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Results for “Omnigenic model”

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Simulation of CRISPR/Cas9-mediated gene editing for the Vitellogenin gene in Apis mellifera.

CRISPR/Cas9 genome editing provides a powerful framework for interrogating gene function in Apis mellifera. Yet, empirical application remains challenging due to biological constraints, including haplodiploid genetics, narrow embryonic injection window, and the social rearing requirements that complicate functional validation. These constraints necessitate in silico pre-screening to maximize editing success before resource-intensive wet-lab implementation. Within the omnigenic framework, which distinguishes core regulatory genes from peripheral loci buffered by network effects, vitellogenin (Vg) represents an optimal target which is ancestrally dedicated to yolk provisioning; it has been co-opted to orchestrate diverse non-reproductive functions including longevity, stress resistance, immunity, and social behavior. We developed a computational pipeline to design a list of 57 and 56 candidate guide RNAs (gRNA) for targeted Vg knockout, evaluating candidate sites in both functional exons 2 and 3 based on structural accessibility and frameshift efficiency. Comparative analysis revealed complementary strengths in two top-best candidates from initial target pool of predicted gRNAs. The gRNA targeting exon 2 exhibits weaker secondary structure (ΔG = -0.25 kcal/mol versus -2.10 kcal/mol for exon 3), aligning with empirical evidence that sites with ΔG > -1.0 kcal/mol achieve 2-5 × higher Cas9 binding efficiency. This site yielded moderate frameshift frequency (77.8%; 61.9 percentile). Conversely, the predicted editing outcome for the gRNA targeting exon 3, despite stronger structural constraints, demonstrated superior functional disruption metrics demonstrating very high frameshift frequency (88.3%; 95.2 percentile), high in silico editing precision, minimal microhomology-mediated repair bias, and reproducible outcomes wherein nearly all predicted indels disrupt the coding sequence. Protein structure and domain analyses further predict that frameshift edits will generate a truncated protein missing all downstream functional domains. We recommend parallel empirical validation of both exon 2 and exon 3 targets to resolve the trade-off between structural accessibility (favoring higher editing rates) and frameshift efficacy (favoring complete loss-of-function). This dual-target strategy accommodates uncertainty in in vivo performance while maximizing the probability of generating informative phenotypes. Our in silico framework enables rational CRISPR design in non-model organisms by computationally balancing biophysical accessibility with functional impact, accelerating functional genomics in species where empirical optimization faces substantial biological constraints.

Animals

Genome-Wide Aggregated Trans Effects Analysis Identifies Genes Encoding Immune Checkpoints as Core Genes for Rheumatoid Arthritis.

OBJECTIVE: The sparse effector "omnigenic" hypothesis postulates that the polygenic effects of common single nucleotide polymorphisms (SNPs) on a typical complex trait are mediated by trans effects that coalesce on expression of a relatively sparse set of core genes. The objective of this study was to identify core genes for rheumatoid arthritis by testing for association of rheumatoid arthritis with genome-wide aggregated trans effects (GATE) scores for expression of each gene as transcript in whole blood or as circulating protein levels. METHODS: GATE scores were calculated for 5,400 cases and 453,705 non-cases of primary rheumatoid arthritis in UK Biobank participants of European ancestry. RESULTS: Testing for association with GATE scores identified 16 putative core genes for rheumatoid arthritis outside the HLA region, of which six-TP53BP1, PDCD1, TNFRSF14, LAIR1, LILRA4, and IDO1-were supported by Mendelian randomization analysis based on the marginal likelihood of the causal effect parameter. Five of these 16 genes were validated by a reported association of rheumatoid arthritis with SNPs within 200 kb of the transcription site, eight by association of the measured protein level with rheumatoid arthritis in UK Biobank, 10 by experimental perturbation in mouse models of inflammatory arthritis, and two-CTLA4 and PDCD1-by evidence that drugs targeting the gene cause or ameliorate inflammatory arthritis in humans. Fourteen of these 16 genes are in pathways affecting immunity or inflammation, and six-CD5, CTLA4, TIGIT, LAIR1, TNFRSF14, and PDCD1-encode receptors that have been characterized as immune checkpoints exploited by cancer cells to escape the immune response. CONCLUSION: These results highlight the key role of immune checkpoints in rheumatoid arthritis and identify possible therapeutic targets.

Humans