Nonidentifiability of the Source of Intrinsic Noise in Gene Expression from Single-Burst Data

Over the last few years, experimental data on the fluctuations in gene activity between individual cells and within the same cell over time have confirmed that gene expression is a “noisy” process. This variation is in part due to the small number of molecules taking part in some of the key reactions that are involved in gene expression. One of the consequences of this is that protein production often occurs in bursts, each due to a single promoter or transcription factor binding event. Recently, the distribution of the number of proteins produced in such bursts has been experimentally measured, offering a unique opportunity to study the relative importance of different sources of noise in gene expression. Here, we provide a derivation of the theoretical probability distribution of these bursts for a wide variety of different models of gene expression. We show that there is a good fit between our theoretical distribution and that obtained from two different published experimental datasets. We then prove that, irrespective of the details of the model, the burst size distribution is always geometric and hence determined by a single parameter. Many different combinations of the biochemical rates for the constituent reactions of both transcription and translation will therefore lead to the same experimentally observed burst size distribution. It is thus impossible to identify different sources of fluctuations purely from protein burst size data or to use such data to estimate all of the model parameters. We explore methods of inferring these values when additional types of experimental data are available

Effect of promoter architecture on the cell-to-cell variability in gene expression

According to recent experimental evidence, the architecture of a promoter, defined as the number, strength and regulatory role of the operators that control the promoter, plays a major role in determining the level of cell-to-cell variability in gene expression. These quantitative experiments call for a corresponding modeling effort that addresses the question of how changes in promoter architecture affect noise in gene expression in a systematic rather than case-by-case fashion. In this article, we make such a systematic investigation, based on a simple microscopic model of gene regulation that incorporates stochastic effects. In particular, we show how operator strength and operator multiplicity affect this variability. We examine different modes of transcription factor binding to complex promoters (cooperative, independent, simultaneous) and how each of these affects the level of variability in transcription product from cell-to-cell. We propose that direct comparison between in vivo single-cell experiments and theoretical predictions for the moments of the probability distribution of mRNA number per cell can discriminate between different kinetic models of gene regulation.Comment: 35 pages, 6 figures, Submitte

Capacity and Procedural Accounts of Impaired Memory in Depression

Findings of impaired memory in states of dysphoria or depression are summarized and subsumed under different accounts of mood-related memory deficits. Theoretical accounts based on the assumption of a storage system of limited capacity are compared to accounts which emphasize the role of procedures and strategies in attending and remembering. Two reanalyses of a recent experiment in the process-dissociation paradigm are reported. They address issues of dysphoria-related differences in automatic versus controlled uses of memory in a task of word-stem completion. The two reanalyses rest on different assumptions about the relation between automatic and controlled components, but they converge in highlighting the advantages of a procedural rather than capacity-based view of memory deficits. finally. similarities to other research domains and theoretical approaches are outlined

Rhizobium Promotes Non-Legumes Growth and Quality in Several Production Steps: Towards a Biofertilization of Edible Raw Vegetables Healthy for Humans

The biofertilization of crops with plant-growth-promoting microorganisms is currently considered as a healthy alternative to chemical fertilization. However, only microorganisms safe for humans can be used as biofertilizers, particularly in vegetables that are raw consumed, in order to avoid sanitary problems derived from the presence of pathogenic bacteria in the final products. In the present work we showed that Rhizobium strains colonize the roots of tomato and pepper plants promoting their growth in different production stages increasing yield and quality of seedlings and fruits. Our results confirmed those obtained in cereals and alimentary oil producing plants extending the number of non-legumes susceptible to be biofertilized with rhizobia to those whose fruits are raw consumed. This is a relevant conclusion since safety of rhizobia for human health has been demonstrated after several decades of legume inoculation ensuring that they are optimal bacteria for biofertilization

A comprehensive analysis of common genetic variation in prolactin (PRL) and PRL receptor (PRLR) genes in relation to plasma prolactin levels and breast cancer risk: the Multiethnic Cohort

<p>Abstract</p> <p>Background</p> <p>Studies in animals and humans clearly indicate a role for prolactin (PRL) in breast epithelial proliferation, differentiation, and tumorigenesis. Prospective epidemiological studies have also shown that women with higher circulating PRL levels have an increase in risk of breast cancer, suggesting that variability in PRL may also be important in determining a woman's risk.</p> <p>Methods</p> <p>We evaluated genetic variation in the PRL and PRL receptor (PRLR) genes as predictors of plasma PRL levels and breast cancer risk among African-American, Native Hawaiian, Japanese-American, Latina, and White women in the Multiethnic Cohort Study (MEC). We selected single nucleotide polymorphisms (SNPs) from both the public (dbSNP) and private (Celera) databases to construct high density SNP maps that included up to 20 kilobases (kb) upstream of the transcription initiation site and 10 kb downstream of the last exon of each gene, for a total coverage of 59 kb in PRL and 210 kb in PRLR. We genotyped 80 SNPs in PRL and 173 SNPs in PRLR in a multiethnic panel of 349 unaffected subjects to characterize linkage disequilibrium (LD) and haplotype patterns. We sequenced the coding regions of PRL and PRLR in 95 advanced breast cancer cases (19 of each racial/ethnic group) to uncover putative functional variation. A total of 33 and 60 haplotype "tag" SNPs (tagSNPs) that allowed for high predictability (R_h²≥ 0.70) of the common haplotypes in PRL and PRLR, respectively, were then genotyped in a multiethnic breast cancer case-control study of 1,615 invasive breast cancer cases and 1,962 controls in the MEC. We also assessed the association of common genetic variation with circulating PRL levels in 362 postmenopausal controls without a history of hormone therapy use at blood draw. Because of the large number of comparisons being performed we used a relatively stringent type I error criteria (p < 0.0005) for evaluating the significance of any single association to correct for performing approximately 100 independent tests, close to the number of tagSNPs genotyped for both genes.</p> <p>Results</p> <p>We observed no significant associations between PRL and PRLR haplotypes or individual SNPs in relation to breast cancer risk. A nominally significant association was noted between prolactin levels and a tagSNP (tagSNP 44, rs2244502) in intron 1 of PRL. This SNP showed approximately a 50% increase in levels between minor allele homozygotes vs. major allele homozygotes. However, this association was not significant (p = 0.002) using our type I error criteria to correct for multiple testing, nor was this SNP associated with breast cancer risk (p = 0.58).</p> <p>Conclusion</p> <p>In this comprehensive analysis covering 59 kb of the PRL locus and 210 kb of the PRLR locus, we found no significant association between common variation in these candidate genes and breast cancer risk or plasma PRL levels. The LD characterization of PRL and PRLR in this multiethnic population provide a framework for studying these genes in relation to other disease outcomes that have been associated with PRL, as well as for larger studies of plasma PRL levels.</p

The Haploinsufficient Hematopoietic Microenvironment Is Critical to the Pathological Fracture Repair in Murine Models of Neurofibromatosis Type 1

Germline mutations in the NF1 tumor suppressor gene cause neurofibromatosis type 1 (NF1), a complex genetic disorder with a high predisposition of numerous skeletal dysplasias including short stature, osteoporosis, kyphoscoliosis, and fracture non-union (pseudoarthrosis). We have developed murine models that phenocopy many of the skeletal dysplasias observed in NF1 patients, including reduced bone mass and fracture non-union. We also show that the development of these skeletal manifestations requires an Nf1 haploinsufficient background in addition to nullizygous loss of Nf1 in mesenchymal stem/progenitor cells (MSCs) and/or their progenies. This is replicated in two animal models of NF1, PeriCre+;Nf1flox/− and Col2.3Cre+;Nf1flox/−mice. Adoptive transfer experiments demonstrate a critical role of the Nf1+/− marrow microenvironment in the impaired fracture healing in both models and adoptive transfer of WT bone marrow cells improves fracture healing in these mice. To our knowledge, this is the first demonstration of a non-cell autonomous mechanism in non-malignant NF1 manifestations. Collectively, these data provide evidence of a combinatory effect between nullizygous loss of Nf1 in osteoblast progenitors and haploinsufficiency in hematopoietic cells in the development of non-malignant NF1 manifestations

Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas

Summary Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (TP53, ATRX, RB1) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types

Search for neutral MSSM Higgs bosons decaying to a pair of tau leptons in pp collisions

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