Efficient gene-driven germ-line point mutagenesis of C57BL/6J mice

BACKGROUND: Analysis of an allelic series of point mutations in a gene, generated by N-ethyl-N-nitrosourea (ENU) mutagenesis, is a valuable method for discovering the full scope of its biological function. Here we present an efficient gene-driven approach for identifying ENU-induced point mutations in any gene in C57BL/6J mice. The advantage of such an approach is that it allows one to select any gene of interest in the mouse genome and to go directly from DNA sequence to mutant mice. RESULTS: We produced the Cryopreserved Mutant Mouse Bank (CMMB), which is an archive of DNA, cDNA, tissues, and sperm from 4,000 G(1 )male offspring of ENU-treated C57BL/6J males mated to untreated C57BL/6J females. Each mouse in the CMMB carries a large number of random heterozygous point mutations throughout the genome. High-throughput Temperature Gradient Capillary Electrophoresis (TGCE) was employed to perform a 32-Mbp sequence-driven screen for mutations in 38 PCR amplicons from 11 genes in DNA and/or cDNA from the CMMB mice. DNA sequence analysis of heteroduplex-forming amplicons identified by TGCE revealed 22 mutations in 10 genes for an overall mutation frequency of 1 in 1.45 Mbp. All 22 mutations are single base pair substitutions, and nine of them (41%) result in nonconservative amino acid substitutions. Intracytoplasmic sperm injection (ICSI) of cryopreserved spermatozoa into B6D2F1 or C57BL/6J ova was used to recover mutant mice for nine of the mutations to date. CONCLUSIONS: The inbred C57BL/6J CMMB, together with TGCE mutation screening and ICSI for the recovery of mutant mice, represents a valuable gene-driven approach for the functional annotation of the mammalian genome and for the generation of mouse models of human genetic diseases. The ability of ENU to induce mutations that cause various types of changes in proteins will provide additional insights into the functions of mammalian proteins that may not be detectable by knockout mutations

Shifting stoichiometry: Long-term trends in stream-dissolved organic matter reveal altered C:N ratios due to history of atmospheric acid deposition

Este artículo contiene 17 páginas, 6 figuras, 2 tablas.Dissolved organic carbon (DOC) and nitrogen (DON) are important energy and nutrient sources for aquatic ecosystems. In many northern temperate, freshwater systems DOC has increased in the past 50 years. Less is known about how changes in DOC may vary across latitudes, and whether changes in DON track those of DOC. Here, we present long-term DOC and DON data from 74 streams distributed across seven sites in biomes ranging from the tropics to northern boreal forests with varying histories of atmospheric acid deposition. For each stream, we examined the temporal trends of DOC and DON concentrations and DOC:DON molar ratios. While some sites displayed consistent positive or negative trends in stream DOC and DON concentrations, changes in direction or magnitude were inconsistent at regional or local scales. DON trends did not always track those of DOC, though DOC:DON ratios increased over time for ~30% of streams. Our results indicate that the dissolved organic matter (DOM) pool is experiencing fundamental changes due to the recovery from atmospheric acid deposition. Changes in DOC:DON stoichiometry point to a shifting energynutrient balance in many aquatic ecosystems. Sustained changes in the character of DOM can have major implications for stream metabolism, biogeochemical processes, food webs, and drinking water quality (including disinfection by-products). Understanding regional and global variation in DOC and DON concentrations is important for developing realistic models and watershed management protocols to effectively target mitigation efforts aimed at bringing DOM flux and nutrient enrichment under control.National Institute of Food and Agriculture, Grant/Award Number: 1016163, 1019522 and 1022291; Natural Environment Research Council, Grant/Award Number: NE/K010689/1; NSF EPSCoR, Grant/ Award Number: EPS-1929148; Division of Environmental Biology, Grant/ Award Number: 1545288 and 1556603; European Regional Development Fund, Grant/Award Number: RTI2018-094521- B-100 and RYC-2017-22643Peer reviewe

Multivariable Analysis for Advanced Analytics of Wind Turbine Management

Operation and maintenance tasks on the wind turbines have an essen- tial role to ensure the correct condition of the system and to minimize losses and increase the productivity. The condition monitoring systems installed on the main components of the wind turbines provide information about the tasks that should be carried out over the time. A novel statistical methodology for multivariable analysis of big data from wind turbines is presented in this paper. The objective is to analyse the necessary information from the condition monitoring systems installed in wind farms. The novel approach filters the main parameters from the collected signals and uses advanced computational techniques for evaluating the data and giving mean- ing to them. The main advantage of the approach is the possibility of the big data analysis based on the main information available

Priorities for synthesis research in ecology and environmental science

ACKNOWLEDGMENTS We thank the National Science Foundation grant #1940692 for financial support for this workshop, and the National Center for Ecological Analysis and Synthesis (NCEAS) and its staff for logistical support.Peer reviewedPublisher PD

Priorities for synthesis research in ecology and environmental science

ACKNOWLEDGMENTS We thank the National Science Foundation grant #1940692 for financial support for this workshop, and the National Center for Ecological Analysis and Synthesis (NCEAS) and its staff for logistical support.Peer reviewedPublisher PD