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基于单核苷酸多态性(SNP)的简易最小标记基因分型用于啤酒花鉴定和品种验证。

Simple SNP-based minimal marker genotyping for Humulus lupulus L. identification and variety validation.

作者信息

Henning John A, Coggins Jamie, Peterson Matthew

机构信息

USDA-ARS, 3450 SW Campus Way, Corvallis, OR, 97331, USA.

ROY FARMS, INC., 401 Walters Road, Moxee, WA, 98936, USA.

出版信息

BMC Res Notes. 2015 Oct 6;8:542. doi: 10.1186/s13104-015-1492-2.

Abstract

BACKGROUND

Hop is an economically important crop for the Pacific Northwest USA as well as other regions of the world. It is a perennial crop with rhizomatous or clonal propagation system for varietal distribution. A big concern for growers as well as brewers is variety purity and questions are regularly posed to public agencies concerning the availability of genotype testing. Current means for genotyping are based upon 25 microsatellites that provides relatively accurate genotyping but cannot always differentiate sister-lines. In addition, numerous PCR runs (25) are required to complete this process and only a few laboratories exist that perform this service. A genotyping protocol based upon SNPs would enable rapid accurate genotyping that can be assayed at any laboratory facility set up for SNP-based genotyping. The results of this study arose from a larger project designed for whole genome association studies upon the USDA-ARS hop germplasm collection consisting of approximately 116 distinct hop varieties and germplasm (female lines) from around the world.

RESULTS

The original dataset that arose from partial sequencing of 121 genotypes resulted in the identification of 374,829 SNPs using TASSEL-UNEAK pipeline. After filtering out genotypes with more than 50% missing data (5 genotypes) and SNP markers with more than 20% missing data, 32,206 highly filtered SNP markers across 116 genotypes were identified and considered for this study. Minor allele frequency (MAF) was calculated for each SNP and ranked according to the most informative to least informative. Only those markers without missing data across genotypes as well as 60% or less heterozygous gamete calls were considered for further analysis. Genetic distances among individuals in the study were calculated using the marker with the highest MAF value, then by using a combination of the two markers with highest MAF values and so on. This process was reiterated until a set of markers was identified that allowed for all genotypes in the study to be genetically differentiated from each other. Next, we compared genetic matrices calculated from the minimal marker sets [(Table 2; 6-, 7-, 8-, 10- and 12-marker set matrices] and that of a matrix calculated from a set of markers with no missing data across all 116 samples (1006 SNP markers). The minimum number of markers required to meet both specifications was a set of 7-markers (Table 3). These seven SNPs were then aligned with a genome assembly, and DNA sequence both upstream and downstream were used to identify primer sequences that can be used to develop seven amplicons for high resolution melting curve PCR detection or other SNP-based PCR detection methods.

CONCLUSIONS

This study identifies a set of 7 SNP markers that may prove useful for the identification and validation of hop varieties and accessions. Variety validation of unknown samples assumes that the variety under question has been included a priori in a discovery panel. These results are based upon in silica studies and markers need to be validated using different SNP marker technology upon a differential set of hop genotypes. The marker sequence data and suggested primer sets provide potential means to fingerprint hop varieties in most genetic laboratories utilizing SNP-marker technology.

摘要

背景

啤酒花是美国太平洋西北地区以及世界其他地区一种具有重要经济价值的作物。它是一种多年生作物,通过根茎或克隆繁殖系统进行品种传播。种植者和啤酒酿造商非常关注品种纯度,并且经常向公共机构询问基因型检测的可用性。当前的基因分型方法基于25个微卫星,虽然能提供相对准确的基因分型,但并不总能区分姊妹系。此外,完成这个过程需要进行大量的PCR反应(25次),而且只有少数实验室能够提供这项服务。基于单核苷酸多态性(SNP)的基因分型方案将能够实现快速准确的基因分型,并且可以在任何具备基于SNP的基因分型能力的实验室设施中进行检测。本研究的结果源自一个更大的项目,该项目旨在对美国农业部农业研究局(USDA-ARS)收集的啤酒花种质进行全基因组关联研究,这些种质包括来自世界各地的约116个不同的啤酒花品种和种质(雌性系)。

结果

通过TASSEL-UNEAK流程对121个基因型进行部分测序得到的原始数据集,共鉴定出374,829个SNP。在过滤掉缺失数据超过50%的基因型(5个基因型)和缺失数据超过20%的SNP标记后,在116个基因型中鉴定出32,206个经过高度筛选的SNP标记,并用于本研究。计算每个SNP的次要等位基因频率(MAF),并根据信息含量从高到低进行排序。仅考虑那些在基因型中无缺失数据且杂合配子调用率为60%或更低的标记进行进一步分析。使用MAF值最高的标记计算研究中个体之间的遗传距离,然后使用MAF值最高的两个标记的组合进行计算,依此类推。重复这个过程,直到确定一组能够区分研究中所有基因型的标记。接下来,我们比较了由最小标记集(表2;6个、7个、8个、10个和12个标记集矩阵)计算得到的遗传矩阵与由所有116个样本中无缺失数据的一组标记(1006个SNP标记)计算得到的矩阵。满足两个标准所需的最小标记数是一组7个标记(表3)。然后将这7个SNP与基因组组装进行比对,并使用上下游的DNA序列来鉴定可用于开发7个扩增子的引物序列,用于高分辨率熔解曲线PCR检测或其他基于SNP的PCR检测方法。

结论

本研究鉴定出一组7个SNP标记,可能对啤酒花品种和种质的鉴定及验证有用。对未知样本的品种验证假定所研究的品种已预先包含在发现面板中。这些结果基于电子研究,标记需要使用不同的SNP标记技术在不同的啤酒花基因型集上进行验证。标记序列数据和建议的引物集为大多数利用SNP标记技术的遗传实验室提供了对啤酒花品种进行指纹识别的潜在方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7047/4595125/65d57c60e155/13104_2015_1492_Fig1_HTML.jpg

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