Chemosensory Profile of South Tyrolean Pinot Blanc Wines: A Multivariate Regression Approach

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The new 14C chronology for the Palaeolithic site of La Ferrassie, France: the disappearance of Neanderthals and the arrival of Homo sapiens in France

The grand abri at La Ferrassie (France) has been a key site for Palaeolithic research since the early part of the 20th century. It became the eponymous site for one variant of Middle Palaeolithic stone tools, and its sequence was used to define stages of the Aurignacian, an early phase of the Upper Palaeolithic. Several Neanderthal remains, including two relatively intact skeletons, make it one of the most important sites for the study of Neanderthal morphology and one of the more important data sets when discussing the Neanderthal treatment of the dead. However, the site has remained essentially undated. Our goal here is to provide a robust chronological framework of the La Ferrassie sequence to be used for broad regional models about human behaviour during the late Middle to Upper Palaeolithic periods. To achieve this goal, we used a combination of modern excavation methods, extensive geoarchaeological analyses, and radiocarbon dating. If we accept that Neanderthals were responsible for the Châtelperronian, then our results suggest an overlap of ca. 1600 years with the newly arrived Homo sapiens found elsewhere in France

The new 14C chronology for the Palaeolithic site of La Ferrassie, France: the disappearance of Neanderthals and the arrival of Homo sapiens in France

The grand abri at La Ferrassie (France) has been a key site for Palaeolithic research since the early part of the 20th century. It became the eponymous site for one variant of Middle Palaeolithic stone tools, and its sequence was used to define stages of the Aurignacian, an early phase of the Upper Palaeolithic. Several Neanderthal remains, including two relatively intact skeletons, make it one of the most important sites for the study of Neanderthal morphology and one of the more important data sets when discussing the Neanderthal treatment of the dead. However, the site has remained essentially undated. Our goal here is to provide a robust chronological framework of the La Ferrassie sequence to be used for broad regional models about human behaviour during the late Middle to Upper Palaeolithic periods. To achieve this goal, we used a combination of modern excavation methods, extensive geoarchaeological analyses, and radiocarbon dating. If we accept that Neanderthals were responsible for the Châtelperronian, then our results suggest an overlap of ca. 1600 years with the newly arrived Homo sapiens found elsewhere in France.info:eu-repo/semantics/publishedVersio

Hunger Artists: Yeast Adapted to Carbon Limitation Show Trade-Offs under Carbon Sufficiency

As organisms adaptively evolve to a new environment, selection results in the improvement of certain traits, bringing about an increase in fitness. Trade-offs may result from this process if function in other traits is reduced in alternative environments either by the adaptive mutations themselves or by the accumulation of neutral mutations elsewhere in the genome. Though the cost of adaptation has long been a fundamental premise in evolutionary biology, the existence of and molecular basis for trade-offs in alternative environments are not well-established. Here, we show that yeast evolved under aerobic glucose limitation show surprisingly few trade-offs when cultured in other carbon-limited environments, under either aerobic or anaerobic conditions. However, while adaptive clones consistently outperform their common ancestor under carbon limiting conditions, in some cases they perform less well than their ancestor in aerobic, carbon-rich environments, indicating that trade-offs can appear when resources are non-limiting. To more deeply understand how adaptation to one condition affects performance in others, we determined steady-state transcript abundance of adaptive clones grown under diverse conditions and performed whole-genome sequencing to identify mutations that distinguish them from one another and from their common ancestor. We identified mutations in genes involved in glucose sensing, signaling, and transport, which, when considered in the context of the expression data, help explain their adaptation to carbon poor environments. However, different sets of mutations in each independently evolved clone indicate that multiple mutational paths lead to the adaptive phenotype. We conclude that yeasts that evolve high fitness under one resource-limiting condition also become more fit under other resource-limiting conditions, but may pay a fitness cost when those same resources are abundant

Adaptation to climate change in the Ontario public health sector

Background: Climate change is among the major challenges for health this century, and adaptation to manage adverse health outcomes will be unavoidable. The risks in Ontario – Canada’s most populous province – include increasing temperatures, more frequent and intense extreme weather events, and alterations to precipitation regimes. Socio-economic-demographic patterns could magnify the implications climate change has for Ontario, including the presence of rapidly growing vulnerable populations, exacerbation of warming trends by heat-islands in large urban areas, and connectedness to global transportation networks. This study examines climate change adaptation in the public health sector in Ontario using information from interviews with government officials. Methods: Fifty-three semi-structured interviews were conducted, four with provincial and federal health officials and 49 with actors in public health and health relevant sectors at the municipal level. We identify adaptation efforts, barriers and opportunities for current and future intervention. Results: Results indicate recognition that climate change will affect the health of Ontarians. Health officials are concerned about how a changing climate could exacerbate existing health issues or create new health burdens, specifically extreme heat (71%), severe weather (68%) and poor air-quality (57%). Adaptation is currently taking the form of mainstreaming climate change into existing public health programs. While adaptive progress has relied on local leadership, federal support, political will, and inter-agency efforts, a lack of resources constrains the sustainability of long-term adaptation programs and the acquisition of data necessary to support effective policies. Conclusions: This study provides a snapshot of climate change adaptation and needs in the public health sector in Ontario. Public health departments will need to capitalize on opportunities to integrate climate change into policies and programs, while higher levels of government must improve efforts to support local adaptation and provide the capacity through which local adaptation can succeed

A community challenge to evaluate RNA-seq, fusion detection, and isoform quantification methods for cancer discovery

The accurate identification and quantitation of RNA isoforms present in the cancer transcriptome is key for analyses ranging from the inference of the impacts of somatic variants to pathway analysis to biomarker development and subtype discovery. The ICGC-TCGA DREAM Somatic Mutation Calling in RNA (SMC-RNA) challenge was a crowd-sourced effort to benchmark methods for RNA isoform quantification and fusion detection from bulk cancer RNA sequencing (RNA-seq) data. It concluded in 2018 with a comparison of 77 fusion detection entries and 65 isoform quantification entries on 51 synthetic tumors and 32 cell lines with spiked-in fusion constructs. We report the entries used to build this benchmark, the leaderboard results, and the experimental features associated with the accurate prediction of RNA species. This challenge required submissions to be in the form of containerized workflows, meaning each of the entries described is easily reusable through CWL and Docker containers at https://github.com/SMC-RNA-challenge. A record of this paper's transparent peer review process is included in the supplemental information

Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines

The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers project, our effort to generate a comprehensive encyclopedia of somatic mutation calls for the TCGA data to enable robust cross-tumor-type analyses. Our approach accounts for variance and batch effects introduced by the rapid advancement of DNA extraction, hybridization-capture, sequencing, and analysis methods over time. We present best practices for applying an ensemble of seven mutation-calling algorithms with scoring and artifact filtering. The dataset created by this analysis includes 3.5 million somatic variants and forms the basis for PanCan Atlas papers. The results have been made available to the research community along with the methods used to generate them. This project is the result of collaboration from a number of institutes and demonstrates how team science drives extremely large genomics projects

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts