Gene Regulatory Elements Extraction in Breast Cancer by Hi-C Data Using a Meta-Heuristic Method

Abstract

Detection of gene regulatory elements and the interactions among them may be conducive to diagnosis and treatment of many diseases and maladies as cancer. In this regards, Hi-C techniques such as HiCUP, HiC-Pro, HiC-bench, etc., are capable of detecting the gene regulatory elements and their interactions. Extracting only the fixed length gene regulatory elements, these techniques are not able to detect many of gene regulatory elements as they may be of variable-lengths. In this research, we intend to use a two-objective Meta heuristic method based on simulation annealing to provide a method capable of detecting and extracting sequences of variable-length regulators from the genome, and also calculating the interactions between them. In fact, these gene regulatory elements can be potential promoters/enhancers that could play a significant role in the incidence and exacerbation of cancer. To measure the performance and effectiveness of the suggested method, the proposed method is implemented on Hi-C data regarding patients with breast cancer in two blood cells GM12878 and CD34⁺. Then, the results of implementing the proposed method are compared with the HiCUP and HiC-Pro methods. The results show that the proposed method has a better performance than the HiCUP and HiC-Pro methods. In addition, the proposed method has been investigated for the detection and extraction of gene regulatory elements involved in the occurrence and exacerbation of this type of cancer. Experimental studies have shown that the two promoters BLC6 and HOTTIP discovered by the proposed method have had a significant effect on the incidence and severity of breast cancer in the both genetically engineered blood cells GM12878 and CD34⁺.