Literature DB >> 32229123

Identification of stable genes in the corpus luteum of lactating Holstein cows in pregnancy and luteolysis: Implications for selection of reverse-transcription quantitative PCR reference genes.

M A Mezera1, W Li2, A J Edwards3, D J Koch3, A D Beard1, M C Wiltbank4.   

Abstract

In lactating dairy cattle, the corpus luteum (CL) is a dynamic endocrine tissue vital for pregnancy maintenance, fertility, and cyclicity. Understanding processes underlying luteal physiology is therefore necessary to increase reproductive efficiency in cattle. A common technique for investigating luteal physiology is reverse-transcription quantitative PCR (RT-qPCR), a valuable tool for quantifying gene expression. However, reference-gene-based RT-qPCR quantification methods require utilization of stably expressed genes to accurately assess mRNA expression. Historically, selection of reference genes in cattle has relied on subjective selection of a small pool of reference genes, many of which may have significant expression variation among different tissues or physiologic states. This is particularly concerning in dynamic tissues such as the CL, with its capacity for rapid physiologic changes during luteolysis, and likely in the less characterized period of CL maintenance during pregnancy. Thus, there is a clear need to identify reference genes well suited for the bovine CL over a wide range of physiological states. Whole-transcriptome RNA sequencing stands as an effective method to identify new reference genes by enabling the assessment of the expression profile of the entire pool of mRNA transcripts. We report the identification of 13 novel putative reference genes using RNA sequencing in the bovine CL throughout early pregnancy and luteolysis: RPL4, UQCRFS1, COX4I1, RPS4X, SSR3, CST3, ZNF266, CDC42, CD63, HIF1A, YWHAE, EIF3E, and PPIB. Independent RT-qPCR analyses were conducted confirming expression stability in another set of CL tissues from pregnancy and regression, with analyses performed for 3 groups of samples: (1) all samples, (2) samples from pregnancy alone, and (3) samples throughout the process of CL regression. Seven genes were found to be more stable in all states than 2 traditional reference genes (ACTB and GAPDH): RPS4X, COX4I1, PPIB, SSR3, RPL4, YWHAE, and CDC42. When CL tissues from pregnant animals alone were analyzed, CST3, HIF1A, and CD63 were also identified as more stable than ACTB and GAPDH. Identification of these new reference genes will aid in accurate normalization of RT-qPCR results, contributing to proper interpretation of gene expression relevant to luteal physiology. Furthermore, our analysis sheds light on the effects of luteolysis and pregnancy on the stability of gene expression in the bovine CL.
Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  corpus luteum; dairy cow; reference gene; reverse-transcription quantitative PCR

Year:  2020        PMID: 32229123     DOI: 10.3168/jds.2019-17526

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  4 in total

1.  Transcriptome-based selection and validation of optimal house-keeping genes for skin research in goats (Capra hircus).

Authors:  Jipan Zhang; Chengchen Deng; Jialu Li; Yongju Zhao
Journal:  BMC Genomics       Date:  2020-07-18       Impact factor: 3.969

2.  Investigating the effect of positional variation on mid-lactation mammary gland transcriptomics in mice fed either a low-fat or high-fat diet.

Authors:  Adrienne A Cheng; Wenli Li; Laura L Hernandez
Journal:  PLoS One       Date:  2021-08-26       Impact factor: 3.240

3.  Reference gene selection in bovine caruncular epithelial cells under pregnancy-associated hormones exposure.

Authors:  Magdalena Sozoniuk; Monika Jamioł; Marta Kankofer; Krzysztof Kowalczyk
Journal:  Sci Rep       Date:  2022-07-26       Impact factor: 4.996

4.  Selection signatures in two oldest Russian native cattle breeds revealed using high-density single nucleotide polymorphism analysis.

Authors:  Natalia Anatolievna Zinovieva; Arsen Vladimirovich Dotsev; Alexander Alexandrovich Sermyagin; Tatiana Evgenievna Deniskova; Alexandra Sergeevna Abdelmanova; Veronika Ruslanovna Kharzinova; Johann Sölkner; Henry Reyer; Klaus Wimmers; Gottfried Brem
Journal:  PLoS One       Date:  2020-11-16       Impact factor: 3.240

  4 in total

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