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Biology subjects

Mary, A.

Publications and source records attributed to Mary, A..

7 recordsLinked to original sources

Extended t-cores for the de novo identification of transposable elements and other inexact repeats from short read RNAseq data

Transcribed repeats represent a major challenge in the de novo assembly of transcriptomes from short RNA-seq reads. Young transposable elements (TEs) and more generally, inexact repeats, create dense and ambiguous regions in the assembly graph, preventing the correct assembly of transcripts. In this paper, we introduce a fully de novo method based on the discovery of dense regions in the compacted De Bruijn graph (DBG) to identify such repeats directly from short read RNA-seq data, without requiring a reference genome or repeat database. Our approach defines the extended t-cores, subgraphs of the DBG that capture the complex topology induced by expressed inexact repeats appearing in RNA-seq reads. Independently of its interest for transcriptome assembly, the proposed method appears to be effective for the de novo identification of repeats in transcriptomes. After classifying cores using sequence-based motifs to distinguish simple repeats from potential TEs, we demonstrate its potential for the de novo discovery of TEs. We validate the approach on a Mus musculus dataset, showing that extended t-cores correspond to known expressed TE families. We also illustrate its de novo discovery potential on a non-model species, Canis lupus familiaris, where the method was also able to recover known TEs.

bioinformatics↗

Hampered AMPK-ULK1 cascade in Alzheimer disease (AD) instigates mitochondria dysfunctions and AD-related alterations that are alleviated by metformin

BackgroundMitochondrial structure and function alterations are key pathological features in Alzheimers disease (AD) brains. The adenosine monophosphate-activated protein kinase (AMPK) and its downstream effector Unc-51 like autophagy activating kinase 1 (ULK1) represent a key node controlling mitochondria health, the alteration of which likely contribute to AD development. MethodsWe designed this study to investigate AMPK-ULK1 activation state in post-mortem human sporadic AD brains, in 3xTgAD mice that recapitulate most of human AD features, and in neuronal cells expressing the amyloid precursor protein with the familial Swedish mutation (APPswe). We examined the impact of the pharmacological and genetic modulation of AMPK-ULK1 cascade on mitochondria structure and functions in APPswe cells. We evaluated the potential beneficial impact of AMPK-ULK1 activation by Metformin (Met) on mitochondria defects, as well as on early- and late-stage AD-related alterations in vivo and ex vivo. ResultsAt first, we show that AMPK-ULK1 cascade is defective in murine and human AD brains as well as in APPswe cells. We then report that Met administration to 3xTgAD mice alleviates the alterations of neuronal mitochondria structure and function and we consolidate these results in cells using both pharmacological and genetic tools to modulate AMPK-ULK1 cascade. In mice brains, Met reduces the early accumulation of APP C-terminal fragments (APP-CTFs) as well as the amyloid beta (A{beta}) burden present in aged mice. Mechanistically, we show that Met increases the localization of APP-CTFs within cathepsin D-positive lysosomal compartments in vivo and enhances cathepsin D activity in vitro. The reduction of A{beta} load by Met occurs through an increased recruitment of Iba1+ cells to A{beta} plaques and an enhancement of the phagocytic activity of microglia. Accordingly, in symptomatic 3xTgAD mice, Met alleviates microgliosis and astrogliosis, modulates microglia morphology, reduces peripheral proinflammatory cytokines levels, and regulates the expression of a set of inflammatory genes. In addition, Met normalizes dendritic spines shape in organotypic hippocampal slice cultures modeling AD and improves learning performance of 3xTgAD mice. ConclusionsOur study demonstrates potential therapeutic benefits of targeting AMPK-ULK1 cascade to reverse both early and late AD-related alterations, deserving further investigation in fundamental research and in human clinical studies.

neuroscience↗

Resting-state functional connectivity and fast spindle temporal organization contribute to episodic memory consolidation in healthy aging

Episodic memory consolidation relies on the functional specialization of brain networks and sleep quality, both of which are affected by aging. Functional connectivity during wakefulness is crucial to support the integration of newly acquired information into memory networks. Additionally, the temporal dynamics of sleep spindles facilitates overnight memory consolidation by promoting hippocampal replay and integration of memories within neocortical structures. This study aimed at exploring how resting-state functional connectivity during wakefulness contributes to sleep-dependent memory consolidation in aging, and whether spindles clustered in trains modulates this relationship. Forty-two healthy older adults (68.82 {+/-} 3.03 years), enrolled in the Age-Well clinical trial, were included. Sleep-dependent memory consolidation was assessed using a visuo-spatial memory task performed before and after a polysomnography night. Resting-state functional connectivity data were analyzed using graph theory applied to the whole brain, specific brain networks and the hippocampus. Lower limbic network integration and higher centrality of the anterior hippocampus were associated with better memory consolidation. Spindle trains modulated these effects, such that older participants with longer spindle trains exhibited a stronger negative association between limbic network integration and memory consolidation. These results indicate that lower functional specialization at rest is associated with weaker memory consolidation during sleep. This aligns with the dedifferentiation hypothesis, which posits that aging is associated with reduced brain specificity, leading to less efficient cognitive functioning. These findings reveal a novel mechanism linking daytime brain network organization and sleep-dependent memory consolidation, and suggest that targeting spindle dynamics could help preserve cognitive functioning in aging.

neuroscience↗

Detection and identification of transposable element transcripts using Long Read RNA-seq in Drosophila germline tissues

Transposable elements (TEs) are repeated DNA sequences potentially able to move throughout the genome. In addition to their inherent mutagenic effects, TEs can disrupt nearby genes by donating their intrinsic regulatory sequences, for instance, promoting the ectopic expression of a cellular gene. TE transcription is therefore not only necessary for TE transposition per se but can also be associated with TE-gene fusion transcripts, and in some cases, be the product of pervasive transcription. Hence, correctly determining the transcription state of a TE copy is essential to apprehend the impact of the TE in the host genome. Methods to identify and quantify TE transcription have mostly relied on short RNA-seq reads to estimate TE expression at the family level while using specific algorithms to discriminate copy-specific transcription. However, assigning short reads to their correct genomic location, and genomic feature is not trivial. Here we retrieved full-length cDNA (TeloPrime, Lexogen) of Drosophila melanogaster gonads and sequenced them using Oxford Nanopore Technologies. We show that long-read RNA-seq can be used to identify and quantify transcribed TEs at the copy level. In particular, TE insertions overlapping annotated genes are better estimated using long reads than short reads. Nevertheless, long TE transcripts (> 4.5 kb) are not well captured. Most expressed TE insertions correspond to copies that have lost their ability to transpose, and within a family, only a few copies are indeed expressed. Long-read sequencing also allowed the identification of spliced transcripts for around 107 TE copies. Overall, this first comparison of TEs between testes and ovaries uncovers differences in their transcriptional landscape, at the subclass and insertion level.

bioinformatics↗

Do intrinsic functional networks reflect interacting brain rhythms? Assessing the power bias in MEG amplitude connectivity at rest

The oscillatory nature of intrinsic brain networks is largely taken for granted in the systems neuroscience community. However, the hypothesis that brain rhythms--and by extension transient bursting oscillations--underlie functional networks has not been demonstrated per se. Electrophysiological measures of functional connectivity are indeed affected by the power bias, which may lead to artefactual observations of spectrally specific network couplings not genuinely driven by neural oscillations, bursting or not. We investigate this crucial question by introducing a unique combination of a rigorous mathematical analysis of the power bias in frequency-dependent amplitude connectivity with a neurobiologically informed model of cerebral background noise based on hidden Markov modeling of resting-state magnetoencephalography (MEG). We demonstrate that the power bias may be corrected by a suitable renormalization depending nonlinearly on the signal-to-noise ratio, with noise identified as non-bursting oscillations. Applying this correction preserves the spectral content of amplitude connectivity, definitely proving the importance of brain rhythms in intrinsic functional networks. Our demonstration highlights a dichotomy between spontaneous oscillatory bursts underlying network couplings and non-bursting oscillations acting as background noise but whose function remains unsettled. Significance statementBrain rhythms are paramount electrophysiological correlates of human cerebral activity as they coordinate neurons across distinct brain areas and establish neural synchronization. Spontaneous cortical oscillations, and particularly transient "bursts" of oscillations, also appear as the main electrophysiological subtrate of intrinsic functional brain networks. However, we argue that this oscillatory theory of brain networks, despite being widely accepted, should be requestioned due to a critical bias in electrophysiological measures of network connectivity. Here, we combined mathematical and neurobiological modeling techniques with magnetoencephalography recordings to set this theory on firm and rigorous grounds. Key to our analysis are scarcely studied non-bursting cortical oscillations. Although their precise function remains elusive, our results reveal that dissociating bursting and non-bursting oscillations is fundamental to the rigorous interpretation of electrophysiological network connectivity.

neuroscience↗

CALDERA: Finding all significant de Bruijn subgraphs for bacterial GWAS

Genome wide association studies (GWAS), aiming to find genetic variants associated with a trait, have widely been used on bacteria to identify genetic determinants of drug resistance or hypervirulence. Recent bacterial GWAS methods usually rely on k-mers, whose presence in a genome can denote variants ranging from single nucleotide polymorphisms to mobile genetic elements. Since many bacterial species include genes that are not shared among all strains, this approach avoids the reliance on a common reference genome. However, the same gene can exist in slightly different versions across different strains, leading to diluted effects when trying to detect its association to a phenotype through k-mer based GWAS. Here we propose to overcome this by testing covariates built from closed connected subgraphs of the De Bruijn graph defined over genomic k-mers. These covariates are able to capture polymorphic genes as a single entity, improving k-mer based GWAS in terms of power and interpretability. As the number of subgraphs is exponential in the number of nodes in the DBG, a method naively testing all possible subgraphs would result in very low statistical power due to multiple testing corrections, and the mere exploration of these subgraphs would quickly become computationally intractable. The concept of testable hypothesis has successfully been used to address both problems in similar contexts. We leverage this concept to test all closed connected subgraphs by proposing a novel enumeration scheme for these objects which fully exploits the pruning opportunity offered by testability, resulting in drastic improvements in computational efficiency. We illustrate this on both real and simulated datasets and also demonstrate how considering subgraphs leads to a more powerful and interpretable method. Our method integrates with existing visual tools to facilitate interpretation. We also provide an implementation of our method, as well as code to reproduce all results at https://github.com/HectorRDB/Caldera_Recomb.

genetics↗

Changes in electrophysiological static and dynamic human brain functional architecture from childhood to late adulthood

This magnetoencephalography study aimed at characterizing age-related changes in resting-state functional brain organization from mid-childhood to late adulthood. We investigated neuromagnetic brain activity at rest in 105 participants divided into three age groups: children (6-9 years), young adults (18-34 years) and healthy elders (53-78 years). The effects of age on static resting-state functional integration were assessed using band-limited power envelope correlation, whereas those on transient functional dynamics were disclosed using hidden Markov modeling of power envelope activity. Brain development from childhood to adulthood came with (i) a strengthening of functional integration within and between resting-state networks and (ii) an increased temporal stability of transient (100-300 ms lifetime) and recurrent states of network activation or deactivation mainly encompassing lateral or medial associative neocortical areas. Healthy aging was characterized by decreased static resting-state functional integration and dynamical stability within the visual network. These results based on electrophysiological measurements free of neurovascular biases suggest that functional brain integration mainly evolves during brain development, with limited changes in healthy aging. These novel electrophysiological insights into human brain functional architecture across the lifespan pave the way for future clinical studies investigating how brain disorders affect brain development or healthy aging.

neuroscience↗