Using network modeling to identification immunomodulators of induced immune response under stress condition

سال انتشار: 1396
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 508

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شناسه ملی سند علمی:

ICAENR01_017

تاریخ نمایه سازی: 13 شهریور 1396

چکیده مقاله:

RNA-Seq is a revolutionary DNA sequencing technology recently developed that provides a large amount of gene expression information. Bayesian network is one of the statistical approaches that used for extracting meaningful biological knowledge from this information by predicts interactions between genes. In current study we focused on Bayesian gene network on bovine leukocytes RNA-seq data to reflect the major genes that affect immune system under weaning stress. Gene detection and level of gene expression was performed by Tophat2 and HTseq. Bayesian network was constructed on genes with differential expression by networkBMA package. Genes that expressed as regulators in this network usually have conserved sequence and effect on immune function by influencing apoptosis, RNA splicing, DNA repairing and regulating cell division. It is recommended that these genes can be used in gene assessed selection, designing of microarray and genomic selection by researching on these genes polymorphisms and evaluating relationship between different alleles and immune response.

نویسندگان

Elham Behdani

Department of Animal Sciences, faculty of Agriculture and Natural Resources, Ramin University, Khozestan, Iran

Hedayatallah Roshanfekr

Department of Animal Sciences, faculty of Agriculture and Natural Resources, Ramin University, Khozestan, Iran

Mostafa Ghaderi-Zefrehei

Department of Animal Sciences, faculty of Agriculture and Natural Resources, Yasouj University, Yasouj, Iran