肿瘤微阵列数据统计分析概述

微阵列技术已广泛应用于生物学和医学研究领域,如肿瘤的诊断和分型、预测和治疗,理解肿瘤的发生机制、生物学通路和基因网络。统计学方法在这一科学挑战中的地位至关重要。我们综述了微阵列实验数据分析的统计学方法最新发展,主要描述了微阵列数据的标准化、差异表达基因的统计学检验及微阵列技术在肿瘤治疗中的应用,重点介绍了时间序列微阵列数据分析方法和基因调控网络在肿瘤研究中的最新发展。     

Habitat filtering influences the phylogenetic structure of avian communities across a coastal gradient in southern Brazil

The evolution of a particular trait or combination of traits within lineages may affect subsequent evolutionary outcomes, leading closely related species to exhibit higher phenotypic similarity than expected under a simple Brownian‐motion evolutionary model. Niche theory postulates that phenotypes determine species distribution across environmental gradients, leading to a phylogenetic signature in the community assembly. Thus, the incorporation of species phylogeny in the analysis of community ecology structure allows one to link broader environmental, spatial and temporal factors to local, small‐scale ecological processes, thus enabling understanding of community assembly patterns in a broader context. We used the net relatedness index to assess phylogenetic structure within avian communities across a harshness gradient in coastal habitats in southern Brazil. We also evaluated phylogenetic beta diversity, to test whether closely related species exploit habitats with similar environmental conditions. In order to do so, we scaled up phylogenetic information from the species to site level using phylogenetic fuzzy weighting. We found a pattern of phylogenetic clustering in less‐vegetated habitats, namely sandy beach and dunes, which are subject to harsher conditions because of proximity to the ocean. Basal lineages were associated with the more structurally homogeneous sandy beach, while late‐divergence clades occurred in more complex habitats, which were positively related to vegetation cover and height. The observed pattern of phylogenetic clustering suggested the importance of harsh conditions in constraining the distribution of avian lineages. Furthermore, contrasting environmental features between habitats influenced phylogenetic variation, demonstrating the prevalence of phylogenetic habitat filtering. From an applied point of view, such as planning and management of biological reserves, we showed that the full array of habitat patches embedded within coastal ecological gradients must be included in order to preserve distinct evolutionary lineages.     

NGSpeciesID: DNA barcode and amplicon consensus generation from long‐read sequencing data

Third‐generation sequencing technologies, such as Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio), have gained popularity over the last years. These platforms can generate millions of long‐read sequences. This is not only advantageous for genome sequencing projects, but also advantageous for amplicon‐based high‐throughput sequencing experiments, such as DNA barcoding. However, the relatively high error rates associated with these technologies still pose challenges for generating high‐quality consensus sequences. Here, we present NGSpeciesID, a program which can generate highly accurate consensus sequences from long‐read amplicon sequencing technologies, including ONT and PacBio. The tool includes clustering of the reads to help filter out contaminants or reads with high error rates and employs polishing strategies specific to the appropriate sequencing platform. We show that NGSpeciesID produces consensus sequences with improved usability by minimizing preprocessing and software installation and scalability by enabling rapid processing of hundreds to thousands of samples, while maintaining similar consensus accuracy as current pipelines.     

Computational Approaches for RNA Structure Ensemble Deconvolution from Structure Probing Data

RNA structure probing experiments have emerged over the last decade as a straightforward way to determine the structure of RNA molecules in a number of different contexts. Although powerful, the ability of RNA to dynamically interconvert between, and to simultaneously populate, alternative structural configurations, poses a nontrivial challenge to the interpretation of data derived from these experiments. Recent efforts aimed at developing computational methods for the reconstruction of coexisting alternative RNA conformations from structure probing data are paving the way to the study of RNA structure ensembles, even in the context of living cells. In this review, we critically discuss these methods, their limitations and possible future improvements.     

一种基于信息理论的距离系数

给出了一种基于信息理论的距离系数,这一新的信息系数是通过对信息论中的离散增量系数改进而得,并证明其满足距离系数的三个性质．将其应用于一组同源辅助蛋白的聚类分析,表明是可行的．与离散增量系数及经典的欧氏距离系数的聚类结果进行比较,应用相干系数对聚类结果进行评价,结果表明由新信息距离系数所确定的聚类结构与聚类数据问的拟合程度最好.     

Estimation of Excess Cancer Risk on Time-Weighted Lifetime Average Daily Intake of PAHs from Food Ingestion

The purposes of this study were to quantify the time-weighted, lifetime average, daily intake (LADI) of polycyclic aromatic hydrocarbons (PAHs) through food ingestion and to estimate the excess cancer risk based on lifetime dietary PAH intake. Twenty-seven different food commodities were selected from the 2001 Korean National Health and Nutrition survey based on their frequent consumption and high PAH level. The foods were analyzed for the profile of 14 PAH congeners using high performance liquid chromatography (HPLC) and fluorescence detector. Considering the toxic equivalent (TEQ) level converted with the toxic equivalent factors (TEFs), the highest total TEQ level of PAHs in foods was detected from roasted laver at 1.2 ug TEQ/kg. For the PAH exposure assessment according to ingested foods, the average body weight was separated according to the following age groups, 1–6, 7–19, 20–64 and over 64 years, and the daily food ingestion rates from the National Health and Nutrition survey were used. The estimated Lifetime Average Daily Intake (LADI) of PAHs was 3.22 × 10^–3 ug/kg/day for carcinogenic effects and was higher in the younger age groups under 20 years old than in the older groups. The dietary excess cancer risk estimated using the cancer potency of benzo(a)pyrene (7.3(mg/kg/day)^?1) was 2.3 × 10^?5, which is equivalent to a probability of tumor eruption in the upper gastrointestinal tract of two per hundred thousand persons.     

Averaged gene expressions for regression

Although averaging is a simple technique, it plays an important role in reducing variance. We use this essential property of averaging in regression of the DNA microarray data, which poses the challenge of having far more features than samples. In this paper, we introduce a two-step procedure that combines (1) hierarchical clustering and (2) Lasso. By averaging the genes within the clusters obtained from hierarchical clustering, we define supergenes and use them to fit regression models, thereby attaining concise interpretation and accuracy. Our methods are supported with theoretical justifications and demonstrated on simulated and real data sets.     

What determines protein folding type? An investigation of intrinsic structural properties and its implications for understanding folding mechanisms

Protein folding experiments demonstrate that the folding behaviors of many proteins can be roughly classified into two types: two-state kinetics and multi-state kinetics. Although the two types of protein folding kinetics have been observed for a long time, what determines the folding type of a protein is still largely unclear. The present work performed a comparative study based on a dataset of 43 two-state and 42 multi-state folders at different levels of proteins' intrinsic properties from the simplest sequence length to native structure topology. The results show that protein's amino acids composition and the long-range interaction-based topological complexity rather than secondary structure contents are the major determinants of protein folding type. Furthermore, a sequence-based folding type prediction achieved an accuracy of more than 80%. These findings implicate that there is no clear boundary between secondary and tertiary structure formation during the protein folding process and support the existence of a continuum of folding mechanism between the two ends of hierarchic and nucleation folding scenarios.     

GABAA receptor associated proteins: a key factor regulating GABAA receptor function

gamma-Aminobutyric acid (GABA), an important inhibitory neurotransmitter in both vertebrates and invertebrates, acts on GABA receptors that are ubiquitously expressed in the CNS. GABA(A) receptors also represent a major site of action of clinically relevant drugs, such as benzodiazepines, barbiturates, ethanol, and general anesthetics. It has been shown that the intracellular M3-M4 loop of GABA(A) receptors plays an important role in regulating GABA(A) receptor function. Therefore, studies of the function of receptor intracellular loop associated proteins become important for understanding mechanisms of regulating receptor activity. Recently, several labs have used the yeast two-hybrid assay to identify proteins interacting with GABA(A) receptors, for example, the interaction of GABA(A) receptor associated protein (GABARAP) and Golgi-specific DHHC zinc finger protein (GODZ) with gamma subunits, PRIP, phospholipase C-related, catalytically inactive proteins (PRIP-1) and (PRIP-2) with GABARAP and receptor gamma2 and beta subunits, Plic-1 with some alpha and beta subunits, radixin with the alpha5 subunit, HAP1 with the beta1 subunit, GABA(A) receptor interacting factor-1 (GRIF-1) with the beta2 subunit, and brefeldin A-inhibited GDP/GTP exchange factor 2 (BIG2) with the beta3 subunit. These proteins have been shown to play important roles in modulating the activities of GABA(A) receptors ranging from enhancing trafficking, to stabilizing surface and internalized receptors, to regulating modification of GABA(A) receptors. This article reviews the current studies of GABA(A) receptor intracellular loop-associated proteins.