What does the structure-function relationship of the HIV-1 Tat protein teach us about developing an AIDS vaccine?

The human immunodeficiency virus type 1 (HIV-1) trans-activator of transcription protein Tat is an important factor in viral pathogenesis. In addition to its function as the key trans-activator of viral transcription, Tat is also secreted by the infected cell and taken up by neighboring cells where it has an effect both on infected and uninfected cells. In this review we will focus on the relationship between the structure of the Tat protein and its function as a secreted factor. To this end we will summarize some of the exogenous functions of Tat that have been implicated in HIV-1 pathogenesis and the impact of structural variations and viral subtype variants of Tat on those functions. Finally, since in some patients the presence of Tat-specific antibodies or CTL frequencies are associated with slow or non-progression to AIDS, we will also discuss the role of Tat as a potential vaccine candidate, the advances made in this field, and the importance of using a Tat protein capable of eliciting a protective or therapeutic immune response to viral challenge

A linear complexity phasing method for thousands of genomes.

Human-disease etiology can be better understood with phase information about diploid sequences. We present a method for estimating haplotypes, using genotype data from unrelated samples or small nuclear families, that leads to improved accuracy and speed compared to several widely used methods. The method, segmented haplotype estimation and imputation tool (SHAPEIT), scales linearly with the number of haplotypes used in each iteration and can be run efficiently on whole chromosomes. © 2012 Nature America, Inc. All rights reserved

Haplotype estimation using sequencing reads.

High-throughput sequencing technologies produce short sequence reads that can contain phase information if they span two or more heterozygote genotypes. This information is not routinely used by current methods that infer haplotypes from genotype data. We have extended the SHAPEIT2 method to use phase-informative sequencing reads to improve phasing accuracy. Our model incorporates the read information in a probabilistic model through base quality scores within each read. The method is primarily designed for high-coverage sequence data or data sets that already have genotypes called. One important application is phasing of single samples sequenced at high coverage for use in medical sequencing and studies of rare diseases. Our method can also use existing panels of reference haplotypes. We tested the method by using a mother-father-child trio sequenced at high-coverage by Illumina together with the low-coverage sequence data from the 1000 Genomes Project (1000GP). We found that use of phase-informative reads increases the mean distance between switch errors by 22% from 274.4 kb to 328.6 kb. We also used male chromosome X haplotypes from the 1000GP samples to simulate sequencing reads with varying insert size, read length, and base error rate. When using short 100 bp paired-end reads, we found that using mixtures of insert sizes produced the best results. When using longer reads with high error rates (5-20 kb read with 4%-15% error per base), phasing performance was substantially improved