Meta-analysis of RNA-seq expression data across species, tissues and studies.

BackgroundDifferences in gene expression drive phenotypic differences between species, yet major organs and tissues generally have conserved gene expression programs. Several comparative transcriptomic studies have observed greater similarity in gene expression between homologous tissues from different vertebrate species than between diverse tissues of the same species. However, a recent study by Lin and colleagues reached the opposite conclusion. These studies differed in the species and tissues analyzed, and in technical details of library preparation, sequencing, read mapping, normalization, gene sets, and clustering methods.ResultsTo better understand gene expression evolution we reanalyzed data from four studies, including that of Lin, encompassing 6-13 tissues each from 11 vertebrate species using standardized mapping, normalization, and clustering methods. An analysis of independent data showed that the set of tissues chosen by Lin et al. were more similar to each other than those analyzed by previous studies. Comparing expression in five common tissues from the four studies, we observed that samples clustered exclusively by tissue rather than by species or study, supporting conservation of organ physiology in mammals. Furthermore, inter-study distances between homologous tissues were generally less than intra-study distances among different tissues, enabling informative meta-analyses. Notably, when comparing expression divergence of tissues over time to expression variation across 51 human GTEx tissues, we could accurately predict the clustering of expression for arbitrary pairs of tissues and species.ConclusionsThese results provide a framework for the design of future evolutionary studies of gene expression and demonstrate the utility of comparing RNA-seq data across studies

A quantitative model of the initiation of DNA replication in Saccharomyces cerevisiae predicts the effects of system perturbations.

BackgroundEukaryotic cell proliferation involves DNA replication, a tightly regulated process mediated by a multitude of protein factors. In budding yeast, the initiation of replication is facilitated by the heterohexameric origin recognition complex (ORC). ORC binds to specific origins of replication and then serves as a scaffold for the recruitment of other factors such as Cdt1, Cdc6, the Mcm2-7 complex, Cdc45 and the Dbf4-Cdc7 kinase complex. While many of the mechanisms controlling these associations are well documented, mathematical models are needed to explore the network's dynamic behaviour. We have developed an ordinary differential equation-based model of the protein-protein interaction network describing replication initiation.ResultsThe model was validated against quantified levels of protein factors over a range of cell cycle timepoints. Using chromatin extracts from synchronized Saccharomyces cerevisiae cell cultures, we were able to monitor the in vivo fluctuations of several of the aforementioned proteins, with additional data obtained from the literature. The model behaviour conforms to perturbation trials previously reported in the literature, and accurately predicts the results of our own knockdown experiments. Furthermore, we successfully incorporated our replication initiation model into an established model of the entire yeast cell cycle, thus providing a comprehensive description of these processes.ConclusionsThis study establishes a robust model of the processes driving DNA replication initiation. The model was validated against observed cell concentrations of the driving factors, and characterizes the interactions between factors implicated in eukaryotic DNA replication. Finally, this model can serve as a guide in efforts to generate a comprehensive model of the mammalian cell cycle in order to explore cancer-related phenotypes

Secure and equal access to land for all: Lessons on land governance and climate resilience from Dar es Salaam, Tanzania

Secure land and property rights are essential for improving the livelihoods of the poor and ending poverty. Effective and equitable land governance can also contribute to economic development, domestic resource mobilisation and climate change resilience. Promoting fair and transparent land tenure systems should therefore be a priority for national governments

Low Carbon Cities: Is Ambitious Action Affordable?

Research has begun to uncover the extent that greenhouse gas emissions can be attributed to cities, as well as the scope for cities to contribute to emissions reduction. But assessments of the economics of urban climate mitigation are lacking, and are currently based on selective case studies or specific sectors. Further analysis is crucial to enable action at the urban level. Here we consider the investment needs associated with 11 clusters of low carbon measures that could be deployed across the world’s urban areas in a way that is consistent with a broader 2°C target. Economic assessment of these low carbon measures finds that they could be deployed around the world with investments of c$1 trillion per year between 2015 and 2050 (equivalent to 1.3$16.6 trillion USD in the period to 2050. However, discount rates, energy prices and rates of technological learning are key to the economic feasibility of climate action, with the NPV of these measures ranging from -$1.1 trillion USD to$65.2 trillion USD under different conditions

Building Climate Resilience and Water Security in Cities: Lessons from the sponge city of Wuhan, China

The vulnerability of Chinese cities to water-related disasters is being exacerbated by climate change. To counter the effects of flooding, water scarcity and water pollution, the government has been trialling innovative green solutions. This policy brief looks at how the “Sponge City” approach has been implemented in Wuhan

Producer Cities and Consumer Cities: Using Production- and Consumption-Based Carbon Accounts to Guide Climate Action in China, the UK, and the US

Meeting the commitments made in the Paris Agreement on climate change will require different approaches in different countries. However, a common feature in many contexts relates to the continued and sometimes increasing significance of the carbon footprints of urban centres. These footprints consider both production or territorial (i.e. Scope 1 and 2) emissions, and consumption or extra-territorial (i.e. Scope 3) emissions. Although a growing number of cities have adopted targets for their production-based emissions, very few have even started to analyse or address their consumption-based emissions. This presents a potential challenge for urban policymaking if consumption emissions rise while production emissions fall, and for climate mitigation more broadly if emissions are effectively migrating to areas without carbon reduction targets or capabilities. To explore these issues, in this paper we analyse and compare production- and consumption-based emissions accounts for urban centres in China, the UK and the US. Results show that per-capita income and population density are strong predictors of consumption-based emissions levels, and consumption-based emissions appear to diminish but not decouple with higher per-capita incomes. In addition, results show that per-capita income is a predictor of net emissions - or the difference between production- and consumption-based accounts - suggesting that continuing increases in per capita income levels may drive the ‘leakage’ of urban emissions. These findings highlight a risk in placing too much faith in city-level climate strategies focused only on production-based emissions, and stress the importance of new city-level initiatives that focus on consumption-based emissions, especially in cities that are shifting from producer to consumer city status

Towards Sustainable Mobility and Improved Public Health: Lessons from bike sharing in Shanghai, China

Reliable, affordable and safe transport is key to making cities sustainable. At present, however, many cities are beset by congestion, inadequate connectivity, wasted public space and poor air quality. This policy brief presents lessons from Shanghai, where the world’s largest bicycle-sharing scheme has been implemented to address the challenges presented by inadequate current transport networks and climate change

Using crowdsourced data to estimate the carbon footprints of global cities

Cities are at the forefront of the battle against climate change. However, intercity comparisons and responsibility allocations among cities are hindered because cost- and time-effective methods to calculate the carbon footprints of global cities have yet to be developed. Here, we establish a hybrid method integrating top-down input–output analysis and bottom-up crowdsourced data to estimate the carbon footprints of global cities. Using city purchasing power as the main predictor of the carbon footprint, we estimate the carbon footprints of 465 global cities in 2020. Those cities comprise 10% of the global population but account for 18% of the global carbon emissions showing a significant concentration of carbon emissions. The Gini coefficients are applied to show that global carbon inequality is less than income inequality. In addition, the increased carbon emissions that come from high consumption lifestyles offset the carbon reduction by efficiency gains that could result from compact city design and large city scale. Large climate benefits could be obtained by achieving a low-carbon transition in a small number of global cities, emphasizing the need for leadership from globally important urban centres

Using crowdsourced data to estimate the carbon footprints of global cities

Cities are at the forefront of the battle against climate change. However, intercity comparisons and responsibility allocations among cities are hindered because cost- and time-effective methods to calculate the carbon footprints of global cities have yet to be developed. Here, we establish a hybrid method integrating top-down input–output analysis and bottom-up crowdsourced data to estimate the carbon footprints of global cities. Using city purchasing power as the main predictor of the carbon footprint, we estimate the carbon footprints of 465 global cities in 2020. Those cities comprise 10% of the global population but account for 18% of the global carbon emissions showing a significant concentration of carbon emissions. The Gini coefficients are applied to show that global carbon inequality is less than income inequality. In addition, the increased carbon emissions that come from high consumption lifestyles offset the carbon reduction by efficiency gains that could result from compact city design and large city scale. Large climate benefits could be obtained by achieving a low-carbon transition in a small number of global cities, emphasizing the need for leadership from globally important urban centres