MicroRNAs (miRNAs) are a class of non-coding RNAs that regulate gene post-transcriptional expres- sion in plants and animals. Low levels of some miRNAs and time- and tissue-specific expression pat- terns lead to the d...MicroRNAs (miRNAs) are a class of non-coding RNAs that regulate gene post-transcriptional expres- sion in plants and animals. Low levels of some miRNAs and time- and tissue-specific expression pat- terns lead to the difficulty for experimental identification of miRNAs. Here we present a bioinformatic approach for expressed sequence tags (ESTs) prediction of novel miRNAs as well as their targets in Solanum tuberosum. We blasted the databases of S. tuberosum ESTs to search for potential miRNAs, using previously known miRNA sequences from Arabidopsis, rice and other plant species. By analyzing parameters of plant precursors, including secondary structure, stem length and conservation of miRNAs, and following a variety of filtering criteria, a total of 22 potential miRNAs were detected. Using the newly identified miRNA sequences, we were able to further blast the S. tuberosum mRNA database and detected 75 potential targets of miRNAs in S. tuberosum. According to the mRNA annotations provided by the National Center for Biotechnology Information (NCBI) (http://www.ncbi.nlm.nih.gov/), most of the miRNA target genes were predicted to encode transcription factors that regulate cell growth and development, signaling, and metabolism.展开更多
文摘MicroRNAs (miRNAs) are a class of non-coding RNAs that regulate gene post-transcriptional expres- sion in plants and animals. Low levels of some miRNAs and time- and tissue-specific expression pat- terns lead to the difficulty for experimental identification of miRNAs. Here we present a bioinformatic approach for expressed sequence tags (ESTs) prediction of novel miRNAs as well as their targets in Solanum tuberosum. We blasted the databases of S. tuberosum ESTs to search for potential miRNAs, using previously known miRNA sequences from Arabidopsis, rice and other plant species. By analyzing parameters of plant precursors, including secondary structure, stem length and conservation of miRNAs, and following a variety of filtering criteria, a total of 22 potential miRNAs were detected. Using the newly identified miRNA sequences, we were able to further blast the S. tuberosum mRNA database and detected 75 potential targets of miRNAs in S. tuberosum. According to the mRNA annotations provided by the National Center for Biotechnology Information (NCBI) (http://www.ncbi.nlm.nih.gov/), most of the miRNA target genes were predicted to encode transcription factors that regulate cell growth and development, signaling, and metabolism.
