Assessment of simple sequence repeats signature in hepatitis E virus (HEV) genomes

Abstract

Background Hepatitis E virus (HEV) is small (27–34 nm diameter) non-enveloped with positive sense ssRNA genome. Microsatellites or simple sequence repeats (SSR) are short tandem repeat sequences present across coding and non-coding regions of both prokaryotes and eukaryotes. They are involved with genome function and evolution at multiple levels. Results The complete genome sequences of 22 HEV genomes of the family Hepeviridae and genus Orthohepevirus (21 species) and Piscihepevirus (1 species) were extracted from NCBI database (http://www.ncbi.nlm.nih.gov/). The extraction of microsatellites was done using Imperfect Microsatellite Extractor (IMEx) in ‘Advance-Mode’. The average genome size of the studied HEV genomes was 7003nt and it ranged from 6649nt (HEV11) to 7310nt (HEV22). The average GC content of the genomes was ~ 55%. A total of 519 SSRs and 21 cSSRS were extracted from the HEV genomes with an average incidence of 24 per genome ranging from 14 (HEV13) to 34 (HEV19). The cSSR incidence ranged from 0 (eight species) to 4 (HEV19). The genomes with no cSSR incidence had an SSR incidence range from 14 to 28. There were just four hexa-nucleotide repeat motifs and 5 penta-nucleotide repeat motifs observed. The most prevalent mono-, di-, and tri-nucleotide repeat motifs were “C”, “GT/TG”, and “GAC/CTG” respectively. The studied genomes had a minimum of ~ 90% incident SSRs present in the coding regions. Viruses with same or similar hosts are placed together on the phylogenetic tree implicating viral host being one of the driving forces for evolution. Conclusions Host range in viruses is being decided by multiple factors aided by the unique genome SSR signature and genomes of varied compositions need to be analyzed to forge a widely acceptable rule for predicting the same.

EasySSR: a user-friendly web application with full command-line features for large-scale batch microsatellite mining and samples comparison

“… Laskar et al (2021) , ( 2022 ), Jilani and Ali (2022) used similar information about incidence, prevalence, composition, and localization in their studies of Simple Sequence Repeats Signature in viruses using IMEx. Those analyses might seem basic, but they require a lot of data tabulation before the tables are ready for analysis, a feature that is already automated by EasySSR.…”

“…It is possible to notice that when mismatches were allowed in a tract, EasySSR through the IMEx algorithm could extend tracts that were previously interrupted by an imperfection and considered as perfect because it had passed the repetition cutoff when they were actually part of longer imperfect tracts; thus, the average amount of perfect SSRs per genome decreased from 53.5 to 40 in the analysis that included imperfections. Laskar et al (2021Laskar et al ( ), (2022, Jilani and Ali (2022) used similar information about incidence, prevalence, composition, and localization in their studies of Simple Sequence Repeats Signature in viruses using IMEx. Those analyses might seem basic, but they require a lot of data tabulation before the tables are ready for analysis, a feature that is already automated by EasySSR.…”

Systems biology of the genomes’ microsatellite signature of Orthopoxvirus including the Monkeypox virus

“…In terms of motif composition of SSRs, we observed that found all the mono-nucleotide SSRs were almost exclusively localized to the A/T region. This is significant because when viruses have human and related hosts, the mono-nucleotide SSRs are either exclusively or predominantly present in the A/T region of the genome irrespective of the genome GC% [15] , [16] , [17] . Amongst the di-nucleotide repeats motif, AT/TA has high prevalence of 63% which can serve as hotspots for mutation and genome evolution [29] , [30] .…”

“…They have greater role (10–100-fold) in mutation in coding region than another part of genomic region [13] . The pattern and distribution of SSRs has also been used as marker for speciation, host divergence and evolution [14] , [15] , [16] , [17] , [18] , [19] .…”