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Whole Genome Sequence Data From Captive Baboons Implicate RBFOX1 in Epileptic Seizure Risk.

ABSTRACT: In this study, we investigate the genetic determinants that underlie epilepsy in a captive baboon pedigree and evaluate the potential suitability of this non-human primate model for understanding the genetic etiology of human epilepsy. Archived whole-genome sequence data were analyzed using both a candidate gene approach that targeted variants in baboon homologs of 19 genes (n = 20,881 SNPs) previously implicated in genetic generalized epilepsy (GGE) and a more agnostic approach that examined protein-altering mutations genome-wide as assessed by snpEff (n = 36,169). Measured genotype association tests for baboon cases of epileptic seizure were performed using SOLAR, as well as gene set enrichment analyses (GSEA) and protein-protein interaction (PPI) network construction of top association hits genome-wide (p < 0.01; n = 441 genes). The maximum likelihood estimate of heritability for epileptic seizure in the pedigreed baboon sample is 0.76 (SE = 0.77; p = 0.07). Among candidate genes for GGE, a significant association was detected for an intronic SNP in RBFOX1 (p = 5.92 × 10^-6; adjusted p = 0.016). For protein-altering variants, no genome-wide significant results were observed for epilepsy status. However, GSEA revealed significant positive enrichment for genes involved in the extracellular matrix structure (ECM; FDR = 0.0072) and collagen formation (FDR = 0.017), which was reflected in a major PPI network cluster. This preliminary study highlights the potential role of RBFOX1 in the epileptic baboon, a protein involved in transcriptomic regulation of multiple epilepsy candidate genes in humans and itself previously implicated in human epilepsy, both focal and generalized. Moreover, protein-damaging variants from across the genome exhibit a pattern of association that links collagen-containing ECM to epilepsy risk. These findings suggest a shared genetic etiology between baboon and human forms of GGE and lay the foundation for follow-up research.

SUBMITTER: Kos MZ

PROVIDER: S-EPMC8417722 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe hamadryas baboon (Papio hamadryas) is a highly social primate that lives in complex multilevel societies exhibiting a wide range of group behaviors akin to humans. In contrast to the widely studied human microbiome, there is a paucity of information on the host-associated microbiomes of nonhuman primates (NHPs). Here, our goal was to understand the microbial composition throughout different body sites of cohabiting baboons.ResultsWe analyzed 170 oral, oropharyngeal, cervical, uterine, vaginal, nasal and rectal samples from 16 hamadryas baboons via 16S rRNA gene sequencing. Additionally, raw Miseq sequencing data from 1041 comparable publicly available samples from the human oral cavity, gut and vagina were reanalyzed using the same pipeline. We compared the baboon and human microbiome of the oral cavity, gut and vagina, showing that the baboon microbiome is distinct from the human. Baboon cohabitants share similar microbial profiles in their cervix, uterus, vagina, and gut. The oral cavity, gut and vagina shared more bacterial amplicon sequence variants (ASVs) in group living baboons than in humans. The shared ASVs had significantly positive correlations between most body sites, suggesting a potential bacterial exchange throughout the body. No significant differences in gut microbiome composition were detected within the maternity line and between maternity lines, suggesting that the offspring gut microbiota is shaped primarily through bacterial exchange among cohabitants. Finally, Lactobacillus was not so predominant in baboon vagina as in the human vagina but was the most abundant genus in the baboon gut.ConclusionsThis study is the first to provide comprehensive analyses of the baboon microbiota across different body sites. We contrast this to human body sites and find substantially different microbiomes. This group of cohabitating baboons generally showed higher microbial diversity and remarkable similarities between body sites than were observed in humans. These data and findings from one group of baboons can form the basis of future microbiome studies in baboons and be used as a reference in research where the microbiome is expected to impact human modeling with baboons.

Project description:The determination of the relationship between a pair of individuals is a fundamental application of genetics. Previously, we and others have demonstrated that identity-by-descent (IBD) information generated from high-density single-nucleotide polymorphism (SNP) data can greatly improve the power and accuracy of genetic relationship detection. Whole-genome sequencing (WGS) marks the final step in increasing genetic marker density by assaying all single-nucleotide variants (SNVs), and thus has the potential to further improve relationship detection by enabling more accurate detection of IBD segments and more precise resolution of IBD segment boundaries. However, WGS introduces new complexities that must be addressed in order to achieve these improvements in relationship detection. To evaluate these complexities, we estimated genetic relationships from WGS data for 1490 known pairwise relationships among 258 individuals in 30 families along with 46 population samples as controls. We identified several genomic regions with excess pairwise IBD in both the pedigree and control datasets using three established IBD methods: GERMLINE, fastIBD, and ISCA. These spurious IBD segments produced a 10-fold increase in the rate of detected false-positive relationships among controls compared to high-density microarray datasets. To address this issue, we developed a new method to identify and mask genomic regions with excess IBD. This method, implemented in ERSA 2.0, fully resolved the inflated cryptic relationship detection rates while improving relationship estimation accuracy. ERSA 2.0 detected all 1(st) through 6(th) degree relationships, and 55% of 9(th) through 11(th) degree relationships in the 30 families. We estimate that WGS data provides a 5% to 15% increase in relationship detection power relative to high-density microarray data for distant relationships. Our results identify regions of the genome that are highly problematic for IBD mapping and introduce new software to accurately detect 1(st) through 9(th) degree relationships from whole-genome sequence data.

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Whole Genome Sequence Data From Captive Baboons Implicate RBFOX1 in Epileptic Seizure Risk.

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