The Bio3D packages for structural bioinformatics

Bio3D is a family of R packages for the analysis of biomolecular sequence, structure, and dynamics. Major functionality includes biomolecular database searching and retrieval, sequence and structure conservation analysis, ensemble normal mode analysis, protein structure and correlation network analysis, principal component, and related multivariate analysis methods. Here, we review recent package developments, including a new underlying segregation into separate packages for distinct analysis, and introduce a new method for structure analysis named ensemble difference distance matrix analysis (eDDM). The eDDM approach calculates and compares atomic distance matrices across large sets of homologous atomic structures to help identify the residue wise determinants underlying specific functional processes. An eDDM workflow is detailed along with an example application to a large protein family. As a new member of the Bio3D family, the Bio3D‐eddm package supports both experimental and theoretical simulation‐generated structures, is integrated with other methods for dissecting sequence‐structure–function relationships, and can be used in a highly automated and reproducible manner. Bio3D is distributed as an integrated set of platform independent open source R packages available from: http://thegrantlab.org/bio3d/ .     

Using Integrative Modeling Platform to compute,validate, and archive a model of a protein complex structure

Biology is advanced by producing structural models of biological systems, such as protein complexes. Some systems are recalcitrant to traditional structure determination methods. In such cases, it may still be possible to produce useful models by integrative structure determination that depends on simultaneous use of multiple types of data. An ensemble of models that are sufficiently consistent with the data is produced by a structural sampling method guided by a data‐dependent scoring function. The variation in the ensemble of models quantified the uncertainty of the structure, generally resulting from the uncertainty in the input information and actual structural heterogeneity in the samples used to produce the data. Here, we describe how to generate, assess, and interpret ensembles of integrative structural models using our open source Integrative Modeling Platform program ( https://integrativemodeling.org ).     

环渤海滨海湿地鸻鹬类水鸟多样性及其环境影响因子

环渤海湿地是水鸟南北迁徙的重要驿站,尤其对于该线路上的鸻鹬鸟类具有非常重要的意义。以环渤海地区12处典型滨海湿地为研究对象,于2016-2020年每年春季开展水鸟调查,明确了鸻鹬类水鸟群落组成及其时空变化,采用结构方程模型 （Structural Equation Modeling,SEM）分析了鸻鹬类水鸟多样性与环境因子的响应关系,评估了各环境因子的影响强度。结果表明：（1）共记录到鸻鹬类水鸟7科51种,几乎全部为旅鸟。全球极危物种1种,濒危物种3种,近危物种9种。国家一级保护鸟类2种,国家二级保护鸟类8种。黑腹滨鹬（Calidris alpina）、大滨鹬（Calidris tenuirostris）、黑尾塍鹬（Limosa limosa）、灰鸻（Pluvialis squatarola）、斑尾塍鹬（Limosa lapponica）个体数量最多。（2）山东黄河三角洲、辽宁辽河口、天津北大港等河口湿地,水鸟种类多,单位面积水鸟数量较少。（3）河北沧州沿海、山东滨州贝壳堤岛及其周边区域为环渤海地区湿地集中区,水鸟种类较多。（4）综合影响强度为保护强度>食物>气候,建立自然保护地是保护水鸟多样性的最有效措施。（5）建议将河北南大港湿地和鸟类省级自然保护区提升至国家级,扩大滨州贝壳堤岛与湿地国家级自然保护区面积,对山东黄河三角洲、辽宁辽河口覆盖的各级各类自然保护地进行优化整合。研究结果能为环渤海地区鸻鹬类水鸟保护策略的制定提供相关依据。     

吉林省天然阔叶混交林生态系统多功能性及驱动因素

量化天然林生态系统的多功能性,分析不同功能间的权衡-协同关系及驱动因子,对于天然林保护及修复具有重要的意义。基于吉林省第8次森林资源清查天然阔叶混交林固定样地调查数据、土壤及气候数据,选取土壤保持、涵养水源、碳储量、气候调节、土壤肥力维持、生物多样性、生产力和木材生产8个生态系统功能来表征生态系统多功能性。利用平均值法中的最大值转换法计算多功能性指数。结果表明：（1）8个功能间权衡、协同和中性关系均存在,但以协同关系为主。生物多样性除与气候调节为权衡关系外,与其他功能均为协同关系;碳储量-木材生产协同关系最强（r=0.960,P<0.01）,气候调节-涵养水源间权衡关系最强（r=-0.934,P<0.01）;（2）吉林省天然阔叶混交林的多功能性指数在0.31-0.89之间,且生物多样性和气候调节为主导功能;（3）多功能性与驱动因子的结构方程模型确定系数为R²=0.795,多功能性的驱动因子的总路径系数依次为：林分密度指数（0.752） > 平均年龄（0.375） > 年降雨量（0.365） > 树种丰富度（0.101） > 土壤pH（0.064） > 结构多样性（-0.037） > 年均温（-0.105）,林分密度是最重要的驱动因子。结果对理解天然阔叶混交林的多功能形成及经营调控有一定的意义。     

吉林蛟河针阔混交林林层结构对生产力的影响

探讨不同林层物种多样性和林分结构与森林生产力之间的关系,为森林可持续经营管理策略优化提供理论支持。以吉林蛟河30 hm²针阔混交林固定监测样地中的38432株木本植物的野外调查数据为研究对象,利用结构方程模型探讨了不同林层物种多样性和林分结构多样性对森林生产力的作用机制。结果表明：（1）林冠层林分结构多样性和生产力之间呈负相关关系,路径系数为-0.138;林下层林分结构多样性和生产力之间呈正相关关系,路径系数为0.083。（2）林冠层物种多样性和生产力之间呈正相关关系,路径系数为0.099;林下层物种多样性和生产力之间关系不显著,且物种多样性在林冠层和林下层呈正相关关系,路径系数为0.147。物种多样性和林分结构多样性与森林生产力之间不存在唯一的关系,这种关系的大小、方向和潜在机制与林层有关。为此,在森林经营过程中要充分考虑不同林层物种多样性和林分结构多样性与森林生产力之间的关系。     

A penalized structural equation modeling method accounting for secondary phenotypes for variable selection on genetically regulated expression from PrediXcan for Alzheimer's disease

As the global burden of mental illness is estimated to become a severe issue in the near future, it demands the development of more effective treatments. Most psychiatric diseases are moderately to highly heritable and believed to involve many genes. Development of new treatment options demands more knowledge on the molecular basis of psychiatric diseases. Toward this end, we propose to develop new statistical methods with improved sensitivity and accuracy to identify disease‐related genes specialized for psychiatric diseases. The qualitative psychiatric diagnoses such as case control often suffer from high rates of misdiagnosis and oversimplify the disease phenotypes. Our proposed method utilizes endophenotypes, the quantitative traits hypothesized to underlie disease syndromes, to better characterize the heterogeneous phenotypes of psychiatric diseases. We employ the structural equation modeling using the liability‐index model to link multiple genetically regulated expressions from PrediXcan and the manifest variables including endophenotypes and case‐control status. The proposed method can be considered as a general method for multivariate regression, which is particularly helpful for psychiatric diseases. We derive penalized retrospective likelihood estimators to deal with the typical small sample size issue. Simulation results demonstrate the advantages of the proposed method and the real data analysis of Alzheimer's disease illustrates the practical utility of the techniques. Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative database.     

Genomic regions associated with microdeletion/microduplication syndromes exhibit extreme diversity of structural variation

Segmental duplications (SDs) are a class of long, repetitive DNA elements whose paralogs share a high level of sequence similarity with each other. SDs mediate chromosomal rearrangements that lead to structural variation in the general population as well as genomic disorders associated with multiple congenital anomalies, including the 7q11.23 (Williams–Beuren Syndrome, WBS), 15q13.3, and 16p12.2 microdeletion syndromes. Population-level characterization of SDs has generally been lacking because most techniques used for analyzing these complex regions are both labor and cost intensive. In this study, we have used a high-throughput technique to genotype complex structural variation with a single molecule, long-range optical mapping approach. We characterized SDs and identified novel structural variants (SVs) at 7q11.23, 15q13.3, and 16p12.2 using optical mapping data from 154 phenotypically normal individuals from 26 populations comprising five super-populations. We detected several novel SVs for each locus, some of which had significantly different prevalence between populations. Additionally, we localized the microdeletion breakpoints to specific paralogous duplicons located within complex SDs in two patients with WBS, one patient with 15q13.3, and one patient with 16p12.2 microdeletion syndromes. The population-level data presented here highlights the extreme diversity of large and complex SVs within SD-containing regions. The approach we outline will greatly facilitate the investigation of the role of inter-SD structural variation as a driver of chromosomal rearrangements and genomic disorders.     

Physical enrichment research for captive fish: Time to focus on the DETAILS

Growing research effort has shown that physical enrichment (PE) can improve fish welfare and research validity. However, the inclusion of PE does not always result in positive effects and conflicting findings have highlighted the many nuances involved. Effects are known to depend on species and life stage tested, but effects may also vary with differences in the specific items used as enrichment between and within studies. Reporting fine-scale characteristics of items used as enrichment in studies may help to reveal these factors. We conducted a survey of PE-focused studies published in the last 5 years to examine the current state of methodological reporting. The survey results suggest that some aspects of enrichment are not adequately detailed. For example, the amount and dimensions of objects used as enrichment were frequently omitted. Similarly, the ecological relevance, or other justification, for enrichment items was frequently not made explicit. Focusing on ecologically relevant aspects of PE and increasing the level of detail reported in studies may benefit future work and we propose a framework with the acronym DETAILS ( D imensions, E cological rationale, T iming of enrichment, A mount, I nputs, L ighting and S ocial environment). We outline the potential importance of each of the elements of this framework with the hope it may aid in the level of reporting and standardization across studies, ultimately aiding the search for more beneficial types of PE and the development of our understanding and ability to improve the welfare of captive fish and promote more biologically relevant behaviour.     

Cu2O纳米颗粒对小麦根系形态及遗传毒性的影响

为了阐明Cu₂O纳米颗粒(NPs)暴露对植物根系的毒性效应,本研究以小麦品种‘周麦18’为材料,采用水培试验方法,研究了10、50、100和200 mg·L^-1浓度的Cu₂O-NPs对小麦幼苗生长、根系活性、形态结构及细胞遗传学毒性的影响。结果表明: 不同浓度的Cu₂O-NPs降低了小麦幼苗的根芽长度、鲜重、根活性和根冠比,增加了初生根的数量;随着Cu₂O-NPs浓度的升高,幼苗根伸长区缩短、根系变硬变脆、根径增加、根冠变大;100 mg·L^-1浓度的Cu₂O-NPs处理下,小麦根尖有丝分裂指数显著降低,根尖细胞形状不规则化、质壁分离、细胞出现空泡化、细胞核核膜模糊、核内染色体异常。在水培条件下,Cu₂O-NPs对小麦幼苗具有一定的遗传学毒性效应,从而影响小麦幼苗的生长发育和根系形态结构。