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通过叶绿体全基因组分析鉴定小麦属植物的有效DNA条形码

Identification of effective DNA barcodes for Triticum plants through chloroplast genome-wide analysis.

作者信息

Awad Mohamed, Fahmy Ragab M, Mosa Kareem A, Helmy Mohamed, El-Feky Fawzy A

机构信息

Department of Biotechnology, Faculty of Agriculture, Al-Azhar University, Cairo, 11651, Egypt.

Genetic Resources Research Department, Agriculture Research Center, Giza, Egypt.

出版信息

Comput Biol Chem. 2017 Dec;71:20-31. doi: 10.1016/j.compbiolchem.2017.09.003. Epub 2017 Sep 12.

Abstract

The Egyptian flora is rich with a large number of Triticum plants, which are very difficult to discriminate between in the early developmental stages. This study assesses the significance of using two DNA Barcoding loci (matK and rbcL) in distinguishing between 18 different Triticum accessions in Egypt. We isolated and sequenced 15 rbcL and six matK fragments, but our analysis of the resultant sequences demonstrated a limited ability of matK and rbcL in distinguishing between Triticum accessions. Therefore, we pursued a bioinformatics approach to determine the most useful loci which may be used as DNA barcodes for the Triticum spp. We obtained the 10 available chloroplast genomes of the 10 Triticum species and sub-species from NCBI, and performed chloroplast genome-wide analysis to find the potential barcode loci. A total of 134 chloroplast genes, gene combinations, intergenic regions and intergenic region combinations were tested using a Tree-based method. We were unable to discriminate between Triticum species by using chloroplast genes, gene combinations and intergenic regions. However, a combination of the intergenic region (trnfM-trnT) with either (trnD-psbM), (petN-trnC), (matK-rps16) or (rbcL-psaI) demonstrated a very high discrimination capacity, suggesting their utilization as DNA barcodes for the Triticum plants. Furthermore, our novel DNA barcodes demonstrated high discrimination capacity for other Poaceae members.

摘要

埃及植物区系中有大量小麦属植物,在其发育早期很难区分。本研究评估了使用两个DNA条形码位点(matK和rbcL)区分埃及18种不同小麦种质的意义。我们分离并测序了15个rbcL片段和6个matK片段,但对所得序列的分析表明,matK和rbcL区分小麦种质的能力有限。因此,我们采用生物信息学方法来确定最有用的位点,这些位点可作为小麦属植物的DNA条形码。我们从NCBI获得了10个小麦种和亚种的10个可用叶绿体基因组,并进行了叶绿体全基因组分析以寻找潜在的条形码位点。使用基于树的方法共测试了134个叶绿体基因、基因组合、基因间区域和基因间区域组合。我们无法通过叶绿体基因、基因组合和基因间区域来区分小麦种。然而,基因间区域(trnfM-trnT)与(trnD-psbM)、(petN-trnC)、(matK-rps16)或(rbcL-psaI)的组合显示出非常高的区分能力,表明它们可作为小麦属植物的DNA条形码。此外,我们新的DNA条形码对其他禾本科成员也显示出很高的区分能力。

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