Persistent bill and corolla matching despite shifting temporal resources in tropical hummingbird‐plant interactions

By specialising on specific resources, species evolve advantageous morphologies to increase the efficiency of nutrient acquisition. However, many specialists face variation in resource availability and composition. Whether specialists respond to these changes depends on the composition of the resource pulses, the cost of foraging on poorly matched resources, and the strength of interspecific competition. We studied hummingbird bill and plant corolla matching during seasonal variation in flower availability and morphology. Using a hierarchical Bayesian model, we accounted for the detectability and spatial overlap of hummingbird‐plant interactions. We found that despite seasonal pulses of flowers with short‐corollas, hummingbirds consistently foraged on well‐matched flowers, leading to low niche overlap. This behaviour suggests that the costs of searching for rare and more specialised resources are lower than the benefit of switching to super‐abundant resources. Our results highlight the trade‐off between foraging efficiency and interspecific competition, and underline niche partitioning in maintaining tropical diversity.     

Network‐based visualisation reveals new insights into transposable element diversity

Transposable elements (TEs) are widespread across eukaryotic genomes, yet their content varies widely between different species. Factors shaping the diversity of TEs are poorly understood. Understanding the evolution of TEs is difficult because their sequences diversify rapidly and TEs are often transferred through non‐conventional means such as horizontal gene transfer. We developed a method to track TE evolution using network analysis to visualise TE sequence and TE content across different genomes. We illustrate our method by first using a monopartite network to study the sequence evolution of Tc1/mariner elements across focal species. We identify a connection between two subfamilies associated with convergent acquisition of a domain from a protein‐coding gene. Second, we use a bipartite network to study how TE content across species is shaped by epigenetic silencing mechanisms. We show that the presence of Piwi‐interacting RNAs is associated with differences in network topology after controlling for phylogenetic effects. Together, our method demonstrates how a network‐based approach can identify hitherto unknown properties of TE evolution across species.     

Convergent mechanisms favor fast amyloid formation in two lambda 6a Ig light chain mutants

Extracellular deposition as amyloids of immunoglobulin light chains causes light chain amyloidosis. Among the light chain families, lambda 6a is one of the most frequent in light chain amyloidosis patients. Its germline protein, 6aJL2, and point mutants, R24G and P7S, are good models to study fibrillogenesis, because their stability and fibril formation characteristics have been described. Both mutations make the germline protein unstable and speed up its ability to aggregate. To date, there is no molecular mechanism that explains how these differences in amyloidogenesis can arise from a single mutation. To look into the structural and dynamical differences in the native state of these proteins, we carried out molecular dynamics simulations at room temperature. Despite the structural similarity of the germline protein and the mutants, we found differences in their dynamical signatures that explain the mutants’ increased tendency to form amyloids. The contact network alterations caused by the mutations, though different, converge in affecting two anti‐aggregation motifs present in light chain variable domains, suggesting a different starting point for aggregation in lambda chains compared to kappa chains.     

带时间延迟的Cohen-Grossberg神经网络全局鲁棒稳定性的一个结果（英文）

在本文中,我们讨论了一类带时间延迟的Cohen-Grossberg神经网络,并研究了这个系统平衡点的全局鲁棒稳定性。利用Lyapunov函数,我们得出了全局鲁棒收敛性的几个充分条件。这些条件以线性矩阵不等式（LMI）的形式表达。因此,从计算的角度出发他们是高效的。另外,这些条件不依赖于时间延迟和神经网络的激发函数。     

一个生物网络比对的启发式算法

随着各种高通量生物实验技术的发明和广泛应用,越来越多的分子生物网络数据被公布.有效而且可靠的比对这些网络对检测分子生物网络的保守性功能模块和推测物种间的进化关系有着十分重要的意义.然而,由于网络比对在理论上是NP-困难（nondeterministic polynomialtime-hard）问题,它已经成为当前计算生物学需要攻克的主要难点之一.本文提出了一个比对两个蛋白质相互作用网络的启发式算法.该算法首先通过比较两个网络中所有顶点的邻域相似性给出这两个网络的顶点相似性矩阵,然后利用该矩阵将全局网络比对问题转化为一个二部图匹配问题.众所周知,二部图匹配问题具有多项式时间复杂度算法,本文利用ILOG CPLEX软件进行求解.为了验证该算法的优越性,作者比对了水痘病毒（varicella-zoster,VZV）和卡波济（氏）肉瘤病毒（kaposi＇s sarcomaassociated herpesvirus,KSHV）的蛋白质相互作用网络,并且把比对结果同其它网络比对算法进行比较.结果证明该算法显著提高了全局网络比对的精确度.     

Do we consent to rules of consent and confidentiality?

Confidentiality and informed consent are important concepts enabling the sharing of sensitive data. In a paper on this topic of this issue, Williams and Pigeot ( 2017 ) discuss that these have to be balanced with openness to ensure research standards. In this opinion paper, we give some background on how the paper by Williams and Pigeot evolved, reflect on their concepts, and provide some examples of the application of these concepts in various settings relevant to biostatisticians working in health research.     

Eco-evolution from deep time to contemporary dynamics: The role of timescales and rate modulators

Eco-evolutionary dynamics, or eco-evolution for short, are often thought to involve rapid demography (ecology) and equally rapid heritable phenotypic changes (evolution) leading to novel, emergent system behaviours. We argue that this focus on contemporary dynamics is too narrow: Eco-evolution should be extended, first, beyond pure demography to include all environmental dimensions and, second, to include slow eco-evolution which unfolds over thousands or millions of years. This extension allows us to conceptualise biological systems as occupying a two-dimensional time space along axes that capture the speed of ecology and evolution. Using Hutchinson's analogy: Time is the ‘theatre’ in which ecology and evolution are two interacting ‘players’. Eco-evolutionary systems are therefore dynamic: We identify modulators of ecological and evolutionary rates, like temperature or sensitivity to mutation, which can change the speed of ecology and evolution, and hence impact eco-evolution. Environmental change may synchronise the speed of ecology and evolution via these rate modulators, increasing the occurrence of eco-evolution and emergent system behaviours. This represents substantial challenges for prediction, especially in the context of global change. Our perspective attempts to integrate ecology and evolution across disciplines, from gene-regulatory networks to geomorphology and across timescales, from today to deep time.     

Evolving modular genetic regulatory networks with a recursive,top-down approach

Being able to design genetic regulatory networks (GRNs) to achieve a desired cellular function is one of the main goals of synthetic biology. However, determining minimal GRNs that produce desired time-series behaviors is non-trivial. In this paper, we propose a ‘top-down’ approach to evolving small GRNs and then use these to recursively boot-strap the identification of larger, more complex, modular GRNs. We start with relatively dense GRNs and then use differential evolution (DE) to evolve interaction coefficients. When the target dynamical behavior is found embedded in a dense GRN, we narrow the focus of the search and begin aggressively pruning out excess interactions at the end of each generation. We first show that the method can quickly rediscover known small GRNs for a toggle switch and an oscillatory circuit. Next we include these GRNs as non-evolvable subnetworks in the subsequent evolution of more complex, modular GRNs. Successful solutions found in canonical DE where we truncated small interactions to zero, with or without an interaction penalty term, invariably contained many excess interactions. In contrast, by incorporating aggressive pruning and the penalty term, the DE was able to find minimal or nearly minimal GRNs in all test problems.