Elevated HIV viral load is associated with higher recombination rate in vivo.

HIVs 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 HIVs 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 ( 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.