Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA343954 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR4290830_1.fastq.gz | Fastqsanger.gz | |||
| SRR4290830_2.fastq.gz | Fastqsanger.gz | |||
| SRR4290840_1.fastq.gz | Fastqsanger.gz | |||
| SRR4290840_2.fastq.gz | Fastqsanger.gz | |||
| SRR4290821_1.fastq.gz | Fastqsanger.gz |
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Project description:Mammalian genomes harbor millions of noncoding elements called enhancers that quantitatively regulate gene expression, but the mechanisms that determine which enhancers regulate which genes are not well understood. Here we describe a high-throughput approach, based on CRISPR interference, RNA FISH, and flow cytometry (CRISPRi-FlowFISH), to perturb enhancers in the genome and apply it to test >3,000 potential regulatory enhancer-gene connections across multiple genomic loci. Seemingly complex patterns of enhancer-gene connections in this dataset can largely be explained by a simple quantitative Activity-by-Contact (ABC) model, in which the effect of a candidate enhancer on a target gene is predicted by the intrinsic activity of the enhancer multiplied by the contact frequency between the enhancer and promoter. This ABC score can identify regulatory enhancer-gene connections and predict their quantitative effects from DNase-Seq, H3K27ac ChIP-seq, and Hi-C measurements. The ABC model can explain even complex regulatory phenomena including the ability of an enhancer to “skip” over one gene to regulate a more distant one. Our approach provides a foundation for dissecting mechanisms of enhancer-gene regulation and predicting enhancer-gene connections across cell types.
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Project description:Mammalian genomes harbor millions of noncoding elements called enhancers that quantitatively regulate gene expression, but the mechanisms that determine which enhancers regulate which genes are not well understood. Here we describe a high-throughput approach, based on CRISPR interference, RNA FISH, and flow cytometry (CRISPRi-FlowFISH), to perturb enhancers in the genome and apply it to test >3,000 potential regulatory enhancer-gene connections across multiple genomic loci. Seemingly complex patterns of enhancer-gene connections in this dataset can largely be explained by a simple quantitative Activity-by-Contact (ABC) model, in which the effect of a candidate enhancer on a target gene is predicted by the intrinsic activity of the enhancer multiplied by the contact frequency between the enhancer and promoter. This ABC score can identify regulatory enhancer-gene connections and predict their quantitative effects from DNase-Seq, H3K27ac ChIP-seq, and Hi-C measurements. The ABC model can explain even complex regulatory phenomena including the ability of an enhancer to “skip” over one gene to regulate a more distant one. Our approach provides a foundation for dissecting mechanisms of enhancer-gene regulation and predicting enhancer-gene connections across cell types.
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Project description:Mammalian genomes harbor millions of noncoding elements called enhancers that quantitatively regulate gene expression, but the mechanisms that determine which enhancers regulate which genes are not well understood. Here we describe a high-throughput approach, based on CRISPR interference, RNA FISH, and flow cytometry (CRISPRi-FlowFISH), to perturb enhancers in the genome and apply it to test >3,000 potential regulatory enhancer-gene connections across multiple genomic loci. Seemingly complex patterns of enhancer-gene connections in this dataset can largely be explained by a simple quantitative Activity-by-Contact (ABC) model, in which the effect of a candidate enhancer on a target gene is predicted by the intrinsic activity of the enhancer multiplied by the contact frequency between the enhancer and promoter. This ABC score can identify regulatory enhancer-gene connections and predict their quantitative effects from DNase-Seq, H3K27ac ChIP-seq, and Hi-C measurements. The ABC model can explain even complex regulatory phenomena including the ability of an enhancer to “skip” over one gene to regulate a more distant one. Our approach provides a foundation for dissecting mechanisms of enhancer-gene regulation and predicting enhancer-gene connections across cell types.
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Project description:Kynureninase is a member of a large family of catalytically diverse but structurally homologous pyridoxal 5'-phosphate (PLP) dependent enzymes known as the aspartate aminotransferase superfamily or alpha-family. The Homo sapiens and other eukaryotic constitutive kynureninases preferentially catalyze the hydrolytic cleavage of 3-hydroxy-l-kynurenine to produce 3-hydroxyanthranilate and l-alanine, while l-kynurenine is the substrate of many prokaryotic inducible kynureninases. The human enzyme was cloned with an N-terminal hexahistidine tag, expressed, and purified from a bacterial expression system using Ni metal ion affinity chromatography. Kinetic characterization of the recombinant enzyme reveals classic Michaelis-Menten behavior, with a Km of 28.3 +/- 1.9 microM and a specific activity of 1.75 micromol min-1 mg-1 for 3-hydroxy-dl-kynurenine. Crystals of recombinant kynureninase that diffracted to 2.0 A were obtained, and the atomic structure of the PLP-bound holoenzyme was determined by molecular replacement using the Pseudomonas fluorescens kynureninase structure (PDB entry 1qz9) as the phasing model. A structural superposition with the P. fluorescens kynureninase revealed that these two structures resemble the "open" and "closed" conformations of aspartate aminotransferase. The comparison illustrates the dynamic nature of these proteins' small domains and reveals a role for Arg-434 similar to its role in other AAT alpha-family members. Docking of 3-hydroxy-l-kynurenine into the human kynureninase active site suggests that Asn-333 and His-102 are involved in substrate binding and molecular discrimination between inducible and constitutive kynureninase substrates.
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Project description:CRISPR Inversion of CTCF Sites Alters Genome Topology and Enhancer/Promoter Function
| PRJNA290779 | ENA
Project description:As the evolution of miRNA genes has been found to be one of the important factors in formation of the modern type of man, we performed a comparative analysis of the evolution of miRNA genes in two archaic hominines, Homo sapiens neanderthalensis and Homo sapiens denisova, and elucidated the expression of their target mRNAs in bain.A comparative analysis of the genomes of primates, including species in the genus Homo, identified a group of miRNA genes having fixed substitutions with important implications for the evolution of Homo sapiens neanderthalensis and Homo sapiens denisova. The mRNAs targeted by miRNAs with mutations specific for Homo sapiens denisova exhibited enhanced expression during postnatal brain development in modern humans. By contrast, the expression of mRNAs targeted by miRNAs bearing variations specific for Homo sapiens neanderthalensis was shown to be enhanced in prenatal brain development.Our results highlight the importance of changes in miRNA gene sequences in the course of Homo sapiens denisova and Homo sapiens neanderthalensis evolution. The genetic alterations of miRNAs regulating the spatiotemporal expression of multiple genes in the prenatal and postnatal brain may contribute to the progressive evolution of brain function, which is consistent with the observations of fine technical and typological properties of tools and decorative items reported from archaeological Denisovan sites. The data also suggest that differential spatial-temporal regulation of gene products promoted by the subspecies-specific mutations in the miRNA genes might have occurred in the brains of Homo sapiens denisova and Homo sapiens neanderthalensis, potentially contributing to the cultural differences between these two archaic hominines.
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Project description:PurposeWe investigated the evidence of recent positive selection in the human phototransduction system at single nucleotide polymorphism (SNP) and gene level.MethodsSNP genotyping data from the International HapMap Project for European, Eastern Asian, and African populations was used to discover differences in haplotype length and allele frequency between these populations. Numeric selection metrics were computed for each SNP and aggregated into gene-level metrics to measure evidence of recent positive selection. The level of recent positive selection in phototransduction genes was evaluated and compared to a set of genes shown previously to be under recent selection, and a set of highly conserved genes as positive and negative controls, respectively.ResultsSix of 20 phototransduction genes evaluated had gene-level selection metrics above the 90th percentile: RGS9, GNB1, RHO, PDE6G, GNAT1, and SLC24A1. The selection signal across these genes was found to be of similar magnitude to the positive control genes and much greater than the negative control genes.ConclusionsThere is evidence for selective pressure in the genes involved in retinal phototransduction, and traces of this selective pressure can be demonstrated using SNP-level and gene-level metrics of allelic variation. We hypothesize that the selective pressure on these genes was related to their role in low light vision and retinal adaptation to ambient light changes. Uncovering the underlying genetics of evolutionary adaptations in phototransduction not only allows greater understanding of vision and visual diseases, but also the development of patient-specific diagnostic and intervention strategies.
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