Genetic architecture of flowering time in maize as inferred from quantitative trait loci meta-analysis and synteny conservation with the rice genome.

Genetic architecture of flowering time in maize was addressed by synthesizing a total of 313 quantitative trait loci (QTL) available for this trait. These were analyzed first with an overview statistic that highlighted regions of key importance and then with a meta-analysis method that yielded a synthetic genetic model with 62 consensus QTL. Six of these displayed a major effect. Meta-analysis led in this case to a twofold increase in the precision in QTL position estimation, when compared to the most precise initial QTL position within the corresponding region. The 62 consensus QTL were compared first to the positions of the few flowering-time candidate genes that have been mapped in maize. We then projected rice candidate genes onto the maize genome using a synteny conservation approach based on comparative mapping between the maize genetic map and japonica rice physical map. This yielded 19 associations between maize QTL and genes involved in flowering time in rice and in Arabidopsis. Results suggest that the combination of meta-analysis within a species of interest and synteny-based projections from a related model plant can be an efficient strategy for identifying new candidate genes for trait variation.

Large-scale analysis of gene expression: methods and application to the kidney.

Characterization of tissue-specific gene expression profiles, or transcriptomes, may serve two purposes: a) establishing relationships between cell transcriptomes and functions (i.e. molecular and physiological phenotypes) under physiological and pathophysiological conditions serves to elucidate gene functions, and b) determination of the totality of genes expressed in a cell seems a prerequisite for understanding cell functions, because the properties of proteins vary with their environment. Sophisticated methods are now available for transcriptome analysis. They are based on serial, partial sequencing of cDNAs (sequencing of expressed sequenced tags (ESTs) and serial analysis of gene expression (SAGE)), or on parallel hybridization of labeled cDNAs to specific probes immobilized on a grid (macro- and microarrays and DNA chips). Some methods were designed specifically to compare gene expression under different conditions (substractive hybridization, glass microarrays). However, all these methods require several microg of mRNA as starting material, making impossible, in most tissues, to analyse gene expression in homogeneous cell populations. To get around this limitation, we developed a scaled-down SAGE method (SAGE adaptation to downsized extracts: SADE) in our laboratory. SAGE is based on the following: a) each cDNA is characterized by a 10-bp informative sequence called tag, b) the information from several transcripts is condensed into a single DNA molecule by concatenation of several tags, c) sequencing of individual clones from the library of concatemers, computer analysis of sequences and interrogation of sequence databases allow quantitative gene expression profiling. Applied to microdissected mouse nephron segments, SADE made it possible to determine segment-specific transcriptomes.

Renal transcriptomes: segmental analysis of differential expression.

BACKGROUND/AIMS: Progress accomplished by complete genomes and cDNA-sequencing projects calls for methods that fully use these resources to study gene expression patterns in characterized cell populations. However, since the number of functional genes cannot be readily inferred from the genomic sequence, it is highly desirable to make use of methods enabling to study both known and unknown genes. METHODS: The method of serial analysis of gene expression provides short diagnostic cDNA tags without bias towards known genes. In addition, the frequency of each tag in the library conveys quantitative information on gene expression. A microassay was set-up to perform serial analysis of gene expression in minute samples such as those obtained by microdissecting nephron segments. RESULTS: Studies carried out in the thick ascending limb of Henle's loop and the collecting duct of the mouse kidney provided expression data for several thousand genes. Known markers were found appropriately enriched, and several of the thick ascending limb or collecting duct specific transcripts had no database match. CONCLUSIONS: The microassay for serial analysis of gene expression makes possible large-scale quantitative measurements of mRNA levels in nephron segments. The comprehensive picture generated by analyzing both known and unknown transcripts in defined cell populations should help to discover genes with dedicated functions.