Forecasting Seasonal Habitat Connectivity in a Developing Landscape

Connectivity and wildlife corridors are often key components to successful conservation and management plans. Connectivity for wildlife is typically modeled in a static environment that reflects a single snapshot in time. However, it has been shown that, when compared with dynamic connectivity models, static models can underestimate connectivity and mask important population processes. Therefore, including dynamism in connectivity models is important if the goal is to predict functional connectivity. We incorporated four levels of dynamism (individual, daily, seasonal, and interannual) into an individual-based movement model for black bears (Ursus americanus) in Massachusetts, USA. We used future development projections to model movement into the year 2050. We summarized habitat connectivity over the 32-year simulation period as the number of simulated movement paths crossing each pixel in our study area. Our results predict black bears will further colonize the expanding part of their range in the state and move beyond this range towards the greater Boston metropolitan area. This information is useful to managers for predicting and addressing human–wildlife conflict and in targeting public education campaigns on bear awareness. Including dynamism in connectivity models can produce more realistic models and, when future projections are incorporated, can ensure the identification of areas that offer long-term functional connectivity for wildlife

Predicting Dispersal and Conflict Risk for Wolf Recolonization in Colorado

1. The colonization of suitable yet unoccupied habitat due to natural dispersal or human introduction can benefit recovery of threatened species. Predicting habitat suitability and conflict potential of colonization areas can facilitate conservation planning. 2. Planning for reintroduction of gray wolves (Canis lupus) to the United States state of Colorado is underway. Assessing which occupancy sites minimize the likelihood of human-wolf conflict during dispersal events and seasonal movements is critical to the success of this initiative. 3. We used a spatial absorbing Markov chain (SAMC) framework, which extends random walk theory and probabilistically accounts for both movement behavior and mortality risk, to compare the viability of potential occupancy sites (public lands \u3e 500 km2 to minimally meet wolf pack range area). The SAMC framework produced spatially explicit predictions of wolf dispersal, philopatry and conflict risk ahead of recolonization prior to reintroduction efforts. Our SAMC model included: (1) movement resistance based on terrain, roads and housing density; (2) mortality risk and potential conflict (absorption) based on livestock presence, social tolerance, land ownership and state boundaries; and (3) site fidelity based on habitat quality. Using this model, we compared 21 public land units by deriving predictions of: (A) relative survival time outside each site, (B) intensity of use and retention time within each site, and (C) the probability of use on adjacent public lands. We also predicted and mapped potential conflict hot spots associated with each site. 4. Among the units assessed, a complex of United States Forest Service Wilderness areas near Aspen, chiefly the Hunter-Fryingpan and Collegiate Peaks Wilderness areas, had the best overall rankings when comparing predictions of each metric. The area balances high-quality, well-connected habitat with relatively low livestock density and high social tolerance. 5. Synthesis and applications. Our findings highlight the utility of the SAMC framework for assessing colonization areas and the capacity to identify locations for effective proactive management, especially of conflict prone species. The flexibility of the SAMC framework enables predicting likely areas of philopatry and human-wildlife conflict using spatially explicit metrics which can improve the success of conservation translocations and management of species with changing geographic extents

Conversion of lanthanide glutarate chlorides with interstitial THF into lanthanide glutarates with unprecedented topologies

Using slow diffusion methods at room temperature (RT), we obtained four isomorphous lanthanide glutarate chlorides, accommodating interstitial THF and water molecules, [Ln2(Glut)2Cl2(H2O)8]•2H2O•THF (1 - 4), with Ln = La (1), Ce (2), Pr (3), Nd (4). They assemble as 3-dimensional (3D) lanthanide (Ln) coordination polymers with LnO10 coordination polyhedra. Their topology was elucidated to be a 4-coordinated sql net. 1 – 4 slowly dissolve in water liberating the entrapped THF molecules and reassemble as regular Ln-glutarate hydrates when the solution is deprived of THF and water by slow evaporation. The new products crystallize as [Ln2(Glut)3(H2O)3]•5H2O (5 - 7), with Ln = La (5), Ce (6), Pr (7), and [Nd2(Glut)3(H2O)2]•3.5H2O (8). 5 – 7 are isomorphous and crystallize as 3D-networks with two crystallographically independent LnO10 and LnO9 coordination spheres that assemble into Ln2O18 and Ln2O16 polyhedra via edge sharing. Their topology has not previously been observed and was found to be a 3,4,4,5,6-coordinated 3,4,4,5,6T61 net. The known compound 8 crystallizes also as a 3D-network and is isomorphous to other previously described lanthanide glutarate hydrates. 8 has a 3,4,5-coordinated 3,4,5T202 net topology, which has not been determined before

Using simulations to evaluate Mantel-based methods for assessing landscape resistance to gene flow

Mantel-based tests have been the primary analytical methods for understanding how landscape features influence observed spatial genetic structure. Simulation studies examining Mantel-based approaches have highlighted major challenges associated with the use of such tests and fueled debate on when the Mantel test is appropriate for landscape genetics studies. We aim to provide some clarity in this debate using spatially explicit, individual-based, genetic simulations to examine the effects of the following on the performance of Mantel-based methods: (1) landscape configuration, (2) spatial genetic nonequilibrium, (3) nonlinear relationships between genetic and cost distances, and (4) correlation among cost distances derived from competing resistance models. Under most conditions, Mantel-based methods performed poorly. Causal modeling identified the true model only 22% of the time. Using relative support and simple Mantel r values boosted performance to approximately 50%. Across all methods, performance increased when landscapes were more fragmented, spatial genetic equilibrium was reached, and the relationship between cost distance and genetic distance was linearized. Performance depended on cost distance correlations among resistance models rather than cell-wise resistance correlations. Given these results, we suggest that the use of Mantel tests with linearized relationships is appropriate for discriminating among resistance models that have cost distance correlations <0.85 with each other for causal modeling, or <0.95 for relative support or simple Mantel r. Because most alternative parameterizations of resistance for the same landscape variable will result in highly correlated cost distances, the use of Mantel test-based methods to fine-tune resistance values will often not be effective.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by John Wiley & Sons, Ltd. The published article can be found at: http://onlinelibrary.wiley.com/journal/10.1002/%28ISSN%292045-7758Keywords: landscape genetics, landscape resistance, landscape fragmentation, simulations, CDPOPKeywords: landscape genetics, landscape resistance, landscape fragmentation, simulations, CDPO

FLNC Gene Splice Mutations Cause Dilated\ua0Cardiomyopathy

OBJECTIVE: To identify novel dilated cardiomyopathy (DCM) causing genes, and to elucidate the pathological mechanism leading to DCM by utilizing zebrafish as a model organism. BACKGROUND: DCM, a major cause of heart failure, is frequently familial and caused by a genetic defect. However, only 50% of DCM cases can be attributed to a known DCM gene variant, motivating the ongoing search for novel disease genes. METHODS: We performed whole exome sequencing (WES) in two multigenerational Italian families and one US family with arrhythmogenic DCM without skeletal muscle defects, in whom prior genetic testing had been unrevealing. Pathogenic variants were sought by a combination of bioinformatic filtering and cosegregation testing among affected individuals within the families. We performed function assays and generated a zebrafish morpholino knockdown model. RESULTS: A novel filamin C gene splicing variant (FLNC c.7251+1 G>A) was identified by WES in all affected family members in the two Italian families. A separate novel splicing mutation (FLNC c.5669-1delG) was identified in the US family. Western blot analysis of cardiac heart tissue from an affected individual showed decreased FLNC protein, supporting a haploinsufficiency model of pathogenesis. To further analyze this model, a morpholino knockdown of the ortholog filamin Cb in zebrafish was created which resulted in abnormal cardiac function and ultrastructure. CONCLUSIONS: Using WES, we identified two novel FLNC splicing variants as the likely cause of DCM in three families. We provided protein expression and in vivo zebrafish data supporting haploinsufficiency as the pathogenic mechanism leading to DCM

Reptile-like physiology in Early Jurassic stem-mammals

Despite considerable advances in knowledge of the anatomy, ecology and evolution of early mammals, far less is known about their physiology. Evidence is contradictory concerning the timing and fossil groups in which mammalian endothermy arose. To determine the state of metabolic evolution in two of the earliest stem-mammals, the Early Jurassic Morganucodon and Kuehneotherium, we use separate proxies for basal and maximum metabolic rate. Here we report, using synchrotron X-ray tomographic imaging of incremental tooth cementum, that they had maximum lifespans considerably longer than comparably sized living mammals, but similar to those of reptiles, and so they likely had reptilian-level basal metabolic rates. Measurements of femoral nutrient foramina show Morganucodon had blood flow rates intermediate between living mammals and reptiles, suggesting maximum metabolic rates increased evolutionarily before basal metabolic rates. Stem mammals lacked the elevated endothermic metabolism of living mammals, highlighting the mosaic nature of mammalian physiological evolution. Modern mammals are endothermic, but it has not been clear when this type of metabolism evolved. Here, Newham et al. analyse tooth and bone structure in Early Jurassic stem-mammal fossils to estimate lifespan and blood flow rates, which inform about basal and maximum metabolic rates, respectively, and show these stem-mammals had metabolic rates closer to modern ectothermic reptiles than to endothermic mammals.Peer reviewe

The molecular epidemiology of multiple zoonotic origins of SARS-CoV-2

Understanding the circumstances that lead to pandemics is important for their prevention. Here, we analyze the genomic diversity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) early in the coronavirus disease 2019 (COVID-19) pandemic. We show that SARS-CoV-2 genomic diversity before February 2020 likely comprised only two distinct viral lineages, denoted A and B. Phylodynamic rooting methods, coupled with epidemic simulations, reveal that these lineages were the result of at least two separate cross-species transmission events into humans. The first zoonotic transmission likely involved lineage B viruses around 18 November 2019 (23 October–8 December), while the separate introduction of lineage A likely occurred within weeks of this event. These findings indicate that it is unlikely that SARS-CoV-2 circulated widely in humans prior to November 2019 and define the narrow window between when SARS-CoV-2 first jumped into humans and when the first cases of COVID-19 were reported. As with other coronaviruses, SARS-CoV-2 emergence likely resulted from multiple zoonotic events

Human Genetics in Rheumatoid Arthritis Guides a High-Throughput Drug Screen of the CD40 Signaling Pathway

Although genetic and non-genetic studies in mouse and human implicate the CD40 pathway in rheumatoid arthritis (RA), there are no approved drugs that inhibit CD40 signaling for clinical care in RA or any other disease. Here, we sought to understand the biological consequences of a CD40 risk variant in RA discovered by a previous genome-wide association study (GWAS) and to perform a high-throughput drug screen for modulators of CD40 signaling based on human genetic findings. First, we fine-map the CD40 risk locus in 7,222 seropositive RA patients and 15,870 controls, together with deep sequencing of CD40 coding exons in 500 RA cases and 650 controls, to identify a single SNP that explains the entire signal of association (rs4810485, P = 1.4×10(−9)). Second, we demonstrate that subjects homozygous for the RA risk allele have ∼33% more CD40 on the surface of primary human CD19+ B lymphocytes than subjects homozygous for the non-risk allele (P = 10(−9)), a finding corroborated by expression quantitative trait loci (eQTL) analysis in peripheral blood mononuclear cells from 1,469 healthy control individuals. Third, we use retroviral shRNA infection to perturb the amount of CD40 on the surface of a human B lymphocyte cell line (BL2) and observe a direct correlation between amount of CD40 protein and phosphorylation of RelA (p65), a subunit of the NF-κB transcription factor. Finally, we develop a high-throughput NF-κB luciferase reporter assay in BL2 cells activated with trimerized CD40 ligand (tCD40L) and conduct an HTS of 1,982 chemical compounds and FDA–approved drugs. After a series of counter-screens and testing in primary human CD19+ B cells, we identify 2 novel chemical inhibitors not previously implicated in inflammation or CD40-mediated NF-κB signaling. Our study demonstrates proof-of-concept that human genetics can be used to guide the development of phenotype-based, high-throughput small-molecule screens to identify potential novel therapies in complex traits such as RA

DNA mismatch repair gene MSH6 implicated in determining age at natural menopause

notes: PMCID: PMC3976329This is a freely-available open access publication. Please cite the published version which is available via the DOI link in this record.The length of female reproductive lifespan is associated with multiple adverse outcomes, including breast cancer, cardiovascular disease and infertility. The biological processes that govern the timing of the beginning and end of reproductive life are not well understood. Genetic variants are known to contribute to ∼50% of the variation in both age at menarche and menopause, but to date the known genes explain <15% of the genetic component. We have used genome-wide association in a bivariate meta-analysis of both traits to identify genes involved in determining reproductive lifespan. We observed significant genetic correlation between the two traits using genome-wide complex trait analysis. However, we found no robust statistical evidence for individual variants with an effect on both traits. A novel association with age at menopause was detected for a variant rs1800932 in the mismatch repair gene MSH6 (P = 1.9 × 10(-9)), which was also associated with altered expression levels of MSH6 mRNA in multiple tissues. This study contributes to the growing evidence that DNA repair processes play a key role in ovarian ageing and could be an important therapeutic target for infertility.UK Medical Research CouncilWellcome Trus

Abdominal aortic aneurysm is associated with a variant in low-density lipoprotein receptor-related protein 1

Abdominal aortic aneurysm (AAA) is a common cause of morbidity and mortality and has a significant heritability. We carried out a genome-wide association discovery study of 1866 patients with AAA and 5435 controls and replication of promising signals (lead SNP with a p value &lt; 1 × 10-5) in 2871 additional cases and 32,687 controls and performed further follow-up in 1491 AAA and 11,060 controls. In the discovery study, nine loci demonstrated association with AAA (p &lt; 1 × 10-5). In the replication sample, the lead SNP at one of these loci, rs1466535, located within intron 1 of low-density-lipoprotein receptor-related protein 1 (LRP1) demonstrated significant association (p = 0.0042). We confirmed the association of rs1466535 and AAA in our follow-up study (p = 0.035). In a combined analysis (6228 AAA and 49182 controls), rs1466535 had a consistent effect size and direction in all sample sets (combined p = 4.52 × 10-10, odds ratio 1.15 [1.10-1.21]). No associations were seen for either rs1466535 or the 12q13.3 locus in independent association studies of coronary artery disease, blood pressure, diabetes, or hyperlipidaemia, suggesting that this locus is specific to AAA. Gene-expression studies demonstrated a trend toward increased LRP1 expression for the rs1466535 CC genotype in arterial tissues; there was a significant (p = 0.029) 1.19-fold (1.04-1.36) increase in LRP1 expression in CC homozygotes compared to TT homozygotes in aortic adventitia. Functional studies demonstrated that rs1466535 might alter a SREBP-1 binding site and influence enhancer activity at the locus. In conclusion, this study has identified a biologically plausible genetic variant associated specifically with AAA, and we suggest that this variant has a possible functional role in LRP1 expression