal an enhancer that contains an IBD risk variant and that regulates the expression of PPIF to alter the membrane potential of mitochondria in macrophages. Our study reveals principles of genome regulation, identifies genes that affect IBD and provides a resource and generalizable strategy to connect risk variants of common diseases to their molecular and cellular functions.

Nasser J
Bergman DT
Fulco CP
Guckelberger P
Doughty BR
Patwardhan TA
Jones TR
Nguyen TH
Ulirsch JC
Lekschas F
Mualim K
Natri HM
Weeks EM
Munson G
Kane M
Kang HY
Cui A
Ray JP
Eisenhaure TM
Collins RL
Dey K
Pfister H
Price AL
Epstein CB
Kundaje A
Xavier RJ
Daly MJ
Huang H
Finucane HK
Hacohen N
Lander ES
Engreitz JM

Cell Line
Chromosomes, Human, Pair 10
Cyclophilins
Dendritic Cells
Enhancer Elements, Genetic
Female
Genetic Predisposition to Disease
Genetic Variation
Genome, Human
Genome-Wide Association Study
Humans
Inflammatory Bowel Diseases
Macrophages
Male
Mitochondria
Organ Specificity
Phenotype
Peptidyl-Prolyl Isomerase D


Author Correction: Inherited causes of clonal haematopoiesis in 97,691 whole genomes

NHLBI Trans-Omics for Precision Medicine Consortium


A regulatory variant at 3q21.1 confers an increased pleiotropic risk for hyperglycemia and altered bone mineral density

Abstract: Skeletal and glycemic traits have shared etiology, but the underlying genetic factors remain largely unknown. To identify genetic loci that may have pleiotropic effects, we studied Genome-wide association studies (GWASs) for bone mineral density and glycemic traits and identified a bivariate risk locus at 3q21. Using sequence and epigenetic modeling, we prioritized an adenylate cyclase 5 (ADCY5) intronic causal variant, rs56371916. This SNP changes the binding affinity of SREBP1 and leads to differential ADCY5 gene expression, altering the chromatin landscape from poised to repressed. These alterations result in bone- and type 2 diabetes-relevant cell-autonomous changes in lipid metabolism in osteoblasts and adipocytes. We validated our findings by directly manipulating the regulator SREBP1, the target gene ADCY5, and the variant rs56371916, which together imply a novel link between fatty acid oxidation and osteoblast differentiation. Our work, by systematic functional dissection of pleiotropic GWAS loci, represents a framework to uncover biological mechanisms affecting pleiotropic traits.

Sinnott-Armstrong N
Sousa IS
Laber S
Rendina-Ruedy E
Nitter Dankel SE
Ferreira T
Mellgren G
Karasik D
Rivas M
Pritchard J
Guntur AR
Cox RD
Lindgren CM
Hauner H
Sallari R
Rosen CJ
Hsu YH
Lander ES
Kiel DP
Claussnitzer M

Sterol Regulatory Element Binding Protein 1


Human Molecular Genetics and Genomics - Important Advances and Exciting Possibilities

Collins FS
Doudna JA
Lander ES
Rotimi CN

Clustered Regularly Interspaced Short Palindromic Repeats

National Academies of Science, Engineering, and Medicine, U.S., Health and Medicine Division


Delivery Mode Affects Stability of Early Infant Gut Microbiota

Abstract: Mode of delivery strongly influences the early infant gut microbiome. Children born by cesarean section (C-section) lack Bacteroides species until 6-18 months of age. One hypothesis is that these differences stem from lack of exposure to the maternal vaginal microbiome. Here, we re-evaluate this hypothesis by comparing the microbial profiles of 75 infants born vaginally or by planned versus emergent C-section. Multiple children born by C-section have a high abundance of Bacteroides in their first few days of life, but at 2 weeks, both C-section groups lack Bacteroides (primarily according to 16S sequencing), despite their difference in exposure to the birth canal. Finally, a comparison of microbial strain profiles between infants and maternal vaginal or rectal samples finds evidence for mother-to-child transmission of rectal rather than vaginal strains. These results suggest differences in colonization stability as an important factor in infant gut microbiome composition rather than birth canal exposure.

Mitchell CM
Mazzoni C
Hogstrom L
Bryant A
Bergerat A
Cher A
Pochan S
Herman P
Carrigan M
Sharp K
Huttenhower C
Lander ES
Vlamakis H
Xavier RJ
Yassour M

Infectious Disease Transmission, Vertical


HyPR-seq: Single-cell quantification of chosen RNAs via hybridization and sequencing of DNA probes

Abstract: Single-cell quantification of RNAs is important for understanding cellular heterogeneity and gene regulation, yet current approaches suffer from low sensitivity for individual transcripts, limiting their utility for many applications. Here we present Hybridization of Probes to RNA for sequencing (HyPR-seq), a method to sensitively quantify the expression of hundreds of chosen genes in single cells. HyPR-seq involves hybridizing DNA probes to RNA, distributing cells into nanoliter droplets, amplifying the probes with PCR, and sequencing the amplicons to quantify the expression of chosen genes. HyPR-seq achieves high sensitivity for individual transcripts, detects nonpolyadenylated and low-abundance transcripts, and can profile more than 100,000 single cells. We demonstrate how HyPR-seq can profile the effects of CRISPR perturbations in pooled screens, detect time-resolved changes in gene expression via measurements of gene introns, and detect rare transcripts and quantify cell-type frequencies in tissue using low-abundance marker genes. By directing sequencing power to genes of interest and sensitively quantifying individual transcripts, HyPR-seq reduces costs by up to 100-fold compared to whole-transcriptome single-cell RNA-sequencing, making HyPR-seq a powerful method for targeted RNA profiling in single cells.

Marshall JL
Doughty BR
Subramanian V
Guckelberger P
Wang Q
Chen LM
Rodriques SG
Zhang K
Fulco CP
Nasser J
Grinkevich EJ
Noel T
Mangiameli S
Bergman DT
Greka A
Lander ES
Chen F
Engreitz JM

Animals
CRISPR-Cas Systems
DNA Probes
Gene Expression
High-Throughput Nucleotide Sequencing
Humans
Introns
K562 Cells
Kidney
Mice
Nucleic Acid Hybridization
Polyadenylation
RNA
RNA, Messenger
Single-Cell Analysis
THP-1 Cells
Time Factors


The SARS-CoV-2 RNA-protein interactome in infected human cells

Abstract: Characterizing the interactions that SARS-CoV-2 viral RNAs make with host cell proteins during infection can improve our understanding of viral RNA functions and the host innate immune response. Using RNA antisense purification and mass spectrometry, we identified up to 104 human proteins that directly and specifically bind to SARS-CoV-2 RNAs in infected human cells. We integrated the SARS-CoV-2 RNA interactome with changes in proteome abundance induced by viral infection and linked interactome proteins to cellular pathways relevant to SARS-CoV-2 infections. We demonstrated by genetic perturbation that cellular nucleic acid-binding protein (CNBP) and La-related protein 1 (LARP1), two of the most strongly enriched viral RNA binders, restrict SARS-CoV-2 replication in infected cells and provide a global map of their direct RNA contact sites. Pharmacological inhibition of three other RNA interactome members, PPIA, ATP1A1, and the ARP2/3 complex, reduced viral replication in two human cell lines. The identification of host dependency factors and defence strategies as presented in this work will improve the design of targeted therapeutics against SARS-CoV-2.

Schmidt N
Lareau CA
Keshishian H
Ganskih S
Schneider C
Hennig T
Melanson R
Werner S
Wei Y
Zimmer M
Ade J
Kirschner L
Zielinski S
Dölken L
Lander ES
Caliskan N
Fischer U
Vogel J
Carr SA
Bodem J
Munschauer M

Autoantigens
COVID-19
Cell Line
Host-Pathogen Interactions
Humans
Protein Interaction Maps
Proteome
RNA, Viral
RNA-Binding Proteins
Ribonucleoproteins
SARS-CoV-2
Virus Replication
SS-B Antigen


Inherited causes of clonal haematopoiesis in 97,691 whole genomes

Abstract: Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown1. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer2-4 and coronary heart disease5-this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP)6. Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.

Intracellular Signaling Peptides and Proteins

National Heart, Lung, and Blood Institute (U.S.)


Polygenic background modifies penetrance of monogenic variants for tier 1 genomic conditions

Abstract: Genetic variation can predispose to disease both through (i) monogenic risk variants that disrupt a physiologic pathway with large effect on disease and (ii) polygenic risk that involves many variants of small effect in different pathways. Few studies have explored the interplay between monogenic and polygenic risk. Here, we study 80,928 individuals to examine whether polygenic background can modify penetrance of disease in tier 1 genomic conditions - familial hypercholesterolemia, hereditary breast and ovarian cancer, and Lynch syndrome. Among carriers of a monogenic risk variant, we estimate substantial gradients in disease risk based on polygenic background - the probability of disease by age 75 years ranged from 17% to 78% for coronary artery disease, 13% to 76% for breast cancer, and 11% to 80% for colon cancer. We propose that accounting for polygenic background is likely to increase accuracy of risk estimation for individuals who inherit a monogenic risk variant.

Fahed AC
Wang M
Homburger JR
Patel AP
Bick AG
Neben CL
Lai C
Brockman D
Philippakis A
Ellinor PT
Cassa CA
Lebo M
Ng K
Lander ES
Zhou AY
Kathiresan S
Khera AV

Aged
Breast Neoplasms
Case-Control Studies
Colorectal Neoplasms
Coronary Artery Disease
Female
Genetic Predisposition to Disease
Genome, Human
Humans
Male
Middle Aged
Multifactorial Inheritance
Odds Ratio
Penetrance
Risk Factors


Mapping and characterization of structural variation in 17,795 human genomes

Abstract: A key goal of whole-genome sequencing for studies of human genetics is to interrogate all forms of variation, including single-nucleotide variants, small insertion or deletion (indel) variants and structural variants. However, tools and resources for the study of structural variants have lagged behind those for smaller variants. Here we used a scalable pipeline1 to map and characterize structural variants in 17,795 deeply sequenced human genomes. We publicly release site-frequency data to create the largest, to our knowledge, whole-genome-sequencing-based structural variant resource so far. On average, individuals carry 2.9 rare structural variants that alter coding regions; these variants affect the dosage or structure of 4.2 genes and account for 4.0-11.2% of rare high-impact coding alleles. Using a computational model, we estimate that structural variants account for 17.2% of rare alleles genome-wide, with predicted deleterious effects that are equivalent to loss-of-function coding alleles; approximately 90% of such structural variants are noncoding deletions (mean 19.1 per genome). We report 158,991 ultra-rare structural variants and show that 2% of individuals carry ultra-rare megabase-scale structural variants, nearly half of which are balanced or complex rearrangements. Finally, we infer the dosage sensitivity of genes and noncoding elements, and reveal trends that relate to element class and conservation. This work will help to guide the analysis and interpretation of structural variants in the era of whole-genome sequencing.

NHGRI Centers for Common Disease Genomics

Alleles
Case-Control Studies
Epigenesis, Genetic
Female
Gene Dosage
Genetic Variation
Genetics, Population
Genome, Human
High-Throughput Nucleotide Sequencing
Humans
Male
Molecular Sequence Annotation
Quantitative Trait Loci
Racial Groups
Software
Whole Genome Sequencing


Towards a treatment for genetic prion disease: trials and biomarkers

Abstract: Prion disease is a rare, fatal, and exceptionally rapid neurodegenerative disease. Although incurable, prion disease follows a clear pathogenic mechanism, in which a single gene gives rise to a single prion protein (PrP) capable of converting into the sole causal disease agent, the misfolded prion. As efforts progress to leverage this mechanistic knowledge toward rational therapies, a principal challenge will be the design of clinical trials. Previous trials in prion disease have been done in symptomatic patients who are often profoundly debilitated at enrolment. About 15% of prion disease cases are genetic, creating an opportunity for early therapeutic intervention to delay or prevent disease. Highly variable age of onset and absence of established prodromal biomarkers might render infeasible existing models for testing drugs before disease onset. Advancement of near-term targeted therapeutics could crucially depend on thoughtful design of rigorous presymptomatic trials.

Vallabh SM
Minikel EV
Schreiber SL
Lander ES

Animals
Biomarkers
Humans
Neurodegenerative Diseases
Prion Diseases
Prion Proteins
Prions


Prioritizing disease and trait causal variants at the TNFAIP3 locus using functional and genomic features

Abstract: Genome-wide association studies have associated thousands of genetic variants with complex traits and diseases, but pinpointing the causal variant(s) among those in tight linkage disequilibrium with each associated variant remains a major challenge. Here, we use seven experimental assays to characterize all common variants at the multiple disease-associated TNFAIP3 locus in five disease-relevant immune cell lines, based on a set of features related to regulatory potential. Trait/disease-associated variants are enriched among SNPs prioritized based on either: (1) residing within CRISPRi-sensitive regulatory regions, or (2) localizing in a chromatin accessible region while displaying allele-specific reporter activity. Of the 15 trait/disease-associated haplotypes at TNFAIP3, 9 have at least one variant meeting one or both of these criteria, 5 of which are further supported by genetic fine-mapping. Our work provides a comprehensive strategy to characterize genetic variation at important disease-associated loci, and aids in the effort to identify trait causal genetic variants.

Ray JP
de Boer CG
Fulco CP
Lareau CA
Kanai M
Ulirsch JC
Tewhey R
Ludwig LS
Reilly SK
Bergman DT
Engreitz JM
Issner R
Finucane HK
Lander ES
Regev A
Hacohen N

Tumor Necrosis Factor alpha-Induced Protein 3


The Angiosarcoma Project: enabling genomic and clinical discoveries in a rare cancer through patient-partnered research

Abstract: Despite rare cancers accounting for 25% of adult tumors1, they are difficult to study due to the low disease incidence and geographically dispersed patient populations, which has resulted in significant unmet clinical needs for patients with rare cancers. We assessed whether a patient-partnered research approach using online engagement can overcome these challenges, focusing on angiosarcoma, a sarcoma with an annual incidence of 300 cases in the United States. Here we describe the development of the Angiosarcoma Project (ASCproject), an initiative enabling US and Canadian patients to remotely share their clinical information and biospecimens for research. The project generates and publicly releases clinically annotated genomic data on tumor and germline specimens on an ongoing basis. Over 18 months, 338 patients registered for the ASCproject, which comprises a large proportion of all patients with angiosarcoma. Whole-exome sequencing (WES) of 47 tumors revealed recurrently mutated genes that included KDR, TP53, and PIK3CA. PIK3CA-activating mutations were observed predominantly in primary breast angiosarcoma, which suggested a therapeutic rationale. Angiosarcoma of the head, neck, face and scalp (HNFS) was associated with a high tumor mutation burden (TMB) and a dominant ultraviolet damage mutational signature, which suggested that for the subset of patients with angiosarcoma of HNFS, ultraviolet damage may be a causative factor and that immune checkpoint inhibition may be beneficial. Medical record review revealed that two patients with HNFS angiosarcoma had received off-label therapeutic use of antibody to the programmed death-1 protein (anti-PD-1) and had experienced exceptional responses, which highlights immune checkpoint inhibition as a therapeutic avenue for HNFS angiosarcoma. This patient-partnered approach has catalyzed an opportunity to discover the etiology and potential therapies for patients with angiosarcoma. Collectively, this proof-of-concept study demonstrates that empowering patients to directly participate in research can overcome barriers in rare diseases and can enable discoveries.

Painter CA
Jain E
Tomson BN
Dunphy M
Stoddard RE
Thomas BS
Damon AL
Shah S
Kim D
Gómez Tejeda Zañudo J
Hornick JL
Chen YL
Merriam P
Raut CP
Demetri GD
Van Tine BA
Lander ES
Golub TR
Wagle N

Vascular Endothelial Growth Factor Receptor-2


Identification of cancer driver genes based on nucleotide context

Abstract: Cancer genomes contain large numbers of somatic mutations but few of these mutations drive tumor development. Current approaches either identify driver genes on the basis of mutational recurrence or approximate the functional consequences of nonsynonymous mutations by using bioinformatic scores. Passenger mutations are enriched in characteristic nucleotide contexts, whereas driver mutations occur in functional positions, which are not necessarily surrounded by a particular nucleotide context. We observed that mutations in contexts that deviate from the characteristic contexts around passenger mutations provide a signal in favor of driver genes. We therefore developed a method that combines this feature with the signals traditionally used for driver-gene identification. We applied our method to whole-exome sequencing data from 11,873 tumor-normal pairs and identified 460 driver genes that clustered into 21 cancer-related pathways. Our study provides a resource of driver genes across 28 tumor types with additional driver genes identified according to mutations in unusual nucleotide contexts.

Dietlein F
Weghorn D
Taylor-Weiner A
Richters A
Reardon B
Liu D
Lander ES
Van Allen EM
Sunyaev SR

Cluster Analysis
Computational Biology
Humans
Mutation
Neoplasms
Nucleotides
Proteins
Exome Sequencing


Control of human hemoglobin switching by LIN28B-mediated regulation of BCL11A translation

Abstract: Increased production of fetal hemoglobin (HbF) can ameliorate the severity of sickle cell disease and β-thalassemia1. BCL11A represses the genes encoding HbF and regulates human hemoglobin switching through variation in its expression during development2-7. However, the mechanisms underlying the developmental expression of BCL11A remain mysterious. Here we show that BCL11A is regulated at the level of messenger RNA (mRNA) translation during human hematopoietic development. Despite decreased BCL11A protein synthesis earlier in development, BCL11A mRNA continues to be associated with ribosomes. Through unbiased genomic and proteomic analyses, we demonstrate that the RNA-binding protein LIN28B, which is developmentally expressed in a pattern reciprocal to that of BCL11A, directly interacts with ribosomes and BCL11A mRNA. Furthermore, we show that BCL11A mRNA translation is suppressed by LIN28B through direct interactions, independently of its role in regulating let-7 microRNAs, and that BCL11A is the major target of LIN28B-mediated HbF induction. Our results reveal a previously unappreciated mechanism underlying human hemoglobin switching that illuminates new therapeutic opportunities.

Basak A
Munschauer M
Lareau CA
Montbleau KE
Ulirsch JC
Hartigan CR
Schenone M
Lian J
Wang Y
Huang Y
Wu X
Gehrke L
Rice CM
An X
Christou HA
Mohandas N
Carr SA
Chen JJ
Orkin SH
Lander ES
Sankaran VG

Adult
Animals
Binding Sites
Cells, Cultured
Erythroid Cells
Erythropoiesis
Gene Expression Regulation
Hemoglobins
Humans
Infant, Newborn
MicroRNAs
Protein Biosynthesis
RNA, Messenger
RNA, Ribosomal, 18S
RNA-Binding Proteins
Repressor Proteins
Ribosomes


Activity-by-contact model of enhancer-promoter regulation from thousands of CRISPR perturbations

Abstract: Enhancer elements in the human genome control how genes are expressed in specific cell types and harbor thousands of genetic variants that influence risk for common diseases1-4. Yet, we still do not know how enhancers regulate specific genes, and we lack general rules to predict enhancer-gene connections across cell types5,6. We developed an experimental approach, CRISPRi-FlowFISH, to perturb enhancers in the genome, and we applied it to test >3,500 potential enhancer-gene connections for 30 genes. We found that a simple activity-by-contact model substantially outperformed previous methods at predicting the complex connections in our CRISPR dataset. This activity-by-contact model allows us to construct genome-wide maps of enhancer-gene connections in a given cell type, on the basis of chromatin state measurements. Together, CRISPRi-FlowFISH and the activity-by-contact model provide a systematic approach to map and predict which enhancers regulate which genes, and will help to interpret the functions of the thousands of disease risk variants in the noncoding genome.

Fulco CP
Nasser J
Jones TR
Munson G
Bergman DT
Subramanian V
Grossman SR
Anyoha R
Doughty BR
Patwardhan TA
Nguyen TH
Kane M
Perez EM
Durand NC
Lareau CA
Stamenova EK
Aiden EL
Lander ES
Engreitz JM


Rare Genetic Variants Associated With Sudden Cardiac Death in Adults

Abstract: Sudden cardiac death occurs in ∼220,000 U.S. adults annually, the majority of whom have no prior symptoms or cardiovascular diagnosis. Rare pathogenic DNA variants in any of 49 genes can pre-dispose to 4 important causes of sudden cardiac death: cardiomyopathy, coronary artery disease, inherited arrhythmia syndrome, and aortopathy or aortic dissection. This study assessed the prevalence of rare pathogenic variants in sudden cardiac death cases versus controls, and the prevalence and clinical importance of such mutations in an asymptomatic adult population. The authors performed whole-exome sequencing in a case-control cohort of 600 adult-onset sudden cardiac death cases and 600 matched controls from 106,098 participants of 6 prospective cohort studies. Observed DNA sequence variants in any of 49 genes with known association to cardiovascular disease were classified as pathogenic or likely pathogenic by a clinical laboratory geneticist blinded to case status. In an independent population of 4,525 asymptomatic adult participants of a prospective cohort study, the authors performed whole-genome sequencing and determined the prevalence of pathogenic or likely pathogenic variants and prospective association with cardiovascular death. Among the 1,200 sudden cardiac death cases and controls, the authors identified 5,178 genetic variants and classified 14 as pathogenic or likely pathogenic. These 14 variants were present in 15 individuals, all of whom had experienced sudden cardiac death-corresponding to a pathogenic variant prevalence of 2.5% in cases and 0% in controls (p < 0.0001). Among the 4,525 participants of the prospective cohort study, 41 (0.9%) carried a pathogenic or likely pathogenic variant and these individuals had 3.24-fold higher risk of cardiovascular death over a median follow-up of 14.3 years (p = 0.02). Gene sequencing identifies a pathogenic or likely pathogenic variant in a small but potentially important subset of adults experiencing sudden cardiac death; these variants are present in ∼1% of asymptomatic adults.

Journal of the American College of Cardiology

Khera AV
Mason-Suares H
Brockman D
Wang M
VanDenburgh MJ
Senol-Cosar O
Patterson C
Newton-Cheh C
Zekavat SM
Pester J
Chasman DI
Kabrhel C
Jensen MK
Manson JE
Gaziano JM
Taylor KD
Sotoodehnia N
Post WS
Rich SS
Rotter JI
Lander ES
Rehm HL
Ng K
Philippakis A
Lebo M
Albert CM
Kathiresan S

Aged
Aged, 80 and over
Case-Control Studies
Death, Sudden, Cardiac
Female
Genetic Predisposition to Disease
Humans
Male
Middle Aged
Exome Sequencing


Correction: Whole exome sequencing study identifies novel rare and common Alzheimer's-Associated variants involved in immune response and transcriptional regulation

Abstract: A correction to this paper has been published and can be accessed via a link at the top of the paper.

Bis JC
Jian X
Kunkle BW
Chen Y
Hamilton-Nelson KL
Bush WS
Salerno WJ
Lancour D
Ma Y
Renton AE
Marcora E
Farrell JJ
Zhao Y
Qu L
Ahmad S
Amin N
Amouyel P
Beecham GW
Below JE
Campion D
Cantwell L
Charbonnier C
Chung J
Crane PK
Cruchaga C
Cupples LA
Dartigues JF
Debette S
Deleuze JF
Fulton L
Gabriel SB
Genin E
Gibbs RA
Goate A
Grenier-Boley B
Gupta N
Haines JL
Havulinna AS
Helisalmi S
Hiltunen M
Howrigan DP
Ikram MA
Kaprio J
Konrad J
Kuzma A
Lander ES
Lathrop M
Lehtimäki T
Lin H
Mattila K
Mayeux R
Muzny DM
Nasser W
Neale B
Nho K
Nicolas G
Patel D
Pericak-Vance MA
Perola M
Psaty BM
Quenez O
Rajabli F
Redon R
Reitz C
Remes AM
Salomaa V
Sarnowski C
Schmidt H
Schmidt M
Schmidt R
Soininen H
Thornton TA
Tosto G
Tzourio C
van der Lee SJ
van Duijn CM
Valladares O
Vardarajan B
Wang LS
Wang W
Wijsman E
Wilson RK
Witten D
Worley KC
Zhang X
Alzheimer’s Disease Sequencing Project
Bellenguez C
Lambert JC
Kurki MI
Palotie A
Daly M
Boerwinkle E
Lunetta KL
Destefano AL
Dupuis J
Martin ER
Schellenberg GD
Seshadri S
Naj AC
Fornage M
Farrer LA


Gain-of-Function Claims for Type-2-Diabetes-Associated Coding Variants in SLC16A11 Are Not Supported by the Experimental Data

Abstract: Human genetic variants in SLC16A11 are associated with increased risk of type 2 diabetes (T2D). We previously identified two distinct mechanisms through which co-inherited T2D-risk coding and non-coding variants disrupt SLC16A11 expression and activity, thus implicating reduced SLC16A11 function as the disease-relevant direction of effect. In a recent publication, Zhao et al. (2019a) argue that human SLC16A11 coding variants confer gain of function, basing their conclusions on phenotypic changes observed following overexpression of mutant murine Slc16a11. However, data necessary to demonstrate gain-of-function activity are not reported. Furthermore, several fundamental flaws in their experimental system-including inaccurate modeling of the human variant haplotype and expression conditions that are not physiologically relevant-prevent conclusions about T2D-risk variant effects on human physiology. This Matters Arising paper is in response to Zhao et al. (2019a), published in Cell Reports. See also the response by Zhao et al. (2019b) in this issue of Cell Reports.

Animals
Diabetes Mellitus, Type 2
Gain of Function Mutation
Haplotypes
Humans
Mice
Monocarboxylic Acid Transporters


Small Molecule Targets TMED9 and Promotes Lysosomal Degradation to Reverse Proteinopathy

Abstract: Intracellular accumulation of misfolded proteins causes toxic proteinopathies, diseases without targeted therapies. Mucin 1 kidney disease (MKD) results from a frameshift mutation in the MUC1 gene (MUC1-fs). Here, we show that MKD is a toxic proteinopathy. Intracellular MUC1-fs accumulation activated the ATF6 unfolded protein response (UPR) branch. We identified BRD4780, a small molecule that clears MUC1-fs from patient cells, from kidneys of knockin mice and from patient kidney organoids. MUC1-fs is trapped in TMED9 cargo receptor-containing vesicles of the early secretory pathway. BRD4780 binds TMED9, releases MUC1-fs, and re-routes it for lysosomal degradation, an effect phenocopied by TMED9 deletion. Our findings reveal BRD4780 as a promising lead for the treatment of MKD and other toxic proteinopathies. Generally, we elucidate a novel mechanism for the entrapment of misfolded proteins by cargo receptors and a strategy for their release and anterograde trafficking to the lysosome.

Dvela-Levitt M
Kost-Alimova M
Emani M
Kohnert E
Thompson R
Sidhom EH
Rivadeneira A
Sahakian N
Roignot J
Papagregoriou G
Montesinos MS
Clark AR
McKinney D
Gutierrez J
Roth M
Ronco L
Elonga E
Carter TA
Gnirke A
Melanson M
Hartland K
Wieder N
Hsu JC
Deltas C
Hughey R
Bleyer AJ
Kmoch S
Živná M
Barešova V
Kota S
Schlondorff J
Heiman M
Alper SL
Wagner F
Weins A
Golub TR
Lander ES
Greka A

Activating Transcription Factor 6
Animals
Benzamides
Bridged Bicyclo Compounds
Epithelial Cells
Female
Frameshift Mutation
Heptanes
Humans
Imidazoline Receptors
Induced Pluripotent Stem Cells
Kidney
Kidney Diseases
Lysosomes
Male
Mice
Mice, Transgenic
Mucin-1
RNA Interference
RNA, Small Interfering
Unfolded Protein Response
Vesicular Transport Proteins


Large-scale chemical-genetics yields new M. tuberculosis inhibitor classes

Abstract: New antibiotics are needed to combat rising levels of resistance, with new Mycobacterium tuberculosis (Mtb) drugs having the highest priority. However, conventional whole-cell and biochemical antibiotic screens have failed. Here we develop a strategy termed PROSPECT (primary screening of strains to prioritize expanded chemistry and targets), in which we screen compounds against pools of strains depleted of essential bacterial targets. We engineered strains that target 474 essential Mtb genes and screened pools of 100-150 strains against activity-enriched and unbiased compound libraries, probing more than 8.5 million chemical-genetic interactions. Primary screens identified over tenfold more hits than screening wild-type Mtb alone, with chemical-genetic interactions providing immediate, direct target insights. We identified over 40 compounds that target DNA gyrase, the cell wall, tryptophan, folate biosynthesis and RNA polymerase, as well as inhibitors that target EfpA. Chemical optimization yielded EfpA inhibitors with potent wild-type activity, thus demonstrating the ability of PROSPECT to yield inhibitors against targets that would have eluded conventional drug discovery.

Johnson EO
LaVerriere E
Office E
Stanley M
Meyer E
Kawate T
Gomez JE
Audette RE
Bandyopadhyay N
Betancourt N
Delano K
Da Silva I
Davis J
Gallo C
Gardner M
Golas AJ
Guinn KM
Kennedy S
Korn R
McConnell JA
Moss CE
Murphy KC
Nietupski RM
Papavinasasundaram KG
Pinkham JT
Pino PA
Proulx MK
Ruecker N
Song N
Thompson M
Trujillo C
Wakabayashi S
Wallach JB
Watson C
Ioerger TR
Lander ES
Hubbard BK
Serrano-Wu MH
Ehrt S
Fitzgerald M
Rubin EJ
Sassetti CM
Schnappinger D
Hung DT

Antitubercular Agents
DNA Gyrase
Drug Discovery
Drug Resistance, Microbial
Folic Acid
Gene Deletion
Microbial Sensitivity Tests
Molecular Targeted Therapy
Mycobacterium tuberculosis
Mycolic Acids
Reproducibility of Results
Small Molecule Libraries
Substrate Specificity
Topoisomerase II Inhibitors
Tryptophan
Tuberculosis


Defining the core essential genome of Pseudomonas aeruginosa

Abstract: Genomics offered the promise of transforming antibiotic discovery by revealing many new essential genes as good targets, but the results fell short of the promise. While numerous factors contributed to the disappointing yield, one factor was that essential genes for a bacterial species were often defined based on a single or limited number of strains grown under a single or limited number of in vitro laboratory conditions. In fact, the essentiality of a gene can depend on both the genetic background and growth condition. We thus developed a strategy for more rigorously defining the core essential genome of a bacterial species by studying many pathogen strains and growth conditions. We assessed how many strains must be examined to converge on a set of core essential genes for a species. We used transposon insertion sequencing (Tn-Seq) to define essential genes in nine strains of Pseudomonas aeruginosa on five different media and developed a statistical model, FiTnEss, to classify genes as essential versus nonessential across all strain-medium combinations. We defined a set of 321 core essential genes, representing 6.6% of the genome. We determined that analysis of four strains was typically sufficient in P. aeruginosa to converge on a set of core essential genes likely to be essential across the species across a wide range of conditions relevant to in vivo infection, and thus to represent attractive targets for novel drug discovery.

Poulsen BE
Yang R
Clatworthy AE
White T
Osmulski SJ
Li L
Penaranda C
Lander ES
Shoresh N
Hung DT

DNA Transposable Elements
Genes, Essential
Genome, Bacterial
Models, Statistical
Pseudomonas aeruginosa


Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood

Abstract: Severe obesity is a rapidly growing global health threat. Although often attributed to unhealthy lifestyle choices or environmental factors, obesity is known to be heritable and highly polygenic; the majority of inherited susceptibility is related to the cumulative effect of many common DNA variants. Here we derive and validate a new polygenic predictor comprised of 2.1 million common variants to quantify this susceptibility and test this predictor in more than 300,000 individuals ranging from middle age to birth. Among middle-aged adults, we observe a 13-kg gradient in weight and a 25-fold gradient in risk of severe obesity across polygenic score deciles. In a longitudinal birth cohort, we note minimal differences in birthweight across score deciles, but a significant gradient emerged in early childhood and reached 12 kg by 18 years of age. This new approach to quantify inherited susceptibility to obesity affords new opportunities for clinical prevention and mechanistic assessment.

Khera AV
Chaffin M
Wade KH
Zahid S
Brancale J
Xia R
Distefano M
Senol-Cosar O
Haas ME
Bick A
Aragam KG
Lander ES
Smith GD
Mason-Suares H
Fornage M
Lebo M
Timpson NJ
Kaplan LM
Kathiresan S

Adolescent
Body Mass Index
Body Weight
Child
Databases, Factual
Female
Genome-Wide Association Study
Humans
Infant, Newborn
Longitudinal Studies
Male
Middle Aged
Multifactorial Inheritance
Obesity
Risk Factors
Severity of Illness Index

Journal Article
Research Support, N.I.H., Extramural
Research Support, N.I.H., Intramural
Research Support, Non-U.S. Gov't


Multi-tissue analyses of allele-specific chromatin accessibility nominate likely functional variants for type 2 diabetes

Abstract: Genome-wide association studies (GWAS) have identified >1,200 signals associated with type 2 diabetes (T2D), yet identifying functional variants remains challenging because the majority of them lie in noncoding regions of the genome and are in areas of high linkage disequilibrium (LD). While chromatin accessibility QTL (caQTL) and expression QTL (eQTL) analyses are useful for nominating regulatory mechanisms underlying GWAS signals, limitations still exist in pinpointing functional variants within regions of high LD. A complementary approach that has been less frequently applied is to focus on the allele-specific effect on chromatin accessibility at heterozygous single-nucleotide polymorphisms (SNPs), hereafter referred to as "allelic imbalance". We analyzed the allelic imbalance of reads generated from an assay for transposase-accessible chromatin with sequencing (ATAC-seq) across genotyped samples from 490 donors in T2D-relevant tissues: skeletal muscle, liver, pancreatic islets, adipose tissue, and relevant cell types. We identified 119,949 allelically imbalanced SNPs (FDR<0.05) across the genome. The allelic imbalance was often most prominent in one tissue and showed an enrichment overlapping with tissue-specific transcription factor (TF) binding footprints. Focusing on the 8,581 SNPs in previously published 99% credible sets from 338 T2D GWAS signals, we identified 256 imbalanced SNPs across 123 (36.4% of) signals, each showing allelic imbalance in at least one tissue or cell type. Of these, 71 signals contained only a single imbalanced SNP, representing excellent candidate causative variants. As a proof-of-concept, we showed that 23 of the 256 imbalanced SNPs were supported by allelic assays from previous studies. Further, we experimentally validated two imbalanced SNPs as likely functional variants: rs34584161 among a seven-SNP T2D credible set at the RNF6 signal in islets and rs849134 among a 13-SNP credible set at the JAZF1 signal in liver. This study demonstrates the power of integrating ATAC-seq allelic imbalance (ASAI) with GWAS statistical fine-mapping to identify candidate functional regulatory variants from among tightly linked GWAS variants in disease-relevant tissues. While applied here in T2D, this approach represents a widely applicable high-throughput framework for refining the genetic architecture of complex traits.

medRxiv : the preprint server for health sciences

Narisu N
Li HX
Rathbun CJM
Varshney A
Swift AJ
Yan T
Sinha N
Currin KW
Xue D
Robertson CC
Taylor DL
Taylor HJ
Beck A
Lee BN
Wang L
Broadaway KA
Wilson EP
Stringham H
Saramies J
Lakka TA
Spracklen CN
Scott LJ
Stitzel ML
Tuomilehto J
Laakso M
Koistinen HA
Boehnke M
Arda HE
Chen S
Biesecker LG
Bonnycastle LL
Erdos MR
Mohlke KL
Parker SCJ
Collins FS


Scalable hypothalamic neuron differentiation from human pluripotent stem cells suitable for modeling metabolic disorders

Abstract: The hypothalamus, composed of multiple nuclei, is essential for maintaining the body's homeostasis. Within the mediobasal hypothalamus, the arcuate nucleus (ARC) contains key neuronal populations, including appetite-suppressing pro-opiomelanocortin (POMC) neurons that regulate energy and glucose balance. Here, we present a chemically defined, scalable method for differentiating human pluripotent stem cells (hPSCs) into hypothalamic neurons enriched for POMC cells, compatible with robotic cell culture platforms for high-throughput use. Neuronal identity was validated by MERFISH single-cell transcriptomics, RNA-Seq, ATAC-Seq, and comparison to human hypothalamus. The method is robust across multiple hPSC lines, showing consistent induction of ventral diencephalon and hypothalamic markers. Derived neurons display metabolic disease-relevant features, including body mass index (BMI)-associated gene enrichment, and ATAC-Seq identifies potential candidate regulatory regions linked to hypothalamic development and metabolic traits. Functional assays reveal neuronal responses to insulin and the GLP-1 receptor agonist Exendin-4, and transcriptional responses to altered glucose conditions. This platform delivers a physiologically relevant model of human hypothalamic neurons that enables deeper mechanistic and therapeutic studies of metabolic disease.

Jovanovic VM
Narisu N
Bonnycastle LL
Castellano D
Ryu S
Tharakan R
Mesch KT
Chen Q
Betül Erol FM
Glover HJ
Yan T
Sinha N
Sen C
Yang S
Blivis D
Bennett DF
Rosales-Soto G
Inman J
Ormanoglu P
LeClair CA
Shaw ND
Xia M
Schneider M
Hernandez-Ochoa EO
Erdos MR
Simeonov A
Chen S
Collins FS
Doege CA
Tristan CA

Humans
Neurons
Pluripotent Stem Cells
Cell Differentiation
Hypothalamus
Metabolic Diseases
Pro-Opiomelanocortin
Models, Biological
Insulin
Glucose


Genetics of growth rate in induced pluripotent stem cells

Abstract: Induced pluripotent stem cells (iPSCs) enabled the generation of diverse cell types; however, certain fundamental biological properties, such as the genetic and epigenetic determinants of proliferation, remain poorly characterized. We quantified proliferation across 602 unique donors with a time-lapse imaging-based growth area under the curve (gAUC) phenotype and correlated gAUC with cell line gene expression and genotype. We identified 3,091 differentially expressed genes and found that rare deleterious variants in WDR54, TMEM250, and C2orf81 were associated with reduced iPSC growth. Notably, WDR54 was differentially expressed with respect to gAUC. Although no common variants were associated, common genetic variation explained 71%-75% of the variance. These results indicate a complex genetic architecture of iPSC growth rates, where rare, large-effect variants in important growth regulators are layered onto a highly polygenic background. These findings can impact the design of pooled iPSC-based studies and disease models, which may be confounded by intrinsic growth differences.

Lee BN
Taylor HJ
Cipriani F
Narisu N
Robertson CC
Swift AJ
Sinha N
Yan T
Bonnycastle LL
Dale N
Butt A
Parsaud H
Semrau S
NYSCF Global Stem Cell Array Team
GENESiPS Consortium
iPSCORE Consortium
Knowles JW
Carcamo-Orive I
D'Antonio-Chronowska A
Frazer KA
Biesecker LG
Noggle S
Erdos MR
Paull D
Collins FS
Taylor DL

Induced Pluripotent Stem Cells
Humans
Cell Proliferation
Phenotype
Polymorphism, Single Nucleotide


Donor-matched iPSC model reveals context-dependent T2D genetic signals in fibro-adipogenic progenitors

Abstract: Fibro-adipogenic progenitors (FAPs) in skeletal muscle have been implicated in type 2 diabetes (T2D) risk, yet their heterogeneity and context-dependent regulation remain poorly understood. Here, we establish induced pluripotent stem cell (iPSC)-derived FAPs as a faithful model of primary FAPs by leveraging a unique resource: iPSC lines and skeletal muscle biopsies obtained from the same 30 individuals. Donor-matched comparisons reveal that iPSC-FAPs recapitulate the transcriptome, epigenome, and subtype composition of muscle tissue FAPs. Using single-nucleus multiomics, we show that high-insulin exposure drives iPSC-FAPs toward an adipogenic fate - and that this adipogenic subtype is enriched for T2D GWAS signals, an enrichment undetectable under baseline conditions. We map the T2D-associated rs3814707 non-coding signal to LTBP3, a gene that influences FAP adipogenic differentiation. These findings reveal how disease-relevant regulatory mechanisms can be masked in unstimulated cells and establish iPSC-FAPs as a powerful platform for dissecting the state-dependent biology of complex metabolic disease.

Ventresca C
Varshney A
Orchard P
Vu HTH
Tsan YC
Monteiro da Rocha A
Erdos MR
Kinnunen L
Lakka TA
Saramies J
Laakso M
Tuomilehto J
Mohlke KL
Boehnke M
Scott LJ
Koistinen HA
Collins FS
Herron T
Bielas S
Parker SCJ


Genetic integration with cell-specific nucleosome positioning resolves causal relationships underlying chromatin accessibility profiles

Abstract: Cell type-specific chromatin accessibility QTL (caQTL) mapping is a promising approach to understand genetic control of chromatin landscapes and identify regulatory mechanisms underlying GWAS associations. However, current caQTL studies lack resolution and do not distinguish nucleosome-free regions (NFR) from positioned nucleosomes. Here, we leverage statistical modeling of fragment position and length to decompose ATAC-seq profiles into NFRs and phased nucleosomes. With single nucleus (sn)ATAC-seq from 281 human muscle biopsies, we map cell type-specific genetic effects on NFRs (76,027 nfrQTLs) and nucleosome occupancy (24,623 nucQTLs) across skeletal muscle cell types. Colocalization and causal inference between nucQTLs and nearby nfrQTLs and show that nfrQTLs are substantially more likely to causally influence nucQTLs and phase adjacent nucleosomes, indicating a causal relationship in shaping chromatin profiles. Hundreds of nfrQTLs colocalize with GWAS signals for muscle-related traits, including grip strength, atrial fibrillation, and fasting insulin, and the majority of colocalizing signals mapped to credible sets overlapping the corresponding nfrPeak. This approach adds mechanistic insights for how variants underlying caQTLs and GWAS signals exert their cis regulatory effects by initially modifying NFR accessibility and subsequently shaping broader chromatin landscapes, nucleosome positioning, gene expression, and ultimately higher-level traits and disease.

Wang X
Robertson CC
Varshney A
Manickam N
Orchard P
Laakso M
Tuomilehto J
Lakka TA
Mohlke KL
Boehnke M
Scott LJ
Koistinen HA
Collins FS
Parker SCJ


Inverse directions of association of higher physical activity and higher insulin resistance with human skeletal muscle cell type abundance and fiber-type-level gene expression

Abstract: To investigate the interplay between physical activity and cardiometabolic traits in human skeletal muscle, we characterized gene expression and chromatin accessibility across skeletal muscle cell types in 263 Finnish individuals from the FUSION Tissue Biopsy Study. We analyzed skeletal muscle single-nucleus RNA-seq data (168,309 nuclei, 23,849 genes), ATAC-seq data (242,069 nuclei, 927,588 peaks), and bulk RNA-seq data (22,309 genes). Lower insulin resistance (HOMA-IR) and higher total physical activity were both associated with higher proportions of Type 1 nuclei and lower proportions of Type 2x nuclei. We identified cell-type-level and tissue-level gene expression-trait and gene set-trait associations for cardiometabolic and physical activity traits, and a smaller proportion of cell-type-level chromatin accessibility-trait associations. Traits typically associated with better health-lower trait values of cardiometabolic traits (BMI, HOMA-IR, normal glucose tolerance vs. type 2 diabetes, 2-hour plasma glucose) and higher physical activity levels (total and vigorous)-were associated with higher expression of energy metabolism genes and lower expression of signaling pathway genes across muscle fiber types, total pseudobulk, and to some extent in bulk tissue. For HOMA-IR and physical activity, these directions of association remained when adjusting for both traits in the same model, indicating apparently independent associations in the same pathways.

Ciotlos DL
Hanks SC
Varshney A
Erdos MR
Manickam N
Stringham HM
Orchard P
Hill-Burns EM
Narisu N
Bonnycastle LL
Sweeney MD
Saramies J
Laakso M
Tuomilehto J
Lakka TA
Mohlke KL
Boehnke M
Collins FS
Koistinen HA
Parker SCJ
Scott LJ


Screening for Hepatitis C in Emergency Departments


Skeletal muscle eQTL meta-analysis implicates genes in the genetic architecture of muscular and cardiometabolic traits

Abstract: Identifying genetic variants that regulate gene expression can help uncover mechanisms underlying complex traits. We performed a meta-analysis of skeletal muscle expression quantitative trait locus (eQTL) using data from 1,002 individuals from two studies. A stepwise analysis identified 18,818 conditionally distinct signals for 12,283 genes, and 35% of these genes contained two or more signals. Colocalization of these eQTL signals with 26 muscular and cardiometabolic trait genome-wide association studies (GWASs) identified 2,252 GWAS-eQTL colocalizations that nominated 1,342 candidate genes. Notably, 22% of the GWAS-eQTL colocalizations involved non-primary eQTL signals. Additionally, 37% of the colocalized GWAS-eQTL signals corresponded to the closest protein-coding gene, while 44% were located >50 kb from the transcription start site of the nominated gene. To assess tissue specificity for a heterogeneous trait, we compared colocalizations with type 2 diabetes (T2D) signals across muscle, adipose, liver, and islet eQTLs; we identified 551 candidate genes for 309 T2D signals representing 36% of T2D signals tested and over 100 more than were detected with any one tissue alone. We then functionally validated the allelic regulatory effect of an eQTL variant for INHBB linked to T2D in both muscle and adipose tissue. Together, these results further demonstrate the value of skeletal muscle eQTLs in elucidating mechanisms underlying complex traits.

Wilson EP
Broadaway KA
Parsons VA
Vadlamudi S
Narisu N
Brotman SM
Currin KW
Stringham HM
Erdos MR
Welch R
Holtzman JK
Lakka TA
Laakso M
Tuomilehto J
Boehnke M
Koistinen HA
Collins FS
Parker SCJ
Scott LJ
Mohlke KL

Quantitative Trait Loci
Humans
Muscle, Skeletal
Genome-Wide Association Study
Diabetes Mellitus, Type 2
Polymorphism, Single Nucleotide
Genetic Predisposition to Disease

Journal Article
Meta-Analysis
Research Support, N.I.H., Intramural
Research Support, N.I.H., Extramural


A spatial transcriptomics dataset of pancreas sections in normal glucose tolerance and type 2 diabetic donors

Abstract: Understanding the spatial distribution of gene expression in the pancreas is essential for establishing the molecular basis of pancreatic function in healthy and disease contexts. Recent platforms offer a robust method for quantifying gene expression within a spatial context. Here, we report spatial transcriptomic profiling from pancreas samples obtained from three donors with type 2 diabetes (T2D) and three donors with normal glucose tolerance (NGT). Our analysis identified a major technical challenge: substantial transcript bleed of highly abundant genes (e.g., INS and GCG) into adjacent tissue regions. We demonstrate that this bleed can be computationally corrected using probabilistic models. Our analysis highlights the importance of incorporating bleed-correction techniques in the preprocessing of spatial transcriptomic profiling data. In summary, this study provides a dataset, methods, and resources to investigate the spatial regulation of gene expression in normal and T2D-affected human pancreas.

Howell N
Weiss Z
Bonnycastle LL
Grenko CM
Randazzo D
Dampier CH
Sinha N
Narisu N
Swift AJ
Erdos MR
Biesecker LG
Collins FS
Robertson CC
Taylor DL

Humans
Diabetes Mellitus, Type 2
Pancreas
Transcriptome
Gene Expression Profiling


Integrative single-cell multi-omics profiling of human pancreatic islets identifies T1D-associated genes and regulatory signals

Abstract: Genome-wide association studies (GWASs) have identified over 100 signals associated with type 1 diabetes (T1D). However, it has been challenging to translate any given T1D GWAS signal into mechanistic insights, such as causal variants, their target genes, and the specific cell types involved. Here, we present a comprehensive multi-omic integrative analysis of single-cell/nucleus resolution profiles of gene expression and chromatin accessibility in human pancreatic islets under baseline and T1D-stimulating conditions. We nominate effector cell types for all T1D GWAS signals and the regulatory elements and genes for three independent T1D signals acting through β cells at the DLK1/MEG3, RASGRP1, and TOX loci. Subsequently, we validated the functional impact of these genes and regulatory regions using isogenic human embryonic stem cells (hESCs). We found that loss of RASGRP1 or DLK1, as well as disruption of their corresponding regulatory regions, led to increased β cell apoptosis. Furthermore, β cells derived from isogenic hESCs carrying the T1D risk allele of rs3783355 associated with DLK1 showed elevated β cell death. Through additional RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin using sequencing (ATAC-seq) analyses, we identified five genes upregulated in both RASGRP1-/- and DLK1-/- β-like cells, four of which are near T1D GWAS signals. This integrative approach combining single-cell multi-omics, GWASs, and isogenic human pluripotent stem cell (hPSC)-derived β-like cells illuminates cell type context, genes, single nucleotide polymorphisms (SNPs), and regulatory elements underlying T1D-associated signals, providing insights into the biological functions and molecular mechanisms involved.

D'Oliveira Albanus R
Zhang X
Zhao Z
Taylor HJ
Tang X
Han Y
Orchard P
Varshney A
Zhang T
Manickam N
Erdos MR
Narisu N
Taylor L
Saavedra X
Liu X
Zhong A
Li B
Zhou T
Naji A
Liu C
Collins FS
Parker SCJ
Chen S

Humans
Diabetes Mellitus, Type 1
Single-Cell Analysis
Genome-Wide Association Study
Islets of Langerhans
Insulin-Secreting Cells
Polymorphism, Single Nucleotide
Human Embryonic Stem Cells
Apoptosis
Multiomics
Calcium-Binding Proteins
Membrane Proteins


Polygenic prediction of body mass index and obesity through the life course and across ancestries

Abstract: Polygenic scores (PGSs) for body mass index (BMI) may guide early prevention and targeted treatment of obesity. Using genetic data from up to 5.1 million people (4.6% African ancestry, 14.4% American ancestry, 8.4% East Asian ancestry, 71.1% European ancestry and 1.5% South Asian ancestry) from the GIANT consortium and 23andMe, Inc., we developed ancestry-specific and multi-ancestry PGSs. The multi-ancestry score explained 17.6% of BMI variation among UK Biobank participants of European ancestry. For other populations, this ranged from 16% in East Asian-Americans to 2.2% in rural Ugandans. In the ALSPAC study, children with higher PGSs showed accelerated BMI gain from age 2.5 years to adolescence, with earlier adiposity rebound. Adding the PGS to predictors available at birth nearly doubled explained variance for BMI from age 5 onward (for example, from 11% to 21% at age 8). Up to age 5, adding the PGS to early-life BMI improved prediction of BMI at age 18 (for example, from 22% to 35% at age 5). Higher PGSs were associated with greater adult weight gain. In intensive lifestyle intervention trials, individuals with higher PGSs lost modestly more weight in the first year (0.55 kg per s.d.) but were more likely to regain it. Overall, these data show that PGSs have the potential to improve obesity prediction, particularly when implemented early in life.

DiscovEHR (DiscovEHR and MyCode Community Health Initiative)

eMERGE (Electronic Medical Records and Genomics Network)

Adolescent
Adult
Child
Child, Preschool
Female
Humans
Male
Middle Aged
Young Adult
Adiposity
Body Mass Index
Genetic Predisposition to Disease
Multifactorial Inheritance
Obesity
White People
Racial Groups


Systematic phenotype and genotype characterization of Moebius syndrome

Abstract: To explore the phenotypic spectrum and genetic etiologies of Moebius Syndrome (MBS), a rare neurological disorder defined by congenital, nonprogressive facial weakness and limitations in ocular abduction. We applied strict diagnostic criteria and conducted clinical phenotyping of 149 individuals with MBS. Subsequently, we performed exome and/or genome sequencing on 67 of these individuals and 117 unaffected family members. All 149 individuals had sporadic MBS, with no recurrence within or across generations. Common co-occurring phenotypes included tongue hypoplasia (81.9%), micrognathia (66.4%), congenital talipes equinovarus (42.3%), major limb anomalies (31.5%), intellectual disability (30.9%), sleep difficulties (22.8%), and Poland anomaly (14.1%). Filtering for rare de novo or autosomal recessive single-nucleotide, insertion/deletion, and structural variants in the sequenced cohort yielded 173 single-nucleotide variant/indels in 113 genes. Although we prioritized 7 candidate genes with de novo variants and 5 with biallelic variants, no compelling recurrently mutated genes were identified. Similarly, we found no convincing variants in 2 putative genes previously implicated in MBS: PLXND1 (HGNC:9107) and REV3L (HGNC:9968). We did not identify a strong or unifying germline genetic etiology for MBS. Future studies may explore alternative causes, including environmental exposures, somatic variants, and/or complex inheritance patterns affecting brainstem and organ embryogenesis.

Webb BD
Jurgens JA
Narisu N
Zhang Z
Barry BJ
Van Ryzin C
Bonnycastle LL
Chan WM
Yan T
Di Gioia SA
Swift AJ
MacKinnon SE
Oystreck DT
Rucker JC
Frempong T
Whitman MC
FitzGibbon EJ
Lee JS
Hao K
Andrews C
Erazo M
Facio FM
Shaaban S
Naidich TP
Chines PS
Lehky TJ
Toro C
Gropman AL
Butman JA
Zalewski CK
Brewer CC
Thurm A
Snow J
Paul SM
Brooks BP
Pierpaoli C
Robson CD
Hunter DG
Collins FS
Jabs EW
Engle EC
Manoli I


Abstract: Human induced pluripotent stem cells (iPSCs) have transformed biomedical research by enabling the generation of diverse cell types from accessible somatic tissues. However, certain fundamental biological properties, such as the genetic and epigenetic determinants of iPSC proliferation, remain poorly characterized. We measured the growth of iPSC lines derived from 602 unique donors using high-throughput time-lapse imaging, quantified proliferation through a growth Area-Under-the-Curve (gAUC) phenotype, and correlated gAUC with the gene expression and genotype of the cell lines. We identified 3,091 genes associated with gAUC, many of which are well established regulators of cell proliferation. We also found that rare deleterious variants in WDR54 were associated with reduced iPSC growth and that WDR54 was differentially expressed with respect to gAUC. Although no common variants showed a genome-wide association with gAUC, iPSC lines from monozygotic twins were highly correlated, and common genetic variation explained approximately 71-75% of the variance in iPSC growth rates. These results indicate a complex genetic architecture of iPSC growth rates, where rare, large-effect variants in important growth regulators, including WDR54, are layered onto a highly polygenic background. These findings have important implications for the design of pooled iPSC-based studies and disease models, which may be confounded by intrinsic growth differences.


Multimodality Craniofacial Phenotyping of Congenital Facial Weakness Disorders

Abstract: ObjectiveCongenital facial weakness (CFW) disorders are a heterogeneous group of rare conditions, that present at birth, with reduced facial movement, and mask-like facies. This study utilized a multimodality approach to examine the craniofacial and intraoral phenotypes among CFW disorders: Moebius syndrome (MBS), Hereditary Congenital Facial Palsy (HCFP), β-tubulin isotype 3 syndrome (CFEOM3A-TUBB3), Carey-Fineman-Ziter syndrome (CFZS), and a group of rarer disorders (Other).DesignProspective cohort study.Setting: Dental clinic.Participants: Sixty individuals (sex ratio 1:1, mean age 26.2 ± 17.5 years) with a diagnosis of CFW.Interventions: Deep clinical craniofacial and dental phenotyping, three-dimensional facial surface and cone-beam computed tomography scans, and cephalometric and geometric morphometric analyses.ResultsCFEOM3A-TUBB3, MBS, and CFZS groups had the highest prevalence of craniofacial anomalies; HCFP individuals were least affected. CFEOM3A-TUBB3 had a higher prevalence of short lower face (75%), poor oral hygiene (100%)/decay (75%), and Class II malocclusion (87.5%). Moebius syndrome was associated with lagophthalmos (90.9%), tongue fissures (72.4%), tight/small oral orifice (51.7%), and tongue fasciculations (50%). Carey-Fineman-Ziter syndrome had oblong facial shape (100%), downward lip commissures (100%), and abnormal hearing (60%). Moderate-severe decay/gingivitis correlated with restricted oral orifice, common among patients with facial animation/sling surgery. Morphologically, the CFW cohort had a relatively small craniofacial centroid size, anthropometric measurements, and distinct craniofacial shapes for each subtype.ConclusionsCongenital facial weakness can result in abnormal craniofacial development in addition to the loss of facial movement. Multimodality phenotypic characterization of CFW disorders elucidated key clinical findings and distinct craniofacial shape segregation among the different groups.

The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association

Almpani K
Devine KR
Liberton DK
Mishra R
Bassim C
Van Ryzin C
Facio FM
Webb BD
Barry BJ
Engle EC
Wang Jabs E
Collins FS
Manoli I
Lee JS
Moebius Syndrome Research Consortium

Humans
Phenotype
Male
Female
Facial Paralysis
Adult
Craniofacial Abnormalities
Cephalometry
Cone-Beam Computed Tomography
Imaging, Three-Dimensional
Cohort Studies
Child
Adolescent
Mobius Syndrome


Detecting Protein-DNA binding in single molecules using antibody guided methylation

Abstract: Characterization of DNA binding sites for specific proteins is of fundamental importance in molecular biology. It is commonly addressed experimentally by chromatin immunoprecipitation and sequencing (ChIP-seq) of bulk samples (103-107 cells). We have developed an alternative method that uses a Chromatin Antibody-mediated Methylating Protein (ChAMP) composed of a GpC methyltransferase fused to protein G. By tethering ChAMP to a primary antibody directed against the DNA-binding protein of interest, and selectively switching on its enzymatic activity in situ, we generated distinct and identifiable methylation patterns adjacent to the protein binding sites. This method is compatible with methods of single-cell methylation-detection and single molecule methylation identification. Indeed, as every binding event generates multiple nearby methylations, we were able to confidently detect protein binding in long single molecules.

Thatavarty A
Sagy N
Erdos MR
Lee I
Simpson JT
Timp W
Collins FS
Bar DZ

DNA Methylation
Humans
Protein Binding
DNA-Binding Proteins
DNA
Antibodies
Binding Sites


Direct RNA nanopore sequencing reveals rapid RNA modification changes following glucose stimulation of human pancreatic beta-cell lines

Abstract: RNA modifications are critical regulators of gene expression and cellular processes; however, the epitranscriptome is less well studied than the epigenome. Here, we studied transcriptome-wide changes in RNA modifications and expression levels in two human pancreatic beta-cell lines, EndoC-BH1 and EndoC-BH3, after one hour of glucose stimulation. Using direct RNA nanopore sequencing (dRNA-seq), we measured N6-methyladenosine (m6A), 5-methylcytosine (m5C), inosine, and pseudouridine concurrently across the transcriptome. We developed a differential RNA modification method and identified 1,697 differentially modified sites (DMSs) across all modifications. These DMSs were largely independent of changes in gene expression levels and enriched in transcripts for type 2 diabetes (T2D) genes. Our study demonstrates how dRNA-seq can be used to detect and quantify RNA modification changes in response to cellular stimuli at the single-nucleotide level and provides new insights into RNA-mediated mechanisms that may contribute to normal beta-cell response and potential dysfunction in T2D.

Mulroney L
Taylor HJ
Lee A
Swift AJ
Zdravkov M
Bonnycastle LL
Brooks SY
Lee BN
Fitzgerald T
Narisu N
Biesecker LG
Erdos MR
Nicassio F
Birney E
Collins FS
Taylor DL


ChemPerturb-seq screen identifies a small molecule cocktail enhancing human beta cell survival after subcutaneous transplantation

Abstract: Traditional chemical screens have focused on a single assay per screen, making them labor intensive and costly. Here, we combined a chemical screen with single-cell RNA sequencing (scRNA-seq) to perform Chemical Perturb-seq (ChemPerturb-seq), enabling a systematic analysis of the molecular changes of human beta cells upon individual small molecule treatments. Using this platform, we performed an in vivo barcoded screen and discovered a small molecule cocktail, including beta-lipotropin 61-91, insulin growth factor-1, and prostaglandin E2, with which preconditioning human beta cells and primary islets significantly enhanced function and survival when transplanted subcutaneously to female, but not to male, mice. We identified two additional molecules, serotonin and histamine, that promote islet function when transplanted subcutaneously to male mice using ChemPerturb-seq. Such small molecule cocktails could be applied to improve the current FDA-approved islet transplantation procedure. Finally, we developed an artificial intelligence (AI)-powered website, ChemPerturbDB, which provides user-friendly open access analysis of the extensive ChemPerturb-seq dataset.

Vandana JJ
Zhu J
Giani AM
Zhang T
Lacko LA
Leng D
Taylor DL
Lee BN
Han Z
Jiao T
Huang Y
Zhao M
Liu X
Chong ACN
Xue D
Meng Z
Xiang JZ
Pan C
Wang W
Naji A
Evans T
Liu J
Collins FS
Liu C
Chen S

Humans
Animals
Insulin-Secreting Cells
Mice
Female
Male
Islets of Langerhans Transplantation
Cell Survival
Small Molecule Libraries
Single-Cell Analysis
Sequence Analysis, RNA