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Parent-offspring regression to estimate the heritability of an HIV-1 trait in a realistic setup.

机译:亲子回归分析,以评估实际设置中HIV-1性状的遗传性。

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摘要

Parent-offspring (PO) regression is a central tool to determine the heritability of phenotypic traits; i.e., the relative extent to which those traits are controlled by genetic factors. The applicability of PO regression to viral traits is unclear because the direction of viral transmission-who is the donor (parent) and who is the recipient (offspring)-is typically unknown and viral phylogenies are sparsely sampled.We assessed the applicability of PO regression in a realistic setting using Ornstein-Uhlenbeck simulated data on phylogenies built from 11,442 Swiss HIV Cohort Study (SHCS) partial pol sequences and set-point viral load (SPVL) data from 3293 patients.We found that the misidentification of donor and recipient plays a minor role in estimating heritability and showed that sparse sampling does not influence the mean heritability estimated by PO regression. A mixed-effect model approach yielded the same heritability as PO regression but could be extended to clusters of size greater than 2 and allowed for the correction of confounding effects. Finally, we used both methods to estimate SPVL heritability in the SHCS. We employed a wide range of transmission pair criteria to measure heritability and found a strong dependence of the heritability estimates to these criteria. For the most conservative genetic distance criteria, for which heritability estimates are conceptually expected to be closest to true heritability, we found estimates ranging from 32 to 46% across different bootstrap criteria. For less conservative distance criteria, we found estimates ranging down to 8%. All estimates did not change substantially after adjusting for host-demographic factors in the mixed-effect model (±2%).For conservative transmission pair criteria, both PO regression and mixed-effect models are flexible and robust tools to estimate the contribution of viral genetic effects to viral traits under real-world settings. Overall, we find a strong effect of viral genetics on SPVL that is not confounded by host demographics.
机译:亲子(PO)回归是确定表型性状遗传力的主要工具。即这些性状受遗传因素控制的相对程度。 PO回归对病毒性状的适用性尚不清楚,因为病毒传播的方向-谁是供体(父母)和谁是受体(后代)-通常是未知的,并且病毒系统发育被稀疏采样。我们评估了PO回归的适用性在现实环境中,使用Ornstein-Uhlenbeck模拟的系统发育数据(根据11,442份瑞士HIV队列研究(SHCS)部分pol序列和3293位患者的设定点病毒载量(SPVL)数据构建),我们发现供体和受体的错误识别起着在估计遗传力方面起次要作用,并表明稀疏采样不会影响通过PO回归估计的平均遗传力。混合效应模型方法产生的遗传力与PO回归相同,但可以扩展到大小大于2的簇,并且可以纠正混杂效应。最后,我们使用两种方法来估计SHCS中SPVL的遗传力。我们采用了多种传输对标准来衡量遗传力,并发现遗传力估计值对这些标准的强烈依赖性。对于最保守的遗传距离标准,其遗传力估计在概念上预计最接近真实遗传力,我们发现在不同的自举标准中,估计值介于32%至46%之间。对于不太保守的距离标准,我们发现估计范围低至8%。调整混合效应模型中的宿主人口因素后,所有估计值均没有实质性变化(±2%)。对于保守的传播对标准,PO回归和混合效应模型都是灵活而强大的工具,可用来估算病毒的贡献在现实环境中对病毒性状的遗传效应。总体而言,我们发现病毒遗传学对SPVL具有很强的影响力,而不受宿主人口统计学的影响。

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