Romero Elena V, Feder Alison F
Department of Genome Sciences, University of Washington, Seattle, WA, USA.
bioRxiv. 2023 Oct 10:2023.05.05.539643. doi: 10.1101/2023.05.05.539643.
HIV's exceptionally high recombination rate drives its intra-host diversification, enabling immune escape and multi-drug resistance within people living with HIV. While we know that HIV's recombination rate varies by genomic position, we have little understanding of how recombination varies throughout infection or between individuals as a function of the rate of cellular coinfection. We hypothesize that denser intra-host populations may have higher rates of coinfection and therefore recombination. To test this hypothesis, we develop a new approach (Recombination Analysis via Time Series Linkage Decay, or RATS-LD) to quantify recombination using autocorrelation of linkage between mutations across time points. We validate RATS-LD on simulated data under short read sequencing conditions and then apply it to longitudinal, high-throughput intra-host viral sequencing data, stratifying populations by viral load (a proxy for density). Among sampled viral populations with the lowest viral loads (< 26,800 copies/mL), we estimate a recombination rate of 1.5 × 10 events/bp/generation (95% CI: 7 × 10 - 2.9 × 10), similar to existing estimates. However, among samples with the highest viral loads (> 82,000 copies/mL), our median estimate is approximately 6 times higher. In addition to co-varying across individuals, we also find that recombination rate and viral load are associated within single individuals across different time points. Our findings suggest that rather than acting as a constant, uniform force, recombination can vary dynamically and drastically across intra-host viral populations and within them over time. More broadly, we hypothesize that this phenomenon may affect other facultatively asexual populations where spatial co-localization varies.
HIV极高的重组率推动其在宿主体内的多样化,使得HIV感染者能够实现免疫逃逸和产生多药耐药性。虽然我们知道HIV的重组率因基因组位置而异,但对于重组在整个感染过程中如何变化,或者在个体之间如何随细胞共感染率而变化,我们了解甚少。我们推测,宿主体内密度更高的病毒群体可能具有更高的共感染率,进而具有更高的重组率。为了验证这一推测,我们开发了一种新方法(通过时间序列连锁衰减进行重组分析,即RATS-LD),利用跨时间点突变之间连锁的自相关性来量化重组。我们在短读长测序条件下的模拟数据上验证了RATS-LD,然后将其应用于纵向、高通量的宿主体内病毒测序数据,并根据病毒载量(密度的一个指标)对群体进行分层。在病毒载量最低(<26,800拷贝/毫升)的采样病毒群体中,我们估计重组率为1.5×10事件/碱基对/代(95%置信区间:7×10 - 2.9×10),与现有估计值相似。然而,在病毒载量最高(>82,000拷贝/毫升)的样本中,我们的中位数估计值大约高出6倍。除了在个体之间共同变化外,我们还发现,在单个个体的不同时间点,重组率和病毒载量也存在关联。我们的研究结果表明,重组并非作为一种恒定、均匀的力量起作用,而是可以在宿主体内病毒群体之间及其内部随时间动态且剧烈地变化。更广泛地说,我们推测这种现象可能会影响其他空间共定位情况不同的兼性无性繁殖群体。