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- Santangelo, James S., et al.
(författare)
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Global urban environmental change drives adaptation in white clover
- 2022
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 375
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Tidskriftsartikel (refereegranskat)abstract
- Urbanization transforms environments in ways that alter biological evolution. We examined whether urban environmental change drives parallel evolution by sampling 110,019 white clover plants from 6169 populations in 160 cities globally. Plants were assayed for a Mendelian antiherbivore defense that also affects tolerance to abiotic stressors. Urban-rural gradients were associated with the evolution of clines in defense in 47% of cities throughout the world. Variation in the strength of clines was explained by environmental changes in drought stress and vegetation cover that varied among cities. Sequencing 2074 genomes from 26 cities revealed that the evolution of urban-rural dines was best explained by adaptive evolution, but the degree of parallel adaptation varied among cities. Our results demonstrate that urbanization leads to adaptation at a global scale.
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- Abend, M., et al.
(författare)
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RENEB Inter-Laboratory Comparison 2021 : The Gene Expression Assay
- 2023
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Ingår i: Radiation Research. - 0033-7587 .- 1938-5404. ; 199:6, s. 598-615
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Tidskriftsartikel (refereegranskat)abstract
- Early and high-throughput individual dose estimates are essential following large-scale radiation exposure events. In the context of the Running the European Network for Biodosimetry and Physical Dosimetry (RENEB) 2021 exercise, gene expression assays were conducted and their corresponding performance for dose-assessment is presented in this publication. Three blinded, coded whole blood samples from healthy donors were exposed to 0, 1.2 and 3.5 Gy X-ray doses (240 kVp, 1 Gy/min) using the X-ray source Yxlon. These exposures correspond to clinically relevant groups of unexposed, low dose (no severe acute health effects expected) and high dose exposed individuals (requiring early intensive medical health care). Samples were sent to eight teams for dose estimation and identification of clinically relevant groups. For quantitative reverse transcription polymerase chain reaction (qRT-PCR) and microarray analyses, samples were lysed, stored at 20°C and shipped on wet ice. RNA isolations and assays were run in each laboratory according to locally established protocols. The time-to-result for both rough early and more precise later reports has been documented where possible. Accuracy of dose estimates was calculated as the difference between estimated and reference doses for all doses (summed absolute difference, SAD) and by determining the number of correctly reported dose estimates that were defined as ±0.5 Gy for reference doses <2.5 Gy and ±1.0 Gy for reference doses >3 Gy, as recommended for triage dosimetry. We also examined the allocation of dose estimates to clinically/diagnostically relevant exposure groups. Altogether, 105 dose estimates were reported by the eight teams, and the earliest report times on dose categories and estimates were 5 h and 9 h, respectively. The coefficient of variation for 85% of all 436 qRT-PCR measurements did not exceed 10%. One team reported dose estimates that systematically deviated several-fold from reported dose estimates, and these outliers were excluded from further analysis. Teams employing a combination of several genes generated about two-times lower median SADs (0.8 Gy) compared to dose estimates based on single genes only (1.7 Gy). When considering the uncertainty intervals for triage dosimetry, dose estimates of all teams together were correctly reported in 100% of the 0 Gy, 50% of the 1.2 Gy and 50% of the 3.5 Gy exposed samples. The order of dose estimates (from lowest to highest) corresponding to three dose categories (unexposed, low dose and highest exposure) were correctly reported by all teams and all chosen genes or gene combinations. Furthermore, if teams reported no exposure or an exposure >3.5 Gy, it was always correctly allocated to the unexposed and the highly exposed group, while low exposed (1.2 Gy) samples sometimes could not be discriminated from highly (3.5 Gy) exposed samples. All teams used FDXR and 78.1% of correct dose estimates used FDXR as one of the predictors. Still, the accuracy of reported dose estimates based on FDXR differed considerably among teams with one team's SAD (0.5 Gy) being comparable to the dose accuracy employing a combination of genes. Using the workflow of this reference team, we performed additional experiments after the exercise on residual RNA and cDNA sent by six teams to the reference team. All samples were processed similarly with the intention to improve the accuracy of dose estimates when employing the same workflow. Re-evaluated dose estimates improved for half of the samples and worsened for the others. In conclusion, this inter-laboratory comparison exercise enabled (1) identification of technical problems and corrections in preparations for future events, (2) confirmed the early and high-throughput capabilities of gene expression, (3) emphasized different biodosimetry approaches using either only FDXR or a gene combination, (4) indicated some improvements in dose estimation with FDXR when employing a similar methodology, which requires further research for the final conclusion and (5) underlined the applicability of gene expression for identification of unexposed and highly exposed samples, supporting medical management in radiological or nuclear scenarios.
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| 7. |
- Gong, T., et al.
(författare)
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Understanding the relationship between asthma and autism spectrum disorder: a population-based family and twin study
- 2023
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Ingår i: Psychological Medicine. - : Cambridge University Press (CUP). - 0033-2917 .- 1469-8978. ; 53:7, s. 3096-3104
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Tidskriftsartikel (refereegranskat)abstract
- Background There is some evidence that autism spectrum disorder (ASD) frequently co-occurs with immune-mediated conditions including asthma. We aimed to explore the familial co-aggregation of ASD and asthma using different genetically informed designs. Methods We first examined familial co-aggregation of asthma and ASD in individuals born in Sweden from 1992 to 2007 (n = 1 569 944), including their full- and half-siblings (n = 1 704 388 and 356 544 pairs) and full cousins (n = 3 921 890 pairs), identified using Swedish register data. We then applied quantitative genetic modeling to siblings (n = 620 994 pairs) and twins who participated in the Child and Adolescent Twin Study in Sweden (n = 15 963 pairs) to estimate the contribution of genetic and environmental factors to the co-aggregation. Finally, we estimated genetic correlations between traits using linkage disequilibrium score regression (LDSC). Results We observed a within-individual association [adjusted odds ratio (OR) 1.33, 95% confidence interval (CI) 1.28-1.37] and familial co-aggregation between asthma and ASD, and the magnitude of the associations decreased as the degree of relatedness decreased (full-siblings: OR 1.44, 95% CI 1.38-1.50, maternal half-siblings: OR 1.28, 95% CI 1.18-1.39, paternal half-siblings: OR 1.05, 95% CI 0.96-1.15, full cousins: OR 1.06, 95% CI 1.03-1.09), suggesting shared familial liability. Quantitative genetic models estimated statistically significant genetic correlations between ASD traits and asthma. Using the LDSC approach, we did not find statistically significant genetic correlations between asthma and ASD (coefficients between -0.09 and 0.12). Conclusions Using different genetically informed designs, we found some evidence of familial co-aggregation between asthma and ASD, suggesting the weak association between these disorders was influenced by shared genetics.
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| 10. |
- Thysell, Elin, et al.
(författare)
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Clinical and biological relevance of the transcriptomic-based prostate cancer metastasis subtypes MetA-C
- 2022
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Ingår i: Molecular Oncology. - : Wiley. - 1574-7891 .- 1878-0261. ; 16:4, s. 846-859
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Tidskriftsartikel (refereegranskat)abstract
- To improve treatment of metastatic prostate cancer, the biology of metastases needs to be understood. We recently described three subtypes of prostate cancer bone metastases (MetA-C), based on differential gene expression. The aim of this study was to verify the clinical relevance of these subtypes and to explore their biology and relations to genetic drivers. Freshly-frozen metastasis samples were obtained as hormone-naive (n = 17), short-term castrated (n = 21), or castration-resistant (n = 65) from a total of 67 patients. Previously published sequencing data from 573 metastasis samples were also analyzed. Through transcriptome profiling and sample classification based on a set of predefined MetA-C-differentiating genes, we found that most metastases were heterogeneous for the MetA-C subtypes. Overall, MetA was the most common subtype, while MetB was significantly enriched in castration-resistant samples and in liver metastases, and consistently associated with poor prognosis. By gene set enrichment analysis, the phenotype of MetA was described by high androgen response, protein secretion and adipogenesis, MetB by high cell cycle activity and DNA repair, and MetC by epithelial-to-mesenchymal transition and inflammation. The MetB subtype demonstrated single nucleotide variants of RB transcriptional corepressor 1 (RB1) and loss of 21 genes at chromosome 13, including RB1, but provided independent prognostic value to those genetic aberrations. In conclusion, a distinct set of gene transcripts can be used to classify prostate cancer metastases into the subtypes MetA-C. The MetA-C subtypes show diverse biology, organ tropism, and prognosis. The MetA-C classification may be used independently, or in combination with genetic markers, primarily to identify MetB patients in need of complementary therapy to conventional androgen receptor-targeting treatments.
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| 11. |
- Yakaboylu, E., et al.
(författare)
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Quantum impurity model for anyons
- 2020
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Ingår i: Physical Review B. - : American Physical Society (APS). - 2469-9950 .- 2469-9969. ; 102:14
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Tidskriftsartikel (refereegranskat)abstract
- One of the hallmarks of quantum statistics, tightly entwined with the concept of topological phases of matter, is the prediction of anyons. Although anyons are predicted to be realized in certain fractional quantum Hall systems, they have not yet been unambiguously detected in experiment. Here we introduce a simple quantum impurity model, where bosonic or fermionic impurities turn into anyons as a consequence of their interaction with the surrounding many-particle bath. A cloud of phonons dresses each impurity in such a way that it effectively attaches fluxes or vortices to it and thereby converts it into an Abelian anyon. The corresponding quantum impurity model, first, provides a different approach to the numerical solution of the many-anyon problem, along with a concrete perspective of anyons as emergent quasiparticles built from composite bosons or fermions. More importantly, the model paves the way toward realizing anyons using impurities in crystal lattices as well as ultracold gases. In particular, we consider two heavy electrons interacting with a two-dimensional lattice crystal in a magnetic field, and show that when the impurity-bath system is rotated at the cyclotron frequency, impurities behave as anyons as a consequence of the angular momentum exchange between the impurities and the bath. A possible experimental realization is proposed by identifying the statistics parameter in terms of the mean-square distance of the impurities and the magnetization of the impurity-bath system, both of which are accessible to experiment. Another proposed application is impurities immersed in a two-dimensional weakly interacting Bose gas.
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