Searching journal content for articles similar to Ovchinnikov et al. 11 (12): 2050.

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  1. ...(Fig. 4B). Again, processed and unprocessed pseudogenes show different patterns, reporting the highest overlap with LINEs and SINEs, respectively. Because pseudogenes originate from a non-random subset of protein-coding genes, we next asked whether enrichment of TEs in pseudogene promoters could...
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  2. ...lost by random mutations (McLaughlin et al. 2014). This hypothetical model was also proposed in the viral restriction factors derived from ERVs (Johnson 2019). Nonetheless, a recent reporter-based assay showed that the human L1TD1 protein is not capable of suppressing human L1 activity (Jin et al. 2024...
  3. ...genes (seven and eight regions, respectively; P < 0.01 when compared with 500 randomly generated genomic regions by binomial test). High LINE repeat content has previously been shown to be associated with random monoallelic genes such as the olfactory and vomeronasal receptors (Allen et al. 2003...
  4. ...shown as a number on the right of the bar. The black transparent bars represent the expected number of peaks following a random distribution. The FDR of the enrichment is shown with stars (FDR > 0.0001 = ****, >0.001 = ***, >0.01 = **, >0.05 = *, ≥0.05 = n.s.). Rows are ordered by FDR. The number next...
  5. ...observed fractions (left bars) and fractions based on random shuffling of TE insertion identities across the , keeping locations fixed (right bars, color desaturated). P-values calculated using binomial tests. (E) Median, per family, distance of insertions from nearest genes. Top halves indicate distance...
  6. ...Fig. S3). Based on this random distribution, we might expect to see atmost two insertions specific to any possible grouping of three populations from this data set. Taken together, these results suggest a significant level of retrotransposition-induced interpopulation variation, although the majority...
  7. ...and then configured in a random order (Stephens et al. 2011; Ly et al. 2017), matching the molecular signatures of clustered interchromosomal rearrangements found in the HepG2 Δt8 deletion clone.In the deletion clone HepG2 Δi50, we postulate that the detected large genomic deletion resided on one allele whereas...
  8. ...of the nascent transcriptome using allele-specific Precision nuclear Run-On sequencing (PRO-seq). We have developed a Random Forest machine-learning model that can predict the measured silencing dynamics based on a large set of epigenetic and genomic features and tested its predictive power experimentally...
  9. ...trios) (Table S2 of Stewart et al. 2011). The long sequencing reads were particularly useful due to the difficulty of identifying repetitive insertions using random short reads. Naturally, high-coverage whole- sequencing yields more total information than a targeted approach. The two main limitations...
  10. ...the publishedmethods to the identification of insertions polymorphic among taxa could be both more and less difficult. Obviously, there are likely to be multiple polymorphisms when comparing two species that diverged multiple millions of years ago. Thus, finding random differential insertions could be a trivial task...
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