RESUMO
These last 20 years, several techniques have been developed for quantifying DNA methylation, the most studied epigenetic marks in eukaryotes, including the gold standard method, whole-genome bisulphite sequencing (WGBS). WGBS quantifies genome-wide DNA methylation but has several inconveniences rendering it less suitable for population-scale epigenetic studies. The high cost of deep sequencing and the large amounts of data generated prompted us to seek an alternative approach. Restricting studies to parts of the genome would be a satisfactory alternative had there not been a major limitation: the need to select upstream targets corresponding to differentially methylated regions (DMRs) as targets. Given the need to study large numbers of samples, we propose a strategy for investigating DNA methylation variation in natural populations, considering the structural complexity of the genomes with their size and their content in unique as coding regions versus repeated regions as transposable elements. We first identified regions of highly variable DNA methylation in a representative subset of genotypes representative of the biological diversity in the population by WGBS. We then analysed the variations of DNA methylation in these targeted regions at the population level by Sequencing Capture Bisulphite (SeqCapBis). The entire strategy was then validated by applying it to another species. Our strategy was developed as a proof of concept on natural populations of two forest species: Populus nigra and Quercus petraea.
RESUMO
The TATA box is one of the best characterized transcription factor binding sites. However, it is not a ubiquitous element of core promoters, and other sequence motifs such as Y Patches seem to play a major role in plants. Here, we present a first genome-wide computational analysis of the TATA box and Y Patch distribution in rice (Oryza sativa L. subsp. japonica) promoter sequences. Utilizing a probabilistic sequence model, we ascertain that only approximately 19% of rice genes possess the TATA box, but approximately 50% contain one or more Y Patches in their core promoters. By computational processing of identified elements, we generated extended TATA box and Y Patch nucleotide frequency matrices capable of predicting these motifs in plants with a high degree of confidence.
