RESUMEN
Combining genetic inheritance information, for both molecular profiles and complex traits, is a promising strategy not only for detecting quantitative trait loci (QTLs) for complex traits but for understanding which genes, pathways, and biological processes are also under the influence of a given QTL. As a primary step in determining the feasibility of such an approach in humans, we present the largest survey to date, to our knowledge, of the heritability of gene-expression traits in segregating human populations. In particular, we measured expression for 23,499 genes in lymphoblastoid cell lines for members of 15 Centre d'Etude du Polymorphisme Humain (CEPH) families. Of the total set of genes, 2,340 were found to be expressed, of which 31% had significant heritability when a false-discovery rate of 0.05 was used. QTLs were detected for 33 genes on the basis of at least one P value <.000005. Of these, 13 genes possessed a QTL within 5 Mb of their physical location. Hierarchical clustering was performed on the basis of both Pearson correlation of gene expression and genetic correlation. Both reflected biologically relevant activity taking place in the lymphoblastoid cell lines, with greater coherency represented in Kyoto Encyclopedia of Genes and Genomes database (KEGG) pathways than in Gene Ontology database pathways. However, more pathway coherence was observed in KEGG pathways when clustering was based on genetic correlation than when clustering was based on Pearson correlation. As more expression data in segregating populations are generated, viewing clusters or networks based on genetic correlation measures and shared QTLs will offer potentially novel insights into the relationship among genes that may underlie complex traits.
Asunto(s)
Perfilación de la Expresión Génica , Ligamiento Genético , Linfocitos/metabolismo , Sitios de Carácter Cuantitativo , Línea Celular , Análisis por Conglomerados , Bases de Datos Genéticas , Familia , Humanos , Modelos Estadísticos , Análisis de Secuencia por Matrices de Oligonucleótidos , Reacción en Cadena de la Polimerasa de Transcriptasa InversaRESUMEN
The most important product of the sequencing of a genome is a complete, accurate catalogue of genes and their products, primarily messenger RNA transcripts and their cognate proteins. Such a catalogue cannot be constructed by computational annotation alone; it requires experimental validation on a genome scale. Using 'exon' and 'tiling' arrays fabricated by ink-jet oligonucleotide synthesis, we devised an experimental approach to validate and refine computational gene predictions and define full-length transcripts on the basis of co-regulated expression of their exons. These methods can provide more accurate gene numbers and allow the detection of mRNA splice variants and identification of the tissue- and disease-specific conditions under which genes are expressed. We apply our technique to chromosome 22q under 69 experimental condition pairs, and to the entire human genome under two experimental conditions. We discuss implications for more comprehensive, consistent and reliable genome annotation, more efficient, full-length complementary DNA cloning strategies and application to complex diseases.
Asunto(s)
Cromosomas Humanos Par 22 , Biología Computacional , Genoma Humano , Análisis de Secuencia por Matrices de Oligonucleótidos , Algoritmos , Empalme Alternativo , Línea Celular , ADN Complementario , Exones , Proyecto Genoma Humano , Humanos , Sondas de OligonucleótidosRESUMEN
Gene expression profiling is rapidly becoming a mainstay of functional genomic studies. However, there have been relatively few studies of how the data from expression profiles integrate with more classic approaches to examine gene expression. This study used gene expression profiling of a portion of the genome of Saccharomyces cerevisiae to explore the impact of blocks in the isoprenoid biosynthetic pathway on the expression of genes and the regulation of this pathway. Approximately 50% of the genes whose expression was altered by blocks in isoprenoid biosynthesis were genes previously known to participate in the pathway. In contrast to this simple correspondence, the regulatory patterns revealed by different blocks, and in particular by antifungal azoles, was complex in a manner not anticipated by earlier studies.