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Fischl, M.

Publications and source records attributed to Fischl, M..

2 recordsLinked to original sources

A hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data

BackgroundMethylation Quantitative Trait Loci (meQTLs) are chromosomal regions that harbor genetic variants affecting DNA methylation levels. The identification of meQTLs can be accomplished through quantifying the effects of single nucleotide polymorphisms (SNPs) on DNA methylation levels, and these inferred meQTLs can shed light on the complex interplay between the genome and methylome. However, most meQTL studies to date utilize bulk methylation datasets composed of different cell types that may have distinct methylation patterns in each cell type. Current technological challenges hinder the comprehensive collection of large-scale, cell-type-specific (CTS) methylation data, which limits our understanding of CTS methylation regulation. To address this challenge, we propose a hierarchical Bayesian interaction model (HBI) to infer CTS meQTLs from bulk methylation data. ResultsOur HBI method integrates bulk methylations data from a large number of samples and CTS methylation data from a small number of samples to estimate CTS meQTLs. Through simulations, we show that HBI improves the estimation (accuracy and power) of CTS genetic effects on DNA methylation. To systematically characterize genome-wide SNP-methylation level associations in multiple cell types, we apply HBI to bulk methylation data measured in peripheral blood mononuclear cells (PBMC) from a cohort of 431 individuals together with flow-sorted cell-derived methylation sequencing (MC-seq) data measured in isolated white blood cells (CD4+ T-cells, CD8+ T-cells, CD16+ monocytes) for 47 individuals. We demonstrate that HBI can identify CTS meQTLs and improve the functional annotation of SNPs. ConclusionsHBI can incorporate strong and robust signals from MC-seq data to improve the estimation of CTS meQTLs. Applying HBI to link the methylome and genome data helps to identify biologically relevant cell types for complex traits.

genetics↗

Fast inhibition slows and desynchronizes auditory efferent neuron activity

The encoding of acoustic stimuli requires precise neuron timing. Auditory neurons in the cochlear nucleus (CN) and brainstem are well-suited for accurate analysis of fast acoustic signals, given their physiological specializations of fast membrane time constants, fast axonal conduction, and reliable synaptic transmission. The medial olivocochlear (MOC) neurons that provide efferent inhibition of the cochlea reside in the ventral brainstem and participate in these fast neural circuits. However, their modulation of cochlear function occurs over time scales of a slower nature. This suggests the presence of mechanisms that restrict MOC inhibition of cochlear function. To determine how monaural excitatory and inhibitory synaptic inputs integrate to affect the timing of MOC neuron activity, we developed a novel in vitro slice preparation ( wedge-slice). The wedge-slice maintains the ascending auditory nerve root, the entire CN and projecting axons, while preserving the ability to perform visually guided patch-clamp electrophysiology recordings from genetically identified MOC neurons. The in vivo-like timing of the wedge-slice demonstrates that the inhibitory pathway accelerates relative to the excitatory pathway when the ascending circuit is intact, and the CN portion of the inhibitory circuit is precise enough to compensate for reduced precision in later synapses. When combined with machine learning PSC analysis and computational modeling, we demonstrate a larger suppression of MOC neuron activity when the inhibition occurs with in vivo-like timing. This delay of MOC activity may ensure that the MOC system is only engaged by sustained background sounds, preventing a maladaptive hyper-suppression of cochlear activity. Significance StatementAuditory brainstem neurons are specialized for speed and fidelity to encode rapid features of sound. Extremely fast inhibition contributes to precise brainstem sound encoding. This circuit also projects to medial olivocochlear (MOC) efferent neurons that suppress cochlear function to enhance detection of signals in background sound. Using a novel brain slice preparation with intact ascending circuitry, we show that inhibition of MOC neurons can also be extremely fast, with the speed of the circuit localized to the cochlear nucleus. In contrast with the enhancement of precision afforded by fast inhibition in other brainstem auditory circuits, inhibition to MOC neurons instead has a variable onset that delays and desynchronizes activity, thus reducing precision for a slow, sustained response to background sounds.

neuroscience↗