4 research outputs found
La cartographie des sites de régulation génétique à partir de données de débalancement allélique
En 1975, Wilson et King ont proposé que l'évolution opère non seulement via des
changements affectant la structure des protéines, mais aussi via des mutations qui
modifient la régulation génétique. L'étude des éléments régulateurs de l'expression
génétique a un rôle important dans la compréhension de l'expression de différentes
maladies et de la réponse thérapeutique. Nous avons développé un algorithme bio-
informatique qui nous permet rapidement de trouver des sites de régulation génétique
à travers tout le génome et pour une grande quantité de gènes. Notre approche
consiste à trouver des sites polymorphes (SNPs) qui sont en déséquilibre de liaison
avec le débalancement allélique (AI) afin de cartographier la région régulatrice et le
site responsable. Notre méthode est avantageuse par rapport à d'autres méthodes, car elle n'a pas besoin des données « phasées». De plus, les données de débalancement allélique ne sont pas affectées par des facteurs externes étant donné qu'ils sont mesurés dans la même cellule. Nous avons démontré que notre approche est fiable et qu'elle peut détecter des sites loin du gène. De plus, il peut être appliqué à des données de génotypage sans avoir besoin de les « phaser » .Wilson and King (1975) proposed that evolution frequently operates through mutations affecting genetic regulation. Likewise, it is expected that genetic variation responsible for inter-individual differences will be due to variation in regulatory sites. Identifying such sites is thus important in the genetic and medical research. We have developed a new bioinformatics algorithm to find genome-wide regulatory sites for a big number of genes. Individuals carrying different alleles at a regulatory site will exhibit allelic imbalance(AI) due to differential expression of the two copies the same locus. Our approach consists of searching polymorphic sites (SNPs) in linkage disequilibrium with AI in order to map regulatory regions. We have detected many SNPs associated to the regulation of different genes pointed in previous studies. We have also found regulatory regions far from the transcription start site
(TSS). The major advantage of this method is that phased data is not needed. In addition, AI data has the benefit of not being affected by external factors since it is
measured in the same cell. The results show that our approach is reliable and it can
detect sites far from the gene
An atlas of over 90.000 conserved noncoding sequences provides insight into crucifer regulatory regions
Despite the central importance of noncoding DNA to gene regulation and evolution, understanding of the extent of selection on plant noncoding DNA remains limited compared to that of other organisms. Here we report sequencing of genomes from three Brassicaceae species (Leavenworthia alabamica, Sisymbrium irio and Aethionema arabicum) and their joint analysis with six previously sequenced crucifer genomes. Conservation across orthologous bases suggests that at least 17% of the Arabidopsis thaliana genome is under selection, with nearly one-quarter of the sequence under selection lying outside of coding regions. Much of this sequence can be localized to approximately 90,000 conserved noncoding sequences (CNSs) that show evidence of transcriptional and post-transcriptional regulation. Population genomics analyses of two crucifer species, A. thaliana and Capsella grandiflora, confirm that most of the identified CNSs are evolving under medium to strong purifying selection. Overall, these CNSs highlight both similarities and several key differences between the regulatory DNA of plants and other species
The Capsella rubella genome and the genomic consequences of rapid mating system evolution
The shift from outcrossing to selfing is common in flowering plants, but the genomic consequences and the speed at which they emerge remain poorly understood. An excellent model for understanding the evolution of self fertilization is provided by Capsella rubella, which became self compatible <200,000 years ago. We report a C. rubella reference genome sequence and compare RNA expression and polymorphism patterns between C. rubella and its outcrossing progenitor Capsella grandiflora. We found a clear shift in the expression of genes associated with flowering phenotypes, similar to that seen in Arabidopsis, in which self fertilization evolved about 1 million years ago. Comparisons of the two Capsella species showed evidence of rapid genome-wide relaxation of purifying selection in C. rubella without a concomitant change in transposable element abundance. Overall we document that the transition to selfing may be typified by parallel shifts in gene expression, along with a measurable reduction of purifying selection