• Animal Bioscience
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• 제34권11호
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• pp.1739-1748
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• 2021

Objective: In recent years, long noncoding RNAs (lncRNAs) have been identified in many species, and some of them have been shown to play important roles in muscle development and myogenesis. However, the differences in lncRNAs between Kazakh cattle and Xinjiang brown cattle remain undefined; therefore, we aimed to confirm whether lncRNAs are differentially expressed in the longissimus dorsi between these two types of cattle and whether differentially expressed lncRNAs regulate muscle differentiation. Methods: We used RNA-seq technology to identify lncRNAs in longissimus muscles from these cattle. The expression of lncRNAs were analyzed using StringTie (1.3.1) in terms of the fragments per kilobase of transcript per million mapped reads values of the encoding genes. The differential expression of the transcripts in the two samples were analyzed using the DESeq R software package. The resulting false discovery rate was controlled by the Benjamini and Hochberg's approach. KOBAS software was utilized to measure the expression of different genes in Kyoto encyclopedia of genes and genomes pathways. We randomly selected eight lncRNA genes and validated them by quantitative reverse transcription polymerase chain reaction (RT-qPCR). Results: We found that 182 lncRNA transcripts, including 102 upregulated and 80 downregulated transcripts, were differentially expressed between Kazakh cattle and Xinjiang brown cattle. The results of RT-qPCR were consistent with the sequencing results. Enrichment analysis and functional annotation of the target genes revealed that the differentially expressed lncRNAs were associated with the mitogen-activated protein kinase, Ras, and phosphatidylinositol 3-kinase (PI3k)/Akt signaling pathways. We also constructed a lncRNA/mRNA coexpression network for the PI3k/Akt signaling pathway. Conclusion: Our study provides insights into cattle muscle-associated lncRNAs and will contribute to a more thorough understanding of the molecular mechanism underlying muscle growth and development in cattle.

• Genomics & Informatics
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• 제18권3호
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• pp.33.1-33.7
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• 2020

This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-column biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.