Structural variation across 138,134 samples in the TOPMed consortium.
Goo JunAdam EnglishGinger MetcalfJianzhi YangMark J P ChaissonNathan D PankratzVipin K MenonWilliam SalernoOlga KrashenininaAlbert Vernon SmithJohn LaneThomas BlackwellHyun Min KangSejal SalviQingchang MengHua ShenDivya PashamSravya BhamidipatiKavya KottapalliDonna K ArnettAllison Elizabeth Ashley-KochPaul L AuerKAthleen BeutelJoshua C BisJohn E BlangeroDonald BowdenJennifer A BrodyBrian E CadeYii-Der Ida ChenMichael ChoJoanne E CurranMyriam FornageBarry FrredmanTasha FingerlinBruce D GelbLifang HouYi-Jen HungJohn P KaneRobert KaplanWonji KimRuth J F LoosGregory M MarcusRasika A MathiasStephen T McGarveyCourtney MontgomeryTake NaseriSeyed NouraieMichael H PreussNicholette D D AllredPatricia A PeyserLaura RaffieldAakrosh RatanSusan RedlineMuagututia ReupenaJerome RotterStephen S RichMichiel RienstraIngo RuczinskiVijay G SankaranDavid A SchwartzChristine E SeidmanJonathan G SeidmanEdwin SilvermanJennifer A SmithAdrienne M StilpKent TaylorMarilyn TelenScott WeissL Keoki WilliamsBaojun WuLisa R YanekYingze ZhangJessica Lasky-SuMarie-Claude GingrasSusan K DutcherEvan EichlerStacey GabrielSoren GermerRyan KimKarine MartinezDeborah NickersonJames LuoAlexander P ReinerRichard GibbsEric BoerwinkleGoncaol AbecasisFritz J SedlazeckPublished in: Research square (2023)
Ever larger Structural Variant (SV) catalogs highlighting the diversity within and between populations help researchers better understand the links between SVs and disease. The identification of SVs from DNA sequence data is non-trivial and requires a balance between comprehensiveness and precision. Here we present a catalog of 355,667 SVs (59.34% novel) across autosomes and the X chromosome (50bp+) from 138,134 individuals in the diverse TOPMed consortium. We describe our methodologies for SV inference resulting in high variant quality and >90% allele concordance compared to long-read de-novo assemblies of well-characterized control samples. We demonstrate utility through significant associations between SVs and important various cardio-metabolic and hematologic traits. We have identified 690 SV hotspots and deserts and those that potentially impact the regulation of medically relevant genes. This catalog characterizes SVs across multiple populations and will serve as a valuable tool to understand the impact of SV on disease development and progression.