Characterizing transcriptome variation in human populations at single-cell resolution

Phenotypic diversity in human populations is a direct consequence of genetic variation, which acts in conjunction with environmental and behavioral factors to produce phenotypic variation, from eye color and height to disease susceptibility and responses to drugs (1). High population-specific variability in disease’s prevalence have been described, including multiple examples where a disease is strongly overrepresented in a single population, for instance sickle cell anemia in Africans, hemochromatosis in Northern-Europeans or familial Gaucher’s disease in Ashkenazi Jews (2). In addition, population differences in response to drugs have been documented, for instance, 5-Fluorouracil (cancer chemotherapeutic), Warfarin (anticoagulant for preventing thrombosis and embolism) or nicotine (3). In this context, there has been a growing interest in profiling the molecular causes underlying infectious disease-related phenotypic differences across individuals from populations of different genetic backgrounds. Studies using RNA-seq data from primary monocytes, as a model of an innate immunity, have shown that human populations differ in their transcriptional responses to immune challenges, which are largely controlled by genetics and have been shaped by natural selection (4). In addition, a similar work focusing on alternative splicing characterisation upon immune activation highlights the contribution of positive selection to diversify the splicing landscape of human populations (5). Moreover, additional works using single-cell RNA-seq indicate that most of the ancestry effects on the immune response are cell type specific, exceptuating interferon (IFN) response which is strongly correlated with European ancestry after infection with influenza A virus (Figure 1) (6). Also in line with previous evidence, it has been seen that eQTLs explains > 50% of population differences in response to infection, stressing the key role played by genetics in shaping population differences in immune responses (6). This evidence suggests that genetic ancestry is a main driver of inter-individual differences in response to infection. In turn, these findings highlight the importance of studying the effect of human population genetic variation over disease and disease response for developing effective treatments, and in order to lay the foundations for the establishment of personalized medicine. Moreover, the characterisation of the transcriptome differences derived from human genetic variation can provide further insights into the evolution of human populations

Transcriptome analysis of differential gene expression in disease

Many diseases strongly impact the human transcriptome at the gene expression level [1]. However, previous work has focused on accessible tissues [2], and has not incorporated the effect of demographic traits, known risk factors for complex diseases [3]. Here, we leveraged the GTEx dataset to investigate the gene expression changes associated with different diseases. By studying the transcriptomes from an organismal perspective -across tissues and individuals- we can gain deeper insights into disease biology and help preventing complex diseases

Systematic characterization of regulatory variants of blood pressure genes

High blood pressure (BP) is the major risk factor for cardiovascular disease. Genome-wide association studies have identified genetic variants for BP, but functional insights into causality and related molecular mechanisms lag behind. We functionally characterize 4,608 genetic variants in linkage with 135 BP loci in vascular smooth muscle cells and cardiomyocytes by massively parallel reporter assays. High densities of regulatory variants at BP loci (i.e., ULK4, MAP4, CFDP1, PDE5A) indicate that multiple variants drive genetic association. Regulatory variants are enriched in repeats, alter cardiovascular-related transcription factor motifs, and spatially converge with genes controlling specific cardiovascular pathways. Using heuristic scoring, we define likely causal variants, and CRISPR prime editing finally determines causal variants for KCNK9, SFXN2, and PCGF6, which are candidates for developing high BP. Our systems-level approach provides a catalog of functionally relevant variants and their genomic architecture in two trait-relevant cell lines for a better understanding of BP gene regulation.We thank the Melé and Maass labs for intellectual input, Dr. Steven Erwood from Dr. Ronald Cohn’s lab for guidance in applying CRISPR prime editing, The Centre for Applied Genomics, The Structural & Biophysical Core Facility, and The Imaging Facility, The Hospital for Sick Children, Toronto, Canada, for assistance with high-throughput sequencing, luminescence detection, and imaging. We thank Dovetail Genomics, LLC, 100 Enterprise Way, Suite A101, Scotts Valley, CA 95066, USA, for generating Omni-C libraries and for the collaborative support throughout the project. W.O. was supported by a Fundació la Marató grant (ref. 321/C/2019), K.K. was supported by an OGS fellowship, J.W.L.B. was supported by a CGS-D fellowship, and D.F.L. was supported by an Ontario Genomics-CANSSI Ontario Postdoctoral Fellowship in Genome Data Science. This project was supported by Canada’s New Frontiers in Research Fund (NFRFE-2018-01305), the Canadian Institutes of Health Research (CIHR PJT 173542 [P.G.M.] and PJT 175034 [S.M., J.E.]), CIHR ENP 161429 under the frame of ERA PerMed (S.M.), the Ted Rogers Centre for Heart Research (S.M., J.E.), and the Heart and Stroke Foundation of Canada. J.E. holds a Canada Research Chair Tier 1 in Stem Cell Models of Childhood Disease, S.M. holds the Heart and Stroke Foundation of Canada & Robert M. Freedom Chair in Cardiovascular Science, M. Melé was supported by a Ramon y Cajal fellowship (RYC-2017-22249), and P.G.M. holds a Canada Research Chair Tier 2 in Non-coding Disease Mechanisms.Peer Reviewed"Article signat per 14 autors/es: Winona Oliveros, Kate Delfosse, Daniella F. Lato , Katerina Kiriakopulos, Milad Mokhtaridoost, Abdelrahman Said, Brandon J. McMurray, Jared W.L. Browning, Kaia Mattioli, Guoliang Meng, James Ellis, Seema Mital, Marta Melé, Philipp G. Maass"Postprint (published version

Whole genome sequencing delineates regulatory, copy number, and cryptic splice variants in early onset cardiomyopathy

Cardiomyopathy (CMP) is a heritable disorder. Over 50% of cases are gene-elusive on clinical gene panel testing. The contribution of variants in non-coding DNA elements that result in cryptic splicing and regulate gene expression has not been explored. We analyzed whole-genome sequencing (WGS) data in a discovery cohort of 209 pediatric CMP patients and 1953 independent replication genomes and exomes. We searched for protein-coding variants, and non-coding variants predicted to affect the function or expression of genes. Thirty-nine percent of cases harbored pathogenic coding variants in known CMP genes, and 5% harbored high-risk loss-of-function (LoF) variants in additional candidate CMP genes. Fifteen percent harbored high-risk regulatory variants in promoters and enhancers of CMP genes (odds ratio 2.25, p = 6.70 × 10−7 versus controls). Genes involved in α-dystroglycan glycosylation (FKTN, DTNA) and desmosomal signaling (DSC2, DSG2) were most highly enriched for regulatory variants (odds ratio 6.7–58.1). Functional effects were confirmed in patient myocardium and reporter assays in human cardiomyocytes, and in zebrafish CRISPR knockouts. We provide strong evidence for the genomic contribution of functionally active variants in new genes and in regulatory elements of known CMP genes to early onset CMP.This project was supported by the Ted Rogers Centre for Heart Research (SM, JE), the Canadian Institutes of Health Research (PJT 175034) (SM, JE) and by the Canadian Institutes of Health Research (ENP 161429), under the frame of ERA PerMed (SM). SM holds the Heart and Stroke Foundation of Canada & Robert M Freedom Chair in Cardiovascular Science. SWS holds the GlaxoSmithKline Endowed Chair in Genome Sciences at the Hospital for Sick Children and the University of Toronto. PGM holds a Canada Research Chair Tier 2 in Non-coding Disease Mechanisms. PGM acknowledges the support of the Government of Canada’s New Frontiers in Research Fund (NFRF), [NFRFE-2018-01305]. EO holds the Bitove Family Professorship of Adult Congenital Heart Disease. MM holds a Ramon y Cajal grant from the Spanish Ministry of Science and Innovation (RYC-2017-22249). WO is supported by funding from Fundació La Marató (321/C/2019). JB is funded by a Frans Van de Werf fellowship for clinical cardiovascular research, and by a senior clinical investigator fellowship of the FWO Flanders. KM was a National Science Foundation Graduate Research Fellow under grant no. DGE1144152 during the majority of the project. CS is the recipient of a National Health and Medical Research Council (NHMRC) Practitioner Fellowship (1154992). JI is the recipient of an NHMRC Career Development Fellowship (1162929). RDB is the recipient of a New South Wales Health Cardiovascular Disease Senior Scientist Grant. PSD is supported by the DBT/Wellcome Trust- Indian Alliance. We acknowledge the Labatt Family Heart Centre Biobank at the Hospital for Sick Children for access to DNA samples, and The Centre for Applied Genomics at the Hospital for Sick Children for performing WGS. We thank Xiucheng Cui and Emanuela Pannia for performing the zebrafish experiments at the SickKids Zebrafish Genetics and Disease Models Core (CRISPR-Cas9 and gRNA syntheses, zebrafish embryo microinjections, gRNA PCR validation, qRT-PCR, cardiac imaging). This research was made possible through access to the data and findings generated by the 100,000 Genomes Project. The 100,000 Genomes Project is managed by Genomics England Limited (a wholly owned company of the Department of Health and Social Care). The 100,000 Genomes Project is funded by the National Institute for Health Research and NHS England. The Wellcome Trust, Cancer Research UK and the Medical Research Council have also funded research infrastructure. The 100,000 Genomes Project uses data provided by patients and collected by the National Health Service as part of their care and support. We thank members of the ICGC/PCAWG working groups for generating the variant calls used in our case-control burden analyses.Peer Reviewed"Article signat per 38 autors/es: Robert Lesurf, Abdelrahman Said, Oyediran Akinrinade, Jeroen Breckpot, Kathleen Delfosse, Ting Liu, Roderick Yao, Gabrielle Persad, Fintan McKenna, Ramil R. Noche, Winona Oliveros, Kaia Mattioli, Shreya Shah, Anastasia Miron, Qian Yang, Guoliang Meng, Michelle Chan Seng Yue, Wilson W. L. Sung, Bhooma Thiruvahindrapuram, Jane Lougheed, Erwin Oechslin, Tapas Mondal, Lynn Bergin, John Smythe, Shashank Jayappa, Vinay J. Rao, Jayaprakash Shenthar, Perundurai S. Dhandapany, Christopher Semsarian, Robert G. Weintraub, Richard D. Bagnall, Jodie Ingles, Genomics England Research Consortium, Marta Melé, Philipp G. Maass, James Ellis, Stephen W. Scherer & Seema Mital"Postprint (published version

Human metastatic cholangiocarcinoma patient-derived xenografts and tumoroids for preclinical drug evaluation

Cholangiocarcinoma (CCA) is usually diagnosed at advanced stages, with limited therapeutic options. Preclinical models focused on unresectable metastatic CCA are necessary to develop rational treatments. Pathogenic mutations in IDH1/2, ARID1A/B, BAP1, and BRCA1/2 have been identified in 30\\%–50\\% of patients with CCA. Several types of tumor cells harboring these mutations exhibit homologous recombination deficiency (HRD) phenotype with enhanced sensitivity to PARP inhibitors (PARPi). However, PARPi treatment has not yet been tested for effectiveness in patient-derived models of advanced CCA.We have established a collection of patient-derived xenografts from patients with unresectable metastatic CCA (CCA\_PDX). The CCA\_PDXs were characterized at both histopathologic and genomic levels. We optimized a protocol to generate CCA tumoroids from CCA\_PDXs. We tested the effects of PARPis in both CCA tumoroids and CCA\_PDXs. Finally, we used the RAD51 assay to evaluate the HRD status of CCA tissues.This collection of CCA\_PDXs recapitulates the histopathologic and molecular features of their original tumors. PARPi treatments inhibited the growth of CCA tumoroids and CCA\_PDXs with pathogenic mutations of BRCA2, but not those with mutations of IDH1, ARID1A, or BAP1. In line with these findings, only CCA\_PDX and CCA patient biopsy samples with mutations of BRCA2 showed RAD51 scores compatible with HRD.Our results suggest that patients with advanced CCA with pathogenic mutations of BRCA2, but not those with mutations of IDH1, ARID1A, or BAP1, are likely to benefit from PARPi therapy. This collection of CCA\_PDXs provides new opportunities for evaluating drug response and prioritizing clinical trials.The authors would like to thank the patients and their families for their support. This work was supported by grants from the Fundaci o Marat o TV3 awarded to T. Macarulla, M. Mel e, and S. Peir o; BeiGene research grant awarded toT. Macarulla and S. Peir o; AECC (INVES20036TIAN), Ram on y Cajal investigator program (RYC2020-029098-I), Proyecto de IþDþi (PID2019-108008RJ-I00), and FERO Foundation grant awarded to T.V. Tian; Proyecto de Investigaci on en Salud from the Instituto de Salud Carlos III (ISCIII) (PI20/00898) awarded to T. Macarulla; FIS/FEDER from the Instituto de Salud Carlos III (ISCIII) (PI12/01250; CP08/00223; PI16/00253 and CB16/12/00449) awarded to S. Peir o; and Ram on y Cajal investigator program (RYC-2017-22249) awarded to M. Mel e. Q. Serra-Camprubí is a recipient of the Ph.D. fellowship from La Caixa Foundation (LCF/PR/PR12/51070001). A. LlopGuevara was supported by the AECC (INVES20095LLOP) and V. Serra by the ISCIII (CPII19/00033). E.J. Arenas was funded by the AECC (POSTD211413AREN).J. Arribas is funded by the Instituto de Salud Carlos III (AC15/00062, CB16/12/00449, and PI22/00001). This publication is based upon the work of COST Action CA18122, European Cholangiocarcinoma Network, supported by the COST (European Cooperation in Science and Technology, www.cost.eu), a funding agency for research and innovation networks. The authors would like to thank Dr. V.A. Raker for manuscript editing and Drs. N. Herranz and J. Mateo for scientific discussions. The authors acknowledge the infrastructure and support of the FERO Foundation, La Caixa Foundation, and the Cellex Foundation.Peer Reviewed"Article signat per 31 autors/es: Queralt Serra-Camprubí; Helena Verdaguer; Winona Oliveros; Núria Lupión-Garcia; Núria Lupión-Garcia;Alba Llop-Guevara; Cristina Molina; Maria Vila-Casadesús; Anthony Turpin; Cindy Neuzillet; Joan Frigola; Jessica Querol; Mariana Yáñez-Bartolomé; Florian Castet; Carles Fabregat-Franco; Carmen Escudero-Iriarte; Marta Escorihuela; Enrique J. Arenas; Cristina Bernadó-Morales; Noemí Haro; Francis J. Giles; Óscar J. Pozo; Josep M. Miquel ; Paolo G. Nuciforo; Ana Vivancos; Marta Melé; Violeta Serra ; Joaquín Arribas; Josep Tabernero; Sandra Peiró; Teresa Macarulla; Tian V. Tian"Postprint (published version

Genetic, parental and lifestyle factors influence telomere length

The average length of telomere repeats (TL) declines with age and is considered to be a marker of biological ageing. Here, we measured TL in six blood cell types from 1046 individuals using the clinically validated Flow-FISH method. We identified remarkable cell-type-specific variations in TL. Host genetics, environmental, parental and intrinsic factors such as sex, parental age, and smoking are associated to variations in TL. By analysing the genome-wide methylation patterns, we identified that the association of maternal, but not paternal, age to TL is mediated by epigenetics. Single-cell RNA-sequencing data for 62 participants revealed differential gene expression in T-cells. Genes negatively associated with TL were enriched for pathways related to translation and nonsense-mediated decay. Altogether, this study addresses cell-type-specific differences in telomere biology and its relation to cell-type-specific gene expression and highlights how perinatal factors play a role in determining TL, on top of genetics and lifestyle.We thank J. Dekens for management, A. Maatman and M. Platteel for technical support and K. Mc Intyre for English editing. This project was funded by the BBMRI grant for measuring telomere length and by a Rosalind Franklin Fellowship to A.Z. The researchers participated in this project are supported by Netherlands Heart Foundation (IN-CONTROL CVON grants 2012-03 and 2018-27); the Netherlands Organization for Scientific Research (NWO) Gravitation Netherlands Organ-on-Chip Initiative to J.F. and C.W.; NWO Gravitation Exposome-NL (024.004.017) to J.F., A.K. and A.Z.; NWO-VIDI (864.13.013) and NWO-VICI (VI.C.202.022) to J.F.; NWO-VIDI (016.178.056) to A.Z.; NWO-VIDI (917.14.374) to L.F.; NWO-VENI (194.006) to D.V.Z.; NWO-VENI (192.029) to M.W.; NWO Spinoza Prize SPI 92–266 to C.W.; the European Research Council (ERC) (FP7/2007–2013/ERC Advanced Grant 2012-322698) to C.W.; ERC Starting grant 637640 to L.F.; ERC Starting Grant 715772 to A.Z.; ERC Consolidator Grant (grant agreement No. 101001678) to J.F.; and RuG Investment Agenda Grant Personalized Health to C.W. MM work is supported by RYC- 2017-22249 and PID2019-107937GA-I00 grants. T.S. holds scholarships from the Junior Scientific Masterclass, University of Groningen[grant no. 17–34]. AR is funded by a Formación Personal Investigador (FPI) grant [grant no. PRE2019-090193]. The Lifelines Biobank initiative has been made possible by a subsidy from the Dutch Ministry of Health, Welfare and Sport; the Dutch Ministry of Economic Affairs; the University Medical Centre Groningen (UMCG, the Netherlands); the University of Groningen and the Northern Provinces of the Netherlands. The authors wish to acknowledge the services of the Lifelines Cohort Study, the contributing research centres delivering data to Lifelines and all the study participants. Finally, we would like to acknowledge the Genomics Coordination Centre (GCC) at the University Medical College Groningen for the HPC support and the MOLGENIS team for the cloud storage of the data associated with this work.Peer Reviewed"Article signat per 16 autors/es: Sergio Andreu-Sánchez, Geraldine Aubert, Aida Ripoll-Cladellas, Sandra Henkelman, Daria V. Zhernakova, Trishla Sinha, Alexander Kurilshikov, Maria Carmen Cenit, Marc Jan Bonder, Lude Franke, Cisca Wijmenga, Jingyuan Fu, Monique G. P. van der Wijst, Marta Melé, Peter Lansdorp & Alexandra Zhernakova"Postprint (published version

Cis and trans effects differentially contribute to the evolution of promoters and enhancers

Background Gene expression differences between species are driven by both cis and trans effects. Whereas cis effects are caused by genetic variants located on the same DNA molecule as the target gene, trans effects are due to genetic variants that affect diffusible elements. Previous studies have mostly assessed the impact of cis and trans effects at the gene level. However, how cis and trans effects differentially impact regulatory elements such as enhancers and promoters remains poorly understood. Here, we use massively parallel reporter assays to directly measure the transcriptional outputs of thousands of individual regulatory elements in embryonic stem cells and measure cis and trans effects between human and mouse. Results Our approach reveals that cis effects are widespread across transcribed regulatory elements, and the strongest cis effects are associated with the disruption of motifs recognized by strong transcriptional activators. Conversely, we find that trans effects are rare but stronger in enhancers than promoters and are associated with a subset of transcription factors that are differentially expressed between human and mouse. While we find that cis-trans compensation is common within promoters, we do not see evidence of widespread cis-trans compensation at enhancers. Cis-trans compensation is inversely correlated with enhancer redundancy, suggesting that such compensation may often occur across multiple enhancers. Conclusions Our results highlight differences in the mode of evolution between promoters and enhancers in complex mammalian genomes and indicate that studying the evolution of individual regulatory elements is pivotal to understand the tempo and mode of gene expression evolution.K.M. was a National Science Foundation Graduate Research Fellow under grant no. DGE1144152 during the majority of the project. M.M. was a Gilead Fellow of the Life Sciences Research Foundation during part of the project and is currently supported by the Spanish Ministry of Science and Innovation with a Ramon y Cajal grant (RYC-2017-22249). J.L.R. is an HHMI faculty scholar.Peer ReviewedPostprint (published version

Minimizing recombinations in consensus networks for phylogeographic studies

<p>Abstract</p> <p>Background</p> <p>We address the problem of studying recombinational variations in (human) populations. In this paper, our focus is on one computational aspect of the general task: Given two networks <it>G</it>₁and <it>G</it>₂, with both mutation and recombination events, defined on overlapping sets of extant units the objective is to compute a consensus network <it>G</it>₃with minimum number of additional recombinations. We describe a polynomial time algorithm with a guarantee that the number of computed new recombination events is within <it>ϵ </it>= <it>sz</it>(<it>G</it>₁, <it>G</it>₂) (function <it>sz </it>is a well-behaved function of the sizes and topologies of <it>G</it>₁and <it>G</it>₂) of the optimal <it>number </it>of recombinations. To date, this is the best known result for a network consensus problem.</p> <p>Results</p> <p>Although the network consensus problem can be applied to a variety of domains, here we focus on structure of human populations. With our preliminary analysis on a segment of the human Chromosome X data we are able to infer ancient recombinations, population-specific recombinations and more, which also support the widely accepted 'Out of Africa' model. These results have been verified independently using traditional manual procedures. To the best of our knowledge, this is the first recombinations-based characterization of human populations.</p> <p>Conclusion</p> <p>We show that our mathematical model identifies recombination spots in the individual haplotypes; the aggregate of these spots over a set of haplotypes defines a recombinational landscape that has enough signal to detect continental as well as population divide based on a short segment of Chromosome X. In particular, we are able to infer ancient recombinations, population-specific recombinations and more, which also support the widely accepted 'Out of Africa' model. The agreement with mutation-based analysis can be viewed as an indirect validation of our results and the model. Since the model in principle gives us more information embedded in the networks, in our future work, we plan to investigate more non-traditional questions via these structures computed by our methodology.</p

Functional identification of cis-regulatory long noncoding RNAs at controlled false discovery rates.

A key attribute of some long noncoding RNAs (lncRNAs) is their ability to regulate expression of neighbouring genes in cis. However, such 'cis-lncRNAs' are presently defined using ad hoc criteria that, we show, are prone to false-positive predictions. The resulting lack of cis-lncRNA catalogues hinders our understanding of their extent, characteristics and mechanisms. Here, we introduce TransCistor, a framework for defining and identifying cis-lncRNAs based on enrichment of targets amongst proximal genes. TransCistor's simple and conservative statistical models are compatible with functionally defined target gene maps generated by existing and future technologies. Using transcriptome-wide perturbation experiments for 268 human and 134 mouse lncRNAs, we provide the first large-scale survey of cis-lncRNAs. Known cis-lncRNAs are correctly identified, including XIST, LINC00240 and UMLILO, and predictions are consistent across analysis methods, perturbation types and independent experiments. We detect cis-activity in a minority of lncRNAs, primarily involving activators over repressors. Cis-lncRNAs are detected by both RNA interference and antisense oligonucleotide perturbations. Mechanistically, cis-lncRNA transcripts are observed to physically associate with their target genes and are weakly enriched with enhancer elements. In summary, TransCistor establishes a quantitative foundation for cis-lncRNAs, opening a path to elucidating their molecular mechanisms and biological significance

Antibody conversion rates to SARS-CoV-2 in saliva from children attending summer schools in Barcelona, Spain.

Background: Surveillance tools to estimate viral transmission dynamics in young populations are essential to guide recommendations for school opening and management during viral epidemics. Ideally, sensitive techniques are required to detect low viral load exposures among asymptomatic children. We aimed to estimate SARS-CoV-2 infection rates in children and adult populations in a school-like environment during the initial COVID-19 pandemic waves using an antibody-based field-deployable and non-invasive approach. Methods: Saliva antibody conversion defined as ≥ 4-fold increase in IgM, IgA, and/or IgG levels to five SARS-CoV-2 antigens including spike and nucleocapsid constructs was evaluated in 1509 children and 396 adults by high-throughput Luminex assays in samples collected weekly in 22 summer schools and 2 pre-schools in 27 venues in Barcelona, Spain, from June 29th to July 31st, 2020. Results: Saliva antibody conversion between two visits over a 5-week period was 3.22% (49/1518) or 2.36% if accounting for potentially cross-reactive antibodies, six times higher than the cumulative infection rate (0.53%) assessed by weekly saliva RT-PCR screening. IgG conversion was higher in adults (2.94%, 11/374) than children (1.31%, 15/1144) (p=0.035), IgG and IgA levels moderately increased with age, and antibodies were higher in females. Most antibody converters increased both IgG and IgA antibodies but some augmented either IgG or IgA, with a faster decay over time for IgA than IgG. Nucleocapsid rather than spike was the main antigen target. Anti-spike antibodies were significantly higher in individuals not reporting symptoms than symptomatic individuals, suggesting a protective role against COVID-19. Conclusion: Saliva antibody profiling including three isotypes and multiplexing antigens is a useful and user-friendlier tool for screening pediatric populations to detect low viral load exposures among children, particularly while they are not vaccinated and vulnerable to highly contagious variants, and to recommend public health policies during pandemics