Cited by 523Genetic Associations and EpidemiologyGenetic and phenotypic traits in livestockGenetic Mapping and Diversity in Plants and Animals

Trans effects on gene expression can drive omnigenic inheritance

Open access
Liu, Xuanyao, Li, Yang I., Pritchard, Jonathan K.·2019·Cell

Published version of a preprint

Abstract

Early genome-wide association studies (GWASs) led to the surprising discovery that, for typical complex traits, most of the heritability is due to huge numbers of common variants with tiny effect sizes. Previously, we argued that new models are needed to understand these patterns. Here, we provide a formal model in which genetic contributions to complex traits are partitioned into direct effects from core genes and indirect effects from peripheral genes acting in trans. We propose that most heritability is driven by weak trans-eQTL SNPs, whose effects are mediated through peripheral genes to impact the expression of core genes. In particular, if the core genes for a trait tend to be co-regulated, then the effects of peripheral variation can be amplified such that nearly all of the genetic variance is driven by weak trans effects. Thus, our model proposes a framework for understanding key features of the architecture of complex traits.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.cell.2019.04.014

Cites

16 of 16 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Recent evidence from quantitative genetics in humans suggests that polygenic traits tend to be omnigenic; heritable variation in traits is not mainly due to a core biological process or pathway, but causative variants may act on almost any gene expressed in a relevant cell type, mediated by trans-regulatory variation.

    “Recent evidence from quantitative genetics (Boyle et al. 2017) in humans suggests that polygenic traits tend to be omnigenic. That is, heritable variation in traits is not mainly due to a core biological process or pathway, but causative variants may act on almost any gene expressed in a relevant cell type, mediated by trans-regulatory variation (Liu et al. 2019).”

    From The neural crest cell hypothesis: no unified explanation for domestication (2021) · cites this paper as Liu et al. 2019

  • APOE4 is a 'core' gene of AD pathogenesis in the sense that the strong effect on amyloid pathology, a core pathway of AD, explains the strong specific association with AD (odds ratio ~3.7-14.5).

    “Therefore, we propose that APOE4 is a “core” gene (Liu et al, 2019) of AD pathogenesis in the sense that the strong effect on amyloid pathology, a core pathway of AD, explains the strong specific association with AD (odds ratio ~3.7–14.5).”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 64

  1. Albert FW, Bloom JS, Siegel J, Day L, and Kruglyak L (2018). Genetics of trans-regulatory variation in gene expression. eLife 7, e35471. 30014850 PMC6072440
  2. Anttila V, Bulik-Sullivan B, Finucane HK, Walters RK, Bras J, Duncan L, Escott-Price V, Falcone GJ, Gormley P, Malik R,; Brainstorm Consortium (2018). Analysis of shared heritability in common disorders of the brain. Science 360, eaap8757. 29930110 PMC6097237
  3. Ardlie KG, Deluca DS, Segrè AV, Sullivan TJ, Young TR, Gelfand ET, Trowbridge CA, Maller JB, Tukiainen T, Lek M,; GTEx Consortium (2015). Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348, 648– 660. 25954001 PMC4547484
  4. Barton NH, Etheridge AM, and Vèber A (2017). The infinitesimal model: Definition, derivation, and implications. Theor. Popul. Biol. 118, 50– 73. 28709925
  5. Battle A, Mostafavi S, Zhu X, Potash JB, Weissman MM, McCormick C, Haudenschild CD, Beckman KB, Shi J, Mei R, (2014). Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals. Genome Res. 24, 14– 24. 24092820 PMC3875855
  6. Boyle EA, Li YI, and Pritchard JK (2017a). An Expanded View of Complex Traits: From Polygenic to Omnigenic. Cell 160, 1177– 1186. PMC5536862 28622505
  7. Bulik-Sullivan B, Finucane HK, Anttila V, Gusev A, Day FR, Loh P-R, Duncan L, Perry JR, Patterson N, Robinson EB,; ReproGen Consortium; Psychiatric Genomics Consortium; Genetic Consortium for Anorexia Nervosa of the WellcomeTrust Case Control Consortium 3 (2015). An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236– 1241. 26414676 PMC4797329
  8. Chen H, Wu C-I, and He X (2017). The genotype-phenotype relationships in the light of natural selection. Mol. Biol. Evol. 35, 525– 542. PMC5850688 29136190
  9. Chick JM, Munger SC, Simecek P, Huttlin EL, Choi K, Gatti DM, Raghupathy N, Svenson KL, Churchill GA, and Gygi SP (2016). Defining the consequences of genetic variation on a proteome-wide scale. Nature 534, 500– 505. 27309819 PMC5292866
  10. Chun S, Casparino A, Patsopoulos NA, Croteau-Chonka DC, Raby BA, De Jager PL, Sunyaev SR, and Cotsapas C (2017). Limited statistical evidence for shared genetic effects of eQTLs and autoimmune-disease-associated loci in three major immune-cell types. Nat. Genet. 49, 600– 605. 28218759 PMC5374036
  11. Claussnitzer M, Dankel SN, Kim KH, Quon G, Meuleman W, Haugen C, Glunk V, Sousa IS, Beaudry JL, Puviindran V, (2015). FTO Obesity Variant Circuitry and Adipocyte Browning in Humans. N. Engl. J. Med. 373, 895– 907. 26287746 PMC4959911
  12. Clément K, Vaisse C, Lahlou N, Cabrol S, Pelloux V, Cassuto D, Gourmelen M, Dina C, Chambaz J, Lacorte J-M, (1998). Amutation in the human leptin receptor gene causes obesity and pituitary dysfunction. Nature 392, 398– 401. 9537324
  13. Dron JS, and Hegele RA (2016). Genetics of lipid and lipoprotein disorders and traits. Curr. Genet. Med. Rep. 4, 130– 141. 28286704 PMC5325854
  14. Emilsson V, Ilkov M, Lamb JR, Finkel N, Gudmundsson EF, Pitts R, Hoover H, Gudmundsdottir V, Horman SR, Aspelund T, (2018). Co-regulatory networks of human serum proteins link genetics to disease. Science 361, 769– 773. 30072576 PMC6190714
  15. Evans DM, and Davey Smith G (2015). Mendelian randomization: new applications in the coming age of hypothesis-free causality. Annu. Rev. Genomics Hum. Genet. 16, 327– 350. 25939054
  16. Fernandez-Tajes J, Gaulton KJ, van de Bunt M, Torres J, Mahajan A, Gloyn AL, Lage K, and McCarthy MI (2018). Developing a network view of type 2 diabetes risk pathways through integration of genetic, genomic and functional data. bioRxiv. 10.1101/350181. PMC6436236 30914061 · DOI
  17. Finucane HK, Bulik-Sullivan B, Gusev A, Trynka G, Reshef Y, Loh P-R, Anttila V, Xu H, Zang C, Farh K,; ReproGen Consortium; Schizophrenia Working Group of the Psychiatric Genomics Consortium; RACI Consortium (2015). Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat. Genet. 47, 1228– 1235. 26414678 PMC4626285
  18. Fisher RA (1918). The correlation between relatives on the supposition of Mendelian inheritance. Transactions of the Royal Society of Edinburgh 52, 399– 433.
  19. Fromer M, Pocklington AJ, Kavanagh DH, Williams HJ, Dwyer S, Gormley P, Georgieva L, Rees E, Palta P, Ruderfer DM, (2014). De novo mutations in schizophrenia implicate synaptic networks. Nature 506, 179– 184. 24463507 PMC4237002
  20. Fuchsberger C, Flannick J, Teslovich TM, Mahajan A, Agarwala V, Gaulton KJ, Ma C, Fontanillas P, Moutsianas L, McCarthy DJ, (2016). The genetic architecture of type 2 diabetes. Nature 536, 41– 47. 27398621 PMC5034897
  21. Gamazon ER, Wheeler HE, Shah KP, Mozaffari SV, Aquino-Michaels K, Carroll RJ, Eyler AE, Denny JC, Nicolae DL, Cox NJ, and Im HK; GTEx Consortium (2015). Agene-based association method for mapping traits using reference transcriptome data. Nat. Genet. 47, 1091– 1098. 26258848 PMC4552594
  22. Glassberg EC, Gao Z, Harpak A, Lan X, and Pritchard JK (2019). Evidence for Weak Selective Constraint on Human Gene Expression. Genetics 211, 757– 772. 30554168 PMC6366908
  23. Goldinger A, Henders AK, McRae AF, Martin NG, Gibson G, Montgomery GW, Visscher PM, and Powell JE (2013). Genetic and non-genetic variation revealed for the principal components of human gene expression. Genetics 195, 1117– 1128. 24026092 PMC3813841
  24. Gusev A, Ko A, Shi H, Bhatia G, Chung W, Penninx BW, Jansen R, de Geus EJ, Boomsma DI, Wright FA, (2016). Integrative approaches for large-scale transcriptome-wide association studies. Nat. Genet. 48, 245– 252. 26854917 PMC4767558
  25. Hoffmann TJ, Theusch E, Haldar T, Ranatunga DK, Jorgenson E, Medina MW, Kvale MN, Kwok P-Y, Schaefer C, Krauss RM, (2018). A large electronic-health-record-based genome-wide study of serum lipids. Nat. Genet. 50, 401– 413. 29507422 PMC5942247
  26. Jaitin DA, Weiner A, Yofe I, Lara-Astiaso D, Keren-Shaul H, David E, Salame TM, Tanay A, van Oudenaarden A, and Amit I (2016). Dissecting immune circuits by linking CRISPR-pooled screens with single-cell RNA-seq. Cell 167, 1883– 1896. e15. 27984734
  27. Jones SE, Lane JM, Wood AR, van Hees VT, Tyrrell J, Beaumont RN, Jeffries AR, Dashti HS, Hillsdon M, Ruth KS, (2019). Genome-wide association analyses of chronotype in 697,828 individuals provides insights into circadian rhythms. Nat. Commun. 10, 343. 30696823 PMC6351539
  28. Jostins L, Ripke S, Weersma RK, Duerr RH, McGovern DP, Hui KY, Lee JC, Schumm LP, Sharma Y, Anderson CA,; International IBD Genetics Consortium (IIBDGC) (2012). Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 491, 119– 124. 23128233 PMC3491803
  29. Kramer NJ, Haney MS, Morgens DW, Jovičić A, Couthouis J, Li A, Ousey J, Ma R, Bieri G, Tsui CK, (2018). CRISPR-Cas9 screens in human cells and primary neurons identify modifiers of C9ORF72 dipeptide-repeat-protein toxicity. Nat. Genet. 50, 603– 612. 29507424 PMC5893388
  30. Liao Y, Smyth GK, and Shi W (2014). featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923– 930. 24227677
  31. Liu X, Finucane HK, Gusev A, Bhatia G, Gazal S, O’Connor L, Bulik-Sullivan B, Wright FA, Sullivan PF, Neale BM, and Price AL (2017). Functional architectures of local and distal regulation of gene expression in multiple human tissues. Am. J. Hum. Genet. 100, 605– 616. 28343628 PMC5384099
  32. Lu X, Peloso GM, Liu DJ, Wu Y, Zhang H, Zhou W, Li J, Tang CS, Dorajoo R, Li H,; GLGC Consortium (2017). Exome chip meta-analysis identifies novel loci and East Asian-specific coding variants that contribute to lipid levels and coronary artery disease. Nat. Genet. 49, 1722– 1730. 29083407 PMC5899829
  33. Lukowski SW, Lloyd-Jones LR, Holloway A, Kirsten H, Hemani G, Yang J, Small K, Zhao J, Metspalu A, Dermitzakis ET, (2017). Genetic correlations reveal the shared genetic architecture of transcription in human peripheral blood. Nat. Commun. 8, 483. 28883458 PMC5589780
  34. Natarajan P, Peloso GM, Zekavat SM, Montasser M, Ganna A, Chaffin M, Khera AV, Zhou W, Bloom JM, Engreitz JM,; NHLBI TOPMed Lipids Working Group (2018). Deep-coverage whole genome sequences and blood lipids among 16,324 individuals. Nat. Commun. 9, 3391. 30140000 PMC6107638
  35. Parnas O, Jovanovic M, Eisenhaure TM, Herbst RH, Dixit A, Ye CJ, Przybylski D, Platt RJ, Tirosh I, Sanjana NE, (2015). A genomewide CRISPR screen in primary immune cells to dissect regulatory networks. Cell 162, 675– 686. 26189680 PMC4522370
  36. Petretto E, Mangion J, Dickens NJ, Cook SA, Kumaran MK, Lu H, Fischer J, Maatz H, Kren V, Pravenec M, (2006). Heritability and tissue specificity of expression quantitative trait loci. PLoS Genet. 2, e172. 17054398 PMC1617131
  37. Pickrell JK (2014). Joint analysis of functional genomic data and genomewide association studies of 18 human traits. Am. J. Hum. Genet. 94, 559– 573. 24702953 PMC3980523
  38. Pickrell JK, Berisa T, Liu JZ, Segurel L, Tung JY, and Hinds DA (2016). Detection and interpretation of shared genetic influences on 42 human traits. Nat. Genet. 48, 709– 717. 27182965 PMC5207801
  39. Price AL, Patterson N, Hancks DC, Myers S, Reich D, Cheung VG, and Spielman RS (2008). Effects of cis and trans genetic ancestry on gene expression in African Americans. PLoS Genet. 4, e1000294. 19057673 PMC2586034
  40. Price AL, Helgason A, Thorleifsson G, McCarroll SA, Kong A, and Stefansson K (2011). Single-tissue and cross-tissue heritability of gene expression via identity-by-descent in related or unrelated individuals. PLoS Genet. 7, e1001317. 21383966 PMC3044684
  41. Purcell SM, Moran JL, Fromer M, Ruderfer D, Solovieff N, Roussos P, O’Dushlaine C, Chambert K, Bergen SE, Kähler A, (2014). A polygenic burden of rare disruptive mutations in schizophrenia. Nature 506, 185– 190. 24463508 PMC4136494
  42. Reshef YA, Finucane HK, Kelley DR, Gusev A, Kotliar D, Ulirsch JC, Hormozdiari F, Nasser J, O’Connor L, van deGeijn B, (2018). Detecting genome-wide directional effects of transcription factor binding on polygenic disease risk. Nat. Genet. 50, 1483– 1493. 30177862 PMC6202062
  43. Rivas MA, Beaudoin M, Gardet A, Stevens C, Sharma Y, Zhang CK, Boucher G, Ripke S, Ellinghaus D, Burtt N,; National Institute of Diabetes and Digestive Kidney Diseases Inflammatory Bowel Disease Genetics Consortium (NIDDK IBDGC); United Kingdom Inflammatory Bowel Disease Genetics Consortium; International Inflammatory Bowel Disease Genetics Consortium (2011). Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease. Nat. Genet. 43, 1066– 1073. 21983784 PMC3378381
  44. Ruben MD, Wu G, Smith DF, Schmidt RE, Francey LJ, Anafi RC, and Hogenesch JB (2018). A population-based human enCYCLOPedia for circadian medicine. bioRxiv 10.1101/301580. · DOI
  45. Sekar A, Bialas AR, de Rivera H, Davis A, Hammond TR, Kamitaki N, Tooley K, Presumey J, Baum M, Van Doren V,; Schizophrenia Working Group of the Psychiatric Genomics Consortium (2016). Schizophrenia risk from complex variation of complement component 4. Nature 530, 177– 183. 26814963 PMC4752392
  46. Shi H, Kichaev G, and Pasaniuc B (2016). Contrasting the genetic architecture of 30 complex traits from summary association data. Am. J. Hum. Genet. 99, 139– 153. 27346688 PMC5005444
  47. Shi H, Mancuso N, Spendlove S, and Pasaniuc B (2017). Local genetic correlation gives insights into the shared genetic architecture of complex traits. Am. J. Hum. Genet. 101, 737– 751. 29100087 PMC5673668
  48. Simons YB, Bullaughey K, Hudson RR, and Sella G (2018). A population genetic interpretation of GWAS findings for human quantitative traits. PLoS Biol. 16, e2002985. 29547617 PMC5871013
  49. Sivakumaran S, Agakov F, Theodoratou E, Prendergast JG, Zgaga L, Manolio T, Rudan I, McKeigue P, Wilson JF, and Campbell H (2011). Abundant pleiotropy in human complex diseases and traits. Am. J. Hum. Genet. 89, 607– 618. 22077970 PMC3213397
  50. Small KS, Todorčević M, Civelek M, El-Sayed Moustafa JS, Wang X, Simon MM, Fernandez-Tajes J, Mahajan A, Horikoshi M, Hugill A, (2018). Regulatory variants at KLF14 influence type 2 diabetes risk via a female-specific effect on adipocyte size and body composition. Nat. Genet. 50, 572– 580. 29632379 PMC5935235
  51. Smemo S, Tena JJ, Kim K-H, Gamazon ER, Sakabe NJ, Gómez-Marín C, Aneas I, Credidio FL, Sobreira DR, Wasserman NF, (2014). Obesity-associated variants within FTO form long-range functional connections with IRX3. Nature 507, 371– 375. 24646999 PMC4113484
  52. Sun BB, Maranville JC, Peters JE, Stacey D, Staley JR, Blackshaw J, Burgess S, Jiang T, Paige E, Surendran P, (2018). Genomic atlas of the human plasma proteome. Nature 558, 73– 79. 29875488 PMC6697541
  53. Takahashi JS (2017). Transcriptional architecture of the mammalian circadian clock. Nat. Rev. Genet. 18, 164– 179. 27990019 PMC5501165
  54. Torkamani A, Wineinger NE, and Topol EJ (2018). The personal and clinical utility of polygenic risk scores. Nat. Rev. Genet. 19, 581– 590. 29789686
  55. Trynka G, Sandor C, Han B, Xu H, Stranger BE, Liu XS, and Raychaudhuri S (2013). Chromatin marks identify critical cell types for fine mapping complex trait variants. Nat. Genet. 45, 124– 130. 23263488 PMC3826950
  56. Võsa U, Claringbould A, Westra H-J, Bonder MJ, Deelen P, Zeng B, Kirsten H, Saha A, Kreuzhuber R, Kasela S, (2018). Unraveling the polygenic architecture of complex traits using blood eQTL meta-analysis. bioRxiv 10.1101/447367. · DOI · Paper page
  57. Wagner GP, and Zhang J (2011). The pleiotropic structure of the genotype-phenotype map: the evolvability of complex organisms. Nat. Rev. Genet. 12, 204– 213. 21331091
  58. Wellcome Trust Case Control Consortium (2007). Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661– 678. 17554300 PMC2719288
  59. Westra H-J, Peters MJ, Esko T, Yaghootkar H, Schurmann C, Kettunen J, Christiansen MW, Fairfax BP, Schramm K, Powell JE, (2013). Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat. Genet. 45, 1238– 1243. 24013639 PMC3991562
  60. Willer CJ, Schmidt EM, Sengupta S, Peloso GM, Gustafsson S, Kanoni S, Ganna A, Chen J, Buchkovich ML, Mora S,; Global Lipids Genetics Consortium (2013). Discovery and refinement of loci associated with lipid levels. Nat. Genet. 45, 1274– 1283. 24097068 PMC3838666
  61. Wood AR, Esko T, Yang J, Vedantam S, Pers TH, Gustafsson S, Chu AY, Estrada K, Luan J, Kutalik Z,; Electronic Medical Records and Genomics (eMEMERGEGE) Consortium; MIGen Consortium; PAGEGE Consortium; LifeLines Cohort Study (2014). Defining the role of common variation in the genomic and biological architecture of adult human height. Nat. Genet. 46, 1173– 1186. 25282103 PMC4250049
  62. Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, Madden PA, Heath AC, Martin NG, Montgomery GW, (2010). Common SNPs explain a large proportion of the heritability for human height. Nat. Genet. 42, 565– 569. 20562875 PMC3232052
  63. Yang J, Lee SH, Goddard ME, and Visscher PM (2011). GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76– 82. 21167468 PMC3014363
  64. Zhu X, and Stephens M (2018). Large-scale genome-wide enrichment analyses identify new trait-associated genes and pathways across 31 human phenotypes. Nat. Commun. 9, 4361. 30341297 PMC6195536

Cited by

Sorted by citations

Authors
Liu, X., Li, Y. I., & Pritchard, J. K.
Affiliations
  • University of Chicago (US)
  • Howard Hughes Medical Institute (US)
Corresponding author
  • Liu, Xuanyao
  • Li, Yang I.
  • Pritchard, Jonathan K.
Venue
Cell
Publisher
Elsevier BV
Published
2019-05
Volume
177
Issue
4
Pages
1022-1034.e6
ISSN
0092-8674 (ISSN-L)
OpenAlex
W2952835495
Cited by
523
References
16
Citations by year
2026: 45 · 2025: 65 · 2024: 96 · 2023: 62 · 2022: 59 · 2021: 70 · 2020: 87 · 2019: 37 · 2018: 2
FWCI
39.17
Type
journal article
Language
en
Open access
Locations
  • Cell (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • Howard Hughes Medical Institute
  • National Institutes of Health (HG008140, HG009431)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Keywords
trans-eQTL, heritability of gene expression, complex traits, core genes, co-regulation, genetic architecture
MeSH terms
Gene Expression Regulation, Humans, Models, Theoretical, Phenotype, Polymorphism, Genetic, Genetic Variation, Gene Expression, Multifactorial Inheritance, Gene Expression Profiling, Databases, Genetic, Quantitative Trait Loci, Heredity, Genome-Wide Association Study

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review