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      Comprehensive analysis of differentially expressed profiles of non-coding RNAs in peripheral blood and ceRNA regulatory networks in non-syndromic orofacial clefts

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          Abstract

          Non-syndromic orofacial clefts (NSOC), which include cleft lip with or without cleft palate (CL/P) and cleft palate only (CPO), are common congenital birth defects in humans. Accumulating evidence indicates that long non-coding RNAs (lncRNAs) and microRNAs (miRNAs or miRs) play important roles in NSOC; however, the potential regulatory associations between them remain largely unknown. In this study, we performed next-generation RNA sequencing (RNA-seq) to identify transcriptome profiles, including mRNAs, lncRNAs and miRNAs, in patients with CL/P and CPO. A total of 36 lncRNAs, 1,341 mRNAs and 60 miRNAs were found to be differentially expressed in the CL/P group compared to the control group, and 57 lncRNAs, 1,255 mRNAs and 162 miRNAs were found to be differentially expressed in the CPO group compared to the control group. Subsequently, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed to validate the expression of selected lncRNAs, miRNAs and mRNAs. In addition, bioinformatics methods were employed to explore the potential functions of ncRNAs and to construct lncRNA-miRNA-mRNA regulatory networks. To the best of our knowledge, this is the first study to comprehensively analyze regulated non-coding RNAs (ncRNAs) in CL/P and CPO, providing a novel perspective on the etiology of NSOC and laying the foundation for future research into the potential regulatory mechanisms of ncRNAs and mRNAs in NSOC.

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          Most cited references48

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          PhyloCSF: a comparative genomics method to distinguish protein coding and non-coding regions

          Motivation: As high-throughput transcriptome sequencing provides evidence for novel transcripts in many species, there is a renewed need for accurate methods to classify small genomic regions as protein coding or non-coding. We present PhyloCSF, a novel comparative genomics method that analyzes a multispecies nucleotide sequence alignment to determine whether it is likely to represent a conserved protein-coding region, based on a formal statistical comparison of phylogenetic codon models. Results: We show that PhyloCSF's classification performance in 12-species Drosophila genome alignments exceeds all other methods we compared in a previous study. We anticipate that this method will be widely applicable as the transcriptomes of many additional species, tissues and subcellular compartments are sequenced, particularly in the context of ENCODE and modENCODE, and as interest grows in long non-coding RNAs, often initially recognized by their lack of protein coding potential rather than conserved RNA secondary structures. Availability and Implementation: The Objective Caml source code and executables for GNU/Linux and Mac OS X are freely available at http://compbio.mit.edu/PhyloCSF Contact: mlin@mit.edu; manoli@mit.edu
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            Transcriptomics technologies

            Transcriptomics technologies are the techniques used to study an organism’s transcriptome, the sum of all of its RNA transcripts. The information content of an organism is recorded in the DNA of its genome and expressed through transcription. Here, mRNA serves as a transient intermediary molecule in the information network, whilst noncoding RNAs perform additional diverse functions. A transcriptome captures a snapshot in time of the total transcripts present in a cell. The first attempts to study the whole transcriptome began in the early 1990s, and technological advances since the late 1990s have made transcriptomics a widespread discipline. Transcriptomics has been defined by repeated technological innovations that transform the field. There are two key contemporary techniques in the field: microarrays, which quantify a set of predetermined sequences, and RNA sequencing (RNA-Seq), which uses high-throughput sequencing to capture all sequences. Measuring the expression of an organism’s genes in different tissues, conditions, or time points gives information on how genes are regulated and reveals details of an organism’s biology. It can also help to infer the functions of previously unannotated genes. Transcriptomic analysis has enabled the study of how gene expression changes in different organisms and has been instrumental in the understanding of human disease. An analysis of gene expression in its entirety allows detection of broad coordinated trends which cannot be discerned by more targeted assays.
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              Transcriptome analysis using next-generation sequencing.

              Up to date research in biology, biotechnology, and medicine requires fast genome and transcriptome analysis technologies for the investigation of cellular state, physiology, and activity. Here, microarray technology and next generation sequencing of transcripts (RNA-Seq) are state of the art. Since microarray technology is limited towards the amount of RNA, the quantification of transcript levels and the sequence information, RNA-Seq provides nearly unlimited possibilities in modern bioanalysis. This chapter presents a detailed description of next-generation sequencing (NGS), describes the impact of this technology on transcriptome analysis and explains its possibilities to explore the modern RNA world. Copyright © 2012 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                Mol Med Rep
                Mol Med Rep
                Molecular Medicine Reports
                D.A. Spandidos
                1791-2997
                1791-3004
                July 2019
                22 May 2019
                22 May 2019
                : 20
                : 1
                : 513-528
                Affiliations
                [1 ]Department of Oral Maxillofacial Surgery, The First Affiliated Hospital, Harbin Medical University, Harbin, Heilongjiang 150001, P.R. China
                [2 ]Laboratory of Medical Genetics, Harbin Medical University, Harbin, Heilongjiang 150081, P.R. China
                [3 ]Department of Oral Maxillofacial Surgery, The Fourth Affiliated Hospital, Harbin Medical University, Harbin, Heilongjiang 150001, P.R. China
                Author notes
                Correspondence to: Professor Xiaohui Jiao, Department of Oral Maxillofacial Surgery, The First Affiliated Hospital, Harbin Medical University, 23 Youzheng Street, Nangang, Harbin, Heilongjiang 150001, P.R. China, E-mail: jiaoxiaohui_dds@ 123456163.com
                Article
                mmr-20-01-0513
                10.3892/mmr.2019.10261
                6579990
                31115538
                0e73088f-d17e-486c-a6ce-b48f08cc46ee
                Copyright: © Gao et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

                History
                : 04 November 2018
                : 11 April 2019
                Categories
                Articles

                long non-coding rna,microrna,mrna,rna sequencing,cerna,non-syndromic orofacial clefts

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