Functional-based networks analyzed in each enriched CD4+ T cell gene expression module.

<p><b>A</b>: Functional-based network obtained from the immunologically enriched M9 gene expression module. <b>B</b>: Functional-based network obtained from the immunologically enriched M12 gene expression module. The dimensions of each node (i.e. gene) are proportional to its DC value and its color is based on its BC value, ranging from green (lowest BC values) to red (highest BC values). The edge width is proportional to the strength of the functional association evidences between two genes. The edge betweenness determines the edge color, ranging from green (edges connecting nodes with the lowest BC values) to red (edges connecting nodes with the highest BC values).</p

Building of functional-based networks for M9 and M12 CD4+ gene expression modules using biological knowledge.

<p><b>A</b>: Functional-based network obtained from the immunologically enriched M9 gene expression module where 15 genes display a connected network. <b>B</b>: Functional-based network obtained from the immunologically enriched M12 gene expression module, which shows a complex network structure with different subnetworks involving 247 interconnected genes.</p

Transcript Complexity Value analysis of T cell differentiation genes.

<p>The type and quantity of significant eQTLs in RA CD4+ T cells and LCL cells are compared in the genes from the Th1, Th2, Th17 and Treg differentiation pathways. Only those genes showing a significantly different genomic regulation profile (P<0.05) are shown.</p

GStream method for SNP genotyping.

<p>This figure shows how GStream genotyping method works on two example markers, the first one representing a typical marker capturing a SNP (A and B) and the second one capturing both a SNP and a CNV (C and D). The leftmost graphs show the effects of the normalization procedure for the two markers, where the dotted blue lines enclose the ranges where candidate homozygotes and heterozygotes are identified in order to compute the scaling factors for each channel (black points over the axes). The rightmost graphs give an overview of the genotyping procedure: Upper subfigures represent the scaled BAF probability density function with the solid vertical lines setting the identified genotype centres, the dotted vertical lines setting the genotype limits and the horizontal lines representing the sequential search of genotype cluster peaks. Medium and lower subfigures represent genotype calls and quality call scores respectively.</p

Power to detect CNP associations.

A<p>CNV dataset provided by custom genotyping microarray-based studies.</p>B<p>CNV datasets provided by CGH-based studies.</p><p>Percentage of −log₁₀<i>P</i> ratios higher than 0.9 and lower than 1.1 over the CNV population-associated regions computed for each study. Platform difference refers to the percentage differences between HumanOmni1-Quad and Human1M-Duo platforms.</p

GStream method for CNV genotyping.

<p>(A) Each CNV analysis is divided in four independent sets where the number of allele copies per channel intensity is estimated. Here, the homozygote intensities over its respective informative channels (upper rightmost and leftmost graphs) are fitted with a two-component model (in this case, capturing a deletion) while heterozygote intensities over each channel are better fitted with a one-component model (upper centre graphs). Lower graphs show the intensity distributions (solid black lines) together with the corresponding copy number score (red points) assigned to each sample. AA homozygotes are mostly classified as deletions (scores near to 1), BB homozygotes are divided into diploids (scores∼2) and deletions (scores∼1) while heterozygotes are classified as diploids (i.e. one allele detected at each channel). (B) Final representation of the analyzed probe where points represent samples and colour their relative copy number scores. SNP and CNV genotypes are assigned along the BAF and the intensity axis respectively.</p

Transcript Complexity Value analysis of RA risk genes.

<p>TCV from the RA CD4+ T cell and control LCLs analyzed in RA risk genes. <b>A</b>: JAK-STAT signaling pathway. <b>B</b>: T cell receptor signaling pathway. <b>C</b>: TNF signaling pathway. <b>D</b>: Cell adhesion pathway. <b>E</b>: Toll-like receptor signaling pathway. <b>F</b>: Antigen processing and presentation pathway. <b>G</b>: B cell development function pathway. The genes that are framed represent those genes showing significant genomic regulation profiles between RA CD4+ T cells and LCLs (P<0.05).</p

Workflow of the systems genetics approach for <i>trans</i>-eQTL identification.

<p>The new systems genetics approach is based on four steps that are performed before the <i>trans</i>-eQTL analysis in order to efficiently reduce the number of analyzed genes: 1) Identification of the gene expression modules (M) that characterize CD4+ T cell gene expression 2) Enrichment analysis of a specific biological process that is related to the trait of interest 3) Construction of the functional-based networks using biological knowledge within the significantly enriched modules 4) Network analysis to identify those genes that are likely to play a central role in the functional-based networks 5) <i>Trans</i>-eQTL analysis using the subset of genes that show the highest centrality in each module. Abbreviations: AT, association transfer between organisms; BK, curated biological pathway knowledge; CP, computational predictions; G, gene; M, module; PI, physical interactions; TM, text-mining.</p

Gene expression modules identified in RA CD4+ T cells.

<p>Applying the new systems genetics approach for <i>trans</i>-eQTL identification in RA CD4+ T cells and using WGCNA, 16 genes expression modules (M) that characterize the CD4+ T cells were identified. For each gene expression module, the number of gene transcripts representing each module is shown, as well as the results of the immunological enrichment analysis.</p><p>Abbreviations: NS, No Significant.</p><p>* Significant (P<0.05).</p

<i>Trans</i>-eQTL associations revealed by the application of the systems genetics approach.

<p>Applying the new systems genetics approach for <i>trans</i>-eQTL identification in RA CD4+ T cells, the associations obtained after performing the <i>trans</i>-eQTL analysis are displayed for each immunity-enriched module (P_FDR<0.01).</p><p>Abbreviations: Bp, Base pair; β, Slope coefficient; P_FDR, P-value False Discovery Rate.</p><p>* Significant (P_FDR<0.05).</p