Targeted screening of cis-regulatory variation in human haplotypes (original) (raw)

  1. Dominique J. Verlaan1,2,3,5,
  2. Bing Ge2,5,
  3. Elin Grundberg1,2,
  4. Rose Hoberman1,
  5. Kevin C.L. Lam2,
  6. Vonda Koka2,
  7. Joana Dias2,
  8. Scott Gurd2,
  9. Nicolas W. Martin2,
  10. Hans Mallmin4,
  11. Olof Nilsson4,
  12. Eef Harmsen2,
  13. Ken Dewar1,2,
  14. Tony Kwan2 and
  15. Tomi Pastinen1,2,6
  16. 1 Department of Human Genetics, McGill University, Montréal H3A 1B1, Canada;
  17. 2 McGill University and Genome Québec Innovation Centre, Montréal H3A 1A4, Canada;
  18. 3 Hôpital Ste-Justine, Université de Montréal, Montréal H3T 1C5, Canada;
  19. 4 Department of Surgical Sciences, Uppsala University, Uppsala SE-75185, Sweden
  20. ↵5 These authors contributed equally to this work.

Abstract

Regulatory _cis-_acting variants account for a large proportion of gene expression variability in populations. _Cis-_acting differences can be specifically measured by comparing relative levels of allelic transcripts within a sample. Allelic expression (AE) mapping for _cis-_regulatory variant discovery has been hindered by the requirements of having informative or heterozygous single nucleotide polymorphisms (SNPs) within genes in order to assign the allelic origin of each transcript. In this study we have developed an approach to systematically screen for heritable _cis-_variants in common human haplotypes across >1000 genes. In order to achieve the highest level of information per haplotype studied, we carried out allelic expression measurements by using both intronic and exonic SNPs in primary transcripts. We used a novel RNA pooling strategy in immortalized lymphoblastoid cell lines (LCLs) and primary human osteoblast cell lines (HObs) to allow for high-throughput AE. Screening hits from RNA pools were further validated by performing allelic expression mapping in individual samples. Our results indicate that >10% of expressed genes in human LCLs show genotype-linked AE. In addition, we have validated _cis-_acting variants in over 20 genes linked with common disease susceptibility in recent genome-wide studies. More generally, our results indicate that RNA pooling coupled with AE read-out by second generation sequencing or by other methods provides a high-throughput tool for cataloging the impact of common noncoding variants in the human genome.

Footnotes