miRNA conservation in clustered and non-clustered miRNAs.

<p>(<b>A</b>) Single nucleotide variant (SNV) density in clustered or non-clustered miRNAs, calculated as the average number of fixed substitutions in any of the great ape populations across the precursor miRNA. (<b>B</b>) Molecular age of clustered and non-clustered miRNAs. Molecular age is taken from Iwama et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0154194#pone.0154194.ref017" target="_blank">17</a>] were each integer represents a period of origin with the oldest miRNAs having a value of -1 (right after the split between mammals and birds) and the youngest a value of 13 (after the split between humans and chimpanzees). (<b>C</b>) Correlation between SNV density and expression, calculated as the average expression values for miRNAs across five human tissues (cerebellum, brain, heart, kidney and testis) taken from Meunier et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0154194#pone.0154194.ref016" target="_blank">16</a>].</p

Deregulated and target genes of the studied miRNAs.

<p>(<b>A</b>) Number of deregulated genes for human (black), non-human (white) and both (grey) miRNA variants from microarray experiments in transfected SH-SY5Y cells. Deregulated genes were obtained based on the fold change in gene expression (adjusted p < 0.05; fold change > 1.2) when comparing cells transfected with the studied miRNA mimic variants and cells transfected with the negative control. (<b>B</b>) Number of target genes predicted by PITA algorithm (ΔΔG score ≤ -10) for the studied miRNAs for human (black), non-human (white) and both (grey) miRNA variants. Percentages indicate the portion of exclusive (outside the intersection) or common (inside the intersection) genes among the total number of regulated (<b>A</b>) or target (<b>B</b>) genes for each variant.</p

Main characteristics of the miRNAs selected for functional analyses.

<p>Main characteristics of the miRNAs selected for functional analyses.</p

Candidate genes exclusively deregulated and targeted by human miR-541-3p.

<p>Candidate genes exclusively deregulated and targeted by human miR-541-3p.</p

Variation across miRNA (precursor, mature and seed) and flanking (3’ and 5’) regions, in the great ape populations.

<p>(<b>A</b>) Single nucleotide variant (SNV) density calculated as the average number of fixed substitutions in concatenated regions within each population. (<b>B</b>) Boxplot showing standardized (Z-score) nucleotide diversity (pi). (<b>C</b>) Average PhastCons conservation scores. Regions with no statistically significant differences share the same color. Asteriks represent statistically significant differences. Error bars in (<b>A</b>) and (<b>C</b>) represent the standard error of the mean.</p

Hairpin structures and stabilities of the studied miRNAs.

<p>Minimum free energy (MFE) and secondary structure predictions for human (hsa), chimpanzee (ptr) and macaque (mml) miRNA precursor sequences (miRBase, release 21), according to RNAfold. Grey circles represent nucleotide changes between miRNAs.</p

miRNA expression levels.

<p>(<b>A</b>) Expression levels represented as total number of sequencing reads of the ten miRNAs with human-specific substitutions in the mature or seed region and with the highest expression levels across brain regions (values taken from Allan Brain Atlas) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0154194#pone.0154194.ref032" target="_blank">32</a>]. (<b>B</b>-<b>C</b>) Expression levels of miR-299-3p, miR-503-3p, miR-508-3p and miR-541-3p measured by RT-qPCR in different mammalian tissues (<b>B</b>) and in different human brain regions (<b>C</b>). Brain regions in (<b>A</b>) are A1C: primary auditory cortex (core); AMY: amygdaloid complex; CBC: cerebellar cortex; DFC: dorsolateral prefrontal cortex; HIP: hippocampus (hippocampal formation); IPC: posteroinferior (ventral) parietal cortex; ITC: inferolateral temporal cortex (area TEv, area 20); M1C: primary motor cortex (area M1, area 4); MD: mediodorsal nucleus of thalamus; MFC: anterior (rostral) cingulate (medial prefrontal) cortex; OFC: orbital frontal cortex; S1C: primary somatosensory cortex (area S1, areas 3,1,2); STC: posterior (caudal) superior temporal cortex (area TAc); STR: striatum; V1C: primary visual cortex (striate cortex, area V1/17); VFC: ventrolateral prefrontal cortex. Brain tissues in (<b>B</b>) correspond to frontal cortex in all species.</p

Great ape individuals and miRNAs changes analyzed in this study.

<p>Boxes indicate the number of species-specific nucleotide substitutions along the great ape phylogeny since the split with humans (or with chimpanzees in the case of humans), in the precursor (dark grey), mature (light grey) and seed (white) miRNA regions. Total number of miRNAs in which these changes occur is shown in brackets. No species-specific nucleotide substitutions were considered for bonobo (<i>Pan paniscus</i>) due to the low quality genome annotation in this group may underestimate the real number of species-specific substitutions in the rest of the groups, and for gorillas (<i>Gorilla beringei</i>) due to the low number of individuals that are representative of this population.</p

data_sheet_1_Evaluating the Genetics of Common Variable Immunodeficiency: Monogenetic Model and Beyond.PDF

<p>Common variable immunodeficiency (CVID) is the most frequent symptomatic primary immunodeficiency characterized by recurrent infections, hypogammaglobulinemia and poor response to vaccines. Its diagnosis is made based on clinical and immunological criteria, after exclusion of other diseases that can cause similar phenotypes. Currently, less than 20% of cases of CVID have a known underlying genetic cause. We have analyzed whole-exome sequencing and copy number variants data of 36 children and adolescents diagnosed with CVID and healthy relatives to estimate the proportion of monogenic cases. We have replicated an association of CVID to p.C104R in TNFRSF13B and reported the second case of homozygous patient to date. Our results also identify five causative genetic variants in LRBA, CTLA4, NFKB1, and PIK3R1, as well as other very likely causative variants in PRKCD, MAPK8, or DOCK8 among others. We experimentally validate the effect of the LRBA stop-gain mutation which abolishes protein production and downregulates the expression of CTLA4, and of the frameshift indel in CTLA4 producing expression downregulation of the protein. Our results indicate a monogenic origin of at least 15–24% of the CVID cases included in the study. The proportion of monogenic patients seems to be lower in CVID than in other PID that have also been analyzed by whole exome or targeted gene panels sequencing. Regardless of the exact proportion of CVID monogenic cases, other genetic models have to be considered for CVID. We propose that because of its prevalence and other features as intermediate penetrancies and phenotypic variation within families, CVID could fit with other more complex genetic scenarios. In particular, in this work, we explore the possibility of CVID being originated by an oligogenic model with the presence of heterozygous mutations in interacting proteins or by the accumulation of detrimental variants in particular immunological pathways, as well as perform association tests to detect association with rare genetic functional variation in the CVID cohort compared to healthy controls.</p