4.4 Article

A comparison of six methods for genomic DNA extraction suitable for PCR-based genotyping applications using ovine milk samples

期刊

MOLECULAR AND CELLULAR PROBES
卷 24, 期 2, 页码 93-98

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.mcp.2009.11.001

关键词

Dairy sheep; Bulk milk; DNA extraction; Real-time PCR

资金

  1. European Commission [030278, FPC-2004-SMW-COLL]

向作者/读者索取更多资源

Isolation of amplifiable genomic DNA is a prerequisite for the genetic assessment of diseases and disease susceptibility in farm animals. Milk somatic cells are a practical, animal friendly and cost-effective source of genomic DNA in milking ruminants. In this study, six different DNA extraction methods were optimized, evaluated and compared for the isolation of DNA from ovine milk samples. Methods I and 2 were direct applications of two commercial kits, Nucleospin (R) Blood and Nucleospin (R) Tissue, respectively. Methods 3 and 4 were based on modified protocols of methods I and 2, respectively, aiming at increasing DNA recovery and integrity, and eliminating PCR inhibitors. Method 5 was a standard Phenol-Chloroform protocol application and method 6 was based on an in-house developed protocol using silica as the affinity matrix. Spectrophotometer, gel electrophoresis and real-time PCR measurements were used as criteria for evaluating quantity and quality of the extracted DNA. Processing time, intensity of labor and cost for each method were also evaluated. Results suggested that methods 1-4 were considered suitable for molecular downstream applications and performed better than methods 5 and 6. Modifications of protocols 3 and 4 increased the quantity and quality of the extracted DNA from ovine milk samples. Method 3 was proved to be highly efficient and robust for large scale use as demonstrated by its successful application to 1000 individual ovine milk and 50 bulk milk samples. (C) 2009 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据