Transcriptome analysis of testes gene expression to explore genetic diversity of Mangalica and Camborough boars.

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Keigo Yamane, Sangwoo Kim, Akari Koide, Erina Yoneda, Mitsunori Kayano, Yuki Muranishi
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引用次数: 0

Abstract

The testis, an important reproductive organ, is involved in spermatogenesis and steroid hormone secretion and has been the subject of a wide variety of studies. Pigs are often used as model animals for studies on human physiology and disease, and studies on the testicular development of pigs could shed light on human reproduction. Mangalica, an indigenous Hungarian pig breed, has reproductive traits that are different from those of commercial pig breeds. This specificity could reveal important differences in the cascades and reproductive genes between humans and other animals. In this study, we conducted RNA-sequencing analysis of the testes of 14 days old Mangalica and Camborough boars. We also performed clustering and pathway analysis of differentially expressed genes. These datasets and analyses are expected to provide important gene sets for pig testis development that can be applied in future studies on human reproductive mechanisms.

曼加利加和坎伯勒公猪睾丸基因表达转录组分析探讨遗传多样性。
睾丸是一个重要的生殖器官,参与精子发生和类固醇激素的分泌,一直是各种研究的主题。猪经常被用作人体生理学和疾病研究的模型动物,对猪睾丸发育的研究可以为人类生殖研究提供线索。Mangalica是匈牙利本土猪品种,具有不同于商品猪品种的生殖特征。这种特异性可以揭示人类和其他动物在级联和生殖基因方面的重要差异。在本研究中,我们对14日龄曼加利察公猪和坎伯勒公猪的睾丸进行了rna测序分析。我们还对差异表达基因进行了聚类和通路分析。这些数据集和分析有望为猪睾丸发育提供重要的基因集,并可应用于未来人类生殖机制的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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