An online conserved SSR discovery through cross-species comparison

Abstract

Simple sequence repeats (SSRs) play important roles in gene regulation and genome evolution. Although there exist several online resources for SSR mining, most of them only extract general SSR patterns without providing functional information. Here, an online search tool, CG-SSR (Comparative Genomics SSR discovery), has been developed for discovering potential functional SSRs from vertebrate genomes through cross-species comparison. In addition to revealing SSR candidates in conserved regions among various species, it also combines accurate coordinate and functional genomics information. CG-SSR is the first comprehensive and efficient online tool for conserved SSR discovery.

Efficient algorithms for identifying orthologous simple sequence repeats of disease genes

“…This information facilitates the proposed system to aid in demarcation and comprehension of the distinct parts of a gene (upstream, downstream, 3' UTR, 5' UTR, intron, coding). For SSR information, the OSDG integrated with the CGSSR searching system that contributes all SSR motifs among multiple species [22] . Each SSR record includes information about the core repeat pattern, core pattern length, location on the chromosome, and ratio of tolerance.…”

“…The second phase, overlapped adjacency analysis, contains record merging, cutting, and threshold filtering processes that verify overlapped segments and confirm that there are no redundant perfect/imperfect SSR patterns. Extensive procedural details about these 2 phases, of which only overviews are provided here, can be found in the work by Pai, et al [22] .…”

“…These systems include Sputnik [32] , TRF [33] , STRING [34] , Mreps [35] , ATRHunter [36] , Msatfinder [37] , TandemSWAN [38] , SciRoKo [39] , IMEx [40] , and our proposed CGSSR algorithms [22] . Here we randomly selected 3 DNA segments with lengths of 1,000,000 nucleotides from zebrafish (Zv7, chr19: 10233602-11233601, named seq1), mouse (mm9, chr16: 11256954-12256953, named seq2), and human (hg18, chr19: 46606207-47606206, named seq3).…”

“…To identify the potential functional SSR patterns for genetic disorders based on a genomics comparison mechanism, the proposed system was developed by employing the online Mendelian inheritance in man (OMIM) [20] and HomoloGene databases [21] for resources of human genetic diseases and homologous gene information. In addition, we developed efficient SSR searching algorithms for identifying perfect and imperfect SSR patterns from various genomes and constitute a significant SSR database through cross-species comparison [22] .…”

A Comprehensive System for Identifying Internal Repeat Substructures of Proteins

“…Several implementations were designed at the DNA level, such as Reputer [9], CGSSR [10], Repseek [11], while Swelfe [12], REPRO [13], and REPETITA [14] performed at the structure level. Traditional approaches for identifying internal repeats were based on sequence alignment strategies, especially when coping with protein sequences without resolved protein structures.…”