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A novel workflow to improve genotyping of multigene families in wildlife species: An experimental set-up with a known model system.

一种改进野生动物多基因家族基因分型的新工作流程: 一个已知模型系统的实验装置。

  • 影响因子:7.01
  • DOI:10.1111/1755-0998.13290
  • 作者列表:"Gillingham MAF","Montero BK","Wihelm K","Grudzus K","Sommer S","Santos PSC
  • 发表时间:2021-04-01
Abstract

:Genotyping complex multigene families in novel systems is particularly challenging. Target primers frequently amplify simultaneously multiple loci leading to high PCR and sequencing artefacts such as chimeras and allele amplification bias. Most genotyping pipelines have been validated in nonmodel systems whereby the real genotype is unknown and the generation of artefacts may be highly repeatable. Further hindering accurate genotyping, the relationship between artefacts and genotype complexity (i.e. number of alleles per genotype) within a PCR remains poorly described. Here, we investigated the latter by experimentally combining multiple known major histocompatibility complex (MHC) haplotypes of a model organism (chicken, Gallus gallus, 43 artificial genotypes with 2-13 alleles per amplicon). In addition to well-defined 'optimal' primers, we simulated a nonmodel species situation by designing 'cross-species' primers based on sequence data from closely related Galliform species. We applied a novel open-source genotyping pipeline (ACACIA; https://gitlab.com/psc_santos/ACACIA), and compared its performance with another, previously published pipeline (AmpliSAS). Allele calling accuracy was higher when using ACACIA (98.5% versus 97% and 77.8% versus 75% for the 'optimal' and 'cross-species' data sets, respectively). Systematic allele dropout of three alleles owing to primer mismatch in the 'cross-species' data set explained high allele calling repeatability (100% when using ACACIA) despite low accuracy, demonstrating that repeatability can be misleading when evaluating genotyping workflows. Genotype complexity was positively associated with nonchimeric artefacts, chimeric artefacts (nonlinearly by levelling when amplifying more than 4-6 alleles) and allele amplification bias. Our study exemplifies and demonstrates pitfalls researchers should avoid to reliably genotype complex multigene families.

摘要

: 新系统中复杂多基因家族的基因分型尤其具有挑战性。靶引物经常同时扩增多个位点,导致高PCR和测序伪影,如嵌合体和等位基因扩增偏倚。大多数基因分型管道已经在非模型系统中得到验证,其中真正的基因型是未知的,并且伪影的产生可以是高度可重复的。进一步阻碍准确的基因分型,人工制品和基因型复杂性之间的关系 (即PCR中每个基因型的等位基因数) 仍然描述不足。在这里,我们通过实验结合模型生物的多个已知的主要组织相容性复合体 (MHC) 单倍型 (鸡,Gallus gallus,43个人工基因型,每个扩增子有2-13个等位基因) 来研究后者。除了定义明确的 “最佳” 引物之外,我们还通过基于来自密切相关的alli形物种的序列数据设计 “交叉物种” 引物来模拟非模型物种情况。我们应用了一个新的开源基因分型管道 (ACACIA; https://gitlab.com/psc_santos/ACACIA),并将其性能与另一个先前发表的管道 (AmpliSAS) 进行了比较。当使用阿拉伯胶时,等位基因识别准确度更高 (对于 “最佳” 和 “杂交物种” 数据集,分别为98.5% 对97% 和77.8% 对75%)。由于 '交叉物种' 数据集中的引物错配导致的三个等位基因的系统性等位基因缺失解释了高等位基因调用可重复性 (当使用阿拉伯胶时为100%),尽管准确性低,这表明可重复性在评估基因分型工作流程时可能具有误导性。基因型复杂性与非嵌合artefacts、嵌合artefacts (当扩增超过4-6个等位基因时,通过水平非线性) 和等位基因扩增偏倚呈正相关。我们的研究举例说明并证明了研究人员应该避免的陷阱,以可靠地对复杂的多基因家族进行基因型分型。

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