Featured Publications
The 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 updateGeneticsMitochondrial 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, MitochondrialGenome-Wide Association StudyGTP-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, HumanGenome-Wide Association StudyGenomicsHigh-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 variantsGeneticsThe Complete Genome Sequences, Unique Mutational Spectra, and Developmental Potency of Adult Neurons Revealed by Cloning
Hazen JL, Faust GG, Rodriguez AR, Ferguson WC, Shumilina S, Clark RA, Boland MJ, Martin G, Chubukov P, Tsunemoto RK, Torkamani A, Kupriyanov S, Hall IM, Baldwin KK. The Complete Genome Sequences, Unique Mutational Spectra, and Developmental Potency of Adult Neurons Revealed by Cloning. Neuron 2016, 89: 1223-1236. PMID: 26948891, PMCID: PMC4795965, DOI: 10.1016/j.neuron.2016.02.004.Peer-Reviewed Original ResearchMeSH KeywordsAge FactorsAnimalsAnimals, NewbornCadherin Related ProteinsCadherinsCell DivisionCloning, MolecularDNA Transposable ElementsEmbryo, MammalianFemaleHumansKi-67 AntigenMiceMice, TransgenicMicrosatellite RepeatsMutationNerve Tissue ProteinsNeuronsNuclear Transfer TechniquesOlfactory BulbOocytesSequence Analysis, DNAConceptsCell type diversificationComplete genome sequenceMobile element insertionsNuclear transfer methodWhole-genome sequencingNeuronal genomeGene-disrupting mutationsNeuronal mutationsGenome sequenceUnique mutational spectrumDevelopmental potencyComprehensive mutation detectionElement insertionsGenomic mutationsRecurrent rearrangementsNovel mechanismUnique mutationsMutationsSomatic mutationsGene biasGenomeAdult neuronsMutational spectrumFertile miceMutation detectionBreakpoint profiling of 64 cancer genomes reveals numerous complex rearrangements spawned by homology-independent mechanisms
Malhotra A, Lindberg M, Faust GG, Leibowitz ML, Clark RA, Layer RM, Quinlan AR, Hall IM. Breakpoint profiling of 64 cancer genomes reveals numerous complex rearrangements spawned by homology-independent mechanisms. Genome Research 2013, 23: 762-776. PMID: 23410887, PMCID: PMC3638133, DOI: 10.1101/gr.143677.112.Peer-Reviewed Original ResearchConceptsComplex genomic rearrangementsSingle mutational eventCancer genomesMutational eventsBreakpoint clusterDNA double-strand breaksHomology-independent mechanismsComplex rearrangementsDouble-strand breaksLarge-scale rearrangementsGenome architectureGenome rearrangementsNonhomologous repairGenomic rearrangementsChromothripsis eventsSelective advantageMore chromosomesTumor genomesGenomeGlioblastoma samplesTemplated insertionsState profilingPunctuated changeBreakpoint sequencesAllele frequenciesCharacterizing complex structural variation in germline and somatic genomes
Quinlan AR, Hall IM. Characterizing complex structural variation in germline and somatic genomes. Trends In Genetics 2011, 28: 43-53. PMID: 22094265, PMCID: PMC3249479, DOI: 10.1016/j.tig.2011.10.002.Peer-Reviewed Original ResearchConceptsComplex structural variationsStructural variationsNext-generation DNA sequencingHallmarks of cancerSomatic genomeGenetic diversityMultiple chromosomesSingle locusDistinct lociRecombination eventsComplex variantsSingle mutationMapping experimentsDNA sequencingComplicated rearrangementsMammalsCurrent knowledgeMapping studiesLociSubtle alterationsVariantsGenomeSurprising numberChromosomesGermlineRecurrent DNA copy number variation in the laboratory mouse
Egan CM, Sridhar S, Wigler M, Hall IM. Recurrent DNA copy number variation in the laboratory mouse. Nature Genetics 2007, 39: 1384-1389. PMID: 17965714, DOI: 10.1038/ng.2007.19.Peer-Reviewed Original ResearchConceptsCopy number variationsCopy numberNumber variationsGenome-wide analysisDNA copy number variationsRecent common ancestryGenerations of inbreedingRecurrent copy number variationsHigh-resolution microarraysCommon ancestryNatural variationGenetic differencesDifferent speciesDifferent lociGenerational timeLaboratory miceNonrandom processGenomeRecurrent mutationsLociAdditional strainsInbreedingLineagesGenesDiscrete segments
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 genomes
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 ResearchGenetic effects on gene expression across human tissues
Aguet F, Brown A, Castel S, Davis J, He Y, Jo B, Mohammadi P, Park Y, Parsana P, Segrè A, Strober B, Zappala Z, Cummings B, Gelfand E, Hadley K, Huang K, Lek M, Li X, Nedzel J, Nguyen D, Noble M, Sullivan T, Tukiainen T, MacArthur D, Getz G, Addington A, Guan P, Koester S, Little A, Lockhart N, Moore H, Rao A, Struewing J, Volpi S, 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, Mash D, Davis D, Sobin L, Barcus M, Branton P, Abell N, Balliu B, Delaneau O, Frésard L, Gamazon E, Garrido-Martín D, Gewirtz A, Gliner G, Gloudemans M, Han B, He A, Hormozdiari F, Li X, Liu B, Kang E, McDowell I, Ongen H, Palowitch J, Peterson C, Quon G, Ripke S, Saha A, Shabalin A, Shimko T, Sul J, Teran N, Tsang E, Zhang H, Zhou Y, Bustamante C, Cox N, Guigó R, Kellis M, McCarthy M, Conrad D, Eskin E, Li G, Nobel A, Sabatti C, Stranger B, Wen X, Wright F, Ardlie K, Dermitzakis E, Lappalainen T, 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. Genetic effects on gene expression across human tissues. Nature 2017, 550: 204-213. PMID: 29022597, PMCID: PMC5776756, DOI: 10.1038/nature24277.Peer-Reviewed Original ResearchConceptsGene expression levelsGenetic effectsExpression levelsGenotype-Tissue Expression (GTEx) projectLocal genetic variationMajority of genesHuman genetic traitsDisease-associated variationMolecular functionsGene regulationHuman genomeHuman tissuesExpression projectGenetic variationGenetic basisDiverse tissuesGene expressionTissue specificityGenetic traitsCellular mechanismsGenesFunctional propertiesGenomeTissueLociUsing 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
2014
Population-based structural variation discovery with Hydra-Multi
Lindberg MR, Hall IM, Quinlan AR. Population-based structural variation discovery with Hydra-Multi. Bioinformatics 2014, 31: 1286-1289. PMID: 25527832, PMCID: PMC4393510, DOI: 10.1093/bioinformatics/btu771.Peer-Reviewed Original ResearchConceptsNumber of genomesSV analysisStructural variation discoveryStructural variant detectionHuman genomeCancer Genome AtlasVariation discoveryGenomic rearrangementsGenome ProjectSequence alignmentSignal integrationIndel discoveryGenome AtlasGenomeMultiple individualsSupplementary dataSize variabilityVariant detectionCommodity hardwarePoor scalabilityAvailable datasetsAnalysis workflowScalabilityExtant toolsDiscovery