2017
Authors
Tan, MH; Li, Q; Shanmugam, R; Piskol, R; Kohler, J; Young, AN; Liu, KI; Zhang, R; Ramaswami, G; Ariyoshi, K; Gupte, A; Keegan, LP; George, CX; Ramu, A; Huang, N; Pollina, EA; Leeman, DS; Rustighi, A; Goh, YPS; Aguet, F; Ardlie, KG; Cummings, BB; Gelfand, ET; Getz, G; Hadley, K; Handsaker, RE; Huang, KH; Kashin, S; Karczewski, KJ; Lek, M; Li, X; MacArthur, DG; Nedzel, JL; Nguyen, DT; Noble, MS; Segrè, AV; Trowbridge, CA; Tukiainen, T; Abell, NS; Balliu, B; Barshir, R; Basha, O; Battle, A; Bogu, GK; Brown, A; Brown, CD; Castel, SE; Chen, LS; Chiang, C; Conrad, DF; Cox, NJ; Damani, FN; Davis, JR; Delaneau, O; Dermitzakis, ET; Engelhardt, BE; Eskin, E; Ferreira, PG; Frésard, L; Gamazon, ER; Garrido-Martín, D; Gewirtz, ADH; Gliner, G; Gloudemans, MJ; Guigo, R; Hall, IM; Han, B; He, Y; Hormozdiari, F; Howald, C; Kyung Im, H; Jo, B; Yong Kang, E; Kim, Y; Kim-Hellmuth, S; Lappalainen, T; Li, G; Li, X; Liu, B; Mangul, S; McCarthy, MI; McDowell, IC; Mohammadi, P; Monlong, J; Montgomery, SB; Muñoz-Aguirre, M; Ndungu, AW; Nicolae, DL; Nobel, AB; Oliva, M; Ongen, H; Palowitch, JJ; Panousis, N; Papasaikas, P; Park, Y; Parsana, P; Payne, AJ; Peterson, CB; Quan, J; Reverter, F; Sabatti, C; Saha, A; Sammeth, M; Scott, AJ; Shabalin, AA; Sodaei, R; Stephens, M; Stranger, BE; Strober, BJ; Sul, JH; Tsang, EK; Urbut, S; van de Bunt, M; Wang, G; Wen, X; Wright, FA; Xi, HS; Yeger-Lotem, E; Zappala, Z; Zaugg, JB; Zhou, Y; Akey, JM; Bates, D; Chan, J; Chen, LS; Claussnitzer, M; Demanelis, K; Diegel, M; Doherty, JA; Feinberg, AP; Fernando, MS; Halow, J; Hansen, KD; Haugen, E; Hickey, PF; Hou, L; Jasmine, F; Jian, R; Jiang, L; Johnson, A; Kaul, R; Kellis, M; Kibriya, MG; Lee, K; Li, JB; Li, Q; Li, X; Lin, J; Lin, S; Linder, S; Linke, C; Liu, Y; Maurano, MT; Molinie, B; Montgomery, SB; Nelson, J; Neri, FJ; Oliva, M; Park, Y; Pierce, BL; Rinaldi, NJ; Rizzardi, LF; Sandstrom, R; Skol, A; Smith, KS; Snyder, MP; Stamatoyannopoulos, J; Stranger, BE; Tang, H; Tsang, EK; Wang, L; Wang, M; Van Wittenberghe, N; Wu, F; Zhang, R; Nierras, CR; Branton, PA; Carithers, LJ; Guan, P; Moore, HM; Rao, A; Vaught, JB; Gould, SE; Lockart, NC; Martin, C; Struewing, JP; Volpi, S; Addington, AM; Koester, SE; Little, AR; Brigham, LE; Hasz, R; Hunter, M; Johns, C; Johnson, M; Kopen, G; Leinweber, WF; Lonsdale, JT; McDonald, A; Mestichelli, B; Myer, K; Roe, B; Salvatore, M; Shad, S; Thomas, JA; Walters, G; Washington, M; Wheeler, J; Bridge, J; Foster, BA; Gillard, BM; Karasik, E; Kumar, R; Miklos, M; Moser, MT; Jewell, SD; Montroy, RG; Rohrer, DC; Valley, DR; Davis, DA; Mash, DC; Undale, AH; Smith, AM; Tabor, DE; Roche, NV; McLean, JA; Vatanian, N; Robinson, KL; Sobin, L; Barcus, ME; Valentino, KM; Qi, L; Hunter, S; Hariharan, P; Singh, S; Um, KS; Matose, T; Tomaszewski, MM; Barker, LK; Mosavel, M; Siminoff, LA; Traino, HM; Flicek, P; Juettemann, T; Ruffier, M; Sheppard, D; Taylor, K; Trevanion, SJ; Zerbino, DR; Craft, B; Goldman, M; Haeussler, M; Kent, WJ; Lee, CM; Paten, B; Rosenbloom, KR; Vivian, J; Zhu, J; Chawla, A; Del Sal, G; Peltz, G; Brunet, A; Conrad, DF; Samuel, CE; O’Connell, MA; Walkley, CR; Nishikura, K; Li, JB;
Publication
Nature
Abstract
Adenosine-to-inosine (A-to-I) RNA editing is a conserved posttranscriptional mechanism mediated by ADAR enzymes that diversifies the transcriptome by altering selected nucleotides in RNA molecules1. Although many editing sites have recently been discovered2-7, the extent to which most sites are edited and how the editing is regulated in different biological contexts are not fully understood8-10. Here we report dynamic spatiotemporal patterns and new regulators of RNA editing, discovered through an extensive profiling of A-to-I RNA editing in 8,551 human samples (representing 53 body sites from 552 individuals) from the Genotype-Tissue Expression (GTEx) project and in hundreds of other primate and mouse samples. We show that editing levels in non-repetitive coding regions vary more between tissues than editing levels in repetitive regions. Globally, ADAR1 is the primary editor of repetitive sites and ADAR2 is the primary editor of nonrepetitive coding sites, whereas the catalytically inactive ADAR3 predominantly acts as an inhibitor of editing. Cross-species analysis of RNA editing in several tissues revealed that species, rather than tissue type, is the primary determinant of editing levels, suggesting stronger cis-directed regulation of RNA editing for most sites, although the small set of conserved coding sites is under stronger trans-regulation. In addition, we curated an extensive set of ADAR1 and ADAR2 targets and showed that many editing sites display distinct tissue-specific regulation by the ADAR enzymes in vivo. Further analysis of the GTEx data revealed several potential regulators of editing, such as AIMP2, which reduces editing in muscles by enhancing the degradation of the ADAR proteins. Collectively, our work provides insights into the complex cis-and trans-regulation of A-to-I editing.
2015
Authors
Borel, C; Ferreira, PG; Santoni, F; Delaneau, O; Fort, A; Popadin, KY; Garieri, M; Falconnet, E; Ribaux, P; Guipponi, M; Padioleau, I; Carninci, P; Dermitzakis, ET; Antonarakis, SE;
Publication
American Journal of Human Genetics
Abstract
The study of gene expression in mammalian single cells via genomic technologies now provides the possibility to investigate the patterns of allelic gene expression. We used single-cell RNA sequencing to detect the allele-specific mRNA level in 203 single human primary fibroblasts over 133,633 unique heterozygous single-nucleotide variants (hetSNVs). We observed that at the snapshot of analyses, each cell contained mostly transcripts from one allele from the majority of genes; indeed, 76.4% of the hetSNVs displayed stochastic monoallelic expression in single cells. Remarkably, adjacent hetSNVs exhibited a haplotype-consistent allelic ratio; in contrast, distant sites located in two different genes were independent of the haplotype structure. Moreover, the allele-specific expression in single cells correlated with the abundance of the cellular transcript. We observed that genes expressing both alleles in the majority of the single cells at a given time point were rare and enriched with highly expressed genes. The relative abundance of each allele in a cell was controlled by some regulatory mechanisms given that we observed related single-cell allelic profiles according to genes. Overall, these results have direct implications in cellular phenotypic variability. © 2015 The American Society of Human Genetics.
2014
Authors
Ongen, H; Andersen, CL; Bramsen, JB; Oster, B; Rasmussen, MH; Ferreira, PG; Sandoval, J; Vidal, E; Whiffin, N; Planchon, A; Padioleau, I; Bielser, D; Romano, L; Tomlinson, I; Houlston, RS; Esteller, M; Orntoft, TF; Dermitzakis, ET;
Publication
Nature
Abstract
The cis-regulatory effects responsible for cancer development have not been as extensively studied as the perturbations of the protein coding genome in tumorigenesis. To better characterize colorectal cancer (CRC) development we conducted an RNA-sequencing experiment of 103 matched tumour and normal colon mucosa samples from Danish CRC patients, 90 of which were germline-genotyped. By investigating allele-specific expression (ASE) we show that the germline genotypes remain important determinants of allelic gene expression in tumours. Using the changes in ASE in matched pairs of samples we discover 71 genes with excess of somatic cis-regulatory effects in CRC, suggesting a cancer driver role. We correlate genotypes and gene expression to identify expression quantitative trait loci (eQTLs) and find 1,693 and 948 eQTLs in normal samples and tumours, respectively. We estimate that 36% of the tumour eQTLs are exclusive to CRC and show that this specificity is partially driven by increased expression of specific transcription factors and changes in methylation patterns. We show that tumour-specific eQTLs are more enriched for low CRC genome-wide association study (GWAS) P values than shared eQTLs, which suggests that some of the GWAS variants are tumour specific regulatory variants. Importantly, tumour-specific eQTL genes also accumulate more somatic mutations when compared to the shared eQTL genes, raising the possibility that they constitute germline-derived cancer regulatory drivers. Collectively the integration of genome and the transcriptome reveals a substantial number of putative somatic and germline cis-regulatory cancer changes that may have a role in tumorigenesis.
2017
Authors
Cummings, BB; Marshall, JL; Tukiainen, T; Lek, M; Donkervoort, S; Foley, AR; Bolduc, V; Waddell, LB; Sandaradura, SA; O'Grady, GL; Estrella, E; Reddy, HM; Zhao, F; Weisburd, B; Karczewski, KJ; O'Donnell Luria, AH; Birnbaum, D; Sarkozy, A; Hu, Y; Gonorazky, H; Claeys, K; Joshi, H; Bournazos, A; Oates, EC; Ghaoui, R; Davis, MR; Laing, NG; Topf, A; Kang, PB; Beggs, AH; North, KN; Straub, V; Dowling, JJ; Muntoni, F; Clarke, NF; Cooper, ST; Bönnemann, CG; MacArthur, DG; Ardlie, KG; Getz, G; Gelfand, ET; Segrè, AV; Aguet, F; Sullivan, TJ; Li, X; Nedzel, JL; Trowbridge, CA; Hadley, K; Huang, KH; Noble, MS; Nguyen, DT; Nobel, AB; Wright, FA; Shabalin, AA; Palowitch, JJ; Zhou, YH; Dermitzakis, ET; McCarthy, MI; Payne, AJ; Lappalainen, T; Castel, S; Kim Hellmuth, S; Mohammadi, P; Battle, A; Parsana, P; Mostafavi, S; Brown, A; Ongen, H; Delaneau, O; Panousis, N; Howald, C; Van De Bunt, M; Guigo, R; Monlong, J; Reverter, F; Garrido, D; Munoz, M; Bogu, G; Sodaei, R; Papasaikas, P; Ndungu, AW; Montgomery, SB; Li, X; Fresard, L; Davis, JR; Tsang, EK; Zappala, Z; Abell, NS; Gloudemans, MJ; Liu, B; Damani, FN; Saha, A; Kim, Y; Strober, BJ; He, Y; Stephens, M; Pritchard, JK; Wen, X; Urbut, S; Cox, NJ; Nicolae, DL; Gamazon, ER; Im, HK; Brown, CD; Engelhardt, BE; Park, Y; Jo, B; McDowell, IC; Gewirtz, A; Gliner, G; Conrad, D; Hall, I; Chiang, C; Scott, A; Sabatti, C; Eskin, E; Peterson, C; Hormozdiari, F; Kang, EY; Mangul, S; Han, B; Sul, JH; Feinberg, AP; Rizzardi, LF; Hansen, KD; Hickey, P; Akey, J; Kellis, M; Li, JB; Snyder, M; Tang, H; Jiang, L; Lin, S; Stranger, BE; Fernando, M; Oliva, M; Stamatoyannopoulos, J; Kaul, R; Halow, J; Sandstrom, R; Haugen, E; Johnson, A; Lee, K; Bates, D; Diegel, M; Pierce, BL; Chen, L; Kibriya, MG; Jasmine, F; Doherty, J; Demanelis, K; Smith, KS; Li, Q; Zhang, R; Nierras, CR; Moore, HM; Rao, A; Guan, P; Vaught, JB; Branton, PA; Carithers, LJ; Volpi, S; Struewing, JP; Martin, CG; Nicole, LC; Koester, SE; Addington, AM; Little, AR; Leinweber, WF; Thomas, JA; Kopen, G; McDonald, A; Mestichelli, B; Shad, S; Lonsdale, JT; Salvatore, M; Hasz, R; Walters, G; Johnson, M; Washington, M; Brigham, LE; Johns, C; Wheeler, J; Roe, B; Hunter, M; Myer, K; Foster, BA; Moser, MT; Karasik, E; Gillard, BM; Kumar, R; Bridge, J; Miklos, M; Jewell, SD; Rohrer, DC; Valley, D; Montroy, RG; Mash, DC; Davis, DA; Undale, AH; Smith, AM; Tabor, DE; Roche, NV; McLean, JA; Vatanian, N; Robinson, KL; Sobin, L; Barcus, ME; Valentino, KM; Qi, L; Hunter, S; Hariharan, P; Singh, S; Um, KS; Matose, T; Tomadzewski, MM; Siminoff, LA; Traino, HM; Mosavel, M; Barker, LK; Zerbino, DR; Juettmann, T; Taylor, K; Ruffier, M; Sheppard, D; Trevanion, S; Flicek, P; Kent, WJ; Rosenbloom, KR; Haeussler, M; Lee, CM; Paten, B; Vivan, J; Zhu, J; Goldman, M; Craft, B; Li, G; Ferreira, PG; Yeger Lotem, E; Maurano, MT; Barshir, R; Basha, O; Xi, HS; Quan, J; Sammeth, M; Zaugg, JB;
Publication
Science Translational Medicine
Abstract
Exome and whole-genome sequencing are becoming increasingly routine approaches in Mendelian disease diagnosis. Despite their success, the current diagnostic rate for genomic analyses across a variety of rare diseases is approximately 25 to 50%. We explore the utility of transcriptome sequencing [RNA sequencing (RNA-seq)] as a complementary diagnostic tool in a cohort of 50 patients with genetically undiagnosed rare muscle disorders. We describe an integrated approach to analyze patient muscle RNA-seq, leveraging an analysis framework focused on the detection of transcript-level changes that are unique to the patient compared to more than 180 control skeletal muscle samples. We demonstrate the power of RNA-seq to validate candidate splice-disrupting mutations and to identify splice-altering variants in both exonic and deep intronic regions, yielding an overall diagnosis rate of 35%. We also report the discovery of a highly recurrent de novo intronic mutation in COL6A1 that results in a dominantly acting splice-gain event, disrupting the critical glycine repeat motif of the triple helical domain. We identify this pathogenic variant in a total of 27 genetically unsolved patients in an external collagen VI-like dystrophy cohort, thus explaining approximately 25% of patients clinically suggestive of having collagen VI dystrophy in whom prior genetic analysis is negative. Overall, this study represents a large systematic application of transcriptome sequencing to rare disease diagnosis and highlights its utility for the detection and interpretation of variants missed by current standard diagnostic approaches. 2017 © The Authors.
2015
Authors
Arous, C; Ferreira, PG; Dermitzakis, ET; Halban, PA;
Publication
Journal of Biological Chemistry
Abstract
2015
Authors
Melé, M; Ferreira, PG; Reverter, F; DeLuca, DS; Monlong, J; Sammeth, M; Young, TR; Goldmann, JM; Pervouchine, DD; Sullivan, TJ; Johnson, R; Segrè, AV; Djebali, S; Niarchou, A; Wright, FA; Lappalainen, T; Calvo, M; Getz, G; Dermitzakis, ET; Ardlie, KG; Guigó, R;
Publication
Science
Abstract
Transcriptional regulation and posttranscriptional processing underlie many cellular and organismal phenotypes. We used RNA sequence data generated by Genotype-Tissue Expression (GTEx) project to investigate the patterns of transcriptome variation across individuals and tissues. Tissues exhibit characteristic transcriptional signatures that show stability in postmortem samples. These signatures are dominated by a relatively small number of genes - which is most clearly seen in blood - though few are exclusive to a particular tissue and vary more across tissues than individuals. Genes exhibiting high interindividual expression variation include disease candidates associated with sex, ethnicity, and age. Primary transcription is the major driver of cellular specificity, with splicing playing mostly a complementary role; except for the brain, which exhibits a more divergent splicing program. Variation in splicing, despite its stochasticity, may play in contrast a comparatively greater role in defining individual phenotypes.
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