Two in one: cryptic species discovered in biological control agent populations using molecular data and crossbreeding experiments

There are many examples of cryptic species that have been identified through DNA‐barcoding or other genetic techniques. There are, however, very few confirmations of cryptic species being reproductively isolated. This study presents one of the few cases of cryptic species that has been confirmed to be reproductively isolated and therefore true species according to the biological species concept. The cryptic species are of special interest because they were discovered within biological control agent populations. Two geographically isolated populations of Eccritotarsus catarinensis (Carvalho) [Hemiptera: Miridae], a biological control agent for the invasive aquatic macrophyte, water hyacinth, Eichhornia crassipes (Mart.) Solms [Pontederiaceae], in South Africa, were sampled from the native range of the species in South America. Morphological characteristics indicated that both populations were the same species according to the current taxonomy, but subsequent DNA analysis and breeding experiments revealed that the two populations are reproductively isolated. Crossbreeding experiments resulted in very few hybrid offspring when individuals were forced to interbreed with individuals of the other population, and no hybrid offspring were recorded when a choice of mate from either population was offered. The data indicate that the two populations are cryptic species that are reproductively incompatible. Subtle but reliable diagnostic characteristics were then identified to distinguish between the two species which would have been considered intraspecific variation without the data from the genetics and interbreeding experiments. These findings suggest that all consignments of biological control agents from allopatric populations should be screened for cryptic species using genetic techniques and that the importation of multiple consignments of the same species for biological control should be conducted with caution.     

Automated system for gene annotation and metabolic pathway reconstruction using general sequence databases

Despite the growing number of genomes published or currently being sequenced, there is a relative paucity of software for functional classification of newly discovered genes and their assignment to metabolic pathways. Available software for such analyses has a very steep learning curve and requires the installation, configuration, and maintenance of large amounts of complex infrastructure, including complementary software and databases. Many such tools are restricted to one or a few data sources and classification schemes. In this work, we report an automated system for gene annotation and metabolic pathway reconstruction (ASGARD), which was designed to be powerful and generalizable, yet simple for the biologist to install and run on centralized, commonly available computers. It avoids the requirement for complex resources such as relational databases and web servers, as well as the need for administrator access to the operating system. Our methodology contributes to a more rapid investigation of the potential biochemical capabilities of genes and genomes by the biological researcher, and is useful in biochemical as well as comparative and evolutionary studies of pathways and networks.     

鸡基因组差异表达基因翻译起始密码子上下游序列的比较研究

翻译起始调控是基因表达调控的一个关键步骤之一。本文以鸡为研究材料,比较研究了鸡基因组高表达基因和低表达基因翻译起始密码子上下游的碱基序列差异,旨在寻找影响鸡基因表达水平的特异性调控位点。全部3 020个单剪接基因完整的mRNA序列及有详细注释的5＇UTRs序列从Ensembl下载。编写计算机程序,读取每个基因mRNA起始密码子上下游各位点的碱基。研究发现,起始密码子上游-3、-2位点可能是鸡基因组基因表达起始密码子正确识别的关键位点。起始密码子上下游的碱基组成分析发现,高表达基因和低表达基因起始密码子的上游均倾向使用（G＋C）,高表达基因的使用偏倚尤为强烈。序列差异比较发现,高表达基因在-9、-6、-3、＋4位点显著偏向G,在-1、-2、-4、-5位点显著偏向C。低表达基因起始密码子上游使用A、U的频率显著高于低表达基因。在-19位点强烈偏向A,在＋1、＋11、＋14位点强烈偏向U。     

基因外显子连接序列与相应内含子序列的相互作用

剪接后的内含子与相应mRNA序列的相互作用在基因表达调控过程中起着非常重要的作用。基于27个物种的核糖核蛋白基因序列,采用Smith—Waterman局域比对方法得到外显子连接序列与相应内含子序列的最佳匹配片段,分析了外显子连接序列上的匹配频率分布和匹配片段的序列特征。发现一些低等真核生物EJC结合区域的匹配频率明显低于其它区域,所有物种EJC结合区域的序列构成呈现出相对低的结构序。最佳匹配片段的平均长度和配对率分布与siRNA和miRNA的结合特征相同。推测EJC和内含子在与外显子序列结合的过程中存在相互竞争和相互协作的关系,内含子中部序列在基因表达调控过程中起着重要的作用。     

拽线法:一个构建系统发育树的新算法

这篇文章要讨论的拽线法（DL）是贪婪算法的一种。和Fitch—Margoliash（FM）一样,DL也是基于距离矩阵构建系统发育树,但是和FM算法相比,DL具有低复杂度、较高的容错性和准确度高的优点。当存在误差时,DL算法只是加大了不在同一个父节点下的基因序列的距离,但能够准确的判断序列的亲缘关系,进而得到完美的进化树拓扑结构;相比之下,FM算法让各个基因序列间的距离均摊了这种误差,从而有可能将本应该具有相同父节点的基因序列分到不同的分支。     

GPGPU加速生物序列比对研究进展

序列比对是生物信息学中最常用和最经典的研究手段。生物序列比对需要有强大计算能力的硬件支撑,而近年快速发展起来的GPGPU正好可堪此任。本文首先介绍GPGPU的发展过程,进而讲述GPGPU硬件设备与其编程环境,然后对GPGPU做科学计算时需要的数学库函数做一介绍,最后综述近年来国内外基于GPGPU的生物序列比对软件和相关研究工作,并总结和展望其辉煌前景。     

基于序列特征的环状RNA识别

环状RNA是新发现的一类具有重要生物学功能的RNA。现有的环状RNA识别工具依赖高通量测序数据,因数据本身和识别方式的弊端而普遍存在准确性不足、不同方法间重复性低以及假阳性率/假阴性率高等缺点。为了解决该问题,我们搭建模型来实现不依赖于测序数据而根据序列的内在特征的环状RNA从头预测。本文选取了包括剪接位点上下游内含子的长度、A-to-I密度和Alu重复序列等100个与RNA成环相关的序列特征,建立了机器学习模型,并识别了人类基因组中的环状RNA,比较了两种机器学习方法随机森林法(RF)和支持向量机(SVM)的分类效果。结果表明,所选序列特征能有效地鉴别RNA能否成环,同时,不同序列特征对模型的分类预测能力的贡献也不同。相比于SVM方法,RF分类的效果更好。