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Chromatin organization in the C. elegans germline is tightly regulated and critical for germ cell differentiation. Although certain germline epigenetic regulatory mechanisms have been identified, how they influence chromatin structure and ultimately gene expression remains unclear, in part because most genomic studies have focused on data collected from intact worms comprising both somatic and germline tissues. We therefore analyzed histone modification and chromatin accessibility data from isolated germ nuclei representing undifferentiated proliferating and meiosis I populations to define chromatin states. We correlated these states with overall transcript abundance, spatiotemporal expression patterns, and the function of small RNA pathways. Because the essential role of the germline is to transmit genetic information and establish gene expression in the early embryo, we compared epigenetic and transcriptomic profiles from undifferentiated germ cells to those of embryos to define the epigenetic changes during this developmental transition. The active histone modification H3K4me3 shows particularly dynamic remodeling as germ cells differentiate into oocytes, which suggests a mechanism for establishing early transcription of essential genes during zygotic genome activation. This analysis highlights the dynamism of the chromatin landscape across developmental transitions and provides a resource for future investigation into epigenetic regulatory mechanisms in germ cells.
Pubmed ID: 38164610
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Original SAMTOOLS package has been split into three separate repositories including Samtools, BCFtools and HTSlib. Samtools for manipulating next generation sequencing data used for reading, writing, editing, indexing,viewing nucleotide alignments in SAM,BAM,CRAM format. BCFtools used for reading, writing BCF2,VCF, gVCF files and calling, filtering, summarising SNP and short indel sequence variants. HTSlib used for reading, writing high throughput sequencing data.
View all literature mentionsSoftware package to comprehensively evaluate different aspects of RNA-seq experiments, such as sequence quality, GC bias, polymerase chain reaction bias, nucleotide composition bias, sequencing depth, strand specificity, coverage uniformity and read distribution over the genome structure. RSeQC takes both SAM and BAM files as input, which can be produced by most RNA-seq mapping tools as well as BED files, which are widely used for gene models.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE, documented on January 19, 2022.
View all literature mentionsCompute differentially bound sites from multiple ChIP-seq experiments using affinity (quantitative) data. Also enables occupancy (overlap) analysis and plotting functions.
View all literature mentionsPython based tools to process, visualize and analyse high-throughput sequencing data, such as ChIP-seq, RNA-seq or MNase-seq. Implemented within Galaxy framework. Used to perform complete bioinformatic workflows ranging from quality controls and normalizations of aligned reads to integrative analyses, including clustering and visualization approaches.
View all literature mentionsSoftware R package for statistical analysis and visualization of functional profiles for genes and gene clusters.
View all literature mentionsSoftware package to arrange multiple heatmaps and support various annotation graphics. Used to visualize associations between different sources of data sets and to reveal potential patterns.
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