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plasmids encoding mouse lrh1 #16342  (Addgene inc)


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    Addgene inc plasmids encoding mouse lrh1 #16342
    Plasmids Encoding Mouse Lrh1 #16342, supplied by Addgene inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Average 90 stars, based on 1 article reviews
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    Addgene inc plasmids encoding mouse lrh1 #16342
    Plasmids Encoding Mouse Lrh1 #16342, supplied by Addgene inc, 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/result/plasmids encoding mouse lrh1 #16342/product/Addgene inc
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    Addgene inc mouse lrh1
    The core TFs identified in the liver. (A) H3K27Ac ChIP-seq and DNase-seq profiles at the Hnf4a (left) and the Sec62 (right) loci in mouse liver. Gray bars indicate enhancer regions. (B) Distribution of H3K27Ac ChIP-seq signal intensities across 9891 enhancers in the liver. H3K27Ac occupancy was not evenly distributed across the enhancer regions, with a subset of 460 enhancers containing exceptionally high amounts of H3K27Ac (i.e., super-enhancers) (left). A box plot of H3K27Ac ChIP-seq densities at constituent enhancers within 9431 typical enhancers or 460 super-enhancers (right). (C) Gene ontology (GO) functional categories regarding molecular functions for super-enhancer-associated genes. Genes encoding for the factors controlling transcription were enriched. (D) A protein-protein interaction network of super-enhancer-associated transcription factors (TFs) according to STRING database. <t>LRH1</t> (also known as Nr5a2 ), HNF4α, PPARα, and RXRα make a core network. The TFs were divided into two groups (multiple interactions with quadruple evidences and multiple interactions with double or triple evidences) according to the number of evidences in the above network. The red dotted line designates the cutoff dividing core and second-tier TFs. (E) A network displaying interactions between GO categories. Each node indicates GO term. The thickness of node colour represents the degree of statistical significance for enrichment. Node sizes show the number of gene counts assigned to each GO term. The network was generated by analysis of Cytoscape plugin BiNGO. (F) H3K27Ac ChIP-seq data at the loci of Nr5a2 (LRH1), Hnf4a , Ppara, and Rxra . (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
    Mouse Lrh1, supplied by Addgene inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Danaher Inc rabbit anti mouse lrh1 abcam
    The core TFs identified in the liver. (A) H3K27Ac ChIP-seq and DNase-seq profiles at the Hnf4a (left) and the Sec62 (right) loci in mouse liver. Gray bars indicate enhancer regions. (B) Distribution of H3K27Ac ChIP-seq signal intensities across 9891 enhancers in the liver. H3K27Ac occupancy was not evenly distributed across the enhancer regions, with a subset of 460 enhancers containing exceptionally high amounts of H3K27Ac (i.e., super-enhancers) (left). A box plot of H3K27Ac ChIP-seq densities at constituent enhancers within 9431 typical enhancers or 460 super-enhancers (right). (C) Gene ontology (GO) functional categories regarding molecular functions for super-enhancer-associated genes. Genes encoding for the factors controlling transcription were enriched. (D) A protein-protein interaction network of super-enhancer-associated transcription factors (TFs) according to STRING database. <t>LRH1</t> (also known as Nr5a2 ), HNF4α, PPARα, and RXRα make a core network. The TFs were divided into two groups (multiple interactions with quadruple evidences and multiple interactions with double or triple evidences) according to the number of evidences in the above network. The red dotted line designates the cutoff dividing core and second-tier TFs. (E) A network displaying interactions between GO categories. Each node indicates GO term. The thickness of node colour represents the degree of statistical significance for enrichment. Node sizes show the number of gene counts assigned to each GO term. The network was generated by analysis of Cytoscape plugin BiNGO. (F) H3K27Ac ChIP-seq data at the loci of Nr5a2 (LRH1), Hnf4a , Ppara, and Rxra . (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
    Rabbit Anti Mouse Lrh1 Abcam, supplied by Danaher Inc, 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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    The core TFs identified in the liver. (A) H3K27Ac ChIP-seq and DNase-seq profiles at the Hnf4a (left) and the Sec62 (right) loci in mouse liver. Gray bars indicate enhancer regions. (B) Distribution of H3K27Ac ChIP-seq signal intensities across 9891 enhancers in the liver. H3K27Ac occupancy was not evenly distributed across the enhancer regions, with a subset of 460 enhancers containing exceptionally high amounts of H3K27Ac (i.e., super-enhancers) (left). A box plot of H3K27Ac ChIP-seq densities at constituent enhancers within 9431 typical enhancers or 460 super-enhancers (right). (C) Gene ontology (GO) functional categories regarding molecular functions for super-enhancer-associated genes. Genes encoding for the factors controlling transcription were enriched. (D) A protein-protein interaction network of super-enhancer-associated transcription factors (TFs) according to STRING database. LRH1 (also known as Nr5a2 ), HNF4α, PPARα, and RXRα make a core network. The TFs were divided into two groups (multiple interactions with quadruple evidences and multiple interactions with double or triple evidences) according to the number of evidences in the above network. The red dotted line designates the cutoff dividing core and second-tier TFs. (E) A network displaying interactions between GO categories. Each node indicates GO term. The thickness of node colour represents the degree of statistical significance for enrichment. Node sizes show the number of gene counts assigned to each GO term. The network was generated by analysis of Cytoscape plugin BiNGO. (F) H3K27Ac ChIP-seq data at the loci of Nr5a2 (LRH1), Hnf4a , Ppara, and Rxra . (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

    Journal: EBioMedicine

    Article Title: LRH1-driven transcription factor circuitry for hepatocyte identity: Super-enhancer cistromic analysis

    doi: 10.1016/j.ebiom.2018.12.056

    Figure Lengend Snippet: The core TFs identified in the liver. (A) H3K27Ac ChIP-seq and DNase-seq profiles at the Hnf4a (left) and the Sec62 (right) loci in mouse liver. Gray bars indicate enhancer regions. (B) Distribution of H3K27Ac ChIP-seq signal intensities across 9891 enhancers in the liver. H3K27Ac occupancy was not evenly distributed across the enhancer regions, with a subset of 460 enhancers containing exceptionally high amounts of H3K27Ac (i.e., super-enhancers) (left). A box plot of H3K27Ac ChIP-seq densities at constituent enhancers within 9431 typical enhancers or 460 super-enhancers (right). (C) Gene ontology (GO) functional categories regarding molecular functions for super-enhancer-associated genes. Genes encoding for the factors controlling transcription were enriched. (D) A protein-protein interaction network of super-enhancer-associated transcription factors (TFs) according to STRING database. LRH1 (also known as Nr5a2 ), HNF4α, PPARα, and RXRα make a core network. The TFs were divided into two groups (multiple interactions with quadruple evidences and multiple interactions with double or triple evidences) according to the number of evidences in the above network. The red dotted line designates the cutoff dividing core and second-tier TFs. (E) A network displaying interactions between GO categories. Each node indicates GO term. The thickness of node colour represents the degree of statistical significance for enrichment. Node sizes show the number of gene counts assigned to each GO term. The network was generated by analysis of Cytoscape plugin BiNGO. (F) H3K27Ac ChIP-seq data at the loci of Nr5a2 (LRH1), Hnf4a , Ppara, and Rxra . (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

    Article Snippet: The plasmids encoding mouse LRH1 (#16342, RRID: Addgene_16,342) and mouse PPARα (#22751, RRID: Addgene_22,751) were supplied from Addgene (Cambridge, MA).

    Techniques: ChIP-sequencing, Functional Assay, Generated

    Correlation between identified core TF and each gene transcript levels. (A) Correlation analyses in a large cohort of cirrhosis patients (GSE25097) ( N = 46). Pearson's r correlation coefficients with corresponding P -values for co-variation between each core TF mRNA levels (x axis) and hepatocyte identity gene transcripts (y axis) show robust correlations. (B) Pearson correlation analyses in mice treated as in C. For single and multiple CCl 4 treatment models, group sizes (N) are 12 and 7, respectively. (C) Results of KEGG pathway analysis of the up- or down-regulated genes after hepatocyte-specific deletion of LRH1 (GSE68718). Enriched signaling pathways of each gene cluster were analyzed using DAVID.

    Journal: EBioMedicine

    Article Title: LRH1-driven transcription factor circuitry for hepatocyte identity: Super-enhancer cistromic analysis

    doi: 10.1016/j.ebiom.2018.12.056

    Figure Lengend Snippet: Correlation between identified core TF and each gene transcript levels. (A) Correlation analyses in a large cohort of cirrhosis patients (GSE25097) ( N = 46). Pearson's r correlation coefficients with corresponding P -values for co-variation between each core TF mRNA levels (x axis) and hepatocyte identity gene transcripts (y axis) show robust correlations. (B) Pearson correlation analyses in mice treated as in C. For single and multiple CCl 4 treatment models, group sizes (N) are 12 and 7, respectively. (C) Results of KEGG pathway analysis of the up- or down-regulated genes after hepatocyte-specific deletion of LRH1 (GSE68718). Enriched signaling pathways of each gene cluster were analyzed using DAVID.

    Article Snippet: The plasmids encoding mouse LRH1 (#16342, RRID: Addgene_16,342) and mouse PPARα (#22751, RRID: Addgene_22,751) were supplied from Addgene (Cambridge, MA).

    Techniques: Protein-Protein interactions

    LRH1 protection of the liver from toxicant-induced injury. (A) LRH1 protection of the liver from APAP-induced injury. H&E staining (upper left). At four days after a hydrodynamic injection of the plasmid encoding LRH1 or mock vector (pcDNA3.1), mice were fasted overnight and subjected to a single dose of APAP (300 mg/kg), and the liver tissues were obtained six h afterward. TUNEL staining (upper right). The scale bars represent 100 μm. Serum ALT and AST activities (lower left). Liver weight per body weight ratio (middle). Correlation between serum ALT activities and LRH1 transcript levels in the liver (lower right). (B) LRH1 protection of the liver from CCl 4 -induced injury. H&E staining (upper left). Mice were subjected to a single dose of CCl 4 (0.6 mL/kg) four days after a hydrodynamic injection of the plasmid encoding LRH1 or mock vector (pcDNA3.1), and the liver tissues were obtained two days afterward. TUNEL staining (upper right). TUNEL-stained tissues were separated to non-tissue, normal and apoptotic areas by blue, green and red colors, respectively. Insets showed true-colour images. The scale bars represent 100 μm. Serum ALT and AST activities (lower left). Correlation between serum ALT activities and LRH1 ( Nr5a2 ) mRNA levels in the liver (lower right). (C) Immunoblottings for apoptosis or liver regeneration markers (left). Values were obtained using scanning densitometry (right). Data information: For A, data represent the means ± SEM (Mock+Veh, n = 7; Mock+APAP, n = 8; LRH1 + APAP, n = 13; and non-injected control (Con), n = 5, significantly different as compared to vehicle control, ** P < .01; or APAP-treated control, # P < .05; ## P < .01). For B, data represent the means ± SEM (Mock+Veh, n = 6; Mock+CCl 4 , n = 14; LRH1 + CCl 4 , n = 4; and non-injected control (Con), n = 4, significantly different as compared to vehicle control, ** P < .01; or CCl 4 -treated control: # P < .05; ## P < .01). For C, data represent the means ± SEM (n = 4 each, significantly different as compared to vehicle control, * P < .05; ** P < .01; or CCl 4 -treated control: # P < .05; ## P < .01). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

    Journal: EBioMedicine

    Article Title: LRH1-driven transcription factor circuitry for hepatocyte identity: Super-enhancer cistromic analysis

    doi: 10.1016/j.ebiom.2018.12.056

    Figure Lengend Snippet: LRH1 protection of the liver from toxicant-induced injury. (A) LRH1 protection of the liver from APAP-induced injury. H&E staining (upper left). At four days after a hydrodynamic injection of the plasmid encoding LRH1 or mock vector (pcDNA3.1), mice were fasted overnight and subjected to a single dose of APAP (300 mg/kg), and the liver tissues were obtained six h afterward. TUNEL staining (upper right). The scale bars represent 100 μm. Serum ALT and AST activities (lower left). Liver weight per body weight ratio (middle). Correlation between serum ALT activities and LRH1 transcript levels in the liver (lower right). (B) LRH1 protection of the liver from CCl 4 -induced injury. H&E staining (upper left). Mice were subjected to a single dose of CCl 4 (0.6 mL/kg) four days after a hydrodynamic injection of the plasmid encoding LRH1 or mock vector (pcDNA3.1), and the liver tissues were obtained two days afterward. TUNEL staining (upper right). TUNEL-stained tissues were separated to non-tissue, normal and apoptotic areas by blue, green and red colors, respectively. Insets showed true-colour images. The scale bars represent 100 μm. Serum ALT and AST activities (lower left). Correlation between serum ALT activities and LRH1 ( Nr5a2 ) mRNA levels in the liver (lower right). (C) Immunoblottings for apoptosis or liver regeneration markers (left). Values were obtained using scanning densitometry (right). Data information: For A, data represent the means ± SEM (Mock+Veh, n = 7; Mock+APAP, n = 8; LRH1 + APAP, n = 13; and non-injected control (Con), n = 5, significantly different as compared to vehicle control, ** P < .01; or APAP-treated control, # P < .05; ## P < .01). For B, data represent the means ± SEM (Mock+Veh, n = 6; Mock+CCl 4 , n = 14; LRH1 + CCl 4 , n = 4; and non-injected control (Con), n = 4, significantly different as compared to vehicle control, ** P < .01; or CCl 4 -treated control: # P < .05; ## P < .01). For C, data represent the means ± SEM (n = 4 each, significantly different as compared to vehicle control, * P < .05; ** P < .01; or CCl 4 -treated control: # P < .05; ## P < .01). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

    Article Snippet: The plasmids encoding mouse LRH1 (#16342, RRID: Addgene_16,342) and mouse PPARα (#22751, RRID: Addgene_22,751) were supplied from Addgene (Cambridge, MA).

    Techniques: Staining, Injection, Plasmid Preparation, TUNEL Assay, Control

    LRH1-dependent recovery of hepatocyte identity genes. (A) Principal component analysis of RNA-seq data. RNA-seq data was generated using liver of mice treated with APAP alone or APAP+LRH1 overexpression vector as in A. RNA-seq data are deposited in the GEO under accession number GSE104302. (B) Pie graphs showing the enhancer composition. Genes having P -values lower than 0.05 between APAP and LRH1 + APAP groups were defined as LRH1-dependent genes. (C) Heatmaps and hierarchical correlation analyses of differentially expressed genes (DEGs). DEGs were selected as the genes with independent t -test ( P -values < .05 with a fold-change of >1.5). The DEGs were hierarchically clustered and presented as heatmaps according to the row Z score. Super-enhancer- or typical enhancer (SE or TE)-associated DEGs represent significantly altered genes in the APAP group as compared to the vehicle group among the SE-associated or TE-associated genes. Not assigned DEGs are DEGs which are assigned neither to SE nor TE. Heatmaps of total DEGs (a), SE-associated DEGs (b), TE-associated DEGs (c), and not assigned DEGs (d) are presented in left. The proportions of the gene clusters depicted in the heatmaps (left) were shown as a graph (right). (D) Results of KEGG pathway analysis of the clustered DEGs. A schematic description of the gene clusters (a). Enriched signaling pathways of each gene cluster were analyzed using DAVID (b-d).

    Journal: EBioMedicine

    Article Title: LRH1-driven transcription factor circuitry for hepatocyte identity: Super-enhancer cistromic analysis

    doi: 10.1016/j.ebiom.2018.12.056

    Figure Lengend Snippet: LRH1-dependent recovery of hepatocyte identity genes. (A) Principal component analysis of RNA-seq data. RNA-seq data was generated using liver of mice treated with APAP alone or APAP+LRH1 overexpression vector as in A. RNA-seq data are deposited in the GEO under accession number GSE104302. (B) Pie graphs showing the enhancer composition. Genes having P -values lower than 0.05 between APAP and LRH1 + APAP groups were defined as LRH1-dependent genes. (C) Heatmaps and hierarchical correlation analyses of differentially expressed genes (DEGs). DEGs were selected as the genes with independent t -test ( P -values < .05 with a fold-change of >1.5). The DEGs were hierarchically clustered and presented as heatmaps according to the row Z score. Super-enhancer- or typical enhancer (SE or TE)-associated DEGs represent significantly altered genes in the APAP group as compared to the vehicle group among the SE-associated or TE-associated genes. Not assigned DEGs are DEGs which are assigned neither to SE nor TE. Heatmaps of total DEGs (a), SE-associated DEGs (b), TE-associated DEGs (c), and not assigned DEGs (d) are presented in left. The proportions of the gene clusters depicted in the heatmaps (left) were shown as a graph (right). (D) Results of KEGG pathway analysis of the clustered DEGs. A schematic description of the gene clusters (a). Enriched signaling pathways of each gene cluster were analyzed using DAVID (b-d).

    Article Snippet: The plasmids encoding mouse LRH1 (#16342, RRID: Addgene_16,342) and mouse PPARα (#22751, RRID: Addgene_22,751) were supplied from Addgene (Cambridge, MA).

    Techniques: RNA Sequencing, Generated, Over Expression, Plasmid Preparation, Protein-Protein interactions

    LRH1 as a driver gene for the core TF circuitry. (A) Hepatic super-enhancer-associated TF network with gene expression changes in mice treated with APAP alone or APAP+LRH1 overexpression vector. The node colors reflect log2 gene expression ratio in mice treated with APAP alone (left) or APAP+LRH1 overexpression (right) as compared to vehicle treatment (red, upregulation; blue, downregulation). Log2 fold changes of the core TFs are presented as an inset table. (B) The core TF mRNA levels from the APAP model. (C) The core TF mRNA levels from the CCl 4 model. (D) The effect of each core TF overexpression on other core TFs. qRT-PCR assays were done on AML12 cells transfected with pcDNA3.1, LRH1, HNF4α, PPARα or RXRα for 48 h. The first lane of each graph is transfection reagent-treated control. Heatmap presents averages of core TF mRNA levels. O/E, overexpression. (E) Super-enhancer (SE)-luciferase reporter assays. Luciferase assays were done on AML12 cells co-transfected with each SE-luciferase reporter, and pcDNA3.1, LRH1, HNF4α, PPARα or RXRα overexpression vector for 24 h. Relative luciferase activities represent arbitrary units of luminescence normalized to the pcDNA3.1 group. The schematic illustrations showing each SE-luciferase construct are presented in the upper panel. The ChIP-seq signal peaks in the scheme are also shown in F. Red bars indicate the peaks excised for cloning of each SE-luciferase reporter construct. O/E, overexpression. (F) A proposed scheme showing auto-regulatory loops for the core TFs. In healthy liver, the core TFs form an interconnected feedback loop for gene expression. Upon injury, the signal circuitry loses its integrity with decrease of hepatocyte identity. LRH1 serves a driver for reconstitution of the signal circuitry. Data information: For B, data represent the means ± SEM (Mock+Veh, n = 7; Mock+APAP, n = 8; and LRH1 + APAP, n = 13, significantly different as compared to vehicle control, ** P < .01; or APAP-treated control, # P < .05; ## P < .01). For C, data represent the means ± SEM (Mock+Veh, n = 6; Mock+CCl 4 , n = 14; and LRH1 + CCl 4 , n = 4; significantly different as compared to vehicle control, * P < .05; ** P < .01; or CCl 4 -treated control: # P < .05; ## P < .01). For D and E, data represent the means ± SEM ( n = 3 each, significantly different as compared to pcDNA3.1 group, * P < .05; ** P < .01). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

    Journal: EBioMedicine

    Article Title: LRH1-driven transcription factor circuitry for hepatocyte identity: Super-enhancer cistromic analysis

    doi: 10.1016/j.ebiom.2018.12.056

    Figure Lengend Snippet: LRH1 as a driver gene for the core TF circuitry. (A) Hepatic super-enhancer-associated TF network with gene expression changes in mice treated with APAP alone or APAP+LRH1 overexpression vector. The node colors reflect log2 gene expression ratio in mice treated with APAP alone (left) or APAP+LRH1 overexpression (right) as compared to vehicle treatment (red, upregulation; blue, downregulation). Log2 fold changes of the core TFs are presented as an inset table. (B) The core TF mRNA levels from the APAP model. (C) The core TF mRNA levels from the CCl 4 model. (D) The effect of each core TF overexpression on other core TFs. qRT-PCR assays were done on AML12 cells transfected with pcDNA3.1, LRH1, HNF4α, PPARα or RXRα for 48 h. The first lane of each graph is transfection reagent-treated control. Heatmap presents averages of core TF mRNA levels. O/E, overexpression. (E) Super-enhancer (SE)-luciferase reporter assays. Luciferase assays were done on AML12 cells co-transfected with each SE-luciferase reporter, and pcDNA3.1, LRH1, HNF4α, PPARα or RXRα overexpression vector for 24 h. Relative luciferase activities represent arbitrary units of luminescence normalized to the pcDNA3.1 group. The schematic illustrations showing each SE-luciferase construct are presented in the upper panel. The ChIP-seq signal peaks in the scheme are also shown in F. Red bars indicate the peaks excised for cloning of each SE-luciferase reporter construct. O/E, overexpression. (F) A proposed scheme showing auto-regulatory loops for the core TFs. In healthy liver, the core TFs form an interconnected feedback loop for gene expression. Upon injury, the signal circuitry loses its integrity with decrease of hepatocyte identity. LRH1 serves a driver for reconstitution of the signal circuitry. Data information: For B, data represent the means ± SEM (Mock+Veh, n = 7; Mock+APAP, n = 8; and LRH1 + APAP, n = 13, significantly different as compared to vehicle control, ** P < .01; or APAP-treated control, # P < .05; ## P < .01). For C, data represent the means ± SEM (Mock+Veh, n = 6; Mock+CCl 4 , n = 14; and LRH1 + CCl 4 , n = 4; significantly different as compared to vehicle control, * P < .05; ** P < .01; or CCl 4 -treated control: # P < .05; ## P < .01). For D and E, data represent the means ± SEM ( n = 3 each, significantly different as compared to pcDNA3.1 group, * P < .05; ** P < .01). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

    Article Snippet: The plasmids encoding mouse LRH1 (#16342, RRID: Addgene_16,342) and mouse PPARα (#22751, RRID: Addgene_22,751) were supplied from Addgene (Cambridge, MA).

    Techniques: Gene Expression, Over Expression, Plasmid Preparation, Quantitative RT-PCR, Transfection, Control, Luciferase, Construct, ChIP-sequencing, Cloning