[Show abstract][Hide abstract] ABSTRACT: Names and characteristics of the hubs. For each of the 74 hubs the table provides: - the number of observed connections, - the number of expected connections, - the difference between the two, which could be seen as their connectivity score.
[Show abstract][Hide abstract] ABSTRACT: RACEfrag assignment. This figure is divided into three parts: 1) on the top, the annotations of a given chromosome are represented, which are here the different alternative transcripts of three loci: A, B and C; 2) in the middle, the primers and RACEfrags of three different pools in several tissues are represented; 3) on the bottom, the formula of the assignment confidence score is provided again as well as its application on 5 different (RACEfrag, locus) pairs (note that here two RACEfrags with the same coordinates are given the same identifier). The first two parts of the figure are thus dedicated to the description of the assignment method, while the third part shows how the assignment score behaves on already assigned RACEfrags associated to their locus. Primers are named and colored after the locus they are originating from, and RACEfrags after the locus they have been assigned to. In pool 1, primer C1 is active and points in the direction of all RACEfrags, so all RACEfrags of pool 1 are assigned to primer C1. In pool 2, it is the same with primer C2, and in pool 3 the same with primer A1. Then the ACS formula is applied to 5 different (RACEfrag, locus) pairs, and the lower the score the more confidence we have in the assignment of the RACEfrag to the locus. Here the (RACEfrag, locus) pair we are the most confident in is (3,C) since RACEfrag 3 appears 4 times in total and each time it appears it is assigned to locus C. Also, the fact that it is assigned to two different primers of locus C, primers C1 and C2, strengthens the confidence we have in this pair. The pair (4,C) is similar to the pair (3,C) except that RACEfrag 4 appears in 2 experiments instead of 4. It thus also has a good score, although less than the one of (3,C). The pair (2,C) is like the pair (3,C) except that RACEfrag 2 also appears in pool 3, tissue 1 where it is assigned to locus A. This makes it more uncertain we should assign RACEfrags 2 to locus C, as compared to RACEfrag 3, and this is why the score of (2,C) is lower than the one of (3,C). The pair (5,C) is similar to the pair (4,C) except that RACEfrag 5 is only assigned to 1 primer of locus C (primer C1), compared to two primers of locus C for RACEfrag 4 (primers C1 and C2). This explains the lower score of (5,C) with respect to the one of (4,C). Finally the pair (2,A) is given a very bad score since RACEfrag 2 appears 5 times but is assigned only once to locus A.
[Show abstract][Hide abstract] ABSTRACT: Pairwise correlations between cell types based on pure reciprocal gene to gene connections. This figure represents the pairwise correlations between the cell types used in the RACEarray experiments as a heatmap: the closer to the white, the more correlated. More precisely for each pair of cell types, the Pearson's product moment correlation between them was computed based on the number of reciprocal gene to gene connections commonly observed, in the universe of all possible reciprocal gene to gene connections. This number is the one indicated in the corresponding cell of the heatmap. Note that genes g1 and g2 form a possible reciprocal gene to gene connection if and only if there is a RACE primer in g1 pointing in the direction of g2 and a RACE primer in g2 pointing in the direction of g1.
[Show abstract][Hide abstract] ABSTRACT: Different categories of genes used in the RACEarray experiments. Proportional Venn diagram representation of inclusion relationships between some of the most used sets of genes used in this study. The area highlighted in light blue corresponds to non-hub genes, which are all reciprocally connected.
[Show abstract][Hide abstract] ABSTRACT: Number of observed (left) and of expected (right) gene to gene connections on chromosomes 21 (top) and 22 (bottom). The shape of the observed distributions is similar for the two chromosomes, as well as the shape of the expected ones, however the distributions are decreasing much more rapidly for the expected connections compared to the observed connections.
[Show abstract][Hide abstract] ABSTRACT: RACEfrag calling. This figure represents the exonic accuracy of 10 RACEfrag sets coming from 10 randomly chosen experiments, as a function of the intensity threshold (I) and the maxgap (M), for 3 different minrun values (m): 3, 4 and 5. The blue arrows indicate the maximum exonic accuracy found over all the possible values of the three parameters, and the red arrows the minimum exonic accuracy. The maximum is reached for I = 99.1%ile, M = 59 bp, m = 5 probes.
[Show abstract][Hide abstract] ABSTRACT: Reciprocal gene to gene connections in chromosome 21 (A) and 22 (B). All 2,324 pure and composite gene/gene reciprocal connections observed in the 10 cell types studied are represented as blue (connection involving two genes on the same chromosome strand) and orange (connection involving two genes on different strands) inner ribbons. See Figure 2A for further legend details. Pseudogene tracks were removed for clarity purposes (See Figures S9 and S10 for reciprocal gene/gene connections in each cell type).
[Show abstract][Hide abstract] ABSTRACT: Model of possible structure of fused fragments for chimera OTTHUMP00000221101. Models for the N- and C-terminal sections have been obtained respectively from structures 2hym and 3g9v by comparative modeling (Modeller, http://salilab.org/modeller). Linker region (shown as a gap in the structure) is located in flexible regions for both templates. Domain folds could then be maintained independently.
[Show abstract][Hide abstract] ABSTRACT: Chromosome 21 transcriptional networks. RACE connection networks in all 10 assayed cell types are represented. In each plot, the chromosome is depicted as a circle, and RACEfrag connections as inner links between genomic regions (5′ and 3′ RACE connections are red and blue, respectively). The circular tracks are, going inwards: (1) - chromosome scale (in megabases, starting at 14 Mb), (2) - plus-strand annotated genes (green), (3) - plus-strand annotated pseudogenes, (4) - minus-strand annotated genes, (5) - minus-strand annotated pseudogenes.
[Show abstract][Hide abstract] ABSTRACT: This book provides an entry point into Systems Biology for researchers in genetics, molecular biology, cell biology, microbiology and biomedical science to understand the key concepts to expanding their work. Chapters organized around broader themes of Organelles and Organisms, Systems Properties of Biological Processes, Cellular Networks, and Systems Biology and Disease discuss the development of concepts, the current applications, and the future prospects. Emphasis is placed on concepts and insights into the multi-disciplinary nature of the field as well as the importance of systems biology in human biological research. Technology, being an extremely important aspect of scientific progress overall, and in the creation of new fields in particular, is discussed in 'boxes' within each chapter to relate to appropriate topics. 2013 Honorable Mention for Single Volume Reference in Science from the Association of American Publishers' PROSE Awards Emphasizes the interdisciplinary nature of systems biology wi
[Show abstract][Hide abstract] ABSTRACT: Cyclin D-dependent kinases (CDK4 and CDK6) are positive regulators of cell cycle entry and they are overactive in the majority of human cancers. However, it is currently not completely understood by which cellular mechanisms CDK4/6 promote tumorigenesis, largely due to the limited number of identified substrates. Here we performed a systematic screen for substrates of cyclin D1-CDK4 and cyclin D3-CDK6. We identified the Forkhead Box M1 (FOXM1) transcription factor as a common critical phosphorylation target. CDK4/6 stabilize and activate FOXM1, thereby maintain expression of G1/S phase genes, suppress the levels of reactive oxygen species (ROS), and protect cancer cells from senescence. Melanoma cells, unlike melanocytes, are highly reliant on CDK4/6-mediated senescence suppression, which makes them particularly susceptible to CDK4/6 inhibition.
[Show abstract][Hide abstract] ABSTRACT: Differentiated mammary epithelium shows apicobasal polarity, and loss of tissue organization is an early hallmark of breast carcinogenesis. In BRCA1 mutation carriers, accumulation of stem and progenitor cells in normal breast tissue and increased risk of developing tumors of basal-like type suggest that BRCA1 regulates stem/progenitor cell proliferation and differentiation. However, the function of BRCA1 in this process and its link to carcinogenesis remain unknown. Here we depict a molecular mechanism involving BRCA1 and RHAMM that regulates apicobasal polarity and, when perturbed, may increase risk of breast cancer. Starting from complementary genetic analyses across families and populations, we identified common genetic variation at the low-penetrance susceptibility HMMR locus (encoding for RHAMM) that modifies breast cancer risk among BRCA1, but probably not BRCA2, mutation carriers: n = 7,584, weighted hazard ratio ((w)HR) = 1.09 (95% CI 1.02-1.16), p(trend) = 0.017; and n = 3,965, (w)HR = 1.04 (95% CI 0.94-1.16), p(trend) = 0.43; respectively. Subsequently, studies of MCF10A apicobasal polarization revealed a central role for BRCA1 and RHAMM, together with AURKA and TPX2, in essential reorganization of microtubules. Mechanistically, reorganization is facilitated by BRCA1 and impaired by AURKA, which is regulated by negative feedback involving RHAMM and TPX2. Taken together, our data provide fundamental insight into apicobasal polarization through BRCA1 function, which may explain the expanded cell subsets and characteristic tumor type accompanying BRCA1 mutation, while also linking this process to sporadic breast cancer through perturbation of HMMR/RHAMM.
[Show abstract][Hide abstract] ABSTRACT: Four different SYP proteins (SYP-1, SYP-2, SYP-3, and SYP-4) have been proposed to form the central region of the synaptonemal complex (SC) thereby bridging the axes of paired meiotic chromosomes in Caenorhabditis elegans. Their interdependent localization suggests that they may interact within the SC. Our studies reveal for the first time how these SYP proteins are organized in the central region of the SC. Yeast two-hybrid and co-immunoprecipitation studies show that SYP-1 is the only SYP protein that is capable of homotypic interactions, and is able to interact with both SYP-2 and SYP-3 directly, whereas SYP-2 and SYP-3 do not seem to interact with each other. Specifically, the coiled-coil domain of SYP-1 is required both for its homotypic interactions and its interaction with the C-terminal domain of SYP-2. Meanwhile, SYP-3 interacts with the C-terminal end of SYP-1 via its N-terminal domain. Immunoelectron microscopy analysis provides insight into the orientation of these proteins within the SC. While the C-terminal domain of SYP-3 localizes in close proximity to the chromosome axes, the N-terminal domains of both SYP-1 and SYP-4, as well as the C-terminal domain of SYP-2, are located in the middle of the SC. Taking into account the different sizes of these proteins, their interaction abilities, and their orientation within the SC, we propose a model of how the SYP proteins link the homologous axes to provide the conserved structure and width of the SC in C. elegans.
[Show abstract][Hide abstract] ABSTRACT: Plants have unique features that evolved in response to their environments and ecosystems. A full account of the complex cellular networks that underlie plant-specific functions is still missing. We describe a proteome-wide binary protein-protein interaction map for the interactome network of the plant Arabidopsis thaliana containing about 6200 highly reliable interactions between about 2700 proteins. A global organization of plant biological processes emerges from community analyses of the resulting network, together with large numbers of novel hypothetical functional links between proteins and pathways. We observe a dynamic rewiring of interactions following gene duplication events, providing evidence for a model of evolution acting upon interactome networks. This and future plant interactome maps should facilitate systems approaches to better understand plant biology and improve crops.
[Show abstract][Hide abstract] ABSTRACT: Plants generate effective responses to infection by recognizing both conserved and variable pathogen-encoded molecules. Pathogens deploy virulence effector proteins into host cells, where they interact physically with host proteins to modulate defense. We generated an interaction network of plant-pathogen effectors from two pathogens spanning the eukaryote-eubacteria divergence, three classes of Arabidopsis immune system proteins, and ~8000 other Arabidopsis proteins. We noted convergence of effectors onto highly interconnected host proteins and indirect, rather than direct, connections between effectors and plant immune receptors. We demonstrated plant immune system functions for 15 of 17 tested host proteins that interact with effectors from both pathogens. Thus, pathogens from different kingdoms deploy independently evolved virulence proteins that interact with a limited set of highly connected cellular hubs to facilitate their diverse life-cycle strategies.
[Show abstract][Hide abstract] ABSTRACT: Functional characterization of the human genome requires tools for systematically modulating gene expression in both loss-of-function and gain-of-function experiments. We describe the production of a sequence-confirmed, clonal collection of over 16,100 human open-reading frames (ORFs) encoded in a versatile Gateway vector system. Using this ORFeome resource, we created a genome-scale expression collection in a lentiviral vector, thereby enabling both targeted experiments and high-throughput screens in diverse cell types.
[Show abstract][Hide abstract] ABSTRACT: Supplementary Figure 1 Pilot experiments to optimize pooling strategy for next-generation sequencing of ORF clones.
Supplementary Figure 2 Coverage histograms of sequencing hORFeome V8.1.
Supplementary Figure 3 Flowchart of hORFeome V8.1 creation.
Supplementary Figure 4 Alignment results of 14,524 completely sequenced clones with current NCBI RefSeq transcripts.
Supplementary Figure 5 Plasmid maps of pLX lentiviral expression vectors created as part of this study.
Supplementary Figure 6 Confirmation of viral preparations.
Supplementary Figure 7 Determination of virus titer and ORF expression.
Supplementary Figure 8 Virus titer and ORF expression are maintained across a wide range of ORF lengths.
Supplementary Figure 9 Western blot showing expressed ORFs.
Supplementary Figure 10 Viral preparations enable immunofluoresence high throughout screens.
Supplementary Table 1a Clonal and sequenced ORF Gateway entry clone collections
Supplementary Table 1b Comparison of Nomura and CCSB-Broad ORF collections
Supplementary Table 2 Illumina sequencing pilot data
Supplementary Table 3 Overview of next generation sequencing results
Supplementary Table 4 Annotated list of hORFeome V8.1 and CCSB-Broad Lentiviral Expresson Library.
Supplementary Note 1 Availability of clones and distribution procedures
Supplementary Note 2 Pilot experiments to determine number of colonies to isolate per polyclonal ORF.
Supplementary Note 3 Supplementing hORFeome V8.1 with kinase ORFs.
Supplementary Note 4 Challenges of completing the human ORFeome
Supplementary Note 5 Detailed high-throughput protocol of single colony isolation.
Supplementary Note 6 Details of pooled sequencing protocol optimization experiments.
Supplementary Note 7 Computing virus titers.
Supplementary Note 8 Li-COR in-cell Western and immunoblotting.