Nucleoplasm

One of the most prominent features of a eukaryotic cell is the nucleus, which is a complex and highly dynamic organelle. The nucleus was the first cell compartment to be discovered in 1833 by Robert Brown and is the largest organelle in the human cell. Inside the nuclear membrane is the nucleoplasm, which main function is to store DNA and enanble DNA-dependent processes such as transcription to occur in a controlled environment. The nucleoplasm contains several non-membrane bound substructures, such as nuclear bodies and nuclear speckles. Example images of proteins that localized to the nucleus can be seen in Figure 1.

In the subcellular section, 6773 genes (34% of all human protein-coding genes) have been shown to encode proteins that localize to the nucleoplasm and its sub-compartments (Figure 2). A Gene Ontology (GO)-based functional enrichment analysis of genes encoding nuclear shows an enrichment of gene associated with biological processes related to DNA repair, transcription, RNA processing, chromatin modification, regulation of gene expression, differentiation and development. Approximately 67% (n=4556) of the proteins that localize to the nucleoplasm can also be detected in additional cellular compartments, with 8% (n=563) only being detected in the other major nuclear compartments; nucleoli and nuclear membrane. The most common additional localizations except for the nucleoli are the cytosol and vesicles.


PDS5A - A-431

TP53BP1 - A-431

SRRM2 - A-431

Figure 1. Examples of proteins localized to the nucleoplasm and its substructures. PDS5A is thought to keep the sister chromatids in place during mitosis and also play a role in DNA repair. PDS5A has been localized to the nucleoplasm (detected in A-431 cells). TP53BP1 is involved in DNA damage response and is localized to nuclear bodies (detected in A-431 cells). SRRM2 is known to be involved in pre-mRNA splicing and is localized to nuclear speckles (detected in A-431 cells).

  • 34% (6773 proteins) of all human proteins have been experimentally detected in the nucleoplasm by the Human Protein Atlas.
  • 2844 proteins in the nucleoplasm are supported by experimental evidence and out of these 766 proteins are enhanced by the Human Protein Atlas.
  • 4556 proteins in the nucleoplasm have multiple locations.
  • 1338 proteins in the nucleoplasm show single cell variation.

  • Proteins localizing to the nucleoplasm are mainly involved in RNA processing, transcription, chromatin modification and DNA repair, differentiation and development.

Figure 2. 34% of all human protein-coding genes encode proteins that have been shown to localize to the nucleoplasm. Each bar is clickable and gives a search result of proteins that belong to the selected category.

The structure of the nucleoplasm

Substructures

  • Nucleoplasm: 6166
  • Nuclear speckles: 493
  • Nuclear bodies: 588
  • Kinetochore: 6
  • Mitotic chromosome: 74

The nucleus of human cells varies in size depending on cell type and cell cycle stage, but is usually around 10 μm in diameter. The nucleus mainly contains DNA and proteins interacting with DNA in a complex called chromatin. At the first level of chromatin organization, the DNA is wrapped around proteins known as histones, which provides both a way of compacting the long DNA molecules as well as a mechanism to regulate DNA-dependent cellular processes. The chromatin is then further compacted and organized in intricate ways, while yet remaining dynamic. The most densely condensed chromatin, known as heterochromatin, is usually organized in the nuclear periphery while the less packed euchromatin is dispersed throughout the whole nucleus (Spector DL. (1993)).

Many of the nuclear proteins are localized to the entire nucleoplasm where they give rise to a smooth or punctate staining pattern. However, the nucleoplasm is far from homogeneous. It contains several non-membrane bound sub compartments, collectively called nuclear bodies, acting as self-organizing clusters for different nuclear activities. Except for the nucleolus, the most prominent subcompartments are nuclear speckles and nuclear bodies (Lamond AI et al. (1998)). Nuclear speckles, in the form of splicing speckles and paraspeckles, are formed in interchromatin granule clusters (IGCs) and contain pre-messenger RNA (pre-mRNA) splicing factors such as small nuclear ribonucleoprotein particles (snRNPs) (SWIFT H. (1959); Lamond AI et al. (2003)). These granules are connected by fine fibrils, forming clusters that can be seen directly by electron microscopy (Thiry M. (1995)). The appearance of nuclear speckles varies between cell lines, but they all share an irregular mottled pattern, which may change in both size and shape over time. Nuclear bodies vary in size, number and location dependent on the type of nuclear body and the cell line. Cajal bodies (CBs) and gemini of Cajal bodies (gems) are usually found in close proximity to each other, but CBs mainly contain the protein Coilin and snRNPs, while gems mainly contain the snRNP-interacting complex survival of motor neuron (SMN) (Sleeman JE et al. (1999); Darzacq X et al. (2002); Jády BE et al. (2003); Liu Q et al. (1996); Lefebvre S et al. (1995); Fischer U et al. (1997)). PML bodies are characterized by the presence of the PML protein, which acts as a hub for assembly of a macromolecular complex that is highly dynamic and can contain a variety of different proteins (Lallemand-Breitenbach V et al. (2010)). As CBs, gems, PML bodies and other nuclear bodies are all seen as distinct spots scattered throughout the nucleoplasm, they are difficult to differentiate without the use of co-localizing protein markers.

In the subcellular section, there are also annotations of proteins that localize to kinetochores or the perichromosomal layer during mitosis. Kinetochores are large protein structures that assemble on centromeric chromatin and act as an attachment site for microtubules of the mitotic spindle. While the inner kinetochore persists through the cell cycle, the outer kinetochore is assembled only during cell division. Components of the kinetochore include structural proteins, motor proteins and regulatory checkpoint proteins. Upon entry into mitosis, there are also certain proteins and RNP complexes that localize specifically to the surface of the condensed mitotic chromosomes, known as the perichromosomal layer (Booth DG et al. (2017); Stenström L et al. (2020); Ljungberg O et al. (1983)). Many of these proteins, including MKI67 that is considered a major organizer of this region, also localize to nucleoli, and in particular the rim of nucleoli, in interphase. A selection of proteins localized to the nucleus, nuclear speckles and nuclear bodies suitable as markers can be found in Table 1. Highly expressed nuclear proteins are summarized in Table 2. Images showing the different nuclear substructures can be seen in Figure 3.

Table 1. Selection of proteins suitable as markers for the nucleus or its substructures.

Gene Description Substructure
TAF15 TATA-box binding protein associated factor 15 Nucleoplasm
SMARCAD1 SWI/SNF-related, matrix-associated actin-dependent regulator of chromatin, subfamily a, containing DEAD/H box 1 Nucleoplasm
SRRM2 Serine/arginine repetitive matrix 2 Nuclear speckles
RBM25 RNA binding motif protein 25 Nuclear speckles
PML PML nuclear body scaffold Nuclear bodies
SMN2 Survival of motor neuron 2, centromeric Cytosol
Nuclear bodies
MKI67 Marker of proliferation Ki-67 Mitotic chromosome
Nuclear bodies
Nucleoli rim
Nucleoplasm
RSL1D1 Ribosomal L1 domain containing 1 Mitotic chromosome
Nucleoli rim
CENPC Centromere protein C Kinetochore
Midbody
Nuclear bodies
Nucleoplasm

Table 2. Highly expressed single localizing nuclear proteins across different cell lines.

Gene Description Average nTPM
RPS19 Ribosomal protein S19 3499
RAN RAN, member RAS oncogene family 1457
HNRNPA1 Heterogeneous nuclear ribonucleoprotein A1 1146
H2AZ1 H2A.Z variant histone 1 1021
HNRNPC Heterogeneous nuclear ribonucleoprotein C 928
H3-3B H3.3 histone B 844
H3-3A H3.3 histone A 797
HMGB1 High mobility group box 1 793
HNRNPK Heterogeneous nuclear ribonucleoprotein K 709
ATF4 Activating transcription factor 4 504


LSM2 - SK-MEL-30

CTBP1 - A-431

NOSIP - U2OS


RBM25 - HaCaT

NPAT - CACO-2

DAXX - A-431

Figure 3. Examples showing the different nuclear substructures and staining patterns. LSM2 is a protein that might be involved in pre-mRNA splicing and shows a nucleoplasmic punctate staining pattern (detected in SK-MEL-30 cells). CTBP1 is a co-repressor targeting various transcription factors and shows a smooth nucleoplasmic staining pattern (detected in A-431 cells). NOSIP is an E3 ubiquitin-protein regulating several catalytic processes and is localized to the nucleus (detected in U2OS cells). RBM25 is involved in pre-mRNA splicing activities and has been shown to localize to nuclear speckles (detected in HaCaT cells). NPAT is a known Cajal body protein and is required for proper G1/S transition. In the Subcellular Section, NPAT localizes to nuclear bodies (detected in CACO-2 cells). DAXX is a transcription co-repressor involved in a number of different nuclear activities and is known to localize to several nuclear substructures such as PML bodies and centromeres. In the Subcellular Section, DAXX localizes to nuclear bodies (detected in A-431 cells).


Figure 4. 3D-view of the nucleoplasm in U2OS, visualized by immunofluorescent staining of HNRNPC. The morphology of nuclei in human induced stem cells can be seen in the Allen Cell Explorer.

The function of the nucleoplasm

The main function of the nucleus is to store and condense the majority of the human genome, but a major function for proteins that localize to the nucleoplasm is also to participate in and regulate DNA-dependent functions and cellular processes, such as transcription, RNA splicing, RNP assembly, DNA repair, and replication.

Despite the fact that the nuclear substructures are not membrane bound, highly specific tasks are carried out in these regions. Splicing speckles are enriched for pre-mRNA splicing factors (Lamond AI et al. (2003); Melcák I et al. (2000)), and are thought to act as a regulatory site for transcription and pre-mRNA processing, with transcription occurring in close proximity (Spector DL et al. (1991); Misteli T et al. (1997); Cmarko D et al. (1999)). Paraspeckles can sequester nuclear proteins and RNA, thus providing a means for regulation of gene expression. Both splicing speckles and paraspeckles have highly dynamic compositions. CBs probably function as a modification site of snRNPs into fully functional splicing factors before they enter other parts of the cell (Sleeman JE et al. (1999); Darzacq X et al. (2002); Jády BE et al. (2003)). The closely related gems play an important role in the synthesis of cytoplasmic snRNP (Liu Q et al. (1996); Lefebvre S et al. (1995); Fischer U et al. (1997)). As previously mentioned, gems contain the SMN1 protein which has been found to be responsible for the onset of spinal muscular atrophy (SMA). SMA is one of the most lethal autosomal recessive disorders and genetic defects in the SMN gene could cause progressive muscular and mobility impairments (Lefebvre S et al. (1995)). PML bodies have been found to be highly diverse and have been suggested to perform an ever-growing number of tasks in the cell, ranging from apoptosis regulation to anti-viral protection, and much about the function remains to be unraveled (Lallemand-Breitenbach V et al. (2010)).

Kinetochores have an essential role in ensuring proper segregation of sister chromatids in mitosis and meiosis. Apart from serving as a physical attachment point for spindle microtubules, kinetochores contain a number of motor proteins and regulatory factors that orchestrate and control the movements of chromosomes during cell division.The function of the peripheral layer of mitotic chromosomes is not fully known, but it has been suggested to be involved in mitotic chromosome structure, to act as a physical barrier protecting mitotic chromatin from cytoplasmic proteins following nuclear envelope breakdown, and to keep mitotic chromosomes from sticking to one another (Van Hooser AA et al. (2005)). In agreement, MKI67 is essential for proper chromosome segregation and has been shown to act as an emulsifying shield around the chromosomes during mitosis (Booth DG et al. (2014); Cuylen S et al. (2016)). In addition, the peripheral layer may act as a landing pad, concentrating nucleolar proteins to aid in nucleolar reactivation during mitotic exit, and helping to ensure equal distribution of its components to daughter cells.

Gene Ontology (GO) analysis of genes encoding proteins mainly localized to the nucleus shows functions that are well in-line with known functions for this compartment. The enriched terms for the GO domain Biological Process are mainly related to transcription and DNA repair (Figure 5a). Enrichment analysis of the GO domain Molecular Function, gives enrichment of terms related to DNA binding, RNA binding, chromatin binding, and regulation of transcription as well as replication (Figure 5b).

Figure 5a Gene Ontology-based enrichment analysis for the nucleoplasm proteome showing the significantly enriched terms for the GO domain Biological Process. Each bar is clickable and gives a search result of proteins that belong to the selected category.

Figure 5b Gene Ontology-based enrichment analysis for the nucleoplasm proteome showing the significantly enriched terms for the GO domain Molecular Function. Each bar is clickable and gives a search result of proteins that belong to the selected category.

Nucleoplasmic proteins with multiple locations

In the subcellular section, approximately 67% (n=4556) of the proteins that localize to the nucleoplasm also localize to other cell compartments (Figure 6). 563 of the proteins in the nucleoplasm (8%) only localize to other nuclear structures. The network plot shows that the most common locations shared with the nucleus are the cytosol, nucleoli and vesicles. Given that the nucleus is involved both in import and export of proteins to the cytoplasm and other compartments of the cell, these dual locations could highlight proteins functioning in nuclear trafficking as well as proteins functioning in various signaling cascades. Multilocalization between the nucleus and a number of cellular compartments, including nucleoli and the cytosol, are significantly overrepresented, while proteins localizing to the nucleus and to the plasma membrane are significantly underrepresented. Examples of multilocalizing proteins within the nucleoplasmic proteome can be seen in Figure 7.

Figure 6. Interactive network plot of nuclear proteins with multiple localizations. The numbers in the connecting nodes show the proteins that are localized to the nucleus and to one or more additional locations. Only connecting nodes containing more than one protein and at least 0.7% of proteins in the nuclear proteome are shown. The circle sizes are related to the number of proteins. The cyan colored nodes show combinations that are significantly overrepresented, while magenta colored nodes show combinations that are significantly underrepresented as compared to the probability of observing that combination based on the frequency of each annotation and a hypergeometric test (p≤0.05). Note that this calculation is only done for proteins with dual localizations. Each node is clickable and results in a list of all proteins that are found in the connected organelles.


IPO7 - A-431

RRAGC - U2OS

SENP3 - MCF-7

Figure 7. Examples of multilocalizing proteins in the nuclear proteome. The examples show common or overrepresented combinations for multilocalizing proteins in the nuclear proteome. IPO7 is functioning in the nuclear import of proteins and is known to be located at both the nucleoplasmic and cytoplasmic side of the nuclear pore complex (detected in A-431 cells). RRAGC is shuttling between the nucleus and the cytoplasm. It plays a crucial role in the initiation of the TOR signaling cascade where it is required for the amino acid induced relocalization of mTORC1 into the lysosomes (detected in U2OS cells). SENP3 is located in both the nucleoli and the nucleoplasm known to interact with sumoylated proteins regulating the transcriptional capacity in the cell and is also required for rRNA processing (detected in MCF7 cells).

Expression levels of nucleoplasm proteins in tissue

Transcriptome analysis and classification of genes into tissue distribution categories (Figure 8) shows that a larger portion of the genes encoding proteins localizing to the nucleoplasm and its substructures are detected in all tissues, compared to all genes presented in the subcellular section. Significantly smaller portions of these genes are detected in many or in some tissues. Thus, the nucleoplasm is a structure that contains a larger portion of ubiquitously expressed proteins.

Figure 8. Bar plot showing the percentage of genes in different tissue distribution categories for nuclear protein-coding genes compared to all genes in the subcellular section. Asterisk marks a statistically significant deviation (p≤0.05) in the number of genes in a category based on a binomial statistical test. Each bar is clickable and gives a search result of proteins that belong to the selected category.

Relevant links and publications

Uhlen M et al., A proposal for validation of antibodies. Nat Methods. (2016)
PubMed: 27595404 DOI: 10.1038/nmeth.3995

Stadler C et al., Systematic validation of antibody binding and protein subcellular localization using siRNA and confocal microscopy. J Proteomics. (2012)
PubMed: 22361696 DOI: 10.1016/j.jprot.2012.01.030

Poser I et al., BAC TransgeneOmics: a high-throughput method for exploration of protein function in mammals. Nat Methods. (2008)
PubMed: 18391959 DOI: 10.1038/nmeth.1199

Skogs M et al., Antibody Validation in Bioimaging Applications Based on Endogenous Expression of Tagged Proteins. J Proteome Res. (2017)
PubMed: 27723985 DOI: 10.1021/acs.jproteome.6b00821

Hildreth AD et al., Single-cell sequencing of human white adipose tissue identifies new cell states in health and obesity. Nat Immunol. (2021)
PubMed: 33907320 DOI: 10.1038/s41590-021-00922-4

He S et al., Single-cell transcriptome profiling of an adult human cell atlas of 15 major organs. Genome Biol. (2020)
PubMed: 33287869 DOI: 10.1186/s13059-020-02210-0

Bhat-Nakshatri P et al., A single-cell atlas of the healthy breast tissues reveals clinically relevant clusters of breast epithelial cells. Cell Rep Med. (2021)
PubMed: 33763657 DOI: 10.1016/j.xcrm.2021.100219

Lukassen S et al., SARS-CoV-2 receptor ACE2 and TMPRSS2 are primarily expressed in bronchial transient secretory cells. EMBO J. (2020)
PubMed: 32246845 DOI: 10.15252/embj.20105114

Parikh K et al., Colonic epithelial cell diversity in health and inflammatory bowel disease. Nature. (2019)
PubMed: 30814735 DOI: 10.1038/s41586-019-0992-y

Wang W et al., Single-cell transcriptomic atlas of the human endometrium during the menstrual cycle. Nat Med. (2020)
PubMed: 32929266 DOI: 10.1038/s41591-020-1040-z

Menon M et al., Single-cell transcriptomic atlas of the human retina identifies cell types associated with age-related macular degeneration. Nat Commun. (2019)
PubMed: 31653841 DOI: 10.1038/s41467-019-12780-8

Ulrich ND et al., Cellular heterogeneity of human fallopian tubes in normal and hydrosalpinx disease states identified using scRNA-seq. Dev Cell. (2022)
PubMed: 35320732 DOI: 10.1016/j.devcel.2022.02.017

Wang L et al., Single-cell reconstruction of the adult human heart during heart failure and recovery reveals the cellular landscape underlying cardiac function. Nat Cell Biol. (2020)
PubMed: 31915373 DOI: 10.1038/s41556-019-0446-7

Liao J et al., Single-cell RNA sequencing of human kidney. Sci Data. (2020)
PubMed: 31896769 DOI: 10.1038/s41597-019-0351-8

MacParland SA et al., Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat Commun. (2018)
PubMed: 30348985 DOI: 10.1038/s41467-018-06318-7

Tabula Sapiens Consortium* et al., The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans. Science. (2022)
PubMed: 35549404 DOI: 10.1126/science.abl4896

Wagner M et al., Single-cell analysis of human ovarian cortex identifies distinct cell populations but no oogonial stem cells. Nat Commun. (2020)
PubMed: 32123174 DOI: 10.1038/s41467-020-14936-3

Qadir MMF et al., Single-cell resolution analysis of the human pancreatic ductal progenitor cell niche. Proc Natl Acad Sci U S A. (2020)
PubMed: 32354994 DOI: 10.1073/pnas.1918314117

Chen J et al., PBMC fixation and processing for Chromium single-cell RNA sequencing. J Transl Med. (2018)
PubMed: 30016977 DOI: 10.1186/s12967-018-1578-4

Vento-Tormo R et al., Single-cell reconstruction of the early maternal-fetal interface in humans. Nature. (2018)
PubMed: 30429548 DOI: 10.1038/s41586-018-0698-6

Wang Y et al., Single-cell transcriptome analysis reveals differential nutrient absorption functions in human intestine. J Exp Med. (2020)
PubMed: 31753849 DOI: 10.1084/jem.20191130

De Micheli AJ et al., A reference single-cell transcriptomic atlas of human skeletal muscle tissue reveals bifurcated muscle stem cell populations. Skelet Muscle. (2020)
PubMed: 32624006 DOI: 10.1186/s13395-020-00236-3

Solé-Boldo L et al., Single-cell transcriptomes of the human skin reveal age-related loss of fibroblast priming. Commun Biol. (2020)
PubMed: 32327715 DOI: 10.1038/s42003-020-0922-4

Guo J et al., The adult human testis transcriptional cell atlas. Cell Res. (2018)
PubMed: 30315278 DOI: 10.1038/s41422-018-0099-2

Agaton C et al., Affinity proteomics for systematic protein profiling of chromosome 21 gene products in human tissues. Mol Cell Proteomics. (2003)
PubMed: 12796447 DOI: 10.1074/mcp.M300022-MCP200

Lindskog M et al., Selection of protein epitopes for antibody production Biotechniques (2005)
PubMed: 15945371 

Larsson M et al., High-throughput protein expression of cDNA products as a tool in functional genomics. J Biotechnol. (2000)
PubMed: 10908795 DOI: 10.1016/s0168-1656(00)00258-3

Takahashi H et al., 5' end-centered expression profiling using cap-analysis gene expression and next-generation sequencing. Nat Protoc. (2012)
PubMed: 22362160 DOI: 10.1038/nprot.2012.005

Lein ES et al., Genome-wide atlas of gene expression in the adult mouse brain. Nature. (2007)
PubMed: 17151600 DOI: 10.1038/nature05453

Kircher M et al., Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform. Nucleic Acids Res. (2012)
PubMed: 22021376 DOI: 10.1093/nar/gkr771

UhlĂ©n M et al., The human secretome. Sci Signal. (2019)
PubMed: 31772123 DOI: 10.1126/scisignal.aaz0274

Uhlen M et al., A genome-wide transcriptomic analysis of protein-coding genes in human blood cells. Science. (2019)
PubMed: 31857451 DOI: 10.1126/science.aax9198

Fagerberg L et al., Prediction of the human membrane proteome. Proteomics. (2010)
PubMed: 20175080 DOI: 10.1002/pmic.200900258

Zhong W et al., The neuropeptide landscape of human prefrontal cortex. Proc Natl Acad Sci U S A. (2022)
PubMed: 35947618 DOI: 10.1073/pnas.2123146119

Sjöstedt E et al., An atlas of the protein-coding genes in the human, pig, and mouse brain. Science. (2020)
PubMed: 32139519 DOI: 10.1126/science.aay5947

Gilvesy A et al., Spatiotemporal characterization of cellular tau pathology in the human locus coeruleus-pericoerulear complex by three-dimensional imaging. Acta Neuropathol. (2022)
PubMed: 36040521 DOI: 10.1007/s00401-022-02477-6

Jin H et al., Systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation. Nat Commun. (2023)
PubMed: 37669926 DOI: 10.1038/s41467-023-41132-w

Schubert M et al., Perturbation-response genes reveal signaling footprints in cancer gene expression. Nat Commun. (2018)
PubMed: 29295995 DOI: 10.1038/s41467-017-02391-6

Jiang P et al., Systematic investigation of cytokine signaling activity at the tissue and single-cell levels. Nat Methods. (2021)
PubMed: 34594031 DOI: 10.1038/s41592-021-01274-5

Jin L et al., Targeting of CD44 eradicates human acute myeloid leukemic stem cells. Nat Med. (2006)
PubMed: 16998484 DOI: 10.1038/nm1483

Magis AT et al., Untargeted longitudinal analysis of a wellness cohort identifies markers of metastatic cancer years prior to diagnosis. Sci Rep. (2020)
PubMed: 33004987 DOI: 10.1038/s41598-020-73451-z

Santarius T et al., GLO1-A novel amplified gene in human cancer. Genes Chromosomes Cancer. (2010)
PubMed: 20544845 DOI: 10.1002/gcc.20784

Berggrund M et al., Identification of Candidate Plasma Protein Biomarkers for Cervical Cancer Using the Multiplex Proximity Extension Assay. Mol Cell Proteomics. (2019)
PubMed: 30692274 DOI: 10.1074/mcp.RA118.001208

Virgilio L et al., Deregulated expression of TCL1 causes T cell leukemia in mice. Proc Natl Acad Sci U S A. (1998)
PubMed: 9520462 DOI: 10.1073/pnas.95.7.3885

Saberi Hosnijeh F et al., Proteomic markers with prognostic impact on outcome of chronic lymphocytic leukemia patients under chemo-immunotherapy: results from the HOVON 109 study. Exp Hematol. (2020)
PubMed: 32781097 DOI: 10.1016/j.exphem.2020.08.002

Gao L et al., Integrative analysis the characterization of peroxiredoxins in pan-cancer. Cancer Cell Int. (2021)
PubMed: 34246267 DOI: 10.1186/s12935-021-02064-x

Satelli A et al., Galectin-4 functions as a tumor suppressor of human colorectal cancer. Int J Cancer. (2011)
PubMed: 21064109 DOI: 10.1002/ijc.25750

Harlid S et al., A two-tiered targeted proteomics approach to identify pre-diagnostic biomarkers of colorectal cancer risk. Sci Rep. (2021)
PubMed: 33664295 DOI: 10.1038/s41598-021-83968-6

Sun X et al., Prospective Proteomic Study Identifies Potential Circulating Protein Biomarkers for Colorectal Cancer Risk. Cancers (Basel). (2022)
PubMed: 35805033 DOI: 10.3390/cancers14133261

Bhardwaj M et al., Comparison of Proteomic Technologies for Blood-Based Detection of Colorectal Cancer. Int J Mol Sci. (2021)
PubMed: 33530402 DOI: 10.3390/ijms22031189

Chen H et al., Head-to-Head Comparison and Evaluation of 92 Plasma Protein Biomarkers for Early Detection of Colorectal Cancer in a True Screening Setting. Clin Cancer Res. (2015)
PubMed: 26015516 DOI: 10.1158/1078-0432.CCR-14-3051

Thorsen SB et al., Detection of serological biomarkers by proximity extension assay for detection of colorectal neoplasias in symptomatic individuals. J Transl Med. (2013)
PubMed: 24107468 DOI: 10.1186/1479-5876-11-253

Mahboob S et al., A novel multiplexed immunoassay identifies CEA, IL-8 and prolactin as prospective markers for Dukes' stages A-D colorectal cancers. Clin Proteomics. (2015)
PubMed: 25987887 DOI: 10.1186/s12014-015-9081-x

He W et al., Attenuation of TNFSF10/TRAIL-induced apoptosis by an autophagic survival pathway involving TRAF2- and RIPK1/RIP1-mediated MAPK8/JNK activation. Autophagy. (2012)
PubMed: 23051914 DOI: 10.4161/auto.22145

Enroth S et al., A two-step strategy for identification of plasma protein biomarkers for endometrial and ovarian cancer. Clin Proteomics. (2018)
PubMed: 30519148 DOI: 10.1186/s12014-018-9216-y

Jung CS et al., Serum GFAP is a diagnostic marker for glioblastoma multiforme. Brain. (2007)
PubMed: 17998256 DOI: 10.1093/brain/awm263

Jaworski DM et al., BEHAB (brain enriched hyaluronan binding) is expressed in surgical samples of glioma and in intracranial grafts of invasive glioma cell lines. Cancer Res. (1996)
PubMed: 8625302 

Zhang X et al., CEACAM5 stimulates the progression of non-small-cell lung cancer by promoting cell proliferation and migration. J Int Med Res. (2020)
PubMed: 32993395 DOI: 10.1177/0300060520959478

Xu F et al., A Linear Discriminant Analysis Model Based on the Changes of 7 Proteins in Plasma Predicts Response to Anlotinib Therapy in Advanced Non-Small Cell Lung Cancer Patients. Front Oncol. (2021)
PubMed: 35070967 DOI: 10.3389/fonc.2021.756902

Dagnino S et al., Prospective Identification of Elevated Circulating CDCP1 in Patients Years before Onset of Lung Cancer. Cancer Res. (2021)
PubMed: 33574093 DOI: 10.1158/0008-5472.CAN-20-3454

Álvez MB et al., Next generation pan-cancer blood proteome profiling using proximity extension assay. Nat Commun. (2023)
PubMed: 37463882 DOI: 10.1038/s41467-023-39765-y

Wik L et al., Proximity Extension Assay in Combination with Next-Generation Sequencing for High-throughput Proteome-wide Analysis. Mol Cell Proteomics. (2021)
PubMed: 34715355 DOI: 10.1016/j.mcpro.2021.100168

Zeiler M et al., A Protein Epitope Signature Tag (PrEST) library allows SILAC-based absolute quantification and multiplexed determination of protein copy numbers in cell lines. Mol Cell Proteomics. (2012)
PubMed: 21964433 DOI: 10.1074/mcp.O111.009613

Peng Y et al., Identification of key biomarkers associated with cell adhesion in multiple myeloma by integrated bioinformatics analysis. Cancer Cell Int. (2020)
PubMed: 32581652 DOI: 10.1186/s12935-020-01355-z

Gyllensten U et al., Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer. Cancers (Basel). (2022)
PubMed: 35406529 DOI: 10.3390/cancers14071757

Enroth S et al., High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer. Commun Biol. (2019)
PubMed: 31240259 DOI: 10.1038/s42003-019-0464-9

Wang Z et al., DNER promotes epithelial-mesenchymal transition and prevents chemosensitivity through the Wnt/β-catenin pathway in breast cancer. Cell Death Dis. (2020)
PubMed: 32811806 DOI: 10.1038/s41419-020-02903-1

Liu S et al., Discovery of CASP8 as a potential biomarker for high-risk prostate cancer through a high-multiplex immunoassay. Sci Rep. (2021)
PubMed: 33828176 DOI: 10.1038/s41598-021-87155-5

Orchard S et al., The MIntAct project--IntAct as a common curation platform for 11 molecular interaction databases. Nucleic Acids Res. (2014)
PubMed: 24234451 DOI: 10.1093/nar/gkt1115

Robinson JL et al., An atlas of human metabolism. Sci Signal. (2020)
PubMed: 32209698 DOI: 10.1126/scisignal.aaz1482

Uhlen M et al., A pathology atlas of the human cancer transcriptome. Science. (2017)
PubMed: 28818916 DOI: 10.1126/science.aan2507

Hikmet F et al., The protein expression profile of ACE2 in human tissues. Mol Syst Biol. (2020)
PubMed: 32715618 DOI: 10.15252/msb.20209610

Gordon DE et al., A SARS-CoV-2 protein interaction map reveals targets for drug repurposing. Nature. (2020)
PubMed: 32353859 DOI: 10.1038/s41586-020-2286-9

Karlsson M et al., A single-cell type transcriptomics map of human tissues. Sci Adv. (2021)
PubMed: 34321199 DOI: 10.1126/sciadv.abh2169

Jumper J et al., Highly accurate protein structure prediction with AlphaFold. Nature. (2021)
PubMed: 34265844 DOI: 10.1038/s41586-021-03819-2

Varadi M et al., AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models. Nucleic Acids Res. (2022)
PubMed: 34791371 DOI: 10.1093/nar/gkab1061

Pollard TD et al., Actin, a central player in cell shape and movement. Science. (2009)
PubMed: 19965462 DOI: 10.1126/science.1175862

Mitchison TJ et al., Actin-based cell motility and cell locomotion. Cell. (1996)
PubMed: 8608590 

Pollard TD et al., Molecular Mechanism of Cytokinesis. Annu Rev Biochem. (2019)
PubMed: 30649923 DOI: 10.1146/annurev-biochem-062917-012530

dos Remedios CG et al., Actin binding proteins: regulation of cytoskeletal microfilaments. Physiol Rev. (2003)
PubMed: 12663865 DOI: 10.1152/physrev.00026.2002

Campellone KG et al., A nucleator arms race: cellular control of actin assembly. Nat Rev Mol Cell Biol. (2010)
PubMed: 20237478 DOI: 10.1038/nrm2867

Rottner K et al., Actin assembly mechanisms at a glance. J Cell Sci. (2017)
PubMed: 29032357 DOI: 10.1242/jcs.206433

Bird RP., Observation and quantification of aberrant crypts in the murine colon treated with a colon carcinogen: preliminary findings. Cancer Lett. (1987)
PubMed: 3677050 DOI: 10.1016/0304-3835(87)90157-1

HUXLEY AF et al., Structural changes in muscle during contraction; interference microscopy of living muscle fibres. Nature. (1954)
PubMed: 13165697 

HUXLEY H et al., Changes in the cross-striations of muscle during contraction and stretch and their structural interpretation. Nature. (1954)
PubMed: 13165698 

Svitkina T., The Actin Cytoskeleton and Actin-Based Motility. Cold Spring Harb Perspect Biol. (2018)
PubMed: 29295889 DOI: 10.1101/cshperspect.a018267

Malumbres M et al., Cell cycle, CDKs and cancer: a changing paradigm. Nat Rev Cancer. (2009)
PubMed: 19238148 DOI: 10.1038/nrc2602

Massagué J., G1 cell-cycle control and cancer. Nature. (2004)
PubMed: 15549091 DOI: 10.1038/nature03094

Hartwell LH et al., Cell cycle control and cancer. Science. (1994)
PubMed: 7997877 DOI: 10.1126/science.7997877

Barnum KJ et al., Cell cycle regulation by checkpoints. Methods Mol Biol. (2014)
PubMed: 24906307 DOI: 10.1007/978-1-4939-0888-2_2

Weinberg RA., The retinoblastoma protein and cell cycle control. Cell. (1995)
PubMed: 7736585 DOI: 10.1016/0092-8674(95)90385-2

Morgan DO., Principles of CDK regulation. Nature. (1995)
PubMed: 7877684 DOI: 10.1038/374131a0

Teixeira LK et al., Ubiquitin ligases and cell cycle control. Annu Rev Biochem. (2013)
PubMed: 23495935 DOI: 10.1146/annurev-biochem-060410-105307

King RW et al., How proteolysis drives the cell cycle. Science. (1996)
PubMed: 8939846 DOI: 10.1126/science.274.5293.1652

Cho RJ et al., Transcriptional regulation and function during the human cell cycle. Nat Genet. (2001)
PubMed: 11137997 DOI: 10.1038/83751

Whitfield ML et al., Identification of genes periodically expressed in the human cell cycle and their expression in tumors. Mol Biol Cell. (2002)
PubMed: 12058064 DOI: 10.1091/mbc.02-02-0030.

Boström J et al., Comparative cell cycle transcriptomics reveals synchronization of developmental transcription factor networks in cancer cells. PLoS One. (2017)
PubMed: 29228002 DOI: 10.1371/journal.pone.0188772

Lane KR et al., Cell cycle-regulated protein abundance changes in synchronously proliferating HeLa cells include regulation of pre-mRNA splicing proteins. PLoS One. (2013)
PubMed: 23520512 DOI: 10.1371/journal.pone.0058456

Ohta S et al., The protein composition of mitotic chromosomes determined using multiclassifier combinatorial proteomics. Cell. (2010)
PubMed: 20813266 DOI: 10.1016/j.cell.2010.07.047

Ly T et al., A proteomic chronology of gene expression through the cell cycle in human myeloid leukemia cells. Elife. (2014)
PubMed: 24596151 DOI: 10.7554/eLife.01630

Pagliuca FW et al., Quantitative proteomics reveals the basis for the biochemical specificity of the cell-cycle machinery. Mol Cell. (2011)
PubMed: 21816347 DOI: 10.1016/j.molcel.2011.05.031

Ly T et al., Proteomic analysis of the response to cell cycle arrests in human myeloid leukemia cells. Elife. (2015)
PubMed: 25555159 DOI: 10.7554/eLife.04534

Mahdessian D et al., Spatiotemporal dissection of the cell cycle with single-cell proteogenomics. Nature. (2021)
PubMed: 33627808 DOI: 10.1038/s41586-021-03232-9

Dueck H et al., Variation is function: Are single cell differences functionally important?: Testing the hypothesis that single cell variation is required for aggregate function. Bioessays. (2016)
PubMed: 26625861 DOI: 10.1002/bies.201500124

Snijder B et al., Origins of regulated cell-to-cell variability. Nat Rev Mol Cell Biol. (2011)
PubMed: 21224886 DOI: 10.1038/nrm3044

Thul PJ et al., A subcellular map of the human proteome. Science. (2017)
PubMed: 28495876 DOI: 10.1126/science.aal3321

Cooper S et al., Membrane-elution analysis of content of cyclins A, B1, and E during the unperturbed mammalian cell cycle. Cell Div. (2007)
PubMed: 17892542 DOI: 10.1186/1747-1028-2-28

Davis PK et al., Biological methods for cell-cycle synchronization of mammalian cells. Biotechniques. (2001)
PubMed: 11414226 DOI: 10.2144/01306rv01

Domenighetti G et al., Effect of information campaign by the mass media on hysterectomy rates. Lancet. (1988)
PubMed: 2904581 DOI: 10.1016/s0140-6736(88)90943-9

Scialdone A et al., Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods. (2015)
PubMed: 26142758 DOI: 10.1016/j.ymeth.2015.06.021

Sakaue-Sawano A et al., Visualizing spatiotemporal dynamics of multicellular cell-cycle progression. Cell. (2008)
PubMed: 18267078 DOI: 10.1016/j.cell.2007.12.033

Grant GD et al., Identification of cell cycle-regulated genes periodically expressed in U2OS cells and their regulation by FOXM1 and E2F transcription factors. Mol Biol Cell. (2013)
PubMed: 24109597 DOI: 10.1091/mbc.E13-05-0264

Semple JW et al., An essential role for Orc6 in DNA replication through maintenance of pre-replicative complexes. EMBO J. (2006)
PubMed: 17053779 DOI: 10.1038/sj.emboj.7601391

Nigg EA et al., The centrosome cycle: Centriole biogenesis, duplication and inherent asymmetries. Nat Cell Biol. (2011)
PubMed: 21968988 DOI: 10.1038/ncb2345

Doxsey S., Re-evaluating centrosome function. Nat Rev Mol Cell Biol. (2001)
PubMed: 11533726 DOI: 10.1038/35089575

Bornens M., Centrosome composition and microtubule anchoring mechanisms. Curr Opin Cell Biol. (2002)
PubMed: 11792541 

Conduit PT et al., Centrosome function and assembly in animal cells. Nat Rev Mol Cell Biol. (2015)
PubMed: 26373263 DOI: 10.1038/nrm4062

Tollenaere MA et al., Centriolar satellites: key mediators of centrosome functions. Cell Mol Life Sci. (2015)
PubMed: 25173771 DOI: 10.1007/s00018-014-1711-3

Prosser SL et al., Centriolar satellite biogenesis and function in vertebrate cells. J Cell Sci. (2020)
PubMed: 31896603 DOI: 10.1242/jcs.239566

Rieder CL et al., The centrosome in vertebrates: more than a microtubule-organizing center. Trends Cell Biol. (2001)
PubMed: 11567874 

Badano JL et al., The centrosome in human genetic disease. Nat Rev Genet. (2005)
PubMed: 15738963 DOI: 10.1038/nrg1557

Clegg JS., Properties and metabolism of the aqueous cytoplasm and its boundaries. Am J Physiol. (1984)
PubMed: 6364846 

Luby-Phelps K., The physical chemistry of cytoplasm and its influence on cell function: an update. Mol Biol Cell. (2013)
PubMed: 23989722 DOI: 10.1091/mbc.E12-08-0617

Luby-Phelps K., Cytoarchitecture and physical properties of cytoplasm: volume, viscosity, diffusion, intracellular surface area. Int Rev Cytol. (2000)
PubMed: 10553280 

Ellis RJ., Macromolecular crowding: obvious but underappreciated. Trends Biochem Sci. (2001)
PubMed: 11590012 

Bright GR et al., Fluorescence ratio imaging microscopy: temporal and spatial measurements of cytoplasmic pH. J Cell Biol. (1987)
PubMed: 3558476 

Kopito RR., Aggresomes, inclusion bodies and protein aggregation. Trends Cell Biol. (2000)
PubMed: 11121744 

Aizer A et al., Intracellular trafficking and dynamics of P bodies. Prion. (2008)
PubMed: 19242093 

Carcamo WC et al., Molecular cell biology and immunobiology of mammalian rod/ring structures. Int Rev Cell Mol Biol. (2014)
PubMed: 24411169 DOI: 10.1016/B978-0-12-800097-7.00002-6

Lang F., Mechanisms and significance of cell volume regulation. J Am Coll Nutr. (2007)
PubMed: 17921474 

Becht E et al., Dimensionality reduction for visualizing single-cell data using UMAP. Nat Biotechnol. (2018)
PubMed: 30531897 DOI: 10.1038/nbt.4314

Schwarz DS et al., The endoplasmic reticulum: structure, function and response to cellular signaling. Cell Mol Life Sci. (2016)
PubMed: 26433683 DOI: 10.1007/s00018-015-2052-6

Friedman JR et al., The ER in 3D: a multifunctional dynamic membrane network. Trends Cell Biol. (2011)
PubMed: 21900009 DOI: 10.1016/j.tcb.2011.07.004

Travers KJ et al., Functional and genomic analyses reveal an essential coordination between the unfolded protein response and ER-associated degradation. Cell. (2000)
PubMed: 10847680 

Roussel BD et al., Endoplasmic reticulum dysfunction in neurological disease. Lancet Neurol. (2013)
PubMed: 23237905 DOI: 10.1016/S1474-4422(12)70238-7

Neve EP et al., Cytochrome P450 proteins: retention and distribution from the endoplasmic reticulum. Curr Opin Drug Discov Devel. (2010)
PubMed: 20047148 

Kulkarni-Gosavi P et al., Form and function of the Golgi apparatus: scaffolds, cytoskeleton and signalling. FEBS Lett. (2019)
PubMed: 31378930 DOI: 10.1002/1873-3468.13567

Short B et al., The Golgi apparatus. Curr Biol. (2000)
PubMed: 10985372 DOI: 10.1016/s0960-9822(00)00644-8

Wei JH et al., Unraveling the Golgi ribbon. Traffic. (2010)
PubMed: 21040294 DOI: 10.1111/j.1600-0854.2010.01114.x

Wilson C et al., The Golgi apparatus: an organelle with multiple complex functions. Biochem J. (2011)
PubMed: 21158737 DOI: 10.1042/BJ20101058

Farquhar MG et al., The Golgi apparatus: 100 years of progress and controversy. Trends Cell Biol. (1998)
PubMed: 9695800 

Brandizzi F et al., Organization of the ER-Golgi interface for membrane traffic control. Nat Rev Mol Cell Biol. (2013)
PubMed: 23698585 DOI: 10.1038/nrm3588

Potelle S et al., Golgi post-translational modifications and associated diseases. J Inherit Metab Dis. (2015)
PubMed: 25967285 DOI: 10.1007/s10545-015-9851-7

Yoon TY et al., SNARE complex assembly and disassembly. Curr Biol. (2018)
PubMed: 29689222 DOI: 10.1016/j.cub.2018.01.005

Leduc C et al., Intermediate filaments in cell migration and invasion: the unusual suspects. Curr Opin Cell Biol. (2015)
PubMed: 25660489 DOI: 10.1016/j.ceb.2015.01.005

Lowery J et al., Intermediate Filaments Play a Pivotal Role in Regulating Cell Architecture and Function. J Biol Chem. (2015)
PubMed: 25957409 DOI: 10.1074/jbc.R115.640359

Robert A et al., Intermediate filament dynamics: What we can see now and why it matters. Bioessays. (2016)
PubMed: 26763143 DOI: 10.1002/bies.201500142

Fuchs E et al., Intermediate filaments: structure, dynamics, function, and disease. Annu Rev Biochem. (1994)
PubMed: 7979242 DOI: 10.1146/annurev.bi.63.070194.002021

Janmey PA et al., Viscoelastic properties of vimentin compared with other filamentous biopolymer networks. J Cell Biol. (1991)
PubMed: 2007620 

Köster S et al., Intermediate filament mechanics in vitro and in the cell: from coiled coils to filaments, fibers and networks. Curr Opin Cell Biol. (2015)
PubMed: 25621895 DOI: 10.1016/j.ceb.2015.01.001

Herrmann H et al., Intermediate filaments: from cell architecture to nanomechanics. Nat Rev Mol Cell Biol. (2007)
PubMed: 17551517 DOI: 10.1038/nrm2197

Gauster M et al., Keratins in the human trophoblast. Histol Histopathol. (2013)
PubMed: 23450430 DOI: 10.14670/HH-28.817

Ouyang W et al., Analysis of the Human Protein Atlas Image Classification competition. Nat Methods. (2019)
PubMed: 31780840 DOI: 10.1038/s41592-019-0658-6

Janke C., The tubulin code: molecular components, readout mechanisms, and functions. J Cell Biol. (2014)
PubMed: 25135932 DOI: 10.1083/jcb.201406055

Goodson HV et al., Microtubules and Microtubule-Associated Proteins. Cold Spring Harb Perspect Biol. (2018)
PubMed: 29858272 DOI: 10.1101/cshperspect.a022608

Wade RH., On and around microtubules: an overview. Mol Biotechnol. (2009)
PubMed: 19565362 DOI: 10.1007/s12033-009-9193-5

Desai A et al., Microtubule polymerization dynamics. Annu Rev Cell Dev Biol. (1997)
PubMed: 9442869 DOI: 10.1146/annurev.cellbio.13.1.83

Conde C et al., Microtubule assembly, organization and dynamics in axons and dendrites. Nat Rev Neurosci. (2009)
PubMed: 19377501 DOI: 10.1038/nrn2631

Wloga D et al., Post-translational modifications of microtubules. J Cell Sci. (2010)
PubMed: 20930140 DOI: 10.1242/jcs.063727

Schmoranzer J et al., Role of microtubules in fusion of post-Golgi vesicles to the plasma membrane. Mol Biol Cell. (2003)
PubMed: 12686609 DOI: 10.1091/mbc.E02-08-0500

Skop AR et al., Dissection of the mammalian midbody proteome reveals conserved cytokinesis mechanisms. Science. (2004)
PubMed: 15166316 DOI: 10.1126/science.1097931

Waters AM et al., Ciliopathies: an expanding disease spectrum. Pediatr Nephrol. (2011)
PubMed: 21210154 DOI: 10.1007/s00467-010-1731-7

Matamoros AJ et al., Microtubules in health and degenerative disease of the nervous system. Brain Res Bull. (2016)
PubMed: 27365230 DOI: 10.1016/j.brainresbull.2016.06.016

Jordan MA et al., Microtubules as a target for anticancer drugs. Nat Rev Cancer. (2004)
PubMed: 15057285 DOI: 10.1038/nrc1317

Nunnari J et al., Mitochondria: in sickness and in health. Cell. (2012)
PubMed: 22424226 DOI: 10.1016/j.cell.2012.02.035

Friedman JR et al., Mitochondrial form and function. Nature. (2014)
PubMed: 24429632 DOI: 10.1038/nature12985

Calvo SE et al., The mitochondrial proteome and human disease. Annu Rev Genomics Hum Genet. (2010)
PubMed: 20690818 DOI: 10.1146/annurev-genom-082509-141720

McBride HM et al., Mitochondria: more than just a powerhouse. Curr Biol. (2006)
PubMed: 16860735 DOI: 10.1016/j.cub.2006.06.054

Schaefer AM et al., The epidemiology of mitochondrial disorders--past, present and future. Biochim Biophys Acta. (2004)
PubMed: 15576042 DOI: 10.1016/j.bbabio.2004.09.005

Lange A et al., Classical nuclear localization signals: definition, function, and interaction with importin alpha. J Biol Chem. (2007)
PubMed: 17170104 DOI: 10.1074/jbc.R600026200

Ashmarina LI et al., 3-Hydroxy-3-methylglutaryl coenzyme A lyase: targeting and processing in peroxisomes and mitochondria. J Lipid Res. (1999)
PubMed: 9869651 

Wang SC et al., Nuclear translocation of the epidermal growth factor receptor family membrane tyrosine kinase receptors. Clin Cancer Res. (2009)
PubMed: 19861462 DOI: 10.1158/1078-0432.CCR-08-2813

Jeffery CJ., Moonlighting proteins. Trends Biochem Sci. (1999)
PubMed: 10087914 

Jeffery CJ., Why study moonlighting proteins? Front Genet. (2015)
PubMed: 26150826 DOI: 10.3389/fgene.2015.00211

Pancholi V., Multifunctional alpha-enolase: its role in diseases. Cell Mol Life Sci. (2001)
PubMed: 11497239 DOI: 10.1007/pl00000910

Chapple CE et al., Extreme multifunctional proteins identified from a human protein interaction network. Nat Commun. (2015)
PubMed: 26054620 DOI: 10.1038/ncomms8412

Dechat T et al., Nuclear lamins: major factors in the structural organization and function of the nucleus and chromatin. Genes Dev. (2008)
PubMed: 18381888 DOI: 10.1101/gad.1652708

Gruenbaum Y et al., The nuclear lamina comes of age. Nat Rev Mol Cell Biol. (2005)
PubMed: 15688064 DOI: 10.1038/nrm1550

Stuurman N et al., Nuclear lamins: their structure, assembly, and interactions. J Struct Biol. (1998)
PubMed: 9724605 DOI: 10.1006/jsbi.1998.3987

Paine PL et al., Nuclear envelope permeability. Nature. (1975)
PubMed: 1117994 

Reichelt R et al., Correlation between structure and mass distribution of the nuclear pore complex and of distinct pore complex components. J Cell Biol. (1990)
PubMed: 2324201 

CALLAN HG et al., Experimental studies on amphibian oocyte nuclei. I. Investigation of the structure of the nuclear membrane by means of the electron microscope. Proc R Soc Lond B Biol Sci. (1950)
PubMed: 14786306 

WATSON ML., The nuclear envelope; its structure and relation to cytoplasmic membranes. J Biophys Biochem Cytol. (1955)
PubMed: 13242591 

BAHR GF et al., The fine structure of the nuclear membrane in the larval salivary gland and midgut of Chironomus. Exp Cell Res. (1954)
PubMed: 13173504 

Terasaki M et al., A new model for nuclear envelope breakdown. Mol Biol Cell. (2001)
PubMed: 11179431 

Dultz E et al., Systematic kinetic analysis of mitotic dis- and reassembly of the nuclear pore in living cells. J Cell Biol. (2008)
PubMed: 18316408 DOI: 10.1083/jcb.200707026

Salina D et al., Cytoplasmic dynein as a facilitator of nuclear envelope breakdown. Cell. (2002)
PubMed: 11792324 

Beaudouin J et al., Nuclear envelope breakdown proceeds by microtubule-induced tearing of the lamina. Cell. (2002)
PubMed: 11792323 

Gerace L et al., The nuclear envelope lamina is reversibly depolymerized during mitosis. Cell. (1980)
PubMed: 7357605 

Ellenberg J et al., Nuclear membrane dynamics and reassembly in living cells: targeting of an inner nuclear membrane protein in interphase and mitosis. J Cell Biol. (1997)
PubMed: 9298976 

Yang L et al., Integral membrane proteins of the nuclear envelope are dispersed throughout the endoplasmic reticulum during mitosis. J Cell Biol. (1997)
PubMed: 9182656 

Bione S et al., Identification of a novel X-linked gene responsible for Emery-Dreifuss muscular dystrophy. Nat Genet. (1994)
PubMed: 7894480 DOI: 10.1038/ng1294-323

Boisvert FM et al., The multifunctional nucleolus. Nat Rev Mol Cell Biol. (2007)
PubMed: 17519961 DOI: 10.1038/nrm2184

Scheer U et al., Structure and function of the nucleolus. Curr Opin Cell Biol. (1999)
PubMed: 10395554 DOI: 10.1016/S0955-0674(99)80054-4

Németh A et al., Genome organization in and around the nucleolus. Trends Genet. (2011)
PubMed: 21295884 DOI: 10.1016/j.tig.2011.01.002

Cuylen S et al., Ki-67 acts as a biological surfactant to disperse mitotic chromosomes. Nature. (2016)
PubMed: 27362226 DOI: 10.1038/nature18610

Stenström L et al., Mapping the nucleolar proteome reveals a spatiotemporal organization related to intrinsic protein disorder. Mol Syst Biol. (2020)
PubMed: 32744794 DOI: 10.15252/msb.20209469

Visintin R et al., The nucleolus: the magician's hat for cell cycle tricks. Curr Opin Cell Biol. (2000)
PubMed: 10801456 

Marciniak RA et al., Nucleolar localization of the Werner syndrome protein in human cells. Proc Natl Acad Sci U S A. (1998)
PubMed: 9618508 

Tamanini F et al., The fragile X-related proteins FXR1P and FXR2P contain a functional nucleolar-targeting signal equivalent to the HIV-1 regulatory proteins. Hum Mol Genet. (2000)
PubMed: 10888599 

Willemsen R et al., Association of FMRP with ribosomal precursor particles in the nucleolus. Biochem Biophys Res Commun. (1996)
PubMed: 8769090 DOI: 10.1006/bbrc.1996.1126

Isaac C et al., Characterization of the nucleolar gene product, treacle, in Treacher Collins syndrome. Mol Biol Cell. (2000)
PubMed: 10982400 

Drygin D et al., The RNA polymerase I transcription machinery: an emerging target for the treatment of cancer. Annu Rev Pharmacol Toxicol. (2010)
PubMed: 20055700 DOI: 10.1146/annurev.pharmtox.010909.105844

Spector DL., Macromolecular domains within the cell nucleus. Annu Rev Cell Biol. (1993)
PubMed: 8280462 DOI: 10.1146/annurev.cb.09.110193.001405

Lamond AI et al., Structure and function in the nucleus. Science. (1998)
PubMed: 9554838 

SWIFT H., Studies on nuclear fine structure. Brookhaven Symp Biol. (1959)
PubMed: 13836127 

Lamond AI et al., Nuclear speckles: a model for nuclear organelles. Nat Rev Mol Cell Biol. (2003)
PubMed: 12923522 DOI: 10.1038/nrm1172

Thiry M., The interchromatin granules. Histol Histopathol. (1995)
PubMed: 8573995 

Sleeman JE et al., Newly assembled snRNPs associate with coiled bodies before speckles, suggesting a nuclear snRNP maturation pathway. Curr Biol. (1999)
PubMed: 10531003 

Darzacq X et al., Cajal body-specific small nuclear RNAs: a novel class of 2'-O-methylation and pseudouridylation guide RNAs. EMBO J. (2002)
PubMed: 12032087 DOI: 10.1093/emboj/21.11.2746

Jády BE et al., Modification of Sm small nuclear RNAs occurs in the nucleoplasmic Cajal body following import from the cytoplasm. EMBO J. (2003)
PubMed: 12682020 DOI: 10.1093/emboj/cdg187

Liu Q et al., A novel nuclear structure containing the survival of motor neurons protein. EMBO J. (1996)
PubMed: 8670859 

Lefebvre S et al., Identification and characterization of a spinal muscular atrophy-determining gene. Cell. (1995)
PubMed: 7813012 

Fischer U et al., The SMN-SIP1 complex has an essential role in spliceosomal snRNP biogenesis. Cell. (1997)
PubMed: 9323130 

Lallemand-Breitenbach V et al., PML nuclear bodies. Cold Spring Harb Perspect Biol. (2010)
PubMed: 20452955 DOI: 10.1101/cshperspect.a000661

Booth DG et al., Ki-67 and the Chromosome Periphery Compartment in Mitosis. Trends Cell Biol. (2017)
PubMed: 28838621 DOI: 10.1016/j.tcb.2017.08.001

Ljungberg O et al., A compound follicular-parafollicular cell carcinoma of the thyroid: a new tumor entity? Cancer. (1983)
PubMed: 6136320 DOI: 10.1002/1097-0142(19830915)52:6<1053::aid-cncr2820520621>3.0.co;2-q

Melcák I et al., Nuclear pre-mRNA compartmentalization: trafficking of released transcripts to splicing factor reservoirs. Mol Biol Cell. (2000)
PubMed: 10679009 

Spector DL et al., Associations between distinct pre-mRNA splicing components and the cell nucleus. EMBO J. (1991)
PubMed: 1833187 

Misteli T et al., Protein phosphorylation and the nuclear organization of pre-mRNA splicing. Trends Cell Biol. (1997)
PubMed: 17708924 DOI: 10.1016/S0962-8924(96)20043-1

Cmarko D et al., Ultrastructural analysis of transcription and splicing in the cell nucleus after bromo-UTP microinjection. Mol Biol Cell. (1999)
PubMed: 9880337 

Van Hooser AA et al., The perichromosomal layer. Chromosoma. (2005)
PubMed: 16136320 DOI: 10.1007/s00412-005-0021-9

Booth DG et al., Ki-67 is a PP1-interacting protein that organises the mitotic chromosome periphery. Elife. (2014)
PubMed: 24867636 DOI: 10.7554/eLife.01641