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The great hairball gambit


Autoři: Jonathan Flint aff001;  Trey Ideker aff002
Působiště autorů: Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, California, United States of America aff001;  Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, California, United States of America aff002
Vyšlo v časopise: The great hairball gambit. PLoS Genet 15(11): e32767. doi:10.1371/journal.pgen.1008519
Kategorie: Opinion Piece
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1008519


Zdroje

1. Pardinas 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. doi: 10.1038/s41588-018-0059-2 29483656

2. Wray NR, Ripke S, Mattheisen M, Trzaskowski M, Byrne EM, Abdellaoui A, et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet. 2018;50(5):668–81. doi: 10.1038/s41588-018-0090-3 29700475

3. Howard DM, Adams MJ, Clarke T, Hafferty J, Gibson J, Shirali M, et al. Genome-wide meta-analysis of depression in 807,553 individuals identifies 102 independent variants with replication in a further 1,507,153 individuals. Nature Neuroscience. 2018.

4. Grove J, Ripke S, Als TD, Mattheisen M, Walters RK, Won H, et al. Identification of common genetic risk variants for autism spectrum disorder. Nat Genet. 2019;51(3):431–44. doi: 10.1038/s41588-019-0344-8 30804558.

5. Stahl EA, Breen G, Forstner AJ, McQuillin A, Ripke S, Trubetskoy V, et al. Genome-wide association study identifies 30 loci associated with bipolar disorder. Nat Genet. 2019;51(5):793–803. doi: 10.1038/s41588-019-0397-8 31043756.

6. Watson HJ, Yilmaz Z, Thornton LM, Hubel C, Coleman JRI, Gaspar HA, et al. Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa. Nat Genet. 2019. doi: 10.1038/s41588-019-0439-2 31308545.

7. Giurgiu M, Reinhard J, Brauner B, Dunger-Kaltenbach I, Fobo G, Frishman G, et al. CORUM: the comprehensive resource of mammalian protein complexes-2019. Nucleic Acids Res. 2019;47(D1):D559–D63. doi: 10.1093/nar/gky973 30357367

8. Thul PJ, Akesson L, Wiking M, Mahdessian D, Geladaki A, Ait Blal H, et al. A subcellular map of the human proteome. Science. 2017;356(6340). doi: 10.1126/science.aal3321 28495876.

9. Maurano MT, Humbert R, Rynes E, Thurman RE, Haugen E, Wang H, et al. Systematic localization of common disease-associated variation in regulatory DNA. Science. 2012;337(6099):1190–5. Epub 2012/09/08. doi: 10.1126/science.1222794 22955828.

10. Parikshak NN, Luo R, Zhang A, Won H, Lowe JK, Chandran V, et al. Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism. Cell. 2013;155(5):1008–21. Epub 2013/11/26. doi: 10.1016/j.cell.2013.10.031 24267887

11. Wang D, Liu S, Warrell J, Won H, Shi X, Navarro FCP, et al. Comprehensive functional genomic resource and integrative model for the human brain. Science. 2018;362(6420). doi: 10.1126/science.aat8464 30545857.

12. Fromer M, Pocklington AJ, Kavanagh DH, Williams HJ, Dwyer S, Gormley P, et al. De novo mutations in schizophrenia implicate synaptic networks. Nature. 2014;506(7487):179–84. Epub 2014/01/28. doi: 10.1038/nature12929 24463507.

13. Ebert DH, Greenberg ME. Activity-dependent neuronal signalling and autism spectrum disorder. Nature. 2013;493(7432):327–37. doi: 10.1038/nature11860 23325215

14. Willsey AJ, Sanders SJ, Li M, Dong S, Tebbenkamp AT, Muhle RA, et al. Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism. Cell. 2013;155(5):997–1007. doi: 10.1016/j.cell.2013.10.020 24267886

15. Parikshak NN, Gandal MJ, Geschwind DH. Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders. Nat Rev Genet. 2015;16(8):441–58. doi: 10.1038/nrg3934 26149713

16. Lee PH, O’Dushlaine C, Thomas B, Purcell SM. INRICH: interval-based enrichment analysis for genome-wide association studies. Bioinformatics. 2012;28(13):1797–9. doi: 10.1093/bioinformatics/bts191 22513993

17. Wang K, Li M, Bucan M. Pathway-based approaches for analysis of genomewide association studies. Am J Hum Genet. 2007;81(6):1278–83. doi: 10.1086/522374 17966091

18. Holmans P, Green EK, Pahwa JS, Ferreira MA, Purcell SM, Sklar P, et al. Gene ontology analysis of GWA study data sets provides insights into the biology of bipolar disorder. Am J Hum Genet. 2009;85(1):13–24. doi: 10.1016/j.ajhg.2009.05.011 19539887

19. Segre AV, Consortium D, investigators M, Groop L, Mootha VK, Daly MJ, et al. Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits. PLoS Genet. 2010;6(8). doi: 10.1371/journal.pgen.1001058 20714348

20. de Leeuw CA, Mooij JM, Heskes T, Posthuma D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput Biol. 2015;11(4):e1004219. doi: 10.1371/journal.pcbi.1004219 25885710

21. Claussnitzer M, Dankel SN, Kim KH, Quon G, Meuleman W, Haugen C, et al. FTO Obesity Variant Circuitry and Adipocyte Browning in Humans. N Engl J Med. 2015;373(10):895–907. doi: 10.1056/NEJMoa1502214 26287746.

22. Smemo S, Tena JJ, Kim KH, Gamazon ER, Sakabe NJ, Gomez-Marin C, et al. Obesity-associated variants within FTO form long-range functional connections with IRX3. Nature. 2014;507(7492):371–5. Epub 2014/03/22. doi: 10.1038/nature13138 24646999.

23. Lettice LA, Horikoshi T, Heaney SJ, van Baren MJ, van der Linde HC, Breedveld GJ, et al. Disruption of a long-range cis-acting regulator for Shh causes preaxial polydactyly. Proc Natl Acad Sci U S A. 2002;99(11):7548–53. doi: 10.1073/pnas.112212199 12032320.

24. Won H, de la Torre-Ubieta L, Stein JL, Parikshak NN, Huang J, Opland CK, et al. Chromosome conformation elucidates regulatory relationships in developing human brain. Nature. 2016;538(7626):523–7. doi: 10.1038/nature19847 27760116.

25. Huttlin EL, Ting L, Bruckner RJ, Gebreab F, Gygi MP, Szpyt J, et al. The BioPlex Network: A Systematic Exploration of the Human Interactome. Cell. 2015;162(2):425–40. doi: 10.1016/j.cell.2015.06.043 26186194

26. Luck K, Kim D-K, Lambourne L, Spirohn K, Begg BE, Bian W, et al. A reference map of the human protein interactome. bioRxiv. 2019:605451. doi: 10.1101/605451

27. Venkatesan K, Rual JF, Vazquez A, Stelzl U, Lemmens I, Hirozane-Kishikawa T, et al. An empirical framework for binary interactome mapping. Nat Methods. 2009;6(1):83–90. doi: 10.1038/nmeth.1280 19060904

28. Goldstein DB. Common genetic variation and human traits. N Engl J Med. 2009;360(17):1696–8. Epub 2009/04/17. doi: 10.1056/NEJMp0806284 19369660.

29. Boyle EA, Li YI, Pritchard JK. An Expanded View of Complex Traits: From Polygenic to Omnigenic. Cell. 2017;169(7):1177–86. doi: 10.1016/j.cell.2017.05.038 28622505

30. Kramer MH, Farre JC, Mitra K, Yu MK, Ono K, Demchak B, et al. Active Interaction Mapping Reveals the Hierarchical Organization of Autophagy. Mol Cell. 2017;65(4):761–74 e5. doi: 10.1016/j.molcel.2016.12.024 28132844

31. Huang JK, Carlin DE, Yu MK, Zhang W, Kreisberg JF, Tamayo P, et al. Systematic Evaluation of Molecular Networks for Discovery of Disease Genes. Cell Syst. 2018;6(4):484–95 e5. doi: 10.1016/j.cels.2018.03.001 29605183

32. Koopmans F, van Nierop P, Andres-Alonso M, Byrnes A, Cijsouw T, Coba MP, et al. SynGO: An Evidence-Based, Expert-Curated Knowledge Base for the Synapse. Neuron. 2019;103(2):217–34 e4. doi: 10.1016/j.neuron.2019.05.002 31171447

33. Jansen PR, Watanabe K, Stringer S, Skene N, Bryois J, Hammerschlag AR, et al. Genome-wide analysis of insomnia in 1,331,010 individuals identifies new risk loci and functional pathways. Nat Genet. 2019;51(3):394–403. doi: 10.1038/s41588-018-0333-3 30804565.

34. Lee JJ, Wedow R, Okbay A, Kong E, Maghzian O, Zacher M, et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat Genet. 2018;50(8):1112–21. doi: 10.1038/s41588-018-0147-3 30038396.

35. Collins R. What makes UK Biobank special? Lancet. 2012;379(9822):1173–4. doi: 10.1016/S0140-6736(12)60404-8 22463865.

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Genetika Reprodukčná medicína

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PLOS Genetics


2019 Číslo 11
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