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Dominant transcript expression profiles of human protein-coding genes interrogated with GTEx dataset.
Tung, Kuo-Feng; Pan, Chao-Yu; Lin, Wen-Chang.
Afiliação
  • Tung KF; Institute of Biomedical Sciences, Academia Sinica, Taipei, 115, Taiwan, R.O.C.
  • Pan CY; Institute of Biomedical Sciences, Academia Sinica, Taipei, 115, Taiwan, R.O.C.
  • Lin WC; Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan, R.O.C.
Sci Rep ; 12(1): 6969, 2022 04 28.
Article em En | MEDLINE | ID: mdl-35484179
ABSTRACT
The discovery and quantification of mRNA transcripts using short-read next-generation sequencing (NGS) data is a complicated task. There are far more alternative mRNA transcripts expressed by human genes than can be identified from NGS transcriptome data and various bioinformatic pipelines, while the numbers of annotated human protein-coding genes has gradually declined in recent years. It is essential to learn more about the thorough tissue expression profiles of alternative transcripts in order to obtain their molecular modulations and actual functional significance. In this report, we present a bioinformatic database for interrogating the representative tissue of human protein-coding transcripts. The database allows researchers to visually explore the top-ranked transcript expression profiles in particular tissue types. Most transcripts of protein-coding genes were found to have certain tissue expression patterns. This observation demonstrated that many alternative transcripts were particularly modulated in different cell types. This user-friendly tool visually represents transcript expression profiles in a tissue-specific manner. Identification of tissue specific protein-coding genes and transcripts is a substantial advance towards interpreting their biological functions and further functional genomics studies.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sequenciamento de Nucleotídeos em Larga Escala / Transcriptoma Limite: Humans Idioma: En Revista: Sci Rep Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sequenciamento de Nucleotídeos em Larga Escala / Transcriptoma Limite: Humans Idioma: En Revista: Sci Rep Ano de publicação: 2022 Tipo de documento: Article