iTRAQ‐Based Proteomics Reveals that the Tomato ms1035 Gene Causes Male Sterility through Compromising Fat Acid Metabolism

So far, over 50 spontaneous male sterile mutants of tomato have been described and most of them are categorized as genetic male sterility. To date, the mechanism of tomato genetic male sterility remained unclear. In this study, differential proteomic analysis is performed between genetic male sterile line (2‐517), which carries the male sterility (ms10³⁵) gene, and its wild‐type (VF‐11) using isobaric tags for relative and absolute quantification‐based strategy. A total of 8272 proteins are quantified in the 2–517 and VF‐11 lines at the floral bud and florescence stages. These proteins are involved in different cellular and metabolic processes, which express obvious functional tendencies toward the hydroxylation of the ω‐carbon in fatty acids, the tricarboxylic acid cycle, the glycolytic, and pentose phosphate pathways. Based on the results, a protein network explaining the mechanisms of tomato genetic male sterility is proposed, finding the compromising fat acid metabolism may cause the male sterility. These results are confirmed by parallel reaction monitoring, quantitative Real‐time PCR (qRT‐PCR), and physiological assays. Taken together, these results provide new insights into the metabolic pathway of anther abortion induced by ms10³⁵ and offer useful clues to identify the crucial proteins involved in genetic male sterility in tomato.     

LNRLMI: Linear neighbour representation for predicting lncRNA‐miRNA interactions

LncRNA and miRNA are key molecules in mechanism of competing endogenous RNAs(ceRNA), and their interactions have been discovered with important roles in gene regulation. As supplementary to the identification of lncRNA‐miRNA interactions from CLIP‐seq experiments, in silico prediction can select the most potential candidates for experimental validation. Although developing computational tool for predicting lncRNA‐miRNA interaction is of great importance for deciphering the ceRNA mechanism, little effort has been made towards this direction. In this paper, we propose an approach based on linear neighbour representation to predict lncRNA‐miRNA interactions (LNRLMI). Specifically, we first constructed a bipartite network by combining the known interaction network and similarities based on expression profiles of lncRNAs and miRNAs. Based on such a data integration, linear neighbour representation method was introduced to construct a prediction model. To evaluate the prediction performance of the proposed model, k‐fold cross validations were implemented. As a result, LNRLMI yielded the average AUCs of 0.8475 ± 0.0032, 0.8960 ± 0.0015 and 0.9069 ± 0.0014 on 2‐fold, 5‐fold and 10‐fold cross validation, respectively. A series of comparison experiments with other methods were also conducted, and the results showed that our method was feasible and effective to predict lncRNA‐miRNA interactions via a combination of different types of useful side information. It is anticipated that LNRLMI could be a useful tool for predicting non‐coding RNA regulation network that lncRNA and miRNA are involved in.     

The functional roles of species in metacommunities,as revealed by metanetwork analyses of bird–plant frugivory networks

Understanding how biodiversity and interaction networks change across environmental gradients is a major challenge in ecology. We integrated metacommunity and metanetwork perspectives to test species’ functional roles in bird–plant frugivory interactions in a fragmented forest landscape in Southwest China, with consequences for seed dispersal. Availability of fruit resources both on and under trees created vertical feeding stratification for frugivorous birds. Bird–plant interactions involving birds feeding only on‐the‐tree or both on and under‐the‐tree (shared) had a higher centrality and contributed more to metanetwork organisation than interactions involving birds feeding only under‐the‐tree. Moreover, bird–plant interactions associated with large‐seeded plants disproportionately contributed to metanetwork organisation and centrality. Consequently, on‐the‐tree and shared birds contributed more to metanetwork organisation whereas under‐the‐tree birds were more involved in local processes. We would expect that species’ roles in the metanetwork will translate into different conservation values for maintaining functioning of seed‐dispersal networks.     

Communicative roots of complex sociality and cognition

Mammals living in more complex social groups typically have large brains for their body size and many researchers have proposed that the primary driver of the increase in brain size through primate and hominin evolution was the selection pressures associated with sociality. Many mammals, and especially primates, use flexible signals that show a high degree of voluntary control and these signals may play an important role in forming and maintaining social relationships between group members. However, the specific role that cognitive skills play in this complex communication, and how in turn this relates to sociality, is still unclear. The hypothesis for the communicative roots of complex sociality and cognition posits that cognitive demands behind the communication needed to form and maintain bonded social relationships in complex social settings drives the link between brain size and sociality. We review the evidence in support of this hypothesis and why key features of cognitively complex communication such as intentionality and referentiality should be more effective in forming and maintaining bonded relationships as compared with less cognitively complex communication. Exploring the link between cognition, communication and sociality provides insights into how increasing flexibility in communication can facilitate the emergence of social systems characterised by bonded social relationships, such as those found in non‐human primates and humans. To move the field forward and carry out both within‐ and among‐species comparisons, we advocate the use of social network analysis, which provides a novel way to describe and compare social structure. Using this approach can lead to a new, systematic way of examining social and communicative complexity across species, something that is lacking in current comparative studies of social structure.     

Artificial neural network and response surface methodology: a comparative analysis for optimizing rice straw pretreatment and saccharification

Abstract

The present study demonstrates a comparative analysis between the artificial neural network (ANN) and response surface methodology (RSM) as optimization tools for pretreatment and enzymatic hydrolysis of lignocellulosic rice straw. The efficacy for both the processes, that is, pretreatment and enzymatic hydrolysis was evaluated using correlation coefficient (R²) & mean squared error (MSE). The values of R² obtained by ANN after training, validation, and testing were 1, 0.9005, and 0.997 for pretreatment and 0.962, 0.923, and 0.9941 for enzymatic saccharification, respectively. On the other hand, the R² values obtained with RSM were 0.9965 for cellulose recovery and 0.9994 for saccharification efficiency. Thus, ANN and RSM together successfully identify the substantial process conditions for rice straw pretreatment and enzymatic saccharification. The percentage of error for ANN and RSM were 0.009 and 0.01 for cellulose recovery and for 0.004 and 0.005 for saccharification efficiency, respectively, which showed the authority of ANN in exemplifying the non-linear behavior of the system.     

TREEasy: An automated workflow to infer gene trees,species trees,and phylogenetic networks from multilocus data

Multilocus genomic data sets can be used to infer a rich set of information about the evolutionary history of a lineage, including gene trees, species trees, and phylogenetic networks. However, user‐friendly tools to run such integrated analyses are lacking, and workflows often require tedious reformatting and handling time to shepherd data through a series of individual programs. Here, we present a tool written in Python—TREEasy—that performs automated sequence alignment (with MAFFT), gene tree inference (with IQ‐Tree), species inference from concatenated data (with IQ‐Tree and RaxML‐NG), species tree inference from gene trees (with ASTRAL, MP‐EST, and STELLS2), and phylogenetic network inference (with SNaQ and PhyloNet). The tool only requires FASTA files and nine parameters as inputs. The tool can be run as command line or through a Graphical User Interface (GUI). As examples, we reproduced a recent analysis of staghorn coral evolution, and performed a new analysis on the evolution of the “WGD clade” of yeast. The latter revealed novel patterns that were not identified by previous analyses. TREEasy represents a reliable and simple tool to accelerate research in systematic biology ( https://github.com/MaoYafei/TREEasy ).     

玉米转基因技术专利权人合作态势分析

转基因玉米是最重要的转基因主粮作物之一,其转基因技术具有一定的代表性。为了更好地了解和掌握玉米转基因技术领域研发主体合作情况,文章构建了基于专利权人合作网络的目标技术领域专利权人合作态势分析框架,并基于社会网络分析方法与技术,以世界范围内的转基因玉米领域的重要专利权人为分析对象,构建合作网络、分析整体合作特征、挖掘合作子网、探测领域内重要专利权人,从而从宏观、中观和微观三个层面客观展现玉米转基因技术领域专利权人合作态势,为科技战略规划提供一定的决策支撑。     

基于综合评价法的洞庭湖区绿地生态网络构建

绿地生态网络对于改善区域生态空间破碎化、生物多样性降低、生态系统服务供需不平衡及保障区域生态安全具有重要意义。本研究以洞庭湖区为例,在3S技术支持下,从生态系统服务功能、潜在生物多样性、形态空间格局的角度综合评价和识别生态源地及计算栅格单元的基本生态阻力;利用夜间灯光指数修正基本生态阻力;运用最小累积阻力模型识别生态廊道;构建加权评价模型,对源地的聚合度、离散度及廊道的生态连接贡献度进行评价;利用结构特征指数对综合网络、“源-汇”潜在网络及规划网络进行对比分析和评价。结果表明: 源地空间分布不均衡,林地、灌丛与水域三者面积之和占源地总面积的95.9%,位于研究区中部的洞庭湖湿地生态风险较高;源地离生态网络系统中心位置越近及到其他源地的平均最小累积阻力越小,聚合及离散的优势越强;高生态质量源地周围的中、高生态质量源地分布越密集,其聚合度、离散度越高;廊道离高生态质量的源地越近,表现为生态连接贡献度越大;林地、灌丛,尤其是河道在自然生态系统与人类社会系统之间起着非常重要的生态连接作用;“源-汇”规划绿道对“源-汇”潜在生态廊道形成了良好补充,与“源-汇”潜在网络相比,综合网络的α、β、γ、ρ指数分别提高123.1%、25.8%、26.2%、74.6%;与“源-汇”规划网络相比,α、β、γ、ρ指数分别提高了190.0%、31.1%、32.5%、114.6%。本研究结果能为洞庭湖区绿地生态网络构建、国土空间规划提供参考。     

西双版纳国家级自然保护区蚂蚁-树互作网络空间变异

网络分析(network analysis)可以同时分析群落中的物种多样性和种间关系, 为了解生态群落的稳定性机制提供了新的分析思路和方法。本研究从西双版纳国家级自然保护区的纳板河、勐仑和勐腊(补蚌)三个地点采集了树栖性蚂蚁及树木的种类和数量数据, 对蚂蚁-树组成的二分网络进行了分析, 探讨了3个采样点物种的多样性、网络指标以及群落指标之间的关系。我们采用零模型的方法比较了3个样点的标准化网络参数差异。结果表明: 蚂蚁和树木的物种数以及树的异质性指数(Shannon-Wiener多样性指数、Simpson多样性指数)都呈现出勐仑 > 纳板河 > 补蚌的趋势。树木-蚂蚁的灭绝曲线系数大小关系同样为勐仑 > 纳板河 > 补蚌, 灭绝曲线与树的物种数及异质性指数大小趋势一致, 而与蚂蚁的异质性指数并不吻合。根据Z值的绝对值来看, 网络参数(加权嵌套性、平均连接数、特化水平、模块性、连接度)与群落参数(灭绝曲线系数、生态位重叠)的大小趋势相同, 表现出勐仑 > 纳板河 > 补蚌的趋势。综上所述, 蚂蚁-树互作网络的稳定性(灭绝曲线系数)主要由树的数量和异质性指数决定。网络的加权嵌套性和网络中节点的平均连接数也能促进群落的稳定性。而在一个特化的(数值越大表示专性互作越多)和模块化(具有较多密切互作的节点单元)的网络中, 当低营养级物种灭绝时高营养级物种数量将迅速减少。