sequencing data analysis  (Parse Biosciences)

Journal: Nucleic Acids Research

Article Title: High-throughput methods enabling random duplications, deletions, or nucleotide-constrained mutagenesis of entire DNA motifs

doi: 10.1093/nar/gkag236

Figure Lengend Snippet: RADDIM creates random duplications or deletions at one random position within a circular DNA molecule. ( A ) Illustration of the RADDIM workflow when starting from a plasmid template. Illustration created with BioRender.com . ( B ) An ExoChase-treated pUC19 plasmid (Fig. ) containing a CcdB toxin gene was nicked on the forward DNA-strand by the site-specific nickase Nt.BbvCI. The resulting double-nicked plasmids were incubated with Bst DNAP, with or without either the 5′–3′ single-strand-specific RecJ exonuclease, or the 3′–5′ single-strand-specific Thermolabile Exonuclease I, to determine if single-strand exonucleases could remove unwanted DNA-amplifications during a convergent nick-translation reaction. ( C ) Characterization of the DNA-ends that were created by a convergent nick-translation reaction using Bst DNAP and either RecJ or Thermolabile Exo I (Fig. ). ConNickTra linearized plasmids were purified and T7 DNAP was used to repair all DNA-ends. Next, T4 DNA ligase was used to re-circularize the linear plasmids, which were transformed into CcdB-sensitive E. coli cells. This selected for plasmids with a mutation in the ccdB toxin gene. The ccdB gene of 40 successfully sequenced plasmids from the RecJ library ( n = 40), and 39 successfully sequenced plasmids from the Thermolabile Exo I library ( n = 39) were sequenced by single-colony Sanger sequencing. ( D ) A synthetic 196 bp dsDNA fragment was incubated together with Bst DNAP alone, and/or Thermolabile Exo I, for 3 h with or without 1 mM MnCl 2 , to evaluate if manganese could reprogram the Bst DNAP and/or ExoI to degrade the ends of linear DNA molecules. ( E ) A pUC19 plasmid containing a CcdB toxin gene was randomly linearized by a ConNickTra reaction using Bst DNAP and ExoI, followed by an addition of 1 mM MnCl 2 for 10–30 min. After a T7 DNAP-mediated DNA end-repair, and a T4 DNA ligase-mediated re-circularization, plasmids were transformed into CcdB-sensitive E. coli cells. ( F ) The ccdB gene of 25 successfully sequenced plasmids from the 10 min library ( n = 25), 21 plasmids from the 20 min library ( n = 21), and 22 successfully sequenced plasmids from the 30 min library ( n = 22) were analyzed by single-colony Sanger sequencing.

Article Snippet: The RADDIM PacBio Revio deep sequencing data analysis and the Python scripts used to calculate the theoretical mutational landscapes possible with NSM are available from the Novo Nordisk Foundation Center for Biosustainability (DTU Biosustain) GitHub for this project ( https://github.com/biosustain/raddim ) and on Zenodo ( https://doi.org/10.5281/zenodo.18863538 ).

Techniques: Plasmid Preparation, Incubation, Nick Translation, Purification, Transformation Assay, Mutagenesis, Sequencing

Journal: Nucleic Acids Research

Article Title: High-throughput methods enabling random duplications, deletions, or nucleotide-constrained mutagenesis of entire DNA motifs

doi: 10.1093/nar/gkag236

Figure Lengend Snippet: RADDIM allows for in-frame and multi-residue InDels enabling functional protein structure modifications. ( A ) Illustration of an alternative RADDIM workflow to insert random DNA sequences into a RADDIM library by ligating a random DNA sequence oligo library to ConNickTra linearized plasmids, followed by a T7 DNAP-mediated DNA-end-repair/fill-in. Illustration created with BioRender.com . ( B ) Representative β-lactamase compensatory mutations able to restore phenotypic ampicillin resistance of the enzymatically inactivated (A40P and R41W) TEM-1 protein, superimposed onto the wild-type TEM-1 protein structure (PDB: 1ZG4). Red spheres = original inactivating mutations (A40P and R41W), Green spheres = compensatory AA substitutions. Purple marking = site of multi-residue compensatory deletion. Brown marking = site of multi-residue compensatory insertions.

Article Snippet: The RADDIM PacBio Revio deep sequencing data analysis and the Python scripts used to calculate the theoretical mutational landscapes possible with NSM are available from the Novo Nordisk Foundation Center for Biosustainability (DTU Biosustain) GitHub for this project ( https://github.com/biosustain/raddim ) and on Zenodo ( https://doi.org/10.5281/zenodo.18863538 ).

Techniques: Residue, Functional Assay, Sequencing

Journal: Nucleic Acids Research

Article Title: High-throughput methods enabling random duplications, deletions, or nucleotide-constrained mutagenesis of entire DNA motifs

doi: 10.1093/nar/gkag236

Figure Lengend Snippet: Deep sequencing confirms the diversity of RADDIM-generated InDel libraries. ( A ) Size distribution of insertions and deletions across a RADDIM plasmid library and the location of all variants (insertions and deletions) that are 1 nt and >1 nt in length. InDels are shown by their start position in the 5′–3′ direction in the plasmid sequence. Positive values represent insertions and negative values represent deletions. CAT = chloramphenicol acetyltransferase, tCYC1 = transcriptional terminator of iso-1-cytochrome c from S. cerevisiae , ori = pUC19 origin-of-replication, BLA* = inactivated (A40P and R41W) β-lactamase (TEM-1), CcdB = bacterial DNA gyrase toxin, CcdA* = inactivated cognate immunity protein of CcdB. ( B ) Illustration of the plasmid linearization mechanisms attained by combining the ExoChase and ConNickTra methods, enabling random and singular double-stranded DNA-breaks to be enriched within only one half of a plasmid molecule, down-stream of the site-specific DNA-nick. Illustration created with BioRender.com . ( C ) Quantification of all identified deletions ranging from 1 to 30 nt in length. ( D ) Quantification of all identified insertions ranging from 1 to 30 nt in length. ( E ) The number of identified mismatches for all insertions ranging from 2 to 30 nt in length.

Article Snippet: The RADDIM PacBio Revio deep sequencing data analysis and the Python scripts used to calculate the theoretical mutational landscapes possible with NSM are available from the Novo Nordisk Foundation Center for Biosustainability (DTU Biosustain) GitHub for this project ( https://github.com/biosustain/raddim ) and on Zenodo ( https://doi.org/10.5281/zenodo.18863538 ).

Techniques: Sequencing, Generated, Plasmid Preparation

Journal: Nucleic Acids Research

Article Title: High-throughput methods enabling random duplications, deletions, or nucleotide-constrained mutagenesis of entire DNA motifs

doi: 10.1093/nar/gkag236

Figure Lengend Snippet: RADDIM enables a random duplication or deletion of entire regulatory DNA motifs. ( A ) Illustration of the last steps in the RADDIM workflow when starting from a linear PCR-product (Fig. ). Illustration created with BioRender.com . Relative mNeonGreen fluorescent protein expression by S. cerevisiae cells transformed with RADDIM-mutated ( B ) pACT1 ( n = 90) or ( C ) pTEF1 promoter variants ( n = 86) following a FACS of top 1% of fluorescent cells. ( D ) Relative mNeonGreen fluorescent protein expression by reconstituted pACT1 and pTEF1 promoter variants ( n = 3). Statistical significance was calculated by two-way ANOVA with ns: P > 0.05, *: P ≤ 0.05, **: P ≤ 0.005, ***: P ≤ 0.0005, and ****: P ≤ 0.0001. ( E) Relative mNeonGreen fluorescent protein expression by wild-type pACT1 and pTEF1 promoters ( n = 3). Statistical significance was calculated by unpaired t -test with ns: P > 0.05 and *: P ≤ 0.0001.

Article Snippet: The RADDIM PacBio Revio deep sequencing data analysis and the Python scripts used to calculate the theoretical mutational landscapes possible with NSM are available from the Novo Nordisk Foundation Center for Biosustainability (DTU Biosustain) GitHub for this project ( https://github.com/biosustain/raddim ) and on Zenodo ( https://doi.org/10.5281/zenodo.18863538 ).

Techniques: Expressing, Transformation Assay

Journal: Microbiology Spectrum

Article Title: Exacerbated salmonellosis in poly(ADP-ribose) polymerase 14-deficient mice

doi: 10.1128/spectrum.02971-25

Figure Lengend Snippet: Minor macroscopic effects of Parp14 deficiency on the severity of salmonellosis. ( A, B ) Schematic representation of the single-animal experiment executed in this study. The blue box refers to mice, which were subjected to statistical comparisons throughout the study. The tissues marked with an asterisk were longitudinally cut into two pieces, one for histology and one for qPCR/RNA-Seq. Images were partially created with BioRender.com. ( C ) Weight change of the mice during the course of the experiment relative to day −1 (medians with interquartile range). No statistically significant differences between the infected wt and Parp14-deficient mice were detected. Statistical significance values are shown in the figure. Weights of the PBS mice were not statistically compared (NA, not applicable; fewer than three animals to compare, see ). ( D ) Colon lengths at day 1 and day 5. ( E ) Spleen weights at day 1 and day 5. ( F ) Liver weights at day 1 and day 5. ( G–L ) Determination of viable bacteria in different tissues at day 1 and day 5. Bars in sub-panels D–L represent medians with interquartile range. All individual data points are shown. Statistical significance values for the differences between the infected wt and Parp14-deficient mice are shown in each D–L sub-panel. Fecal pellets were not obtained from all mice. Parameters of the PBS mice were not statistically compared (NA, not applicable; fewer than three animals to compare, see ).

Article Snippet: We used the single-cell RNA-Seq data analysis and visualization interface at the Broad Institute Single Cell Portal ( https://singlecell.broadinstitute.org/single_cell ) in order to analyze Parp1 and Parp14 expression.

Techniques: RNA Sequencing, Infection, Bacteria

Journal: Microbiology Spectrum

Article Title: Exacerbated salmonellosis in poly(ADP-ribose) polymerase 14-deficient mice

doi: 10.1128/spectrum.02971-25

Figure Lengend Snippet: Quantitation of Parp14 expression in the mouse gastrointestinal tract. ( A ) The QuPath-based quantitation of Parp14 expression. Representative examples of the Parp14 stainings are shown in . The values on the y -axis refer to the means of DAB staining intensity, that is, the mean OD in the QuPath data output. Each dot refers to a single cell. The numbers of analyzed cells (mostly epithelial cells) are indicated on the x -axis (see ). The red lines above the data points refer to the mean values. Statistical analyses were conducted using the two-tailed unpaired t -test (NA, not applicable; fewer than three animals to compare, see ). One Salmonella -infected day 5 mouse was left out from the quantitation due to poor quality of the FFPE tissue block. ( B ) The qPCR data on relative Parp14 expression (means with standard deviation, statistics performed using two-tailed unpaired t -test). Samples were included in the data analysis if they passed the 0.5 standard deviation Ct filter for replicate runs. No statistical analyses were executed against the PBS groups because there were less than three data points/animal to compare (see ). The calibrators in each sub-panel are the mean dCq values of the day 1 Salmonella -infected mice.

Article Snippet: We used the single-cell RNA-Seq data analysis and visualization interface at the Broad Institute Single Cell Portal ( https://singlecell.broadinstitute.org/single_cell ) in order to analyze Parp1 and Parp14 expression.

Techniques: Quantitation Assay, Expressing, Staining, Single Cell, Two Tailed Test, Infection, Blocking Assay, Standard Deviation

Journal: Microbiology Spectrum

Article Title: Exacerbated salmonellosis in poly(ADP-ribose) polymerase 14-deficient mice

doi: 10.1128/spectrum.02971-25

Figure Lengend Snippet: Transcriptional signatures uniquely detected in S . Typhimurium-infected wt and Parp14-deficient mice. Data from a triplicate RNA-Seq analysis of mouse large intestine sections 1 day post-infection are shown. ( A ) The Venn diagrams of shared and unique genes that were detected to be expressed in the infected wt and Parp14-deficient mice (FPKM value >1). The integer is the number of genes detected to be expressed in both of the genotypes. ( B ) The pie charts of the numbers of identified GO terms based on the genotype-specific lists of expressed genes (BP, biological process; CC, cellular component; MF, molecular function; ). ( C–E ) Bar graph representation of all the identified GO BP terms with the genotype-specific lists of expressed genes. The BP terms are sorted based on the percentage of GO term gene values (number of detected genes in a particular BP term / number of all genes in particular BP term × 100). FDR refers to the false discovery rate value. An FDR value cut-off of <0.05 was used in the searches. The asterisks in the wt sub-panel ( D ) refer to the seven infection- and inflammation response-related BP terms. The sub-panel E displays the genes of these seven infection- and inflammation response-related BP terms. ( F–H ) Pathway-enrichment dot plot representations of all (KO sub-panel) and the top 10 (wt sub-panel) KEGG pathways identified with the genotype-specific lists of expressed genes. All the identified KEGG pathways with the corresponding gene lists are described in . The KEGG pathways are sorted based on the P -value. The count values refer to the number of genes that were detected in a particular KEGG pathway. The asterisk in the wt sub-panel ( G ) refers to the only KEGG pathway with a <0.05 P adj -value. The sub-panel H displays the genes of this IL-17 signaling pathway.

Article Snippet: We used the single-cell RNA-Seq data analysis and visualization interface at the Broad Institute Single Cell Portal ( https://singlecell.broadinstitute.org/single_cell ) in order to analyze Parp1 and Parp14 expression.

Techniques: Infection, RNA Sequencing

Journal: Microbiology Spectrum

Article Title: Exacerbated salmonellosis in poly(ADP-ribose) polymerase 14-deficient mice

doi: 10.1128/spectrum.02971-25

Figure Lengend Snippet: Hampered expression of four cytokines in the large intestine of S . Typhimurium-infected Parp14-deficient mice. Four hit genes of the large intestine bulk tissue RNA-Seq analysis ( Ccl2 , Ccl7 , Cxcl10 , Il1b ) were analyzed. Five other TaqMan qPCR assays on inflammation-associated genes were run in parallel. The figure illustrates the TaqMan qPCR data on relative gene expression with means and standard deviations. The calibrators in all sub-panels are the mean dCq values of the day 1 infected wt mice. Statistical analyses were done with a two-tailed unpaired t -test. All the statistical significance values of the comparisons between the wt and Parp14-deficient mice are indicated.

Article Snippet: We used the single-cell RNA-Seq data analysis and visualization interface at the Broad Institute Single Cell Portal ( https://singlecell.broadinstitute.org/single_cell ) in order to analyze Parp1 and Parp14 expression.

Techniques: Expressing, Infection, RNA Sequencing, Gene Expression, Two Tailed Test

Journal: Microbiology Spectrum

Article Title: Exacerbated salmonellosis in poly(ADP-ribose) polymerase 14-deficient mice

doi: 10.1128/spectrum.02971-25

Figure Lengend Snippet: Transcriptional signature downregulated in S . Typhimurium-infected Parp14-deficient mice. Data from triplicate bulk tissue RNA-Seq analysis of mouse large intestine sections 1 day post-infection are shown. ( A ) Inter-sample correlation heatmap based on the FPKM values of the DEGs in Parp14-deficient vs wt mice comparison. R 2 is the square of Pearson correlation coefficient ( R ). ( B ) Volcano plots of the DEGs. Specific information on the DEGs is given in . The x -axis shows the fold difference in gene expression between different samples, and the y -axis shows the statistical significance of the differences. Red dots represent upregulation genes, and green dots represent downregulation genes. The dashed line indicates the threshold line for statistically significant differential gene expression. The values marked with asterisks refer to the number of DEGs that were used for a stringent downstream data analysis, that is, UP genes, log2(FoldChange) > 0.5 and P adj < 0.05; DOWN genes, log2(FoldChange) < −0.5 and P adj < 0.05 . ( C ) GO term analysis with DEGs in Parp14-deficient vs wt mice comparison (BP, biological process; CC, cellular component; MF, molecular function; ). The GO terms were searched using the canonical Fisher’s test and an FDR value <0.05 filter. ( D ) Bar graph representations of the top 20 identified GO BP terms (all the 107 identified GO BP terms in ) sorted based on the percentage of GO term gene values (number of detected genes in a particular GO term / number of all genes in a particular GO term × 100). The black asterisks in the sub-panel refer to the PB terms with functional relevance to cell adhesion and cytoskeleton remodeling. ( E ) Pathway-enrichment dot plot representations of the top 10 identified KEGG pathways sorted based on the P -value. All the identified KEGG pathways with the corresponding gene lists are described in . The count values refer to the number of genes that were detected in a particular KEGG pathway. The black asterisk in the wt sub-panel refers to the KEGG pathways with a <0.05 P adj -value.

Article Snippet: We used the single-cell RNA-Seq data analysis and visualization interface at the Broad Institute Single Cell Portal ( https://singlecell.broadinstitute.org/single_cell ) in order to analyze Parp1 and Parp14 expression.

Techniques: Infection, RNA Sequencing, Comparison, Gene Expression, Functional Assay

Journal: Microbiology Spectrum

Article Title: Exacerbated salmonellosis in poly(ADP-ribose) polymerase 14-deficient mice

doi: 10.1128/spectrum.02971-25

Figure Lengend Snippet: Epithelial cell-specific transcriptomic signature downregulated in the large intestine of S . Typhimurium-infected Parp14-deficient mice. ( A ) The Venn diagrams of the shared and unique genes in two comparisons, that is (i) genes upregulated by infection in wt mice (single-cell data ) vs genes downregulated by infection in Parp14-deficient mice (bulk tissue data), and (ii) genes downregulated by infection in wt mice (single-cell data ) vs genes upregulated by infection in Parp14-deficient mice (bulk tissue data). ( B ) The key single-cell RNA-Seq differential expression metrics of the shared genes. The numbers behind the gene names indicate the rank numbers, for example, ApoA1 was the third highest upregulated gene in goblet cells. ( C ) The key bulk tissue differential expression metrics of the shared genes. ( D ) TaqMan qPCR validation of the four shared genes with small and large intestine samples at day 1 and day 5. The figure illustrates the TaqMan qPCR data on relative gene expression with means and standard deviations. The calibrators in all sub-panels are the mean dCq values of the infected wt mice. Statistical analyses were done with a two-tailed unpaired t -test. All the statistical significance values of the comparisons between the wt and Parp14-deficient mice are indicated.

Article Snippet: We used the single-cell RNA-Seq data analysis and visualization interface at the Broad Institute Single Cell Portal ( https://singlecell.broadinstitute.org/single_cell ) in order to analyze Parp1 and Parp14 expression.

Techniques: Infection, Single Cell, RNA Sequencing, Quantitative Proteomics, Biomarker Discovery, Gene Expression, Two Tailed Test

Journal: Nature Communications

Article Title: Development of a split-toxin CRISPR screening platform to systematically identify regulators of human myoblast fusion

doi: 10.1038/s41467-025-67583-x

Figure Lengend Snippet: a Design of the muscle-targeted CRISPR knockout library (MyoCRISPR-KO Lib ), comprising 20,496 gene-targeting gRNAs (~3 per gene) and 900 non-targeting control gRNAs. TPM: transcripts per million. b Cumulative mRNA expression levels of genes included in the library, shown as a percentage of total mRNA from all protein-coding genes, based on RNA-seq analysis of seven human myoblast lines. Diff.: differentiation. c Cumulative read count plot showing the uniform distribution of gRNA abundances in the MyoCRISPR-KO Lib , as determined by deep sequencing. d Overview of the myoblast fitness screen. Each dot represents a single gRNA expression and corresponding gene perturbation. d’ , Hypothetical results illustrate the potential impact of gene perturbation, interpreted by comparing gRNA abundance across samples from different time points. e Top three pathways enriched among the 419 genes (Supplementary Data ) identified in the myoblast fitness screen. f gRNA quantification results for two representative hits. g Top three pathways enriched among the 47 negative regulators (Supplementary Data ) identified in the myoblast fitness screen. h gRNA quantification results for two representative hits. Source data are provided as a Source data file.

Article Snippet: Sequencing data analysis was conducted using the ParseBiosciences-Pipeline-v1.1.2.

Techniques: CRISPR, Knock-Out, Control, Expressing, RNA Sequencing, Sequencing