Gene Ontology Based Clustering Analysis for Functionally Linked Genes and Cross-Species Comparison for SSR Biomarkers

• Published in: 2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS) pp. 215 - 218
• Main Authors: Yang-Chun Chang, Chien-Ming Chen, Tun-Wen Pai, Ronshan Cheng, Ming-Hsiung Chiu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2016
• Subjects: Bioinformatics; gene ontology; Genomics; molecular biomarkers; Ontologies; orthologous gene; short sequence repeat
• DOI: 10.1109/CISIS.2016.71

Molecular biomarkers are important and commonly used as classification features for detecting function performances of target genes and distinguishing characteristics of different species or strains. As expeditious development in Next Generation Sequencing technologies, whole genome sequencing delivers a comprehensive view and new insights for novel species. However, utilization of whole genome sequences to discover genetic biomarkers for specific functional gene groups still possess many challenges. To solve this problem, we utilized Gene Ontology definitions and Ensembl orthologous information to decide a set of associated functional genes according to user's query keywords. Then, previously assembled NGS contigs were matched against the selected gene set from model species, and an SSR searching algorithm and a cross-species comparison mechanism were performed to reveal potential polymorphic SSR biomarkers. Each identified SSR would be annotated and classified by important attributes, such as lengths, genetic locations, fundamental repeat patterns, tolerant rates of retrieved SSRs. The developed system could identify novel SSR biomarkers for a specified functional gene group regarding conserved and unique features between the query and the target model species, and which could facilitate biologists in finding potential markers for elucidating biological functions and distinguishable features of a novel species.