Graphic representation of the frequencies of newly generated haplotypes along 24 days (corresponding to 432 generations) of evolution inside the mouse gut (see Tables S3 to S6 for numeric data).

<p>Shaded areas are proportional to the relative abundance of each haplotype. Yellow and blue shaded areas represent the two sub-populations of bacteria labeled either with <i>cfp</i> or <i>yfp</i> alleles. The ancestry relations between haplotypes can be inferred by the accumulation of new mutations in a previously existent genotype. Dash lines mark the time points in days (upper axis) or generations (lower axis) where the sampling took place. For the top two populations 1.1 (A) and 1.11 (B), 40 clones were sampled in each time point. For the bottom two populations 1.12 (C) and 1.5 (D) 20 clones were sampled in each time point.</p

Distribution of fitness effects of beneficial haplotypes that contributed to adaptation.

<p>The fitness of beneficial haplotypes (<i>ω_h</i>) was estimated under a theoretical model which assumes the minimum number of beneficial mutations required to explain the marker dynamics.</p

Evidence for rapid adaptation and CI <i>in vivo</i>.

<p><b>A</b>) Dynamics of marker frequency (with 95% confidence intervals) during the adaptation of <i>E. coli</i> to the gut upon colonization (populations 1.1 to 1.15). The predictions of the simplest model of Darwinian selection <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004182#pgen.1004182-DePaepe1" target="_blank">[22]</a>, for each set of data points are shown as lines. The lines correspond to the model that assumes multiple beneficial mutations (<i>i</i> = 1,2,5) can occur in a given clone at a given time (<i>Tb_i</i>), and these clones have a given fitness (<i>W_i</i>). <i>Tb_i</i> and <i>W_i</i> are fitted by maximum likelihood and the best model, in terms of number of mutations, is chosen according to Akaike criteria. Representative examples of trajectories for the classical signature of a selective sweep (populations 1.5, 1.12 and 1.13) and for the maintenance of neutral diversity under with intense CI (populations 1.6, 1.8 and 1.9) are shown in colours. <b>B</b>) Direct evidence for adaptation and CI: the bars represent the mean selection coefficient (±2 s.e.m, n = 3) from an <i>in vivo</i> competitive fitness assay between evolved and ancestral clones. The first bar shows the neutrality of the fluorescent marker. The following six bars represent the results from competitions of a mixture of thirty clones (with a given fluorescent marker, indicated below the bar) isolated from the respective population (indicated below each bar). Both CFP and YFP mixtures of clones from lineages 1.6 and 1.8 show similar levels of adaptation, consistent with intense CI maintaining a high frequency of both neutral markers. The dashed bars show the results of competitions (n = 2) of single clones isolated from lineage 1.12.</p

Emergence and spread of beneficial mutations in the <i>gat</i> operon.

<p>Dynamics of frequency change of the <i>gat</i>-negative phenotype over time are shown for all populations (1.1 to 1.15). Inset: The natural logarithm of the ratio of <i>gat</i>-negative individuals to wild type over the first 5 days of adaptation is shown as dots. Each group of points was fitted to a linear regression (represented as lines). Highlighted in bold is the population 1.12 for which the slope corresponds to an estimate of the selection coefficient of 0.075±0.01 (per generation).</p

The genetic basis of adaptive mutations and the level of parallelism between populations.

<p>Identified mutations in clones isolated from populations 1.1 to 1.14 (evolved <i>in vivo</i> for 24 days), represented along the <i>E. coli</i> chromosome. For simplicity, the genomes are represented linearly and vertically drawn. The type and position of mutations are shown by triangles for insertions and deletions, small vertical bars denote single nucleotide polymorphisms (SNPs), and one duplication in clone number 1.12 is depicted as a horizontal bar. See the symbol legend for other events. The genes <i>dcuB</i>, <i>srlR</i> and <i>focA</i> and one operon (<i>gat</i>) are highlighted. These represent regions of parallel mutation in at least two genomes. The genomic context of these mutations is represented on the right. (reg) after the gene name, means that the regulatory region, rather than the coding region, was affected. Numbers above marked mutations represent the number of times a particular mutation was detected at the same position.</p

Presentation_1_The rare DRB1*04:08-DQ8 haplotype is the main HLA class II genetic driver and discriminative factor of Early-onset Type 1 diabetes in the Portuguese population.pdf

IntroductionEarly-onset Type 1 diabetes (EOT1D) is considered a disease subtype with distinctive immunological and clinical features. While both Human Leukocyte Antigen (HLA) and non-HLA variants contribute to age at T1D diagnosis, detailed analyses of EOT1D-specific genetic determinants are still lacking. This study scrutinized the involvement of the HLA class II locus in EOT1D genetic control.MethodsWe conducted genetic association and regularized logistic regression analyses to evaluate genotypic, haplotypic and allelic variants in DRB1, DQA1 and DQB1 genes in children with EOT1D (diagnosed at £5 years of age; n=97), individuals with later-onset disease (LaOT1D; diagnosed 8-30 years of age; n=96) and nondiabetic control subjects (n=169), in the Portuguese population.ResultsAllelic association analysis of EOT1D and LaOT1D unrelated patients in comparison with controls, revealed that the rare DRB1*04:08 allele is a distinctive EOT1D susceptibility factor (corrected p-value=7.0x10-7). Conversely, the classical T1D risk allele DRB1*04:05 was absent in EOT1D children while was associated with LaOT1D (corrected p-value=1.4x10-2). In corroboration, HLA class II haplotype analysis showed that the rare DRB1*04:08-DQ8 haplotype is specifically associated with EOT1D (corrected p-value=1.4x10-5) and represents the major HLA class II genetic driver and discriminative factor in the development of early onset disease.DiscussionThis study uncovered that EOT1D holds a distinctive spectrum of HLA class II susceptibility loci, which includes risk factors overlapping with LaOT1D and discriminative genetic configurations. These findings warrant replication studies in larger multicentric settings encompassing other ethnicities and may impact target screening strategies and follow-up of young children with high T1D genetic risk as well as personalized therapeutic approaches.</p

Correlations between CD25^bright/CD4⁺ aTreg frequencies and immunoblot band numbers.

<p>A–C: Bands recognized in immunoblots of HEp2-cytoplasmic proteins by SLE patients, unaffected relatives and unrelated control subjects. D–F: Bands recognized in immunoblots of HEp2-nuclear proteins. Regression lines represent linear regression.</p

Sample characterization.

<p>Sample characterization.</p

Group-wise coreferentialities between CD25^bright/CD4+ aTreg frequencies and <i>IL2RA</i> genetic-effects model scores.

<p>A: SLE patients, B: unaffected relatives, C: unrelated controls. Reactivities to cytoplasmic bands are indicated by filled circles, anti-nuclear reactivities by triangles and anti-brain reactivities by crosses.</p

Correlations between aTreg frequencies (CD25^bright/CD4⁺) and quantified SLE-associated specific autoreactive IgG.

<p>A–C: IgG anti-dsDNA. D–F: IgG anti-Sm. Regression lines represent linear regression.</p