"兰箭3号"春箭筈豌豆叶绿体全基因组草图及特征分析

箭筈豌豆(Vicia sativa)是自花授粉的二倍体一年生豆科牧草,可为我国高海拔地区的反刍动物提供优质蛋白粗饲料。以"兰箭3号"春箭筈豌豆为研究对象,采用DNase I法纯化叶绿体,利用第二代高通量测序平台Illumina Hiseq2000进行测序,并对"兰箭3号"叶绿体全基因组序列的结构特征进行分析。结果表明,"兰箭3号"叶绿体基因组仅包括一个单拷贝的反向重复序列,其叶绿体全基因组大小为121 883bp,共编码了109个基因,包括4个核糖体RNA(rRNA)基因,29个转运RNA(tRNA)基因,75个蛋白质编码基因和1个假基因。"兰箭3号"在叶绿体基因组结构、基因种类、排列顺序上与其它豆科植物基本一致。其叶绿体全基因组序列已在GenBank注册,序列号为KU053796。"兰箭3号"叶绿体全基因组测序的成功为叶绿体分子生物学研究奠定了基础,并可有效地促进箭筈豌豆遗传育种和分子进化研究。     

DNA序列判别分类模型

[目的]结合生物学知识和数学方法构建DNA序列判别分类模型。[方法]根据氨基酸分子中侧链基的极性性质,从不同序列中氨基酸含量不同提炼出能从碱基含量和碱基排列情况两方面代表序列特征的氨基酸类别信息,用一个四维向量来表征,用马氏距离法和FISHER判别法对给定序列进行分类。[结果]该模型中,2种分类方法所得的样本回代率均达100%,分类一致率为90%。[结论]该模型算法简单,分类结果精度较高,优于仅基于碱基含量的判别分类模型。     

Simulation study on the effects of excluding offspring information for genetic evaluation versus using genomic markers for selection in dog breeding

Different modes of selection in dogs were studied with a special focus on the availability of disease information. Canine hip dysplasia (CHD) in the German shepherd dog was used as an example. The study was performed using a simulation model, comparing cases when selection was based on phenotype, true or predicted breeding value, or genomic breeding value. The parameters in the simulation model were drawn from the real population data. The data on all parents and 40% of their progeny were assumed to be available for the genetic evaluation carried out by Gibbs sampling. With respect to the use of disease records on progeny, three scenarios were considered: random exclusion of disease data (no restrictions, N), general exclusion of disease data (G) and exclusion of disease data for popular sires (P). One round of selection was considered, and the response was expressed as change of mean CHD score, proportion of dogs scored as normal, proportion of dogs scored as clearly affected and true mean breeding value in progeny of popular sires in comparison with all sires. When no restrictions on data were applied, selection on breeding value was three times more efficient than when some systematic exclusion was practised. Higher selection response than in the exclusion cases was achieved by selecting on the basis of genomic breeding value and CHD score. Genomic selection would therefore be the method of choice in the future.     

柞蚕核型多角体病毒和家蚕核型多角体病毒的同义密码子使用模式分析

基因组中的基因和基因密码子组成不同使柞蚕核型多角体病毒(ApNPV)与家蚕核型多角体病毒(BmNPV)间不能交叉感染。通过计算有效密码子数(ENc)、相对同义密码子使用度(RSCU)、GC含量、GC3s含量、密码子适应指数(CAI),比较分析ApNPV和BmNPV同义密码子使用模式差异。ApNPV和BmNPV的密码子偏好性均较弱,但二者的ENc值和GC含量差异显著;除碱基组成外,还存在其它因素影响密码子使用模式,但各影响因素的贡献率均较低,在基于密码子使用频率的对应分析中BmNPV的第1、第2向量轴贡献率均低于ApNPV;ApNPV的基因表达水平与GC含量、GC3s含量以及ENc值极显著相关(r分别为0.418、0.735、-0.628,P=0.000),而BmNPV的基因表达水平只与GC3s含量呈弱相关(r=0.214,P=0.010)。分析结果显示,ApNPV和BmNPV的密码子偏好性虽均较弱,但同义密码使用模式及其影响因素存在差异。     

The under-recognized dominance of Verrucomicrobia in soil bacterial communities

Verrucomicrobia are ubiquitous in soil, but members of this bacterial phylum are thought to be present at low frequency in soil, with few studies focusing specifically on verrucomicrobial abundance, diversity, and distribution. Here we used barcoded pyrosequencing to analyze verrucomicrobial communities in surface soils collected across a range of biomes in Antarctica, Europe, and the Americas (112 samples), as well as soils collected from pits dug in a montane coniferous forest (69 samples). Data collected from surface horizons indicate that Verrucomicrobia average 23% of bacterial sequences, making them far more abundant than had been estimated. We show that this underestimation is likely due to primer bias, as many of the commonly used PCR primers appear to exclude verrucomicrobial 16S rRNA genes during amplification. Verrucomicrobia were detected in 180 out of 181 soils examined, with members of the class Spartobacteria dominating verrucomicrobial communities in nearly all biomes and soil depths. The relative abundance of Verrucomicrobia was highest in grasslands and in subsurface soil horizons, where they were often the dominant bacterial phylum. Although their ecology remains poorly understood, Verrucomicrobia appear to be dominant in many soil bacterial communities across the globe, making additional research on their ecology clearly necessary.     

Assessing eddy-covariance flux tower location bias across the Fluxnet-Canada Research Network based on remote sensing and footprint modelling

We describe an approach for evaluating the representativeness of eddy covariance flux measurements and assessing sensor location bias (SLB) based on footprint modelling and remote sensing. This approach was applied to the 12 main sites of the Fluxnet-Canada Research Network (FCRN)/Canadian Carbon Program (CCP) located along an east-west continental-scale transect, covering grassland, forest, and wetland biomes. For each site, monthly and annual footprint climatologies (i.e. monthly or annual cumulative footprints) were calculated using the Simple Analytical Footprint model on Eulerian coordinates (SAFE). The resulting footprint climatologies were then overlaid on to images of the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) derived from LANDSAT Thematic Mapper (TM) imagery, which were used as surrogates of land surface fluxes to estimate SLB. Results indicate that (i) the sizes of annual footprint climatology increased exponentially with increasing cumulative footprint percentages and, for a given percentage of footprint climatology, the footprint areas were significantly different among the sites. Typically, the 90% annual footprint climatology areas varied from 1.1 km² to 5.0 km²; (ii) using either NDVI or EVI as the flux surrogate, the SLB was less than 5% for most sites with respect to the reference area of interest (A_r) at 90% annual footprint climatology (scenario A) and a circular area with radius of 1 km centred at the individual tower (scenario B), with several exceptions; (iii) the SLB decreased with increasing size of footprint climatology for all sites for both scenarios A and B; (iv) out of 12, eight flux towers represented most of the ecosystem surrounding the towers for an area of 0.3 km² up to 10 km² with a satisfactorily low bias of <5%, whereas four towers represented areas ranging from only 0.75 to 4 km²; and (v) the seasonal differences in monthly SLB using NDVI as a flux surrogate were about 1-4% for most sites for both scenarios A and B.     

Effect of the Flanking Sequence Architecture of Translation Initiation AUG Codon on Gene Expression Level in Rice

The relationship between the codon usage bias, gene expression level and the AUG context (from -20 to +6 positions relative to the initiator AUG codon) was examined in 541unigene sequences of rice. A significant correlation for CAI values (codon adaptation index) was observed at five nucleotide positions (-19, -18, -9, -4, +5), eight (-19, -18,-14, -9, -6, -4, -1, +5) for CPP (codon preference parameter), and seven (-18, -16, -15,-9, -7, -1, + 6) for mRNA abundance in the flanking sequence of the initiator AUG codon respectively, but a significantly positive correlation for both CAI and CPP at two positions (-4 and +5), indicating that both those positions are evolutionally under the natural selection constraint at the translational level. By site-directed mutagenesis at seven specific positions (-18, -16, -15, -9, -7, -1 and + 6) for allergenic protein that had the highest mRNA abundance in this study, its expression level decreased dramatically 63.3 and 72.5% respectively, indicating the importance of those 7 positions for gene expression. A highly positive correlation (r= 0.625, P＜ 0.01) between AUGCAI and GC content in the flanking sequence of the initiator AUG codon showed a more effective higher GC content on translation initiation efficiency. The strong preference for G or C at those 8 positions (-6, -5, -3, -2, -1, +4, +5 and +6) in the AUG context suggested that an important factor in modulation of the translation efficiency, as well as synonymous codon usage bias, particularly in highly expressed genes.     

Modelling the biological invasion of Prosopis juliflora using geostatistical-based bioclimatic variables under climate change in arid zones of southwestern Iran

Invasive species have been the focus of ecologists due to their undesired impacts on the environment.The extent and rapid increase in invasive plant species is recognized as a natural cause of global-biodiversity loss and degrading ecosystem services.Biological invasions can affect ecosystems across a wide spectrum of bioclimatic conditions.Understanding the impact of climate change on species invasion is crucial for sustainable biodiversity conservation.In this study,the possibility of mapping the distribution of invasive Prosopis juliflora(Swartz)DC.was shown using present background data in Khuzestan Province,Iran.After removing the spatial bias of background data by creating weighted sampling bias grids for the occurrence dataset,we applied six modelling algorithms(generalized additive model(GAM),classification tree analysis(CTA),random forest(RF),multivariate adaptive regression splines(MARS),maximum entropy(Max Ent)and ensemble model)to predict invasion distribution of the species under current and future climate conditions for both optimistic(RCP2.6)and pessimistic(RCP8.5)scenarios for the years 2050 and 2070,respectively.Predictor variables including weighted mean of CHELSA(climatologies at high resolution for the Earth’s land surface areas)-bioclimatic variables and geostatistical-based bioclimatic variables(1979–2020),physiographic variables extracted from shuttle radar topography mission(SRTM)and some human factors were used in modelling process.To avoid causing a biased selection of predictors or model coefficients,we resolved the spatial autocorrelation of presence points and multi-collinearity of the predictors.As in a conventional receiver operating characteristic(ROC),the area under curve(AUC)is calculated using presence and absence observations to measure the probability and the two error components are weighted equally.All models were evaluated using partial ROC at different thresholds and other statistical indices derived from confusion matrix.Sensitivity analysis showed that mean diurnal range(Bio2)and annual precipitation(Bio12)explained more than 50% of the changes in the invasion distribution and played a pivotal role in mapping habitat suitability of P.juliflora.At all thresholds,the ensemble model showed a significant difference in comparison with single model.However,Max Ent and RF outperformed the others models.Under climate change scenarios,it is predicted that suitable areas for this invasive species will increase in Khuzestan Province,and increasing climatically suitable areas for the species in future will facilitate its future distribution.These findings can support the conservation planning and management efforts in ecological engineering and be used in formulating preventive measures.     

A synthetic control approach to estimate the effect of total allowable catches in the high seas

Total allowable catch restrictions (hereafter referred to as catch quotas) play an important role in maintaining healthy fish stocks. While studies have identified a positive relationship between catch quota implementation and improved stock status, these methods are subject to selection bias as catch quotas are typically applied to stocks that are depleted. We address this challenge using the synthetic control method, which estimates the causal effect of catch quotas on fishing mortality and biomass by predicting a synthetic counterfactual outcome. We focus on high seas stocks (tunas, billfishes, and sharks) managed by tuna Regional Fisheries Management Organizations (tRFMOs), first providing an overview of stock status and current management measures in place. We find that implementation of catch quotas by tRFMOs has more than doubled over the past decade. Second, we predict the hypothetical fishing mortality and biomass trajectory for seven high seas quota-managed stocks in absence of a catch quota. These “synthetic non-quota stocks” are predicted using a weighted selection of high seas non-quota stocks. Credibility of the synthetic non-quota stocks is evaluated through diagnostic checks, and robustness tests assess sensitivity to study design. Five credible fishing mortality synthetic controls are predicted: three add support to the hypothesis that catch quotas successfully reduce fishing mortality, while two find that catch quotas increase fishing mortality. While our analysis is limited in scope, given that all seven quota-managed stocks are managed under a single tRFMO, we highlight the potential for the synthetic control method in fisheries management evaluation.     

Closing the compliance gap in marine protected areas with human behavioural sciences

Advocates, practitioners and policy-makers continue to use and advocate for marine protected areas (MPAs) to meet global ocean protection targets. Yet many of the worlds MPAs, and especially no-take MPAs, are plagued by poaching and ineffective governance. Using a global dataset on coral reefs as an example, we quantify the potential ecological gains of governing MPAs to increase compliance, which we call the ‘compliance gap’. Using ecological simulations based on model posteriors of joint Bayesian hierarchical models, we demonstrate how increased compliance in no-take MPAs could nearly double target fish biomass (91% increases in median fish biomass), and result in a 292% higher likelihood of encountering top predators. Achieving these gains and closing the compliance gap necessitates a substantial shift in approach and practice to go beyond optimizing enforcement, and towards governing for compliance. This will require engaging and integrating a broad suite of actors, principles, and practices across three key domains: (i)) harnessing social influence, (ii) integrating equity principles, and (iii) aligning incentives through market-based instruments. Empowering and shaping communication between actor groups (e.g., between fishers, practitioners, and policy-makers) using theoretically underpinned approaches from the behavioural sciences is one of the most essential, but often underserved aspects of governing MPAs. We therefore close by highlighting how this cross-cutting tool could be further integrated in governance to bolster high levels of compliance in MPAs.