Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Viewpoint
  • Published:

From Mendel to multi-omics: shifting paradigms

European Journal of Human Genetics volume 32, pages 139–142 (2024)Cite this article

Subjects

The foundations of the basic principles of genetic inheritance were discovered about 158 years ago by Gregor Mendel when he investigated the segregation of seven hereditary characters (now referred to as genes) in garden pea in 1865 [1]. Because Mendel’s laws explain discrete inheritance of traits controlled by a few genes with clear dominance and recessive conditions, new strategies have emerged to better understand inheritance of complex traits, including population genetics, which deals with frequencies of alleles and genotypes at a population level, and quantitative genetics, which concentrates on individual continuous phenotype variation due to genotype and environment interactions [2,3,4]. Mendel focused on the fundamental laws of inheritance of traits but not on the chemical nature of inheritance. Recent publications, by van Dijk et al. [5], Fairbanks [6], Nasmyth [7], and Berger [8], discuss the history of Mendel’s experiments, his biography, and the nature of the questions that he investigated.

The discovery of the double-stranded helical structure of DNA in 1953 marked the transition from classical genetics to molecular genetics and paved the way for a vastly increased understanding of the biological mechanisms of life and diseases [9]. Since then, genetics has been led by molecular, statistical, mathematical, and computational methods to identity and unravel the role of about 20,000 human genes and a nearly limitless number of variant combinations. Understanding the function of every gene is important for determining the role of genomics in human health. Genetics is rapidly becoming the backbone of all biomedical research, and as of this publication, there are over 4802 human genes that are biologically implicated in at least one phenotype for a total of 7372 phenotypes (accessed May 20, 2023) [10]. According to the National Human Genome Research Institute’s bold prediction, the use of genetic information will be routine in research laboratory and clinical settings and the biological function of every human gene will be known by 2030 [11]. Although this prediction is an optimistic view, genetic discovery has led us to where we are, and it will lead us to the future.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: A timeline depicting the key events in the history of genetic research and advances in the methods to study genes and gene function.

References

  1. Mendel G. Versuche über Pflanzen-Hybriden. In Verhandlungen des naturforschenden Vereines in Brünn, Vol. IV (1865). pp. 3–47. Brünn: Im Verlage des Vereines, 1866.

  2. Wright S. The Distribution of Gene Frequencies in Populations. Proc Natl Acad Sci USA 1937;23:307–20.

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  3. Fisher R. The correlation between relatives on the supposition of Mendelian inheritance. Trans R Soc Edinb. 1918;52:399–433.

    Article  Google Scholar 

  4. Edwards AW. G. H. Hardy (1908) and Hardy-Weinberg equilibrium. Genetics. 2008;179:1143–50.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. van Dijk PJ, Jessop AP, Ellis THN. How did Mendel arrive at his discoveries? Nat Genet. 2022;54:926–33.

    Article  PubMed  Google Scholar 

  6. Fairbanks DJ. Demystifying the mythical Mendel: a biographical review. Heredity (Edinb). 2022;129:4–11.

    Article  PubMed  Google Scholar 

  7. Nasmyth K. The magic and meaning of Mendel’s miracle. Nat Rev Genet. 2022;23:447–52.

    Article  PubMed  CAS  Google Scholar 

  8. Berger F. Which field of research would Gregor Mendel choose in the 21st century? Plant Cell. 2022;34:2462–5.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Watson JD, Crick FH. Molecular structure of nucleic acids; a structure for deoxyribose nucleic acid. Nature 1953;171:737–8.

    Article  ADS  PubMed  CAS  Google Scholar 

  10. OMIM. OMIM Gene Map Statistics. https://www.omim.org/statistics/geneMap (Accessed May 2023).

  11. Green ED, Gunter C, Biesecker LG, Di Francesco V, Easter CL, Feingold EA, et al. Strategic vision for improving human health at The Forefront of Genomics. Nature 2020;586:683–92.

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  12. Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC, Baldwin J, et al. Initial sequencing and analysis of the human genome. Nature 2001;409:860–921.

    Article  ADS  PubMed  CAS  Google Scholar 

  13. Nurk S, Koren S, Rhie A, Rautiainen M, Bzikadze AV, Mikheenko A, et al. The complete sequence of a human genome. Science. 2022;376:44–53.

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  14. Replogle JM, Saunders RA, Pogson AN, Hussmann JA, Lenail A, Guna A, et al. Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq. Cell. 2022;185:2559–75.

  15. Civelek M, Lusis AJ. Systems genetics approaches to understand complex traits. Nat Rev Genet. 2014;15:34–48.

    Article  PubMed  CAS  Google Scholar 

  16. Fresard L, Smail C, Ferraro NM, Teran NA, Li X, Smith KS, et al. Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts. Nat Med. 2019;25:911–9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Amare AT, Vaez A, Hsu YH, Direk N, Kamali Z, Howard DM, et al. Bivariate genome-wide association analyses of the broad depression phenotype combined with major depressive disorder, bipolar disorder or schizophrenia reveal eight novel genetic loci for depression. Mol Psychiatry. 2020;25:1420–9.

    Article  PubMed  CAS  Google Scholar 

  18. Nolte IM, Munoz ML, Tragante V, Amare AT, Jansen R, Vaez A, et al. Erratum: Genetic loci associated with heart rate variability and their effects on cardiac disease risk. Nat Commun. 2017;8:16140.

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  19. Amare AT, Schubert KO, Klingler-Hoffmann M, Cohen-Woods S, Baune BT. The genetic overlap between mood disorders and cardiometabolic diseases: a systematic review of genome wide and candidate gene studies. Transl Psychiatry. 2017;7:e1007.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Xue A, Wu Y, Zhu Z, Zhang F, Kemper KE, Zheng Z, et al. Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes. Nat Commun. 2018;9:2941.

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  21. Evangelou E, Warren HR, Mosen-Ansorena D, Mifsud B, Pazoki R, Gao H, et al. Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. Nat Genet. 2018;50:1412–25.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Ripke S, Neale BM, Corvin A, Walters JTR, Farh KH, Holmans PA, et al. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421–7.

    Article  ADS  PubMed Central  CAS  Google Scholar 

  23. Choi SW, Mak TS, O'Reilly PF. Tutorial: a guide to performing polygenic risk score analyses. Nat Protoc. 2020;15:2759–72.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Smith PG, Day NE. The design of case-control studies: the influence of confounding and interaction effects. Int J Epidemiol. 1984;13:356–65.

    Article  PubMed  CAS  Google Scholar 

  25. Wang H, Zhang F, Zeng J, Wu Y, Kemper KE, Xue A, et al. Genotype-by-environment interactions inferred from genetic effects on phenotypic variability in the UK Biobank. Sci Adv. 2019;5:eaaw3538.

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  26. Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature 2018;562:203–9.

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  27. Carlsten C, Brauer M, Brinkman F, Brook J, Daley D, McNagny K, et al. Genes, the environment and personalized medicine: We need to harness both environmental and genetic data to maximize personal and population health. EMBO Rep. 2014;15:736–9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Taliun D, Harris DN, Kessler MD, Carlson J, Szpiech ZA, Torres R, et al. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature. 2021;590:290–9.

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  29. Consortium HA, Rotimi C, Abayomi A, Abimiku A, Adabayeri VM, Adebamowo C, et al. Research capacity. Enabling the genomic revolution in Africa. Science. 2014;344:1346–8.

    Article  Google Scholar 

  30. Hindorff LA, Bonham VL, Brody LC, Ginoza MEC, Hutter CM, Manolio TA, et al. Prioritizing diversity in human genomics research. Nat Rev Genet. 2018;19:175–85.

    Article  PubMed  CAS  Google Scholar 

  31. Zschocke J, Byers PH, Wilkie AOM. Mendelian inheritance revisited: dominance and recessiveness in medical genetics. Nature Rev Genet. 2023;24:442–63.

  32. Bentley AR, Callier SL, Rotimi CN. Evaluating the promise of inclusion of African ancestry populations in genomics. NPJ Genom Med. 2020;5:5.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Kang M, Ko E, Mersha TB. A roadmap for multi-omics data integration using deep learning. Brief Bioinform. 2022;23:1.

    Article  Google Scholar 

  34. Greenfieldboyce N. Scientists dig up biologist Gregor Mendel’s body and sequence his DNA. https://www.npr.org/2022/12/30/1146367861/scientists-dig-up-biologist-gregor-mendels-body-and-sequence-his-dna (accessed May 2023)Nell Greenfieldboyce. 2022.

  35. Radzikowska U, Baerenfaller K, Cornejo-Garcia JA, Karaaslan C, Barletta E, Sarac BE, et al. Omics technologies in allergy and asthma research: An EAACI position paper. Allergy. 2022;77:2888–908.

    Article  PubMed  Google Scholar 

  36. Subramanian I, Verma S, Kumar S, Jere A, Anamika K. Multi-omics Data Integration, Interpretation, and Its Application. Bioinform Biol Insights. 2020;14:1177932219899051.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Schulze TG, McMahon FJ. Defining the phenotype in human genetic studies: forward genetics and reverse phenotyping. Hum Hered. 2004;58:131–8.

    Article  PubMed  Google Scholar 

  38. Stover PJ, Harlan WR, Hammond JA, Hendershot T, Hamilton CM. PhenX: a toolkit for interdisciplinary genetics research. Curr Opin Lipido. 2010;21:136–40.

    Article  CAS  Google Scholar 

  39. Gupta J, Johansson E, Bernstein JA, Chakraborty R, Khurana Hershey GK, Rothenberg ME, et al. Resolving the etiology of atopic disorders by using genetic analysis of racial ancestry. J Allergy Clin Immunol. 2016;138:676–99.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Ghosh D, Bernstein JA, Khurana Hershey GK, Rothenberg ME, Mersha TB. Leveraging Multilayered “Omics” Data for Atopic Dermatitis: A Road Map to Precision Medicine. Front Immunol. 2018;9:2727.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Chen S, Ghandikota S, Gautam Y, Mersha TB. AllergyGenDB: A literature and functional annotation-based omics database for allergic diseases. Allergy. 2020;75:1789–93.

    Article  PubMed  Google Scholar 

  42. Namjou B, Lape M, Malolepsza E, DeVore SB, Weirauch MT, Dikilitas O, et al. Multiancestral polygenic risk score for pediatric asthma. J Allergy Clin Immunol. 2022;150:1086–96.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Mendy A, Burcham S, Merianos AL, Mersha TB, Mahabee-Gittens EM, Chen A, et al. Urinary volatile organic compound metabolites and reduced lung function in U.S. adults. Respir Med. 2022;205:107053.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Ghosh D, Mersha TB. Publicly available cytokine data: Limitations and opportunities. J Allergy Clin Immunol. 2022;150:1053–6.

    Article  PubMed  Google Scholar 

  45. Gautam Y, Johansson E, Mersha TB. Multi-Omics Profiling Approach to Asthma: An Evolving Paradigm. J Pers Med. 2022;12:1.

    Article  Google Scholar 

  46. Maganie T. TIME100: The Most Influential People of 2022. https://time.com/collection/100-most-influential-people-2022/ (Accesesd May, 2023). 2022.

  47. Cesarini D, Visscher PM. Genetics and educational attainment. NPJ Sci Learn. 2017;2:4.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Bueno D. Genetics and Learning: How the Genes Influence Educational Attainment. Front Psychol. 2019;10:1622.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Syurina EV, Brankovic I, Probst-Hensch N, Brand A. Genome-based health literacy: a new challenge for public health genomics. Public Health Genom. 2011;14:201–10.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank Shawna Hottinger for editorial assistance.

Funding

This work was supported by the National Institutes of Health (NIH) grant R01 HG011411.

Author information

Authors and Affiliations

  1. Cincinnati Children’s Hospital Medical Center, Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, OH, USA

    Tesfaye B. Mersha

Authors
  1. Tesfaye B. Mersha
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: TBM; Original draft preparation and writing: TBM; TBM has read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Tesfaye B. Mersha.

Ethics declarations

Competing interests

The author declares no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mersha, T.B. From Mendel to multi-omics: shifting paradigms. Eur J Hum Genet 32, 139–142 (2024). https://doi.org/10.1038/s41431-023-01420-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41431-023-01420-x

Search

Advanced search

Quick links