RESUMEN
Large sample datasets have been regarded as the primary basis for innovative discoveries and the solution to missing heritability in genome-wide association studies. However, their computational complexity cannot consider all comprehensive effects and all polygenic backgrounds, which reduces the effectiveness of large datasets. To address these challenges, we included all effects and polygenic backgrounds in a mixed logistic model for binary traits and compressed four variance components into two. The compressed model combined three computational algorithms to develop an innovative method, called FastBiCmrMLM, for large data analysis. These algorithms were tailored to sample size, computational speed, and reduced memory requirements. To mine additional genes, linkage disequilibrium markers were replaced by bin-based haplotypes, which are analyzed by FastBiCmrMLM, named FastBiCmrMLM-Hap. Simulation studies highlighted the superiority of FastBiCmrMLM over GMMAT, SAIGE and fastGWA-GLMM in identifying dominant, small α (allele substitution effect), and rare variants. In the UK Biobank-scale dataset, we demonstrated that FastBiCmrMLM could detect variants as small as 0.03% and with α ≈ 0. In re-analyses of seven diseases in the WTCCC datasets, 29 candidate genes, with both functional and TWAS evidence, around 36 variants identified only by the new methods, strongly validated the new methods. These methods offer a new way to decipher the genetic architecture of binary traits and address the challenges outlined above.
Asunto(s)
Algoritmos , Estudio de Asociación del Genoma Completo , Estudio de Asociación del Genoma Completo/métodos , Humanos , Modelos Logísticos , Estudios de Casos y Controles , Desequilibrio de Ligamiento , Polimorfismo de Nucleótido Simple , Genómica/métodos , Simulación por Computador , Haplotipos , Modelos GenéticosRESUMEN
A linear supramolecular architecture was successfully constructed by the inclusion complexation of α-cyclodextrin with azobenzene and the host-stabilized charge-transfer interaction of naphthalene and a bispyridinium guest with cucurbit[8]uril in water, which was comprehensively characterized by (1)Hâ NMR spectroscopy, UV/Vis absorption, fluorescence, circular dichroism spectroscopy, dynamic laser scattering, and microscopic observations. Significantly, because it benefits from the photoinduced isomerization of the azophenyl group and the chemical reduction of bispyridinium moiety with noncovalent connections, the assembly/disassembly process of this supramolecular nanostructure can be efficiently modulated by external stimuli, including temperature, UV and visible-light irradiation, and chemical redox.
RESUMEN
The impacts of climate change on forest community composition are still not well known. Although directional trends in climate change and community composition change were reported in recent years, further quantitative analyses are urgently needed. Previous studies focused on measuring population growth rates in a single time period, neglecting the development of the populations. Here we aimed to compose a method for calculating the community composition change, and to testify the impacts of climate change on community composition change within a relatively short period (several decades) based on long-term monitoring data from two plots-Dinghushan Biosphere Reserve, China (DBR) and Barro Colorado Island, Panama (BCI)-that are located in tropical and subtropical regions. We proposed a relatively more concise index, Slnλ, which refers to an overall population growth rate based on the dominant species in a community. The results indicated that the population growth rate of a majority of populations has decreased over the past few decades. This decrease was mainly caused by population development. The increasing temperature had a positive effect on population growth rates and community change rates. Our results promote understanding and explaining variations in population growth rates and community composition rates, and are helpful to predict population dynamics and population responses to climate change.