Spontaneous mutation rate in the smallest photosynthetic eukaryotes

Mutation is the ultimate source of genetic variation, and knowledge of mutation rates is fundamental for our understanding of all evolutionary processes. High throughput sequencing of mutation accumulation lines has provided genome wide spontaneous mutation rates in a dozen model species, but estimates from nonmodel organisms from much of the diversity of life are very limited. Here, we report mutation rates in four haploid marine bacterial-sized photosynthetic eukaryotic algae; Bathycoccus prasinos, Ostreococcus tauri, Ostreococcus mediterraneus, and Micromonas pusilla. The spontaneous mutation rate between species varies from μ = 4.4 × 10−10 to 9.8 × 10−10 mutations per nucleotide per generation. Within genomes, there is a two-fold increase of the mutation rate in intergenic regions, consistent with an optimization of mismatch and transcription-coupled DNA repair in coding sequences. Additionally, we show that deviation from the equilibrium GC content increases the mutation rate by ∼2% to ∼12% because of a GC bias in coding sequences. More generally, the difference between the observed and equilibrium GC content of genomes explains some of the inter-specific variation in mutation rates

Quantifying extreme behaviour in geomagnetic activity

Understanding the extremes in geomagnetic activity is an important component in understanding just how severe conditions can become in the terrestrial space environment. Extreme activity also has consequences for technological systems. On the ground, extreme geomagnetic behavior has an impact on navigation and position accuracy and the operation of power grids and pipeline networks. We therefore use a number of decades of one-minute mean magnetic data from magnetic observatories in Europe, together with the technique of extreme value statistics, to provide a preliminary exploration of the extremes in magnetic field variations and their one-minute rates of change. These extremes are expressed in terms of the variations that might be observed every 100 and 200 years in the horizontal strength and in the declination of the field. We find that both measured and extrapolated extreme values generally increase with geomagnetic latitude (as might be expected), though there is a marked maximum in estimated extreme levels between about 53 and 62 degrees north. At typical midlatitude European observatories (55–60 degrees geomagnetic latitude), compass variations may reach approximately 3–8 degrees/minute, and horizontal field changes may reach 1000–4000 nT/minute, in one magnetic storm once every 100 years. For storm return periods of 200 years the equivalent figures are 4–11 degrees/minute and 1000–6000 nT/minute

Molecular brakes regulating mTORC1 activation in skeletal muscle following synergist ablation

The goal of the current work was to profile positive (mTORC1 activation, autocrine/paracrine growth factors) and negative [AMPK, unfolded protein response (UPR)] pathways that might regulate overload-induced mTORC1 (mTOR complex 1) activation with the hypothesis that a number of negative regulators of mTORC1 will be engaged during a supraphysiological model of hypertrophy. To achieve this, mTORC1- IRS-1/2 signaling, BiP/CHOP/IRE1, and AMPK activation were determined in rat plantaris muscle following synergist ablation (SA). SA resulted in significant increases in muscle mass of 4% per day throughout the 21 days of the experiment. The expression of the insulin-like growth factors (IGF) were high throughout the 21st day of overload. However, IGF signaling was limited, since IRS-1 and -2 were undetectable in the overloaded muscle from day 3 to day 9. The decreases in IRS-1/2 protein were paralleled by increases in GRB10 Ser501/503 and S6K1 Thr389 phosphorylation, two mTORC1 targets that can destabilize IRS proteins. PKB Ser473 phosphorylation was higher from 3– 6 days, and this was associated with increased TSC2 Thr939 phosphorylation. The phosphorylation of TSC2 Thr1345 (an AMPK site) was also elevated, whereas phosphorylation at the other PKB site, Thr1462, was unchanged at 6 days. In agreement with the phosphorylation of Thr1345, SA led to activation of AMPK1 during the initial growth phase, lasting the first 9 days before returning to baseline by day 12. The UPR markers CHOP and BiP were elevated over the first 12 days following ablation, whereas IRE1 levels decreased. These data suggest that during supraphysiological muscle loading at least three potential molecular brakes engage to downregulate mTORC1. m

Genome architecture enables local adaptation of Atlantic cod despite high connectivity

Adaptation to local conditions is a fundamental process in evolution; however, mechanisms maintaining local adaptation despite high gene flow are still poorly understood. Marine ecosystems provide a wide array of diverse habitats that frequently promote ecological adaptation even in species characterized by strong levels of gene flow. As one example, populations of the marine fish Atlantic cod (Gadus morhua) are highly connected due to immense dispersal capabilities but nevertheless show local adaptation in several key traits. By combining population genomic analyses based on 12K single nucleotide polymorphisms with larval dispersal patterns inferred using a biophysical ocean model, we show that Atlantic cod individuals residing in sheltered estuarine habitats of Scandinavian fjords mainly belong to offshore oceanic populations with considerable connectivity between these diverse ecosystems. Nevertheless, we also find evidence for discrete fjord populations that are genetically differentiated from offshore populations, indicative of local adaptation, the degree of which appears to be influenced by connectivity. Analyses of the genomic architecture reveal a significant overrepresentation of a large ~5 Mb chromosomal rearrangement in fjord cod, previously proposed to comprise genes critical for the survival at low salinities. This suggests that despite considerable connectivity with offshore populations, local adaptation to fjord environments may be enabled by suppression of recombination in the rearranged region. Our study provides new insights into the potential of local adaptation in high gene flow species within fine geographical scales and highlights the importance of genome architecture in analyses of ecological adaptation

Gene flow among wild and domesticated almond species: insights from chloroplast and nuclear markers

Hybridization has played a central role in the evolutionary history of domesticated plants. Notably, several breeding programs relying on gene introgression from the wild compartment have been performed in fruit tree species within the genus Prunus but few studies investigated spontaneous gene flow among wild and domesticated Prunus species. Consequently, a comprehensive understanding of genetic relationships and levels of gene flow between domesticated and wild Prunus species is needed. Combining nuclear and chloroplastic microsatellites, we investigated the gene flow and hybridization among two key almond tree species, the cultivated Prunus dulcis and one of the most widespread wild relative Prunus orientalis in the Fertile Crescent. We detected high genetic diversity levels in both species along with substantial and symmetric gene flow between the domesticated P. dulcis and the wild P. orientalis. These results were discussed in light of the cultivated species diversity, by outlining the frequent spontaneous genetic contributions of wild species to the domesticated compartment. In addition, crop-to-wild gene flow suggests that ad hoc transgene containment strategies would be required if genetically modified cultivars were introduced in the northwestern Mediterranean

Statistical Methodological Issues in Handling of Fatty Acid Data: Percentage or Concentration, Imputation and Indices

Basic aspects in the handling of fatty acid-data have remained largely underexposed. Of these, we aimed to address three statistical methodological issues, by quantitatively exemplifying their imminent confounding impact on analytical outcomes: (1) presenting results as relative percentages or absolute concentrations, (2) handling of missing/non-detectable values, and (3) using structural indices for data-reduction. Therefore, we reanalyzed an example dataset containing erythrocyte fatty acid-concentrations of 137 recurrently depressed patients and 73 controls. First, correlations between data presented as percentages and concentrations varied for different fatty acids, depending on their correlation with the total fatty acid-concentration. Second, multiple imputation of non-detects resulted in differences in significance compared to zero-substitution or omission of non-detects. Third, patients’ chain length-, unsaturation-, and peroxidation-indices were significantly lower compared to controls, which corresponded with patterns interpreted from individual fatty acid tests. In conclusion, results from our example dataset show that statistical methodological choices can have a significant influence on outcomes of fatty acid analysis, which emphasizes the relevance of: (1) hypothesis-based fatty acid-presentation (percentages or concentrations), (2) multiple imputation, preventing bias introduced by non-detects; and (3) the possibility of using (structural) indices, to delineate fatty acid-patterns thereby preventing multiple testing

Ranking differentially expressed genes from Affymetrix gene expression data: methods with reproducibility, sensitivity, and specificity

<p>Abstract</p> <p>Background</p> <p>To identify differentially expressed genes (DEGs) from microarray data, users of the Affymetrix GeneChip system need to select both a preprocessing algorithm to obtain expression-level measurements and a way of ranking genes to obtain the most plausible candidates. We recently recommended suitable combinations of a preprocessing algorithm and gene ranking method that can be used to identify DEGs with a higher level of sensitivity and specificity. However, in addition to these recommendations, researchers also want to know which combinations enhance reproducibility.</p> <p>Results</p> <p>We compared eight conventional methods for ranking genes: weighted average difference (WAD), average difference (AD), fold change (FC), rank products (RP), moderated <it>t </it>statistic (modT), significance analysis of microarrays (samT), shrinkage <it>t </it>statistic (shrinkT), and intensity-based moderated <it>t </it>statistic (ibmT) with six preprocessing algorithms (PLIER, VSN, FARMS, multi-mgMOS (mmgMOS), MBEI, and GCRMA). A total of 36 real experimental datasets was evaluated on the basis of the area under the receiver operating characteristic curve (AUC) as a measure for both sensitivity and specificity. We found that the RP method performed well for VSN-, FARMS-, MBEI-, and GCRMA-preprocessed data, and the WAD method performed well for mmgMOS-preprocessed data. Our analysis of the MicroArray Quality Control (MAQC) project's datasets showed that the FC-based gene ranking methods (WAD, AD, FC, and RP) had a higher level of reproducibility: The percentages of overlapping genes (POGs) across different sites for the FC-based methods were higher overall than those for the <it>t</it>-statistic-based methods (modT, samT, shrinkT, and ibmT). In particular, POG values for WAD were the highest overall among the FC-based methods irrespective of the choice of preprocessing algorithm.</p> <p>Conclusion</p> <p>Our results demonstrate that to increase sensitivity, specificity, and reproducibility in microarray analyses, we need to select suitable combinations of preprocessing algorithms and gene ranking methods. We recommend the use of FC-based methods, in particular RP or WAD.</p

Nicotinic acetylcholine receptor β2 subunit gene implicated in a systems-based candidate gene study of smoking cessation

Although the efficacy of pharmacotherapy for tobacco dependence has been previously demonstrated, there is substantial variability among individuals in treatment response. We performed a systems-based candidate gene study of 1295 single nucleotide polymorphisms (SNPs) in 58 genes within the neuronal nicotinic receptor and dopamine systems to investigate their role in smoking cessation in a bupropion placebo-controlled randomized clinical trial. Putative functional variants were supplemented with tagSNPs within each gene. We used global tests of main effects and treatment interactions, adjusting the P-values for multiple correlated tests. An SNP (rs2072661) in the 3′ UTR region of the β2 nicotinic acetylcholine receptor subunit (CHRNB2) has an impact on abstinence rates at the end of treatment (adjusted P = 0.01) and after a 6-month follow-up period (adjusted P = 0.0002). This latter P-value is also significant with adjustment for the number of genes tested. Independent of treatment at 6-month follow-up, individuals carrying the minor allele have substantially decreased the odds of quitting (OR = 0.31; 95% CI 0.18–0.55). Effect of estimates indicate that the treatment is more effective for individuals with the wild-type (OR = 2.14, 95% CI 1.20–3.81) compared with individuals carrying the minor allele (OR = 0.83, 95% CI 0.32–2.19), although this difference is only suggestive (P = 0.10). Furthermore, this SNP demonstrated a role in the time to relapse (P = 0.0002) and an impact on withdrawal symptoms at target quit date (TQD) (P = 0.0009). Overall, while our results indicate strong evidence for CHRNB2 in ability to quit smoking, these results require replication in an independent sample