Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations

Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process (“bottom-up”) or inversion (“top-down”) models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45∘ N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash–Sutcliffe model efficiency =0.47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3–41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4–39.9) or 38 (25.9–49.5) Tg(CH4) yr−1. To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available at https://doi.org/10.5281/zenodo.2560163 (Peltola et al., 2019)

Intronic ATTTC repeat expansions in STARD7 in familial adult myoclonic epilepsy linked to chromosome 2

Familial Adult Myoclonic Epilepsy (FAME) is characterised by cortical myoclonic tremor usually from the second decade of life and overt myoclonic or generalised tonic-clonic seizures. Four independent loci have been implicated in FAME on chromosomes (chr) 2, 3, 5 and 8. Using whole genome sequencing and repeat primed PCR, we provide evidence that chr2-linked FAME (FAME2) is caused by an expansion of an ATTTC pentamer within the first intron of STARD7. The ATTTC expansions segregate in 158/158 individuals typically affected by FAME from 22 pedigrees including 16 previously reported families recruited worldwide. RNA sequencing from patient derived fibroblasts shows no accumulation of the AUUUU or AUUUC repeat sequences and STARD7 gene expression is not affected. These data, in combination with other genes bearing similar mutations that have been implicated in FAME, suggest ATTTC expansions may cause this disorder, irrespective of the genomic locus involvedSupplementary Information: Supplementary Data 1; Supplementary Data 2; Reporting Summary.NHMRC; Women’s and Children’s Hospital Research Foundation; Muir Maxwell Trust; Epilepsy Society; The European Fund for Regional Development; The province of Friesland, Dystonia Medical Research Foundation; Stichting Wetenschapsfonds Dystonie Vereniging; Fonds Psychische Gezondheid; Phelps Stichting; The Italian Ministry of Health; Istituto Superiore di Sanità, Italy; Undiagnosed Disease Network Italy; The Fondation maladies rares, University Hospital Essen and UK Department of Health’s NIHR.https://www.nature.com/ncommspm2020Neurolog

Histone H3.3 beyond cancer: Germline mutations in Histone 3 Family 3A and 3B cause a previously unidentified neurodegenerative disorder in 46 patients

Although somatic mutations in Histone 3.3 (H3.3) are well-studied drivers of oncogenesis, the role of germline mutations remains unreported. We analyze 46 patients bearing de novo germline mutations in histone 3 family 3A (H3F3A) or H3F3B with progressive neurologic dysfunction and congenital anomalies without malignancies. Molecular modeling of all 37 variants demonstrated clear disruptions in interactions with DNA, other histones, and histone chaperone proteins. Patient histone posttranslational modifications (PTMs) analysis revealed notably aberrant local PTM patterns distinct from the somatic lysine mutations that cause global PTM dysregulation. RNA sequencing on patient cells demonstrated up-regulated gene expression related to mitosis and cell division, and cellular assays confirmed an increased proliferative capacity. A zebrafish model showed craniofacial anomalies and a defect in Foxd3-derived glia. These data suggest that the mechanism of germline mutations are distinct from cancer-associated somatic histone mutations but may converge on control of cell proliferation

Die Voegel des Duemmer-Gebietes Avifauna eines norddeutschen Flachsees und seiner Umgebung

TIB: RA 4507(21) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

Addressing a systematic bias in carbon dioxide flux measurements with the EC150 and the IRGASON open-path gas analyzers

Across a global network of eddy covariance flux towers, two relatively new open-path infrared gas analyzers (IRGAs), the IRGASON and the EC150, are increasingly used to measure net carbon dioxide (CO2) fluxes (Fc_OP). Differences in net CO2 fluxes derived from open- and closed-path IRGAs in general remain poorly constrained. In particular, the performance of the IRGASON and the EC150 for measuring Fc_OP has not been characterized yet. These IRGAs measure CO2 absorption, which is scaled with air temperature and pressure before converting it to instantaneous CO2 density. This sensor-internal conversion is based on a slow-response thermistor air temperature measurement. Here, we test if the high-frequency temperature attenuation causes selectively systematic Fc_OP errors that scale with kinematic temperature fluxes. First, we examine the relationship between wintertime Fc_OP and kinematic temperature fluxes for eight northern ecosystems. Second, we investigate how residuals between Fc_OP and CO2 fluxes from co-located closed-path IRGAs (FC_CP) are related to kinematic temperature fluxes for three different ecosystem types (i.e., boreal forest, grassland, and irrigated cropland). We find that kinematic temperature fluxes, but not mean ambient air temperatures or CO2 flux regime, consistently determine the absolute magnitude of Fc_OP errors. This selectively systematic bias causes the most pronounced relative Fc_OP errors to occur when “true” CO2 fluxes are low and kinematic temperature fluxes are high (e.g., northern ecosystems during the winter). The smallest relative errors occur during periods with large “true” CO2 fluxes and low kinematic temperature fluxes. To address this bias, we replace the slow-response air temperature in the absorption-to-CO2 density conversion with a fast-response air temperature derived from sonic anemometer measurements. The use of the fast-response air temperature improves the agreement between half-hourly Fc_OP and FC_CP for all open- versus closed-path IRGA comparisons. Additionally, cumulative Fc_OP and Fc_CP sums are more comparable as differences drop from 63 %–13 % to 20 %–8 %. The improved IRGASON and EC150 performance enhances the ability and confidence to synthesize flux measurements across multiple sites including these two relatively new IRGAs

Addressing a systematic bias in carbon dioxide flux measurements with the EC150 and the IRGASON open-path gas analyzers

Across a global network of eddy covariance flux towers, two relatively new open-path infrared gas analyzers (IRGAs), the IRGASON and the EC150, are increasingly used to measure net carbon dioxide (CO2) fluxes (Fc_OP). Differences in net CO2 fluxes derived from open- and closed-path IRGAs in general remain poorly constrained. In particular, the performance of the IRGASON and the EC150 for measuring Fc_OP has not been characterized yet. These IRGAs measure CO2 absorption, which is scaled with air temperature and pressure before converting it to instantaneous CO2 density. This sensor-internal conversion is based on a slow-response thermistor air temperature measurement. Here, we test if the high-frequency temperature attenuation causes selectively systematic Fc_OP errors that scale with kinematic temperature fluxes. First, we examine the relationship between wintertime Fc_OP and kinematic temperature fluxes for eight northern ecosystems. Second, we investigate how residuals between Fc_OP and CO2 fluxes from co-located closed-path IRGAs (FC_CP) are related to kinematic temperature fluxes for three different ecosystem types (i.e., boreal forest, grassland, and irrigated cropland). We find that kinematic temperature fluxes, but not mean ambient air temperatures or CO2 flux regime, consistently determine the absolute magnitude of Fc_OP errors. This selectively systematic bias causes the most pronounced relative Fc_OP errors to occur when “true” CO2 fluxes are low and kinematic temperature fluxes are high (e.g., northern ecosystems during the winter). The smallest relative errors occur during periods with large “true” CO2 fluxes and low kinematic temperature fluxes. To address this bias, we replace the slow-response air temperature in the absorption-to-CO2 density conversion with a fast-response air temperature derived from sonic anemometer measurements. The use of the fast-response air temperature improves the agreement between half-hourly Fc_OP and FC_CP for all open- versus closed-path IRGA comparisons. Additionally, cumulative Fc_OP and Fc_CP sums are more comparable as differences drop from 63 %–13 % to 20 %–8 %. The improved IRGASON and EC150 performance enhances the ability and confidence to synthesize flux measurements across multiple sites including these two relatively new IRGAs

Enigmatic phylogeny of skuas (Aves Stercorariidae)

Multiple sources of evidence show that the skuas (Aves: Stercorariidae) are a monophyletic group, closely related to gulls (Laridae). On morphological and behavioural evidence the Stercorariidae are divided into two widely divergent genera, Catharacta and Stercorarius, consistent with observed levels of nuclear and mitochondrial gene divergence. Catharacta skuas are large-bodied and with one exception breed in the Southern Hemisphere. Stercorarius skuas (otherwise known as jaegers) are smaller bodied and breed exclusively in the Northern Hemisphere. Evidence from both mitochondrial and nuclear genomes and from ectoparasitic lice (Insecta: Phthiraptera) shows that the Pomarine skua, S. pomarinus, which has been recognized as being somewhat intermediate in certain morphological and behavioural characteristics, is much more closely related to species in the genus Catharacta, especially to the Northern Hemisphere-breeding Great skua, C. skua, than it is to the other two Stercorarius skuas, the Arctic skua, S. parasiticus and the Longtailed skua, S. longicaudus. Three possible explanations that might account for this discordant aspect of skua phylogeny are explored. These involve (i) the segregation of ancestral polymorphism, (ii) convergent evolution of morphology and behaviour or (iii) inter-generic hybridization. The available evidence from both nuclear and mitochondrial genomes does not exclude any of these hypotheses. Thus, resolution of this enigma of skua phylogeny awaits further work

Multiplex families with epilepsy: success of clinical and molecular genetic characterization

Objective: To analyze the clinical syndromes and inheritance patterns of multiplex families with epilepsy toward the ultimate aim of uncovering the underlying molecular genetic basis. Methods: Following the referral of families with 2 or more relatives with epilepsy, individuals were classified into epilepsy syndromes. Families were classified into syndromes where at least 2 family members had a specific diagnosis. Pedigrees were analyzed and molecular genetic studies were performed as appropriate. Results: A total of 211 families were ascertained over an 11-year period in Israel. A total of 169 were classified into broad familial epilepsy syndrome groups: 61 generalized, 22 focal, 24 febrile seizure syndromes, 33 special syndromes, and 29 mixed. A total of 42 families remained unclassified. Pathogenic variants were identified in 49/211 families (23%). The majority were found in established epilepsy genes (e.g., SCN1A, KCNQ2, CSTB), but in 11 families, this cohort contributed to the initial discovery (e.g., KCNT1, PCDH19, TBC1D24). We expand the phenotypic spectrum of established epilepsy genes by reporting a familial LAMC3 homozygous variant, where the predominant phenotype was epilepsy with myoclonic-atonic seizures, and a pathogenic SCN1A variant in a family where in 5 siblings the phenotype was broadly consistent with Dravet syndrome, a disorder that usually occurs sporadically. Conclusion: A total of 80% of families were successfully classified, with pathogenic variants identified in 23%. The successful characterization of familial electroclinical and inheritance patterns has highlighted the value of studying multiplex families and their contribution towards uncovering the genetic basis of the epilepsies.Zaid Afawi, Karen L. Oliver, Sara Kivity, Aziz Mazarib, Ilan Blatt, Miriam Y. Neufeld, Katherine L. Helbig, Hadassa Goldberg-Stern, Adel J. Misk, Rachel Straussberg, Simri Walid, Muhammad Mahajnah, Tally Lerman-Sagie, Bruria Ben-Zeev, Esther Kahana, Rafik Masalha, Uri Kramer, Dana Ekstein, Zamir Shorer, Robyn H. Wallace, Marie Mangelsdorf, James N. MacPherson, Gemma L. Carvill, Heather C. Mefford, Graeme D. Jackson, Ingrid E. Scheffer, Melanie Bahlo, Jozef Gecz, Sarah E. Heron, Mark Corbett, John C. Mulley, Leanne M. Dibbens, Amos D. Korczyn and Samuel F. Berkovi