Featured Publications
Mitochondrial 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 traitsGenomeMapping 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 effectsGeneticsGenomic 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
2017
Landscape 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 ResearchUsing Cloning to Amplify Neuronal Genomes for Whole-Genome Sequencing and Comprehensive Mutation Detection and Validation
Hazen J, Duran M, Smith R, Rodriguez A, Martin G, Kupriyanov S, Hall I, Baldwin K. Using Cloning to Amplify Neuronal Genomes for Whole-Genome Sequencing and Comprehensive Mutation Detection and Validation. Neuromethods 2017, 131: 163-185. DOI: 10.1007/978-1-4939-7280-7_9.Peer-Reviewed Original ResearchNeuronal genomeSomatic cell nuclear transferEmbryonic cell lineClasses of mutationsEmbryonic stem cellsSequencing-based approachesCell nuclear transferSomatic mutationsWhole-genome sequencingNext-generation sequencingMutation detectionSomatic cellsBioinformatics methodsComprehensive mutation detectionNuclear transferIndividual mutationsGenomeCell typesStem cellsNew mutationsMutationsSingle cellsSequencingCell linesFalse positive calls