Genetic effects of sequence-conserved enhancer-like elements on human complex traits.
Data integration
Enhancer
Fine mapping
Gene prioritization
Genome-wide association study
Heritability
Sequence conservation
Tissue specificity
Journal
Genome biology
ISSN: 1474-760X
Titre abrégé: Genome Biol
Pays: England
ID NLM: 100960660
Informations de publication
Date de publication:
02 Jan 2024
02 Jan 2024
Historique:
received:
02
09
2022
accepted:
08
12
2023
medline:
4
1
2024
pubmed:
4
1
2024
entrez:
3
1
2024
Statut:
epublish
Résumé
The vast majority of findings from human genome-wide association studies (GWAS) map to non-coding sequences, complicating their mechanistic interpretations and clinical translations. Non-coding sequences that are evolutionarily conserved and biochemically active could offer clues to the mechanisms underpinning GWAS discoveries. However, genetic effects of such sequences have not been systematically examined across a wide range of human tissues and traits, hampering progress to fully understand regulatory causes of human complex traits. Here we develop a simple yet effective strategy to identify functional elements exhibiting high levels of human-mouse sequence conservation and enhancer-like biochemical activity, which scales well to 313 epigenomic datasets across 106 human tissues and cell types. Combined with 468 GWAS of European (EUR) and East Asian (EAS) ancestries, these elements show tissue-specific enrichments of heritability and causal variants for many traits, which are significantly stronger than enrichments based on enhancers without sequence conservation. These elements also help prioritize candidate genes that are functionally relevant to body mass index (BMI) and schizophrenia but were not reported in previous GWAS with large sample sizes. Our findings provide a comprehensive assessment of how sequence-conserved enhancer-like elements affect complex traits in diverse tissues and demonstrate a generalizable strategy of integrating evolutionary and biochemical data to elucidate human disease genetics.
Sections du résumé
BACKGROUND
BACKGROUND
The vast majority of findings from human genome-wide association studies (GWAS) map to non-coding sequences, complicating their mechanistic interpretations and clinical translations. Non-coding sequences that are evolutionarily conserved and biochemically active could offer clues to the mechanisms underpinning GWAS discoveries. However, genetic effects of such sequences have not been systematically examined across a wide range of human tissues and traits, hampering progress to fully understand regulatory causes of human complex traits.
RESULTS
RESULTS
Here we develop a simple yet effective strategy to identify functional elements exhibiting high levels of human-mouse sequence conservation and enhancer-like biochemical activity, which scales well to 313 epigenomic datasets across 106 human tissues and cell types. Combined with 468 GWAS of European (EUR) and East Asian (EAS) ancestries, these elements show tissue-specific enrichments of heritability and causal variants for many traits, which are significantly stronger than enrichments based on enhancers without sequence conservation. These elements also help prioritize candidate genes that are functionally relevant to body mass index (BMI) and schizophrenia but were not reported in previous GWAS with large sample sizes.
CONCLUSIONS
CONCLUSIONS
Our findings provide a comprehensive assessment of how sequence-conserved enhancer-like elements affect complex traits in diverse tissues and demonstrate a generalizable strategy of integrating evolutionary and biochemical data to elucidate human disease genetics.
Identifiants
pubmed: 38167462
doi: 10.1186/s13059-023-03142-1
pii: 10.1186/s13059-023-03142-1
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1Subventions
Organisme : NIH HHS
ID : P50HG007735
Pays : United States
Organisme : NIH HHS
ID : R01HG010359
Pays : United States
Informations de copyright
© 2023. The Author(s).
Références
Kellis M, Wold B, Snyder MP, Bernstein BE, Kundaje A, Marinov GK, et al. Defining functional DNA elements in the human genome. Proc Natl Acad Sci USA. 2014;111(17):6131–8.
pubmed: 24753594
pmcid: 4035993
doi: 10.1073/pnas.1318948111
Loots GG, Locksley RM, Blankespoor CM, Wang ZE, Miller W, Rubin EM, et al. Identification of a coordinate regulator of interleukins 4, 13, and 5 by cross-species sequence comparisons. Science. 2000;288(5463):136–40.
pubmed: 10753117
doi: 10.1126/science.288.5463.136
Boffelli D, McAuliffe J, Ovcharenko D, Lewis KD, Ovcharenko I, Pachter L, et al. Phylogenetic shadowing of primate sequences to find functional regions of the human genome. Science. 2003;299(5611):1391–4.
pubmed: 12610304
doi: 10.1126/science.1081331
Visel A, Blow MJ, Li Z, Zhang T, Akiyama JA, Holt A, et al. ChIP-seq accurately predicts tissue-specific activity of enhancers. Nature. 2009;457(7231):854–8.
pubmed: 19212405
pmcid: 2745234
doi: 10.1038/nature07730
Creyghton MP, Cheng AW, Welstead GG, Kooistra T, Carey BW, Steine EJ, et al. Histone H3K27ac separates active from poised enhancers and predicts developmental state. Proc Natl Acad Sci USA. 2010;107(50):21931–6.
pubmed: 21106759
pmcid: 3003124
doi: 10.1073/pnas.1016071107
Gasperini M, Tome JM, Shendure J. Towards a comprehensive catalogue of validated and target-linked human enhancers. Nat Rev Genet. 2020;21(5):292–310.
pubmed: 31988385
pmcid: 7845138
doi: 10.1038/s41576-019-0209-0
Lindblad-Toh K, Garber M, Zuk O, Lin MF, Parker BJ, Washietl S, et al. A high-resolution map of human evolutionary constraint using 29 mammals. Nature. 2011;478(7370):476–82.
pubmed: 21993624
pmcid: 3207357
doi: 10.1038/nature10530
Sullivan PF, Meadows JR, Gazal S, Phan BN, Li X, Genereux DP, et al. Leveraging base-pair mammalian constraint to understand genetic variation and human disease. Science. 2023;380(6643):eabn2937.
Moore JE, Purcaro MJ, Pratt HE, Epstein CB, Shoresh N, Adrian J, et al. Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature. 2020;583(7818):699–710.
pubmed: 32728249
pmcid: 7410828
doi: 10.1038/s41586-020-2493-4
Boix CA, James BT, Park YP, Meuleman W, Kellis M. Regulatory genomic circuitry of human disease loci by integrative epigenomics. Nature. 2021;590(7845):300–7.
pubmed: 33536621
pmcid: 7875769
doi: 10.1038/s41586-020-03145-z
Claussnitzer M, Cho JH, Collins R, Cox NJ, Dermitzakis ET, Hurles ME, et al. A brief history of human disease genetics. Nature. 2020;577(7789):179–89.
pubmed: 31915397
pmcid: 7405896
doi: 10.1038/s41586-019-1879-7
Madelaine R, Notwell JH, Skariah G, Halluin C, Chen CC, Bejerano G, et al. A screen for deeply conserved non-coding GWAS SNPs uncovers a MIR-9-2 functional mutation associated to retinal vasculature defects in human. Nucleic Acids Res. 2018;46(7):3517–31.
pubmed: 29518216
pmcid: 5909433
doi: 10.1093/nar/gky166
Finucane HK, Bulik-Sullivan B, Gusev A, Trynka G, Reshef Y, Loh PR, et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat Genet. 2015;47(11):1228–35.
pubmed: 26414678
pmcid: 4626285
doi: 10.1038/ng.3404
Blow MJ, McCulley DJ, Li Z, Zhang T, Akiyama JA, Holt A, et al. ChIP-Seq identification of weakly conserved heart enhancers. Nat Genet. 2010;42(9):806–10.
pubmed: 20729851
pmcid: 3138496
doi: 10.1038/ng.650
Nord AS, Blow MJ, Attanasio C, Akiyama JA, Holt A, Hosseini R, et al. Rapid and pervasive changes in genome-wide enhancer usage during mammalian development. Cell. 2013;155(7):1521–31.
pubmed: 24360275
pmcid: 3989111
doi: 10.1016/j.cell.2013.11.033
Kircher M, Witten DM, Jain P, O’roak BJ, Cooper GM, Shendure J. A general framework for estimating the relative pathogenicity of human genetic variants. Nat Genet. 2014;46(3):310–5.
pubmed: 24487276
pmcid: 3992975
doi: 10.1038/ng.2892
Gulko B, Hubisz MJ, Gronau I, Siepel A. A method for calculating probabilities of fitness consequences for point mutations across the human genome. Nat Genet. 2015;47(3):276–83.
pubmed: 25599402
pmcid: 4342276
doi: 10.1038/ng.3196
Siepel A, Bejerano G, Pedersen JS, Hinrichs AS, Hou M, Rosenbloom K, et al. Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 2005;15(8):1034–50.
pubmed: 16024819
pmcid: 1182216
doi: 10.1101/gr.3715005
Davydov EV, Goode DL, Sirota M, Cooper GM, Sidow A, Batzoglou S. Identifying a high fraction of the human genome to be under selective constraint using GERP++. PLoS Comput Biol. 2010;6(12):e1001025.
pubmed: 21152010
pmcid: 2996323
doi: 10.1371/journal.pcbi.1001025
Short PJ, McRae JF, Gallone G, Sifrim A, Won H, Geschwind DH, et al. De novo mutations in regulatory elements in neurodevelopmental disorders. Nature. 2018;555(7698):611–6.
pubmed: 29562236
pmcid: 5912909
doi: 10.1038/nature25983
Gjoneska E, Pfenning AR, Mathys H, Quon G, Kundaje A, Tsai LH, et al. Conserved epigenomic signals in mice and humans reveal immune basis of Alzheimer’s disease. Nature. 2015;518(7539):365–9.
pubmed: 25693568
pmcid: 4530583
doi: 10.1038/nature14252
Hook PW, McCallion AS. Leveraging mouse chromatin data for heritability enrichment informs common disease architecture and reveals cortical layer contributions to schizophrenia. Genome Res. 2020;30(4):528–39.
pubmed: 32303558
pmcid: 7197474
doi: 10.1101/gr.256578.119
Li YE, Preissl S, Hou X, Zhang Z, Zhang K, Qiu Y, et al. An atlas of gene regulatory elements in adult mouse cerebrum. Nature. 2021;598:129–36.
pubmed: 34616068
pmcid: 8494637
doi: 10.1038/s41586-021-03604-1
Srinivasan C, Phan BN, Lawler AJ, Ramamurthy E, Kleyman M, Brown AR, et al. Addiction-associated genetic variants implicate brain cell type-and region-specific cis-regulatory elements in addiction neurobiology. J Neurosci. 2021;41(43):9008–30.
pubmed: 34462306
pmcid: 8549541
doi: 10.1523/JNEUROSCI.2534-20.2021
Villar D, Berthelot C, Aldridge S, Rayner TF, Lukk M, Pignatelli M, et al. Enhancer evolution across 20 mammalian species. Cell. 2015;160(3):554–66.
pubmed: 25635462
pmcid: 4313353
doi: 10.1016/j.cell.2015.01.006
Hujoel ML, Gazal S, Hormozdiari F, van de Geijn B, Price AL. Disease heritability enrichment of regulatory elements is concentrated in elements with ancient sequence age and conserved function across species. Am J Hum Genet. 2019;104(4):611–24.
pubmed: 30905396
pmcid: 6451699
doi: 10.1016/j.ajhg.2019.02.008
Marnetto D, Mantica F, Molineris I, Grassi E, Pesando I, Provero P. Evolutionary rewiring of human regulatory networks by waves of genome expansion. Am J Hum Genet. 2018;102(2):207–18.
pubmed: 29357977
pmcid: 5985534
doi: 10.1016/j.ajhg.2017.12.014
Hardison RC, Oeltjen J, Miller W. Long human-mouse sequence alignments reveal novel regulatory elements: a reason to sequence the mouse genome. Genome Res. 1997;7(10):959–66.
pubmed: 9331366
doi: 10.1101/gr.7.10.959
Wasserman WW, Palumbo M, Thompson W, Fickett JW, Lawrence CE. Human-mouse genome comparisons to locate regulatory sites. Nat Genet. 2000;26(2):225–8.
pubmed: 11017083
doi: 10.1038/79965
Yue F, Cheng Y, Breschi A, Vierstra J, Wu W, Ryba T, et al. A comparative encyclopedia of DNA elements in the mouse genome. Nature. 2014;515(7527):355–64.
pubmed: 25409824
pmcid: 4266106
doi: 10.1038/nature13992
Thanos D, Maniatis T. Virus induction of human IFN[Formula: see text] gene expression requires the assembly of an enhanceosome. Cell. 1995;83(7):1091–100.
Dao LTM, Galindo-Albarrán AO, Castro-Mondragon JA, Andrieu-Soler C, Medina-Rivera A, Souaid C, et al. Genome-wide characterization of mammalian promoters with distal enhancer functions. Nat Genet. 2017;49(7):1081–90.
doi: 10.1038/ng.3884
Lupo G, Nisi PS, Esteve P, Paul YL, Novo CL, Sidders B, et al. Molecular profiling of aged neural progenitors identifies Dbx2 as a candidate regulator of age-associated neurogenic decline. Aging Cell. 2018;17(3):e12745.
pubmed: 29504228
pmcid: 5946077
doi: 10.1111/acel.12745
[Formula: see text] Genomes Project Consortium. A global reference for human genetic variation. Nature. 2015;526(7571):68–74.
Amariuta T, Ishigaki K, Sugishita H, Ohta T, Koido M, Dey KK, et al. Improving the trans-ancestry portability of polygenic risk scores by prioritizing variants in predicted cell-type-specific regulatory elements. Nat Genet. 2020;52(12):1346–54.
pubmed: 33257898
pmcid: 8049522
doi: 10.1038/s41588-020-00740-8
Poch T, Krause J, Casar C, Liwinski T, Glau L, Kaufmann M, et al. Single-cell atlas of hepatic T cells reveals expansion of liver-resident naive-like CD4+ T cells in primary sclerosing cholangitis. J Hepatol. 2021;75(2):414–23.
pubmed: 33774059
pmcid: 8310924
doi: 10.1016/j.jhep.2021.03.016
Yamanaka Y, Gingery A, Oki G, Yang TH, Zhao C, Amadio PC. Blocking fibrotic signaling in fibroblasts from patients with carpal tunnel syndrome. J Cell Physiol. 2018;233(3):2067–74.
pubmed: 28294324
doi: 10.1002/jcp.25901
Nasser J, Bergman DT, Fulco CP, Guckelberger P, Doughty BR, Patwardhan TA, et al. Genome-wide enhancer maps link risk variants to disease genes. Nature. 2021;593(7858):238–43.
pubmed: 33828297
pmcid: 9153265
doi: 10.1038/s41586-021-03446-x
Zhu X, Duren Z, Wong WH. Modeling regulatory network topology improves genome-wide analyses of complex human traits. Nat Commun. 2021;12(1):2851.
pubmed: 33990562
pmcid: 8121952
doi: 10.1038/s41467-021-22588-0
Yengo L, Sidorenko J, Kemper KE, Zheng Z, Wood AR, Weedon MN, et al. Meta-analysis of genome-wide association studies for height and body mass index in [Formula: see text]700000 individuals of European ancestry. Hum Mol Genet. 2018;27(20):3641–9.
Pardiñas AF, Holmans P, Pocklington AJ, Escott-Price V, Ripke S, Carrera N, et al. Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection. Nat Genet. 2018;50(3):381–9.
pubmed: 29483656
pmcid: 5918692
doi: 10.1038/s41588-018-0059-2
Loos RJ, Yeo GS. The genetics of obesity: from discovery to biology. Nat Rev Genet. 2022;23(2):120–33.
pubmed: 34556834
doi: 10.1038/s41576-021-00414-z
Birnbaum R, Weinberger DR. Genetic insights into the neurodevelopmental origins of schizophrenia. Nat Rev Neurosci. 2017;18(12):727–40.
pubmed: 29070826
doi: 10.1038/nrn.2017.125
Gulyaeva O, Nguyen H, Sambeat A, Heydari K, Sul HS. Sox9-Meis1 inactivation is required for adipogenesis, advancing Pref-1+ to PDGFR[Formula: see text]+ cells. Cell Rep. 2018;25(4):1002–17.
Owa T, Taya S, Miyashita S, Yamashita M, Adachi T, Yamada K, et al. Meis1 coordinates cerebellar granule cell development by regulating Pax6 transcription, BMP signaling and Atoh1 degradation. J Neurosci. 2018;38(5):1277–94.
pubmed: 29317485
pmcid: 6596271
doi: 10.1523/JNEUROSCI.1545-17.2017
Huang J, Huffman JE, Huang Y, Do Valle Í, Assimes TL, Raghavan S, et al. Genomics and phenomics of body mass index reveals a complex disease network. Nat Commun. 2022;13(1):7973.
pubmed: 36581621
pmcid: 9798356
doi: 10.1038/s41467-022-35553-2
Bertrand C, Valet P, Castan-Laurell I. Apelin and energy metabolism. Front Physiol. 2015;6:115.
Castan-Laurell I, Dray C, Attané C, Duparc T, Knauf C, Valet P. Apelin, diabetes, and obesity. Endocrine. 2011;40(1):1–9.
pubmed: 21725702
doi: 10.1007/s12020-011-9507-9
Beanan MJ, Sargent TD. Regulation and function of Dlx3 in vertebrate development. Dev Dyn. 2000;218(4):545–53.
pubmed: 10906774
doi: 10.1002/1097-0177(2000)9999:9999<::AID-DVDY1026>3.0.CO;2-B
Pao PC, Tsai LH. Three decades of Cdk5. J Biomed Sci. 2021;28:79.
pubmed: 34814918
pmcid: 8609871
doi: 10.1186/s12929-021-00774-y
Choi JH, Banks AS, Estall JL, Kajimura S, Boström P, Laznik D, et al. Anti-diabetic drugs inhibit obesity-linked phosphorylation of PPAR[Formula: see text] by Cdk5. Nature. 2010;466(7305):451–6.
Magen D, Ofir A, Berger L, Goldsher D, Eran A, Katib N, et al. Autosomal recessive lissencephaly with cerebellar hypoplasia is associated with a loss-of-function mutation in CDK5. Hum Genet. 2015;134(3):305–14.
pubmed: 25560765
doi: 10.1007/s00439-014-1522-5
Pereira C, Azevedo I, Monteiro R, Martins M. 11[Formula: see text]-Hydroxysteroid dehydrogenase type 1: relevance of its modulation in the pathophysiology of obesity, the metabolic syndrome and type 2 diabetes mellitus. Diabetes Obes Metab. 2012;14(10):869–81.
Masuzaki H, Paterson J, Shinyama H, Morton NM, Mullins JJ, Seckl JR, et al. A transgenic model of visceral obesity and the metabolic syndrome. Science. 2001;294(5549):2166–70.
pubmed: 11739957
doi: 10.1126/science.1066285
Lawson AJ, Walker EA, Lavery GG, Bujalska IJ, Hughes B, Arlt W, et al. Cortisone-reductase deficiency associated with heterozygous mutations in 11[Formula: see text]-hydroxysteroid dehydrogenase type 1. Proc Natl Acad Sci USA. 2011;108(10):4111–6.
Akalestou E, Genser L, Rutter GA. Glucocorticoid metabolism in obesity and following weight loss. Front Endocrinol. 2020;11:59.
doi: 10.3389/fendo.2020.00059
McEvilly RJ, de Diaz MO, Schonemann MD, Hooshmand F, Rosenfeld MG. Transcriptional regulation of cortical neuron migration by POU domain factors. Science. 2002;295(5559):1528–32.
pubmed: 11859196
doi: 10.1126/science.1067132
Kuwahara A, Sakai H, Xu Y, Itoh Y, Hirabayashi Y, Gotoh Y. Tcf3 represses Wnt-[Formula: see text]-catenin signaling and maintains neural stem cell population during neocortical development. PLoS ONE. 2014;9(5): e94408.
Riley P, Anaon-Cartwight L, Cross JC. The Hand1 bHLH transcription factor is essential for placentation and cardiac morphogenesis. Nat Genet. 1998;18(3):271–5.
pubmed: 9500551
doi: 10.1038/ng0398-271
Ursini G, Punzi G, Chen Q, Marenco S, Robinson JF, Porcelli A, et al. Convergence of placenta biology and genetic risk for schizophrenia. Nat Med. 2018;24(6):792–801.
pubmed: 29808008
doi: 10.1038/s41591-018-0021-y
Khandaker GM, Cousins L, Deakin J, Lennox BR, Yolken R, Jones PB. Inflammation and immunity in schizophrenia: implications for pathophysiology and treatment. Lancet Psychiatry. 2015;2(3):258–70.
pubmed: 26359903
pmcid: 4595998
doi: 10.1016/S2215-0366(14)00122-9
Splawski I, Timothy KW, Sharpe LM, Decher N, Kumar P, Bloise R, et al. CaV1.2 calcium channel dysfunction causes a multisystem disorder including arrhythmia and autism. Cell. 2004;119(1):19–31.
Chen C, Xu Q, Zhang Y, Davies BA, Huang Y, Katzmann DJ, et al. Ciliopathy protein HYLS1 coordinates the biogenesis and signaling of primary cilia by activating the ciliary lipid kinase PIPKI[Formula: see text]. Sci Adv. 2021;7(26):eabe3401.
Liu S, Trupiano MX, Simon J, Guo J, Anton E. The essential role of primary cilia in cerebral cortical development and disorders. Curr Top Dev Biol. 2021;142:99–146.
pubmed: 33706927
pmcid: 8740521
doi: 10.1016/bs.ctdb.2020.11.003
Djenoune L, Berg K, Brueckner M, Yuan S. A change of heart: new roles for cilia in cardiac development and disease. Nat Rev Cardiol. 2022;19:211–27.
pubmed: 34862511
doi: 10.1038/s41569-021-00635-z
Mee L, Honkala H, Kopra O, Vesa J, Finnilä S, Visapää I, et al. Hydrolethalus syndrome is caused by a missense mutation in a novel gene HYLS1. Hum Mol Genet. 2005;14(11):1475–88.
pubmed: 15843405
doi: 10.1093/hmg/ddi157
Matthijs G, Schollen E, Pardon E, Veiga-Da-Cunha M, Jaeken J, Cassiman JJ, et al. Mutations in PMM2, a phosphomannomutase gene on chromosome 16p13 in carbohydrate-deficient glycoprotein type I syndrome (Jaeken syndrome). Nat Genet. 1997;16(1):88–92.
pubmed: 9140401
doi: 10.1038/ng0597-88
Grünewald S. The clinical spectrum of phosphomannomutase 2 deficiency (CDG-Ia). Biochim Biophys Acta - Mol Basis Dis. 2009;1792(9):827–34.
doi: 10.1016/j.bbadis.2009.01.003
Loaeza-Reyes KJ, Zenteno E, Moreno-Rodríguez A, Torres-Rosas R, Argueta-Figueroa L, Salinas-Marín R, et al. An overview of glycosylation and its impact on cardiovascular health and disease. Front Mol Biosci. 2021;8:751637.
pubmed: 34869586
pmcid: 8635159
doi: 10.3389/fmolb.2021.751637
Rebelo AL, Chevalier MT, Russo L, Pandit A. Role and therapeutic implications of protein glycosylation in neuroinflammation. Trends Mol Med. 2022;28(4):270–89.
pubmed: 35120836
doi: 10.1016/j.molmed.2022.01.004
Williams SE, Mealer RG, Scolnick EM, Smoller JW, Cummings RD. Aberrant glycosylation in schizophrenia: a review of 25 years of post-mortem brain studies. Mol Psychiatry. 2020;25(12):3198–207.
pubmed: 32404945
pmcid: 8081047
doi: 10.1038/s41380-020-0761-1
Correll CU, Solmi M, Veronese N, Bortolato B, Rosson S, Santonastaso P, et al. Prevalence, incidence and mortality from cardiovascular disease in patients with pooled and specific severe mental illness: a large-scale meta-analysis of 3,211,768 patients and 113,383,368 controls. World Psychiatry. 2017;16(2):163–80.
pubmed: 28498599
pmcid: 5428179
doi: 10.1002/wps.20420
Trubetskoy V, Pardiñas AF, Qi T, Panagiotaropoulou G, Awasthi S, Bigdeli TB, et al. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature. 2022;604(7906):502–8.
pubmed: 35396580
pmcid: 9392466
doi: 10.1038/s41586-022-04434-5
Sollis E, Mosaku A, Abid A, Buniello A, Cerezo M, Gil L, et al. The NHGRI-EBI GWAS Catalog: knowledgebase and deposition resource. Nucleic Acids Res. 2023;51(D1):D977–85.
pubmed: 36350656
doi: 10.1093/nar/gkac1010
Lin X, Liu Y, Liu S, Zhu X, Wu L, Zhu Y, et al. Nested epistasis enhancer networks for robust genome regulation. Science. 2022;377(6610):1077–85.
pubmed: 35951677
pmcid: 10259245
doi: 10.1126/science.abk3512
Snetkova V, Ypsilanti AR, Akiyama JA, Mannion BJ, Plajzer-Frick I, Novak CS, et al. Ultraconserved enhancer function does not require perfect sequence conservation. Nat Genet. 2021;53(4):521–8.
pubmed: 33782603
pmcid: 8038972
doi: 10.1038/s41588-021-00812-3
Groza T, Gomez FL, Mashhadi HH, Muñoz-Fuentes V, Gunes O, Wilson R, et al. The International Mouse Phenotyping Consortium: comprehensive knockout phenotyping underpinning the study of human disease. Nucleic Acids Res. 2023;51(D1):D1038–45.
pubmed: 36305825
doi: 10.1093/nar/gkac972
Wong ES, Zheng D, Tan SZ, Bower NI, Garside V, Vanwalleghem G, et al. Deep conservation of the enhancer regulatory code in animals. Science. 2020;370(6517):eaax8137.
Kwon SB, Ernst J. Learning a genome-wide score of human-mouse conservation at the functional genomics level. Nat Commun. 2021;12(1):2495.
pubmed: 33941776
pmcid: 8093196
doi: 10.1038/s41467-021-22653-8
Zhang K, Hocker JD, Miller M, Hou X, Chiou J, Poirion OB, et al. A single-cell atlas of chromatin accessibility in the human genome. Cell. 2021;184(24):5985–6001.
pubmed: 34774128
pmcid: 8664161
doi: 10.1016/j.cell.2021.10.024
Bartosovic M, Kabbe M, Castelo-Branco G. Single-cell CUT &Tag profiles histone modifications and transcription factors in complex tissues. Nat Biotechnol. 2021;39(7):825–35.
pubmed: 33846645
pmcid: 7611252
doi: 10.1038/s41587-021-00869-9
Zhu X, Stephens M. Large-scale genome-wide enrichment analyses identify new trait-associated genes and pathways across 31 human phenotypes. Nat Commun. 2018;9(1):4361.
pubmed: 30341297
pmcid: 6195536
doi: 10.1038/s41467-018-06805-x
Ma S, Chen X, Zhu X, Tsao PS, Wong WH. Leveraging cell-type-specific regulatory networks to interpret genetic variants in abdominal aortic aneurysm. Proc Natl Acad Sci USA. 2022;119(1):e2115601119.
pubmed: 34930827
doi: 10.1073/pnas.2115601119
Ramdas S, Judd J, Graham SE, Kanoni S, Wang Y, Surakka I, et al. A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids. Am J Hum Genet. 2022;109(8):1366–87.
pubmed: 35931049
pmcid: 9388392
doi: 10.1016/j.ajhg.2022.06.012
Castelijns B, Baak ML, Geeven G, Vermunt MW, Wiggers CRM, Timpanaro IS, et al. Recently evolved enhancers emerge with high interindividual variability and less frequently associate with disease. Cell Rep. 2020;31(12):107799.
Destici E, Zhu F, Tran S, Preissl S, Farah EN, Zhang Y, et al. Human-gained heart enhancers are associated with species-specific cardiac attributes. Nat Cardiovasc Res. 2022;1(9):830–43.
pubmed: 36817700
pmcid: 9937543
doi: 10.1038/s44161-022-00124-7
Kuhn RM, Haussler D, Kent WJ. The UCSC genome browser and associated tools. Brief Bioinform. 2013;14(2):144–61.
pubmed: 22908213
doi: 10.1093/bib/bbs038
Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26(6):841–2.
pubmed: 20110278
pmcid: 2832824
doi: 10.1093/bioinformatics/btq033
Zhu X. Sequence-conserved enhancer-like elements. Version 1.0.0 https://doi.org/10.5281/zenodo.8317239 .
Zhu X. Sequence-conserved enhancer-like elements. Version 1.0.0 https://github.com/SUwonglab/m2h-ele . Accessed 18 Aug 2022.
Mangiafico SS. rcompanion: functions to support extension education program evaluation. Version 2.4.16 https://CRAN.R-project.org/package=rcompanion/ . Accessed 4 July 2022.
R Core Team. R: a language and environment for statistical computing. Version 4.2.1 https://www.R-project.org/ . Accessed 23 June 2022.
Lumley T. rmeta: Meta-analysis. Version 3.0 https://CRAN.R-project.org/package=rmeta . Accessed 20 Mar 2018.
Therneau TM. deming: Deming, Theil-Sen, Passing-Bablock and total least squares regression. Version 1.4 https://CRAN.R-project.org/package=deming . Accessed 13 Nov 2018.
Benner C, Spencer CC, Havulinna AS, Salomaa V, Ripatti S, Pirinen M. FINEMAP: efficient variable selection using summary data from genome-wide association studies. Bioinformatics. 2016;32(10):1493–501.
pubmed: 26773131
pmcid: 4866522
doi: 10.1093/bioinformatics/btw018
Wang G, Sarkar A, Carbonetto P, Stephens M. A simple new approach to variable selection in regression, with application to genetic fine mapping. J R Stat Soc, B: Stat Methodol. 2020;82(5):1273–300.
doi: 10.1111/rssb.12388
Zhu X, Stephens M. Bayesian large-scale multiple regression with summary statistics from genome-wide association studies. Ann Appl Stat. 2017;11(3):1561.
pubmed: 29399241
pmcid: 5796536
doi: 10.1214/17-AOAS1046
Yang J, Fritsche LG, Zhou X, Abecasis G, International Age-Related Macular Degeneration Genomics Consortium. A scalable Bayesian method for integrating functional information in genome-wide association studies. Am J Hum Genet. 2017;101(3):404–16.
Zhu X. RSS-NET: Regression with Summary Statistics exploiting NEtwork Topology. Version 1.0.1 https://doi.org/10.5281/zenodo.4553387 .
Zhu X. RSS-NET: Regression with Summary Statistics exploiting NEtwork Topology. Version 1.0.1 https://github.com/SUwonglab/rss-net . Accessed 4 Sept 2023.
Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007;447(7145):661–78.
doi: 10.1038/nature05911
Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell. 2010;38(4):576–89.
pubmed: 20513432
pmcid: 2898526
doi: 10.1016/j.molcel.2010.05.004
Duren Z, Chen X, Jiang R, Wang Y, Wong WH. Modeling gene regulation from paired expression and chromatin accessibility data. Proc Natl Acad Sci USA. 2017;114(25):E4914–23.
pubmed: 28576882
pmcid: 5488952
doi: 10.1073/pnas.1704553114
Yousefi S, Deng R, Lanko K, Salsench EM, Nikoncuk A, van der Linde HC, et al. Comprehensive multi-omics integration identifies differentially active enhancers during human brain development with clinical relevance. Genome Med. 2021;13:162.
pubmed: 34663447
pmcid: 8524963
doi: 10.1186/s13073-021-00980-1
Wang D, Liu S, Warrell J, Won H, Shi X, Navarro FC, et al. Comprehensive functional genomic resource and integrative model for the human brain. Science. 2018;362:eaat8464.
Ren B. Positively correlated connections between genes and candidate cis-regulatory elements in adult mouse cerebrum. http://catlas.org/catlas_downloads/mousebrain/conns . Accessed 8 Feb 2022.
Barakat TS. Additional file 6 of “Comprehensive multi-omics integration identifies differentially active enhancers during human brain development with clinical relevance”. https://doi.org/10.6084/m9.figshare.16829164.v1 .
PsychENCODE Consortium. PsychENCODE Integrative Analysis. http://resource.psychencode.org/ . Accessed 8 Feb 2022.
Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10(1):1523.
pubmed: 30944313
pmcid: 6447622
doi: 10.1038/s41467-019-09234-6
Bult CJ, Blake JA, Smith CL, Kadin JA, Richardson JE. Mouse genome database (MGD) 2019. Nucleic Acids Res. 2019;47(D1):D801–6.
pubmed: 30407599
doi: 10.1093/nar/gky1056
Amberger JS, Bocchini CA, Scott AF, Hamosh A. OMIM.org: leveraging knowledge across phenotype-gene relationships. Nucleic Acids Res. 2019;47(D1):D1038–43.
Zhou Y, Zhang Y, Lian X, Li F, Wang C, Zhu F, et al. Therapeutic target database update 2022: facilitating drug discovery with enriched comparative data of targeted agents. Nucleic Acids Res. 2022;50(D1):D1398–407.
pubmed: 34718717
doi: 10.1093/nar/gkab953