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      Nuclear lipid droplets and nuclear damage in Caenorhabditis elegans

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          Abstract

          Fat stored in the form of lipid droplets has long been considered a defining characteristic of cytoplasm. However, recent studies have shown that nuclear lipid droplets occur in multiple cells and tissues, including in human patients with fatty liver disease. The function(s) of stored fat in the nucleus has not been determined, and it is possible that nuclear fat is beneficial in some situations. Conversely, nuclear lipid droplets might instead be deleterious by disrupting nuclear organization or triggering aggregation of hydrophobic proteins. We show here that nuclear lipid droplets occur normally in C. elegans intestinal cells and germ cells, but appear to be associated with damage only in the intestine. Lipid droplets in intestinal nuclei can be associated with novel bundles of microfilaments (nuclear actin) and membrane tubules that might have roles in damage repair. To increase the normal, low frequency of nuclear lipid droplets in wild-type animals, we used a forward genetic screen to isolate mutants with abnormally large or abundant nuclear lipid droplets. Genetic analysis and cloning of three such mutants showed that the genes encode the lipid regulator SEIP-1/seipin, the inner nuclear membrane protein NEMP-1/Nemp1/TMEM194A, and a component of COPI vesicles called COPA-1/α-COP. We present several lines of evidence that the nuclear lipid droplet phenotype of copa-1 mutants results from a defect in retrieving mislocalized membrane proteins that normally reside in the endoplasmic reticulum. The seip-1 mutant causes most germ cells to have nuclear lipid droplets, the largest of which occupy more than a third of the nuclear volume. Nevertheless, the nuclear lipid droplets do not trigger apoptosis, and the germ cells differentiate into gametes that produce viable, healthy progeny. Thus, our results suggest that nuclear lipid droplets are detrimental to intestinal nuclei, but have no obvious deleterious effect on germ nuclei.

          Author summary

          Several human disorders such as obesity are associated with abnormal fat storage. Cells normally store fat in cytoplasmic organelles called lipid droplets. However, recent studies have shown that fat can also form inside of the cell nucleus, and the effects of nuclear fat are not known. Here we use the cell biology and genetics of the model organism C. elegans to study the causes and consequences of nuclear fat. We show that intestinal cells can contain nuclear fat, particularly during high-low-high changes in cytoplasmic fat that involve de novo fat synthesis. Nuclear fat is associated with multiple changes in intestinal nuclei that appear to represent damage and repair. Germ nuclei that normally differentiate into oocytes can also contain nuclear fat. In germ cells, however, even high levels of nuclear fat appear to cause little or no damage. Our results suggest that intestinal nuclei and germ cell nuclei might have different responses to nuclear fat in part because they differ in chromosomal organization at the nuclear envelope.

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          Most cited references130

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          The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

          Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
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            A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3.

            We describe a new computer program, SnpEff, for rapidly categorizing the effects of variants in genome sequences. Once a genome is sequenced, SnpEff annotates variants based on their genomic locations and predicts coding effects. Annotated genomic locations include intronic, untranslated region, upstream, downstream, splice site, or intergenic regions. Coding effects such as synonymous or non-synonymous amino acid replacement, start codon gains or losses, stop codon gains or losses, or frame shifts can be predicted. Here the use of SnpEff is illustrated by annotating ~356,660 candidate SNPs in ~117 Mb unique sequences, representing a substitution rate of ~1/305 nucleotides, between the Drosophila melanogaster w(1118); iso-2; iso-3 strain and the reference y(1); cn(1) bw(1) sp(1) strain. We show that ~15,842 SNPs are synonymous and ~4,467 SNPs are non-synonymous (N/S ~0.28). The remaining SNPs are in other categories, such as stop codon gains (38 SNPs), stop codon losses (8 SNPs), and start codon gains (297 SNPs) in the 5'UTR. We found, as expected, that the SNP frequency is proportional to the recombination frequency (i.e., highest in the middle of chromosome arms). We also found that start-gain or stop-lost SNPs in Drosophila melanogaster often result in additions of N-terminal or C-terminal amino acids that are conserved in other Drosophila species. It appears that the 5' and 3' UTRs are reservoirs for genetic variations that changes the termini of proteins during evolution of the Drosophila genus. As genome sequencing is becoming inexpensive and routine, SnpEff enables rapid analyses of whole-genome sequencing data to be performed by an individual laboratory.
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              THE GENETICS OF CAENORHABDITIS ELEGANS

              Methods are described for the isolation, complementation and mapping of mutants of Caenorhabditis elegans, a small free-living nematode worm. About 300 EMS-induced mutants affecting behavior and morphology have been characterized and about one hundred genes have been defined. Mutations in 77 of these alter the movement of the animal. Estimates of the induced mutation frequency of both the visible mutants and X chromosome lethals suggests that, just as in Drosophila, the genetic units in C.elegans are large.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Genet
                PLoS Genet
                plos
                PLoS Genetics
                Public Library of Science (San Francisco, CA USA )
                1553-7390
                1553-7404
                16 June 2021
                June 2021
                : 17
                : 6
                : e1009602
                Affiliations
                [1 ] Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
                [2 ] Molecular and Cellular Biology Program, University of Washington, Seattle, Washington, United States of America
                [3 ] Department of Biology, University of Washington, Seattle, Washington, United States of America
                Washington State University, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-2816-2250
                https://orcid.org/0000-0002-3264-5028
                https://orcid.org/0000-0002-4087-7419
                Article
                PGENETICS-D-21-00328
                10.1371/journal.pgen.1009602
                8208577
                34133414
                47254b1a-c830-4629-843b-df0241ab1174
                © 2021 Mosquera 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
                : 8 March 2021
                : 14 May 2021
                Page count
                Figures: 16, Tables: 3, Pages: 60
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: NIH RO1GM098583
                Award Recipient :
                This work was supported by an NIH RO1GM098583 grant to J.R.P. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Anatomy
                Digestive System
                Gastrointestinal Tract
                Medicine and Health Sciences
                Anatomy
                Digestive System
                Gastrointestinal Tract
                Biology and Life Sciences
                Biochemistry
                Proteins
                Cytoskeletal Proteins
                Lamins
                Biology and Life Sciences
                Cell Biology
                Cellular Types
                Animal Cells
                Germ Cells
                Biology and Life Sciences
                Anatomy
                Reproductive System
                Genital Anatomy
                Gonads
                Medicine and Health Sciences
                Anatomy
                Reproductive System
                Genital Anatomy
                Gonads
                Biology and Life Sciences
                Biochemistry
                Lipids
                Biology and Life Sciences
                Cell Biology
                Chromosome Biology
                Chromatin
                Heterochromatin
                Biology and Life Sciences
                Genetics
                Epigenetics
                Chromatin
                Heterochromatin
                Biology and Life Sciences
                Genetics
                Gene Expression
                Chromatin
                Heterochromatin
                Biology and Life Sciences
                Cell Biology
                Cellular Structures and Organelles
                Vesicles
                Biology and Life Sciences
                Biochemistry
                Lipids
                Fats
                Custom metadata
                All the relevant data are within the manuscript and its Supporting Information files.

                Genetics
                Genetics

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