葡萄叶绿体DNA的计算机基因组分析:DNA编码关键区域的鉴定

In Silico Genomic Analysis of Chloroplast DNA in Vitis L.: Identification of Key Regions for DNA Coding.

作者信息

Peña Francisca, Univaso Luciano, Román-Figueroa Celián, Paneque Manuel

机构信息

Bionostra Chile Research Foundation, Almirante Lynch 1179, San Miguel 8920033, Santiago, Chile.

Department of Environmental Sciences and Natural Resources, Faculty of Agricultural Sciences, Universidad de Chile, Santa Rosa 11315, La Pintana 8820808, Santiago, Chile.

出版信息

Genes (Basel). 2025 May 31;16(6):686. doi: 10.3390/genes16060686.

Abstract

BACKGROUND/OBJECTIVES: The genus comprises approximately 70 species with high genetic diversity, among which is the most economically significant. Despite numerous studies on the genetic characterizations of , selecting optimal chloroplast DNA barcoding regions for intraspecific differentiation remains unresolved. Most studies have focused on nuclear markers (SSRs, SNPs) or widely used chloroplast loci (e.g., , ), which have shown limited resolution at the subspecies level. In this study, the complete chloroplast genomes of 34 accessions from different varieties and hybrids (, , , and ) were analyzed to identify the key genomic regions for DNA barcoding.

METHODS

Using bioinformatics tools, we assessed the genome structure, nucleotide variability, microsatellites, codon usage bias, and phylogenetic relationships among the investigated varieties.

RESULTS

The chloroplast genomes displayed a quadripartite structure, with lengths ranging from 160,906 to 160,929 bp and a guanine-cytosine (GC) content of ~37.4%. Phylogenetic analysis revealed an unusual position for VV-5 vini and VVVL-3 lab, suggesting potential taxonomic misclassification or hybridization effects. A single locus showed low discrimination power, but the concatenation of five loci (, , , , and ) exhibited significantly improved resolution (44.11% K2P), surpassing traditional markers.

CONCLUSIONS

This study addresses the gap in the literature regarding the use of concatenated chloroplast loci for subspecies research; the results validate these markers across a broader range of accessions and integrate nuclear and mitochondrial data to achieve a more comprehensive understanding of the evolutionary history and genetic diversity of .

摘要

背景/目的:该属包含约70个具有高度遗传多样性的物种,其中[物种名称]在经济上最为重要。尽管对[物种名称]的遗传特征进行了大量研究,但选择用于种内分化的最佳叶绿体DNA条形码区域仍未得到解决。大多数研究集中在核标记(SSR、SNP)或广泛使用的叶绿体基因座(如[基因座名称1]、[基因座名称2]),这些在亚种水平上的分辨率有限。在本研究中,分析了来自不同品种和杂种([品种1]、[品种2]、[品种3]和[品种4])的34个[物种名称]样本的完整叶绿体基因组,以确定DNA条形码的关键基因组区域。

方法

使用生物信息学工具,我们评估了所研究品种的基因组结构、核苷酸变异性、微卫星、密码子使用偏好和系统发育关系。

结果

叶绿体基因组呈现四分体结构,长度在160,906至160,929 bp之间,鸟嘌呤-胞嘧啶(GC)含量约为37.4%。系统发育分析揭示了VV-5 vini和VVVL-3 lab的异常位置,表明可能存在分类错误或杂交效应。单个基因座的鉴别能力较低,但五个基因座([基因座名称1]、[基因座名称2]、[基因座名称3]、[基因座名称4]和[基因座名称5])的串联显示分辨率显著提高(K2P为44.11%),超过了传统标记。

结论

本研究填补了关于串联叶绿体基因座用于亚种研究的文献空白;结果在更广泛的[物种名称]样本中验证了这些标记,并整合了核和线粒体数据,以更全面地了解[物种名称]的进化历史和遗传多样性。

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