| 1. |
- Hurst, Laurence D., et al.
(författare)
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A simple metric of promoter architecture robustly predicts expression breadth of human genes suggesting that most transcription factors are positive regulators
- 2014
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Ingår i: Genome Biology. - : Springer Science and Business Media LLC. - 1465-6906 .- 1474-760X. ; 15:7, s. 413-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Conventional wisdom holds that, owing to the dominance of features such as chromatin level control, the expression of a gene cannot be readily predicted from knowledge of promoter architecture. This is reflected, for example, in a weak or absent correlation between promoter divergence and expression divergence between paralogs. However, an inability to predict may reflect an inability to accurately measure or employment of the wrong parameters. Here we address this issue through integration of two exceptional resources: ENCODE data on transcription factor binding and the FANTOM5 high-resolution expression atlas. Results: Consistent with the notion that in eukaryotes most transcription factors are activating, the number of transcription factors binding a promoter is a strong predictor of expression breadth. In addition, evolutionarily young duplicates have fewer transcription factor binders and narrower expression. Nonetheless, we find several binders and cooperative sets that are disproportionately associated with broad expression, indicating that models more complex than simple correlations should hold more predictive power. Indeed, a machine learning approach improves fit to the data compared with a simple correlation. Machine learning could at best moderately predict tissue of expression of tissue specific genes. Conclusions: We find robust evidence that some expression parameters and paralog expression divergence are strongly predictable with knowledge of transcription factor binding repertoire. While some cooperative complexes can be identified, consistent with the notion that most eukaryotic transcription factors are activating, a simple predictor, the number of binding transcription factors found on a promoter, is a robust predictor of expression breadth.
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| 2. |
- Hurst, Laurence D., et al.
(författare)
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The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome
- 2015
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Ingår i: PLoS biology. - : Public Library of Science (PLoS). - 1544-9173 .- 1545-7885. ; 13:12
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Tidskriftsartikel (refereegranskat)abstract
- X chromosomes are unusual in many regards, not least of which is their nonrandom gene content. The causes of this bias are commonly discussed in the context of sexual antagonism and the avoidance of activity in the male germline. Here, we examine the notion that, at least in some taxa, functionally biased gene content may more profoundly be shaped by limits imposed on gene expression owing to haploid expression of the X chromosome. Notably, if the X, as in primates, is transcribed at rates comparable to the ancestral rate (per promoter) prior to the X chromosome formation, then the X is not a tolerable environment for genes with very high maximal net levels of expression, owing to transcriptional traffic jams. We test this hypothesis using The Encyclopedia of DNA Elements (ENCODE) and data from the Functional Annotation of the Mammalian Genome (FANTOM5) project. As predicted, the maximal expression of human X-linked genes is much lower than that of genes on autosomes: on average, maximal expression is three times lower on the X chromosome than on autosomes. Similarly, autosome-to-X retroposition events are associated with lower maximal expression of retrogenes on the X than seen for X-to-autosome retrogenes on autosomes. Also as expected, X-linked genes have a lesser degree of increase in gene expression than autosomal ones (compared to the human/Chimpanzee common ancestor) if highly expressed, but not if lowly expressed. The traffic jam model also explains the known lower breadth of expression for genes on the X (and the Z of birds), as genes with broad expression are, on average, those with high maximal expression. As then further predicted, highly expressed tissue-specific genes are also rare on the X and broadly expressed genes on the X tend to be lowly expressed, both indicating that the trend is shaped by the maximal expression level not the breadth of expression per se. Importantly, a limit to the maximal expression level explains biased tissue of expression profiles of X-linked genes. Tissues whose tissue-specific genes are very highly expressed (e.g., secretory tissues, tissues abundant in structural proteins) are also tissues in which gene expression is relatively rare on the X chromosome. These trends cannot be fully accounted for in terms of alternative models of biased expression. In conclusion, the notion that it is hard for genes on the Therian X to be highly expressed, owing to transcriptional traffic jams, provides a simple yet robustly supported rationale of many peculiar features of X's gene content, gene expression, and evolution.
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| 3. |
- Webster, Matthew T., et al.
(författare)
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Direct and indirect consequences of meiotic recombination : implications for genome evolution
- 2012
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Ingår i: Trends in Genetics. - : Elsevier BV. - 0168-9525 .- 1362-4555. ; 28:3, s. 101-109
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Forskningsöversikt (refereegranskat)abstract
- There is considerable variation within eukaryotic genomes in the local rate of crossing over. Why is this and what effect does it have on genome evolution? On the genome scale, it is known that by shuffling alleles, recombination increases the efficacy of selection. By contrast, the extent to which differences in the recombination rate modulate the efficacy of selection between genomic regions is unclear. Recombination also has direct consequences on the origin and fate of mutations: biased gene conversion and other forms of meiotic drive promote the fixation of mutations in a similar way to selection, and recombination itself may be mutagenic. Consideration of both the direct and indirect effects of recombination is necessary to understand why its rate is so variable and for correct interpretation of patterns of genome evolution.
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| 4. |
- Yokoyama, Maho, et al.
(författare)
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Epistasis analysis uncovers hidden antibiotic resistance-associated fitness costs hampering the evolution of MRSA
- 2018
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Ingår i: Genome Biology. - : Springer Science and Business Media LLC. - 1474-7596 .- 1474-760X. ; 19:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Fitness costs imposed on bacteria by antibiotic resistance mechanisms are believed to hamper their dissemination. The scale of these costs is highly variable. Some, including resistance of Staphylococcus aureus to the clinically important antibiotic mupirocin, have been reported as being cost-free, which suggests that there are few barriers preventing their global spread. However, this is not supported by surveillance data in healthy communities, which indicate that this resistance mechanism is relatively unsuccessful. Results: Epistasis analysis on two collections of MRSA provides an explanation for this discord, where the mupirocin resistance-conferring mutation of the ileS gene appears to affect the levels of toxins produced by S. aureus when combined with specific polymorphisms at other loci. Proteomic analysis demonstrates that the activity of the secretory apparatus of the PSM family of toxins is affected by mupirocin resistance. As an energetically costly activity, this reduction in toxicity masks the fitness costs associated with this resistance mutation, a cost that becomes apparent when toxin production becomes necessary. This hidden fitness cost provides a likely explanation for why this mupirocin-resistance mechanism is not more prevalent, given the widespread use of this antibiotic. Conclusions: With dwindling pools of antibiotics available for use, information on the fitness consequences of the acquisition of resistance may need to be considered when designing antibiotic prescribing policies. However, this study suggests there are levels of depth that we do not understand, and that holistic, surveillance and functional genomics approaches are required to gain this crucial information.
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