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Human Genetics

, Volume 135, Issue 2, pp 223–232 | Cite as

Linking short tandem repeat polymorphisms with cytosine modifications in human lymphoblastoid cell lines

  • Zhou Zhang
  • Yinan Zheng
  • Xu Zhang
  • Cong Liu
  • Brian Thomas Joyce
  • Warren A. Kibbe
  • Lifang Hou
  • Wei ZhangEmail author
Original Investigation

Abstract

Inter-individual variation in cytosine modifications has been linked to complex traits in humans. Cytosine modification variation is partially controlled by single nucleotide polymorphisms (SNPs), known as modified cytosine quantitative trait loci (mQTL). However, little is known about the role of short tandem repeat polymorphisms (STRPs), a class of structural genetic variants, in regulating cytosine modifications. Utilizing the published data on the International HapMap Project lymphoblastoid cell lines (LCLs), we assessed the relationships between 721 STRPs and the modification levels of 283,540 autosomal CpG sites. Our findings suggest that, in contrast to the predominant cis-acting mode for SNP-based mQTL, STRPs are associated with cytosine modification levels in both cis-acting (local) and trans-acting (distant) modes. In local scans within the ±1 Mb windows of target CpGs, 21, 9, and 21 cis-acting STRP-based mQTL were detected in CEU (Caucasian residents from Utah, USA), YRI (Yoruba people from Ibadan, Nigeria), and the combined samples, respectively. In contrast, 139,420, 76,817, and 121,866 trans-acting STRP-based mQTL were identified in CEU, YRI, and the combined samples, respectively. A substantial proportion of CpG sites detected with local STRP-based mQTL were not associated with SNP-based mQTL, suggesting that STRPs represent an independent class of mQTL. Functionally, genetic variants neighboring CpG-associated STRPs are enriched with genome-wide association study (GWAS) loci for a variety of complex traits and diseases, including cancers, based on the National Human Genome Research Institute (NHGRI) GWAS Catalog. Therefore, elucidating these STRP-based mQTL in addition to SNP-based mQTL can provide novel insights into the genetic architectures of complex traits.

Keywords

Complex Trait Combine Sample International HapMap Project National Human Genome Research Institute International HapMap Consortium 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was partially supported by grants from the National Institutes of Health: R21HG006367 (to WZ), R21CA187869 (to WZ and LH), and The Robert H. Lurie Comprehensive Cancer Center-Developmental Funds P30CA060553 (to WZ).

Supplementary material

439_2015_1628_MOESM1_ESM.png (269 kb)
Supplementary material 1 Fig. 1 Pearson’s correlation coefficients (ρ) of STRPs and cytosine modifications in local scans between CEU and YRI samples. Scatter plot for Pearson’s correlations (ρ) of STRP length and M-values of local CpGs within ± 1 Mb windows of STRPs for CEU and YRI. (PNG 269 kb)
439_2015_1628_MOESM2_ESM.png (204 kb)
Supplementary material 2 Fig. 2 QQ-plots of the observed p -values for trans -acting STRP-based mQTL. P-values are binned and displayed as hexagons. Different grey scales of each hexagon represent different counts of p-values. A total of > 200 million observed p-values from the whole-genome scan are shown. (a) CEU; (b) YRI. (PNG 204 kb)
439_2015_1628_MOESM3_ESM.png (98 kb)
Supplementary material 3 Fig. 3 Enrichment of GWAS loci among cis -acting STRP-based mQTL. The null distributions of the numbers of SNPs overlapped with GWAS loci are displayed as histograms. The asterisk marks the true number of SNPs overlapped with GWAS loci within different windows: (a) ± 100 Kb; (b) ± 500 Kb; and (c) ± 1 Mb of cis-acting STRP-based mQTL (p-value < 10−3). (PNG 97 kb)
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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Zhou Zhang
    • 1
    • 2
  • Yinan Zheng
    • 2
    • 3
  • Xu Zhang
    • 4
  • Cong Liu
    • 5
  • Brian Thomas Joyce
    • 2
    • 6
  • Warren A. Kibbe
    • 7
  • Lifang Hou
    • 2
    • 8
  • Wei Zhang
    • 2
    • 8
    • 9
    Email author
  1. 1.Driskill Graduate Program in Life SciencesNorthwestern University Feinberg School of MedicineChicagoUSA
  2. 2.Department of Preventive MedicineNorthwestern University Feinberg School of MedicineChicagoUSA
  3. 3.Institute for Public Health and Medicine, Feinberg School of MedicineNorthwestern UniversityChicagoUSA
  4. 4.Section of Hematology/Oncology, Department of MedicineUniversity of Illinois at ChicagoChicagoUSA
  5. 5.Department of BioengineeringUniversity of Illinois at ChicagoChicagoUSA
  6. 6.Division of Epidemiology and Biostatistics, School of Public HealthUniversity of Illinois at ChicagoChicagoUSA
  7. 7.Center for Biomedical Informatics and Information TechnologyNational Cancer InstituteRockvilleUSA
  8. 8.The Robert H. Lurie Comprehensive Cancer CenterNorthwestern University Feinberg School of MedicineChicagoUSA
  9. 9.Center for Genetic MedicineNorthwestern University Feinberg School of MedicineChicagoUSA

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