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Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic data sets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and to the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed frameworkstdpopsimseeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version ofstdpopsimfocused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release ofstdpopsim(version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than three-fold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements tostdpopsimaim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

BACKGROUND & AIMS: The sucrase-isomaltase (SI) c.273_274delAG loss-of-function variant is common in Arctic populations and causes congenital sucrase-isomaltase deficiency, which is an inability to break down and absorb sucrose and isomaltose. Children with this condition experience gastrointestinal symptoms when dietary sucrose is introduced. We aimed to describe the health of adults with sucrase-isomaltase deficiency.METHODS: The association between c.273_274delAG and phenotypes related to metabolic health was assessed in 2 cohorts of Greenlandic adults (n = 4922 and n = 1629). A sucrase-isomaltase knockout (Sis-KO) mouse model was used to further elucidate the findings.RESULTS: Homozygous carriers of the variant had a markedly healthier metabolic profile than the remaining population, including lower body mass index (β [standard error], -2.0 [0.5] kg/m2; P = 3.1 × 10-5), body weight (-4.8 [1.4] kg; P = 5.1 × 10-4), fat percentage (-3.3% [1.0%]; P = 3.7 × 10-4), fasting triglyceride (-0.27 [0.07] mmol/L; P = 2.3 × 10-6), and remnant cholesterol (-0.11 [0.03] mmol/L; P = 4.2 × 10-5). Further analyses suggested that this was likely mediated partly by higher circulating levels of acetate observed in homozygous carriers (β [standard error], 0.056 [0.002] mmol/L; P = 2.1 × 10-26), and partly by reduced sucrose uptake, but not lower caloric intake. These findings were verified in Sis-KO mice, which, compared with wild-type mice, were leaner on a sucrose-containing diet, despite similar caloric intake, had significantly higher plasma acetate levels in response to a sucrose gavage, and had lower plasma glucose level in response to a sucrose-tolerance test.CONCLUSIONS: These results suggest that sucrase-isomaltase constitutes a promising drug target for improvement of metabolic health, and that the health benefits are mediated by reduced dietary sucrose uptake and possibly also by higher levels of circulating acetate.

The common Arctic-specific

The common Arctic-specific LDLR p.G137S variant was recently shown to be associated with elevated lipid levels. Motivated by this, we aimed to investigate the effect of p.G137S on metabolic health and cardiovascular disease risk among Greenlanders to quantify its impact on the population. In a population-based Greenlandic cohort (n = 5,063), we tested for associations between the p.G137S variant and metabolic health traits as well as cardiovascular disease risk based on registry data. In addition, we explored the variant's impact on plasma NMR measured lipoprotein concentration and composition in another Greenlandic cohort (n = 1,629); 29.5% of the individuals in the cohort carried at least one copy of the p.G137S risk allele. Furthermore, 25.4% of the heterozygous and 54.7% of the homozygous carriers had high levels (>4.9 mmol/L) of serum LDL cholesterol, which is above the diagnostic level for familial hypercholesterolemia (FH). Moreover, p.G137S was associated with an overall atherosclerotic lipid profile, and increased risk of ischemic heart disease (HR [95% CI], 1.51 [1.18–1.92], p = 0.00096), peripheral artery disease (1.69 [1.01–2.82], p = 0.046), and coronary operations (1.78 [1.21–2.62], p = 0.0035). Due to its high frequency and large effect sizes, p.G137S has a marked population-level impact, increasing the risk of FH and cardiovascular disease for up to 30% of the Greenlandic population. Thus, p.G137S is a potential marker for early intervention in Arctic populations.