Search bioRxiv⌕ Search

bioRxiv · 10.1101/212753

Genomic Loci Modulating Retinal Ganglion Cell Death Following Elevated IOP in the Mouse

Abstract

The present study was designed to identify genomic loci modulating the susceptibility of retinal ganglion cells (RGC) to elevated intraocular pressure (IOP) in the BXD recombinant inbred mouse strain set. IOP was elevated by injecting magnetic microspheres into the anterior chamber and blocking the trabecular meshwork using a handheld magnet to impede drainage. The IOP was then measured over the next 21 days. Only animals with IOP greater than 25 mmHg for two consecutive days or an IOP above 30 mmHg on a single day after microsphere-injection were used in this study. On day 21, mice were sacrificed and the optic nerve was processed for histology. Axons were counted for both the injected and the control eye in 49 BXD strains, totaling 181 normal counts and 191 counts associated with elevated IOP. The axon loss for each strain was calculated and the data were entered into genenetwork.org. The average number of normal axons in the optic nerve across all strains was 54,788 {+/-} 16% (SD), which dropped to 49,545 {+/-} 20% in animals with artificially elevated IOP. Interval mapping demonstrated a relatively similar genome-wide map for both conditions with a suggestive Quantitative Trait Locus (QTL) on proximal Chromosome 3. When the relative axon loss was used to generate a genome-wide interval map, we identified one significant QTL (p<0.05) on Chromosome 18 between 53.6 and 57 Mb. Within this region, the best candidate gene for modulating axon loss was Aldh7a1. Immunohistochemistry demonstrated ALDH7A1 expression in mouse RGCs. ALDH7A1 variants were not significantly associated with glaucoma in the NEIGHBORHOOD GWAS dataset, but this enzyme was identified as part of the butanoate pathway previously associated with glaucoma risk. Our results suggest that genomic background influences susceptibility to RGC degeneration and death in an inducible glaucoma model.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Struebing, F. L., King, R., Li, Y., Bailey, J. C., NEIGHBORHOOD Consortium,, Wiggs, J., Geisert, E. E.. 2017-11-01. Genomic Loci Modulating Retinal Ganglion Cell Death Following Elevated IOP in the Mouse. https://doi.org/10.1101/212753

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Cellular context shapes the transcriptomic impact of somatic variants

Somatic SNVs are commonly prioritized by recurrence or sequence annotation, leaving the molecular consequences of private variants unresolved. We developed PrismSNV and Ligo-Seq, a single-cell full-length transcriptome sequencing platform, to quantify transcriptomic displacement associated with within-cell SNV-state toggling. Across 26 samples from three cancer types, more than 60% of candidate SNVs showed significant cell-type-specific displacement with over 30% variation in magnitude. Sequence-based deleteriousness was poorly aligned with cellular displacement, and fewer than 3% of top-displacement SNVs across six tumor types were catalogued in ClinVar. Displacement was strongest in transcriptionally plastic, less differentiated states. Analysis of 655,349 CD4+ T-cell transcriptomes further showed that SNV-gene associations changed in magnitude and sometimes direction during activation. Lack of recurrence or clinical annotation does not imply transcriptomic inertness; variant impact is shaped by cellular context rather than sequence alone, establishing the variant-cell pair as a critical unit for interpreting somatic variation.

genetics↗

Genetic and Epigenetic Landscape of Self-Identified Hispanics/Latino in All Of Us

Human genetic studies still underrepresent many populations, limiting discovery and interpretation of medically relevant variation. Extensive admixture in self-identified Hispanic/Latino populations increases the need for representative reference data and ancestry-aware interpretation of medically relevant variation. We used long-read sequencing to analyze genetic variation, ancestry, and DNA methylation in 1,490 self-identified Hispanic/Latino participants from the All of Us Research Program. We identified 10 million novel variants and more than 100 candidate phenotype associations, with fine-mapping prioritizing structural variants over nearby single-nucleotide variants in more than half. We linked 3,329 tandem repeats to DNA methylation, resolved widespread allele-specific methylation, and identified ancestry-linked regulation across paralogous genes. These results reveal previously inaccessible genetic and regulatory variation and show the value of long-read sequencing for diverse populations.

genetics↗

The genetic architecture of human DNA methylome variation

Population DNA methylome analyses remain largely confined to reference-defined genomic space despite extensive human genetic diversity. A central challenge is therefore to define comparable methylation phenotypes across diverse genomes and map the genetic architecture of methylome variation. Here, using 460 haplotypes from the Human Pangenome Reference Consortium Release 2, we develop two complementary pangenome-based frameworks: one compares methylation within homologous regions while retaining haplotype-specific structural configuration and CpG content; the other represents CpG island (CGI) variation at homologous loci as sequence-resolved alleles. We identified 47,039 CGI alleles, including 8,040 absent from CHM13; 62% were attributable to structural variants and 31% to small variants. Through local genealogies, we reconstructed CGI gain, loss and turnover, revealing how present-day methylation differences align with CGI evolutionary trajectories. We found that genome-wide, methylation variability was buffered against genetic diversity across more than 90% of the genome, with exceptions at extreme nucleotide diversity and locally around structural variants. Our methylation framework enabled population-scale allele-aware methylation quantitative trait locus (mQTL) mapping into non-reference and structurally complex sequence, where mQTL-associated intervals were enriched. mQTLs linked methylation to transcriptomic phenotypes, population differentiation and complex traits, supporting 8% of population differentially methylated regions and colocalizing with more than half of genome-wide association study loci. Together, our study redefines human methylome analysis and our findings reveal a genome-wide architecture of genetic-epigenetic coupling, reshaping how methylation variation is interpreted across human development and disease.

genetics↗