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Chapter 53 : Host Genomic Profiling in Human Immunodeficiency Virus Infection

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Abstract:

Host data can be presented under the concept of genetics of candidate genes, genome-wide studies, and the more specific areas of comparative and evolutionary genetics, and pharmacogenetics. A parallel development is taking place in the field of pharmacogenetics that aims at the identification of genetic variants that modulate drug response, pharmacokinetics, and toxicity. This chapter emphasizes the technical and technological possibilities in genetics and genomics for the study of host susceptibility to human immunodeficiency virus type 1 infection. Study phenotypes should be easily measurable and reliable (i.e., low intraindividual variability), but variable (i.e., high interindividual variability). In the HIV field these include standardized quantitative traits, such as viral load, CD4 T-cell count, and other biomarkers of disease. Clinical endpoints are best studied if they are not the composite result of multiple biological and environmental factors. All essentially involve a set of probes on an array and require amplification and labeling of cDNA/cRNA followed by hybridization to the probes on the array. Recently, groups have started to perform sequencing experiments on the entire transcriptome. This approach is similar to sequencing an entire human genome, except the input is cDNA rather than genomic DNA. It is too early to measure the full potential of large-scale genome research in HIV-1 infection. However, some general principles can be drawn. The first aspect relates to the fact that the human genome is a canvas that provides reference to multiple types of data. The second aspect concerns the use of new knowledge.

Citation: Shianna K, Telenti A. 2011. Host Genomic Profiling in Human Immunodeficiency Virus Infection, p 833-840. In Persing D, Tenover F, Tang Y, Nolte F, Hayden R, van Belkum A (ed), Molecular Microbiology. ASM Press, Washington, DC. doi: 10.1128/9781555816834.ch53

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FIGURE 1

Pattern of evolution of primate proteins involved in antiviral intrinsic cellular defense (TRIM5α and -22 and APOBE3G and -3F) and in innate immunity (DC-SIGN family and Toll-like receptors) in comparison with a random set of 19 proteins. Analysis estimated the Ka/Ks values (ratio of the rate of nonsynonymous substitutions [Ka] to the rate of synonymous substitutions [Ks]), which can be used as an indication of positive selection on a protein-coding gene. Analysis included human, chimpanzee, orangutan, rhesus monkey, and marmoset genome data. Bars indicate median values.

Citation: Shianna K, Telenti A. 2011. Host Genomic Profiling in Human Immunodeficiency Virus Infection, p 833-840. In Persing D, Tenover F, Tang Y, Nolte F, Hayden R, van Belkum A (ed), Molecular Microbiology. ASM Press, Washington, DC. doi: 10.1128/9781555816834.ch53
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Tables

Generic image for table
TABLE 1

Genetic variants modulating HIV-1 susceptibility and disease

Citation: Shianna K, Telenti A. 2011. Host Genomic Profiling in Human Immunodeficiency Virus Infection, p 833-840. In Persing D, Tenover F, Tang Y, Nolte F, Hayden R, van Belkum A (ed), Molecular Microbiology. ASM Press, Washington, DC. doi: 10.1128/9781555816834.ch53
Generic image for table
TABLE 2

Comparative assessment of common genotyping and expression technologies

Citation: Shianna K, Telenti A. 2011. Host Genomic Profiling in Human Immunodeficiency Virus Infection, p 833-840. In Persing D, Tenover F, Tang Y, Nolte F, Hayden R, van Belkum A (ed), Molecular Microbiology. ASM Press, Washington, DC. doi: 10.1128/9781555816834.ch53
Generic image for table
TABLE 3

Genome-wide and other high-throughput studies for the investigation of HIV-1 pathogenesis

Citation: Shianna K, Telenti A. 2011. Host Genomic Profiling in Human Immunodeficiency Virus Infection, p 833-840. In Persing D, Tenover F, Tang Y, Nolte F, Hayden R, van Belkum A (ed), Molecular Microbiology. ASM Press, Washington, DC. doi: 10.1128/9781555816834.ch53

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