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97
Twist Bioscience viral capture probe panel
SARS-CoV-2 and Epstein-Barr Virus (EBV) detection in colorectal tissue and matched blood samples from participants with Long COVID (LC) and recovered (R) controls. A summary of <t>viral</t> detection sorted by time from initial infection ( a ) and most recent known or reported infection ( b ) to colorectal biopsy are shown. These graphs summarize results from tissue quantitative PCR (qPCR) for Spike (S) and Nucleocapsid (N) RNA, in-situ hybridization (RNAscope) of single-stranded (ss) and double-stranded (ds) viral RNAs targeting the S and ORF1a/b genomic regions, metagenomic sequencing (mNGS) with and without viral <t>capture</t> <t>probe</t> enrichment and nCounter, and circulating plasma S and N proteins. <t>Panel</t> ( c ) shows the sequence alignment locations of viral reads across the entire SARS-CoV-2 genome from each participant with a positive mGNS test. Panel ( d ) shows representative single-stranded (green) and double-stranded (red) SARS-CoV-2 RNA in colorectal sections from LC and recovered participants. Panel ( e ) shows example of duplexed ACE2 (red) and CD68 (yellow) fluorescent tissue immunohistochemical staining from participant LC33. CD68+ immune cells were observed scattered throughout the lamina propria (LP) in addition to residing in the sub-epithelium. ACE2 expression was low overall but was associated with epithelium and in subepithelial cells. PBMC = peripheral blood mononuclear cells, ORF open reading frame, NSP = non-structural proteins.
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Complete Genomics Inc mgieasy exome capture v5 probe set
Key challenges encountered during autonomous WES implementation in Algeria, with contextual evidence and implemented or planned solutions. Challenges operate at two interconnected levels: interpretive (dark grey, relating to population underrepresentation, VUS burden, and consanguinity) and ethical/structural (medium grey, relating to incidental findings, infrastructure, and territorial access). Each challenge is paired with its evidentiary context and the corresponding response developed within this programme. ACMG, American College of Medical Genetics and Genomics; AI, artificial intelligence (here: in-house computational tools for variant prioritisation and interpretation); AMinGen, Application for Medical Inquiry and Nexus in Genornics (national clinical genetics referral platform); AMP, Association for Molecular Pathology; ATM, ataxia telangiectasia mutated gene; CERIST, ResearchCentre for Scientific and Technical Information; DzNA, Database of Algerian variants and allele frequencies; HPO, Human Phenotype Ontology; MH, malignant hyperthermia; ROH, runs of homozygosity; RYRl, ryanodine receptor 1 gene; VUS, variant of uncertain significance; WES, <t>whole-exome</t> sequencing.
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Twist Bioscience capture probe design
Key challenges encountered during autonomous WES implementation in Algeria, with contextual evidence and implemented or planned solutions. Challenges operate at two interconnected levels: interpretive (dark grey, relating to population underrepresentation, VUS burden, and consanguinity) and ethical/structural (medium grey, relating to incidental findings, infrastructure, and territorial access). Each challenge is paired with its evidentiary context and the corresponding response developed within this programme. ACMG, American College of Medical Genetics and Genomics; AI, artificial intelligence (here: in-house computational tools for variant prioritisation and interpretation); AMinGen, Application for Medical Inquiry and Nexus in Genornics (national clinical genetics referral platform); AMP, Association for Molecular Pathology; ATM, ataxia telangiectasia mutated gene; CERIST, ResearchCentre for Scientific and Technical Information; DzNA, Database of Algerian variants and allele frequencies; HPO, Human Phenotype Ontology; MH, malignant hyperthermia; ROH, runs of homozygosity; RYRl, ryanodine receptor 1 gene; VUS, variant of uncertain significance; WES, <t>whole-exome</t> sequencing.
Capture Probe Design, supplied by Twist Bioscience, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Twist Bioscience custom twist capture probe panel
Key challenges encountered during autonomous WES implementation in Algeria, with contextual evidence and implemented or planned solutions. Challenges operate at two interconnected levels: interpretive (dark grey, relating to population underrepresentation, VUS burden, and consanguinity) and ethical/structural (medium grey, relating to incidental findings, infrastructure, and territorial access). Each challenge is paired with its evidentiary context and the corresponding response developed within this programme. ACMG, American College of Medical Genetics and Genomics; AI, artificial intelligence (here: in-house computational tools for variant prioritisation and interpretation); AMinGen, Application for Medical Inquiry and Nexus in Genornics (national clinical genetics referral platform); AMP, Association for Molecular Pathology; ATM, ataxia telangiectasia mutated gene; CERIST, ResearchCentre for Scientific and Technical Information; DzNA, Database of Algerian variants and allele frequencies; HPO, Human Phenotype Ontology; MH, malignant hyperthermia; ROH, runs of homozygosity; RYRl, ryanodine receptor 1 gene; VUS, variant of uncertain significance; WES, <t>whole-exome</t> sequencing.
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Twist Bioscience hybridization capture
Key challenges encountered during autonomous WES implementation in Algeria, with contextual evidence and implemented or planned solutions. Challenges operate at two interconnected levels: interpretive (dark grey, relating to population underrepresentation, VUS burden, and consanguinity) and ethical/structural (medium grey, relating to incidental findings, infrastructure, and territorial access). Each challenge is paired with its evidentiary context and the corresponding response developed within this programme. ACMG, American College of Medical Genetics and Genomics; AI, artificial intelligence (here: in-house computational tools for variant prioritisation and interpretation); AMinGen, Application for Medical Inquiry and Nexus in Genornics (national clinical genetics referral platform); AMP, Association for Molecular Pathology; ATM, ataxia telangiectasia mutated gene; CERIST, ResearchCentre for Scientific and Technical Information; DzNA, Database of Algerian variants and allele frequencies; HPO, Human Phenotype Ontology; MH, malignant hyperthermia; ROH, runs of homozygosity; RYRl, ryanodine receptor 1 gene; VUS, variant of uncertain significance; WES, <t>whole-exome</t> sequencing.
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Twist Bioscience custom designed hybrid capture probes
Key challenges encountered during autonomous WES implementation in Algeria, with contextual evidence and implemented or planned solutions. Challenges operate at two interconnected levels: interpretive (dark grey, relating to population underrepresentation, VUS burden, and consanguinity) and ethical/structural (medium grey, relating to incidental findings, infrastructure, and territorial access). Each challenge is paired with its evidentiary context and the corresponding response developed within this programme. ACMG, American College of Medical Genetics and Genomics; AI, artificial intelligence (here: in-house computational tools for variant prioritisation and interpretation); AMinGen, Application for Medical Inquiry and Nexus in Genornics (national clinical genetics referral platform); AMP, Association for Molecular Pathology; ATM, ataxia telangiectasia mutated gene; CERIST, ResearchCentre for Scientific and Technical Information; DzNA, Database of Algerian variants and allele frequencies; HPO, Human Phenotype Ontology; MH, malignant hyperthermia; ROH, runs of homozygosity; RYRl, ryanodine receptor 1 gene; VUS, variant of uncertain significance; WES, <t>whole-exome</t> sequencing.
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Twist Bioscience tg26372 mouse utilized custom capture probes
Key challenges encountered during autonomous WES implementation in Algeria, with contextual evidence and implemented or planned solutions. Challenges operate at two interconnected levels: interpretive (dark grey, relating to population underrepresentation, VUS burden, and consanguinity) and ethical/structural (medium grey, relating to incidental findings, infrastructure, and territorial access). Each challenge is paired with its evidentiary context and the corresponding response developed within this programme. ACMG, American College of Medical Genetics and Genomics; AI, artificial intelligence (here: in-house computational tools for variant prioritisation and interpretation); AMinGen, Application for Medical Inquiry and Nexus in Genornics (national clinical genetics referral platform); AMP, Association for Molecular Pathology; ATM, ataxia telangiectasia mutated gene; CERIST, ResearchCentre for Scientific and Technical Information; DzNA, Database of Algerian variants and allele frequencies; HPO, Human Phenotype Ontology; MH, malignant hyperthermia; ROH, runs of homozygosity; RYRl, ryanodine receptor 1 gene; VUS, variant of uncertain significance; WES, <t>whole-exome</t> sequencing.
Tg26372 Mouse Utilized Custom Capture Probes, supplied by Twist Bioscience, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Twist Bioscience region capture probes
a) Genome browser plot of the Il17a / Il17f locus (70kb window) integrating 500bp resolution <t>region</t> <t>capture</t> Micro-C (RCMC; ICE balanced, normalized by observed/expected), with 3D contacts annotated by dashed line and Il17a-5 enhancer contacts indicated by blue triangles; ATAC-STARR-seq pooled input DNA library coverage track containing DNA fragments from Th0 Th1 Th2 Th17 and Treg ATAC-seq (grey); ATAC-STARR-seq activity score (Log2 fold change CPM) from Th0 (blue), Th1 (orange), Th2 (red), Th17 (yellow) and Treg (green) RNA versus Input DNA; Effect sizes for gRNA in CRISPRi for Il17a and Il17f (grey = tested; red = FDR < 0.05). OCRs are labeled with direction (+/-) and distance (in Kbp) relative to nearest gene. b) Scatter plot comparing sgRNA effect sizes (Log2 fold change high vs low bin) for CRISPRi screens using Il17a and Il17f reporters (green = only Il17f, red = only Il17a, blue = both, grey = non-significant; FDR < 0.05). c) Distribution of elementwise sgRNA effect sizes grouped by top functional OCRs in both Il17a (left) and Il17f (right) CRISPRi screens (lines = tested gRNA per element, blue = FDR < 0.05). Density plot (top) shows distribution of effect sizes for all gRNA. d) Flow cytometry analysis summarizing frequency of IL-17a+ cells or e) geometric MFI of Il17f (HCR-FlowFish) expression from in vitro derived Th17 cells following CRISPRi-mediated perturbation with candidate gRNAs. f) Representative stacked histograms to show distribution of in vitro derived Th17 cell Il17a and Il17f signal (red) relative to non-transduced (grey) following CRISPRi-mediated repression with top candidate single gRNA. Statistical analysis was performed using one-way ANOVA with Dunnett’s post-hoc test versus NTC and sandwich standard error ( d ) or one-sample t-tests with Benjamini-Hochberg correction (e) . Data are shown as mean ± s.e.m. for gRNA-transduced (Thy1.1 + ) relative to non-transduced (Thy1.1-) cell signal; *** p<0.001; ** p<0.0001; * p<0.05.
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Complete Genomics Inc mgieasy exome capture v5 probe
a) Genome browser plot of the Il17a / Il17f locus (70kb window) integrating 500bp resolution <t>region</t> <t>capture</t> Micro-C (RCMC; ICE balanced, normalized by observed/expected), with 3D contacts annotated by dashed line and Il17a-5 enhancer contacts indicated by blue triangles; ATAC-STARR-seq pooled input DNA library coverage track containing DNA fragments from Th0 Th1 Th2 Th17 and Treg ATAC-seq (grey); ATAC-STARR-seq activity score (Log2 fold change CPM) from Th0 (blue), Th1 (orange), Th2 (red), Th17 (yellow) and Treg (green) RNA versus Input DNA; Effect sizes for gRNA in CRISPRi for Il17a and Il17f (grey = tested; red = FDR < 0.05). OCRs are labeled with direction (+/-) and distance (in Kbp) relative to nearest gene. b) Scatter plot comparing sgRNA effect sizes (Log2 fold change high vs low bin) for CRISPRi screens using Il17a and Il17f reporters (green = only Il17f, red = only Il17a, blue = both, grey = non-significant; FDR < 0.05). c) Distribution of elementwise sgRNA effect sizes grouped by top functional OCRs in both Il17a (left) and Il17f (right) CRISPRi screens (lines = tested gRNA per element, blue = FDR < 0.05). Density plot (top) shows distribution of effect sizes for all gRNA. d) Flow cytometry analysis summarizing frequency of IL-17a+ cells or e) geometric MFI of Il17f (HCR-FlowFish) expression from in vitro derived Th17 cells following CRISPRi-mediated perturbation with candidate gRNAs. f) Representative stacked histograms to show distribution of in vitro derived Th17 cell Il17a and Il17f signal (red) relative to non-transduced (grey) following CRISPRi-mediated repression with top candidate single gRNA. Statistical analysis was performed using one-way ANOVA with Dunnett’s post-hoc test versus NTC and sandwich standard error ( d ) or one-sample t-tests with Benjamini-Hochberg correction (e) . Data are shown as mean ± s.e.m. for gRNA-transduced (Thy1.1 + ) relative to non-transduced (Thy1.1-) cell signal; *** p<0.001; ** p<0.0001; * p<0.05.
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SARS-CoV-2 and Epstein-Barr Virus (EBV) detection in colorectal tissue and matched blood samples from participants with Long COVID (LC) and recovered (R) controls. A summary of viral detection sorted by time from initial infection ( a ) and most recent known or reported infection ( b ) to colorectal biopsy are shown. These graphs summarize results from tissue quantitative PCR (qPCR) for Spike (S) and Nucleocapsid (N) RNA, in-situ hybridization (RNAscope) of single-stranded (ss) and double-stranded (ds) viral RNAs targeting the S and ORF1a/b genomic regions, metagenomic sequencing (mNGS) with and without viral capture probe enrichment and nCounter, and circulating plasma S and N proteins. Panel ( c ) shows the sequence alignment locations of viral reads across the entire SARS-CoV-2 genome from each participant with a positive mGNS test. Panel ( d ) shows representative single-stranded (green) and double-stranded (red) SARS-CoV-2 RNA in colorectal sections from LC and recovered participants. Panel ( e ) shows example of duplexed ACE2 (red) and CD68 (yellow) fluorescent tissue immunohistochemical staining from participant LC33. CD68+ immune cells were observed scattered throughout the lamina propria (LP) in addition to residing in the sub-epithelium. ACE2 expression was low overall but was associated with epithelium and in subepithelial cells. PBMC = peripheral blood mononuclear cells, ORF open reading frame, NSP = non-structural proteins.

Journal: bioRxiv

Article Title: Multiomic and Spatial Profiling of Colorectal Tissue Reveals Viral Persistence and Immune Dysregulation in Long COVID

doi: 10.64898/2026.08.07.743616

Figure Lengend Snippet: SARS-CoV-2 and Epstein-Barr Virus (EBV) detection in colorectal tissue and matched blood samples from participants with Long COVID (LC) and recovered (R) controls. A summary of viral detection sorted by time from initial infection ( a ) and most recent known or reported infection ( b ) to colorectal biopsy are shown. These graphs summarize results from tissue quantitative PCR (qPCR) for Spike (S) and Nucleocapsid (N) RNA, in-situ hybridization (RNAscope) of single-stranded (ss) and double-stranded (ds) viral RNAs targeting the S and ORF1a/b genomic regions, metagenomic sequencing (mNGS) with and without viral capture probe enrichment and nCounter, and circulating plasma S and N proteins. Panel ( c ) shows the sequence alignment locations of viral reads across the entire SARS-CoV-2 genome from each participant with a positive mGNS test. Panel ( d ) shows representative single-stranded (green) and double-stranded (red) SARS-CoV-2 RNA in colorectal sections from LC and recovered participants. Panel ( e ) shows example of duplexed ACE2 (red) and CD68 (yellow) fluorescent tissue immunohistochemical staining from participant LC33. CD68+ immune cells were observed scattered throughout the lamina propria (LP) in addition to residing in the sub-epithelium. ACE2 expression was low overall but was associated with epithelium and in subepithelial cells. PBMC = peripheral blood mononuclear cells, ORF open reading frame, NSP = non-structural proteins.

Article Snippet: We then co-extracted cellular RNA and DNA from cryopreserved bulk colorectal tissues and performed (1) unbiased metagenomic next-generation sequencing (mNGS) with and without enrichment using a viral capture probe panel (Twist Bioscience, South San Francisco, CA) targeting more than 1,000 eukaryotic viruses, including known human pathogens (2) multiplexed RNA probe hybridization quantitation (nCounter, nanoString Technologies, Seattle, WA) incorporating 807 human host-viral response transcripts and viral transcripts across multiple genomic regions of SARS-CoV-2, SARS-CoV-1, and Epstein-Barr Virus (EBV), a ubiquitous human herpesvirus that has been implicated in LC pathogenesis – (complete list of genes included in the panel in Table S1 ); and (3) real-time PCR targeting the SARS-CoV-2 S1, S2, and N regions .

Techniques: Virus, Infection, Real-time Polymerase Chain Reaction, RNA In Situ Hybridization, RNAscope, Sequencing, Clinical Proteomics, Immunohistochemical staining, Staining, Expressing

Key challenges encountered during autonomous WES implementation in Algeria, with contextual evidence and implemented or planned solutions. Challenges operate at two interconnected levels: interpretive (dark grey, relating to population underrepresentation, VUS burden, and consanguinity) and ethical/structural (medium grey, relating to incidental findings, infrastructure, and territorial access). Each challenge is paired with its evidentiary context and the corresponding response developed within this programme. ACMG, American College of Medical Genetics and Genomics; AI, artificial intelligence (here: in-house computational tools for variant prioritisation and interpretation); AMinGen, Application for Medical Inquiry and Nexus in Genornics (national clinical genetics referral platform); AMP, Association for Molecular Pathology; ATM, ataxia telangiectasia mutated gene; CERIST, ResearchCentre for Scientific and Technical Information; DzNA, Database of Algerian variants and allele frequencies; HPO, Human Phenotype Ontology; MH, malignant hyperthermia; ROH, runs of homozygosity; RYRl, ryanodine receptor 1 gene; VUS, variant of uncertain significance; WES, whole-exome sequencing.

Journal: medRxiv

Article Title: Challenges and perspectives in implementing whole-exome sequencing in Algeria: lessons from a fully autonomous in-country cohort

doi: 10.64898/2026.03.23.26348909

Figure Lengend Snippet: Key challenges encountered during autonomous WES implementation in Algeria, with contextual evidence and implemented or planned solutions. Challenges operate at two interconnected levels: interpretive (dark grey, relating to population underrepresentation, VUS burden, and consanguinity) and ethical/structural (medium grey, relating to incidental findings, infrastructure, and territorial access). Each challenge is paired with its evidentiary context and the corresponding response developed within this programme. ACMG, American College of Medical Genetics and Genomics; AI, artificial intelligence (here: in-house computational tools for variant prioritisation and interpretation); AMinGen, Application for Medical Inquiry and Nexus in Genornics (national clinical genetics referral platform); AMP, Association for Molecular Pathology; ATM, ataxia telangiectasia mutated gene; CERIST, ResearchCentre for Scientific and Technical Information; DzNA, Database of Algerian variants and allele frequencies; HPO, Human Phenotype Ontology; MH, malignant hyperthermia; ROH, runs of homozygosity; RYRl, ryanodine receptor 1 gene; VUS, variant of uncertain significance; WES, whole-exome sequencing.

Article Snippet: Exome enrichment targeting all coding exons and flanking canonical splice junctions within approximately ±50 bp was performed using the MGIEasy Exome Capture V5 probe set (MGI Tech).

Techniques: Variant Assay, Sequencing

a) Genome browser plot of the Il17a / Il17f locus (70kb window) integrating 500bp resolution region capture Micro-C (RCMC; ICE balanced, normalized by observed/expected), with 3D contacts annotated by dashed line and Il17a-5 enhancer contacts indicated by blue triangles; ATAC-STARR-seq pooled input DNA library coverage track containing DNA fragments from Th0 Th1 Th2 Th17 and Treg ATAC-seq (grey); ATAC-STARR-seq activity score (Log2 fold change CPM) from Th0 (blue), Th1 (orange), Th2 (red), Th17 (yellow) and Treg (green) RNA versus Input DNA; Effect sizes for gRNA in CRISPRi for Il17a and Il17f (grey = tested; red = FDR < 0.05). OCRs are labeled with direction (+/-) and distance (in Kbp) relative to nearest gene. b) Scatter plot comparing sgRNA effect sizes (Log2 fold change high vs low bin) for CRISPRi screens using Il17a and Il17f reporters (green = only Il17f, red = only Il17a, blue = both, grey = non-significant; FDR < 0.05). c) Distribution of elementwise sgRNA effect sizes grouped by top functional OCRs in both Il17a (left) and Il17f (right) CRISPRi screens (lines = tested gRNA per element, blue = FDR < 0.05). Density plot (top) shows distribution of effect sizes for all gRNA. d) Flow cytometry analysis summarizing frequency of IL-17a+ cells or e) geometric MFI of Il17f (HCR-FlowFish) expression from in vitro derived Th17 cells following CRISPRi-mediated perturbation with candidate gRNAs. f) Representative stacked histograms to show distribution of in vitro derived Th17 cell Il17a and Il17f signal (red) relative to non-transduced (grey) following CRISPRi-mediated repression with top candidate single gRNA. Statistical analysis was performed using one-way ANOVA with Dunnett’s post-hoc test versus NTC and sandwich standard error ( d ) or one-sample t-tests with Benjamini-Hochberg correction (e) . Data are shown as mean ± s.e.m. for gRNA-transduced (Thy1.1 + ) relative to non-transduced (Thy1.1-) cell signal; *** p<0.001; ** p<0.0001; * p<0.05.

Journal: bioRxiv

Article Title: Enhancer hubs govern chromatin topology and Th17 identity

doi: 10.64898/2026.04.02.715458

Figure Lengend Snippet: a) Genome browser plot of the Il17a / Il17f locus (70kb window) integrating 500bp resolution region capture Micro-C (RCMC; ICE balanced, normalized by observed/expected), with 3D contacts annotated by dashed line and Il17a-5 enhancer contacts indicated by blue triangles; ATAC-STARR-seq pooled input DNA library coverage track containing DNA fragments from Th0 Th1 Th2 Th17 and Treg ATAC-seq (grey); ATAC-STARR-seq activity score (Log2 fold change CPM) from Th0 (blue), Th1 (orange), Th2 (red), Th17 (yellow) and Treg (green) RNA versus Input DNA; Effect sizes for gRNA in CRISPRi for Il17a and Il17f (grey = tested; red = FDR < 0.05). OCRs are labeled with direction (+/-) and distance (in Kbp) relative to nearest gene. b) Scatter plot comparing sgRNA effect sizes (Log2 fold change high vs low bin) for CRISPRi screens using Il17a and Il17f reporters (green = only Il17f, red = only Il17a, blue = both, grey = non-significant; FDR < 0.05). c) Distribution of elementwise sgRNA effect sizes grouped by top functional OCRs in both Il17a (left) and Il17f (right) CRISPRi screens (lines = tested gRNA per element, blue = FDR < 0.05). Density plot (top) shows distribution of effect sizes for all gRNA. d) Flow cytometry analysis summarizing frequency of IL-17a+ cells or e) geometric MFI of Il17f (HCR-FlowFish) expression from in vitro derived Th17 cells following CRISPRi-mediated perturbation with candidate gRNAs. f) Representative stacked histograms to show distribution of in vitro derived Th17 cell Il17a and Il17f signal (red) relative to non-transduced (grey) following CRISPRi-mediated repression with top candidate single gRNA. Statistical analysis was performed using one-way ANOVA with Dunnett’s post-hoc test versus NTC and sandwich standard error ( d ) or one-sample t-tests with Benjamini-Hochberg correction (e) . Data are shown as mean ± s.e.m. for gRNA-transduced (Thy1.1 + ) relative to non-transduced (Thy1.1-) cell signal; *** p<0.001; ** p<0.0001; * p<0.05.

Article Snippet: Region-capture probes were designed by Twist Bioscience to multiplex-capture the Il17a/f (chr1:20198461-22383378), Rorc (chr3:93261362-95108248), and Batf (chr12:84681315-86479642) loci using end-to-end tiling with 80-120mer non-overlapping probes, and low off-target stringency settings.

Techniques: Activity Assay, Labeling, Functional Assay, Flow Cytometry, Expressing, In Vitro, Derivative Assay

a) Multimodal view of the Batf locus (100k bp window). Top: Region-capture Micro-C (RCMC) contact map (200bp resolution; ICE balanced), with interactions annotated by dotted lines. Tracks display Th17 ATAC-seq coverage by condition (non-targeting control [NTC] = grey; +19kb CRISPRi = red), Th17 ATAC-STARR-seq activity (Log2 CPM RNA / DNA; yellow), and CRISPRi/CRISPRa screen effect sizes (points indicate tested sgRNA, red = FDR < 0.05). Enhancers are annotated by distance (kb) and direction (+/-) relative to the Batf TSS. b) Scatter plot comparing CRISPRi versus CRISPRa effect sizes (Log2 fold change) for all tested sgRNA. Points coloured by significance (FDR < 0.05). c) Distribution of sgRNA effect sizes at selected elements from CRISPRi (left) and CRISPRa (right) screens (blue = significant; grey = tested) d) Comparison of RCMC contact frequency (500bp resolution) at the Batf locus following transduction with Batf +19kb-targeting (top) or NTC (bottom) sgRNAs in dCas9-KRAB Th17 cells. e) Differential contact map showing Log2 fold-change in interaction frequency (Batf +19kb sgRNA / NTC) f) Aggregate Peak Analysis quantifying contact frequency of interactions between the Batf-TSS (P), Batf +19kb (E1) and Batf +43kb (E2) elements in CRISPRi-mediated Batf +19kb perturbed Th17 cells (red) versus NTC (grey). g) Quantitative comparison of transcriptomic changes measured by RNA-seq (Log2 fold-changes relative to control) or h) chromatin accessibility changes by ATAC-seq (Log2 fold-change relative to control) in Batf-/-(BATF-KO) and CRISPRi-mediated Batf +19kb enhancer perturbation (Batf-gRNA) of in vitro derived Th17 cells (RNA Pearson’s r = 0.78; ATAC Pearson’s r = 0.774). i) MFI of BATF (red) or RORyt (green), and frequency of IL-17A+ (blue) from in vitro derived Th17 cells following CRISPRi-mediated repression of candidate OCRs with single gRNA relative to non-targeting control. Box plots summarise n=3 biological replicates j) Representative stacked histograms for BATF (red) IL-17a (blue) and RORγt (green) protein levels in Th17 cells following CRISPRi-mediated repression of Batf +19kb enhancer compared to nontargeting control (grey). Statistical analysis was performed using one-way ANOVA with Dunnett’s test versus the NTC and sandwich standard errors. Data are shown as mean ± s.e.m. relative to the NTC; * p <0.001.

Journal: bioRxiv

Article Title: Enhancer hubs govern chromatin topology and Th17 identity

doi: 10.64898/2026.04.02.715458

Figure Lengend Snippet: a) Multimodal view of the Batf locus (100k bp window). Top: Region-capture Micro-C (RCMC) contact map (200bp resolution; ICE balanced), with interactions annotated by dotted lines. Tracks display Th17 ATAC-seq coverage by condition (non-targeting control [NTC] = grey; +19kb CRISPRi = red), Th17 ATAC-STARR-seq activity (Log2 CPM RNA / DNA; yellow), and CRISPRi/CRISPRa screen effect sizes (points indicate tested sgRNA, red = FDR < 0.05). Enhancers are annotated by distance (kb) and direction (+/-) relative to the Batf TSS. b) Scatter plot comparing CRISPRi versus CRISPRa effect sizes (Log2 fold change) for all tested sgRNA. Points coloured by significance (FDR < 0.05). c) Distribution of sgRNA effect sizes at selected elements from CRISPRi (left) and CRISPRa (right) screens (blue = significant; grey = tested) d) Comparison of RCMC contact frequency (500bp resolution) at the Batf locus following transduction with Batf +19kb-targeting (top) or NTC (bottom) sgRNAs in dCas9-KRAB Th17 cells. e) Differential contact map showing Log2 fold-change in interaction frequency (Batf +19kb sgRNA / NTC) f) Aggregate Peak Analysis quantifying contact frequency of interactions between the Batf-TSS (P), Batf +19kb (E1) and Batf +43kb (E2) elements in CRISPRi-mediated Batf +19kb perturbed Th17 cells (red) versus NTC (grey). g) Quantitative comparison of transcriptomic changes measured by RNA-seq (Log2 fold-changes relative to control) or h) chromatin accessibility changes by ATAC-seq (Log2 fold-change relative to control) in Batf-/-(BATF-KO) and CRISPRi-mediated Batf +19kb enhancer perturbation (Batf-gRNA) of in vitro derived Th17 cells (RNA Pearson’s r = 0.78; ATAC Pearson’s r = 0.774). i) MFI of BATF (red) or RORyt (green), and frequency of IL-17A+ (blue) from in vitro derived Th17 cells following CRISPRi-mediated repression of candidate OCRs with single gRNA relative to non-targeting control. Box plots summarise n=3 biological replicates j) Representative stacked histograms for BATF (red) IL-17a (blue) and RORγt (green) protein levels in Th17 cells following CRISPRi-mediated repression of Batf +19kb enhancer compared to nontargeting control (grey). Statistical analysis was performed using one-way ANOVA with Dunnett’s test versus the NTC and sandwich standard errors. Data are shown as mean ± s.e.m. relative to the NTC; * p <0.001.

Article Snippet: Region-capture probes were designed by Twist Bioscience to multiplex-capture the Il17a/f (chr1:20198461-22383378), Rorc (chr3:93261362-95108248), and Batf (chr12:84681315-86479642) loci using end-to-end tiling with 80-120mer non-overlapping probes, and low off-target stringency settings.

Techniques: Control, Activity Assay, Comparison, Transduction, RNA Sequencing, In Vitro, Derivative Assay