Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians

We conducted a three-stage genetic study to identify susceptibility loci for type 2 diabetes (T2D) in east Asian populations. We followed our stage 1 meta-analysis of eight T2D genome-wide association studies (6,952 cases with T2D and 11,865 controls) with a stage 2 in silico replication analysis (5,843 cases and 4,574 controls) and a stage 3 de novo replication analysis (12,284 cases and 13,172 controls). The combined analysis identified eight new T2D loci reaching genome-wide significance, which mapped in or near GLIS3, PEPD, FITM2-R3HDML-HNF4A, KCNK16, MAEA, GCC1-PAX4, PSMD6 and ZFAND3. GLIS3, which is involved in pancreatic beta cell development and insulin gene expression1,2, is known for its association with fasting glucose levels3,4. The evidence of an association with T2D for PEPD5 and HNF4A6,7 has been shown in previous studies. KCNK16 may regulate glucose-dependent insulin secretion in the pancreas. These findings, derived from an east Asian population, provide new perspectives on the etiology of T2D

Estimation of Linkage Disequilibrium, Effective Population Size, and Genetic Parameters of Phenotypic Traits in Dabieshan Cattle

Dabieshan cattle (DBSC) are a valuable genetic resource for indigenous cattle breeds in China. It is a small to medium-sized breed with slower growth, but with good meat quality and fat deposition. Genetic markers could be used for the estimation of population genetic structure and genetic parameters. In this work, we genotyped the DBSC breeding population (n = 235) with the GeneSeek Genomic Profiler (GGP) 100 k density genomic chip. Genotype data of 222 individuals and 81,579 SNPs were retained after quality control. The average minor allele frequency (MAF) was 0.20 and the average linkage disequilibrium (LD) level (r2) was 0.67 at a distance of 0–50 Kb. The estimated relationship coefficient and effective population size (Ne) were 0.023 and 86 for the current generation. In addition, we used genotype data to estimate the genetic parameters of the population’s phenotypic traits. Among them, height at hip cross (HHC) and shin circumference (SC) were rather high heritability traits, with heritability of 0.41 and 0.54, respectively. The results reflected the current cattle population’s extent of inbreeding and history. Through the principal breeding parameters, genomic breeding would significantly improve the genetic progress of breeding

Polymorphisms of the Growth Hormone Releasing Hormone Receptor Gene Affect Body Conformation Traits in Chinese Dabieshan Cattle

This study was performed to expose the polymorphisms of the growth hormone-releasing hormone receptor gene in Chinese Dabieshan cattle, evaluate its effect on body conformation traits, and find potential molecular markers in Chinese cattle. The GHRHR structure and the phylogenetic tree were analyzed using bioinformatics software. The polymorphism of the GHRHR gene in 486 female cattle was genotyped by PCR-RFLP and DNA sequencing, and the association between SNPs and body conformation traits of Chinese Dabieshan cattle was analyzed by one-way ANOVA in SPSS software. GHRHR was often conserved in nine species, and its sequence of cattle was closest to sheep and goats. Six polymorphic SNPs were identified, g.10667A > C and g.10670A > C were missense mutation. The association analysis indicated that the six SNPs significantly influenced the body conformation traits of Chinese Dabieshan cattle (p < 0.05). Six haplotypes were identified and Hap1 (-CAACGA-) had the highest frequency (36.10%). The Hap3/5 (-GCCCCCGGAAGG-) exhibited a significantly greater wither height (WH), hip height (HH), heart girth (HG), and hip width (HW) (p < 0.05). Overall, the polymorphisms of GHRHR affected the body conformation traits of Chinese Dabieshan cattle, and the GHRHR gene could be used as a molecular marker in Dabieshan cattle breeding programs

Relationship between Tree Richness and Temporary Stability of Plant Communities: A Case Study of a Forest in Northeast China

The relationship between diversity and stability is a classic issue in ecology, but no general consensus has been achieved. To address this relationship, a field survey of a forest in Northeast China was conducted. The temporary stability was defined from the perspective of community characteristics. The results showed that communities with the highest temporary stability value were characterized by a single dominant species. A significant linear relationship with a low R2 value was observed between temporary stability and tree richness. When dominant and non-dominant tree species were studied, no significant linear relationship was obtained between temporary stability and non-dominant tree richness. However, the relationship between temporary stability and dominant tree richness was significant with a high R2 value, and the temporary stability decreased with increasing dominant tree richness. This study demonstrates that dominant tree richness is closely related to temporary stability, and temporary stability can serve as a stability indicator. The results provide a new perspective for understanding stability and additional information for revealing the relationship between diversity and stability in forest ecosystems

Enhanced visible-light-driven photocatalytic performance of Ag/AgGaO2 metal semiconductor heterostructures

A novel visible-light-driven photocatalyst of Ag/AgGaO₂ metal semiconductor heterostructures (MSH) has been prepared by a combined sol-gel and ion exchange method. XRD, DRS, SEM, PL and XPS were employed to characterize the as-synthesized samples. The Ag/AgGaO₂ MSH exhibited a remarkably high photocatalytic activity for the degradation of methyl blue (MB) under visible light irradiation. The degradation rate of Ag/AgGaO₂ MSH reached to 95% in decomposing MB for 180 min, which is 31.2% higher compared to that of pure AgGaO₂ photocatalyst. The improved photocatalytic performance of Ag/AgGaO₂ MSH could be ascribed to the synergistic effect, which is the enhanced visible-light absorption and efficient electron-hole separation. This suggests that Ag/AgGaO₂ MSH would have a potential application in the fields of dye wastewater purification

Assessment of Permeability Windbreak Forests with Different Porosities Based on Laser Scanning and Computational Fluid Dynamics

Accurate modeling of windbreaks is essential for the precise assessment of wind protection performance. However, in most windbreak studies, the models used the approximate shape of the simulated trees, resulting in significant differences between the simulated results and the actual situation. In this study, terrestrial laser scanning (TLS) was used to extract tree parameters, which were used in a quantitative structural model (AdQSM) to recreate the tree structure and restore the wind field environment using the computational fluid dynamics software PHOENICS. In addition, we compared the bias, precision, and accuracy of porosity of Ginkgo biloba (with elliptical crown) and Populus alba (with conical crown), which have been commonly used in previous windbreak studies. The results showed that AdQSM has a high reduction rate and ability to reproduce the field conditions of the study area. After wind field simulation, the wind speed root mean square errors of the point cloud model at three heights (3, 6, and 9 m) were 0.272, 0.377, and 0.437 m/s, respectively, and the wind speed correlation coefficients r were 0.967, 0.965, and 0.937, respectively, which were significantly more accurate than those of the remaining two structures. Finally, the porosity of the windbreak forest obtained using the modeled sample plot showed a higher correlation with the wind permeability coefficient than that obtained using the existing approach. Windbreak models with three different porosities under the same conditions had different effects on the wind environment, particularly the location of the maximum wind speed reduction, variation of wind speed with porosity, and recovery rate of leeward wind speed. TLS can accurately extract windbreak factors and calculate the porosity, thus greatly improving the reliability of windbreak effect research in windbreak forests. This study provides a promising direction for future research related to the simulation of windbreak effects in windbreak forests

Classification of Street Tree Species Using UAV Tilt Photogrammetry

As an important component of the urban ecosystem, street trees have made an outstanding contribution to alleviating urban environmental pollution. Accurately extracting tree characteristics and species information can facilitate the monitoring and management of street trees, as well as aiding landscaping and studies of urban ecology. In this study, we selected the suburban areas of Beijing and Zhangjiakou and investigated six representative street tree species using unmanned aerial vehicle (UAV) tilt photogrammetry. We extracted five tree attributes and four combined attribute parameters and used four types of commonly-used machine learning classification algorithms as classifiers for tree species classification. The results show that random forest (RF), support vector machine (SVM), and back propagation (BP) neural network provide better classification results when using combined parameters for tree species classification, compared with those using individual tree attributes alone; however, the K-nearest neighbor (KNN) algorithm produced the opposite results. The best combination for classification is the BP neural network using combined attributes, with a classification precision of 89.1% and F-measure of 0.872, and we conclude that this approach best meets the requirements of street tree surveys. The results also demonstrate that optical UAV tilt photogrammetry combined with a machine learning classification algorithm is a low-cost, high-efficiency, and high-precision method for tree species classification

Classification of Street Tree Species Using UAV Tilt Photogrammetry

As an important component of the urban ecosystem, street trees have made an outstanding contribution to alleviating urban environmental pollution. Accurately extracting tree characteristics and species information can facilitate the monitoring and management of street trees, as well as aiding landscaping and studies of urban ecology. In this study, we selected the suburban areas of Beijing and Zhangjiakou and investigated six representative street tree species using unmanned aerial vehicle (UAV) tilt photogrammetry. We extracted five tree attributes and four combined attribute parameters and used four types of commonly-used machine learning classification algorithms as classifiers for tree species classification. The results show that random forest (RF), support vector machine (SVM), and back propagation (BP) neural network provide better classification results when using combined parameters for tree species classification, compared with those using individual tree attributes alone; however, the K-nearest neighbor (KNN) algorithm produced the opposite results. The best combination for classification is the BP neural network using combined attributes, with a classification precision of 89.1% and F-measure of 0.872, and we conclude that this approach best meets the requirements of street tree surveys. The results also demonstrate that optical UAV tilt photogrammetry combined with a machine learning classification algorithm is a low-cost, high-efficiency, and high-precision method for tree species classification

Genetic Diversity and Selective Signature in Dabieshan Cattle Revealed by Whole-Genome Resequencing

Dabieshan cattle are a typical breed of southern Chinese cattle that have the characteristics of muscularity, excellent meat quality and tolerance to temperature and humidity. Based on 148 whole-genome data, our analysis disclosed the ancestry components of Dabieshan cattle with Chinese indicine (0.857) and East Asian taurine (0.139). The Dabieshan genome demonstrated a higher genomic diversity compared with the other eight populations, supported by the observed nucleotide diversity, linkage disequilibrium decay and runs of homozygosity. The candidate genes were detected by a selective sweep, which might relate to the fertility (GPX5, GPX6), feed efficiency (SLC2A5), immune response (IGLL1, BOLA-DQA2, BOLA-DQB), heat resistance (DnaJC1, DnaJC13, HSPA4), fat deposition (MLLT10) and the coat color (ASIP). We also identified the “East Asian taurine-like” segments in Dabieshan cattle, which might contribute to meat quality traits. The results revealed by the unique and valuable genomic data can build a foundation for the genetic improvement and conservation of genetic resources for indigenous cattle breeds

Four Novel SNPs of MYO1A Gene Associated with Heat-Tolerance in Chinese Cattle

Based on the previous GWAS research related to bovine heat tolerance trait, this study aimed to explore the effect of myosin-1a (MYO1A) gene on bovine heat tolerance trait, and find the molecular markers related to the heat tolerance of Chinese cattle. In our study, four novel candidate SNPs highly conserved in B. indicus breeds but barely existed in B. taurus were identified in MYO1A gene according to Bovine Genome Variation Database and Selective Signatures (BGVD). PCR and DNA sequencing were used to genotype 1072 individuals including 34 Chinese indigenous cattle breeds as well as Angus and Indian zebu. Two synonymous mutations (rs208210464 and rs110123931), one missense mutation (rs209999142; Phe172Ser), and one intron mutation (rs135771836) were detected. The frequencies of mutant alleles of the four SNPs gradually increased from northern groups to southern groups of Chinese cattle, which was consistent with the distribution of various climatic conditions of China. Additionally, four SNPs were significantly associated with four climatic conditions including annual mean temperature (T), relative humidity (H), temperature-humidity index (THI), and average annual sunshine hours (100-cloudiness) (SR). Among these, rs209999142 and Hap 1/1 had better performance than others. Our results suggested that rs209999142 was associated with heat-tolerance trait and rs208210464, rs110123931, and rs135771836 showed high phenotypic effect on heat-tolerance trait because of the strong linkage with rs209999142. These SNPs could be used as candidates for marker-assisted selection (MAS) in cattle breeding