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dnase i hotspot data from encode, blueprint, and consolidated and unconsolidated roadmap  (Epigenomics ag)

 
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    Epigenomics ag dnase i hotspot data from encode, blueprint, and consolidated and unconsolidated roadmap
    GWAS enrichments for immune cell H3K4me1 broadPeaks from consolidated <t>Roadmap</t> Epigenomics consortium data: shown are significant cell type-specific enrichment results ( q value < 0.01, BH correction) for FORGE2 analysis across the NHGRI/EBI GWAS catalogue (downloaded 2 September 2019). GWAS phenotypes (rows) are clustered using complete linkage clustering (Euclidean distance), while different tissues and cell types (columns) are grouped according to related tissue or cell type categories (e.g. T cell categories are placed together, as are haematopoietic stem cell categories, etc.). All sample categories, including non-immune cell categories, are shown. Values are row-normalised, with reference lineplot on the left indicating top enrichment value for each category. Clustering reveals grouping of related phenotypes with similar immune cell type-specific enrichment profiles. We highlighted several groups including known related phenotypes such as mean corpuscular volume for HSCs, monocyte count for monocytes and rheumatoid arthritis for B cells (right panel). A zoomable version of this figure can be found at: https://www.easyzoom.com/imageaccess/e8c2fd02c90f456b85f629635c2f30a3
    Dnase I Hotspot Data From Encode, Blueprint, And Consolidated And Unconsolidated Roadmap, supplied by Epigenomics ag, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/encode/dnase+i+hotspot+data+from+encode++blueprint++and+consolidated+and+unconsolidated+roadmap/pmc08742386-233-32-34
    Average 90 stars, based on 1 article reviews
    dnase i hotspot data from encode, blueprint, and consolidated and unconsolidated roadmap - by Bioz Stars, 2026-10
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    Images

    1) Product Images from "Integrative analysis of 3604 GWAS reveals multiple novel cell type-specific regulatory associations"

    Article Title: Integrative analysis of 3604 GWAS reveals multiple novel cell type-specific regulatory associations

    Journal: Genome Biology

    doi: 10.1186/s13059-021-02560-3

    GWAS enrichments for immune cell H3K4me1 broadPeaks from consolidated Roadmap Epigenomics consortium data: shown are significant cell type-specific enrichment results ( q value < 0.01, BH correction) for FORGE2 analysis across the NHGRI/EBI GWAS catalogue (downloaded 2 September 2019). GWAS phenotypes (rows) are clustered using complete linkage clustering (Euclidean distance), while different tissues and cell types (columns) are grouped according to related tissue or cell type categories (e.g. T cell categories are placed together, as are haematopoietic stem cell categories, etc.). All sample categories, including non-immune cell categories, are shown. Values are row-normalised, with reference lineplot on the left indicating top enrichment value for each category. Clustering reveals grouping of related phenotypes with similar immune cell type-specific enrichment profiles. We highlighted several groups including known related phenotypes such as mean corpuscular volume for HSCs, monocyte count for monocytes and rheumatoid arthritis for B cells (right panel). A zoomable version of this figure can be found at: https://www.easyzoom.com/imageaccess/e8c2fd02c90f456b85f629635c2f30a3
    Figure Legend Snippet: GWAS enrichments for immune cell H3K4me1 broadPeaks from consolidated Roadmap Epigenomics consortium data: shown are significant cell type-specific enrichment results ( q value < 0.01, BH correction) for FORGE2 analysis across the NHGRI/EBI GWAS catalogue (downloaded 2 September 2019). GWAS phenotypes (rows) are clustered using complete linkage clustering (Euclidean distance), while different tissues and cell types (columns) are grouped according to related tissue or cell type categories (e.g. T cell categories are placed together, as are haematopoietic stem cell categories, etc.). All sample categories, including non-immune cell categories, are shown. Values are row-normalised, with reference lineplot on the left indicating top enrichment value for each category. Clustering reveals grouping of related phenotypes with similar immune cell type-specific enrichment profiles. We highlighted several groups including known related phenotypes such as mean corpuscular volume for HSCs, monocyte count for monocytes and rheumatoid arthritis for B cells (right panel). A zoomable version of this figure can be found at: https://www.easyzoom.com/imageaccess/e8c2fd02c90f456b85f629635c2f30a3

    Techniques Used:

    Shared and distinct tissue-specific enrichments for histone mark broadPeaks from consolidated Roadmap Epigenomics consortium data: ( A ) 231 tissue-specific enriched phenotypes from histone mark broadPeaks are shared with the set of enriched phenotypes for DNase I hotspot data for the same tissues, including examples for brain (central panel, self-reported math ability -MTAG-, H3K4me1 and H3K4me3 enrichment), heart (atrial fibrillation, H3K4me1 and H3K4me3 enrichment), kidney (estimated glomerular filtration rate or eGFR, H3K4me3 and H3K36me3 enrichment), and thymus (family history of Alzheimer’s, H3K9me3 enrichment). ( B ) 265 tissue-specific enriched phenotypes from histone mark broadPeaks are not shared with the set of enriched phenotypes for DNase I hotspot analysis for the same tissues, including examples for brain (central panel, cognitive performance H3K4me1 enrichment), heart (electrocardiographic traits, H3K4me1 enrichment), and thymus (nodular sclerosing Hodgkin lymphoma or NSHL H3K36me3 enrichment). PR interval (P wave to initiation of QRS complex interval), QT interval (Q wave to end of T wave interval), RBCs (red blood cells), WBCs (white blood cells), MTAG (multi-trait analysis of GWAS), NSHL (nodular sclerosis Hodgkin's lymphoma), Apolipoprotein E allele E4 (APOE e4). Tissue images used here are from Roadmap Epigenomics Consortium et al., 2015 [6]. A zoomable version of this figure can be found at: https://www.easyzoom.com/imageaccess/196e07438d2f48f6b24cb378d65f31b7
    Figure Legend Snippet: Shared and distinct tissue-specific enrichments for histone mark broadPeaks from consolidated Roadmap Epigenomics consortium data: ( A ) 231 tissue-specific enriched phenotypes from histone mark broadPeaks are shared with the set of enriched phenotypes for DNase I hotspot data for the same tissues, including examples for brain (central panel, self-reported math ability -MTAG-, H3K4me1 and H3K4me3 enrichment), heart (atrial fibrillation, H3K4me1 and H3K4me3 enrichment), kidney (estimated glomerular filtration rate or eGFR, H3K4me3 and H3K36me3 enrichment), and thymus (family history of Alzheimer’s, H3K9me3 enrichment). ( B ) 265 tissue-specific enriched phenotypes from histone mark broadPeaks are not shared with the set of enriched phenotypes for DNase I hotspot analysis for the same tissues, including examples for brain (central panel, cognitive performance H3K4me1 enrichment), heart (electrocardiographic traits, H3K4me1 enrichment), and thymus (nodular sclerosing Hodgkin lymphoma or NSHL H3K36me3 enrichment). PR interval (P wave to initiation of QRS complex interval), QT interval (Q wave to end of T wave interval), RBCs (red blood cells), WBCs (white blood cells), MTAG (multi-trait analysis of GWAS), NSHL (nodular sclerosis Hodgkin's lymphoma), Apolipoprotein E allele E4 (APOE e4). Tissue images used here are from Roadmap Epigenomics Consortium et al., 2015 [6]. A zoomable version of this figure can be found at: https://www.easyzoom.com/imageaccess/196e07438d2f48f6b24cb378d65f31b7

    Techniques Used: Filtration

    GWAS enrichments for enhancer (Enh) HMM chromatin state regions from consolidated Roadmap Epigenomics consortium data: ( A ) Shown are significant tissue-specific enrichment results ( q value < 0.01, BH correction) for a representative random subset with 40 phenotypes from FORGE2 analysis across the NHGRI/EBI GWAS catalogue (downloaded 2 September 2019, full set shown in Additional File : Figure S19). GWAS phenotypes (rows) are clustered using complete linkage clustering (Euclidean distance), while different tissues and cell types (columns) are grouped according to related tissue or cell type categories (e.g. white blood cell categories are placed together, as are fibroblast categories, etc.). Values are row-normalised, with reference lineplot on the left indicating top enrichment value for each category. Clustering reveals grouping of related phenotypes with similar tissue-specific enrichment profiles. We highlighted several groups from each tissue, including phenotypes such as self-reported allergy for blood cells, atrial fibrillation for heart tissue or high-density lipoprotein (HDL) cholesterol levels for liver. ( B ) Number of shared vs unique (non-shared) tissue-specific enrichment profiles for different GWAS phenotypes across 15 chromatin states. ( C ) Venn diagram showing number of shared and unique (non-shared) phenotypes between DNase-seq datasets (DNase I hotspots), chromatin states and histone mark broadPeak datasets. The largest category is unique enriched phenotypes for histone mark broadPeaks (204, 34.8%), followed by shared enriched phenotypes across all three categories (160, 27.3%). A zoomable version of this figure can be found at: https://www.easyzoom.com/imageaccess/9e3b9bab699148f586db26ad36ba0002
    Figure Legend Snippet: GWAS enrichments for enhancer (Enh) HMM chromatin state regions from consolidated Roadmap Epigenomics consortium data: ( A ) Shown are significant tissue-specific enrichment results ( q value < 0.01, BH correction) for a representative random subset with 40 phenotypes from FORGE2 analysis across the NHGRI/EBI GWAS catalogue (downloaded 2 September 2019, full set shown in Additional File : Figure S19). GWAS phenotypes (rows) are clustered using complete linkage clustering (Euclidean distance), while different tissues and cell types (columns) are grouped according to related tissue or cell type categories (e.g. white blood cell categories are placed together, as are fibroblast categories, etc.). Values are row-normalised, with reference lineplot on the left indicating top enrichment value for each category. Clustering reveals grouping of related phenotypes with similar tissue-specific enrichment profiles. We highlighted several groups from each tissue, including phenotypes such as self-reported allergy for blood cells, atrial fibrillation for heart tissue or high-density lipoprotein (HDL) cholesterol levels for liver. ( B ) Number of shared vs unique (non-shared) tissue-specific enrichment profiles for different GWAS phenotypes across 15 chromatin states. ( C ) Venn diagram showing number of shared and unique (non-shared) phenotypes between DNase-seq datasets (DNase I hotspots), chromatin states and histone mark broadPeak datasets. The largest category is unique enriched phenotypes for histone mark broadPeaks (204, 34.8%), followed by shared enriched phenotypes across all three categories (160, 27.3%). A zoomable version of this figure can be found at: https://www.easyzoom.com/imageaccess/9e3b9bab699148f586db26ad36ba0002

    Techniques Used:

    Relationship between enriched GWAS phenotypes for different epigenomic marks from consolidated Roadmap Epigenomics consortium data: heatmap showing the number of tissue-specific enriched phenotypes ( q value < 0.01, BH correction) for FORGE2 analysis across the GWAS catalogue for DNase I hotspots, histone mark broadPeaks and HMM chromatin states. Epigenomic mark categories are clustered using complete linkage clustering (Euclidean distance), across rows and columns. Clustering reveals 5 main groups of epigenomic marks, coloured in purple (group 1), dark blue (group 2), green (group 3), yellow (group 4), and light blue (group 5). A zoomable version of this figure can be found at: https://www.easyzoom.com/imageaccess/4e114698194f492faa1d6812d325cd30
    Figure Legend Snippet: Relationship between enriched GWAS phenotypes for different epigenomic marks from consolidated Roadmap Epigenomics consortium data: heatmap showing the number of tissue-specific enriched phenotypes ( q value < 0.01, BH correction) for FORGE2 analysis across the GWAS catalogue for DNase I hotspots, histone mark broadPeaks and HMM chromatin states. Epigenomic mark categories are clustered using complete linkage clustering (Euclidean distance), across rows and columns. Clustering reveals 5 main groups of epigenomic marks, coloured in purple (group 1), dark blue (group 2), green (group 3), yellow (group 4), and light blue (group 5). A zoomable version of this figure can be found at: https://www.easyzoom.com/imageaccess/4e114698194f492faa1d6812d325cd30

    Techniques Used:

    Myeloproliferative neoplasm GWAS enrichment for DNase I hotspots and consolidated histone mark broadPeaks from Roadmap Epigenomics consortium data: ( A ) Significant tissue- and cell type-specific enrichment results ( q value < 0.01, Benjamini-Hochberg (BH) correction) for FORGE2 DNase I hotspot analysis on 25 suggestive MPN GWAS associations ( p value < 1 × 10 −6 ). Different tissues and cell types (rows) are grouped according to related tissue or cell type categories (e.g. white blood cell categories are placed together, as are fibroblast categories, etc.). FORGE2 DNase I hotspot analysis reveals a cell type-specific enrichment profile for CD34+ haematopoietic stem cells (red dot). ( B ) Significant tissue- and cell type-specific enrichment results ( q value < 0.01, Benjamini-Hochberg (BH) correction) for FORGE2 histone mark broadPeak analysis for the same variants. Different tissues and cell types (rows) are grouped according to related tissue or cell type categories (e.g. white blood cell categories are placed together, as are fibroblast categories, etc.). Here, FORGE2 analysis reveals a cell type-specific enrichment profile for CD34+ haematopoietic stem cell H3K4me1 broadPeaks, a mark enriched for enhancer regions (red dot). A zoomable version of this figure can be found at: https://www.easyzoom.com/imageaccess/3245f515d6894a8eb644b35ea22b2ef5
    Figure Legend Snippet: Myeloproliferative neoplasm GWAS enrichment for DNase I hotspots and consolidated histone mark broadPeaks from Roadmap Epigenomics consortium data: ( A ) Significant tissue- and cell type-specific enrichment results ( q value < 0.01, Benjamini-Hochberg (BH) correction) for FORGE2 DNase I hotspot analysis on 25 suggestive MPN GWAS associations ( p value < 1 × 10 −6 ). Different tissues and cell types (rows) are grouped according to related tissue or cell type categories (e.g. white blood cell categories are placed together, as are fibroblast categories, etc.). FORGE2 DNase I hotspot analysis reveals a cell type-specific enrichment profile for CD34+ haematopoietic stem cells (red dot). ( B ) Significant tissue- and cell type-specific enrichment results ( q value < 0.01, Benjamini-Hochberg (BH) correction) for FORGE2 histone mark broadPeak analysis for the same variants. Different tissues and cell types (rows) are grouped according to related tissue or cell type categories (e.g. white blood cell categories are placed together, as are fibroblast categories, etc.). Here, FORGE2 analysis reveals a cell type-specific enrichment profile for CD34+ haematopoietic stem cell H3K4me1 broadPeaks, a mark enriched for enhancer regions (red dot). A zoomable version of this figure can be found at: https://www.easyzoom.com/imageaccess/3245f515d6894a8eb644b35ea22b2ef5

    Techniques Used:

    Related Articles

    Filtration:

    Article Title: Integrative analysis of 3604 GWAS reveals multiple novel cell type-specific regulatory associations
    Article Snippet: We ran FORGE2 with default settings (i.e. 1000 background repetitions) and a significance threshold of q value< 0.01, across the following datasets: DNase I hotspot data from ENCODE, BLUEPRINT, and consolidated and unconsolidated Roadmap Epigenomics, 5 histone mark categories from consolidated Roadmap Epigenomics data and 15 HMM chromatin state datasets from consolidated Roadmap Epigenomics data.



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    Image Search Results


    (A) Strategy for generating Zfp536 p.(Gln169Ter) KI mice using CRISPR/Cas9-mediated genome editing within exon 4. Mouse NM_172385.3 has six exons, and the lower panel is a zoomed in view of exon 4 where the mutation encoding p.(Gln169Ter) is located. (B) Representative Sanger sequencing chromatograms of PCR products from tail DNA, showing WT, HET, and HOM genotypes. (C) Distribution of offspring genotypes from HET × HET crosses. (D) Survival curves of WT, HET, and HOM mice within the first 40 postnatal days. (E) Three-chamber social interaction test. Time spent with an object (O) versus stranger 1 (S1), and stranger 1 (S1) versus stranger 2 (S2), is shown. Preference indexes (S1:O and S2:S1) are compared between WT and HET mice. (F) Repetitive behavior assessment. Statistical comparison of grooming duration, digging duration, and rearing frequency between WT and HET mice. (G) Novel object recognition test. Exploration time with old versus novel objects is compared within each genotype, and discrimination indexes are compared between WT and HET mice. (H) Light–dark box test. Time spent in the light compartment and number of light box entries are compared between WT and HET mice. (I) Open field test. Total distance traveled and time spent in the central zone are compared between WT and HET mice. (J) Elevated plus maze test. Duration and distance traveled in the open and closed arms are compared between WT and HET mice. All data are presented as mean ± SEM. Statistical analyses were performed using Student’s t-test. ns, not significant; *p < 0.05, **p < 0.01. WT, wild type; HET, heterozygous; HOM, homozygous.

    Journal: American journal of human genetics

    Article Title: Monoallelic loss-of-function variants in ZNF536 are associated with a neurodevelopmental disorder with prominent behavioral features

    doi: 10.1016/j.ajhg.2026.08.013

    Figure Lengend Snippet: (A) Strategy for generating Zfp536 p.(Gln169Ter) KI mice using CRISPR/Cas9-mediated genome editing within exon 4. Mouse NM_172385.3 has six exons, and the lower panel is a zoomed in view of exon 4 where the mutation encoding p.(Gln169Ter) is located. (B) Representative Sanger sequencing chromatograms of PCR products from tail DNA, showing WT, HET, and HOM genotypes. (C) Distribution of offspring genotypes from HET × HET crosses. (D) Survival curves of WT, HET, and HOM mice within the first 40 postnatal days. (E) Three-chamber social interaction test. Time spent with an object (O) versus stranger 1 (S1), and stranger 1 (S1) versus stranger 2 (S2), is shown. Preference indexes (S1:O and S2:S1) are compared between WT and HET mice. (F) Repetitive behavior assessment. Statistical comparison of grooming duration, digging duration, and rearing frequency between WT and HET mice. (G) Novel object recognition test. Exploration time with old versus novel objects is compared within each genotype, and discrimination indexes are compared between WT and HET mice. (H) Light–dark box test. Time spent in the light compartment and number of light box entries are compared between WT and HET mice. (I) Open field test. Total distance traveled and time spent in the central zone are compared between WT and HET mice. (J) Elevated plus maze test. Duration and distance traveled in the open and closed arms are compared between WT and HET mice. All data are presented as mean ± SEM. Statistical analyses were performed using Student’s t-test. ns, not significant; *p < 0.05, **p < 0.01. WT, wild type; HET, heterozygous; HOM, homozygous.

    Article Snippet: KI mice harboring the Zfp536 p.Gln169Ter-encoding mutation were bred and maintained under specific pathogen-free (SPF) conditions at the Cyagen animal facility.

    Techniques: CRISPR, Mutagenesis, DNA Sequencing, Comparison

    (A) Representative images of E18.5 mouse brains and quantification of brain weight, cortical anterior–dorsal (A–D) length, anterior–posterior (A–P) length, and cortical surface area. Scale bar, 2 mm. (B) Representative DAPI staining of the E18.5 cerebral cortex. Scale bar, 100 μm. (C) Quantification of total cortical thickness based on DAPI staining. (D) Quantification of cortical plate (CP), intermediate zone (IZ), and ventricular/subventricular zone (VZ/SVZ) thickness. (E) Representative immunofluorescence staining of SATB2, CTIP2, and TBR1 in the E18.5 cortex. SATB2 marks upper-layer neurons (layers 2–4), CTIP2 marks layer 5 neurons, and TBR1 marks layer 6 neurons. Scale bar, 100 μm. (F) Quantification of layer thickness across genotypes. (G) Representative high-magnification images of SATB2+, CTIP2+, and TBR1+ neurons within 5000 μm 2 cortical regions. Scale bar, 20 μm. (H) Quantification of neuronal density across cortical layers (SATB2+ in L2–4, CTIP2+ in L5, TBR1+ in L6). All data are presented as mean ± SEM. Statistical analyses were performed using Student’s t-test. ns, not significant; *p < 0.05, **p < 0.01. WT, wild type; HET, heterozygous; HOM, homozygous.

    Journal: American journal of human genetics

    Article Title: Monoallelic loss-of-function variants in ZNF536 are associated with a neurodevelopmental disorder with prominent behavioral features

    doi: 10.1016/j.ajhg.2026.08.013

    Figure Lengend Snippet: (A) Representative images of E18.5 mouse brains and quantification of brain weight, cortical anterior–dorsal (A–D) length, anterior–posterior (A–P) length, and cortical surface area. Scale bar, 2 mm. (B) Representative DAPI staining of the E18.5 cerebral cortex. Scale bar, 100 μm. (C) Quantification of total cortical thickness based on DAPI staining. (D) Quantification of cortical plate (CP), intermediate zone (IZ), and ventricular/subventricular zone (VZ/SVZ) thickness. (E) Representative immunofluorescence staining of SATB2, CTIP2, and TBR1 in the E18.5 cortex. SATB2 marks upper-layer neurons (layers 2–4), CTIP2 marks layer 5 neurons, and TBR1 marks layer 6 neurons. Scale bar, 100 μm. (F) Quantification of layer thickness across genotypes. (G) Representative high-magnification images of SATB2+, CTIP2+, and TBR1+ neurons within 5000 μm 2 cortical regions. Scale bar, 20 μm. (H) Quantification of neuronal density across cortical layers (SATB2+ in L2–4, CTIP2+ in L5, TBR1+ in L6). All data are presented as mean ± SEM. Statistical analyses were performed using Student’s t-test. ns, not significant; *p < 0.05, **p < 0.01. WT, wild type; HET, heterozygous; HOM, homozygous.

    Article Snippet: KI mice harboring the Zfp536 p.Gln169Ter-encoding mutation were bred and maintained under specific pathogen-free (SPF) conditions at the Cyagen animal facility.

    Techniques: Mutagenesis, Staining, Immunofluorescence

    Schematic of constructing engineered Y. lipolytica strain for squalene production. I indicate lipid droplet engineering to modulate triacylglycerols synthesis and increase squalene storage capacity. II indicates modulation of the MVA pathway to promote squalene synthesis flux. III indicates enzyme fusion engineering to promote catalytic efficiency between ERG20 and SQS. IV indicates iterative copy numbering of the ScHMG1 gene. V indicates adaptive evolutionary engineering strategies. Red font represents endogenous genes, and blue font represents heterologous genes. DGA1, Diacylglycerol acyltransferase; LRO1, Phospholipid: diacylglycerol acyltransferase; ERG10, Acetyl-CoA acetyltransferase; ERG13, HMG-CoA synthase; ScHMG1, 3-hydroxy-3-methyl glutaryl coenzyme A reductase of S. cerevisiae origin; ERG20, farnesyl diphosphate synthase; SQS, squalene synthase.

    Journal: Synthetic and Systems Biotechnology

    Article Title: Metabolic engineering and adaptive laboratory evolution enhance squalene production in Yarrowia lipolytica

    doi: 10.1016/j.synbio.2026.01.017

    Figure Lengend Snippet: Schematic of constructing engineered Y. lipolytica strain for squalene production. I indicate lipid droplet engineering to modulate triacylglycerols synthesis and increase squalene storage capacity. II indicates modulation of the MVA pathway to promote squalene synthesis flux. III indicates enzyme fusion engineering to promote catalytic efficiency between ERG20 and SQS. IV indicates iterative copy numbering of the ScHMG1 gene. V indicates adaptive evolutionary engineering strategies. Red font represents endogenous genes, and blue font represents heterologous genes. DGA1, Diacylglycerol acyltransferase; LRO1, Phospholipid: diacylglycerol acyltransferase; ERG10, Acetyl-CoA acetyltransferase; ERG13, HMG-CoA synthase; ScHMG1, 3-hydroxy-3-methyl glutaryl coenzyme A reductase of S. cerevisiae origin; ERG20, farnesyl diphosphate synthase; SQS, squalene synthase.

    Article Snippet: The 3-hydroxy-3-methylglutaryl-CoA reductase encoding gene ScHMG1 (GenBank ID: 854900) from S. cerevisiae was codon-optimized and synthesized (Genewiz, Suzhou, China).

    Techniques:

    Enhancing the expression of ScHMG1 to boost squalene synthesis . (A) Schematic design of overexpressing ScHMG1 at the IntC locus. (B) Effects of enhanced ScHMG1 expression on squalene and lipid synthesis in the engineered Y. lipolytica strain. (C) The pH, biomass, and glucose consumption of the engineered strains after 72 h of fermentation.

    Journal: Synthetic and Systems Biotechnology

    Article Title: Metabolic engineering and adaptive laboratory evolution enhance squalene production in Yarrowia lipolytica

    doi: 10.1016/j.synbio.2026.01.017

    Figure Lengend Snippet: Enhancing the expression of ScHMG1 to boost squalene synthesis . (A) Schematic design of overexpressing ScHMG1 at the IntC locus. (B) Effects of enhanced ScHMG1 expression on squalene and lipid synthesis in the engineered Y. lipolytica strain. (C) The pH, biomass, and glucose consumption of the engineered strains after 72 h of fermentation.

    Article Snippet: The 3-hydroxy-3-methylglutaryl-CoA reductase encoding gene ScHMG1 (GenBank ID: 854900) from S. cerevisiae was codon-optimized and synthesized (Genewiz, Suzhou, China).

    Techniques: Expressing