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1. The evolution of the human DNA replication timing program

   https://doi.org/10.1073/pnas.2213896120  

   Bracci, Alexa N.; Dallmann, Anissa; Ding, Qiliang; Hubisz, Melissa J.; Caballero, Madison; Koren, Amnon (March 2023, Proceedings of the National Academy of Sciences)

   DNA is replicated according to a defined spatiotemporal program that is linked to both gene regulation and genome stability. The evolutionary forces that have shaped replication timing programs in eukaryotic species are largely unknown. Here, we studied the molecular causes and consequences of replication timing evolution across 94 humans, 95 chimpanzees, and 23 rhesus macaques. Replication timing differences recapitulated the species’ phylogenetic tree, suggesting continuous evolution of the DNA replication timing program in primates. Hundreds of genomic regions had significant replication timing variation between humans and chimpanzees, of which 66 showed advances in replication origin firing in humans, while 57 were delayed. Genes overlapping these regions displayed correlated changes in expression levels and chromatin structure. Many human–chimpanzee variants also exhibited interindividual replication timing variation, pointing to ongoing evolution of replication timing at these loci. Association of replication timing variation with genetic variation revealed that DNA sequence evolution can explain replication timing variation between species. Taken together, DNA replication timing shows substantial and ongoing evolution in the human lineage that is driven by sequence alterations and could impact regulatory evolution at specific genomic sites. 

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2. Telomere-to-telomere human DNA replication timing profiles

   https://doi.org/10.1038/s41598-022-13638-8  

   Massey, Dashiell J.; Koren, Amnon (June 2022, Scientific Reports)

   Abstract The spatiotemporal organization of DNA replication produces a highly robust and reproducible replication timing profile. Sequencing-based methods for assaying replication timing genome-wide have become commonplace, but regions of high repeat content in the human genome have remained refractory to analysis. Here, we report the first nearly-gapless telomere-to-telomere replication timing profiles in human, using the T2T-CHM13 genome assembly and sequencing data for five cell lines. We find that replication timing can be successfully assayed in centromeres and large blocks of heterochromatin. Centromeric regions replicate in mid-to-late S-phase and contain replication-timing peaks at a similar density to other genomic regions, while distinct families of heterochromatic satellite DNA differ in their bias for replicating in late S-phase. The high degree of consistency in centromeric replication timing across chromosomes within each cell line prompts further investigation into the mechanisms dictating that some cell lines replicate their centromeres earlier than others, and what the consequences of this variation are. 

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3. Integrating regulatory DNA sequence and gene expression to predict genome-wide chromatin accessibility across cellular contexts

   https://doi.org/10.1093/bioinformatics/btz352  

   Nair, Surag; Kim, Daniel S; Perricone, Jacob; Kundaje, Anshul (July 2019, Bioinformatics)

   Abstract Motivation Genome-wide profiles of chromatin accessibility and gene expression in diverse cellular contexts are critical to decipher the dynamics of transcriptional regulation. Recently, convolutional neural networks have been used to learn predictive cis-regulatory DNA sequence models of context-specific chromatin accessibility landscapes. However, these context-specific regulatory sequence models cannot generalize predictions across cell types. Results We introduce multi-modal, residual neural network architectures that integrate cis-regulatory sequence and context-specific expression of trans-regulators to predict genome-wide chromatin accessibility profiles across cellular contexts. We show that the average accessibility of a genomic region across training contexts can be a surprisingly powerful predictor. We leverage this feature and employ novel strategies for training models to enhance genome-wide prediction of shared and context-specific chromatin accessible sites across cell types. We interpret the models to reveal insights into cis- and trans-regulation of chromatin dynamics across 123 diverse cellular contexts. Availability and implementation The code is available at https://github.com/kundajelab/ChromDragoNN. Supplementary information Supplementary data are available at Bioinformatics online. 

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4. ODGI: understanding pangenome graphs

   https://doi.org/10.1093/bioinformatics/btac308  

   Guarracino, Andrea; Heumos, Simon; Nahnsen, Sven; Prins, Pjotr; Garrison, Erik (May 2022, Bioinformatics)

   Robinson, Peter (Ed.)

   Abstract Motivation Pangenome graphs provide a complete representation of the mutual alignment of collections of genomes. These models offer the opportunity to study the entire genomic diversity of a population, including structurally complex regions. Nevertheless, analyzing hundreds of gigabase-scale genomes using pangenome graphs is difficult as it is not well-supported by existing tools. Hence, fast and versatile software is required to ask advanced questions to such data in an efficient way. Results We wrote Optimized Dynamic Genome/Graph Implementation (ODGI), a novel suite of tools that implements scalable algorithms and has an efficient in-memory representation of DNA pangenome graphs in the form of variation graphs. ODGI supports pre-built graphs in the Graphical Fragment Assembly format. ODGI includes tools for detecting complex regions, extracting pangenomic loci, removing artifacts, exploratory analysis, manipulation, validation and visualization. Its fast parallel execution facilitates routine pangenomic tasks, as well as pipelines that can quickly answer complex biological questions of gigabase-scale pangenome graphs. Availability and implementation ODGI is published as free software under the MIT open source license. Source code can be downloaded from https://github.com/pangenome/odgi and documentation is available at https://odgi.readthedocs.io. ODGI can be installed via Bioconda https://bioconda.github.io/recipes/odgi/README.html or GNU Guix https://github.com/pangenome/odgi/blob/master/guix.scm. Supplementary information Supplementary data are available at Bioinformatics online. 

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5. Chemically Induced Chromosomal Interaction (CICI) method to study chromosome dynamics and its biological roles

   https://doi.org/10.1038/s41467-022-28416-3  

   Du, Manyu; Zou, Fan; Li, Yi; Yan, Yujie; Bai, Lu (February 2022, Nature Communications)

   Abstract Numerous intra- and inter-chromosomal contacts have been mapped in eukaryotic genomes, but it remains challenging to link these 3D structures to their regulatory functions. To establish the causal relationships between chromosome conformation and genome functions, we  develop a method, Chemically Induced Chromosomal Interaction (CICI), to selectively perturb the chromosome conformation at targeted loci. Using this method, long-distance chromosomal interactions can be induced dynamically between intra- or inter-chromosomal loci pairs, including the ones with very low Hi-C contact frequencies. Measurement of CICI formation time allows us to probe chromosome encounter dynamics between different loci pairs across the cell cycle. We also conduct two functional tests of CICI. We perturb the chromosome conformation near a DNA double-strand break and observe altered donor preference in homologous recombination; we force interactions between early and late-firing DNA replication origins and find no significant changes in replication timing. These results suggest that chromosome conformation plays a deterministic role in homology-directed DNA repair, but not in the establishment of replication timing. Overall, our study demonstrates that CICI is a powerful tool to study chromosome dynamics and 3D genome function. 

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