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Onecut1和Onecut2基因缺陷型视网膜的转录组学分析。

Transcriptomic analyses of Onecut1 and Onecut2 deficient retinas.

作者信息

Goetz Jillian J, Trimarchi Jeffrey M

机构信息

Department of Genetics, Development and Cell Biology, 2114 Molecular Biology, Iowa State University, Ames, IA 50011, USA.

出版信息

Genom Data. 2015 Apr 1;4:88-9. doi: 10.1016/j.gdata.2015.03.010. eCollection 2015 Jun.

DOI:10.1016/j.gdata.2015.03.010
PMID:26484186
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4535938/
Abstract

In this article, we further explore the data generated for the research article "Onecut1 and Onecut2 play critical roles in the development of the mouse retina". To better understand the functionality of the Onecut family of transcription factors in retinogenesis, we investigated the retinal transcriptomes of developing and mature mice to identify genes with differential expression. This data article reports the full transcriptomes resulting from these experiments and provides tables detailing the differentially expressed genes between wildtype and Onecut1 or 2 deficient retinas. The raw array data of our transcriptomes as generated using Affymetrix microarrays are available on the NCBI Gene Expression Omnibus (GEO) browser (Reference number GSE57917 and GSE57918GSE57917GSE57918).

摘要

在本文中,我们进一步探究了为研究论文《Onecut1和Onecut2在小鼠视网膜发育中起关键作用》所生成的数据。为了更好地理解Onecut转录因子家族在视网膜生成中的功能,我们研究了发育中和成熟小鼠的视网膜转录组,以鉴定差异表达的基因。本数据文章报告了这些实验产生的完整转录组,并提供了详细列出野生型与Onecut1或2缺陷型视网膜之间差异表达基因的表格。我们使用Affymetrix微阵列生成的转录组原始阵列数据可在NCBI基因表达综合数据库(GEO)浏览器上获取(参考编号GSE57917和GSE57918GSE57917GSE57918)。

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Front Cell Dev Biol. 2021 Mar 18;9:602450. doi: 10.3389/fcell.2021.602450. eCollection 2021.
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Analysis of mir-9 Expression Pattern in Rat Retina during Postnatal Development.分析 miR-9 在大鼠视网膜发育过程中的表达模式。
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本文引用的文献

1
Onecut1 and Onecut2 play critical roles in the development of the mouse retina.Onecut1和Onecut2在小鼠视网膜发育中发挥关键作用。
PLoS One. 2014 Oct 14;9(10):e110194. doi: 10.1371/journal.pone.0110194. eCollection 2014.
2
affy--analysis of Affymetrix GeneChip data at the probe level.affy——在探针水平对Affymetrix基因芯片数据进行分析。
Bioinformatics. 2004 Feb 12;20(3):307-15. doi: 10.1093/bioinformatics/btg405.