Fig 1: Identification of 1st tier candidate L1 expression regulators in the European cohort.(A) A schematic for how 1st tier candidate genes were defined. In short, these were genes in trios with index SNVs that were at the top of their respective peak. (B) The three-part integration results for three protein-coding genes—STARD5, IL16, HSD17B12—that we considered first tier candidates for functional, in vitro testing. In the left column are the trans-eQTLs, in the middle column are the cis-eQTLs, and in the right column are the linear regressions for gene expression against L1 subfamily expression. Expression values following an inverse normal transform (INT) are shown. The FDR for each analysis is listed at the top of each plot. FDR: False Discovery Rate.
Fig 2: Impact of IL16 and STARD5 overexpression on LCL gene and TE expression landscapes.IL16 and STARD5 overexpression induce changes consistent with their known biology, as well as subtle but widespread upregulation of TE families. (A) Scheme for experimentally validating the roles of IL16 and STARD5 in L1 regulation. GSEA analysis for top, differentially regulated (B) GO Biological Process and (C) Reactome pathway gene sets following IL16 overexpression. GSEA analysis for top, differentially regulated (D) GO Biological Process and (E) Reactome pathway gene sets following STARD5 overexpression. (F) GSEA analysis for shared, significantly regulated TE family gene sets following IL16 and STARD5 overexpression. (G) GSEA plots for the L1 family gene set results summarized in (F). For these plots, the FDR value is listed. In each bubble plot, the size of the dot represents the −log10(FDR) and the color reflects the normalized enrichment score. FDR: False Discovery Rate. Some panels were created with BioRender.com.
Fig 3: rhIL16 treatment is sufficient to transiently upregulate an L1 family gene set.(A) Scheme for experimentally validating the role of rhIL16 in L1 regulation. GSEA analysis for top, shared, concomitantly regulated (B) GO Biological Process and (C) Reactome pathway gene sets following IL16 overexpression and rhIL16 exposure for 24 hours. Shared gene sets were ranked by combining p-values from each individual treatment analysis using Fisher’s method. (D) GSEA analysis for top, differentially regulated TE family gene sets following rhIL16 exposure for 24 hours. The GSEA plot for the L1 family gene set result summarized in the bubble plot is also shown. For this plot, the FDR value is listed. In each bubble plot, the size of the dot represents the −log10(FDR) and the color reflects the normalized enrichment score. FDR: False Discovery Rate. Some panels were created with BioRender.com.
Fig 4: L1 trans-eQTLs are associated with subtle, widespread differences in TE families and known TE-associated pathways.(A) Scheme for functionally annotating gene-linked index SNVs by GSEA. (B) GSEA analysis for shared, significantly regulated TE family gene sets across genotypes for rs11635336 (IL16/STARD5), rs9271894 (HLA), and rs1061810 (HSD17B12). (C) GSEA plots for the L1 family gene set results summarized in (B). For these plots, the FDR value is listed. GSEA analysis for top, shared, concomitantly regulated (D) MSigDB Hallmark pathway, (E) GO Biological Process, and (F) Reactome pathway gene sets across genotypes for rs11635336 (IL16/STARD5), rs9271894 (HLA), and rs1061810 (HSD17B12). Shared gene sets were ranked by combining p-values from each individual SNV analysis using Fisher’s method. In each bubble plot, the size of the dot represents the −log10(FDR) and the color reflects the normalized enrichment score. FDR: False Discovery Rate.
Fig 5: L1 trans-eQTLs are co-associated with aging traits in GWAS databases.(A) Scheme for obtaining trans-eQTL SNV-associated aging phenotypes from the Open Targets Genetics platform. (B) A pie chart representing the number of SNVs (222/499) associated with an aging-related MeSH trait, either by PheWAS or indirectly linked to the phenotype through a proxy lead SNP in LD with the SNV. (C) Histogram depicting the distribution of number of aging MeSH traits associated with the 222/499 SNVs by PheWAS. (D) Histogram depicting the distribution of number of aging MeSH traits linked with the 222/499 SNVs through a proxy lead SNP in LD with the SNVs. (E) A diagram highlighting the organ targets of the top 10 most frequently associated aging traits. (F) The concentrations of circulating IL16 in aging mice of both sexes was assessed by ELISA. Significance across age in each sex was assessed using a Wilcoxon test. The p-values from each sex (females in pink and males in blue) were combined by meta-analysis using Fisher’s method. Any p-value < 0.05 was considered significant. Some panels were created with BioRender.com.
Supplier Page from Abcam for Mouse IL-16 ELISA Kit