Skip to main content

Thank you for visiting 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.

Identification of an imprinted master trans regulator at the KLF14 locus related to multiple metabolic phenotypes

A Corrigendum to this article was published on 28 September 2011

This article has been updated


Genome-wide association studies have identified many genetic variants associated with complex traits. However, at only a minority of loci have the molecular mechanisms mediating these associations been characterized. In parallel, whereas cis regulatory patterns of gene expression have been extensively explored, the identification of trans regulatory effects in humans has attracted less attention. Here we show that the type 2 diabetes and high-density lipoprotein cholesterol–associated cis-acting expression quantitative trait locus (eQTL) of the maternally expressed transcription factor KLF14 acts as a master trans regulator of adipose gene expression. Expression levels of genes regulated by this trans-eQTL are highly correlated with concurrently measured metabolic traits, and a subset of the trans-regulated genes harbor variants directly associated with metabolic phenotypes. This trans-eQTL network provides a mechanistic understanding of the effect of the KLF14 locus on metabolic disease risk and offers a potential model for other complex traits.

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

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type



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

Figure 1: KLF14 is a master regulator of gene expression in adipose tissue.
Figure 2: Regional signal plots at the KLF14 locus.

Accession codes



Change history

  • 22 September 2011

    In the version of this article initially published, there were several errors in the P values reported in the Adiponectin and HOMA-IR columns of Table 3. These errors have been corrected in the HTML and PDF versions of the article.


  1. Voight, B.F. et al. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat. Genet. 42, 579–589 (2010).

    Article  CAS  Google Scholar 

  2. Teslovich, T.M. et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466, 707–713 (2010).

    Article  CAS  Google Scholar 

  3. Kong, A. et al. Parental origin of sequence variants associated with complex diseases. Nature 462, 868–874 (2009).

    Article  CAS  Google Scholar 

  4. Nica, A.C. et al. The architecture of gene regulatory variation across multiple human tissues: the MuTHER study. PLoS Genet. 7, e1002003 (2011).

    Article  CAS  Google Scholar 

  5. Emilsson, V. et al. Genetics of gene expression and its effect on disease. Nature 452, 423–428 (2008).

    Article  CAS  Google Scholar 

  6. Dang, D.T., Pevsner, J. & Yang, V.W. The biology of the mammalian Kruppel-like family of transcription factors. Int. J. Biochem. Cell Biol. 32, 1103–1121 (2000).

    Article  CAS  Google Scholar 

  7. Zambelli, F., Pesole, G. & Pavesi, G. Pscan: finding over-represented transcription factor binding site motifs in sequences from co-regulated or co-expressed genes. Nucleic Acids Res. 37, W247–W252 (2009).

    Article  CAS  Google Scholar 

  8. Portales-Casamar, E. et al. JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles. Nucleic Acids Res. 38, D105–D110 (2010).

    Article  CAS  Google Scholar 

  9. Kaczynski, J., Cook, T. & Urrutia, R. Sp1- and Kruppel-like transcription factors. Genome Biol. 4, 206 (2003).

    Article  Google Scholar 

  10. McConnell, B.B. & Yang, V.W. Mammalian Kruppel-like factors in health and diseases. Physiol. Rev. 90, 1337–1381 (2010).

    Article  CAS  Google Scholar 

  11. Dupuis, J. et al. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat. Genet. 42, 105–116 (2010).

    Article  CAS  Google Scholar 

  12. Heid, I.M. et al. Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution. Nat. Genet. 42, 949–960 (2010).

    Article  CAS  Google Scholar 

  13. Speliotes, E.K. et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat. Genet. 42, 937–948 (2010).

    Article  CAS  Google Scholar 

  14. Spector, T.D. & Williams, F.M. The UK Adult Twin Registry (TwinsUK). Twin Res. Hum. Genet. 9, 899–906 (2006).

    Article  Google Scholar 

  15. Skidmore, P.M. et al. Relation of birth weight, body mass index, and change in size from birth to adulthood to insulin resistance in a female twin cohort. J. Clin. Endocrinol. Metab. 93, 516–520 (2008).

    Article  CAS  Google Scholar 

  16. Aulchenko, Y.S. et al. Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts. Nat. Genet. 41, 47–55 (2009).

    Article  CAS  Google Scholar 

  17. Richards, J.B., Valdes, A.M., Burling, K., Perks, U.C. & Spector, T.D. Serum adiponectin and bone mineral density in women. J. Clin. Endocrinol. Metab. 92, 1517–1523 (2007).

    Article  CAS  Google Scholar 

  18. Prokopenko, I. et al. Variants in MTNR1B influence fasting glucose levels. Nat. Genet. 41, 77–81 (2009).

    Article  CAS  Google Scholar 

  19. Falchi, M., Wilson, S.G., Paximadas, D., Swaminathan, R. & Spector, T.D. Quantitative linkage analysis for pancreatic B-cell function and insulin resistance in a large twin cohort. Diabetes 57, 1120–1124 (2008).

    Article  CAS  Google Scholar 

  20. Li, H., Ruan, J. & Durbin, R. Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Res. 18, 1851–1858 (2008).

    Article  CAS  Google Scholar 

  21. Aulchenko, Y.S., Ripke, S., Isaacs, A. & van Duijn, C.M. GenABEL: an R library for genome-wide association analysis. Bioinformatics 23, 1294–1296 (2007).

    Article  CAS  Google Scholar 

  22. Aulchenko, Y.S., Struchalin, M.V. & van Duijn, C.M. ProbABEL package for genome-wide association analysis of imputed data. BMC Bioinformatics 11, 134 (2010).

    Article  Google Scholar 

  23. Barrett, T. et al. NCBI GEO: archive for functional genomics data sets–10 years on. Nucleic Acids Res. 39, D1005–D1010 (2011).

    Article  CAS  Google Scholar 

  24. Visscher, P.M., Benyamin, B. & White, I. The use of linear mixed models to estimate variance components from data on twin pairs by maximum likelihood. Twin Res. 7, 670–674 (2004).

    Article  Google Scholar 

  25. de Bakker, P.I. et al. Efficiency and power in genetic association studies. Nat. Genet. 37, 1217–1223 (2005).

    Article  CAS  Google Scholar 

  26. Teo, Y.Y. et al. A genotype calling algorithm for the Illumina BeadArray platform. Bioinformatics 23, 2741–2746 (2007).

    Article  CAS  Google Scholar 

  27. Howie, B.N., Donnelly, P. & Marchini, J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 5, e1000529 (2009).

    Article  Google Scholar 

Download references


The MuTHER study was funded by the Wellcome Trust Program grant # 081917. Genotyping of TwinsUK samples was provided by the Wellcome Trust Sanger Institute and the National Eye Institute via a US National Institutes of Health (NIH)/Center for Inherited Disease Research (CIDR) genotyping project. TwinsUK also receives support from the ENGAGE project grant agreement HEALTH-F4-2007-201413 and from the Department of Health via the National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre award to Guy's & St. Thomas' National Health Service Foundation Trust in partnership with King's College London. T.D.S. is an NIHR senior investigator and European Research Council (ERC) senior investigator. M.I.M. is supported by the Oxford NIHR Biomedical Research Centre. Additional support was provided by the Louis-Jeantet Foundation to E.T.D. and A.C.N. and via NIH-NIMH grant R01 MH090941 to E.T.D. and M.I.M.

Author information

Authors and Affiliations



K.S.S., Å.K.H., E.G., G.T. and A.C.N. analyzed data. G.T., A.K., S.-Y.S., H.B.R., N.S. and C.M.L. contributed reagents, materials and analysis tools. U.T., K.R.A., K.S., E.T.D., P.D., M.I.M. and T.D.S. conceived and designed the experiments. K.S.S. and M.I.M. wrote the paper with contributions from Å.K.H. and E.G. All authors read and approved the manuscript before submission.

Corresponding author

Correspondence to Mark I McCarthy.

Ethics declarations

Competing interests

The author declare no competing financial interests.

Additional information

A full list of members is provided in the Supplementary Note.

A full list of members is provided in the Supplementary Note.

A full list of members is provided in the Supplementary Note.

A full list of members is provided in the Supplementary Note.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1 and 2, Supplementary Table 1 and Supplementary Note. (PDF 612 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

the MuTHER Consortium. Identification of an imprinted master trans regulator at the KLF14 locus related to multiple metabolic phenotypes. Nat Genet 43, 561–564 (2011).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing