SNP rediscovery rate increases with increasing sample size when using the whole exome sequencing results as the gold standard.

<p>The dotted line shows the discovery rates of the total 886 individuals with WGS data. Each point is an average of 100 subsamples of size <i>n</i> from 886 individuals. Bootstrap resampling without replacement was carried out for each data point at various sample sizes.</p

Distribution of ENCODE functional regions genome-wide and in the top 1% of iHS hits.

<p>Categories are the 7 identified ENCODE functional regions inferred from the combined ChromHMM and Segway results plus the “none” category indicating loci without functional annotation. All categories except for weak enhancers (WE) show significant differences between the two datasets with a <i>P</i> <0.0063 by a χ² test. CTCF: CTCF enriched element; WE:Weak Enhancer; T:Transcribed Region; E: Enhancer; PF:Promoter Flank; R: Repressed/Low Activity; TSS: promoter region including transcription start site.</p

Genetic diversity across functional categories in the CHARGE-S participants.

<p><b>A</b> is the distribution of nucleotide diversity across different categories of non-coding regions. <b>B</b> presents the frequency spectra of the minor allele in the studied population. The <i>x</i>-axis is the number of minor alleles in each non-coding category and the <i>y</i>-axis is the frequency of the chromosomes that carry that allele.</p

Nucleotide diversities (π) in the 3’UTRs and miRNA target sites that are identified in the TargetScan program.

<p><b>A</b> the target sites of the conserved miRNAs that are identified with conservation criteria of miRNA-target pairing. Sites are classified with increasing P_CT score, which means higher stringency criteria. P_CT = 0 means the nucleotide sites in the 3’ UTRs are not inside any “seed pairing” regions. <b>B</b> the target sites of the conserved miRNAs that are identified with the context score of the miRNA pairing. Smaller context scores mean the target sites have high probability to be regulated by miRNAs. The nucleotide sites in the 3’ UTRs that are not inside any “seed pairing” regions have a context score of 0.05.</p

Population Genomic Analysis of 962 Whole Genome Sequences of Humans Reveals Natural Selection in Non-Coding Regions

<div><p>Whole genome analysis in large samples from a single population is needed to provide adequate power to assess relative strengths of natural selection across different functional components of the genome. In this study, we analyzed next-generation sequencing data from 962 European Americans, and found that as expected approximately 60% of the top 1% of positive selection signals lie in intergenic regions, 33% in intronic regions, and slightly over 1% in coding regions. Several detailed functional annotation categories in intergenic regions showed statistically significant enrichment in positively selected loci when compared to the null distribution of the genomic span of ENCODE categories. There was a significant enrichment of purifying selection signals detected in enhancers, transcription factor binding sites, microRNAs and target sites, but not on lincRNA or piRNAs, suggesting different evolutionary constraints for these domains. Loci in “repressed or low activity regions” and loci near or overlapping the transcription start site were the most significantly over-represented annotations among the top 1% of signals for positive selection.</p></div

Intervention dans le Podcast les Arts du FLE pour faire le point sur la perspective actionnelle en classe de langues

Ce podcast est disponible en ligne, à l'adresse suivante :https://agi.to/podcast/arts-du-fle-08-actionne-ton-approche/Ce numéro 8 des Arts du FLE (émission spécialisée en FLE) propose un dossier spécial approches pédagogiques et perspective actionnelle. J'en suis l'invitée et j'y réponds de manière détaillée pendant près d'une heure aux questions de l'animateur et créateur de ce Podcast, Sébastien Durietz (en poste actuellement à l'ONU, à New-York)

Additional file 10: Table S9. of DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases

Significant associations between DNA methylation and corresponding nearby genetic variants and between the genetic variant and CRP in the largest published GWAS of CRP (n = 66,185). (XLSX 12 kb

Additional file 6: Figures S1–S4. of DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases

(PDF 1036 kb

Additional file 9: Table S8. of DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases

Significant methylation-expression results and corresponding expression-CRP results for the replicated CpGs. (XLSX 11 kb