The inability to digest lactose, due to lactase nonpersistence, is a common trait in adult mammals, except in certain human populations that exhibit lactase persistence. It is not known how the lactase gene is dramatically downregulated with age in most individuals but remains active in some individuals. We performed a comprehensive epigenetic study of human and mouse small intestines, by using chromosome-wide DNA-modification profiling and targeted bisulfite sequencing. Epigenetically controlled regulatory elements accounted for the differences in lactase mRNA levels among individuals, intestinal cell types and species. We confirmed the importance of these regulatory elements in modulating lactase mRNA levels by using CRISPR–Cas9-induced deletions. Genetic factors contribute to epigenetic changes occurring with age at the regulatory elements, because lactase-persistence and lactase-nonpersistence DNA haplotypes demonstrated markedly different epigenetic aging. Thus, genetic factors enable a gradual accumulation of epigenetic changes with age, thereby influencing phenotypic outcome.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.


Primary accessions

Gene Expression Omnibus


  1. 1.

    et al. Transcriptional downregulation of the lactase (LCT) gene during childhood. Gut 54, 1660–1661 (2005).

  2. 2.

    , & Hypolactasia in a fixed cohort of young Finnish adults: a follow-up study. Scand. J. Gastroenterol. 18, 865–870 (1983).

  3. 3.

    , , , & Lactose digestion and the evolutionary genetics of lactase persistence. Hum. Genet. 124, 579–591 (2009).

  4. 4.

    et al. Identification of a variant associated with adult-type hypolactasia. Nat. Genet. 30, 233–237 (2002).

  5. 5.

    et al. The causal element for the lactase persistence/non-persistence polymorphism is located in a 1 Mb region of linkage disequilibrium in Europeans. Ann. Hum. Genet. 67, 298–311 (2003).

  6. 6.

    et al. Genetic signatures of strong recent positive selection at the lactase gene. Am. J. Hum. Genet. 74, 1111–1120 (2004).

  7. 7.

    et al. Evidence of still-ongoing convergence evolution of the lactase persistence T-13910 alleles in humans. Am. J. Hum. Genet. 81, 615–625 (2007).

  8. 8.

    , , , & The origins of lactase persistence in Europe. PLoS Comput. Biol. 5, e1000491 (2009).

  9. 9.

    et al. Genome flux and stasis in a five millennium transect of European prehistory. Nat. Commun. 5, 5257 (2014).

  10. 10.

    et al. Genetic origins of lactase persistence and the spread of pastoralism in Africa. Am. J. Hum. Genet. 94, 496–510 (2014).

  11. 11.

    et al. Convergent adaptation of human lactase persistence in Africa and Europe. Nat. Genet. 39, 31–40 (2007).

  12. 12.

    et al. Diversity of lactase persistence alleles in Ethiopia: signature of a soft selective sweep. Am. J. Hum. Genet. 93, 538–544 (2013).

  13. 13.

    , , & An upstream polymorphism associated with lactase persistence has increased enhancer activity. Gastroenterology 125, 1686–1694 (2003).

  14. 14.

    & Lactase persistence DNA variant enhances lactase promoter activity in vitro: functional role as a cis regulatory element. Hum. Mol. Genet. 12, 2333–2340 (2003).

  15. 15.

    et al. The -14010*C variant associated with lactase persistence is located between an Oct-1 and HNF1α binding site and increases lactase promoter activity. Hum. Genet. 130, 483–493 (2011).

  16. 16.

    , , & The human lactase persistence-associated SNP -13910*T enables in vivo functional persistence of lactase promoter-reporter transgene expression. Hum. Genet. 131, 1153–1159 (2012).

  17. 17.

    Roadmap Epigenomics Consortium. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).

  18. 18.

    et al. Intermediate DNA methylation is a conserved signature of genome regulation. Nat. Commun. 6, 6363 (2015).

  19. 19.

    DNA methylation age of human tissues and cell types. Genome Biol. 14, R115 (2013).

  20. 20.

    et al. Epigenome-wide scans identify differentially methylated regions for age and age-related phenotypes in a healthy ageing population. PLoS Genet. 8, e1002629 (2012).

  21. 21.

    et al. Alzheimer's disease: early alterations in brain DNA methylation at ANK1, BIN1, RHBDF2 and other loci. Nat. Neurosci. 17, 1156–1163 (2014).

  22. 22.

    et al. Conserved epigenomic signals in mice and humans reveal immune basis of Alzheimer's disease. Nature 518, 365–369 (2015).

  23. 23.

    Intestinal epithelial cell surface membrane glycoprotein synthesis. I. An indicator of cellular differentiation. J. Biol. Chem. 248, 2536–2541 (1973).

  24. 24.

    et al. DNA unmethylome profiling by covalent capture of CpG sites. Nat. Commun. 4, 2190 (2013).

  25. 25.

    , & Spatio-temporal patterns of intestine-specific transcription factor expression during postnatal mouse gut development. Gene Expr. Patterns 6, 426–432 (2006).

  26. 26.

    et al. Library-free methylation sequencing with bisulfite padlock probes. Nat. Methods 9, 270–272 (2012).

  27. 27.

    et al. The NIH Roadmap Epigenomics Mapping Consortium. Nat. Biotechnol. 28, 1045–1048 (2010).

  28. 28.

    ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).

  29. 29.

    et al. Herders of Indian and European cattle share their predominant allele for lactase persistence. Mol. Biol. Evol. 29, 249–260 (2012).

  30. 30.

    et al. Genome-wide DNA methylome analysis reveals epigenetically dysregulated non-coding RNAs in human breast cancer. Sci. Rep. 5, 8790 (2015).

  31. 31.

    et al. DNMT1-interacting RNAs block gene-specific DNA methylation. Nature 503, 371–376 (2013).

  32. 32.

    , , & Regulation of chromatin structure by long noncoding RNAs: focus on natural antisense transcripts. Trends Genet. 28, 389–396 (2012).

  33. 33.

    et al. Developmentally programmed 3′ CpG island methylation confers tissue- and cell-type-specific transcriptional activation. Mol. Cell. Biol. 33, 1845–1858 (2013).

  34. 34.

    et al. CRISPR inversion of CTCF sites alters genome topology and enhancer/promoter function. Cell 162, 900–910 (2015).

  35. 35.

    & CTCF: an architectural protein bridging genome topology and function. Nat. Rev. Genet. 15, 234–246 (2014).

  36. 36.

    et al. DNA methylation is required for the control of stem cell differentiation in the small intestine. Genes Dev. 28, 652–664 (2014).

  37. 37.

    et al. DNA methylation dynamics during intestinal stem cell differentiation reveals enhancers driving gene expression in the villus. Genome Biol. 14, R50 (2013).

  38. 38.

    et al. T-13910 DNA variant associated with lactase persistence interacts with Oct-1 and stimulates lactase promoter activity in vitro. Hum. Mol. Genet. 14, 3945–3953 (2005).

  39. 39.

    et al. Competition between DNA methylation and transcription factors determines binding of NRF1. Nature 528, 575–579 (2015).

  40. 40.

    et al. Human colorectal cancer-specific CCAT1-L lncRNA regulates long-range chromatin interactions at the MYC locus. Cell Res. 24, 513–531 (2014).

  41. 41.

    et al. Epigenome editing by a CRISPR-Cas9-based acetyltransferase activates genes from promoters and enhancers. Nat. Biotechnol. 33, 510–517 (2015).

  42. 42.

    & Childhood health: trends and consequences over the life course. Future Child. 22, 43–63 (2012).

  43. 43.

    et al. Polygenic risk and the development and course of asthma: an analysis of data from a four-decade longitudinal study. Lancet Respir. Med. 1, 453–461 (2013).

  44. 44.

    et al. Genome editing with Cas9 in adult mice corrects a disease mutation and phenotype. Nat. Biotechnol. 32, 551–553 (2014).

  45. 45.

    et al. CRISPR-Cas9 knockin mice for genome editing and cancer modeling. Cell 159, 440–455 (2014).

  46. 46.

    , & Intestinal lactase expression and epithelial cell transit in hormone-treated suckling rats. Am. J. Physiol. 260, G379–G384 (1991).

  47. 47.

    , , & Lactase-phlorizin hydrolase and sucrase-isomaltase genes are expressed differently along the villus-crypt axis of rat jejunum. J. Nutr. 129, 1107–1113 (1999).

  48. 48.

    , & An efficient pseudomedian filter for tiling microrrays. BMC Bioinformatics 8, 186 (2007).

  49. 49.

    & Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics 27, 1571–1572 (2011).

  50. 50.

    1000 Genomes Project Consortium. An integrated map of genetic variation from 1,092 human genomes. Nature 491, 56–65 (2012).

  51. 51.

    & BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

  52. 52.

    et al. Identifying novel constrained elements by exploiting biased substitution patterns. Bioinformatics 25, i54–i62 (2009).

  53. 53.

    et al. Genome engineering using the CRISPR-Cas9 system. Nat. Protoc. 8, 2281–2308 (2013).

  54. 54.

    et al. Double nicking by RNA-guided CRISPR Cas9 for enhanced genome editing specificity. Cell 154, 1380–1389 (2013).

  55. 55.

    et al. Circos: an information aesthetic for comparative genomics. Genome Res. 19, 1639–1645 (2009).

Download references


We thank A. Turinsky and L. Strug for statistical recommendations; T. Karvelis for help with sgRNA construction; M. Susic for technical assistance; A. Patterson, P. Kapranov and D. Swallow for comments on the manuscript; and F. Zhang (Broad Institute of MIT and Harvard University) for pX330 plasmid. This work was supported in part by the Canadian Institutes of Health Research (MOP-199170, MOP-119451 and MOP-77689), the US National Institutes of Health (MH088413 and DK085698), the Krembil Foundation and Brain Canada, to A.P. This work was also supported by the Canadian Centre for Computational Genomics (C3G), part of the Genome Innovation Network (GIN), funded by Genome Canada through Genome Quebec and Ontario Genomics, to M.B. A.P. is supported as the Tapscott Chair in Schizophrenia Studies, University of Toronto, Canada. E.K. was supported by a grant from the Research Council of Lithuania (MIP-045/2013). J.G. and K.K. were funded by a grant (MIP-14032) from the Research Council of Lithuania. V.L. was supported by a Canadian Institutes of Health Research Fellowship (200910MFE-211514-141430).

Author information

Author notes

    • Viviane Labrie
    •  & Orion J Buske

    These authors contributed equally to this work.


  1. Krembil Family Epigenetics Laboratory, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.

    • Viviane Labrie
    • , Edward Oh
    • , Richie Jeremian
    • , Carolyn Ptak
    • , Akhil Nair
    • , Aiping Zhang
    • , Sasha Ebrahimi
    • , Gabriel Oh
    •  & Arturas Petronis
  2. Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.

    • Viviane Labrie
    •  & Arturas Petronis
  3. Center for Neurodegenerative Science, Van Andel Research Institute, Grand Rapids, Michigan, USA.

    • Viviane Labrie
  4. Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.

    • Orion J Buske
    •  & Michael Brudno
  5. Centre for Computational Medicine, Hospital for Sick Children, Toronto, Ontario, Canada.

    • Orion J Buske
    •  & Michael Brudno
  6. Department of Protein-DNA Interactions, Institute of Biotechnology, Vilnius University, Vilnius, Lithuania.

    • Giedrius Gasiūnas
    •  & Virginijus Šikšnys
  7. Department of Surgery, Lithuanian University of Health Sciences, Kaunas, Lithuania.

    • Almantas Maleckas
  8. Department of Gastroenterology, Lithuanian University of Health Sciences, Kaunas, Lithuania.

    • Rūta Petereit
    • , Aida Žvirbliene
    • , Kęstutis Adamonis
    •  & Limas Kupčinskas
  9. Institute for Digestive Research, Lithuanian University of Health Sciences, Kaunas, Lithuania.

    • Aida Žvirbliene
    •  & Limas Kupčinskas
  10. Department of Biological DNA Modification, Institute of Biotechnology, Vilnius University, Vilnius, Lithuania.

    • Edita Kriukienė
  11. Institute of Mathematics and Informatics, Vilnius University, Vilnius, Lithuania.

    • Karolis Koncevičius
    •  & Juozas Gordevičius


  1. Search for Viviane Labrie in:

  2. Search for Orion J Buske in:

  3. Search for Edward Oh in:

  4. Search for Richie Jeremian in:

  5. Search for Carolyn Ptak in:

  6. Search for Giedrius Gasiūnas in:

  7. Search for Almantas Maleckas in:

  8. Search for Rūta Petereit in:

  9. Search for Aida Žvirbliene in:

  10. Search for Kęstutis Adamonis in:

  11. Search for Edita Kriukienė in:

  12. Search for Karolis Koncevičius in:

  13. Search for Juozas Gordevičius in:

  14. Search for Akhil Nair in:

  15. Search for Aiping Zhang in:

  16. Search for Sasha Ebrahimi in:

  17. Search for Gabriel Oh in:

  18. Search for Virginijus Šikšnys in:

  19. Search for Limas Kupčinskas in:

  20. Search for Michael Brudno in:

  21. Search for Arturas Petronis in:


The study was designed by V.L. and A.P., and directed and coordinated by V.L., M.B. and A.P. V.L., E.O., R.J. and C.P. planned and performed the experimental work. O.J.B. coordinated and performed the computational analysis. J.G. and K.K. contributed to the computational analysis of the microarrays. A.M., R.P., A.Ž., K.A. and L.K. collected the human jejunum surgical samples and other human tissues. G.G. and V.Š. prepared the CRISPR–Cas9n cell-line constructs, and R.J. and A.N. contributed to the CRISPR–Cas9n cell-line work. K.K. was involved in the haplotype-dependent epigenetic aging analysis. E.K. consulted on the mTAG approach. S.E., A.Z. and G.O. were involved in bisulfite padlock-probe design and preparation. The manuscript was written by V.L., O.J.B. and A.P., and was commented on by all authors.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Arturas Petronis.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–8, Supplementary Tables 1 and 2 and Supplementary Notes 1 and 2

Excel files

  1. 1.

    Supplementary Table 3

    sgRNAs and primer sequences used for the CRISPR-Cas9 deletions in mice and a human intestinal cell line.

  2. 2.

    Supplementary Table 4

    Bisulfite padlock probe sequences and barcode primers used for the high resolution DNA modification analysis at lactase gene region in humans and mice.

  3. 3.

    Supplementary Data Set 1

    Chromosome-wide scan of jejunal enterocytes identifies significant DNA modification differences between infant and adult mice.

About this article

Publication history






Further reading