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      Transcriptomic analysis of the upper lip and primary palate development in mice

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          Abstract

          Background: Normal fusion of the upper lip and primary palate is a complex process involving a series of characteristic and orderly regulated cellular events. Cleft lip with or without palate (CL/P), one of the most common congenital malformations, may be induced by abnormalities in any of these events. However, less is known about the precise regulatory process in the fusion of the upper lip and primary palate.

          Methods: Lambdoidal junction tissues of mice from embryonic days 10.5, 11.5, and 12.5— three key fusion stages—were acquired for RNA sequencing.

          Results: Gene expression profiles in distinct fusion stages of mice were identified. Some of the differentially expressed genes (DEGs) have been reported to affect upper lip and primary palate development. However, other DEGs, such as Krt5, Pax1, Ambn, Hey2, and Tnmd, have not previously been investigated. Gene set enrichment analysis (GSEA) of these DEGs revealed the sequential intensification of Wnt, PI3K-Akt, MAPK, Hippo, and TGF-beta signaling pathways and identified relatively highly expressed genes including Tnn, Wnt3a, and Wnt16. We also observed substantial alternative splicing events during the fusion of the upper lip and primary palate and identified potentially important genes including Gtpbp8, Armcx1, Tle3, and Numa1. Protein-protein interaction (PPI) network analysis identified a series of hub genes, including Col1a2, Fos, Bmp2, Shh, Col1a1, Wnt3a, Anxa1, Gem, etc.

          Conclusion: Overall, the results of this study provided a comprehensive analysis of the development of the upper lip and primary palate. Our work provides insight into future studies of normal upper lip and primary palate development and the etiology of CL/P.

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          Most cited references44

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            clusterProfiler: an R package for comparing biological themes among gene clusters.

            Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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              rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data.

              Ultra-deep RNA sequencing (RNA-Seq) has become a powerful approach for genome-wide analysis of pre-mRNA alternative splicing. We previously developed multivariate analysis of transcript splicing (MATS), a statistical method for detecting differential alternative splicing between two RNA-Seq samples. Here we describe a new statistical model and computer program, replicate MATS (rMATS), designed for detection of differential alternative splicing from replicate RNA-Seq data. rMATS uses a hierarchical model to simultaneously account for sampling uncertainty in individual replicates and variability among replicates. In addition to the analysis of unpaired replicates, rMATS also includes a model specifically designed for paired replicates between sample groups. The hypothesis-testing framework of rMATS is flexible and can assess the statistical significance over any user-defined magnitude of splicing change. The performance of rMATS is evaluated by the analysis of simulated and real RNA-Seq data. rMATS outperformed two existing methods for replicate RNA-Seq data in all simulation settings, and RT-PCR yielded a high validation rate (94%) in an RNA-Seq dataset of prostate cancer cell lines. Our data also provide guiding principles for designing RNA-Seq studies of alternative splicing. We demonstrate that it is essential to incorporate biological replicates in the study design. Of note, pooling RNAs or merging RNA-Seq data from multiple replicates is not an effective approach to account for variability, and the result is particularly sensitive to outliers. The rMATS source code is freely available at rnaseq-mats.sourceforge.net/. As the popularity of RNA-Seq continues to grow, we expect rMATS will be useful for studies of alternative splicing in diverse RNA-Seq projects.
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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                06 January 2023
                2022
                : 13
                : 1039850
                Affiliations
                [1] 1 The Department of Cleft Lip and Palate of Plastic Surgery Hospital , Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing, China
                [2] 2 Research Center of Plastic Surgery Hospital , Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing, China
                Author notes

                Edited by: Rafael Denadai, A&D DermePlastique, Brazil

                Reviewed by: Irfan Saadi, University of Kansas Medical Center, United States

                Makoto Kashima, Aoyama Gakuin University, Japan

                *Correspondence: Ningbei Yin, yin_nb@ 123456126.com

                This article was submitted to Genetics of Common and Rare Diseases, a section of the journal Frontiers in Genetics

                Article
                1039850
                10.3389/fgene.2022.1039850
                9852879
                36685938
                a712bee3-2606-41c7-9dc2-3285ee9f33c0
                Copyright © 2023 Cai, Si, Wang and Yin.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 08 September 2022
                : 14 December 2022
                Categories
                Genetics
                Original Research

                Genetics
                cleft lip with or without cleft palate,rna sequencing,gene expression profile,development,upper lip and primary palate

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