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SNP development from RNA-seq data in a nonmodel fish: How many individuals are needed for accurate allele frequency prediction?

机译:从非模型鱼中RNA-seq数据开发SNP:准确的等位基因频率预测需要多少个人?

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Single nucleotide polymorphisms (SNPs) are rapidly becoming the marker of choice in population genetics due to a variety of advantages relative to other markers, including higher genomic density, data quality, reproducibility and genotyping efficiency, as well as ease of portability between laboratories. Advances in sequencing technology and methodologies to reduce genomic representation have made the isolation of SNPs feasible for nonmodel organisms. RNA-seq is one such technique for the discovery of SNPs and development of markers for large-scale genotyping. Here, we report the development of 192 validated SNP markers for parentage analysis in Tripterygion delaisi (the black-faced blenny), a small rocky-shore fish from the Mediterranean Sea. RNA-seq data for 15 individual samples were used for SNP discovery by applying a series of selection criteria. Genotypes were then collected from 1599 individuals from the same population with the resulting loci. Differences in heterozygosity and allele frequencies were found between the two data sets. Heterozygosity was lower, on average, in the population sample, and the mean difference between the frequencies of particular alleles in the two data sets was 0.135 ± 0.100. We used bootstrap resampling of the sequence data to predict appropriate sample sizes for SNP discovery. As cDNA library production is time-consuming and expensive, we suggest that using seven individuals for RNA sequencing reduces the probability of discarding highly informative SNP loci, due to lack of observed polymorphism, whereas use of more than 12 samples does not considerably improve prediction of true allele frequencies.
机译:单核苷酸多态性(SNP)由于相对于其他标记具有多种优势,包括具有更高的基因组密度,数据质量,可重复性和基因分型效率,以及易于在实验室之间移植,因此正迅速成为群体遗传学中选择的标记。减少基因组代表性的测序技术和方法学的进步使SNP的分离对于非模型生物变得可行。 RNA-seq是一种用于发现SNP和开发用于大规模基因分型的标记物的技术。在这里,我们报告了来自地中海的小石滩鱼雷公藤(黑三叶鱼)中用于亲子分析的192个经过验证的SNP标记的开发。通过应用一系列选择标准,将15个单独样品的RNA-seq数据用于SNP发现。然后,从具有相同基因座的同一人群中的1599个个体中收集基因型。在两个数据集之间发现了杂合性和等位基因频率的差异。在总体样本中,杂合度平均较低,两个数据集中特定等位基因的频率之间的平均差异为0.135±0.100。我们使用了序列数据的自举重采样来预测SNP发现的合适样本量。由于cDNA文库的生产既耗时又昂贵,我们建议使用7个个体进行RNA测序可降低由于缺乏观察到的多态性而丢弃高信息量SNP位点的可能性,而使用12个以上的样品并不能显着改善对SNP位点的预测真正的等位基因频率。

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