2024
Semi-supervised machine learning method for predicting homogeneous ancestry groups to assess Hardy-Weinberg equilibrium in diverse whole-genome sequencing studies
Shyr D, Dey R, Li X, Zhou H, Boerwinkle E, Buyske S, Daly M, Gibbs R, Hall I, Matise T, Reeves C, Stitziel N, Zody M, Neale B, Lin X. Semi-supervised machine learning method for predicting homogeneous ancestry groups to assess Hardy-Weinberg equilibrium in diverse whole-genome sequencing studies. American Journal Of Human Genetics 2024, 111: 2129-2138. PMID: 39270648, PMCID: PMC11480788, DOI: 10.1016/j.ajhg.2024.08.018.Peer-Reviewed Original ResearchHardy-Weinberg equilibriumWhole-genome sequencing studiesWhole-genome sequencingHomogeneous ancestryWGS studiesDownstream analysisAssociation analysisPresence of population structureAncestry groupsGenetic ancestry groupsPopulation structureSequencing studiesSelf-reported raceGenetic researchQuality variantsAncestrySubsets of samplesProgram centersVariantsIncreasing diversityHeterogeneous sampleAncestralAssociationGeneticsSequence
2023
Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification
de Vries P, Conomos M, Singh K, Nicholson C, Jain D, Hasbani N, Jiang W, Lee S, Lino Cardenas C, Lutz S, Wong D, Guo X, Yao J, Young E, Tcheandjieu C, Hilliard A, Bis J, Bielak L, Brown M, Musharoff S, Clarke S, Terry J, Palmer N, Yanek L, Xu H, Heard-Costa N, Wessel J, Selvaraj M, Li R, Sun X, Turner A, Stilp A, Khan A, Newman A, Rasheed A, Freedman B, Kral B, McHugh C, Hodonsky C, Saleheen D, Herrington D, Jacobs D, Nickerson D, Boerwinkle E, Wang F, Heiss G, Jun G, Kinney G, Sigurslid H, Doddapaneni H, Hall I, Bensenor I, Broome J, Crapo J, Wilson J, Smith J, Blangero J, Vargas J, Mosquera J, Smith J, Viaud-Martinez K, Ryan K, Young K, Taylor K, Lange L, Emery L, Bittencourt M, Budoff M, Montasser M, Yu M, Mahaney M, Mahamdeh M, Fornage M, Franceschini N, Lotufo P, Natarajan P, Wong Q, Mathias R, Gibbs R, Do R, Mehran R, Tracy R, Kim R, Nelson S, Damrauer S, Kardia S, Rich S, Fuster V, Napolioni V, Zhao W, Tian W, Yin X, Min Y, Manning A, Peloso G, Kelly T, O’Donnell C, Morrison A, Curran J, Zapol W, Bowden D, Becker L, Correa A, Mitchell B, Psaty B, Carr J, Pereira A, Assimes T, Stitziel N, Hokanson J, Laurie C, Rotter J, Vasan R, Post W, Peyser P, Miller C, Malhotra R. Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification. Nature Cardiovascular Research 2023, 2: 1159-1172. PMID: 38817323, PMCID: PMC11138106, DOI: 10.1038/s44161-023-00375-y.Peer-Reviewed Original ResearchGenome-wide association studiesMultiple ancestral groupsWhole-genome sequencingPotential drug targetsNovel lociAncestral groupsLociCoronary artery calcificationVascular smooth muscle cellsDrug targetsFunctional assaysPhenotypic switchingCoronary artery diseaseVascular smooth muscle cell phenotypic switchingHuman vascular smooth muscle cellsARSEG alleleArtery calcificationVascular calcificationPredictor of coronary artery diseaseReplicate analysesRegulation of vascular calcificationSmooth muscle cellsCalcifiersSequenceA draft human pangenome reference
Liao W, Asri M, Ebler J, Doerr D, Haukness M, Hickey G, Lu S, Lucas J, Monlong J, Abel H, Buonaiuto S, Chang X, Cheng H, Chu J, Colonna V, Eizenga J, Feng X, Fischer C, Fulton R, Garg S, Groza C, Guarracino A, Harvey W, Heumos S, Howe K, Jain M, Lu T, Markello C, Martin F, Mitchell M, Munson K, Mwaniki M, Novak A, Olsen H, Pesout T, Porubsky D, Prins P, Sibbesen J, Sirén J, Tomlinson C, Villani F, Vollger M, Antonacci-Fulton L, Baid G, Baker C, Belyaeva A, Billis K, Carroll A, Chang P, Cody S, Cook D, Cook-Deegan R, Cornejo O, Diekhans M, Ebert P, Fairley S, Fedrigo O, Felsenfeld A, Formenti G, Frankish A, Gao Y, Garrison N, Giron C, Green R, Haggerty L, Hoekzema K, Hourlier T, Ji H, Kenny E, Koenig B, Kolesnikov A, Korbel J, Kordosky J, Koren S, Lee H, Lewis A, Magalhães H, Marco-Sola S, Marijon P, McCartney A, McDaniel J, Mountcastle J, Nattestad M, Nurk S, Olson N, Popejoy A, Puiu D, Rautiainen M, Regier A, Rhie A, Sacco S, Sanders A, Schneider V, Schultz B, Shafin K, Smith M, Sofia H, Abou Tayoun A, Thibaud-Nissen F, Tricomi F, Wagner J, Walenz B, Wood J, Zimin A, Bourque G, Chaisson M, Flicek P, Phillippy A, Zook J, Eichler E, Haussler D, Wang T, Jarvis E, Miga K, Garrison E, Marschall T, Hall I, Li H, Paten B. A draft human pangenome reference. Nature 2023, 617: 312-324. PMID: 37165242, PMCID: PMC10172123, DOI: 10.1038/s41586-023-05896-x.Peer-Reviewed Original ResearchGaps and complex structurally variant loci in phased genome assemblies
Porubsky D, Vollger M, Harvey W, Rozanski A, Ebert P, Hickey G, Hasenfeld P, Sanders A, Stober C, Consortium H, Korbel J, Paten B, Marschall T, Eichler E, Abel H, Antonacci-Fulton L, Asri M, Baid G, Baker C, Belyaeva A, Billis K, Bourque G, Buonaiuto S, Carroll A, Chaisson M, Chang P, Chang X, Cheng H, Chu J, Cody S, Colonna V, Cook D, Cook-Deegan R, Cornejo O, Diekhans M, Doerr D, Ebert P, Ebler J, Eichler E, Eizenga J, Fairley S, Fedrigo O, Felsenfeld A, Feng X, Fischer C, Flicek P, Formenti G, Frankish A, Fulton R, Gao Y, Garg S, Garrison E, Garrison N, Giron C, Green R, Groza C, Guarracino A, Haggerty L, Hall I, Harvey W, Haukness M, Haussler D, Heumos S, Hickey G, Hoekzema K, Hourlier T, Howe K, Jain M, Jarvis E, Ji H, Kenny E, Koenig B, Kolesnikov A, Korbel J, Kordosky J, Koren S, Lee H, Lewis A, Li H, Liao W, Lu S, Lu T, Lucas J, Magalhães H, Marco-Sola S, Marijon P, Markello C, Marschall T, Martin F, McCartney A, McDaniel J, Miga K, Mitchell M, Monlong J, Mountcastle J, Munson K, Mwaniki M, Nattestad M, Novak A, Nurk S, Olsen H, Olson N, Paten B, Pesout T, Phillippy A, Popejoy A, Porubsky D, Prins P, Puiu D, Rautiainen M, Regier A, Rhie A, Sacco S, Sanders A, Schneider V, Schultz B, Shafin K, Sibbesen J, Sirén J, Smith M, Sofia H, Tayoun A, Thibaud-Nissen F, Tomlinson C, Tricomi F, Villani F, Vollger M, Wagner J, Walenz B, Wang T, Wood J, Zimin A, Zook J. Gaps and complex structurally variant loci in phased genome assemblies. Genome Research 2023, 33: 496-510. PMID: 37164484, PMCID: PMC10234299, DOI: 10.1101/gr.277334.122.Peer-Reviewed Original ResearchConceptsProtein-coding genesGenome assemblyMbp of DNALinked-read dataLarge segmental duplicationsStrand-seqDiversity panelInversion polymorphismHaploid genomeSegmental duplicationsEuchromatic DNAMore haplotypesIdentical repeatsHaploid assembliesVariant lociDNAHaplotypesGenesFrequent expansionAssembly gapsImportant targetAssemblyHuman speciesHuman samplesMBP
2022
Semi-automated assembly of high-quality diploid human reference genomes
Jarvis E, Formenti G, Rhie A, Guarracino A, Yang C, Wood J, Tracey A, Thibaud-Nissen F, Vollger M, Porubsky D, Cheng H, Asri M, Logsdon G, Carnevali P, Chaisson M, Chin C, Cody S, Collins J, Ebert P, Escalona M, Fedrigo O, Fulton R, Fulton L, Garg S, Gerton J, Ghurye J, Granat A, Green R, Harvey W, Hasenfeld P, Hastie A, Haukness M, Jaeger E, Jain M, Kirsche M, Kolmogorov M, Korbel J, Koren S, Korlach J, Lee J, Li D, Lindsay T, Lucas J, Luo F, Marschall T, Mitchell M, McDaniel J, Nie F, Olsen H, Olson N, Pesout T, Potapova T, Puiu D, Regier A, Ruan J, Salzberg S, Sanders A, Schatz M, Schmitt A, Schneider V, Selvaraj S, Shafin K, Shumate A, Stitziel N, Stober C, Torrance J, Wagner J, Wang J, Wenger A, Xiao C, Zimin A, Zhang G, Wang T, Li H, Garrison E, Haussler D, Hall I, Zook J, Eichler E, Phillippy A, Paten B, Howe K, Miga K. Semi-automated assembly of high-quality diploid human reference genomes. Nature 2022, 611: 519-531. PMID: 36261518, PMCID: PMC9668749, DOI: 10.1038/s41586-022-05325-5.Peer-Reviewed Original ResearchConceptsDiploid genome assemblyGenome assemblyProtein-coding genesGlobal genetic variationCurrent human reference genomeDiploid human genomeHigh-quality assemblyAccurate long readsNon-synonymous amino acid changesHuman reference genomeAmino acid changesMost chromosomesReference assemblyReference genomeHuman genomeCentromeric regionsGenetic variationHigh diversityGenome sequencingLong readsSingle nucleotideGenomeAcid changesManual curationBiological genomesIntegrating transcriptomics, metabolomics, and GWAS helps reveal molecular mechanisms for metabolite levels and disease risk
Yin X, Bose D, Kwon A, Hanks S, Jackson A, Stringham H, Welch R, Oravilahti A, Silva L, FinnGen, Locke A, Fuchsberger C, Service S, Erdos M, Bonnycastle L, Kuusisto J, Stitziel N, Hall I, Morrison J, Ripatti S, Palotie A, Freimer N, Collins F, Mohlke K, Scott L, Fauman E, Burant C, Boehnke M, Laakso M, Wen X. Integrating transcriptomics, metabolomics, and GWAS helps reveal molecular mechanisms for metabolite levels and disease risk. American Journal Of Human Genetics 2022, 109: 1727-1741. PMID: 36055244, PMCID: PMC9606383, DOI: 10.1016/j.ajhg.2022.08.007.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesMolecular mechanismsGWAS resultsDisease traitsGene expressionMetabolic pathwaysTranscriptome-wide associationSame causal variantsMetabolomics resultsTranscriptomic resultsMolecular traitsTranscriptomic dataGTEx projectCausal variantsGlycerophospholipid metabolic pathwayTranscriptomicsAssociation studiesColocalization analysisMetabolite levelsDistinct pathwaysPutative causal effectGenetic variantsGenesUGT1A4 expressionGenetic associationHigh-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios
Byrska-Bishop M, Evani U, Zhao X, Basile A, Abel H, Regier A, Corvelo A, Clarke W, Musunuri R, Nagulapalli K, Fairley S, Runnels A, Winterkorn L, Lowy E, Consortium H, Eichler E, Korbel J, Lee C, Marschall T, Devine S, Harvey W, Zhou W, Mills R, Rausch T, Kumar S, Alkan C, Hormozdiari F, Chong Z, Chen Y, Yang X, Lin J, Gerstein M, Kai Y, Zhu Q, Yilmaz F, Xiao C, Flicek P, Germer S, Brand H, Hall I, Talkowski M, Narzisi G, Zody M. High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios. Cell 2022, 185: 3426-3440.e19. PMID: 36055201, PMCID: PMC9439720, DOI: 10.1016/j.cell.2022.08.004.Peer-Reviewed Original ResearchThe Human Pangenome Project: a global resource to map genomic diversity
Wang T, Antonacci-Fulton L, Howe K, Lawson HA, Lucas JK, Phillippy AM, Popejoy AB, Asri M, Carson C, Chaisson MJP, Chang X, Cook-Deegan R, Felsenfeld AL, Fulton RS, Garrison EP, Garrison N, Graves-Lindsay TA, Ji H, Kenny EE, Koenig BA, Li D, Marschall T, McMichael JF, Novak AM, Purushotham D, Schneider VA, Schultz BI, Smith MW, Sofia HJ, Weissman T, Flicek P, Li H, Miga KH, Paten B, Jarvis ED, Hall IM, Eichler EE, Haussler D. The Human Pangenome Project: a global resource to map genomic diversity. Nature 2022, 604: 437-446. PMID: 35444317, PMCID: PMC9402379, DOI: 10.1038/s41586-022-04601-8.Peer-Reviewed Original ResearchConceptsHuman reference genomeReference genomeGenomic diversityGenomic variationHuman genomic variationGlobal genomic diversitySingle nucleotide variantsGene-disease associationsDiploid genomeGenetic resourcesGenomeGenomic researchFuture biomedical researchHigh-quality referenceStructural variantsHuman geneticsRoutine assemblyCommon variantsFunctional elementsPolymorphic regionDiversityBiomedical researchVariantsMajor updateGenetics
2021
Structural variants are a major source of gene expression differences in humans and often affect multiple nearby genes
Scott AJ, Chiang C, Hall IM. Structural variants are a major source of gene expression differences in humans and often affect multiple nearby genes. Genome Research 2021, 31: gr.275488.121. PMID: 34544830, PMCID: PMC8647827, DOI: 10.1101/gr.275488.121.Peer-Reviewed Original ResearchRare structural variantsGene expression differencesStructural variantsNearby genesExpression differencesGene expressionMultiple nearby genesIndividual structural variantsHuman genome diversityMobile element insertionsGene expression changesGene expression outliersCommon structural variantsCurrent annotationGenome diversityPhenotypic variationGTEx projectRegulatory elementsElement insertionsExpression outliersMultiple genesDifferent genesExpression changesMultitissue analysesGenesMitochondrial genome copy number measured by DNA sequencing in human blood is strongly associated with metabolic traits via cell-type composition differences
Ganel L, Chen L, Christ R, Vangipurapu J, Young E, Das I, Kanchi K, Larson D, Regier A, Abel H, Kang CJ, Scott A, Havulinna A, Chiang CWK, Service S, Freimer N, Palotie A, Ripatti S, Kuusisto J, Boehnke M, Laakso M, Locke A, Stitziel NO, Hall IM. Mitochondrial genome copy number measured by DNA sequencing in human blood is strongly associated with metabolic traits via cell-type composition differences. Human Genomics 2021, 15: 34. PMID: 34099068, PMCID: PMC8185936, DOI: 10.1186/s40246-021-00335-2.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedApoptosis Regulatory ProteinsCell LineageDNA Copy Number VariationsDNA, MitochondrialExome SequencingFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyGenome, MitochondrialGTP-Binding ProteinsHumansMaleMembrane ProteinsMendelian Randomization AnalysisMiddle AgedPhenotypePolymorphism, Single NucleotideProto-Oncogene Proteins c-mybSequence Analysis, DNAConceptsCell type compositionGenome copy numberBlood-derived DNAMitochondrial genome copy numberCombination of genomesCopy numberBulk DNA sequencingDNA sequencingPolygenic risk scoresNumber of mitochondriaExome sequencing dataRelated traitsSequencing dataMetabolic traitsTraitsCommon variantsLociRare variantsSequencingDNAFinnish individualsMendelian randomization frameworkUK BiobankMetS traitsGenomeAssociation of structural variation with cardiometabolic traits in Finns
Chen L, Abel HJ, Das I, Larson DE, Ganel L, Kanchi KL, Regier AA, Young EP, Kang CJ, Scott AJ, Chiang C, Wang X, Lu S, Christ R, Service SK, Chiang CWK, Havulinna AS, Kuusisto J, Boehnke M, Laakso M, Palotie A, Ripatti S, Freimer NB, Locke AE, Stitziel NO, Hall IM. Association of structural variation with cardiometabolic traits in Finns. American Journal Of Human Genetics 2021, 108: 583-596. PMID: 33798444, PMCID: PMC8059371, DOI: 10.1016/j.ajhg.2021.03.008.Peer-Reviewed Original ResearchMeSH KeywordsAllelesCardiovascular DiseasesCholesterolDNA Copy Number VariationsFemaleFinlandGenome, HumanGenomic Structural VariationGenotypeHigh-Throughput Nucleotide SequencingHumansMaleMitochondrial ProteinsPromoter Regions, GeneticPyruvate Dehydrogenase (Lipoamide)-PhosphatasePyruvic AcidSerum Albumin, HumanConceptsSingle nucleotide variantsCopy number variantsQuantitative traitsGenome-wide significant associationStructural variationsTrait mapping studiesDeep whole-genome sequencing dataGenome structural variationsWhole-genome sequencing dataStrong phenotypic effectsComplex genomic regionsCardiometabolic traitsLow-frequency structural variationsEvolutionary timeGenomic regionsPhenotypic effectsSequencing dataNucleotide variantsGenotype dataGene deletionNumber variantsTraitsGenetic associationCandidate associationsExome sequencing
2020
Mapping and characterization of structural variation in 17,795 human genomes
Abel HJ, Larson DE, Regier AA, Chiang C, Das I, Kanchi KL, Layer RM, Neale BM, Salerno WJ, Reeves C, Buyske S, Matise T, Muzny D, Zody M, Lander E, Dutcher S, Stitziel N, Hall I. Mapping and characterization of structural variation in 17,795 human genomes. Nature 2020, 583: 83-89. PMID: 32460305, PMCID: PMC7547914, DOI: 10.1038/s41586-020-2371-0.Peer-Reviewed Original ResearchConceptsStructural variantsWhole-genome sequencingHuman genomeUltra-rare structural variantsRare structural variantsSuch structural variantsSingle nucleotide variantsNoncoding elementsDosage sensitivityGenomeHuman geneticsSmall insertionsComplex rearrangementsDeletion variantsSmall variantsStructural variationsGenesSequencingAllelesForm of variationVariantsElement classesSite frequency dataDeleterious effectsGenetics
2019
Exome sequencing of Finnish isolates enhances rare-variant association power
Locke AE, Steinberg KM, Chiang CWK, Service SK, Havulinna AS, Stell L, Pirinen M, Abel HJ, Chiang CC, Fulton RS, Jackson AU, Kang CJ, Kanchi KL, Koboldt DC, Larson DE, Nelson J, Nicholas TJ, Pietilä A, Ramensky V, Ray D, Scott LJ, Stringham HM, Vangipurapu J, Welch R, Yajnik P, Yin X, Eriksson JG, Ala-Korpela M, Järvelin MR, Männikkö M, Laivuori H, Dutcher S, Stitziel N, Wilson R, Hall I, Sabatti C, Palotie A, Salomaa V, Laakso M, Ripatti S, Boehnke M, Freimer N. Exome sequencing of Finnish isolates enhances rare-variant association power. Nature 2019, 572: 323-328. PMID: 31367044, PMCID: PMC6697530, DOI: 10.1038/s41586-019-1457-z.Peer-Reviewed Original Researchsvtools: population-scale analysis of structural variation
Larson DE, Abel HJ, Chiang C, Badve A, Das I, Eldred JM, Layer RM, Hall IM. svtools: population-scale analysis of structural variation. Bioinformatics 2019, 35: 4782-4787. PMID: 31218349, PMCID: PMC6853660, DOI: 10.1093/bioinformatics/btz492.Peer-Reviewed Original ResearchGenomic Analysis in the Age of Human Genome Sequencing
Lappalainen T, Scott AJ, Brandt M, Hall IM. Genomic Analysis in the Age of Human Genome Sequencing. Cell 2019, 177: 70-84. PMID: 30901550, PMCID: PMC6532068, DOI: 10.1016/j.cell.2019.02.032.Peer-Reviewed Original ResearchMeSH KeywordsBiological Specimen BanksChromosome MappingGenetic Predisposition to DiseaseGenetic TestingGenetic VariationGenome-Wide Association StudyGenome, HumanGenomicsHigh-Throughput Nucleotide SequencingHuman Genome ProjectHumansPolymorphism, Single NucleotideSequence Analysis, DNAWhole Genome SequencingConceptsFunctional genomics approachAllele frequency spectrumHuman genome sequencingGene mapping studiesGenome sequencing technologiesRare human diseasesWhole-genome sequencingGenomic approachesGenetic variant discoveryGenome variationHuman genomeGenome analysisGenomic analysisSequencing technologiesGenome sequencingVariant discoveryHuman diseasesHuman geneticsGenomeFunctional interpretationMapping studiesFunctional effectsSequencingGermline variantsGenetics
2018
Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects
Regier AA, Farjoun Y, Larson DE, Krasheninina O, Kang HM, Howrigan DP, Chen BJ, Kher M, Banks E, Ames DC, English AC, Li H, Xing J, Zhang Y, Matise T, Abecasis GR, Salerno W, Zody MC, Neale BM, Hall IM. Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects. Nature Communications 2018, 9: 4038. PMID: 30279509, PMCID: PMC6168605, DOI: 10.1038/s41467-018-06159-4.Peer-Reviewed Original ResearchDifferences in the commonly used genotype imputation algorithms and their imputation accuracy estimates
Pärn K, Pirinen M, Kals M, Mägi R, Salomaa V, Boehnke M, Hall I, Stitziel N, Freimer N, Daly M, Palotie A, Ripatti S, Palta P. Differences in the commonly used genotype imputation algorithms and their imputation accuracy estimates. 2018, 293-294. DOI: 10.1109/escience.2018.00058.Peer-Reviewed Original Research
2017
The impact of rare variation on gene expression across tissues
Aguet F, Ardlie K, Cummings B, Gelfand E, Getz G, Hadley K, Handsaker R, Huang K, Kashin S, Karczewski K, Lek M, Li X, MacArthur D, Nedzel J, Nguyen D, Noble M, Segrè A, Trowbridge C, Tukiainen T, Abell N, Balliu B, Barshir R, Basha O, Battle A, Bogu G, Brown A, Brown C, Castel S, Chen L, Chiang C, Conrad D, Cox N, Damani F, Davis J, Delaneau O, Dermitzakis E, Engelhardt B, Eskin E, Ferreira P, Frésard L, Gamazon E, Garrido-Martín D, Gewirtz A, Gliner G, Gloudemans M, Guigo R, Hall I, 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 M, McDowell I, Mohammadi P, Monlong J, Montgomery S, Muñoz-Aguirre M, Ndungu A, Nicolae D, Nobel A, Oliva M, Ongen H, Palowitch J, Panousis N, Papasaikas P, Park Y, Parsana P, Payne A, Peterson C, Quan J, Reverter F, Sabatti C, Saha A, Sammeth M, Scott A, Shabalin A, Sodaei R, Stephens M, Stranger B, Strober B, Sul J, Tsang E, Urbut S, van de Bunt M, Wang G, Wen X, Wright F, Xi H, Yeger-Lotem E, Zappala Z, Zaugg J, Zhou Y, Akey J, Bates D, Chan J, Chen L, Claussnitzer M, Demanelis K, Diegel M, Doherty J, Feinberg A, Fernando M, Halow J, Hansen K, Haugen E, Hickey P, Hou L, Jasmine F, Jian R, Jiang L, Johnson A, Kaul R, Kellis M, Kibriya M, Lee K, Billy Li J, Li Q, Li X, Lin J, Lin S, Linder S, Linke C, Liu Y, Maurano M, Molinie B, Montgomery S, Nelson J, Neri F, Oliva M, Park Y, Pierce B, Rinaldi N, Rizzardi L, Sandstrom R, Skol A, Smith K, Snyder M, Stamatoyannopoulos J, Stranger B, Tang H, Tsang E, Wang L, Wang M, Van Wittenberghe N, Wu F, Zhang R, Nierras C, Branton P, Carithers L, Guan P, Moore H, Rao A, Vaught J, Gould S, Lockart N, Martin C, Struewing J, Volpi S, Addington A, Koester S, Little A, Brigham L, Hasz R, Hunter M, Johns C, Johnson M, Kopen G, Leinweber W, Lonsdale J, McDonald A, Mestichelli B, Myer K, Roe B, Salvatore M, Shad S, Thomas J, Walters G, Washington M, Wheeler J, Bridge J, Foster B, Gillard B, Karasik E, Kumar R, Miklos M, Moser M, Jewell S, Montroy R, Rohrer D, Valley D, Davis D, Mash D, Undale A, Smith A, Tabor D, Roche N, McLean J, Vatanian N, Robinson K, Sobin L, Barcus M, Valentino K, Qi L, Hunter S, Hariharan P, Singh S, Um K, Matose T, Tomaszewski M, Barker L, Mosavel M, Siminoff L, Traino H, Flicek P, Juettemann T, Ruffier M, Sheppard D, Taylor K, Trevanion S, Zerbino D, Craft B, Goldman M, Haeussler M, Kent W, Lee C, Paten B, Rosenbloom K, Vivian J, Zhu J. The impact of rare variation on gene expression across tissues. Nature 2017, 550: 239-243. PMID: 29022581, PMCID: PMC5877409, DOI: 10.1038/nature24267.Peer-Reviewed Original ResearchDynamic landscape and regulation of RNA editing in mammals
Aguet F, Ardlie K, Cummings B, Gelfand E, Getz G, Hadley K, Handsaker R, Huang K, Kashin S, Karczewski K, Lek M, Li X, MacArthur D, Nedzel J, Nguyen D, Noble M, Segrè A, Trowbridge C, Tukiainen T, Abell N, Balliu B, Barshir R, Basha O, Battle A, Bogu G, Brown A, Brown C, Castel S, Chen L, Chiang C, Conrad D, Cox N, Damani F, Davis J, Delaneau O, Dermitzakis E, Engelhardt B, Eskin E, Ferreira P, Frésard L, Gamazon E, Garrido-Martín D, Gewirtz A, Gliner G, Gloudemans M, Guigo R, Hall I, 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 M, McDowell I, Mohammadi P, Monlong J, Montgomery S, Muñoz-Aguirre M, Ndungu A, Nicolae D, Nobel A, Oliva M, Ongen H, Palowitch J, Panousis N, Papasaikas P, Park Y, Parsana P, Payne A, Peterson C, Quan J, Reverter F, Sabatti C, Saha A, Sammeth M, Scott A, Shabalin A, Sodaei R, Stephens M, Stranger B, Strober B, Sul J, Tsang E, Urbut S, van de Bunt M, Wang G, Wen X, Wright F, Xi H, Yeger-Lotem E, Zappala Z, Zaugg J, Zhou Y, Akey J, Bates D, Chan J, Chen L, Claussnitzer M, Demanelis K, Diegel M, Doherty J, Feinberg A, Fernando M, Halow J, Hansen K, Haugen E, Hickey P, Hou L, Jasmine F, Jian R, Jiang L, Johnson A, Kaul R, Kellis M, Kibriya M, Lee K, Li J, Li Q, Li X, Lin J, Lin S, Linder S, Linke C, Liu Y, Maurano M, Molinie B, Montgomery S, Nelson J, Neri F, Oliva M, Park Y, Pierce B, Rinaldi N, Rizzardi L, Sandstrom R, Skol A, Smith K, Snyder M, Stamatoyannopoulos J, Stranger B, Tang H, Tsang E, Wang L, Wang M, Van Wittenberghe N, Wu F, Zhang R, Nierras C, Branton P, Carithers L, Guan P, Moore H, Rao A, Vaught J, Gould S, Lockart N, Martin C, Struewing J, Volpi S, Addington A, Koester S, Little A, Brigham L, Hasz R, Hunter M, Johns C, Johnson M, Kopen G, Leinweber W, Lonsdale J, McDonald A, Mestichelli B, Myer K, Roe B, Salvatore M, Shad S, Thomas J, Walters G, Washington M, Wheeler J, Bridge J, Foster B, Gillard B, Karasik E, Kumar R, Miklos M, Moser M, Jewell S, Montroy R, Rohrer D, Valley D, Davis D, Mash D, Undale A, Smith A, Tabor D, Roche N, McLean J, Vatanian N, Robinson K, Sobin L, Barcus M, Valentino K, Qi L, Hunter S, Hariharan P, Singh S, Um K, Matose T, Tomaszewski M, Barker L, Mosavel M, Siminoff L, Traino H, Flicek P, Juettemann T, Ruffier M, Sheppard D, Taylor K, Trevanion S, Zerbino D, Craft B, Goldman M, Haeussler M, Kent W, Lee C, Paten B, Rosenbloom K, Vivian J, Zhu J. Dynamic landscape and regulation of RNA editing in mammals. Nature 2017, 550: 249-254. PMID: 29022589, PMCID: PMC5723435, DOI: 10.1038/nature24041.Peer-Reviewed Original ResearchLandscape of X chromosome inactivation across human tissues
Aguet F, Ardlie K, Cummings B, Gelfand E, Getz G, Hadley K, Handsaker R, Huang K, Kashin S, Karczewski K, Lek M, Li X, MacArthur D, Nedzel J, Nguyen D, Noble M, Segrè A, Trowbridge C, Tukiainen T, Abell N, Balliu B, Barshir R, Basha O, Battle A, Bogu G, Brown A, Brown C, Castel S, Chen L, Chiang C, Conrad D, Cox N, Damani F, Davis J, Delaneau O, Dermitzakis E, Engelhardt B, Eskin E, Ferreira P, Frésard L, Gamazon E, Garrido-Martín D, Gewirtz A, Gliner G, Gloudemans M, Guigo R, Hall I, 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 M, McDowell I, Mohammadi P, Monlong J, Montgomery S, Muñoz-Aguirre M, Ndungu A, Nicolae D, Nobel A, Oliva M, Ongen H, Palowitch J, Panousis N, Papasaikas P, Park Y, Parsana P, Payne A, Peterson C, Quan J, Reverter F, Sabatti C, Saha A, Sammeth M, Scott A, Shabalin A, Sodaei R, Stephens M, Stranger B, Strober B, Sul J, Tsang E, Urbut S, van de Bunt M, Wang G, Wen X, Wright F, Xi H, Yeger-Lotem E, Zappala Z, Zaugg J, Zhou Y, Akey J, Bates D, Chan J, Chen L, Claussnitzer M, Demanelis K, Diegel M, Doherty J, Feinberg A, Fernando M, Halow J, Hansen K, Haugen E, Hickey P, Hou L, Jasmine F, Jian R, Jiang L, Johnson A, Kaul R, Kellis M, Kibriya M, Lee K, Li J, Li Q, Li X, Lin J, Lin S, Linder S, Linke C, Liu Y, Maurano M, Molinie B, Montgomery S, Nelson J, Neri F, Oliva M, Park Y, Pierce B, Rinaldi N, Rizzardi L, Sandstrom R, Skol A, Smith K, Snyder M, Stamatoyannopoulos J, Stranger B, Tang H, Tsang E, Wang L, Wang M, Van Wittenberghe N, Wu F, Zhang R, Nierras C, Branton P, Carithers L, Guan P, Moore H, Rao A, Vaught J, Gould S, Lockart N, Martin C, Struewing J, Volpi S, Addington A, Koester S, Little A, Brigham L, Hasz R, Hunter M, Johns C, Johnson M, Kopen G, Leinweber W, Lonsdale J, McDonald A, Mestichelli B, Myer K, Roe B, Salvatore M, Shad S, Thomas J, Walters G, Washington M, Wheeler J, Bridge J, Foster B, Gillard B, Karasik E, Kumar R, Miklos M, Moser M, Jewell S, Montroy R, Rohrer D, Valley D, Davis D, Mash D, Undale A, Smith A, Tabor D, Roche N, McLean J, Vatanian N, Robinson K, Sobin L, Barcus M, Valentino K, Qi L, Hunter S, Hariharan P, Singh S, Um K, Matose T, Tomaszewski M, Barker L, Mosavel M, Siminoff L, Traino H, Flicek P, Juettemann T, Ruffier M, Sheppard D, Taylor K, Trevanion S, Zerbino D, Craft B, Goldman M, Haeussler M, Kent W, Lee C, Paten B, Rosenbloom K, Vivian J, Zhu J. Landscape of X chromosome inactivation across human tissues. Nature 2017, 550: 244-248. PMID: 29022598, PMCID: PMC5685192, DOI: 10.1038/nature24265.Peer-Reviewed Original Research
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