Author: Lemaire, D.; Barbosa, T.; Rihet, P.
Title: Coping with genetic diversity: the contribution of pathogen and human genomics to modern vaccinology Document date: 2011_10_28
ID: q2y7fewk_29
Snippet: The emergence of new technologies, such as the microarray technology and more recently the next generation sequencing technology, gives the illusion that genes controlling a complex phenotype would be easily identified. This is due to the fact that we can obtain a huge amount of biological data for one sample. For example, the whole-genome transcriptome can be analyzed by using one array for an individual, and more than 500,000 SNPs can be simult.....
Document: The emergence of new technologies, such as the microarray technology and more recently the next generation sequencing technology, gives the illusion that genes controlling a complex phenotype would be easily identified. This is due to the fact that we can obtain a huge amount of biological data for one sample. For example, the whole-genome transcriptome can be analyzed by using one array for an individual, and more than 500,000 SNPs can be simultaneously genotyped by using SNP arrays for the same individual (the last generation of Affymetrix chips allows the analysis of 1,8 million SNPs). The nextgeneration sequencers (solexa/illumina and solid/ABI) allow the analysis of the transcriptome, of small RNAs, of DNA methylation, of SNPs, and of copy number variation at the genome scale (55) . All these technologies can produce a huge amount of data that need to be stored, transferred, carefully analyzed and interpreted. The statistical analysis is a significant challenge because a number of statistical tests are performed; to tackle this multi-testing problem, new approaches have been proposed (55, 56) . Such approaches have been used in genome-wide studies and have provided significant results from the statistical point of view. However, it is clear that most biological information is missing. This lack is highlighted by the results obtained in genome-wide linkage and association in infectious diseases. For instance, Fellay et al. (40) estimated that the polymorphisms identified explained 15% of the virus load variance in the study population, suggesting that the effect of other genes had not been detected. Strikingly, a genome-wide association study only detected the association between protection against severe malaria and hemoglobin S after correcting for multi-tests (35) , while several other genes and genetic variants have been associated with severe malaria in independent populations (57) .
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