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      The genome regulatory landscape of Atlantic salmon liver through smoltification

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          Abstract

          The anadromous Atlantic salmon undergo a preparatory physiological transformation before seawater entry, referred to as smoltification. Key molecular developmental processes involved in this life stage transition, such as remodeling of gill functions, are known to be synchronized and modulated by environmental cues like photoperiod. However, little is known about the photoperiod influence and genome regulatory processes driving other canonical aspects of smoltification such as the large-scale changes in lipid metabolism and energy homeostasis in the developing smolt liver. Here we generate transcriptome, DNA methylation, and chromatin accessibility data from salmon livers across smoltification under different photoperiod regimes. We find a systematic reduction of expression levels of genes with a metabolic function, such as lipid metabolism, and increased expression of energy related genes such as oxidative phosphorylation, during smolt development in freshwater. However, in contrast to similar studies of the gill, smolt liver gene expression prior to seawater transfer was not impacted by photoperiodic history. Integrated analyses of gene expression, chromatin accessibility, and transcription factor (TF) binding signatures highlight chromatin remodeling and TF dynamics underlying smolt gene regulatory changes. Differential peak accessibility patterns largely matched differential gene expression patterns during smoltification and we infer that ZNF682, KLFs, and NFY TFs are important in driving a liver metabolic shift from synthesis to break down of organic compounds in freshwater. Overall, chromatin accessibility and TFBS occupancy were highly correlated to changes in gene expression. On the other hand, we identified numerous differential methylation patterns across the genome, but associated genes were not functionally enriched or correlated to observed gene expression changes across smolt development. Taken together, this work highlights the relative importance of chromatin remodeling during smoltification and demonstrates that metabolic remodeling occurs as a preadaptation to life at sea that is not to a large extent driven by photoperiod history.

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          As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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            edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

            Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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              Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position.

              We describe an assay for transposase-accessible chromatin using sequencing (ATAC-seq), based on direct in vitro transposition of sequencing adaptors into native chromatin, as a rapid and sensitive method for integrative epigenomic analysis. ATAC-seq captures open chromatin sites using a simple two-step protocol with 500-50,000 cells and reveals the interplay between genomic locations of open chromatin, DNA-binding proteins, individual nucleosomes and chromatin compaction at nucleotide resolution. We discovered classes of DNA-binding factors that strictly avoided, could tolerate or tended to overlap with nucleosomes. Using ATAC-seq maps of human CD4(+) T cells from a proband obtained on consecutive days, we demonstrated the feasibility of analyzing an individual's epigenome on a timescale compatible with clinical decision-making.
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                Author and article information

                Contributors
                Role: InvestigationRole: MethodologyRole: VisualizationRole: Writing – original draft
                Role: Data curationRole: MethodologyRole: VisualizationRole: Writing – original draft
                Role: InvestigationRole: MethodologyRole: VisualizationRole: Writing – original draft
                Role: Data curationRole: Methodology
                Role: Data curationRole: Methodology
                Role: ConceptualizationRole: Funding acquisition
                Role: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                22 April 2024
                2024
                : 19
                : 4
                : e0302388
                Affiliations
                [1 ] Centre for Integrative Genetics (CIGENE), Department of Animal and Aquacultural Sciences, Faculty of Biosciences, Norwegian University of Life Sciences, Ås, Norway
                [2 ] AquaGen AS, Trondheim, Norway
                [3 ] Michael Sars Centre, University of Bergen, Bergen, Norway
                [4 ] Faculty of Chemistry, Biotechnology and Food Sciences, Norwegian University of Life Sciences, Ås, Norway
                University of Iceland, ICELAND
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-4882-2188
                https://orcid.org/0000-0001-9533-3227
                https://orcid.org/0000-0002-9551-9280
                https://orcid.org/0000-0001-7517-8610
                https://orcid.org/0000-0002-7778-4515
                https://orcid.org/0000-0001-6097-2539
                https://orcid.org/0000-0003-4989-5311
                Article
                PONE-D-23-31449
                10.1371/journal.pone.0302388
                11034671
                38648207
                9bab2784-892d-4b1f-87a6-9d6c548945d8
                © 2024 Harvey et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 28 September 2023
                : 2 April 2024
                Page count
                Figures: 7, Tables: 1, Pages: 25
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100005416, Norges Forskningsråd;
                Award ID: 244164
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100005416, Norges Forskningsråd;
                Award ID: 248792
                Award Recipient :
                This work was supported by the projects GenSysFat (Norges Forskningsrådet 244164 to SS) and DigiSal (Norges Forskningsrådet 248792 to JOV). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The funder website can be found here: https://www.forskningsradet.no/.
                Categories
                Research Article
                Biology and Life Sciences
                Genetics
                Gene Expression
                Biology and life sciences
                Cell biology
                Chromosome biology
                Chromatin
                Chromatin modification
                DNA methylation
                Biology and life sciences
                Genetics
                Epigenetics
                Chromatin
                Chromatin modification
                DNA methylation
                Biology and life sciences
                Genetics
                Gene expression
                Chromatin
                Chromatin modification
                DNA methylation
                Biology and life sciences
                Genetics
                DNA
                DNA modification
                DNA methylation
                Biology and life sciences
                Biochemistry
                Nucleic acids
                DNA
                DNA modification
                DNA methylation
                Biology and life sciences
                Genetics
                Epigenetics
                DNA modification
                DNA methylation
                Biology and life sciences
                Genetics
                Gene expression
                DNA modification
                DNA methylation
                Ecology and Environmental Sciences
                Aquatic Environments
                Marine Environments
                Sea Water
                Earth Sciences
                Marine and Aquatic Sciences
                Aquatic Environments
                Marine Environments
                Sea Water
                Ecology and Environmental Sciences
                Aquatic Environments
                Freshwater Environments
                Fresh Water
                Earth Sciences
                Marine and Aquatic Sciences
                Aquatic Environments
                Freshwater Environments
                Fresh Water
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Fish
                Biology and Life Sciences
                Zoology
                Animals
                Vertebrates
                Fish
                Biology and Life Sciences
                Genetics
                Genomics
                Animal Genomics
                Fish Genomics
                Biology and Life Sciences
                Genetics
                Gene Expression
                Gene Regulation
                Biology and life sciences
                Biochemistry
                Proteins
                DNA-binding proteins
                Transcription Factors
                Biology and Life Sciences
                Genetics
                Gene Expression
                Gene Regulation
                Transcription Factors
                Biology and Life Sciences
                Biochemistry
                Proteins
                Regulatory Proteins
                Transcription Factors
                Custom metadata
                Sequencing data is in the European Nucleotide database for RNA-seq (PRJEB52829), ATAC-seq (PRJEB72206), and RRBS (PRJEB60411), and also available through ArrayExpress (RNA-seq: E-MTAB-11746, ATAC-seq: E-MTAB-13743). Code for running all steps of the analysis and generating results and figures is available on gitlab (gitlab.com/sandve-lab/GSFsmolt).

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