Preview

Vavilov Journal of Genetics and Breeding

Advanced search

Search for signals of positive selection of circadian rhythm genes PER1, PER2, PER3 in different human populations

https://doi.org/10.18699/vjgb-24-71

Abstract

The diversity of geographically distributed human populations shows considerable variation in external and internal traits of individuals. Such differences are largely attributed to genetic adaptation to various environmental influences, which include changes in climatic conditions, variations in sleep and wakefulness, dietary variations, and others. Whole-genome data from individuals of different populations make it possible to determine the specific genetic sites responsible for adaptations and to further understand the genetic structure underlying human adaptive characteristics. In this article, we searched for signals of single nucleotide polymorphisms (SNPs) under selection pressure in people of different populations. To identify selection signals in different population groups, the PER1, PER2 and PER3 genes that are involved in the coordination of thermogenic functions and regulation of circadian rhythms, which is directly reflected in the adaptive abilities of the organism, were investigated. Data were analyzed using publicly available data from the 1000 Genomes Project for 23 populations. The Extended Haplotype Homozygosity Score statistical method was chosen to search for traces of selection. The comparative analysis performed identified points subject to selection pressure. The SNPs were annotated through the GWAS catalog and manually by analyzing Internet resources. This study suggests that living conditions, climate, and other external factors directly influence the genetic structure of populations and vary across races and geographic locations. In addition, many of the selection variants in the PER1, PER2, PER3 genes appear to regulate biological processes that are associated with major modern diseases, including obesity, cancer, metabolic syndrome, bipolar personality disorder, depression, rheumatoid arthritis, diabetes mellitus, lupus erythematosus, stroke and Alzheimer’s disease, making them extremely interesting targets for further research aimed at identifying the genetic causes of human disease. 

About the Authors

A. I. Mishina
Centre for Strategic Planning and Management of Biomedical Health Risks of the Federal Medical Biological Agency
Russian Federation

Moscow



S. Y. Bakoev
Centre for Strategic Planning and Management of Biomedical Health Risks of the Federal Medical Biological Agency
Russian Federation

Moscow



A. Y. Oorzhak
Centre for Strategic Planning and Management of Biomedical Health Risks of the Federal Medical Biological Agency
Russian Federation

Moscow



A. A. Keskinov
Centre for Strategic Planning and Management of Biomedical Health Risks of the Federal Medical Biological Agency
Russian Federation

Moscow



Sh. Sh. Kabieva
Centre for Strategic Planning and Management of Biomedical Health Risks of the Federal Medical Biological Agency
Russian Federation

Moscow



A. V. Korobeinikova
Centre for Strategic Planning and Management of Biomedical Health Risks of the Federal Medical Biological Agency
Russian Federation

Moscow



V. S. Yudin
Centre for Strategic Planning and Management of Biomedical Health Risks of the Federal Medical Biological Agency
Russian Federation

Moscow



M. M. Bobrova
Centre for Strategic Planning and Management of Biomedical Health Risks of the Federal Medical Biological Agency
Russian Federation

Moscow



D. A. Shestakov
Centre for Strategic Planning and Management of Biomedical Health Risks of the Federal Medical Biological Agency
Russian Federation

Moscow



V. V. Makarov
Centre for Strategic Planning and Management of Biomedical Health Risks of the Federal Medical Biological Agency
Russian Federation

Moscow



L. V. Getmantseva
Centre for Strategic Planning and Management of Biomedical Health Risks of the Federal Medical Biological Agency
Russian Federation

Moscow



References

1. 1000 Genomes. [WWW Document]. 2008. URL: https://www.ncbi.nlm.nih.gov/projects/faspftp/1000genomes/ (accessed 9.6.23)

2. Ahrens C.W., Rymer P.D., Stow A., Bragg J., Dillon S., Umbers K.D.L., Dudaniec R.Y. The search for loci under selection: trends, biases and progress. Mol. Ecol. 2018;27(6):1342-1356. DOI 10.1111/mec.14549

3. Azevedo P.G., Miranda L.R., Nicolau E.S., Alves R.B., Bicalho M.A.C., Couto P.P., Ramos A.V., Souza R.P., Longhi R., Friedman E., Marco L., Bastos-Rodrigues L. Genetic association of the PERIOD3 (PER3) Clock gene with extreme obesity. Obes. Res. Clin. Pract. 2021;15(4):334-338. DOI 10.1016/j.orcp.2021.06.006

4. Bacalini M.G., Palombo F., Garagnani P., Giuliani C., Fiorini C., Caporali L., Stanzani Maserati M., Capellari S., Romagnoli M., De Fanti S., Benussi L., Binetti G., Ghidoni R., Galimberti D., Scarpini E., Arcaro M., Bonanni E., Siciliano G., Maestri M., Guarnieri B.; Italian Multicentric Group on clock genes, actigraphy in AD; Martucci M., Monti D., Carelli V., Franceschi C., La Morgia C., Santoro A. Association of rs3027178 polymorphism in the circadian clock gene PER1 with susceptibility to Alzheimer’s disease and longevity in an Italian population. GeroScience. 2022;44(2):881-896. DOI 10.1007/s11357-021-00477-0

5. Bakoev S., Getmantseva L., Kostyunina O., Bakoev N., Prytkov Y., Usatov A., Tatarinova T.V. Genome-wide analysis of genetic diversity and artificial selection in Large White pigs in Russia. PeerJ. 2021;9:e11595. DOI 10.7717/peerj.11595

6. Bakoev S.Y., Korobeinikova A.V., Mishina A.I., Kabieva S.S., Mitrofanov S.I., Ivashechkin A.A., Akinshina A.I., Snigir E.A., Yudin S.M., Yudin V.S., Getmantseva L.V., Anderzhanova E.A. Genomic signatures of positive selection in human populations of the OXT, OXTR, AVP, AVPR1A and AVR1B gene variants related to the regulation of psychoemotional response. Genes (Basel). 2023;14(11): 2053. DOI 10.3390/genes14112053

7. Baranger D.A.A., Ifrah C., Prather A.A., Carey C.E., Corral-Frías N.S., Drabant Conley E., Hariri A.R., Bogdan R. PER1 rs3027172 genotype interacts with early life stress to predict problematic alcohol use, but not reward-related ventral striatum activity. Front. Psychol. 2016;7:464. DOI 10.3389/fpsyg.2016.00464

8. Benton M.L., Abraham A., LaBella A.L., Abbot P., Rokas A., Capra J.A. The influence of evolutionary history on human health and disease. Nat. Rev. Genet. 2021;22(5):269-283. DOI 10.1038/s41576-020-00305-9

9. Biscontin A., Zarantonello L., Russo A., Costa R., Montagnese S. Toward a molecular approach to chronotype assessment. J. Biol. Rhythms. 2022;37(3):272-282. DOI 10.1177/07487304221099365

10. Blomeyer D., Buchmann A.F., Lascorz J., Zimmermann U.S., Esser G., Desrivieres S., Schmidt M.H., Banaschewski T., Schumann G., Laucht M. Association of PER2 genotype and stressful life events with alcohol drinking in young adults. PLoS One. 2013;8(3):e59136. DOI 10.1371/journal.pone.0059136

11. Bondarenko E.A., Shadrina M.I., Druzhkova T.A., Akzhigitov R.G., Gulyaeva N.V., Gekht A.B., Slominsky P.A. An association study of rs10462021 polymorphism in the clock gene PERIOD3 and different clinical types of depression. Mol. Genet. Microbiol. Virol. 2018; 33(1):26-29. DOI 10.3103/S0891416818010056

12. Cade B.E. Variation and selection in human circadian clock genes. Doctoral Thesis. University of Surrey, 2010 Carlson C.S., Thomas D.J., Eberle M.A., Swanson J.E., Livingston R.J., Rieder M.J., Nickerson D.A. Genomic regions exhibiting positive selection identified from dense genotype data. Genome Res. 2005;15(11):1553-1565. DOI 10.1101/gr.4326505

13. Carpen J.D., Archer S.N., Skene D.J., Smits M., von Schantz M. A single‐nucleotide polymorphism in the 5′‐untranslated region of the hPER2 gene is associated with diurnal preference. J. Sleep Res. 2005;14(3):293-297. DOI 10.1111/j.1365-2869.2005.00471.x

14. Chacón-Duque J.-C., Adhikari K., Fuentes-Guajardo M., MendozaRevilla J., Acuña-Alonzo V., Barquera R., Quinto-Sánchez M., … Poletti G., Gallo C., Bedoya G., Rothhammer F., Balding D., Hellenthal G., Ruiz-Linares A. Latin Americans show wide-spread Converso ancestry and imprint of local Native ancestry on physical appearance. Nat. Commun. 2018;9(1):5388. DOI 10.1038/s41467-018-07748-z

15. Chang A.-M., Bjonnes A.C., Aeschbach D., Buxton O.M., Gooley J.J., Anderson C., Van Reen E., Cain S.W., Czeisler C.A., Duffy J.F., Lockley S.W., Shea S.A., Scheer F.A.J.L., Saxena R. Circadian gene variants influence sleep and the sleep electroencephalogram in humans. Chronobiol. Int. 2016;33(5):561-573. DOI 10.3109/0742 0528.2016.1167078

16. Chang Y.-C., Chiu Y.-F., Liu P.-H., Hee S.W., Chang T.-J., Jiang Y.-D., Lee W.-J., Lee P.-C., Kao H.-Y., Hwang J.-J., Chuang L.-M. Genetic variation in the NOC gene is associated with body mass index in chinese subjects. PLoS One. 2013;8(7):e69622. DOI 10.1371/journal.pone.0069622

17. Chappuis S., Ripperger J.A., Schnell A., Rando G., Jud C., Wahli W., Albrecht U. Role of the circadian clock gene Per2 in adaptation to cold temperature. Mol. Metab. 2013;2(3):184-193. DOI 10.1016/j.molmet.2013.05.002

18. Clemente J.C., Pehrsson E.C., Blaser M.J., Sandhu K., Gao Z., Wang B., Magris M., Hidalgo G., Contreras M., Noya-Alarcón Ó., Lander O., McDonald J., Cox M., Walter J., Oh P.L., Ruiz J.F., Rodriguez S., Shen N., Song S.J., Metcalf J., Knight R., Dantas G., DominguezBello M.G. The microbiome of uncontacted Amerindians. Sci. Adv. 2015;1(3):e1500183. DOI 10.1126/sciadv.1500183

19. Dan Y.-L., Zhao C.-N., Mao Y.-M., Wu Q., He Y.-S., Hu Y.-Q., Xiang K., Yang X.-K., Sam N.B., Wu G.-C., Pan H.-F. Association of PER2 gene single nucleotide polymorphisms with genetic susceptibility to systemic lupus erythematosus. Lupus. 2021;30(5): 734-740. DOI 10.1177/0961203321989794

20. Donin A.S., Nightingale C.M., Owen C.G., Rudnicka A.R., McNamara M.C., Prynne C.J., Stephen A.M., Cook D.G., Whincup P.H. Nutritional composition of the diets of South Asian, black AfricanCaribbean and white European children in the United Kingdom: The Child Heart and Health Study in England (CHASE). Br. J. Nutr. 2010;104(2):276-285. DOI 10.1017/S000711451000070X

21. Egan K.J., Knutson K.L., Pereira A.C., von Schantz M. The role of race and ethnicity in sleep, circadian rhythms and cardiovascular health. Sleep Med. Rev. 2017;33:70-78. DOI 10.1016/j.smrv.2016.05.004

22. Forbes E.E., Dahl R.E., Almeida J.R.C., Ferrell R.E., Nimgaonkar V.L., Mansour H., Sciarrillo S.R., Holm S.M., Rodriguez E.E., Phillips M.L. PER2 rs2304672 polymorphism moderates circadianrelevant reward circuitry activity in adolescents. Biol. Psychiatry. 2012;71(5):451-457. DOI 10.1016/j.biopsych.2011.10.012

23. Gafarov V.V., Gagulin I.V., Gromova E.A., Gafarova A.V., Panov D.O. Association of polymorphism rs934945 gene Per2 with sleep disorders in the male population of Novosibirsk 25-44. Mir Nauki, Kul’tury, Obrazovaniya = The World of Science, Culture and Education. 2016;5:283-287 (in Russian)

24. Gintis H., Doebeli M., Flack J. The evolution of human cooperation. Cliodynamics. 2012;3(1):172-190. DOI 10.21237/C7CLIO3112928

25. Gu Z., Wang B., Zhang Y.-B., Ding H., Zhang Y., Yu J., Gu M., Chan P., Cai Y. Association of ARNTL and PER1 genes with Parkinson’s disease: a case-control study of Han Chinese. Sci. Rep. 2015;5(1): 15891. DOI 10.1038/srep15891

26. Guo H., Li X., Li W., Wu J., Wang S., Wei J. Climatic modification effects on the association between PM1 and lung cancer incidence in China. BMC Public Health. 2021;21(1):880. DOI 10.1186/s12889-021-10912-8

27. Hancock A.M., Alkorta-Aranburu G., Witonsky D.B., Di Rienzo A. Adaptations to new environments in humans: the role of subtle allele frequency shifts. Philos. Trans. R. Soc. B Biol. Sci. 2010; 365(1552):2459-2468. DOI 10.1098/rstb.2010.0032

28. Holipah Hinoura T., Kozaka N., Kuroda Y. The correlation between PER3 rs2640908 polymorphism and colorectal Cancer in the Japanese population. Appl. Cancer Res. 2019;39(1):3. DOI 10.1186/s41241-019-0072-5

29. Jansen P.R., Watanabe K., Stringer S., Skene N., Bryois J., Hammerschlag A.R., de Leeuw C.A., Benjamins J.S., Muñoz-Manchado A.B., Nagel M., Savage J.E., Tiemeier H., White T., Tung J.Y., Hinds D.A., Vacic V., Wang X., Sullivan P.F., van der Sluis S., Polderman T.J.C., Smit A.B., Hjerling-Leffler J., Van Someren E.J.W., Posthuma D. 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

30. Jensen J.D., Foll M., Bernatchez L. The past, present and future of genomic scans for selection. Mol. Ecol. 2016;25(1):1-4. DOI 10.1111/mec.13493

31. Jones S.E., Lane J.M., Wood A.R., van Hees V.T., Tyrrell J., Beaumont R.N., Jeffries A.R., … Gehrman P.R., Lawlor D.A., Frayling T.M., Rutter M.K., Hinds D.A., Saxena R., Weedon M.N. Genome-wide association analyses of chronotype in 697,828 individuals provides insights into circadian rhythms. Nat. Commun. 2019;10(1):343. DOI 10.1038/s41467-018-08259-7

32. Kichaev G., Bhatia G., Loh P.-R., Gazal S., Burch K., Freund M.K., Schoech A., Pasaniuc B., Price A.L. Leveraging polygenic functional enrichment to improve GWAS power. Am. J. Hum. Genet. 2019;104(1):65-75. DOI 10.1016/j.ajhg.2018.11.008

33. Kim J.-W., Kim H.-A., Suh C.-H., Jung J.-Y. Sex hormones affect the pathogenesis and clinical characteristics of systemic lupus erythematosus. Front. Med. 2022;9:906475. DOI 10.3389/fmed.2022. 906475

34. Klassmann A., Gautier M. Detecting selection using extended haplotype homozygosity (EHH)-based statistics in unphased or unpolarized data. PLoS One. 2022;17(1):e0262024. DOI 10.1371/journal.pone.0262024

35. Kripke D.F., Nievergelt C.M., Joo E., Shekhtman T., Kelsoe J.R. Circadian polymorphisms associated with affective disorders. J. Circadian Rhythms. 2009;7:2. DOI 10.1186/1740-3391-7-2

36. Lee H., Nah S.-S., Chang S.-H., Kim H.-K., Kwon J.-T., Lee S., Cho I.-H., Lee S.W., Kim Y.O., Hong S.-J., Kim H.-J. PER2 is downregulated by the LPS-induced inflammatory response in synoviocytes in rheumatoid arthritis and is implicated in disease susceptibility. Mol. Med. Rep. 2017;16(1):422-428. DOI 10.3892/mmr.2017.6578

37. Lesicka M., Jabłońska E., Wieczorek E., Pepłońska B., Gromadzińska J., Seroczyńska B., Kalinowski L., Skokowski J., Reszka E. Circadian gene polymorphisms associated with breast cancer susceptibility. Int. J. Mol. Sci. 2019;20(22):5704. DOI 10.3390/ijms 20225704

38. LeVan T.D., Xiao P., Kumar G., Kupzyk K., Qiu F., Klinkebiel D., Eudy J., Cowan K., Berger A.M. Genetic variants in circadian rhythm genes and self-reported sleep quality in women with breast cancer. J. Circadian Rhythms. 2019;17(1):184. DOI 10.5334/jcr.184

39. Levey D.F., Stein M.B., Wendt F.R., Pathak G.A., Zhou H., Aslan M., Quaden R., Harrington K.M., Nuñez Y.Z., Overstreet C., Radhakrishnan K., Sanacora G., McIntosh A.M., Shi J., Shringarpure S.S., Concato J., Polimanti R., Gelernter J. Bi-ancestral depression GWAS in the Million Veteran Program and meta-analysis in >1.2 million individuals highlight new therapeutic directions. Nat. Neurosci. 2021; 24(7):954-963. DOI 10.1038/s41593-021-00860-2

40. Levran O., Randesi M., Rotrosen J., Ott J., Adelson M., Kreek M.J. A 3′ UTR SNP rs885863, a cis-eQTL for the circadian gene VIPR2 and lincRNA 689, is associated with opioid addiction. PLoS One. 2019;14(11):e0224399. DOI 10.1371/journal.pone.0224399

41. Liberman A.R., Kwon S.B., Vu H.T., Filipowicz A., Ay A., Ingram K.K. Circadian clock model supports molecular link between PER3 and human anxiety. Sci. Rep. 2017;7(1):9893. DOI 10.1038/s41598-017-07957-4

42. Lin E., Kuo P.-H., Liu Y.-L., Yang A.C., Kao C.-F., Tsai S.-J. Effects of circadian clock genes and health-related behavior on metabolic syndrome in a Taiwanese population: Evidence from association and interaction analysis. PLoS One. 2017;12(3):e0173861. DOI 10.1371/journal.pone.0173861

43. Lopez M.E., Neira R., Yáñez J.M. Applications in the search for genomic selection signatures in fish. Front. Genet. 2015;5:458. DOI 10.3389/fgene.2014.00458

44. Maryanaji Z. The effect of climatic and geographical factors on breast cancer in Iran. BMC Res. Notes. 2020;13(1):519. DOI 10.1186/s13104-020-05368-9

45. McCarthy M.J., Welsh D.K. Cellular circadian clocks in mood disorders. J. Biol. Rhythms. 2012;27(5):339-352. DOI 10.1177/0748730 412456367

46. Melhuish Beaupre L.M., Gonçalves V.F., Zai C.C., Tiwari A.K., Harripaul R.S., Herbert D., Freeman N., Müller D.J., Kennedy J.L. Genome-wide association study of sleep disturbances in depressive disorders. Mol. Neuropsychiatry. 2020;5(Suppl. 1):34-43. DOI 10.1159/000505804

47. Min W., Tang N., Zou Z., Chen Y., Zhang X., Huang Y., Wang J., Zhang Y., Zhou B., Sun X. A panel of rhythm gene polymorphisms is involved in susceptibility to type 2 diabetes mellitus and bipolar disorder. Ann. Transl. Med. 2021;9(20):1555. DOI 10.21037/atm21-4803

48. Miranda A., Shekhtman T., McCarthy M., DeModena A., Leckband S.G., Kelsoe J.R. Study of 45 candidate genes suggests CACNG2 may be associated with lithium response in bipolar disorder. J. Affect. Disord. 2019;248:175-179. DOI 10.1016/j.jad.2019. 01.010

49. Molina E., Gould N., Lee K., Krimins R., Hardenbergh D., Timlin H. Stress, mindfulness, and systemic lupus erythematosus: An overview and directions for future research. Lupus. 2022;31(13):1549- 1562. DOI 10.1177/09612033221122980

50. National Library of Medicine (US) [WWW Document]. URL https://www.ncbi.nlm.nih.gov/(accessed 9.17.23)

51. Nielsen R. Molecular signatures of natural selection. Annu. Rev. Genet. 2005;39(1):197-218. DOI 10.1146/annurev.genet.39.073003.112420

52. Pan Z., Yu L., Shao M., Ma Y., Cheng Y., Wu Y., Xu S., Zhang C., Zhu J., Pan F., Sun G. The influence of meteorological factors and total malignant tumor health risk in Wuhu city in the context of climate change. BMC Public Health. 2023;23(1):346. DOI 10.1186/s12889-023-15200-1

53. Porras A.M., Shi Q., Zhou H., Callahan R., Montenegro-Bethancourt G., Solomons N., Brito I.L. Geographic differences in gut microbiota composition impact susceptibility to enteric infection. Cell Rep. 2021;36(4):109457. DOI 10.1016/j.celrep.2021.109457

54. Purcell S., Neale B., Todd-Brown K., Thomas L., Ferreira M.A.R., Bender D., Maller J., Sklar P., de Bakker P.I.W., Daly M.J., Sham P.C. PLINK: A tool set for whole-genome association and populationbased linkage analyses. Am. J. Hum. Genet. 2007;81(3):559-575. DOI 10.1086/519795

55. Qu F., Qiao Q., Wang N., Ji G., Zhao H., He L., Wang H., Bao G. Genetic polymorphisms in circadian negative feedback regulation genes predict overall survival and response to chemotherapy in gastric cancer patients. Sci. Rep. 2016;6(1):22424. DOI 10.1038/srep22424

56. Quaglia M., Merlotti G., De Andrea M., Borgogna C., Cantaluppi V. Viral infections and systemic lupus erythematosus: new players in an old story. Viruses. 2021;13(2):277. DOI 10.3390/v13020277

57. Rijo-Ferreira F., Takahashi J.S. Genomics of circadian rhythms in health and disease. Genome Med. 2019;11(1):82. DOI 10.1186/s13073-019-0704-0

58. Sabeti P.C., Reich D.E., Higgins J.M., Levine H.Z.P., Richter D.J., Schaffner S.F., Gabriel S.B., Platko J.V., Patterson N.J., McDonald G.J., Ackerman H.C., Campbell S.J., Altshuler D., Cooper R., Kwiatkowski D., Ward R., Lander E.S. Detecting recent positive selection in the human genome from haplotype structure. Nature. 2002;419(6909):832-837. DOI 10.1038/nature01140

59. Sakurada K., Konta T., Takahashi S., Murakami N., Sato H., Murakami R., Watanabe M., Ishizawa K., Ueno Y., Yamashita H., Kayama T. Circadian clock gene polymorphisms and sleep-onset problems in a population-based cohort study: The yamagata study. Tohoku J. Exp. Med. 2021;255(4):325-331. DOI 10.1620/tjem.255.325

60. Saravanan K.A., Panigrahi M., Kumar H., Bhushan B., Dutt T., Mishra B.P. Selection signatures in livestock genome: A review of concepts, approaches and applications. Livest. Sci. 2020;241: 104257. DOI 10.1016/j.livsci.2020.104257

61. Schroor M.M., Plat J., Mensink R.P. Relation between single nucleotide polymorphisms in circadian clock relevant genes and cholesterol metabolism. Mol. Genet. Metab. 2023;138(4):107561. DOI 10.1016/j.ymgme.2023.107561

62. Shareefa D. Genetic analysis of bipolar disorder and alcohol use disorder. Doctoral Thesis. University of Cape Town, 2015 Shi Y., Liu Y., Yang L., Yan J. A mathematical model to characterize the role of light adaptation in mammalian circadian clock. Front. Mol. Biosci. 2021;8:681696. DOI 10.3389/fmolb.2021.681696

63. Soria V., Martínez-Amorós È., Escaramís G., Valero J., Pérez-Egea R., García C., Gutiérrez-Zotes A., Puigdemont D., Bayés M., Crespo J.M., Martorell L., Vilella E., Labad A., Vallejo J., Pérez V., Menchón J.M., Estivill X., Gratacòs M., Urretavizcaya M. Differential association of circadian genes with mood disorders: CRY1 and NPAS2 are associated with unipolar major depression and CLOCK and VIP with bipolar disorder. Neuropsychopharmacology. 2010; 35(6):1279-1289. DOI 10.1038/npp.2009.230

64. Syromyatnikov M., Nesterova E., Gladkikh M., Smirnova Y., Gryaznova M., Popov V. Characteristics of the gut bacterial composition in people of different nationalities and religions. Microorganisms. 2022;10(9):1866. DOI 10.3390/microorganisms10091866

65. Szpiech Z.A. Selscan 2.0: scanning for sweeps in unphased data. bioRxiv. 2021. DOI 10.1101/2021.10.22.465497

66. Voight B.F., Kudaravalli S., Wen X., Pritchard J.K. A map of recent positive selection in the human genome. PLoS Biol. 2006;4(3):e72. DOI 10.1371/journal.pbio.0040072

67. Wang W.M., Yuan P., Wang J.Y., Ma F., Fan Y., Li Q., Zhang P., Xu B.H. Association of genetic variantions of circadian clock genes and risk of breast cancer. Zhonghua Zhong Liu Za Zhi. 2013;35(3):236-239. DOI 10.3760/cma.j.issn.0253-3766.2013.03.017

68. Wen M., Jiang X., She H., Han C., Pei Z., Cai Y., Zhang T. The Per2 polymorphism rs10462023 is associated with the risk of stroke in a Chinese population. Biol. Rhythm Res. 2015;46(4):545-551. DOI 10.1080/09291016.2015.1026675

69. Xu L., Bickhart D.M., Cole J.B., Schroeder S.G., Song J., Tassell C.P., Sonstegard T.S., Liu G.E. Genomic signatures reveal new evidences for selection of important traits in domestic cattle. Mol. Biol. Evol. 2015;32(3):711-725. DOI 10.1093/molbev/msu333

70. Zhang L., Ptáček L.J., Fu Y.-H. Diversity of human clock genotypes and consequences. 2013;119:51-81. DOI 10.1016/B978-0-12-396971-2.00003-8

71. Zheng W., He Y., Guo Y., Yue T., Zhang H., Li J., Zhou B., Zeng X., Li L., Wang B., Cao J., Chen L., Li C., Li H., Cui C., Bai C., Baimakangzhuo, Qi X., Ouzhuluobu, Su B. Large-scale genome sequencing redefines the genetic footprints of high-altitude adaptation in Tibetans. Genome Biol. 2023;24(1):73. DOI 10.1186/s13059-023- 02912-1


Review

Views: 723


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2500-3259 (Online)