Endurance exercise and selective breeding for longevity extend Drosophila healthspan by overlapping mechanisms

Endurance exercise has emerged as a powerful intervention that promotes healthy aging by maintaining the functional capacity of critical organ systems. In addition, long-term exercise reduces the incidence of age-related diseases in humans and in model organisms. Despite these evident benefits, the genetic pathways required for exercise interventions to achieve these effects are still relatively poorly understood. Here, we compare gene expression changes during endurance training in Drosophila melanogaster to gene expression changes during selective breeding for longevity. Microarrays indicate that 65% of gene expression changes found in flies selectively bred for longevity are also found in flies subjected to three weeks of exercise training. We find that both selective breeding and endurance training increase endurance, cardiac performance, running speed, flying height, and levels of autophagy in adipose tissue. Both interventions generally upregulate stress defense, folate metabolism, and lipase activity, while downregulating carbohydrate metabolism and odorant receptor expression. Several members of the methuselah-like (mthl) gene family are downregulated by both interventions. Knockdown of mthl-3 was sufficient to provide extension of negative geotaxis behavior, endurance and cardiac stress resistance. These results provide support for endurance exercise as a broadly acting anti-aging intervention and confirm that exercise training acts in part by targeting longevity assurance pathways.     

Genome-wide shifts in climate-related variation underpin responses to selective breeding in a widespread conifer

Locally adapted temperate tree populations exhibit genetic trade-offs among climate-related traits that can be exacerbated by selective breeding and are challenging to manage under climate change. To inform climatically adaptive forest management, we investigated the genetic architecture and impacts of selective breeding on four climate-related traits in 105 natural and 20 selectively bred lodgepole pine populations from western Canada. Growth, cold injury, growth initiation, and growth cessation phenotypes were tested for associations with 18,600 single-nucleotide polymorphisms (SNPs) in natural populations to identify “positive effect alleles” (PEAs). The effects of artificial selection for faster growth on the frequency of PEAs associated with each trait were quantified in breeding populations from different climates. Substantial shifts in PEA proportions and frequencies were observed across many loci after two generations of selective breeding for height, and responses of phenology-associated PEAs differed strongly among climatic regions. Extensive genetic overlap was evident among traits. Alleles most strongly associated with greater height were often associated with greater cold injury and delayed phenology, although it is unclear whether potential trade-offs arose directly from pleiotropy or indirectly via genetic linkage. Modest variation in multilocus PEA frequencies among populations was associated with large phenotypic differences and strong climatic gradients, providing support for assisted gene flow polices. Relationships among genotypes, phenotypes, and climate in natural populations were maintained or strengthened by selective breeding. However, future adaptive phenotypes and assisted gene flow may be compromised if selective breeding further increases the PEA frequencies of SNPs involved in adaptive trade-offs among climate-related traits.

Local adaptation of climate-related traits in widespread temperate conifers has been demonstrated for centuries using extensive long-term common garden experiments (1, 2). As early as the 17th century, foresters were instructed to recognize variation in desirable traits and select seed from trees with favorable phenotypes (3). Modern tree improvement programs systematically select upon genetic variation, primarily to achieve growth gains and meet economic objectives. Estimates of genetic variation and gains from selection made using quantitative genetic models assume many anonymous loci of small effect underlie both variation in continuously distributed phenotypes and their responses to selective breeding. However, the type, quantity, effect size, distribution, and dynamics of genes underlying locally adaptive phenotypic variation and responses to selective breeding in forest trees are still poorly understood (4).Directional selection over hundreds or thousands of generations has led to genomic features of domestication in agricultural crops including simplified genetic architectures underlying many traits, reduced genome-wide diversity, and numerous selective sweeps (5–7). Beyond high-gain, short-rotation clonal forestry [e.g., Eucalyptus spp. (8)], we know little about the effects of artificial selection on adaptive genetic variation in forest trees, yet many tree species undergo some degree of selective breeding. Two or three generations of conifer breeding is not expected to have the same magnitude of genetic effects seen in domesticated crops, but if artificial selection for increased productivity is detectable in conifer genomes, it may expose genetic relationships and potential sources of trade-offs between growth and climatically adaptive phenotypes.Climate-related adaptive traits are often intercorrelated due to pleiotropy, natural selection, or linkage disequilibrium (LD), so that strong directional selection on one trait can cause correlated responses in others. Pleiotropic allelic variants associated with phenotypes do not function in isolation. Antagonistic pleiotropic effects among traits can generate adaptive trade-offs among traits within populations, and limit gains from selection on a focal trait (9). Trait–trait correlations can also arise through strong selection acting in parallel on unlinked loci or from LD mediated by physical linkage of loci on chromosomes. Average genome-wide LD estimates in conifers appear to be low (10, 11) but may be greater (r² of 0.2–0.4) within genes under strong selection (12).Conifer studies have identified putatively adaptive phenotype-associated alleles on a locus-by-locus basis using quantitative trait loci (QTL) mapping or genotype–phenotype associations (GPAs) (also known as genome-wide association studies [GWAS]) (13). Genotype–environment association analyses in conifers have identified putatively adaptive environmentally associated loci (e.g., 14, 15), but loci are usually anonymous relative to adaptive phenotypes. All of these approaches are biased toward detecting loci with large phenotypic effects, but expectations that genome scans will discover individual adaptive loci with large effects or frequency differences among populations may be biologically and statistically unrealistic (16, 17). Conifer GPA studies typically detect relatively few statistically significant loci, and locus-by-locus analyses are insufficient to characterize adaptive genome-wide variation associated with adaptive traits and signatures of selective breeding. Multilocus tests for adaptive polygenic signatures of selection have been developed (e.g., refs. 18 and 19), but significant limitations remain (reviewed in refs. 20 and 21).Uncertainty about the effects of selective breeding on adaptive genetic variation is layered upon expectations that forest trees will become maladapted as climates shift (22). Efforts are being made to estimate maladaptation using genome-wide variation associated with adaptive traits and climate (23, 24), because conserving, managing, and efficiently redeploying genetic variation associated with adaptive phenotypes will be a necessary element of strategies to mitigate the effects of shifting climates on forest resources (25). Assisted gene flow strategies in temperate and subboreal forests generally aim to move trees to cooler climates in anticipation of future warming, but trees must then contend with the increased short- to medium-term risk of maladaptation to damaging frost. This means cold tolerance is, perhaps surprisingly, an important trait when planning for warming climates.Genetic approaches have the potential to efficiently and accurately characterize local adaptation to climate. Understanding whether this potential can be realized in a technically robust and operationally feasible way, and whether selection for faster growth compromises genetic variation associated with phenotypic adaptation to climate, has far-reaching implications for developing effective assisted gene flow strategies that mitigate negative climate change impacts on forest health and timber production (26, 27). In this context, our research objectives are to 1) identify the genetic architecture of climate-related adaptive traits in interior lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.); 2) identify genome-wide effects of artificial selection for increased productivity on climate-related traits; and 3) assess the implications of genetic responses to selection for assisted gene flow strategies.Our study combines climatic data, genotype data from ∼50,000 lodgepole pine single-nucleotide polymorphisms (SNPs), and seedling phenotypic data for height, cold injury, growth initiation, and growth cessation traits. These data were collected from a seedling common garden that sampled reforestation seed lots from 105 natural populations and 20 breeding populations from across the species’ range in Alberta (AB) and British Columbia (BC), Canada (Fig. 1 and SI Appendix, Table S1). For each of the four traits, we identify range-wide GPAs using 929 seedlings from all 105 natural populations. Then for the 1% most strongly phenotype-associated SNPs, we examine how artificial selection within breeding populations has changed allele frequencies at individual SNP loci, within individual seedlings, populations (breeding zones), and three climatic regions (Fig. 1). Using elements from the approach of Turchin et al. (18), we study changes in frequency of the alleles that have a positive effect on adaptive traits (positive effect alleles [PEAs]). At each SNP locus, a PEA is the allele associated with increasing numeric values of the respective phenotype, determined in this case through GPA analyses in the natural seedling populations. PEAs reported here are associated with greater seedling height, greater cold injury, delayed growth initiation, and delayed growth cessation. To parse physical genetic linkage from allelic associations due to other causes, we compare LD estimated from our natural seedlings with estimates of recombination among haploid megagametophytes from a single maternal parent, where physical linkage is the only cause of LD. Integrating genetic, climatic, and phenotypic data gives us a robust basis to detect the effects of artificial selection on climate-related genotypes that are relevant to breeding and assisted gene flow strategies.Open in a separate windowFig. 1.Geographic origins of the natural and selected seedling populations sampled from across the range of lodgepole pine in Alberta (AB) and British Columbia (BC). Natural populations are represented by filled circles; selected seedling breeding zones are represented by filled polygons. The three climatic regions we used were AB, BC-Central, and BC-South. AB breeding zones are formally identified as A, B1, B2, C, J, and K1. BC-Central breeding zone abbreviations are as follows: BV, Bulkley Valley; CP, Central Plateau; and PG, Prince George. BC-South breeding zone abbreviations are as follows: EK, East Kootenay; NE, Nelson; and TO, Thompson–Okanagan. Reprinted from ref. 35, with permission from Elsevier.     

Directional $\mathcal{H}^2$ Compression Algorithm: Optimisations and Application to a Discontinuous Galerkin BEM for the Helmholtz Equation

This study aimed to specialise a directional $\mathcal{H}^2 (\mathcal{D}\mathcal{H}^2)$ compression to matrices arising from the discontinuous Galerkin (DG) discretisation of the hypersingular equation in acoustics. The significant finding is an algorithm that takes a DG stiffness matrix and finds a near-optimal $\mathcal{D}\mathcal{H}^2$ approximation for low and high-frequency problems. We introduced the necessary special optimisations to make this algorithm more efficient in the case of a DG stiffness matrix. Moreover, an automatic parameter tuning strategy makes it easy to use and versatile. Numerical comparisons with a classical Boundary Element Method (BEM) show that a DG scheme combined with a $\mathcal{D}\mathcal{H}^2$ gives better computational efficiency than a classical BEM in the case of high-order finite elements and $hp$ heterogeneous meshes. The results indicate that DG is suitable for an auto-adaptive context in integral equations.     

A New Asymmetric Directional Microphone Algorithm With Automatic Mode‐Switching Ability for Binaural Hearing Support Devices

For hearing support devices, it is important to minimize the negative effect of ambient noises for speech recognition but also, at the same time, supply natural ambient sounds to the hearing‐impaired person. However, conventional fixed bilateral asymmetric directional microphone (DM) algorithms cannot perform in such a way when the DM‐mode device and a dominant noise (DN) source are placed on the same lateral hemisphere. In this study, a new binaural asymmetric DM algorithm that can overcome the defects of conventional algorithms is proposed. The proposed algorithm can estimate the position of a specific DN in the 90°–270° range and switch directional‐ and omnidirectional‐mode devices automatically if the DM‐mode device and the DN are placed in opposite lateral hemispheres. Computer simulation and KEMAR mannequin recording tests demonstrated that the performance of the conventional algorithm deteriorated when the DM‐mode device and the DN were placed in the opposite hemisphere; in contrast, the performance of the proposed algorithm was consistently maintained regardless of directional variations in the DN. Based on these experimental results, the proposed algorithm may be able to improve speech quality and intelligibility for hearing‐impaired persons who have similar degrees of hearing impairment in both ears.     

Lower Extremity Revascularization Using Directional Atherectomy: 12-Month Prospective Results of the DEFINITIVE LE Study

ObjectivesThe aim of this study was to assess the safety and effectiveness of directional atherectomy (DA) for endovascular treatment of peripheral arterial disease (PAD) in infrainguinal arteries in patients with claudication or critical limb ischemia.BackgroundTo date, no prospective, multicenter, independently-adjudicated study has evaluated the effectiveness and durability of DA in the treatment of PAD. Previous DA studies have not been prospectively powered to evaluate any differences in outcomes in patients with and without diabetes.MethodsDEFINITIVE LE (Determination of EFfectiveness of the SilverHawk® PerIpheral Plaque ExcisioN System (SIlverHawk Device) for the Treatment of Infrainguinal VEssels / Lower Extremities) prospectively enrolled subjects at 47 multinational centers with an infrainguinal lesion length up to 20 cm. Primary endpoints were defined as primary patency at 12 months for claudicants and freedom from major unplanned amputation for critical limb ischemia (CLI) subjects. A pre-specified statistical hypothesis evaluated noninferiority of primary patency in diabetic versus nondiabetic claudicants. Independent angiographic and sonographic core laboratories assessed outcomes, and events were adjudicated by a clinical events committee.ResultsA total of 800 subjects were enrolled. The 12-month primary patency was 78% (95% confidence interval: 74.0% to 80.6%) in claudicants, with a 77% rate in the diabetic subgroup versus 78% in the nondiabetic subgroup (noninferior, p < 0.001). The rate of freedom from major unplanned amputation of the target limb at 12 months in CLI subjects was 95% (95% confidence interval: 90.7% to 97.4%). Periprocedural adverse events included embolization (3.8%), perforation (5.3%), and abrupt closure (2.0%). The bail-out stent rate was 3.2%.ConclusionsThe DEFINITIVE LE study demonstrated that DA is a safe and effective treatment modality at 12 months for a diverse patient population with either claudication or CLI. Furthermore, DA was shown to be noninferior for treating PAD in patients with diabetes compared with those without diabetes. (Study of SilverHawk/TurboHawk in Lower Extremity Vessels [DEFINITIVE LE]; NCT00883246).     

基于混合多特征的微动脉瘤检测方法

糖尿病性视网膜病变(DR)会严重损害糖尿病患者的视力健康,而微动脉瘤(MA)是DR的早期迹象,可为DR早期诊断提供有益信息,然而仅凭肉眼靠经验观察眼底图像,对大规模筛查难以胜任。因此自动识别和检测势在必行。应用自适应阈值分割法提取候选区域,设计联合定向局部对比度特征(DLC)与哈尔特征(Haar)等混合多特征向量,通过邻近算法(KNN)实现自动分类,并与其他机器学习的常用分类方法,如朴素贝叶斯(NB)、支持向量机(SVM)以及同方向进行了对比研究。所提出的方法在e-ophtha MA公开数据集上进行测试,获得的ROC曲线线下面积(AUC)、敏感性、特异性、FROC-Score分别为0.961 3、0.914 4、0.890 0和 0.386 0。与其他方法比较,本方法在FROC曲线上取得最优结果。     

Systems Biology Application in Research on Sustainable Utilization of Chinese Materia Medica Resources

This paper reviews the progress of systems biology applied to researching on sustainable utilization of Chinese materia medica (CMM) resources in the following aspects: identification and evaluation of CMM resources, analysis of biosynthesis and their regulation of active ingredients in medicinal plants, metabolic engineering and synthetic biology research of medicinal plants, and molecular breeding of medicinal plants. Development of systems biology is currently leading to extremely broad applications in the field of CMM resources, and systems biology will become a significant approach for the sustainable utilization of CMM resources.     

Genetic variations of body weight and GCRV resistance in a random mating population of grass carp

The grass carp (Ctenopharyngodon idellus) is an important species in freshwater aquaculture both in China and on a global scale. Variety degeneration and frequent diseases have limited the further development of grass carp aquaculture. Thus, new and improved varieties are required. Here, we identified and assessed the body weight and disease resistance in a random mating population of 19 ♀ × 22 ♂ grass carp, which were derived from different water systems. In both the growth experimental group of 10,245 fish and grass carp reovirus (GCRV)-infected group with 10,000 fish, 78 full-sib families were statistically analyzed for body weight and GCRV resistance. The findings showed that body weight traits had low heritability (0.11 ± 0.04, 0.10 ± 0.03 and 0.12 ± 0.05), GCRV resistance traits had high heritability (0.63 ± 0.11); body weight was higher in 3 families, whereas GCRV resistance was significantly greater in 11 families. Our results confirmed that the natural germplasm resources of wild grass carp were genetically diverse. Breeding of GCRV resistant varieties of grass carp have better genetic basis. This study provides the basis for constructing basal populations for grass carp selective breeding, quantitative trait loci (QTL) and genome-wide association studies (GWAS) analysis.     

The Application of Biotechnology in Medicinal Plants Breeding Research in China

Breeding is not only an important area of medicinal plants research but also the foundation for the superior varieties acquirement of medicinal plants. The rise of modern biotechnology provides good opportunities and new means for medicinal plants breeding research in China. Biotechnology shows its technical advantages and new development prospects in breeding of new medicinal plants varieties with high and stable yield, good quality, as well as stress-resistance. In this paper, we describe recent advances, problems, and development prospects about the application of modern biotechnology in medicinal plants breeding research in China.