{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T09:06:31Z","timestamp":1774947991191,"version":"3.50.1"},"reference-count":74,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T00:00:00Z","timestamp":1774915200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T00:00:00Z","timestamp":1774915200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Federal State Budgetary Institution \u201cCentre for Strategic Planning and Management of Biomedical Health Risks\u201d of the Federal Medical Biological Agency"},{"DOI":"10.13039\/501100012190","name":"Ministry of Science and Higher Education of the Russian Federation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012190","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Federal Medical Biological Agency"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Immunogenetics"],"DOI":"10.1007\/s00251-026-01396-0","type":"journal-article","created":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T06:54:39Z","timestamp":1774940079000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deciphering the genetic control of immune cell function at single-cell resolution: Disease-Specific Cis-eQTLs analysis of COVID-19"],"prefix":"10.1007","volume":"78","author":[{"given":"E. I.","family":"Romanova","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"D. I.","family":"Tychinin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"A. M.","family":"Shaymardanov","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"V. E.","family":"Akimov","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"A. V.","family":"Korobeinikova","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"V. V.","family":"Shiryagin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"N. I.","family":"Guskova","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"V. A.","family":"Astafieva","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"A. S.","family":"Shingaliev","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"O. A.","family":"Antonova","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"L. A.","family":"Golubnikova","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S. I.","family":"Mitrofanov","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"K. S.","family":"Grammatikati","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"V. S.","family":"Yudin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S. M.","family":"Yudin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"A. V.","family":"Makhotenko","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"A. A.","family":"Keskinov","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S. A.","family":"Kraevoy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"E. A.","family":"Snigir","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"P. Yu.","family":"Volchkov","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"D. V.","family":"Svetlichnyy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"V. I.","family":"Skvortsova","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,3,31]]},"reference":[{"key":"1396_CR1","doi-asserted-by":"publisher","first-page":"1273825","DOI":"10.3389\/fnagi.2023.1273825","volume":"15","author":"DA Kashtanova","year":"2023","unstructured":"Kashtanova DA, Mamchur AA, Dzhumaniyazova IH, Ivanov MV, Erema VV, Zelenova EA, Yakovchik AY, Gusakova MS, Rumyantseva AM, Terekhov MV, Matkava LR, Akopyan AA, Strazhesko ID, Yudin VS, Makarov VV, Kraevoy SA, Tkacheva ON, Yudin SM (2023) Cognitive impairment in long-living adults: a genome-wide association study, polygenic risk score model and molecular modeling of the APOE protein. Front Aging Neurosci 15:1273825","journal-title":"Front Aging Neurosci"},{"key":"1396_CR2","doi-asserted-by":"publisher","first-page":"1178939","DOI":"10.3389\/fmed.2023.1178939","volume":"10","author":"MS Gusakova","year":"2023","unstructured":"Gusakova MS, Ivanov MV, Kashtanova DA, Taraskina AN, Erema VV, Mikova VM, Loshkarev RI, Ignatyeva OA, Akinshina AI, Mitrofanov SI, Snigir EA, Yudin VS, Makarov VV, Keskinov AA, Yudin SM (2023) GWAS reveals genetic basis of a predisposition to severe COVID-19 through in silico modeling of the FYCO1 protein. Front Med 10:1178939","journal-title":"Front Med"},{"key":"1396_CR3","doi-asserted-by":"crossref","unstructured":"Keaton, J.M., Kamali, Z., Xie, T., Vaez, A., Williams, A., Goleva, S.B., Ani, A., Evangelou, E., Hellwege, J.N., Yengo, L., Young, W.J., Traylor, M., Giri, A., Zheng, Z., Zeng, J., Chasman, D.I., Morris, A.P., Caulfield, M.J., Hwang, S.-J., Kooner, J.S., Conen, D., Attia, J.R., Morrison, A.C., Loos, R.J.F., Kristiansson, K., Schmidt, R., Hicks, A.A., Pramstaller, P.P., Nelson, C.P., Samani, N.J., Risch, L., Gyllensten, U., Melander, O., Riese, H., Wilson, J.F., Campbell, H., Rich, S.S., Psaty, B.M., Lu, Y., Rotter, J.I., Guo, X., Rice, K.M., Vollenweider, P., Sundstr\u00f6m, J., Langenberg, C., Tobin, M.D., Giedraitis, V., Luan, J., Tuomilehto, J., Kutalik, Z., Ripatti, S., Salomaa, V., Girotto, G., Trompet, S., Jukema, J.W., Harst, P., Ridker, P.M., Giulianini, F., Vitart, V., Goel, A., Watkins, H., Harris, S.E., Deary, I.J., Most, P.J., Oldehinkel, A.J., Keavney, B.D., Hayward, C., Campbell, A., Boehnke, M., Scott, L.J., Boutin, T., Mamasoula, C., J\u00e4rvelin, M.-R., Peters, A., Gieger, C., Lakatta, E.G., Cucca, F., Hui, J., Knekt, P., Enroth, S., De Borst, M.H., Pola\u0161ek, O., Concas, M.P., Catamo, E., Cocca, M., Li-Gao, R., Hofer, E., Schmidt, H., Spedicati, B., Waldenberger, M., Strachan, D.P., Laan, M., Teumer, A., D\u00f6rr, M., Gudnason, V., Cook, J.P., Ruggiero, D., Kolcic, I., Boerwinkle, E., Traglia, M., Lehtim\u00e4ki, T., Raitakari, O.T., Johnson, A.D., Newton-Cheh, C., Brown, M.J., Dominiczak, A.F., Sever, P.J., Poulter, N., Chambers, J.C., Elosua, R., Siscovick, D., Esko, T., Metspalu, A., Strawbridge, R.J., Laakso, M., Hamsten, A., Hottenga, J.-J., Geus, E., Morris, A.D., Palmer, C.N.A., Nolte, I.M., Milaneschi, Y., Marten, J., Wright, A., Zeggini, E., Howson, J.M.M., O\u2019Donnell, C.J., Spector, T., Nalls, M.A., Simonsick, E.M., Liu, Y., Duijn, C.M., Butterworth, A.S., Danesh, J.N., Menni, C., Wareham, N.J., Khaw, K.-T., Sun, Y.V., Wilson, P.W.F., Cho, K., Visscher, P.M., Denny, J.C., Million Veteran Program, Lifelines Cohort Study, CHARGE consortium, ICBP Consortium, Levy, D., Edwards, T.L., Munroe, P.B., Snieder, H., Warren, H.R.: Genome-wide analysis in over 1 million individuals of european ancestry yields improved polygenic risk scores for blood pressure traits. Nat. Genet. 56(5), 778\u2013791 (2024)","DOI":"10.1038\/s41588-024-01714-w"},{"key":"1396_CR4","doi-asserted-by":"publisher","first-page":"1182579","DOI":"10.3389\/fgene.2023.1182579","volume":"14","author":"J Luo","year":"2023","unstructured":"Luo J, Wu X, Cheng Y, Chen G, Wang J, Song X (2023) Expression quantitative trait locus studies in the era of single-cell omics. Front Genet 14:1182579","journal-title":"Front Genet"},{"key":"1396_CR5","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2021.591122","volume":"15","author":"A Adil","year":"2021","unstructured":"Adil A, Kumar V, Jan AT, Asger M (2021) Single-Cell transcriptomics: Current methods and challenges in data acquisition and analysis. Front Neurosci 15:591122","journal-title":"Front Neurosci"},{"key":"1396_CR6","doi-asserted-by":"crossref","unstructured":"Zhernakova DV, Deelen P, Vermaat M, Iterson M, Galen M, Arindrarto W, Hof P, Mei H, Dijk F, Westra H-J, Bonder MJ, Rooij J, Verkerk M, Jhamai PM, Moed M, Kielbasa SM, Bot J, Nooren I, Pool R, Dongen J, Hottenga JJ, Stehouwer CDA, Kallen CJH, Schalkwijk CG, Zhernakova A, Li Y, Tigchelaar EF, Klein N, Beekman M, Deelen J, Heemst D, Berg LH, Hofman A, Uitterlinden AG, Greevenbroek MMJ, Veldink JH, Boomsma DI, Duijn CM, Wijmenga C, Slagboom PE, Swertz MA, Isaacs A, Meurs JBJ, Jansen R, Heijmans BT, Hoen PAC, Franke L (2017) Identification of context-dependent expression quantitative trait loci in whole blood. Nat Genet 49(1):139\u2013145","DOI":"10.1038\/ng.3737"},{"key":"1396_CR7","doi-asserted-by":"crossref","unstructured":"Magnusson, R., Tegn\u00e9r, J.N., Gustafsson, M.: Deep neural network prediction of genome-wide transcriptome signatures - beyond the black-box. npj Systems Biology and Applications 8(1), 1\u20138 (2022)","DOI":"10.1038\/s41540-022-00218-9"},{"issue":"8","key":"1396_CR8","doi-asserted-by":"publisher","first-page":"955","DOI":"10.1038\/ng.3331","volume":"47","author":"D Lee","year":"2015","unstructured":"Lee D, Gorkin DU, Baker M, Strober BJ, Asoni AL, McCallion AS, Beer MA (2015) A method to predict the impact of regulatory variants from DNA sequence. Nat Genet 47(8):955\u2013961","journal-title":"Nat Genet"},{"issue":"7","key":"1396_CR9","doi-asserted-by":"publisher","first-page":"990","DOI":"10.1101\/gr.200535.115","volume":"26","author":"DR Kelley","year":"2016","unstructured":"Kelley DR, Snoek J, Rinn JL (2016) Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks. Genome Res 26(7):990\u2013999","journal-title":"Genome Res"},{"issue":"10","key":"1396_CR10","doi-asserted-by":"publisher","first-page":"931","DOI":"10.1038\/nmeth.3547","volume":"12","author":"J Zhou","year":"2015","unstructured":"Zhou J, Troyanskaya OG (2015) Predicting effects of noncoding variants with deep learning-based sequence model. Nat Methods 12(10):931\u2013934","journal-title":"Nat Methods"},{"issue":"8","key":"1396_CR11","doi-asserted-by":"publisher","first-page":"1171","DOI":"10.1038\/s41588-018-0160-6","volume":"50","author":"J Zhou","year":"2018","unstructured":"Zhou J, Theesfeld CL, Yao K, Chen KM, Wong AK, Troyanskaya OG (2018) Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk. Nat Genet 50(8):1171\u20131179","journal-title":"Nat Genet"},{"issue":"11","key":"1396_CR12","doi-asserted-by":"publisher","first-page":"1004590","DOI":"10.1371\/journal.pcbi.1004590","volume":"11","author":"D Svetlichnyy","year":"2015","unstructured":"Svetlichnyy D, Imrichova H, Fiers M, Kalender Atak Z, Aerts S (2015) Identification of High-Impact cis-regulatory mutations using transcription factor specific random forest models. PLoS Comput Biol 11(11):1004590","journal-title":"PLoS Comput Biol"},{"issue":"7","key":"1396_CR13","doi-asserted-by":"publisher","first-page":"940","DOI":"10.1038\/s41588-022-01102-2","volume":"54","author":"KM Chen","year":"2022","unstructured":"Chen KM, Wong AK, Troyanskaya OG, Zhou J (2022) A sequence-based global map of regulatory activity for deciphering human genetics. Nat Genet 54(7):940\u2013949","journal-title":"Nat Genet"},{"issue":"11","key":"1396_CR14","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1093\/nar\/gkw226","volume":"44","author":"D Quang","year":"2016","unstructured":"Quang D, Xie X (2016) DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences. Nucleic Acids Res 44(11):107","journal-title":"Nucleic Acids Res"},{"issue":"19","key":"1396_CR15","doi-asserted-by":"publisher","first-page":"2950","DOI":"10.3390\/cells11192950","volume":"11","author":"AM Shaymardanov","year":"2022","unstructured":"Shaymardanov AM, Antonova OA, Sokol AD, Deinichenko KA, Kazakova PG, Milovanov MM, Zakubansky AV, Akinshina AI, Tsypkina AV, Romanova SV, Muhin VE, Mitrofanov SI, Yudin VS, Yudin SM, Makhotenko AV, Keskinov AA, Kraevoy SA, Snigir EA, Svetlichnyy DV, Skvortsova VI (2022) Single-Cell gene expression analysis revealed immune cell signatures of delta COVID-19. Cells 11(19):2950","journal-title":"Cells"},{"key":"1396_CR16","doi-asserted-by":"crossref","unstructured":"Korsunsky, I., Millard, N., Fan, J., Slowikowski, K., Zhang, F., Wei, K., Baglaenko, Y., Brenner, M., Loh, P.R., Raychaudhuri, S.: Fast, sensitive and accurate integration of single-cell data with harmony. Nat. Methods 16(12) (2019)","DOI":"10.1038\/s41592-019-0619-0"},{"issue":"5","key":"1396_CR17","doi-asserted-by":"publisher","first-page":"555","DOI":"10.1038\/s41587-019-0054-x","volume":"37","author":"P Krusche","year":"2019","unstructured":"Krusche P, Trigg L, Boutros PC, Mason CE, De La Vega FM, Moore BL, Gonzalez-Porta M, Eberle MA, Tezak Z, Lababidi S, Truty R, Asimenos G, Funke B, Fleharty M, Chapman BA, Salit M, Zook JM (2019) Global Alliance for Genomics and Health Benchmarking Team: Best practices for benchmarking germline small-variant calls in human genomes. Nat Biotechnol 37(5):555\u2013560","journal-title":"Nat Biotechnol"},{"issue":"5","key":"1396_CR18","doi-asserted-by":"publisher","first-page":"867","DOI":"10.1093\/bioinformatics\/btx699","volume":"34","author":"BS Pedersen","year":"2018","unstructured":"Pedersen BS, Quinlan AR (2018) Mosdepth: quick coverage calculation for genomes and exomes. Bioinformatics 34(5):867\u2013868","journal-title":"Bioinformatics"},{"issue":"8","key":"1396_CR19","doi-asserted-by":"publisher","first-page":"591","DOI":"10.1038\/s41592-018-0051-x","volume":"15","author":"S Kim","year":"2018","unstructured":"Kim S, Scheffler K, Halpern AL, Bekritsky MA, Noh E, K\u00e4llberg M, Chen X, Kim Y, Beyter D, Krusche P, Saunders CT (2018) Strelka2: fast and accurate calling of germline and somatic variants. Nat Methods 15(8):591\u2013594","journal-title":"Nat Methods"},{"key":"1396_CR20","doi-asserted-by":"crossref","unstructured":"Yu, G., Wang, L.G., He, Q.Y.: ChIPseeker: an R\/Bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics 31(14) (2015)","DOI":"10.1093\/bioinformatics\/btv145"},{"issue":"10","key":"1396_CR21","doi-asserted-by":"publisher","first-page":"1353","DOI":"10.1093\/bioinformatics\/bts163","volume":"28","author":"AA Shabalin","year":"2012","unstructured":"Shabalin AA (2012) Matrix eQTL: ultra fast eQTL analysis via large matrix operations. Bioinformatics 28(10):1353\u20131358","journal-title":"Bioinformatics"},{"key":"1396_CR22","doi-asserted-by":"crossref","unstructured":"Durinck, S., Spellman, P.T., Birney, E., Huber, W.: Mapping identifiers for the integration of genomic datasets with the R\/Bioconductor package biomart. Nat. Protoc. 4(8) (2009)","DOI":"10.1038\/nprot.2009.97"},{"issue":"16","key":"1396_CR23","doi-asserted-by":"publisher","first-page":"2046","DOI":"10.1093\/bioinformatics\/btt343","volume":"29","author":"A Heger","year":"2013","unstructured":"Heger A, Webber C, Goodson M, Ponting CP, Lunter G (2013) GAT: a simulation framework for testing the association of genomic intervals. Bioinformatics 29(16):2046\u20132048","journal-title":"Bioinformatics"},{"issue":"1","key":"1396_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13059-021-02572-z","volume":"23","author":"H Vu","year":"2022","unstructured":"Vu H, Ernst J (2022) Universal annotation of the human genome through integration of over a thousand epigenomic datasets. Genome Biol 23(1):1\u201337","journal-title":"Genome Biol"},{"issue":"17","key":"1396_CR25","doi-asserted-by":"publisher","first-page":"9823","DOI":"10.1093\/nar\/gkx659","volume":"45","author":"Y Zhang","year":"2017","unstructured":"Zhang Y, Hardison RC (2017) Accurate and reproducible functional maps in 127 human cell types via 2D genome segmentation. Nucleic Acids Res 45(17):9823","journal-title":"Nucleic Acids Res"},{"key":"1396_CR26","unstructured":"Burdett, T., Hastings, E., Welter, D., SPOT, EMBL-EBI, NHGRI: GWAS Catalog. https:\/\/www.ebi.ac.uk\/gwas\/efotraits\/MONDO_0100096. Accessed: 2024-9-23"},{"key":"1396_CR27","doi-asserted-by":"crossref","unstructured":"Szklarczyk, D., Kirsch, R., Koutrouli, M., Nastou, K., Mehryary, F., Hachilif, R., Gable, A.L., Fang, T., Doncheva, N.T., Pyysalo, S., Bork, P., Jensen, L.J., Mering, C.: The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 51(D1) (2023)","DOI":"10.1093\/nar\/gkac1000"},{"issue":"5","key":"1396_CR28","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1038\/nbt.4096","volume":"36","author":"A Butler","year":"2018","unstructured":"Butler A, Hoffman P, Smibert P, Papalexi E, Satija R (2018) Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat Biotechnol 36(5):411\u2013420","journal-title":"Nat Biotechnol"},{"issue":"5","key":"1396_CR29","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1089\/omi.2011.0118","volume":"16","author":"G Yu","year":"2012","unstructured":"Yu G, Wang L-G, Han Y, He Q-Y (2012) clusterprofiler: an R package for comparing biological themes among gene clusters. OMICS 16(5):284","journal-title":"OMICS"},{"issue":"8","key":"1396_CR30","doi-asserted-by":"publisher","first-page":"1211","DOI":"10.1093\/bioinformatics\/btv735","volume":"32","author":"T-P Chiu","year":"2016","unstructured":"Chiu T-P, Comoglio F, Zhou T, Yang L, Paro R, Rohs R (2016) DNAshapeR: an R\/Bioconductor package for DNA shape prediction and feature encoding. Bioinformatics 32(8):1211","journal-title":"Bioinformatics"},{"issue":"4","key":"1396_CR31","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1038\/s41592-019-0360-8","volume":"16","author":"KM Chen","year":"2019","unstructured":"Chen KM, Cofer EM, Zhou J, Troyanskaya OG (2019) Selene: a PyTorch-based deep learning library for sequence data. Nat Methods 16(4):315\u2013318","journal-title":"Nat Methods"},{"issue":"2","key":"1396_CR32","doi-asserted-by":"publisher","first-page":"396","DOI":"10.4049\/jimmunol.2100581","volume":"208","author":"X Wang","year":"2022","unstructured":"Wang X, Shen X, Chen S, Liu H, Hong N, Zhong H, Chen X, Jin W (2022) Reinvestigation of classic T cell subsets and identification of novel cell subpopulations by Single-Cell RNA sequencing. J Immunol 208(2):396\u2013406","journal-title":"J Immunol"},{"issue":"4","key":"1396_CR33","doi-asserted-by":"publisher","first-page":"775","DOI":"10.1016\/j.cell.2018.11.043","volume":"176","author":"H Li","year":"2019","unstructured":"Li H, Leun AM, Yofe I, Lubling Y, Gelbard-Solodkin D, Akkooi ACJ, Braber M, Rozeman EA, Haanen JBAG, Blank CU, Horlings HM, David E, Baran Y, Bercovich A, Lifshitz A, Schumacher TN, Tanay A, Amit I (2019) Dysfunctional CD8 T cells form a proliferative, dynamically regulated compartment within human melanoma. Cell 176(4):775\u201378918","journal-title":"Cell"},{"key":"1396_CR34","doi-asserted-by":"crossref","unstructured":"Ramesh, A., Schubert, R.D., Greenfield, A.L., Dandekar, R., Loudermilk, R., Sabatino, J.J. Jr, Koelzer, M.T., Tran, E.B., Koshal, K., Kim, K., Pr\u00f6bstel, A.-K., Banerji, D., University of California, San Francisco MS-EPIC Team, Guo, C.-Y., Green, A.J., Bove, R.M., DeRisi, J.L., Gelfand, J.M., Cree, B.A.C., Zamvil, S.S., Baranzini, S.E., Hauser, S.L., Wilson, M.R.: A pathogenic and clonally expanded B cell transcriptome in active multiple sclerosis. Proc. Natl. Acad. Sci. U. S. A. 117(37), 22932\u201322943 (2020)","DOI":"10.1073\/pnas.2008523117"},{"issue":"8","key":"1396_CR35","doi-asserted-by":"publisher","first-page":"1104","DOI":"10.1038\/s41593-022-01128-z","volume":"25","author":"J Bryois","year":"2022","unstructured":"Bryois J, Calini D, Macnair W, Foo L, Urich E, Ortmann W, Iglesias VA, Selvaraj S, Nutma E, Marzin M, Amor S, Williams A, Castelo-Branco G, Menon V, De Jager P, Malhotra D (2022) Cell-type-specific cis-eQTLs in eight human brain cell types identify novel risk genes for psychiatric and neurological disorders. Nat Neurosci 25(8):1104\u20131112","journal-title":"Nat Neurosci"},{"issue":"10","key":"1396_CR36","doi-asserted-by":"publisher","first-page":"5114","DOI":"10.1093\/nar\/gkz182","volume":"47","author":"F Massip","year":"2019","unstructured":"Massip F, Laurent M, Brossas C, Fern\u00e1ndez-Justel JM, G\u00f3mez M, Prioleau M-N, Duret L, Picard F (2019) Evolution of replication origins in vertebrate genomes: rapid turnover despite selective constraints. Nucleic Acids Res 47(10):5114\u20135125","journal-title":"Nucleic Acids Res"},{"key":"1396_CR37","doi-asserted-by":"crossref","unstructured":"Young, R.S., Hayashizaki, Y., Andersson, R., Sandelin, A., Kawaji, H., Itoh, M., Lassmann, T., Carninci, P., FANTOM Consortium, Bickmore, W.A., Forrest, A.R., Taylor, M.S.: The frequent evolutionary birth and death of functional promoters in mouse and human. Genome Res. 25(10), 1546\u20131557 (2015)","DOI":"10.1101\/gr.190546.115"},{"key":"1396_CR38","doi-asserted-by":"crossref","unstructured":"Pataskar, A., Vanderlinden, W., Emmerig, J., Singh, A., Lipfert, J., Tiwari, V.K.: Deciphering the gene regulatory landscape encoded in DNA biophysical features. iScience 21, 638\u2013649 (2019)","DOI":"10.1016\/j.isci.2019.10.055"},{"key":"1396_CR39","doi-asserted-by":"crossref","unstructured":"Yazar, S., Alquicira-Hernandez, J., Wing, K., Senabouth, A., Grace Gordon, M., Andersen, S., Lu, Q., Rowson, A., Taylor, T.R.P., Clarke, L., Maccora, K., Chen, C., Cook, A.L., Ye, C.J., Fairfax, K.A., Hewitt, A.W., Powell, J.E.: Single-cell eQTL mapping identifies cell type-specific genetic control of autoimmune disease. Science (2022)","DOI":"10.1126\/science.abf3041"},{"issue":"10","key":"1396_CR40","doi-asserted-by":"publisher","first-page":"1628","DOI":"10.1038\/s41590-023-01560-8","volume":"24","author":"MJ Lee","year":"2023","unstructured":"Lee MJ, Blish CA (2023) Defining the role of natural killer cells in COVID-19. Nat Immunol 24(10):1628\u20131638","journal-title":"Nat Immunol"},{"key":"1396_CR41","doi-asserted-by":"crossref","unstructured":"Kim-Hellmuth, S., Aguet, F., Oliva, M., Mu\u00f1oz-Aguirre, M., Kasela, S., Wucher, V., Castel, S.E., Hamel, A.R., Vi\u00f1uela, A., Roberts, A.L., Mangul, S., Wen, X., Wang, G., Barbeira, A.N., Garrido-Mart\u00edn, D., Nadel, B.B., Zou, Y., Bonazzola, R., Quan, J., Brown, A., Martinez-Perez, A., Soria, J.M., GTEx Consortium, Getz, G., Dermitzakis, E.T., Small, K.S., Stephens, M., Xi, H.S., Im, H.K., Guig\u00f3, R., Segr\u00e8, A.V., Stranger, B.E., Ardlie, K.G., Lappalainen, T.: Cell type-specific genetic regulation of gene expression across human tissues. Science 369(6509) (2020)","DOI":"10.1126\/science.aaz8528"},{"key":"1396_CR42","doi-asserted-by":"crossref","unstructured":"Connally, N.J., Nazeen, S., Lee, D., Shi, H., Stamatoyannopoulos, J., Chun, S., Cotsapas, C., Cassa, C.A., Sunyaev, S.R.: The missing link between genetic association and regulatory function. Elife 11(e74970) (2022)","DOI":"10.7554\/eLife.74970"},{"issue":"11","key":"1396_CR43","doi-asserted-by":"publisher","first-page":"1866","DOI":"10.1038\/s41588-023-01529-1","volume":"55","author":"H Mostafavi","year":"2023","unstructured":"Mostafavi H, Spence JP, Naqvi S, Pritchard JK (2023) Systematic differences in discovery of genetic effects on gene expression and complex traits. Nat Genet 55(11):1866\u20131875","journal-title":"Nat Genet"},{"key":"1396_CR44","doi-asserted-by":"crossref","unstructured":"Cano-Gamez, E., Trynka, G.: From GWAS to function: Using functional genomics to identify the mechanisms underlying complex diseases. Front. Genet. 11 (2020)","DOI":"10.3389\/fgene.2020.00424"},{"issue":"1","key":"1396_CR45","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1471-2105-7-114","volume":"7","author":"VX Jin","year":"2006","unstructured":"Jin VX, Singer GAC, Agosto-P\u00e9rez FJ, Liyanarachchi S, Davuluri RV (2006) Genome-wide analysis of core promoter elements from conserved human and mouse orthologous pairs. BMC Bioinformatics 7(1):1\u201313","journal-title":"BMC Bioinformatics"},{"key":"1396_CR46","doi-asserted-by":"crossref","unstructured":"Shultz, A.J., Sackton, T.B.: Immune genes are hotspots of shared positive selection across birds and mammals (2019)","DOI":"10.7554\/eLife.41815.079"},{"issue":"8","key":"1396_CR47","doi-asserted-by":"publisher","first-page":"1000592","DOI":"10.1371\/journal.pgen.1000592","volume":"5","author":"DG Torgerson","year":"2009","unstructured":"Torgerson DG, Boyko AR, Hernandez RD, Indap A, Hu X, White TJ, Sninsky JJ, Cargill M, Adams MD, Bustamante CD, Clark AG (2009) Evolutionary processes acting on candidate cis-regulatory regions in humans inferred from patterns of polymorphism and divergence. PLoS Genet 5(8):1000592","journal-title":"PLoS Genet"},{"key":"1396_CR48","doi-asserted-by":"crossref","unstructured":"Shiina, T., Hosomichi, K., Inoko, H., Kulski, J.K.: The HLA genomic loci map: expression, interaction, diversity and disease. J. Hum. Genet. 54(1) (2009)","DOI":"10.1038\/jhg.2008.5"},{"key":"1396_CR49","doi-asserted-by":"crossref","unstructured":"Crux, N.B., Elahi, S.: Human leukocyte antigen (HLA) and immune regulation: How do classical and Non-Classical HLA alleles modulate immune response to human immunodeficiency virus and hepatitis C virus infections? Front. Immunol. 8 (2017)","DOI":"10.3389\/fimmu.2017.00832"},{"key":"1396_CR50","doi-asserted-by":"crossref","unstructured":"Hoseinnezhad, T., Soltani, N., Ziarati, S., Behboudi, E., Mousavi, M.J.: The role of HLA genetic variants in COVID-19 susceptibility, severity, and mortality: A global review. J. Clin. Lab. Anal. 38(1\u20132) (2024)","DOI":"10.1002\/jcla.25005"},{"key":"1396_CR51","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2020.601886","volume":"11","author":"F Tavasolian","year":"2020","unstructured":"Tavasolian F, Rashidi M, Hatam GR, Jeddi M, Hosseini AZ, Mosawi SH, Abdollahi E, Inman RD (2020) HLA, immune response, and susceptibility to COVID-19. Front Immunol 11:601886","journal-title":"Front Immunol"},{"issue":"1","key":"1396_CR52","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1016\/j.ajhg.2023.12.005","volume":"111","author":"S Bian","year":"2024","unstructured":"Bian S, Guo X, Yang X, Wei Y, Yang Z, Cheng S, Yan J, Chen Y, Chen G-B, Du X, Francis SS, Shu Y, Liu S (2024) Genetic determinants of IgG antibody response to COVID-19 vaccination. Am J Hum Genet 111(1):181","journal-title":"Am J Hum Genet"},{"key":"1396_CR53","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.coi.2019.04.013","volume":"60","author":"F Dotiwala","year":"2019","unstructured":"Dotiwala F, Lieberman J (2019) Granulysin: Killer lymphocyte safeguard against microbes. Curr Opin Immunol 60:19","journal-title":"Curr Opin Immunol"},{"issue":"2","key":"1396_CR54","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1158\/2326-6066.CIR-20-0649","volume":"10","author":"X-Y Li","year":"2022","unstructured":"Li X-Y, Corvino D, Nowlan B, Aguilera AR, Ng SS, Braun M, Cillo AR, Bald T, Smyth MJ, Engwerda CR (2022) NKG7 is required for optimal antitumor t-cell immunity. Cancer Immunol Res 10(2):154\u2013161","journal-title":"Cancer Immunol Res"},{"issue":"12","key":"1396_CR55","doi-asserted-by":"publisher","first-page":"6519","DOI":"10.1002\/jmv.27189","volume":"93","author":"A Aksakal","year":"2021","unstructured":"Aksakal A, Kerget B, Kerget F, A\u015fk\u0131n S (2021) Evaluation of the relationship between macrophage migration inhibitory factor level and clinical course in patients with COVID-19 pneumonia. J Med Virol 93(12):6519","journal-title":"J Med Virol"},{"issue":"9","key":"1396_CR56","doi-asserted-by":"publisher","first-page":"1987","DOI":"10.1093\/emboj\/19.9.1987","volume":"19","author":"LM Kelly","year":"2000","unstructured":"Kelly LM, Englmeier U, Lafon I, Sieweke MH, Graf T (2000) MafB is an inducer of monocytic differentiation. EMBO J 19(9):1987","journal-title":"EMBO J"},{"key":"1396_CR57","doi-asserted-by":"crossref","unstructured":"Vega, M.A., Sim\u00f3n-Fuentes, M., Aleja, A., Nieto, C., Colmenares, M., Herrero, C., Dom\u00ednguez-Soto, \u00c1., Corb\u00ed, \u00c1.L.: MAFB and MAF transcription factors as macrophage checkpoints for COVID-19 severity. Front. Immunol. 11 (2020)","DOI":"10.3389\/fimmu.2020.603507"},{"issue":"6","key":"1396_CR58","doi-asserted-by":"publisher","first-page":"1419","DOI":"10.1016\/j.cell.2020.08.001","volume":"182","author":"J Schulte-Schrepping","year":"2020","unstructured":"Schulte-Schrepping J, Reusch N, Paclik D, Ba\u00dfler K, Schlickeiser S, Zhang B, Kr\u00e4mer B, Krammer T, Brumhard S, Bonaguro L, De Domenico E, Wendisch D, Grasshoff M, Kapellos TS, Beckstette M, Pecht T, Saglam A, Dietrich O, Mei HE, Schulz AR, Conrad C, Kunkel D, Vafadarnejad E, Xu C-J, Horne A, Herbert M, Drews A, Thibeault C, Pfeiffer M, Hippenstiel S, Hocke A, M\u00fcller-Redetzky H, Heim K-M, Machleidt F, Uhrig A, Jarcy L, J\u00fcrgens L, Stegemann M, Gl\u00f6senkamp CR, Volk H-D, Goffinet C, Landthaler M, Wyler E, Georg P, Schneider M, Dang-Heine C, Neuwinger N, Kappert K, Tauber R, Corman V, Raabe J, Kaiser KM, Vinh MT, Rieke G, Meisel C, Ulas T, Becker M, Geffers R, Witzenrath M, Drosten C, Suttorp N, Kalle C, Kurth F, H\u00e4ndler K, Schultze JL, Aschenbrenner AC, Li Y, Nattermann J, Sawitzki B, Saliba A-E, Sander LE (2020) Deutsche COVID-19 OMICS Initiative (DeCOI): Severe COVID-19 is marked by a dysregulated myeloid cell compartment. Cell 182(6):1419\u2013144023","journal-title":"Cell"},{"issue":"3","key":"1396_CR59","doi-asserted-by":"publisher","first-page":"2591","DOI":"10.3390\/ijms24032591","volume":"24","author":"C Fang","year":"2023","unstructured":"Fang C, Ma Y (2023) Peripheral blood genes crosstalk between COVID-19 and sepsis. Int J Mol Sci 24(3):2591","journal-title":"Int J Mol Sci"},{"key":"1396_CR60","doi-asserted-by":"crossref","unstructured":"Jeong, H.-H., Jia, J., Dai, Y., Simon, L.M., Zhao, Z.: Investigating cellular trajectories in the severity of COVID-19 and their transcriptional programs using machine learning approaches. Genes 12(5) (2021)","DOI":"10.3390\/genes12050635"},{"key":"1396_CR61","doi-asserted-by":"crossref","unstructured":"Rothenberg, E.V., Hosokawa, H., Ungerb\u00e4ck, J.: Mechanisms of action of hematopoietic transcription factor PU.1 in initiation of T-Cell development. Front. Immunol. 10, 438486 (2019)","DOI":"10.3389\/fimmu.2019.00228"},{"key":"1396_CR62","doi-asserted-by":"crossref","unstructured":"Smith, M.R., Satter, L.R.F., Vargas-Hern\u00e1ndez, A.: STAT5b: A master regulator of key biological pathways. Front. Immunol. 13 (2023)","DOI":"10.3389\/fimmu.2022.1025373"},{"key":"1396_CR63","doi-asserted-by":"crossref","unstructured":"Charman, M., McFarlane, S., Wojtus, J.K., Sloan, E., Dewar, R., Leeming, G., Al-Saadi, M., Hunter, L., Carroll, M.W., Stewart, J.P., Digard, P., Hutchinson, E., Boutell, C.: Constitutive TRIM22 expression in the respiratory tract confers a Pre-Existing defence against influenza a virus infection. Front. Cell. Infect. Microbiol. 11 (2021)","DOI":"10.3389\/fcimb.2021.689707"},{"issue":"9","key":"1396_CR64","doi-asserted-by":"publisher","first-page":"794","DOI":"10.1038\/cmi.2017.76","volume":"14","author":"Q Lian","year":"2017","unstructured":"Lian Q, Sun B (2017) Interferons command trim22 to fight against viruses. Cell Mol Immunol 14(9):794\u2013796","journal-title":"Cell Mol Immunol"},{"key":"1396_CR65","doi-asserted-by":"crossref","unstructured":"Maria, M., Pouyanfar, N., \u00d6rd, T., Kaikkonen, M.U.: The power of Single-Cell RNA sequencing in eQTL discovery. Genes 13(3) (2022)","DOI":"10.3390\/genes13030502"},{"issue":"6","key":"1396_CR66","doi-asserted-by":"publisher","first-page":"830","DOI":"10.1101\/gr.3430605","volume":"15","author":"TH Kim","year":"2005","unstructured":"Kim TH, Barrera LO, Qu C, Van Calcar S, Trinklein ND, Cooper SJ, Luna RM, Glass CK, Rosenfeld MG, Myers RM, Ren B (2005) Direct isolation and identification of promoters in the human genome. Genome Res 15(6):830","journal-title":"Genome Res"},{"issue":"3","key":"1396_CR67","doi-asserted-by":"publisher","first-page":"554","DOI":"10.1016\/j.cell.2015.01.006","volume":"160","author":"D Villar","year":"2015","unstructured":"Villar D, Berthelot C, Aldridge S, Rayner TF, Lukk M, Pignatelli M, Park TJ, Deaville R, Erichsen JT, Jasinska AJ, Turner JMA, Bertelsen MF, Murchison EP, Flicek P, Odom DT (2015) Enhancer evolution across 20 mammalian species. Cell 160(3):554","journal-title":"Cell"},{"key":"1396_CR68","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1016\/j.coi.2014.09.008","volume":"31","author":"JF Brinkworth","year":"2014","unstructured":"Brinkworth JF, Barreiro LB (2014) The contribution of natural selection to present-day susceptibility to chronic inflammatory and autoimmune disease. Curr Opin Immunol 31:66\u201378","journal-title":"Curr Opin Immunol"},{"issue":"1","key":"1396_CR69","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1186\/gb-2012-13-1-r7","volume":"13","author":"DJ Gaffney","year":"2012","unstructured":"Gaffney DJ, Veyrieras J-B, Degner JF, Pique-Regi R, Pai AA, Crawford GE, Stephens M, Gilad Y, Pritchard JK (2012) Dissecting the regulatory architecture of gene expression QTLs. Genome Biol 13(1):7","journal-title":"Genome Biol"},{"key":"1396_CR70","doi-asserted-by":"crossref","unstructured":"Tung, J., Zhou, X., Alberts, S.C., Stephens, M., Gilad, Y.: The genetic architecture of gene expression levels in wild baboons. eLife 4 (2015)","DOI":"10.7554\/eLife.04729"},{"issue":"1","key":"1396_CR71","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1186\/s13040-019-0195-y","volume":"12","author":"D Savel","year":"2019","unstructured":"Savel D, Koyut\u00fcrk M (2019) Characterizing human genomic coevolution in locus-gene regulatory interactions. BioData Min 12(1):8","journal-title":"BioData Min"},{"issue":"18","key":"1396_CR72","doi-asserted-by":"publisher","first-page":"3465","DOI":"10.1182\/blood-2010-03-273953","volume":"116","author":"P Tewary","year":"2010","unstructured":"Tewary P, Yang D, Rosa G, Li Y, Finn MW, Krensky AM, Clayberger C, Oppenheim JJ (2010) Granulysin activates antigen-presenting cells through TLR4 and acts as an immune alarmin. Blood 116(18):3465","journal-title":"Blood"},{"key":"1396_CR73","doi-asserted-by":"crossref","unstructured":"Lelliott, E.J., Ramsbottom, K.M., Dowling, M.R., Shembrey, C., Noori, T., Kearney, C.J., Michie, J., Parish, I.A., Jordan, M.A., Baxter, A.G., Young, N.D., Brennan, A.J., Oliaro, J.: NKG7 enhances CD8+ T cell synapse efficiency to limit inflammation. Front. Immunol. 13 (2022)","DOI":"10.3389\/fimmu.2022.931630"},{"key":"1396_CR74","doi-asserted-by":"crossref","unstructured":"Pavlasova, G., Mraz, M.: The regulation and function of CD20: an \u201cenigma\u201d of b-cell biology and targeted therapy. Haematologica 105(6) (2020)","DOI":"10.3324\/haematol.2019.243543"}],"container-title":["Immunogenetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00251-026-01396-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00251-026-01396-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00251-026-01396-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T08:06:24Z","timestamp":1774944384000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00251-026-01396-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,31]]},"references-count":74,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["1396"],"URL":"https:\/\/doi.org\/10.1007\/s00251-026-01396-0","relation":{},"ISSN":["1432-1211"],"issn-type":[{"value":"1432-1211","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,31]]},"assertion":[{"value":"12 January 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 March 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 March 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interests"}},{"value":"The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by The Local Ethics Committee of the Centre for Strategic Planning of FMBA of Russia (Protocol No. 01\/04\/21, 1 April 2021).","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Institutional Review Board Statement"}}],"article-number":"4"}}