基于分子宏条形码分析四川卧龙国家级自然保护区雪豹的食性

作为中亚和青藏高原山地生态系统中的顶级捕食者, 雪豹(Panthera uncia)对于维持食物网结构和生态系统稳定性有重要作用。了解雪豹的食性组成和变化对于理解其生态系统功能和物种间相互作用有重要意义。以往的雪豹食性分析多基于对其粪便中食物残渣的形态学鉴定, 但准确度受人员经验和主观因素影响较大。邛崃山脉位于雪豹分布区东南缘, 该区域的雪豹种群规模小且相对孤立, 研究匮乏。本研究基于非损伤性取样, 在邛崃山脉的卧龙国家级保护区采集疑似雪豹粪便样品38份, 首先提取粪便DNA, 并扩增线粒体DNA 16S rRNA基因片段进行分子物种鉴定, 确定其中22份为雪豹粪便样品。随后, 利用脊椎动物通用引物和雪豹特异性阻抑引物扩增粪便DNA中的食物成分, 并进行高通量测序, 分析雪豹食性构成。食性分析结果显示岩羊(Pseudois nayaur)是卧龙地区雪豹最主要的食物, 在67%的样品中均有检出。家牦牛(Bos grunniens)在33%的样品中出现, 也在雪豹食性中占较高比例。此外, 鼠兔(Ochotona spp.)和鸟类也在少量样品中发现。可见, 野生猎物是卧龙地区雪豹的主要食物资源; 与大世界大多数其他地区的雪豹食性相同, 野生大型有蹄类是雪豹最重要的食物。然而家畜(牦牛)在卧龙雪豹食谱中有相当高的占比, 显示该区域内可能存在较为严重的由雪豹捕食散养家畜引起的人兽冲突问题。     

Incorporating Genotyping Error Into Non-Invasive DNA-Based Mark—Recapture Population Estimates

ABSTRACT Use of non-invasive sources of DNA, such as hair or scat, to obtain a genetic mark for population estimates is becoming commonplace. Unfortunately, with such marks, potentials for genotyping errors and for the shadow effect have resulted in use of many loci and amplification of each specimen many times at each locus, drastically increasing time and cost of obtaining a population estimate. We proposed a method, the Genotyping Uncertainty Added Variance Adjustment (GUAVA), which statistically adjusts for genotyping errors and the shadow effect, thereby allowing use of fewer loci and one amplification of each specimen per locus. Using allele frequencies and estimates of genotyping error rates, we determined, for each pair of specimens, the probability that the pair was obtained from the same individual, whether or not their observed genotypes match. Using these probabilities, we reconstructed possible capture history matrices and used this distribution to obtain a population estimate. With simulated data, we consistently found our estimates had lower bias and smaller variance than estimates based on single amplifications in which genotyping error was ignored and that were comparable to estimates based on data free of genotyping errors. We also demonstrated the method on a fecal DNA data set from a population of red wolves (Canis rufus). The GUAVA estimate based on only one amplification genotypes compares favorably to the estimate based on consensus genotypes. A program to conduct the analysis is available from the first author for UNIX or Windows platforms. Application of GUAVA may allow for increased accuracy in population estimates at reduced cost.     

Mature leaf selection of Japanese macaques: effects of availability and chemical content

Mature leaf food selection of Japanese macaques was studied in two different altitudinal zones of Yakushima: in the coniferous (1000–1200 m) and coastal forests (0–200 m). Logistic regression analysis was conducted to reveal the effect of chemical [neutral detergent fibre (NDF), crude protein, crude ash, crude lipid, condensed tannin, hydrolysable tannin and crude protein/NDF ratio] and availability properties (density of trees and total basal area) on the macaques' choice between the major food leaves and the rarely eaten or non-food leaves. In both forests, macaques selected leaves with a high crude ash and crude protein content, or a high crude protein/NDF ratio, as major foods. In the coniferous forest, macaques selected leaves with less condensed tannin, but this tendency was absent in the coastal forest. This was because macaques in the coniferous forest suffer from a greater risk of ingesting large amounts of condensed tannins, as their feeding time on mature leaves is seven times as long as that in the coastal forest. Among the chemical and availability properties, stepwise multiple regression analysis revealed that the number of trees (ha⁻¹) was the only significant factor explaining the variations in feeding time among major food leaves, both in the coniferous and coastal forests. The present results suggest that the effect of travelling cost, which can be reduced by selecting common trees, exceeds the benefits gained by selecting high-quality foods.     

基于分型测序技术的粒用高粱遗传多样性和群体结构分析

了解粒用高粱的遗传多样性和群体结构,能有效提高粒用高粱新品种的选育效率。本研究利用基因分型测序技术(GBS,genotyping by sequencing)对120份粒用高粱材料开展了全基因组基因分型,共获得了3456个多态性的SNP标记,其多态性信息含量指数(PIC,polymorphism information content)介于0.013～0.574之间,平均值为0.381。根据SNP标记在120份高粱材料中的基因分型数据,计算了材料间的遗传距离,其变异范围为0.084～0.613,平均遗传距离为0.365。群体进化树分析和主成分分析都将120份高粱材料划分为3个类群,类群1主要由包括美国材料MN-3609在内的亲缘关系较远的高粱材料组成,类群2主要由中国北方的高粱材料组成,类群3主要由中国南方的高粱材料组成。群体结构分析表明,当K=3时,ΔK取得最大值,说明120份高粱材料可以划分为3个类群,其划分结果与群体进化树分析和主成分分析基本一致。本研究从基因型多样性水平上阐释了粒用高粱的遗传背景和群体结构,为中国粒用高粱新品种的选育提供了理论依据。     

Genetic tagging: contemporary molecular ecology

Population genetic analyses have been highly successful in deciphering inter- and intra-specific evolutionary relationships, levels of gene flow, genetic divergence and effective population sizes. Parameters estimated by traditional population genetic analyses are evolutionary averages and thus not necessarily relevant for contemporary ecological or conservation issues. Molecular data can, however, also provide insight into contemporary patterns of divergence, population size and gene flow when a sufficient number of variable loci are analysed to focus subsequent data analyses on individuals rather than populations. Genetic tagging of individuals is an example of such individual-based approaches and recent studies have shown it to be a viable alternative to traditional tagging methods. Owing to the ubiquitous presence of hyper-variable DNA sequences in eukaryote genomes it is in principle possible to tag any eukaryote species and the required DNA can be obtained indirectly from substrates such as faeces, sloughed skin and hair. The purpose of this paper is to present the concept of genetic tagging and to further advocate the extension of individual-based genetic analyses beyond the identification of individuals to other kinds of relationships, such as parent-offspring relations, which more fully exploit the genetic nature of the data.