Biology subjects

Durand, N.

Publications and source records attributed to Durand, N..

5 recordsLinked to original sources

bioRxiv2026

A single-nucleus multi-omic atlas of gene regulation across 21 adult human tissues

Diverse human cell types establish specialized functions through lineage- and context-specific regulatory programs. Interpreting non-coding genetic risk requires integrated multi-omic reference maps that directly connect regulatory DNA to cellular expression across human tissues. Here we present a single-nucleus multi-omic atlas comprising 459,856 transcriptomic and chromatin accessibility profiles from 21 adult human tissues and four donors, including paired measurements from 160,688 nuclei. The atlas resolves nine cell lineages, 61 broad cell types and 313 subclusters, and identifies 1,085,062 candidate cis-regulatory elements (cCREs), including 161,270 novel elements absent from ENCODE. Regulatory activity was dominated by cell identity but refined by tissue context. Joint profiling enabled 871,177 cCRE-gene associations and revealed lineage-specific regulatory architectures. Cross-tissue accessibility further identified lineage-restricted and constitutively inaccessible chromatin domains, the latter showing preferential hypomethylation across human cancers. Furthermore, we leverage this dataset to train sequence-to-function models to predict chromatin-accessibility effects for 548,656 fine-mapped variants, identifying 18,133 high-effect variants, including 1,120 broadly active variants. Models trained for eight endothelial subtypes further resolve predicted variant effects across vascular beds. Together, this atlas provides a comprehensive cellular and computational framework for interpreting regulatory sequence, context-dependent gene control, and complex trait genetics across the human body.

genomics↗

bioRxiv2023

Lsr2, a pleiotropic regulator at the core of the infectious strategy of Mycobacterium abscessus

Mycobacterium abscessus is a non-tuberculous mycobacterium, causing lung infections in cystic fibrosis patients. During pulmonary infection, M. abscessus switches from smooth (Mabs-S) to rough (Mabs-R) morphotypes, the latter being hyper-virulent. Previously, we isolated the lsr2 gene as differentially expressed during S-to-R transition. lsr2 encodes a pleiotropic transcription factor that falls under the superfamily of nucleoid-associated proteins (NAPs). Here, we used two functional genomics methods, RNA-seq and ChIP-seq, to elucidate the molecular role of Lsr2 in the pathobiology of M. abscessus. Transcriptomic analysis shows that Lsr2 differentially regulates gene expression across both morphotypes, most of which are involved in several key cellular processes of M. abscessus, including host adaptation and antibiotic resistance. These results were confirmed through RT-qPCR, as well as by minimum inhibitory concentration (MIC) tests and infection tests on macrophages in the presence of antibiotics. ChIP-seq analysis revealed that Lsr2 extensively binds the M. abscessus genome at AT-rich sequences and appears to form long domains that participate in the repression of its target genes. Unexpectedly, the genomic distribution of Lsr2 revealed no distinctions between Mabs-S and Mabs-R, implying more intricate mechanisms at play for achieving target selectivity. IMPORTANCELsr2 is a crucial transcription factor and chromosome organizer involved in intracellular growth and virulence in the smooth and rough morphotypes of Mycobacterium abscessus (Mabs). Using RNA-seq and ChIP-seq, we investigated the molecular role of Lsr2 in gene expression regulation along with its distribution on Mabs genome. Our study demonstrates the pleiotropic regulatory role of Lsr2, regulating the expression of many genes coordinating essential cellular and molecular processes in both morphotypes. In addition, we have elucidated the role of Lsr2 in antibiotic resistance both in vitro and in vivo, where lsr2 mutant strains display heightened sensitivity to antibiotics. Through ChIP-seq, we reported the widespread distribution of Lsr2 on Mabs genome, revealing a direct repressive effect due to its extensive binding on promoters or coding sequences of its targets. This study unveils the significant regulatory role of Lsr2, intricately intertwined with its function in shaping the organization of the Mabs genome.

genomics↗

bioRxiv2023

Single-cell multi-scale footprinting reveals the modular organization of DNA regulatory elements

Cis-regulatory elements control gene expression and are dynamic in their structure, reflecting changes to the composition of diverse effector proteins over time1-3. Here we sought to connect the structural changes at cis-regulatory elements to alterations in cellular fate and function. To do this we developed PRINT, a computational method that uses deep learning to correct sequence bias in chromatin accessibility data and identifies multi-scale footprints of DNA-protein interactions. We find that multi-scale footprints enable more accurate inference of TF and nucleosome binding. Using PRINT with single-cell multi-omics, we discover wide-spread changes to the structure and function of candidate cis-regulatory elements (cCREs) across hematopoiesis, wherein nucleosomes slide, expose DNA for TF binding, and promote gene expression. Activity segmentation using the co-variance across cell states identifies "sub-cCREs" as modular cCRE subunits of regulatory DNA. We apply this single-cell and PRINT approach to characterize the age-associated alterations to cCREs within hematopoietic stem cells (HSCs). Remarkably, we find a spectrum of aging alterations among HSCs corresponding to a global gain of sub-cCRE activity while preserving cCRE accessibility. Collectively, we reveal the functional importance of cCRE structure across cell states, highlighting changes to gene regulation at single-cell and single-base-pair resolution.

genomics↗

bioRxiv2023

Comparison of genomic-enabled cross selection criteria for the improvement of inbred line breeding populations

A crucial step in inbred plant breeding is the choice of mating design to derive high-performing inbred varieties while also maintaining a competitive breeding population to secure sufficient genetic gain in future generations. In practice, the mating design usually relies on crosses involving the best parental inbred lines to ensure high mean progeny performance. This excludes crosses involving lower performing but more complementary parents in terms of favorable alleles. We predicted crosses with putative outstanding progenies (high mean and high variance progeny distribution) using genomic prediction models to assess the value of top progeny. This study compared the benefits and drawbacks of seven genomic cross selection criteria (CSC) in terms of genetic gain for one trait and genetic diversity in the next generation. Six CSC were already published and we have proposed an improved CSC that can estimate the proportion of progeny above a threshold defined for the whole mating plan. We simulated mating designs optimized using different CSC and 835 elite parents from a real breeding program that were evaluated between 2000 and 2016. We applied constraints on parental contributions and genetic similarities between parents according to usual breeder practices. Our results showed that CSC based on progeny variance estimation increased the genetic value of superior progenies by up to 5% in the next generation compared to CSC based on the progeny mean estimation (i.e. parental genetic values) alone. It also increased the genetic gain (up to 4%) and/or maintained more genetic diversity at QTLs (up to 4% more genic variance when the marker effects were perfectly estimated).

genetics↗

bioRxiv2018

The Hi-Culfite assay reveals relationships between chromatin contacts and DNA methylation state

Hi-Culfite, a protocol combining Hi-C and whole-genome bisulfite sequencing (WGBS), determines chromatin contacts and DNA methylation simultaneously. Hi-Culfite also reveals relationships that cannot be seen when the two assays are performed separately. For instance, we show that loci associated with open chromatin exhibit context-sensitive methylation: when their spatial neighbors lie in closed chromatin, they are much more likely to be methylated.

genomics↗