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- Riehl, Jennifer F. L., et al.
(författare)
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Genomic and transcriptomic analyses reveal polygenic architecture for ecologically important traits in aspen (Populus tremuloides Michx.)
- 2023
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Ingår i: Ecology and Evolution. - : John Wiley & Sons. - 2045-7758. ; 13:10
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Tidskriftsartikel (refereegranskat)abstract
- Intraspecific genetic variation in foundation species such as aspen (Populus tremuloides Michx.) shapes their impact on forest structure and function. Identifying genes underlying ecologically important traits is key to understanding that impact. Previous studies, using single-locus genome-wide association (GWA) analyses to identify candidate genes, have identified fewer genes than anticipated for highly heritable quantitative traits. Mounting evidence suggests that polygenic control of quantitative traits is largely responsible for this “missing heritability” phenomenon. Our research characterized the genetic architecture of 30 ecologically important traits using a common garden of aspen through genomic and transcriptomic analyses. A multilocus association model revealed that most traits displayed a highly polygenic architecture, with most variation explained by loci with small effects (likely below the detection levels of single-locus GWA methods). Consistent with a polygenic architecture, our single-locus GWA analyses found only 38 significant SNPs in 22 genes across 15 traits. Next, we used differential expression analysis on a subset of aspen genets with divergent concentrations of salicinoid phenolic glycosides (key defense traits). This complementary method to traditional GWA discovered 1243 differentially expressed genes for a polygenic trait. Soft clustering analysis revealed three gene clusters (241 candidate genes) involved in secondary metabolite biosynthesis and regulation. Our work reveals that ecologically important traits governing higher-order community- and ecosystem-level attributes of a foundation forest tree species have complex underlying genetic structures and will require methods beyond traditional GWA analyses to unravel.
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- Kielt, Matthew, et al.
(författare)
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Classifying multicenter approaches to invasive mechanical ventilation for infants with bronchopulmonary dysplasia using hierarchical clustering analysis
- 2023
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Ingår i: Pediatric Pulmonology. - : John Wiley & Sons. - 8755-6863 .- 1099-0496. ; 58:8, s. 2323-2332
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Tidskriftsartikel (refereegranskat)abstract
- IntroductionEvidence-based ventilation strategies for infants with severe bronchopulmonary dysplasia (BPD) remain unknown. Determining whether contemporary ventilation approaches cluster as specific BPD strategies may better characterize care and enhance the design of clinical trials. The objective of this study was to test the hypothesis that unsupervised, multifactorial clustering analysis of point prevalence ventilator setting data would classify a discrete number of physiology-based approaches to mechanical ventilation in a multicenter cohort of infants with severe BPD.MethodsWe performed a secondary analysis of a multicenter point prevalence study of infants with severe BPD treated with invasive mechanical ventilation. We clustered the cohort by mean airway pressure (MAP), positive end expiratory pressure (PEEP), set respiratory rate, and inspiratory time (Ti) using Ward's hierarchical clustering analysis (HCA).ResultsSeventy-eight patients with severe BPD were included from 14 centers. HCA classified three discrete clusters as determined by an agglomerative coefficient of 0.97. Cluster stability was relatively strong as determined by Jaccard coefficient means of 0.79, 0.85, and 0.77 for clusters 1, 2, and 3, respectively. The median PEEP, MAP, rate, Ti, and PIP differed significantly between clusters for each comparison by Kruskall–Wallis testing (p < 0.0001).ConclusionsIn this study, unsupervised clustering analysis of ventilator setting data identified three discrete approaches to mechanical ventilation in a multicenter cohort of infants with severe BPD. Prospective trials are needed to determine whether these approaches to mechanical ventilation are associated with specific severe BPD clinical phenotypes and differentially modify respiratory outcomes.
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