Fox Family Protein Jumu Reads 6mA-DNA Codes and Contributes to Zygotic Gene Activation
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ABSTRACT:
PROVIDER: PRJNA355584 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR5092390_1.fastq.gz | Fastqsanger.gz | |||
| SRR5092390_2.fastq.gz | Fastqsanger.gz | |||
| SRR5092400_1.fastq.gz | Fastqsanger.gz | |||
| SRR5092400_2.fastq.gz | Fastqsanger.gz | |||
| SRR5092410_subreads.fastq.gz | Fastqsanger.gz |
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Project description:A long-standing question in the field of embryogenesis is how the zygotic genome is precisely activated by maternal factors, allowing normal early embryonic development. We have previously shown that N6-methyladenine (6mA) DNA modification is highly dynamic in early Drosophila embryos and forms an epigenetic mark. However, little is known about how 6mA-formed epigenetic information is decoded. Here we report that the Fox-family protein Jumu binds 6mA-marked DNA and acts as a maternal factor to regulate the maternal-to-zygotic transition. We find that zelda encoding the pioneer factor Zelda is marked by 6mA. Our genetic assays suggest that Jumu controls the proper zygotic genome activation (ZGA) in early embryos, at least in part, by regulating zelda expression. Thus, our findings not only support that the 6mA-formed epigenetic can be read by specific transcription factors, but also uncover a mechanism by which the Jumu regulates ZGA partially through Zelda in early embryos.
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Project description:Sweat glands play a fundamental role in thermal regulation in man, but the molecular mechanism of their development remains unknown. To initiate analyses, we compared the model of Eda mutant Tabby mice, in which sweat glands were not formed, to wild-type mice. We inferred developmental stages and critical genes based on observations at 7 time points spanning embryonic, postnatal and adult life. In wild-type footpads, sweat gland germs were detected at E17.5. The coiling of secretory portions started at postnatal day 1 (P1), and sweat gland formation was essentially complete by P5. Consistent with a controlled morphological progression, expression profiling revealed stage-specific gene expression changes. Similar to the development of hair follicles the other major skin appendage controlled by EDA sweat gland induction and initial progression was accompanied by Eda-dependent up-regulation of the Shh pathway. During the further development of sweat gland secretory portions, Foxa1 and Foxi1, not at all expressed in hair follicles, were progressively up-regulated in wild-type but not in Tabby footpads. Upon completion of wild-type development, Shh declined to Tabby levels, but Fox family genes remained at elevated levels in mature sweat glands. The results provide a framework for the further analysis of phased downstream regulation of gene action, possibly by a signaling cascade, in response to Eda. This SuperSeries is composed of the following subset Series: GSE14870: Requirement for Shh and Fox family genes at different stages in sweat gland development (E15.5) GSE14871: Requirement for Shh and Fox family genes at different stages in sweat gland development (E16.5) GSE14872: Requirement for Shh and Fox family genes at different stages in sweat gland development (E17.5) GSE14873: Requirement for Shh and Fox family genes at different stages in sweat gland development (P1) GSE14874: Requirement for Shh and Fox family genes at different stages in sweat gland development (P3) GSE14876: Requirement for Shh and Fox family genes at different stages in sweat gland development (P5) GSE14877: Requirement for Shh and Fox family genes at different stages in sweat gland development (Adult) To define target genes of Eda during sweat gland development, we carried out microarray experiments with mouse footpads that from 7 developmental time points including E15.5, E16.5, E17.5, P1, P3, P5 and 8 weeks of wild-type and Tabby mice. Refer to individual Series
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Project description:DNA N6-methyladenine (6mA) is the most widespread type of DNA methylation in prokaryotes. However, the prevalence of 6mA in eukaryotes has recently been challenged due to the limitations of current 6mA detection techniques. Here, we present a chemical-based sequencing method, Nitrite-assisted Amino MEthylation sequencing (NAME-seq), for quantitative, whole-genome mapping of 6mA at single-base resolution. NAME-seq combines nitrite conversion of 6mA to nitrosylated-6mA (6mA-NO) with Klenow Fragment (3'→5' exo-) random priming to induce a 6mA-to-T transversion specifically. We apply NAME-seq to two bacterial species and show that, compared to SMRT-seq, NAME-seq results in a more specific and robust detection of 6mA. NAME-seq can also accurately map 6mA in the C. reinhardtii genome at single-base resolution. Additionally, we show that NAME-seq can be combined with conventional DIP-seq to detect 6mA in the Dam-methylated human genome with high specificity. Therefore, we further perform DIP-NAME-seq to profile 6mA in WT and TASOR KO K562 cell line and revealed that 6mA is enriched at specific motifs (HYYHAG and CACACA) and H3K9me3 regions. In summary, we demonstrate NAME-seq is a specific and sensitive sequencing method for quantitative 6mA mapping at single base resolution across different model organisms.
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Project description:DNA N6-methyladenine (6mA) is the most widespread type of DNA methylation in prokaryotes. However, the prevalence of 6mA in eukaryotes has recently been challenged due to the limitations of current 6mA detection techniques. Here, we present a chemical-based sequencing method, Nitrite-assisted Amino MEthylation sequencing (NAME-seq), for quantitative, whole-genome mapping of 6mA at single-base resolution. NAME-seq combines nitrite conversion of 6mA to nitrosylated-6mA (6mA-NO) with Klenow Fragment (3'→5' exo-) random priming to induce a 6mA-to-T transversion specifically. We apply NAME-seq to two bacterial species and show that, compared to SMRT-seq, NAME-seq results in a more specific and robust detection of 6mA. NAME-seq can also accurately map 6mA in the C. reinhardtii genome at single-base resolution. Additionally, we show that NAME-seq can be combined with conventional DIP-seq to detect 6mA in the Dam-methylated human genome with high specificity. Therefore, we further perform DIP-NAME-seq to profile 6mA in WT and TASOR KO K562 cell line and revealed that 6mA is enriched at specific motifs (HYYHAG and CACACA) and H3K9me3 regions. In summary, we demonstrate NAME-seq is a specific and sensitive sequencing method for quantitative 6mA mapping at single base resolution across different model organisms.
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