Translational medicine is a new discipline aiming to elimi- nate the barrier between preclinical and clinical medicine . It converts promising laboratory discoveries into clini-cal applications and elucidates clinical questions with the use of benchwork, aiming to facilitate prediction, preven-tion, diagnosis, and treatment of diseases . The Director of US National Institutes of Health （NIH）, Dr.
Eukaryotic mRNAs consist of two forms of transcripts:poly(A)+ and poly(A),based on the presence or absence of poly(A) tails at the 3 end.Poly(A)+ mRNAs are mainly protein coding mRNAs,whereas the functions of poly(A) mRNA are largely unknown.Previous studies have shown that a significant proportion of gene transcripts are poly(A) or bimorphic(containing both poly(A)+ and poly(A) transcripts).We compared the expression levels of poly(A) and poly(A)+ RNA mRNAs in normal and cancer cell lines.We also investigated the potential functions of these RNA transcripts using an integrative workflow to explore poly(A)+ and poly(A) transcriptome sequences between a normal human mammary gland cell line(HMEC) and a breast cancer cell line(MCF-7),as well as between a normal human lung cell line(NHLF) and a lung cancer cell line(A549).The data showed that normal and cancer cell lines differentially express these two forms of mRNA.Gene ontology(GO) annotation analyses hinted at the functions of these two groups of transcripts and grouped the differentially expressed genes according to the form of their transcript.The data showed that cell cycle-,apoptosis-,and cell death-related functions corresponded to most of the differentially expressed genes in these two forms of transcripts,which were also associated with the cancers.Furthermore,translational elongation and translation functions were also found for the poly(A) protein-coding genes in cancer cell lines.We demonstrate that poly(A) transcripts play an important role in cancer development.
Mammalian genomes contain tens of thousands of long non-coding RNAs(lnc RNAs) that have been implicated in diverse biological processes. However, the lnc RNA transcriptomes of most mammalian species have not been established, limiting the evolutionary annotation of these novel transcripts. Based on RNA sequencing data from six tissues of nine species, we built comprehensive lnc RNA catalogs(4,142–42,558 lnc RNAs) covering the major mammalian species. Compared to protein-coding RNAs, expression of lnc RNAs exhibits striking lineage specificity. Notably, although 30%–99% human lnc RNAs are conserved across different species on DNA locus level, only 20%–27% of these conserved lnc RNA loci are detected to transcription, which represents a stark contrast to the proportion of conserved protein-coding genes(48%–80%). This finding provides a valuable resource for experimental scientists to study the mechanisms of lnc RNAs. Moreover, we constructed lnc RNA expression phylogenetic trees across nine mammals and demonstrated that lnc RNA expression profiles can reliably determine phylogenic placement in a manner similar to their coding counterparts. Our data also reveal that the evolutionary rate of lnc RNA expression varies among tissues and is significantly higher than those for protein-coding genes. To streamline the processes of browsing lnc RNAs and detecting their evolutionary statuses, we integrate all the data produced in this study into a database named Phylo NONCODE(http://www.bioinfo.org/phylo Noncode). Our work starts to place mammalian lnc RNAs in an evolutionary context and represent a rich resource for comparative and functional analyses of this critical layer of genome.
BU DeChaoLUO HaiTaoJIAO FeiFANG ShuangSangTAN ChengFuLIU ZhiYongZHAO Yi
