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Fluo-Cast-Bright: A Deep Learning Pipeline for the Non-Invasive Prediction of Chromatin Structure and Developmental Potential in Live Oocytes

ABSTRACT: Fluo-Cast-Bright: A Deep Learning Pipeline for the Non-Invasive Prediction of Chromatin Structure and Developmental Potential in Live Oocytes

PROVIDER: PRJNA1108350 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR28920157_1.fastq.gz	Fastqsanger.gz
	SRR28920157_2.fastq.gz	Fastqsanger.gz
	SRR28920158_1.fastq.gz	Fastqsanger.gz
	SRR28920158_2.fastq.gz	Fastqsanger.gz
	SRR28920159_1.fastq.gz	Fastqsanger.gz

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Fluo-Cast-Bright: A Deep Learning Pipeline for the Non-Invasive Prediction of Chromatin Structure and Developmental Potential in Live Oocytes

Project description:In mammalian oocytes, large-scale chromatin organization regulates transcription, nuclear architecture, and maintenance of chromosome stability in preparation for meiosis onset. Pre-ovulatory oocytes with distinct chromatin configuration exhibit profound differences in metabolic and transcriptional profiles that ultimately determine meiotic competence and developmental potential. Here, we developed a deep learning pipeline for the non-invasive prediction of chromatin structure and developmental potential in live mouse oocytes. Our Fluorescence prediction and Classification on Bright-field (Fluo-Cast-Bright) pipeline achieved 91.3% accuracy in the classification of chromatin state in fixed oocytes and 85.7% accuracy in live oocytes. Importantly, transcriptome analysis following non-invasive selection revealed that meiotically competent oocytes exhibit a higher expression of transcripts associated with RNA and protein nuclear export, maternal mRNA deadenylation, histone modifications, chromatin remodeling and signaling pathways regulating microtubule dynamics during the metaphase-I to metaphase-II transition. Our pipeline provides fast and non-invasive selection of meiotically competent oocytes for downstream research and clinical applications.

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Fluo-Cast-Bright: a deep learning pipeline for the non-invasive prediction of chromatin structure and developmental potential in live oocytes.

Project description:In mammalian oocytes, large-scale chromatin organization regulates transcription, nuclear architecture, and maintenance of chromosome stability in preparation for meiosis onset. Pre-ovulatory oocytes with distinct chromatin configurations exhibit profound differences in metabolic and transcriptional profiles that ultimately determine meiotic competence and developmental potential. Here, we developed a deep learning pipeline for the non-invasive prediction of chromatin structure and developmental potential in live mouse oocytes. Our Fluorescence prediction and Classification on Bright-field (Fluo-Cast-Bright) pipeline achieved 91.3% accuracy in the classification of chromatin state in fixed oocytes and 85.7% accuracy in live oocytes. Importantly, transcriptome analysis following non-invasive selection revealed that meiotically competent oocytes exhibit a higher expression of transcripts associated with RNA and protein nuclear export, maternal mRNA deadenylation, histone modifications, chromatin remodeling and signaling pathways regulating microtubule dynamics during the metaphase-I to metaphase-II transition. Fluo-Cast-Bright provides fast and non-invasive selection of meiotically competent oocytes for downstream research and clinical applications.

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T-CAST: An optimized CAST-Seq pipeline for TALEN reveals superior safety and efficacy of obligate-heterodimeric scaffolds

Project description:Transcription activator-like effector nucleases (TALENs) are programmable nucleases that have entered the clinical stage. Each subunit of the dimer consists of a DNA-binding domain composed of an array of TALE repeats fused to the catalytically active portion of the FokI endonuclease. Upon DNA-binding of both TALEN arms in close proximity, the FokI domains dimerize and induce a staggered-end DNA double strand break. In this present study, we describe the implementation and validation of TALEN-specific CAST-Seq (T-CAST), a pipeline based on CAST-Seq that identifies TALEN-mediated off-target effects, nominates off-target sites with high fidelity, and predicts the TALEN pairing conformation leading to off-target cleavage. We validated T-CAST by assessing off-target effects of two promiscuous TALENs designed to target the CCR5 and TRAC loci. Expression of these TALENs caused high levels of translocations between the target sites and various off-target sites in primary T cells. Introduction of amino acid substitutions to the FokI domains, which render TALENs obligate-heterodimeric (OH-TALEN), mitigated the aforementioned off-target effects without loss of on-target activity. Our findings highlight the significance of T-CAST to assess off-target effects of TALEN designer nucleases and to evaluate mitigation strategies, and advocate the use of obligate-heterodimeric TALEN scaffolds for therapeutic genome editing.

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