{"title":"Development of a formula for scoring competence of bovine embryos to sustain pregnancy","authors":"Maria Belen Rabaglino , Peter J. Hansen","doi":"10.1016/j.bbrep.2024.101772","DOIUrl":null,"url":null,"abstract":"<div><p>Embryo transfer in cattle and other species is a key reproductive technology to improve genetic merit. However, pregnancy loss after embryo transfer is still a major barrier to optimal utilization of the technology. Furthermore, the lack of a method to objectively quantify embryonic competence hinders investigations aimed at improving the competence of an embryo. Based on the knowledge that bovine embryos have an inherent molecular signature that determines their ability for pregnancy establishment which can result in distinct gene expression profiles, we have previously integrated transcriptomic data from independent experiments to identify eight genes capable of predicting embryo competence for survival with high accuracy. In this study, we developed a function for the R software containing a mathematical formula based on the model coefficients to yield an embryonic competence index (ECI) according to the expression of those eight critical genes. Application of the function to a gene expression dataset generates a quantitative ECI value for each embryo that can be employed in statistical analyses when performing an experiment. The folder with the R project and required datasets can be found in <span>https://zenodo.org/records/12515587</span><svg><path></path></svg>.</p></div>","PeriodicalId":8771,"journal":{"name":"Biochemistry and Biophysics Reports","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405580824001365/pdfft?md5=d946ebd09ba52a4e310fa14f709d9d20&pid=1-s2.0-S2405580824001365-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biochemistry and Biophysics Reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405580824001365","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Embryo transfer in cattle and other species is a key reproductive technology to improve genetic merit. However, pregnancy loss after embryo transfer is still a major barrier to optimal utilization of the technology. Furthermore, the lack of a method to objectively quantify embryonic competence hinders investigations aimed at improving the competence of an embryo. Based on the knowledge that bovine embryos have an inherent molecular signature that determines their ability for pregnancy establishment which can result in distinct gene expression profiles, we have previously integrated transcriptomic data from independent experiments to identify eight genes capable of predicting embryo competence for survival with high accuracy. In this study, we developed a function for the R software containing a mathematical formula based on the model coefficients to yield an embryonic competence index (ECI) according to the expression of those eight critical genes. Application of the function to a gene expression dataset generates a quantitative ECI value for each embryo that can be employed in statistical analyses when performing an experiment. The folder with the R project and required datasets can be found in https://zenodo.org/records/12515587.
牛和其他物种的胚胎移植是提高遗传优势的关键繁殖技术。然而,胚胎移植后的妊娠损失仍是优化利用该技术的主要障碍。此外,缺乏客观量化胚胎能力的方法也阻碍了旨在提高胚胎能力的研究。牛胚胎具有决定其妊娠能力的固有分子特征,这可能导致不同的基因表达谱,基于这一认识,我们之前整合了来自独立实验的转录组数据,确定了八个能够高精度预测胚胎存活能力的基因。在本研究中,我们为 R 软件开发了一个函数,其中包含一个基于模型系数的数学公式,可根据这八个关键基因的表达得出胚胎能力指数(ECI)。将该函数应用于基因表达数据集可生成每个胚胎的定量 ECI 值,在进行实验时可用于统计分析。包含 R 项目和所需数据集的文件夹可在 https://zenodo.org/records/12515587 中找到。
期刊介绍:
Open access, online only, peer-reviewed international journal in the Life Sciences, established in 2014 Biochemistry and Biophysics Reports (BB Reports) publishes original research in all aspects of Biochemistry, Biophysics and related areas like Molecular and Cell Biology. BB Reports welcomes solid though more preliminary, descriptive and small scale results if they have the potential to stimulate and/or contribute to future research, leading to new insights or hypothesis. Primary criteria for acceptance is that the work is original, scientifically and technically sound and provides valuable knowledge to life sciences research. We strongly believe all results deserve to be published and documented for the advancement of science. BB Reports specifically appreciates receiving reports on: Negative results, Replication studies, Reanalysis of previous datasets.