Biology subjects

Eisenberg, E.

Publications and source records attributed to Eisenberg, E..

3 recordsLinked to original sources

bioRxiv2025

A Cytoplasmic Index for Quantifying Immune-Related A-to-I RNA Editing

Distinguishing self from non-self is a major challenge for the immune system. Endogenous cytoplasmic double-stranded RNA (dsRNA) can mimic viral RNA and activate immune sensors like MDA5. ADAR1-mediated A-to-I editing disrupts base-pairing to suppress immunogenicity of these endogenous structures. Global editing indices are widely used to probe this crucial ADAR1 function. However, they are dominated by nuclear pre-mRNA edits with limited immune relevance. Here we present the Cytoplasmic Editing Index (CEI) that quantifies editing specifically within dsRNA structures in mature cytoplasmic transcripts, which carry higher immunological risk. Analyzing over 25,000 RNA-seq samples, we demonstrate CEI captures ADARp150 activity and outperforms the global editing index in terms of sensitivity and signal-to-noise, enabling sharper tissue-specific profiling, enhanced detection power of infection-induced editing changes, and stronger association with cancer prognoses. An open-source, cloud-native pipeline delivers end-to-end, reproducible analysis at very low cost, supporting immediate, scalable adoption. Micro-abstractThe Cytoplasmic Editing Index (CEI) quantifies immune-relevant A-to-I RNA editing in inverted Alu clusters within 3'UTRs, capturing interferon-inducible ADAR1p150-dependent events. Analysis of >25,000 RNA-seq samples demonstrates CEI outperforms the global editing index in sensitivity and specificity, resolving tissue- and infection-linked editing patterns. An open-source, cloud-native pipeline enables scalable, low-cost deployment. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/692070v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@159ae9org.highwire.dtl.DTLVardef@6d6119org.highwire.dtl.DTLVardef@101b4a1org.highwire.dtl.DTLVardef@f9d96b_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2020

Evolutionary forces on A-to-I RNA editing revealed by sequencing individual honeybee drones

Social insects exhibit extensive phenotypic diversities among the genetically similar individuals, suggesting a role for the epigenetic regulations beyond the genome level. The ADAR-mediated adenosine-to-inosine (A-to-I) RNA editing, an evolutionarily conserved mechanism, facilitates adaptive evolution by expanding proteomic diversities. Here, we characterize the A-to-I RNA editome of honeybees (Apis mellifera), identifying 407 high-confidence A-to-I editing sites. Editing is most abundant in the heads, and shows signatures for positive selection. Editing behavior differs between foragers and nurses, suggesting a role for editing in caste differentiation. Although only five sites are conserved between bees and flies, an unexpectedly large number of genes exhibit editing in both species, albeit at different locations, including the nonsynonymous auto-editing of Adar. This convergent evolution, where the same target genes independently acquire recoding events in distant diverged clades, together with the signals of adaptation observed in honeybees alone, further supports the notion of recoding being adaptive.

evolutionary biology↗

bioRxiv2017

A-to-I RNA editing uncovers hidden signals of adaptive genome evolution in animals

In animals, the most common type of RNA editing is the deamination of adenosines (A) into inosines (I). Because inosines base-pair with cytosines (C), they are interpreted as guanosines (G) by the cellular machinery and genomically encoded G alleles at edited sites mimic the function of edited RNAs. The contribution of this hardwiring effect on genome evolution remains obscure. We looked for population genomics signatures of adaptive evolution associated with A-to-I RNA edited sites in humans and Drosophila melanogaster. We found that single nucleotide polymorphisms at edited sites occur 3 (humans) to 15 times (Drosophila) more often than at unedited sites, the nucleotide G is virtually the unique alternative allele at edited sites and G alleles segregate at higher frequency at edited sites than at unedited sites. Our study reveals that coding synonymous and nonsynonymous as well as silent and intergenic A-to-I RNA editing sites are likely adaptive in the distantly related human and Drosophila lineages.

evolutionary biology↗