Health service use was driven by the number of comorbid conditions, including diabetes and nondiabetes-related conditions, highlighting the importance of aligning diabetes care plans with patients' comorbidities.

BackgroundBy targeting SNPs contained in both coding and non-coding areas of the genome, we are able to identify genetic differences and characterize genome-wide patterns of variation among individuals, populations and species. We investigated the utility of 454 sequencing and MassARRAY genotyping for population genetics in natural populations of the teleost, Fundulus heteroclitus as well as closely related Fundulus species (F. grandis, F. majalis and F. similis).ResultsWe used 454 pyrosequencing and MassARRAY genotyping technology to identify and type 458 genome-wide SNPs and determine genetic differentiation within and between populations and species of Fundulus. Specifically, pyrosequencing identified 96 putative SNPs across coding and non-coding regions of the F. heteroclitus genome: 88.8% were verified as true SNPs with MassARRAY. Additionally, putative SNPs identified in F. heteroclitus EST sequences were verified in most (86.5%) F. heteroclitus individuals; fewer were genotyped in F. grandis (74.4%), F. majalis (72.9%), and F. similis (60.7%) individuals. SNPs were polymorphic and showed latitudinal clinal variation separating northern and southern populations and established isolation by distance in F. heteroclitus populations. In F. grandis, SNPs were less polymorphic but still established isolation by distance. Markers differentiated species and populations.ConclusionsIn total, these approaches were used to quickly determine differences within the Fundulus genome and provide markers for population genetic studies.

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Background Skeletal muscle exhibits remarkable plasticity under both physiological and pathological conditions. One major manifestation of this plasticity is muscle atrophy that is an adaptive response to catabolic stimuli. Because the heterogeneous transcriptome responses to catabolism in different types of muscle cells are not fully characterized, we applied single-nucleus RNA sequencing (snRNA-seq) to unveil muscle atrophy related transcriptional changes at single nucleus resolution. Methods Using a sciatic denervation mouse model of muscle atrophy, snRNA-seq was performed to generate single-nucleus transcriptional profiles of the gastrocnemius muscle from normal and denervated mice. Various bioinformatics analyses, including unsupervised clustering, functional enrichment analysis, trajectory analysis, regulon inference, metabolic signature characterization and cell-cell communication prediction, were applied to illustrate the transcriptome changes of the individual cell types. Results A total of 29 539 muscle nuclei (normal vs. denervation: 15 739 vs. 13 800) were classified into 13 nuclear types according to the known cell markers. Among these, the type IIb myonuclei were further divided into two subgroups, which we designated as type IIb1 and type IIb2 myonuclei. In response to denervation, the proportion of type IIb2 myonuclei increased sharply (78.12% vs. 38.45%, P < 0.05). Concomitantly, trajectory analysis revealed that denervated type IIb2 myonuclei clearly deviated away from the normal type IIb2 myonuclei, indicating that this subgroup underwent robust transcriptional reprogramming upon denervation. Signature genes in denervated type IIb2 myonuclei included Runx1, Gadd45a, Igfn1, Robo2, Dlg2, and Sh3d19 (P < 0.001). The gene regulatory network analysis captured a group of atrophy-related regulons (Foxo3, Runx1, Elk4, and Bhlhe40) whose activities were enhanced (P < 0.01), especially in the type IIb2 myonuclei. The metabolic landscape in the myonuclei showed that most of the metabolic pathways were down-regulated by denervation (P < 0.001), while some of the metabolic signalling, such as glutathione metabolism, was specifically activated in the denervated type IIb2 myonulei. We also investigated the transcriptomic alterations in the type I myofibres, muscle stem cells, fibro-adipogenic progenitors, macrophages, endothelial cells and pericytes and characterized their signature responses to denervation. By predicting the cell-cell interactions, we observed that the communications between myofibres and muscle resident cells were diminished by denervation. Conclusions Our results define the myonuclear transition, metabolic remodelling, and gene regulation networks reprogramming associated with denervation-induced muscle atrophy and illustrate the molecular basis of the heterogeneity and plasticity of muscle cells in response to catabolism. These results provide a useful resource for exploring the molecular mechanism of muscle atrophy.