Identifying and testing marker–trait associations for growth and phenology in three pine species:Implications for genomic prediction

In tree species, genomic prediction offers the potential to forecast mature trait values in early growth stages, if robust marker-trait associations can be identified. Here we apply a novel multispecies approach using genotypes from a new genotyping array, based on 20,795 SNPs from three closely related pine species (Pinus sylvestris, Pinus uncinata and Pinus mugo), to test for associations with growth and phenology data from a common garden study. Predictive models constructed using significantly associated SNPs were then tested and applied to an independent multisite field trial of P. sylvestris and the capability to predict trait values was evaluated. One hundred and eighteen SNPs showed significant associations with the traits in the pine species. Common SNPs (MAF > 0.05) associated with bud set were only found in genes putatively involved in growth and development, whereas those associated with growth and budburst were also located in genes putatively involved in response to environment and, to a lesser extent, reproduction. At one of the two independent sites, the model we developed produced highly significant correlations between predicted values and observed height data (YA, height 2020: r = 0.376, p < 0.001). Predicted values estimated with our budburst model were weakly but positively correlated with duration of budburst at one of the sites (GS, 2015: r = 0.204, p = 0.034; 2018: r = 0.205, p = 0.034-0.037) and negatively associated with budburst timing at the other (YA: r = -0.202, p = 0.046). Genomic prediction resulted in the selection of sets of trees whose mean height was taller than the average for each site. Our results provide tentative support for the capability of prediction models to forecast trait values in trees, while highlighting the need for caution in applying them to trees grown in different environments

Phenotypic trait variation in a long-term multisite common garden experiment of Scots pine in Scotland

Multisite common garden experiments, exposing common pools of genetic diversity to a range of environments, allow quantification of plastic and genetic components of trait variation. For tree species, such studies must be long term as they typically only express mature traits after many years. As well as evaluating standing genetic diversity, these experiments provide an ongoing test of genetic variation against changing environmental conditions and form a vital resource for understanding how species respond to abiotic and biotic variation. Finally, quantitative assessments of phenotypic variation are essential to pair with rapidly accumulating genomic data to advance understanding of the genetic basis of trait variation, and its interaction with climatic change. We describe a multisite, population-progeny, common garden experiment of the economically and ecologically important tree species, Scots pine, collected from across its native range in Scotland and grown in three contrasting environments. Phenotypic traits, including height, stem diameter and budburst were measured over 14 growing seasons from nursery to field site. The datasets presented have a wide range of applications

RENEB accident simulation exercise

Purpose: The RENEB accident exercise was carried out in order to train the RENEB participants in coordinating and managing potentially large data sets that would be generated in case of a major radiological event. Materials and methods: Each participant was offered the possibility to activate the network by sending an alerting email about a simulated radiation emergency. The same participant had to collect, compile and report capacity, triage categorization and exposure scenario results obtained from all other participants. The exercise was performed over 27 weeks and involved the network consisting of 28 institutes: 21 RENEB members, four candidates and three non-RENEB partners. Results: The duration of a single exercise never exceeded 10 days, while the response from the assisting laboratories never came later than within half a day. During each week of the exercise, around 4500 samples were reported by all service laboratories (SL) to be examined and 54 scenarios were coherently estimated by all laboratories (the standard deviation from the mean of all SL answers for a given scenario category and a set of data was not larger than 3 patient codes). Conclusions: Each participant received training in both the role of a reference laboratory (activating the network) and of a service laboratory (responding to an activation request). The procedures in the case of radiological event were successfully established and tested.VII Programa Marco de Investigación y Desarrollo (VIIPM) de la Unión Europea. nº 29551

Systemic lupus erythematosus phenotypes formed from machine learning with a specific focus on cognitive impairment

OBJECTIVE: To phenotype SLE based on symptom burden (disease damage, system involvement and patient reported outcomes), with a specific focus on objective and subjective cognitive function. METHODS: SLE patients ages 18-65&nbsp;years underwent objective cognitive assessment using the ACR Neuropsychological Battery (ACR-NB) and data were collected on demographic and clinical variables, disease burden/activity, health-related quality of life (HRQoL), depression, anxiety, fatigue and perceived cognitive deficits. Similarity network fusion (SNF) was used to identify patient subtypes. Differences between the subtypes were evaluated using Kruskal-Wallis and χ2 tests. RESULTS: Of the 238 patients, 90% were female, with a mean age of 41 years (s.d. 12) and a disease duration of 14 years (s.d. 10) at the study visit. The SNF analysis defined two subtypes (A and B) with distinct patterns in objective and subjective cognitive function, disease burden/damage, HRQoL, anxiety and depression. Subtype A performed worst on all significantly different tests of objective cognitive function (P &lt; 0.03) compared with subtype B. Subtype A also had greater levels of subjective cognitive function (P &lt; 0.001), disease burden/damage (P &lt; 0.04), HRQoL (P &lt; 0.001) and psychiatric measures (P &lt; 0.001) compared with subtype B. CONCLUSION: This study demonstrates the complexity of cognitive impairment (CI) in SLE and that individual, multifactorial phenotypes exist. Those with greater disease burden, from SLE-specific factors or other factors associated with chronic conditions, report poorer cognitive functioning and perform worse on objective cognitive measures. By exploring different ways of phenotyping SLE we may better define CI in SLE. Ultimately this will aid our understanding of personalized CI trajectories and identification of appropriate treatments

RENEB accident simulation exercise

Purpose: The RENEB accident exercise was carried out in order to train the RENEB participants in coordinating and managing potentially large data sets that would be generated in case of a major radiological event. Materials and methods: Each participant was offered the possibility to activate the network by sending an alerting email about a simulated radiation emergency. The same participant had to collect, compile and report capacity, triage categorization and exposure scenario results obtained from all other participants. The exercise was performed over 27 weeks and involved the network consisting of 28 institutes: 21 RENEB members, four candidates and three non-RENEB partners. Results: The duration of a single exercise never exceeded 10 days, while the response from the assisting laboratories never came later than within half a day. During each week of the exercise, around 4500 samples were reported by all service laboratories (SL) to be examined and 54 scenarios were coherently estimated by all laboratories (the standard deviation from the mean of all SL answers for a given scenario category and a set of data was not larger than 3 patient codes). Conclusions: Each participant received training in both the role of a reference laboratory (activating the network) and of a service laboratory (responding to an activation request). The procedures in the case of radiological event were successfully established and tested

Hybrid model of intensive lifestyle intervention is potentially effective in patients with diabetes & obesity for post-COVID era

The Weight Achievement and Intensive Treatment (Why WAIT) program is a 12-week multidisciplinary intensive lifestyle intervention (ILI) for patients with diabetes and obesity in real-world clinical practice that has led to long-term weight loss maintenance for up to 10 years. During COVID-19, we reported that a virtual model (VM) of the program was equally effective in reducing body weight and improving glycemic control. Here, we test a newly-introduced hybrid model (HM), to accommodate ongoing restrictions of the pandemic. We evaluated 56 participants: 18 from HM, 16 from VM and 22 from the in-person model (iPM). At 12 weeks, mean change in body weight from baseline for HM was -8.2 ± 5.0 kg; p&lt;0.001. Mean change in A1C for HM was -0.6 ± 0.6%; p=0.002. There were no significant differences in body weight reduction (p=0.7) or A1C reduction (p=0.6) between groups. Blood pressure, lipid profile, and all other parameters showed improvements without significant differences between groups. Overall, HM is as effective as VM and iPM in reducing body weight and A1C after 12 weeks. Given its scalability, HM could be offered to more patients with diabetes and obesity who may benefit from its increased flexibility and enhanced accountability without compromising the multidisciplinary approach for a post-COVID era

Pinus sylvestris sapling growth and recovery from mammalian browsing

Plants employ a range of resistance and tolerance mechanisms to counteract the effects of herbivory and research is still unravelling which strategies are most effective against which herbivores. In commercial forestry, research has focused on understanding the genetic basis of resistance traits and using resistance as a management strategy. However, there has been less focus on addressing the basis and utility of tolerance traits. Scots pine (Pinus sylvestris) is a well-studied forest tree due to its wide distribution, commercial importance and use in forest restoration of degraded lands as an important foundation tree species. Several herbivore species browse Scots pine and, here, we examine the genetic basis of recovery of Scots pine saplings following browsing by red deer (Cervus elaphus) and attempt to describe which plant traits are associated with sapling tolerance. Three hundred saplings from five different open pollinated mothers (five families) were offered to deer in a feeding trial and saplings were left to recover from browsing for one and a half years (two annual growth seasons) in a randomised, replicated common garden. Seven sapling traits were assessed at this time: survival, stem diameter below the leading bud, stem diameter at the base of the sapling, total sapling height, length of the leading bud, average length of three lateral buds, and the total number of lateral buds. Results indicate that browsing of Scots pine by deer influences sapling survival and recovery ability. There were significant family differences in morphological growth traits and these differences were maintained in the presence and absence of browsing. For one recovery trait, length of the leading bud, overcompensation in response to browsing was evident in all families. These data, matched with our finding of no negative relationships between any recovery traits, indicate that Scots pine is quite robust to once-off browsing events by deer. We suggest that at the sapling stage, Scots pine do not employ resistance as a strategy against deer, but tolerate deer browsing to counteract the negative impacts of herbivory. Hence, the use of recovery traits as a management tool to mitigate the negative impacts of browsing is an option worthy of further investigation