Searching journal content for articles similar to Yoon et al. 21 (11): 1892.

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  1. ...–specific gene GYPB showed a high interaction frequency with GYPE only in cluster 3 (Fig. 4H).DiscussionIn this study, we presented an automated bimodal single-cell technology, ASTAR-seq, which allows for parallel profiling of whole-cell transcriptome and chromatin accessibility within the same single cell...
  2. ...a fundamental gap in the interpretation of their functional evolution. As a result of the whole- duplication, identifying orthologous and paralogous genomic regions across teleosts is challenging, hindering -wide investigations into their polyploid history. Here, we combine tailored gene phylogeny methodology...
  3. ..., which is a hallmark of most bacterial chromosome structure (Le et al. 2013; Marbouty et al. 2017), was barely visible. Therefore, the protocol must first be improved to enrich for contacts in bacterial sequence before parallel analysis of changes in host and pathogen organization can be considered...
  4. ...of evolutionary change accrued during >260 Myr of independent evolution of trionychid softshell turtles and birds, paralleling the relatively lower rates of turtle molecular evolution compared to other sauropsids (Eo and DeWoody 2010; Shaffer et al. 2013; Takezaki 2018).Importantly, our analysis also uncovered...
  5. ....We parallelized this process in a Nextflow (Di Tommaso et al. 2017) workflow available at GitHub (https://github.com/oist/plessy_pairwiseGenomeComparison/tree/v5.1.0). To load the alignment coordinates in the R environment for statistical computing (R Core Team 2023), we wrote a package called Genomic...
  6. ...-altering inversions being subject to negative selection. One such inversion (Chr18_inv4) is depicted in Figure 4, A and B, along with chromatin domains predicted from a parallel analysis of paired human and rhesus Hi-C data generated for this study from LCLs (Methods), as well as previously published data from...
  7. ...understand the functional relevance and the phenotypic implications of the promoter–enhancer interactions predicted with PCHi-C data, we examined their relationship with gene expression evolution. We evaluated gene expression patterns using a comparative transcriptome collection spanning several organs...
  8. ...). Therefore, Hi-C can be used to conduct unbiased -wide chromatin 3D conformation analysis and establish the all-to-all DNA interaction landscape.In this study, Hi-C, epigenetic, and transcriptomic data were combined with biochemical assays to build the global and accurate -wide enhancer map in the silkworm...
  9. ...), and cerebellar gray matter (CB), in three individuals per species (Supplemental Table S1). To reduce experimental variation among species, tissue samples from one individual of each species were pooled and processed in parallel in each brain region (Fig. 3A). The nuclei species’ identity was then recovered...
  10. ...inferred large-scale copy-number alterations for each cell by averaging relative expression levels over large regions. However, the parallel DNA and RNA sequencing also revealed inconsistencies between chromosome-wide genomic and transcriptomic variations. For example, Chromosome 3 displayed a relatively...
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