Identification of SNP-containing regulatory motifs in the myelodysplastic syndromes model using SNP arrays ad gene expression arrays Article

Open Access

cited authors

  • Fan, Jing, Dy, Jennifer G., Chang, Chung-Che, Zhou, Xiaobo

funding text

  • The author would like to thank Dr. Ling-Yun Wu with Institute of Applied Mathematics, Chinese Academy of Science and Dr. Xiao-Rong Yang with Zhejiang Gong-shang University for their suggestions and colleagues at The Methodist Hospital Research Institute, for their discussion in the research. This work was partially supported by grants from NIH (No. 1R01LM010185, 1U01CA166886, and 1U01HL111560).

abstract

  • Myelodysplastic syndromes have increased in frequency and incidence in the American population, but patient prognosis has not significantly improved over the last decade. Such improvements could be realized if biomarkers for accurate diagnosis and prognostic stratification were successfully identified. In this study, we propose a method that associates two state-of-the-art array technologies-single nucleotide polymor-phism (SNP) array and gene expression array-with gene motifs considered transcription factor-binding sites (TFBS). We are particularly interested in SNP-containing motifs introduced by genetic variation and mutation as TFBS. The potential regulation of SNP-containing motifs affects only when certain mutations occur. These motifs can be identified from a group of co-expressed genes with copy number variation. Then, we used a sliding window to identify motif candidates near SNPs on gene sequences. The candidates were filtered by coarse thresholding and fine statistical testing. Using the regression. based LARS-EN algorithm and a level. wise sequence combination procedure, we identified 28 SNP-containing motifs as candidate TFBS. We confirmed 21 of the 28 motifs with ChIP-chip fragments in the TRANSFAC database. Another six motifs were validated by TRANSFAC via searching binding fragments on co-regulated genes. The identified motifs and their location genes can be considered potential biomarkers for myelodysplastic syndromes. Thus, our proposed method, a novel strategy for associating two data categories, is capable of integrating information from different sources to identify reliable candidate regulatory SNP-containing motifs introduced by genetic variation and mutation.

authors

Publication Date

  • April 1, 2013

webpage

published in

category

start page

  • 170

end page

  • 185

volume

  • 32

issue

  • 4

WoS Citations

  • 2

WoS References

  • 34