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Recombination rate and selection strength in HIV intra-patient evolution.

Neher RA, Leitner T - PLoS Comput. Biol. (2010)

Bottom Line: By examining temporal changes in the genetic composition of the population, we estimate the effective recombination to be rho = 1.4+/-0.6 x 10(-5) recombinations per site and generation.These results provide a basis for a more detailed understanding of the evolution of HIV.With the methods developed here, more precise and more detailed studies will be possible as soon as data with higher time resolution and greater sample sizes are available.

View Article: PubMed Central - PubMed

Affiliation: Kavli Institute for Theoretical Physics, University of California, Santa Barbara, California, United States of America. neher@kitp.ucsb.edu

ABSTRACT
The evolutionary dynamics of HIV during the chronic phase of infection is driven by the host immune response and by selective pressures exerted through drug treatment. To understand and model the evolution of HIV quantitatively, the parameters governing genetic diversification and the strength of selection need to be known. While mutation rates can be measured in single replication cycles, the relevant effective recombination rate depends on the probability of coinfection of a cell with more than one virus and can only be inferred from population data. However, most population genetic estimators for recombination rates assume absence of selection and are hence of limited applicability to HIV, since positive and purifying selection are important in HIV evolution. Yet, little is known about the distribution of selection differentials between individual viruses and the impact of single polymorphisms on viral fitness. Here, we estimate the rate of recombination and the distribution of selection coefficients from time series sequence data tracking the evolution of HIV within single patients. By examining temporal changes in the genetic composition of the population, we estimate the effective recombination to be rho = 1.4+/-0.6 x 10(-5) recombinations per site and generation. Furthermore, we provide evidence that the selection coefficients of at least 15% of the observed non-synonymous polymorphisms exceed 0.8% per generation. These results provide a basis for a more detailed understanding of the evolution of HIV. A particularly interesting case is evolution in response to drug treatment, where recombination can facilitate the rapid acquisition of multiple resistance mutations. With the methods developed here, more precise and more detailed studies will be possible as soon as data with higher time resolution and greater sample sizes are available.

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Related in: MedlinePlus

Selection on non-synonymous mutations.The figure shows cumulative distributions of the observed rate of change  of the allele frequencies  between two consecutive samples at times  and  for non-synonymous polymorphisms, synonymous polymorphisms, and synonymous polymorphisms at least 100bp away from the nearest fast changing non-synonymous polymorphism (/generation), see methods. The inset shows the corresponding histograms on a logarithmic scale. Only pairs of time points with sample sizes greater than 10 sequences are included.
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pcbi-1000660-g004: Selection on non-synonymous mutations.The figure shows cumulative distributions of the observed rate of change of the allele frequencies between two consecutive samples at times and for non-synonymous polymorphisms, synonymous polymorphisms, and synonymous polymorphisms at least 100bp away from the nearest fast changing non-synonymous polymorphism (/generation), see methods. The inset shows the corresponding histograms on a logarithmic scale. Only pairs of time points with sample sizes greater than 10 sequences are included.

Mentions: Despite the limited resolution of and due to small sample sizes and large time intervals between samples (6–10 month), we can make a meaningful statement about the strength of selection when averaging over all sites, patients and time points. Figure 4 shows the cumulative distributions of the rates of change of allele frequencies observed during the interval between two consecutive time points for non-synonymous and synonymous polymorphisms. The histograms are shown as insets in the Figure. There are consistently more fast changing non-synonymous polymorphisms than there are synonymous ones, suggesting that a fraction of the non-synonymous polymorphisms is indeed responding to selection. To check whether the fast changing synonymous polymorphisms can be attributed to hitchhiking, we excluded synonymous polymorphisms that are closer than 100bp to a non-synonymous polymorphism that changes faster than per generation. The resulting distribution is much narrower with no allele frequency changes beyond per generation, indicating that the fast changing synonymous polymorphisms are indeed “hitch-hiking”. The cumulative histograms can be compared by the Kolmogorov-Smirnov test, which uses the maximal vertical distance between curves as a test statistics. The test reveals that the non-synonymous distribution is significantly different from both the unconditional synonymous distribution (p-value ) and the synonymous distribution without hitch-hiking (p-value ). Note that not all observations are independent since nearby sites are linked and move coherently. Hence, realistic p-values will be larger.


Recombination rate and selection strength in HIV intra-patient evolution.

Neher RA, Leitner T - PLoS Comput. Biol. (2010)

Selection on non-synonymous mutations.The figure shows cumulative distributions of the observed rate of change  of the allele frequencies  between two consecutive samples at times  and  for non-synonymous polymorphisms, synonymous polymorphisms, and synonymous polymorphisms at least 100bp away from the nearest fast changing non-synonymous polymorphism (/generation), see methods. The inset shows the corresponding histograms on a logarithmic scale. Only pairs of time points with sample sizes greater than 10 sequences are included.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2813257&req=5

pcbi-1000660-g004: Selection on non-synonymous mutations.The figure shows cumulative distributions of the observed rate of change of the allele frequencies between two consecutive samples at times and for non-synonymous polymorphisms, synonymous polymorphisms, and synonymous polymorphisms at least 100bp away from the nearest fast changing non-synonymous polymorphism (/generation), see methods. The inset shows the corresponding histograms on a logarithmic scale. Only pairs of time points with sample sizes greater than 10 sequences are included.
Mentions: Despite the limited resolution of and due to small sample sizes and large time intervals between samples (6–10 month), we can make a meaningful statement about the strength of selection when averaging over all sites, patients and time points. Figure 4 shows the cumulative distributions of the rates of change of allele frequencies observed during the interval between two consecutive time points for non-synonymous and synonymous polymorphisms. The histograms are shown as insets in the Figure. There are consistently more fast changing non-synonymous polymorphisms than there are synonymous ones, suggesting that a fraction of the non-synonymous polymorphisms is indeed responding to selection. To check whether the fast changing synonymous polymorphisms can be attributed to hitchhiking, we excluded synonymous polymorphisms that are closer than 100bp to a non-synonymous polymorphism that changes faster than per generation. The resulting distribution is much narrower with no allele frequency changes beyond per generation, indicating that the fast changing synonymous polymorphisms are indeed “hitch-hiking”. The cumulative histograms can be compared by the Kolmogorov-Smirnov test, which uses the maximal vertical distance between curves as a test statistics. The test reveals that the non-synonymous distribution is significantly different from both the unconditional synonymous distribution (p-value ) and the synonymous distribution without hitch-hiking (p-value ). Note that not all observations are independent since nearby sites are linked and move coherently. Hence, realistic p-values will be larger.

Bottom Line: By examining temporal changes in the genetic composition of the population, we estimate the effective recombination to be rho = 1.4+/-0.6 x 10(-5) recombinations per site and generation.These results provide a basis for a more detailed understanding of the evolution of HIV.With the methods developed here, more precise and more detailed studies will be possible as soon as data with higher time resolution and greater sample sizes are available.

View Article: PubMed Central - PubMed

Affiliation: Kavli Institute for Theoretical Physics, University of California, Santa Barbara, California, United States of America. neher@kitp.ucsb.edu

ABSTRACT
The evolutionary dynamics of HIV during the chronic phase of infection is driven by the host immune response and by selective pressures exerted through drug treatment. To understand and model the evolution of HIV quantitatively, the parameters governing genetic diversification and the strength of selection need to be known. While mutation rates can be measured in single replication cycles, the relevant effective recombination rate depends on the probability of coinfection of a cell with more than one virus and can only be inferred from population data. However, most population genetic estimators for recombination rates assume absence of selection and are hence of limited applicability to HIV, since positive and purifying selection are important in HIV evolution. Yet, little is known about the distribution of selection differentials between individual viruses and the impact of single polymorphisms on viral fitness. Here, we estimate the rate of recombination and the distribution of selection coefficients from time series sequence data tracking the evolution of HIV within single patients. By examining temporal changes in the genetic composition of the population, we estimate the effective recombination to be rho = 1.4+/-0.6 x 10(-5) recombinations per site and generation. Furthermore, we provide evidence that the selection coefficients of at least 15% of the observed non-synonymous polymorphisms exceed 0.8% per generation. These results provide a basis for a more detailed understanding of the evolution of HIV. A particularly interesting case is evolution in response to drug treatment, where recombination can facilitate the rapid acquisition of multiple resistance mutations. With the methods developed here, more precise and more detailed studies will be possible as soon as data with higher time resolution and greater sample sizes are available.

Show MeSH
Related in: MedlinePlus