Phylogenetic Position of a Copper Age Sheep (Ovis aries) Mitochondrial DNA

BACKGROUND: Sheep (Ovis aries) were domesticated in the Fertile Crescent region about 9,000-8,000 years ago. Currently, few mitochondrial (mt) DNA studies are available on archaeological sheep. In particular, no data on archaeological European sheep are available. METHODOLOGY/PRINCIPAL FINDINGS: Here we describe the first portion of mtDNA sequence of a Copper Age European sheep. DNA was extracted from hair shafts which were part of the clothes of the so-called Tyrolean Iceman or Ötzi (5,350-5,100 years before present). Mitochondrial DNA (a total of 2,429 base pairs, encompassing a portion of the control region, tRNA(Phe), a portion of the 12S rRNA gene, and the whole cytochrome B gene) was sequenced using a mixed sequencing procedure based on PCR amplification and 454 sequencing of pooled amplification products. We have compared the sequence with the corresponding sequence of 334 extant lineages. CONCLUSIONS/SIGNIFICANCE: A phylogenetic network based on a new cladistic notation for the mitochondrial diversity of domestic sheep shows that the Ötzi's sheep falls within haplogroup B, thus demonstrating that sheep belonging to this haplogroup were already present in the Alps more than 5,000 years ago. On the other hand, the lineage of the Ötzi's sheep is defined by two transitions (16147, and 16440) which, assembled together, define a motif that has not yet been identified in modern sheep populations

Trans-Species Polymorphism and Selection in the MHC Class II DRA Genes of Domestic Sheep

Highly polymorphic genes with central roles in lymphocyte mediated immune surveillance are grouped together in the major histocompatibility complex (MHC) in higher vertebrates. Generally, across vertebrate species the class II MHC DRA gene is highly conserved with only limited allelic variation. Here however, we provide evidence of trans-species polymorphism at the DRA locus in domestic sheep (Ovis aries). We describe variation at the Ovar-DRA locus that is far in excess of anything described in other vertebrate species. The divergent DRA allele (Ovar-DRA*0201) differs from the sheep reference sequences by 20 nucleotides, 12 of which appear non-synonymous. Furthermore, DRA*0201 is paired with an equally divergent DRB1 allele (Ovar-DRB1*0901), which is consistent with an independent evolutionary history for the DR sub-region within this MHC haplotype. No recombination was observed between the divergent DRA and B genes in a range of breeds and typical levels of MHC class II DR protein expression were detected at the surface of leukocyte populations obtained from animals homozygous for the DRA*0201, DRB1*0901 haplotype. Bayesian phylogenetic analysis groups Ovar-DRA*0201 with DRA sequences derived from species within the Oryx and Alcelaphus genera rather than clustering with other ovine and caprine DRA alleles. Tests for Darwinian selection identified 10 positively selected sites on the branch leading to Ovar-DRA*0201, three of which are predicted to be associated with the binding of peptide antigen. As the Ovis, Oryx and Alcelaphus genera have not shared a common ancestor for over 30 million years, the DRA*0201 and DRB1*0901 allelic pair is likely to be of ancient origin and present in the founding population from which all contemporary domestic sheep breeds are derived. The conservation of the integrity of this unusual DR allelic pair suggests some selective advantage which is likely to be associated with the presentation of pathogen antigen to T-cells and the induction of protective immunity

Precise Regulation of Gene Expression Dynamics Favors Complex Promoter Architectures

Promoters process signals through recruitment of transcription factors and RNA polymerase, and dynamic changes in promoter activity constitute a major noise source in gene expression. However, it is barely understood how complex promoter architectures determine key features of promoter dynamics. Here, we employ prototypical promoters of yeast ribosomal protein genes as well as simplified versions thereof to analyze the relations among promoter design, complexity, and function. These promoters combine the action of a general regulatory factor with that of specific transcription factors, a common motif of many eukaryotic promoters. By comprehensively analyzing stationary and dynamic promoter properties, this model-based approach enables us to pinpoint the structural characteristics underlying the observed behavior. Functional tradeoffs impose constraints on the promoter architecture of ribosomal protein genes. We find that a stable scaffold in the natural design results in low transcriptional noise and strong co-regulation of target genes in the presence of gene silencing. This configuration also exhibits superior shut-off properties, and it can serve as a tunable switch in living cells. Model validation with independent experimental data suggests that the models are sufficiently realistic. When combined, our results offer a mechanistic explanation for why specific factors are associated with low protein noise in vivo. Many of these findings hold for a broad range of model parameters and likely apply to other eukaryotic promoters of similar structure

Noise Reduction by Diffusional Dissipation in a Minimal Quorum Sensing Motif

Cellular interactions are subject to random fluctuations (noise) in quantities of interacting molecules. Noise presents a major challenge for the robust function of natural and engineered cellular networks. Past studies have analyzed how noise is regulated at the intracellular level. Cell–cell communication, however, may provide a complementary strategy to achieve robust gene expression by enabling the coupling of a cell with its environment and other cells. To gain insight into this issue, we have examined noise regulation by quorum sensing (QS), a mechanism by which many bacteria communicate through production and sensing of small diffusible signals. Using a stochastic model, we analyze a minimal QS motif in Gram-negative bacteria. Our analysis shows that diffusion of the QS signal, together with fast turnover of its transcriptional regulator, attenuates low-frequency components of extrinsic noise. We term this unique mechanism “diffusional dissipation” to emphasize the importance of fast signal turnover (or dissipation) by diffusion. We further show that this noise attenuation is a property of a more generic regulatory motif, of which QS is an implementation. Our results suggest that, in a QS system, an unstable transcriptional regulator may be favored for regulating expression of costly proteins that generate public goods

Mitochondrial Variability as a Source of Extrinsic Cellular Noise

We present a study investigating the role of mitochondrial variability in generating noise in eukaryotic cells. Noise in cellular physiology plays an important role in many fundamental cellular processes, including transcription, translation, stem cell differentiation and response to medication, but the specific random influences that affect these processes have yet to be clearly elucidated. Here we present a mechanism by which variability in mitochondrial volume and functionality, along with cell cycle dynamics, is linked to variability in transcription rate and hence has a profound effect on downstream cellular processes. Our model mechanism is supported by an appreciable volume of recent experimental evidence, and we present the results of several new experiments with which our model is also consistent. We find that noise due to mitochondrial variability can sometimes dominate over other extrinsic noise sources (such as cell cycle asynchronicity) and can significantly affect large-scale observable properties such as cell cycle length and gene expression levels. We also explore two recent regulatory network-based models for stem cell differentiation, and find that extrinsic noise in transcription rate causes appreciable variability in the behaviour of these model systems. These results suggest that mitochondrial and transcriptional variability may be an important mechanism influencing a large variety of cellular processes and properties

Diploids in the Cryptococcus neoformans Serotype A Population Homozygous for the α Mating Type Originate via Unisexual Mating

The ubiquitous environmental human pathogen Cryptococcus neoformans is traditionally considered a haploid fungus with a bipolar mating system. In nature, the α mating type is overwhelmingly predominant over a. How genetic diversity is generated and maintained by this heterothallic fungus in a largely unisexual α population is unclear. Recently it was discovered that C. neoformans can undergo same-sex mating under laboratory conditions generating both diploid intermediates and haploid recombinant progeny. Same-sex mating (α-α) also occurs in nature as evidenced by the existence of natural diploid αADα hybrids that arose by fusion between two α cells of different serotypes (A and D). How significantly this novel sexual style contributes to genetic diversity of the Cryptococcus population was unknown. In this study, ∼500 natural C. neoformans isolates were tested for ploidy and close to 8% were found to be diploid by fluorescence flow cytometry analysis. The majority of these diploids were serotype A isolates with two copies of the α MAT locus allele. Among those, several are intra-varietal allodiploid hybrids produced by fusion of two genetically distinct α cells through same-sex mating. The majority, however, are autodiploids that harbor two seemingly identical copies of the genome and arose via either endoreplication or clonal mating. The diploids identified were isolated from different geographic locations and varied genotypically and phenotypically, indicating independent non-clonal origins. The present study demonstrates that unisexual mating produces diploid isolates of C. neoformans in nature, giving rise to populations of hybrids and mixed ploidy. Our findings underscore the importance of same-sex mating in shaping the current population structure of this important human pathogenic fungus, with implications for mechanisms of selfing and inbreeding in other microbial pathogens

Identification of novel targets for breast cancer by exploring gene switches on a genome scale

<p>Abstract</p> <p>Background</p> <p>An important feature that emerges from analyzing gene regulatory networks is the "switch-like behavior" or "bistability", a dynamic feature of a particular gene to preferentially toggle between two steady-states. The state of gene switches plays pivotal roles in cell fate decision, but identifying switches has been difficult. Therefore a challenge confronting the field is to be able to systematically identify gene switches.</p> <p>Results</p> <p>We propose a top-down mining approach to exploring gene switches on a genome-scale level. Theoretical analysis, proof-of-concept examples, and experimental studies demonstrate the ability of our mining approach to identify bistable genes by sampling across a variety of different conditions. Applying the approach to human breast cancer data identified genes that show bimodality within the cancer samples, such as estrogen receptor (ER) and ERBB2, as well as genes that show bimodality between cancer and non-cancer samples, where tumor-associated calcium signal transducer 2 (TACSTD2) is uncovered. We further suggest a likely transcription factor that regulates TACSTD2.</p> <p>Conclusions</p> <p>Our mining approach demonstrates that one can capitalize on genome-wide expression profiling to capture dynamic properties of a complex network. To the best of our knowledge, this is the first attempt in applying mining approaches to explore gene switches on a genome-scale, and the identification of TACSTD2 demonstrates that single cell-level bistability can be predicted from microarray data. Experimental confirmation of the computational results suggest TACSTD2 could be a potential biomarker and attractive candidate for drug therapy against both ER+ and ER- subtypes of breast cancer, including the triple negative subtype.</p

Empirical mean-noise fitness landscapes reveal the fitness impact of gene expression noise

The effects of cell-to-cell variation (noise) in gene expression have proven difficult to quantify because of the mechanistic coupling of noise to mean expression. To independently quantify the effects of changes in mean expression and noise we determine the fitness landscapes in mean-noise expression space for 33 genes in yeast. For most genes, short-lived (noise) deviations away from the expression optimum are nearly as detrimental as sustained (mean) deviations. Fitness landscapes can be classified by a combination of each gene's sensitivity to protein shortage or surplus. We use this classification to explore evolutionary scenarios for gene expression and find that certain landscape topologies can break the mechanistic coupling of mean and noise, thus promoting independent optimization of both properties. These results demonstrate that noise is detrimental for many genes and reveal non-trivial consequences of mean-noise-fitness topologies for the evolution of gene expression systems.This work was supported by a European Research Council Consolidator grant (616434), the Spanish Ministry of Economy and Competitiveness (BFU2011–26206 and SEV-2012–0208), the AXA Research Fund, Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR, 2014SGR831), FP7 project 4DCellFate (277899), the EMBL-CRG Systems Biology Program (all to B.L.), an EMBO Long-Term Fellowship (ALTF 857–2016), the European Union’s Horizon 2020 research and innovation programme (Marie Skłodowska-Curie grant agreement No 752809) (both to J.M.S.) an AGAUR grant (2014SGR0974) and a MINECO grant (BFU2015–68351-P) (both to L.B.C.). The authors acknowledge support from the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership, the Centro de Excelencia Severo Ochoa, and the CERCA Programme / Generalitat de Catalunya