Comparative in silico analysis of SSRs in coding regions of high confidence predicted genes in Norway spruce (Picea abies) and Loblolly pine (Pinus taeda) Sonali Sachin Ranade
Microsatellites or simple sequence repeats (SSRs) are DNA sequences consisting of 1-6 bp tandem repeat motifs present in the genome. SSRs are considered to be one of the most powerful tools in genetic studies. We carried out a comparative study of perfect SSR loci belonging to class I (?20) and class II (≥12 and <20 bp) types located in coding regions of high confidence genes in Picea abies and Pinus taeda. SSRLocator was used to retrieve SSRs from the full length CDS of predicted genes in both species.
Trimers were the most abundant motifs in class I followed by hexamers in Picea abies, while trimers and hexamers were equally abundant in Pinus taeda class I SSRs. Hexamers were most frequent within class II SSRs followed by trimers, in both species. Although the frequency of genes containing SSRs was slightly higher in Pinus taeda, SSR counts per Mbp for class I was similar in both species (P-value?=?0.22); while for class II SSRs, it was significantly higher in Picea abies (P-value?=?0.00009). AT-rich motifs were higher in abundance than the GC-rich motifs, within class II SSRs in both the species (P-values?=?10(-9) and 0). With reference to class I SSRs, AT-rich and GC-rich motifs were detected with equal frequency in Pinus taeda (P-value?=?0.24); while in Picea abies, GC-rich motifs were detected with higher frequency than the AT-rich motifs (P-value?=?0.0005).
Our study gives a comparative overview of the genome SSRs composition based on high confidence genes in the two recently sequenced and economically important conifers and, also provides information on functional molecular markers that can be applied in genetic studies in Pinus and Picea species.
Lin, Y.-C., Van de Peer, Y., García-Gil, M. (2015) Comparative in silico analysis of SSRs in coding regions of high confidence predicted genes in Norway spruce (Picea abies) and Loblolly pine (Pinus taeda) Sonali Sachin Ranade. BMC Genetics 16(1):149.
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