| 1. |
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- 2019
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Tidskriftsartikel (refereegranskat)
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| 2. |
- Campbell, PJ, et al.
(författare)
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Pan-cancer analysis of whole genomes
- 2020
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
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Tidskriftsartikel (refereegranskat)abstract
- Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1–3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10–18.
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| 3. |
- Hartley, Philippa, et al.
(författare)
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SKA Science Data Challenge 2: analysis and results
- 2023
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Ingår i: Monthly Notices of the Royal Astronomical Society. - 0035-8711 .- 1365-2966. ; 523:2, s. 1967-1993
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Tidskriftsartikel (refereegranskat)abstract
- The Square Kilometre Array Observatory (SKAO) will explore the radio sky to new depths in order to conduct transformational science. SKAO data products made available to astronomers will be correspondingly large and complex, requiring the application of advanced analysis techniques to extract key science findings. To this end, SKAO is conducting a series of Science Data Challenges, each designed to familiarize the scientific community with SKAO data and to drive the development of new analysis techniques. We present the results from Science Data Challenge 2 (SDC2), which invited participants to find and characterize 233 245 neutral hydrogen (H i) sources in a simulated data product representing a 2000 h SKA-Mid spectral line observation from redshifts 0.25-0.5. Through the generous support of eight international supercomputing facilities, participants were able to undertake the Challenge using dedicated computational resources. Alongside the main challenge, 'reproducibility awards' were made in recognition of those pipelines which demonstrated Open Science best practice. The Challenge saw over 100 participants develop a range of new and existing techniques, with results that highlight the strengths of multidisciplinary and collaborative effort. The winning strategy - which combined predictions from two independent machine learning techniques to yield a 20 per cent improvement in overall performance - underscores one of the main Challenge outcomes: that of method complementarity. It is likely that the combination of methods in a so-called ensemble approach will be key to exploiting very large astronomical data sets.
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| 4. |
- Kiefer, David, 1989, et al.
(författare)
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Double doping of conjugated polymers with monomer molecular dopants
- 2019
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Ingår i: Nature Materials. - : Springer Science and Business Media LLC. - 1476-4660 .- 1476-1122. ; 18:2, s. 149-155
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Tidskriftsartikel (refereegranskat)abstract
- Molecular doping is a crucial tool for controlling the charge-carrier concentration in organic semiconductors. Each dopant molecule is commonly thought to give rise to only one polaron, leading to a maximum of one donor:acceptor charge-transfer complex and hence an ionization efficiency of 100%. However, this theoretical limit is rarely achieved because of incomplete charge transfer and the presence of unreacted dopant. Here, we establish that common p-dopants can in fact accept two electrons per molecule from conjugated polymers with a low ionization energy. Each dopant molecule participates in two charge-transfer events, leading to the formation of dopant dianions and an ionization efficiency of up to 200%. Furthermore, we show that the resulting integer charge-transfer complex can dissociate with an efficiency of up to 170%. The concept of double doping introduced here may allow the dopant fraction required to optimize charge conduction to be halved.
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| 5. |
- Leebens-Mack, James H., et al.
(författare)
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One thousand plant transcriptomes and the phylogenomics of green plants
- 2019
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Ingår i: Nature. - : Nature Publishing Group. - 0028-0836 .- 1476-4687. ; 574:7780, s. 679-
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Tidskriftsartikel (refereegranskat)abstract
- Green plants (Viridiplantae) include around 450,000-500,000 species(1,2) of great diversity and have important roles in terrestrial and aquatic ecosystems. Here, as part of the One Thousand Plant Transcriptomes Initiative, we sequenced the vegetative transcriptomes of 1,124 species that span the diversity of plants in a broad sense (Archaeplastida), including green plants (Viridiplantae), glaucophytes (Glaucophyta) and red algae (Rhodophyta). Our analysis provides a robust phylogenomic framework for examining the evolution of green plants. Most inferred species relationships are well supported across multiple species tree and supermatrix analyses, but discordance among plastid and nuclear gene trees at a few important nodes highlights the complexity of plant genome evolution, including polyploidy, periods of rapid speciation, and extinction. Incomplete sorting of ancestral variation, polyploidization and massive expansions of gene families punctuate the evolutionary history of green plants. Notably, we find that large expansions of gene families preceded the origins of green plants, land plants and vascular plants, whereas whole-genome duplications are inferred to have occurred repeatedly throughout the evolution of flowering plants and ferns. The increasing availability of high-quality plant genome sequences and advances in functional genomics are enabling research on genome evolution across the green tree of life.
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| 6. |
- Liu, Quanli, 1988, et al.
(författare)
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Modular Pathway Rewiring of Yeast for Amino Acid Production
- 2018
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Ingår i: Methods in Enzymology. - : Elsevier. - 1557-7988 .- 0076-6879. ; 608, s. 417-439
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Amino acids find various applications in biotechnology in view of their importance in the food, feed, pharmaceutical, and personal care industries as nutrients, additives, and drugs, respectively. For the large-scale production of amino acids, microbial cell factories are widely used and the development of amino acid-producing strains has mainly focused on prokaryotes Corynebacterium glutamicum and Escherichia coli. However, the eukaryote Saccharomyces cerevisiae is becoming an even more appealing microbial host for production of amino acids and derivatives because of its superior molecular and physiological features, such as amenable to genetic engineering and high tolerance to harsh conditions. To transform S. cerevisiae into an industrial amino acid production platform, the highly coordinated and multiple layers regulation in its amino acid metabolism should be relieved and reconstituted to optimize the metabolic flux toward synthesis of target products. This chapter describes principles, strategies, and applications of modular pathway rewiring in yeast using the engineering of L-ornithine metabolism as a paradigm. Additionally, detailed protocols for in vitro module construction and CRISPR/Cas-mediated pathway assembly are provided.
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| 7. |
- Liu, Quanli, 1988, et al.
(författare)
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Rewiring carbon metabolism in yeast for high level production of aromatic chemicals
- 2019
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- The production of bioactive plant compounds using microbial hosts is considered a safe, cost-competitive and scalable approach to their production. However, microbial production of some compounds like aromatic amino acid (AAA)-derived chemicals, remains an outstanding metabolic engineering challenge. Here we present the construction of a Saccharomyces cerevisiae platform strain able to produce high levels of p-coumaric acid, an AAA-derived precursor for many commercially valuable chemicals. This is achieved through engineering the AAA biosynthesis pathway, introducing a phosphoketalose-based pathway to divert glycolytic flux towards erythrose 4-phosphate formation, and optimizing carbon distribution between glycolysis and the AAA biosynthesis pathway by replacing the promoters of several important genes at key nodes between these two pathways. This results in a maximum p-coumaric acid titer of 12.5 g L−1 and a maximum yield on glucose of 154.9 mg g−1.
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| 8. |
- Carlevaro-Fita, J, et al.
(författare)
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Cancer LncRNA Census reveals evidence for deep functional conservation of long noncoding RNAs in tumorigenesis
- 2020
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Ingår i: Communications biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1, s. 56-
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Tidskriftsartikel (refereegranskat)abstract
- Long non-coding RNAs (lncRNAs) are a growing focus of cancer genomics studies, creating the need for a resource of lncRNAs with validated cancer roles. Furthermore, it remains debated whether mutated lncRNAs can drive tumorigenesis, and whether such functions could be conserved during evolution. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we introduce the Cancer LncRNA Census (CLC), a compilation of 122 GENCODE lncRNAs with causal roles in cancer phenotypes. In contrast to existing databases, CLC requires strong functional or genetic evidence. CLC genes are enriched amongst driver genes predicted from somatic mutations, and display characteristic genomic features. Strikingly, CLC genes are enriched for driver mutations from unbiased, genome-wide transposon-mutagenesis screens in mice. We identified 10 tumour-causing mutations in orthologues of 8 lncRNAs, including LINC-PINT and NEAT1, but not MALAT1. Thus CLC represents a dataset of high-confidence cancer lncRNAs. Mutagenesis maps are a novel means for identifying deeply-conserved roles of lncRNAs in tumorigenesis.
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| 9. |
- LaScala-Gruenewald, Diana E., et al.
(författare)
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Sensory perception plays a larger role in foraging efficiency than heavy-tailed movement strategies
- 2019
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Ingår i: Ecological Modelling. - : Elsevier BV. - 0304-3800 .- 1872-7026. ; 404, s. 69-82
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Tidskriftsartikel (refereegranskat)abstract
- Animals must balance their rates of energetic intake and expenditure while foraging. Several mathematical models have been put forward as energetically optimal foraging strategies when the food environment is sparse (i.e., the distance between food patches in the environment is much larger than the distance from which the forager can perceive food). In particular, Levy walks with a power law exponent approaching 1 are considered optimal for destructive foragers. However, these models have yet to explore the role of sensory perception in foraging success as the distance between food patches approaches the distance from which the forager can perceive food. Here, we used an agent-based modeling approach to address this question. Our results concur that lower values of the power law exponent (i.e. values approaching 1) result in the most food found, but in contrast to previous studies, we note that, in many cases, lower exponents are not optimal when we consider food found per unit distance traveled. For example, higher values of the exponent resulted in comparable or higher foraging success relative to lower values when the forager's range of sensory perception was restricted to an angle ± 30° from its current heading. In addition, we find that sensory perception has a larger effect on foraging success than the power law exponent. These results suggest that a deeper examination of how animals perceive food sources from a distance may affect longstanding assumptions regarding the optimality of Levy walk foraging patterns, and lend support to the developing theoretical shift towards models that place increasing emphasis on how organisms interact with their environments.
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| 10. |
- Lei, Lei, et al.
(författare)
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A comprehensive evaluation method for indoor air quality of buildings based on rough sets and a wavelet neural network
- 2019
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Ingår i: Building and Environment. - : PERGAMON-ELSEVIER SCIENCE LTD. - 0360-1323 .- 1873-684X. ; 162
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Tidskriftsartikel (refereegranskat)abstract
- Understanding the level of indoor air quality is very important to improve the quality of air that people breathe indoors. In this paper, a comprehensive evaluation method combining rough sets and a wavelet neural network is proposed to evaluate the indoor air quality of buildings. Through on-site inspections of the indoor air in six large shopping malls in Beijing, Wuhan and Guangzhou, raw data of the environmental parameters affecting the indoor air quality of large shopping malls are obtained. First, rough sets are used to reduce the dimension of features that affect indoor air quality by removing unimportant features, and important environmental parameters that affect indoor air quality are obtained. These important environmental parameters are used as input parameters of the wavelet neural network. Then, the structure of the wavelet neural network is determined, and an evaluation model of the indoor air quality of buildings based on rough sets and the wavelet neural network is established. Finally, the model is applied to the evaluation of indoor air quality in large shopping malls, and the back propagation neural network, fuzzy neural network and Elman neural network are introduced for comparison of the testing accuracy of the wavelet neural network in the sample testing stage. The results show that the structure of the wavelet neural network is optimized by using a rough set to reduce the redundant attributes of the data, and that the comprehensive evaluation method based on rough sets and a wavelet neural network can accurately evaluate the indoor air quality level of buildings. The results of this study have significance for and can guide the evaluation of the indoor air quality of buildings.
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