The precise identification of the HIV-1 envelope glycoprotein (Env) responsible for productive clinical infection could be instrumental in elucidating the molecular basis of HIV-1 transmission and in designing effective vaccines. Here, we developed a mathematical model of random viral evolution and, together with phylogenetic tree construction, used it to analyze 3,449 complete env sequences derived by single genome amplification from 102 subjects with acute HIV-1 (clade B) infection. Viral env genes evolving from individual transmitted or founder viruses generally exhibited a Poisson distribution of mutations and star-like phylogeny, which coalesced to an inferred consensus sequence at or near the estimated time of virus transmission. Overall, 78 of 102 subjects had evidence of productive clinical infection by a single virus, and 24 others had evidence of productive clinical infection by a minimum of two to five viruses. Phenotypic analysis of transmitted or early founder Envs revealed a consistent pattern of CCR5 dependence, masking of coreceptor binding regions, and equivalent or modestly enhanced resistance to the fusion inhibitor T1249 and broadly neutralizing antibodies compared with Envs from chronically infected subjects. Low multiplicity infection and limited viral evolution preceding peak viremia suggest a finite window of potential vulnerability of HIV-1 to vaccine-elicited immune responses, although phenotypic properties of transmitted Envs pose a formidable defense.

https://www.pnas.org/content/pnas/105/21/7552.full.pdf

Identification and characterization of transmitted and early founder virus envelopes in primary HIV-1 infection

Medical genetics was revolutionized during the 1980s by the application of genetic mapping to locate the genes responsible for simple Mendelian diseases. Most diseases and traits, however, do not follow simple inheritance patterns. Geneticists have thus begun taking up the even greater challenge of the genetic dissection of complex traits. Four major approaches have been developed: linkage analysis, allele-sharing methods, association studies, and polygenic analysis of experimental crosses. This article synthesizes the current state of the genetic dissection of complex traits—describing the methods, limitations, and recent applications to biological problems.

Genetic Dissection of Complex Traits

There is tremendous interest in using association mapping to identify genes responsible for quantitative variation of complex traits with agricultural and evolutionary importance. Recent advances in genomic technology, impetus to exploit natural diversity, and development of robust statistical analysis methods make association mapping appealing and affordable to plant research programs. Association mapping identifi es quantitative trait loci (QTLs) by examining the marker-trait associations that can be attributed to the strength of linkage disequilibrium between markers and functional polymorphisms across a set of diverse germplasm. General understanding of association mapping has increased signifi cantly since its debut in plants. We have seen a more concerted effort in assembling various association-mapping populations and initiating experiments through either candidategene or genome-wide approaches in different plant species. In this review, we describe the current status of association mapping in plants and outline opportunities and challenges in complex trait dissection and genomics-assisted crop improvement. L arge-scale genome-wide association analyses of major human diseases have yielded very promising results, corroborating fi ndings of previous candidategene association studies and identifying novel disease loci that were previously unknown (Th e Wellcome Trust Case Control Consortium, 2007). Th e same strategy is being exploited in many plant species thanks to the dramatic reduction in costs of genomic technologies. In contrast to the widely used linkage analysis traditional mapping research in plants, association mapping searches for functional variation in a much broader germplasm context. Association mapping enables researchers to use modern genomic technologies to exploit natural diversity, the wealth of which is known to plant geneticists and breeders but has been utilized only on a small scale before the genomics era. Owing to the ease of producing large numbers of progenies from controlled crosses and conducting replicated trials with immortal individuals (inbreds and recombinant inbred lines, RILs), association mapping in plants may prove to be more promising than in human or animal genetics. In the current review,

/pdf/status-and-prospects-of-association-mapping-in-plants-h5kcg1ymdj.pdf

Status and Prospects of Association Mapping in Plants

To understand the high variability of the asymptomatic interval between primary human immunodeficiency virus type 1 (HIV-1) infection and the development of AIDS, we studied the evolution of the C2-V5 region of the HIV-1 env gene and of T-cell subsets in nine men with a moderate or slow rate of disease progression. They were monitored from the time of seroconversion for a period of 6 to 12 years until the development of advanced disease in seven men. Based on the analysis of viral divergence from the founder strain, viral population diversity within sequential time points, and the outgrowth of viruses capable of utilizing the CXCR4 receptor (X4 viruses), the existence of three distinct phases within the asymptomatic interval is suggested: an early phase of variable duration during which linear increases ( approximately 1% per year) in both divergence and diversity were observed; an intermediate phase lasting an average of 1.8 years, characterized by a continued increase in divergence but with stabilization or decline in diversity; and a late phase characterized by a slowdown or stabilization of divergence and continued stability or decline in diversity. X4 variants emerged around the time of the early- to intermediate-phase transition and then achieved peak representation and began a decline around the transition between the intermediate and late phases. The late-phase transition was also associated with failure of T-cell homeostasis (defined by a downward inflection in CD3(+) T cells) and decline of CD4(+) T cells to </=200 cells/microliter. The strength of these temporal associations between viral divergence and diversity, viral coreceptor specificity, and T-cell homeostasis and subset composition supports the concept that the phases described represent a consistent pattern of viral evolution during the course of HIV-1 infection in moderate progressors. Recognition of this pattern may help explain previous conflicting data on the relationship between viral evolution and disease progression and may provide a useful framework for evaluating immune damage and recovery in untreated and treated HIV-1 infections.

Consistent viral evolutionary changes associated with the progression of human immunodeficiency virus type 1 infection

This article discusses the asymptotic behavior of likelihood ratio tests for nonzero variance components in the longitudinal mixed effects linear model described by Laird and Ware (1982, Biometrics 38, 963-974). Our discussion of the large-sample behavior of likelihood ratio tests for nonzero variance components is based on the results for nonstandard testing situations by Self and Liang (1987, Journal of the American Statistical Association 82, 605-610).

Variance components testing in the longitudinal mixed effects model.

Generalized estimating equations are introduced in an ad hoc fashion for the covariance matrix of a multivariate response. These equations are to be solved jointly with score equations from a generalized linear model for mean parameters. A class of quadratic exponential models is used to develop joint estimating equations for mean and covariance parameters in a more systematic fashion, and proposals for the use of such equations are developed. Comments on the relative merits of the ad hoc and model-based approaches to estimation are given and a regression illustration with a bivariate response is provided.

Estimating equations for parameters in means and covariances of multivariate discrete and continuous responses.

Letters from: 

[ Shan-Lu Liu, et al . ][1] 

[ Barton F. Haynes, et al . ][1] 

Human immunodeficiency virus (HIV) behaves as an evolving quasispecies in infected individuals. When the populations of genetic variants that make up this quasispecies are characterized, it is common practice to obtain

https://science.sciencemag.org/content/sci/273/5274/413.4.full.pdf

HIV Quasispecies and Resampling

The rough draft of the human genome map has been used to identify most of the functional genes in the human genome, as well as to identify nucleotide variations, known as “single-nucleotide polymorphisms” (SNPs), in these genes. By use of advanced biotechnologies, researchers are beginning to genotype thousands of SNPs from biological samples. Among the many possible applications, one of them is the study of SNP associations with complex human diseases, such as cancers or coronary heart diseases, by using a case-control study design. Through the gathering of environmental risk factors and other lifestyle factors, such a study can be effectively used to investigate interactions between genes and environmental factors in their associations with disease phenotype. Earlier, we developed a method to statistically construct individuals’ haplotypes and to estimate the distribution of haplotypes of multiple SNPs in a defined population, by use of estimating-equation techniques. Extending this idea, we describe here an analytic method for assessing the association between the constructed haplotypes along with environmental factors and the disease phenotype. This method is also robust to the model assumptions and is scalable to a large number of SNPs. Asymptotic properties of estimations in the method are proved theoretically and are tested for finite sample sizes by use of simulations. To demonstrate the use of the method, we applied it to assess the possible association between apolipoprotein CIII (six coding SNPs) and restenosis by using a case-control data set. Our analysis revealed two haplotypes that may reduce the risk of restenosis.

A Method for the Assessment of Disease Associations with Single-Nucleotide Polymorphism Haplotypes and Environmental Variables in Case-Control Studies

SUMMARY A class of partly exponential models is proposed for the regression analysis of multivariate response data. The class is parameterized in terms of the response mean and a general shape parameter. It includes the generalized linear error model and exponential dispersion models as special cases. Maximum likelihood equations for mean parameters are shown to be of the same form as certain generalized estimating equations, and maximum likelihood estimates of mean and shape parameters are asymptotically independent. Some results are given on the efficiency of the estimating equation procedure under misspecification of the response covariance matrix.

Multivariate Mean Parameter Estimation by Using a Partly Exponential Model

Molecular geneticists are developing the third-generation human genome map with single-nucleotide polymorphisms (SNPs), which can be assayed via chip-based microarrays. One use of these SNP markers is the ability to locate loci that may be responsible for complex traits, via linkage/linkage-disequilibrium analysis. In this communication, we describe a semiparametric method for combined linkage/linkage-disequilibrium analysis using SNP markers. Asymptotic results are obtained for the estimated parameters, and the finite-sample properties are evaluated via a simulation study. We also applied this technique to a simulated genome-scan experiment for mapping a complex trait with two major genes. This experiment shows that separate linkage and linkage-disequilibrium analyses correctly detected the signals of both major genes; but the rates of false-positive signals seem high. When linkage and linkage-disequilibrium signals were combined, the analysis yielded much stronger and clearer signals for the presence of two major genes than did two separate analyses.

Lue Ping Zhao

Papers

Estimating equations for parameters in means and covariances of multivariate discrete and continuous responses.

HIV Quasispecies and Resampling

A Method for the Assessment of Disease Associations with Single-Nucleotide Polymorphism Haplotypes and Environmental Variables in Case-Control Studies

Multivariate Mean Parameter Estimation by Using a Partly Exponential Model

Mapping of complex traits by single-nucleotide polymorphisms.