Prediction and verification of mouse tRNAs identifies intron-containing families. Mus musculus

Computer algorithms are often used to identify tRNA genes in newly sequenced genomes, but these predictions can be challenging. Not only are there structural variations and extremely limited sequence conservation among genes, but vertebrate genomes tend to have highly reiterated short interspersed sequences (SINEs) that originally derived from tRNA genes or tRNA-like transcription units. We have employed two programs, tRNAScan SE and ARAGORN, to predict the tRNA genes in the mouse nuclear genome, resulting in quite diverse but overlapping predicted gene sets. From these, we removed known SINE repeats and sorted the genes into predicted families and single-copy genes. In particular, four families of intron-containing tRNA genes were predicted, with introns in positions and structures analogous to the well characterized intron-containing tRNA genes in yeast. In this work we focus on verifying the expression of the intron-containing tRNA gene familes, as well as the other 30 tRNA gene familes. Keywords: tRNA, direct label Overall design: Total RNa from 12 tissues was screened by microarray for predicted tRNAs.

计算机算法常被用于在新测序的基因组中识别转移RNA（tRNA）基因，但此类预测颇具挑战性。不仅这类基因存在结构变异且序列保守性极低，脊椎动物基因组中还往往存在大量源自tRNA基因或类tRNA转录单元的高度重复短散在序列（SINEs）。本研究采用tRNAScan SE与ARAGORN两款软件，对小鼠核基因组中的tRNA基因进行预测，得到了一组多样性较高但存在重叠的预测基因集。我们从中移除了已知的SINE重复序列，并将预测得到的基因划分为基因家族与单拷贝基因两类。尤为关键的是，本研究预测得到了4个携带内含子的tRNA基因家族，其内含子的位置与结构与已被充分研究的酵母内含子tRNA基因高度相似。本研究重点验证了上述携带内含子的tRNA基因家族，以及其余30个tRNA基因家族的表达情况。关键词：tRNA、直接标注 实验设计：采用微阵列技术，针对12种组织中的总RNA，对预测得到的tRNA进行筛选检测。