The use and misuse of regression models in landscape genetic analyses

The field of landscape genetics has been rapidly evolving, adopting and adapting analytical frameworks to address research questions. Current studies are increasingly using regression‐based frameworks to infer the individual contributions of landscape and habitat variables on genetic differentiation. This paper outlines appropriate and inappropriate uses of multiple regression for these purposes, and demonstrates through simulation the limitations of different analytical frameworks for making correct inference. Of particular concern are recent studies seeking to explain genetic differences by fitting regression models with effective distance variables calculated independently on separate landscape resistance surfaces. When moving across the landscape, organisms cannot respond independently and uniquely to habitat and landscape features. Analyses seeking to understand how landscape features affect gene flow should model a single conductance or resistance surface as a parameterized function of relevant spatial covariates, and estimate the values of these parameters by linking a single set of resistance distances to observed genetic dissimilarity via a loss function. While this loss function may involve a regression‐like step, the associated nuisance parameters are not interpretable in terms of organismal movement and should not be conflated with what is actually of interest: the mapping between spatial covariates and conductance/resistance. The growth and evolution of landscape genetics as a field has been rapid and exciting. It is the goal of this paper to highlight past missteps and demonstrate limitations of current approaches to ensure that future use of regression models will appropriately consider the process being modeled, which will provide clarity to model interpretation.     

Elevated rates of positive selection drive the evolution of pestiferousness in the Colorado potato beetle (Leptinotarsa decemlineata,Say)

Contextualizing evolutionary history and identifying genomic features of an insect that might contribute to its pest status is important in developing early detection and control tactics. In order to understand the evolution of pestiferousness, which we define as the accumulation of traits that contribute to an insect population's success in an agroecosystem, we tested the importance of known genomic properties associated with rapid adaptation in the Colorado potato beetle (CPB), Leptinotarsa decemlineata Say. Within the leaf beetle genus Leptinotarsa, only CPB, and a few populations therein, has risen to pest status on cultivated nightshades, Solanum. Using whole genomes from ten closely related Leptinotarsa species native to the United States, we reconstructed a high‐quality species tree and used this phylogenetic framework to assess evolutionary patterns in four genomic features of rapid adaptation: standing genetic variation, gene family expansion and contraction, transposable element abundance and location, and positive selection at protein‐coding genes. Throughout approximately 20 million years of history, Leptinotarsa species show little evidence of gene family turnover and transposable element variation. However, there is a clear pattern of CPB experiencing higher rates of positive selection on protein‐coding genes. We determine that these rates are associated with greater standing genetic variation due to larger effective population size, which supports the theory that the demographic history contributes to rates of protein evolution. Furthermore, we identify a suite of coding genes under positive selection that are putatively associated with pestiferousness in the Colorado potato beetle lineage. They are involved in the biological processes of xenobiotic detoxification, chemosensation and hormone function.     

心肺运动试验（CPET）评价个体化精准运动整体方案强化管控心脑血管慢病疗效的临床研究*

目的: 探讨研究症状限制性极限运动心肺运动试验（CPET）评价个体化精准运动整体方案强化管控3月后（简称强化管控）的长期慢病患者整体功能的改善。方法: 选取2014年至2016年由我们团队强化管控的长期心脑血管代谢慢病为主的患者20例,签署知情同意书后完成CPET,根据CPET及连续功能学检测结果制定以个体化适度运动强度为核心的整体管理方案,强化管控3月后再行CPET,个体化分析每例患者强化管控前后CPET指标的变化、计算差值和百分差值。结果: 本研究心脑血管代谢性慢病为主的患者20例（18男2女）,年龄（55.75±10.80,26~73）岁,身高（172.20±8.63,153~190）cm,体重（76.35±15.63,53~105）kg,所有患者CPET和强化管控期间均无任何危险事件发生。①强化管控后患者静态肺功能指标及静息收缩压、心率收缩压乘积和空腹血糖等均显著改善（P<0.05）。②强化管控前峰值摄氧量为（55.60±15.69,34.37~77.45）%pred和无氧阈为（60.11±12.26,43.29~80.63）%pred;强化管控后峰值耗氧量为（71.85±21.04,42.40~102.00）%pred和无氧阈为（74.95±17.03,51.90~99.47）%pred;管控后较管控前峰值摄氧量和无氧阈显著提高分别达（29.09±7.38,17.78~41.80）%和（25.16±18.38,1.77~81.86）%（P均<0.01）;其他核心指标峰值氧脉搏、峰值负荷功率、摄氧通气效率平台和递增功率运动持续时间均显著升高（P均<0.01）,二氧化碳排出通气效率最低值及二氧化碳排出通气斜率也显著好转（P<0.01）。③个体化分析而言,强化管控后15例上述8项CPET核心指标全部改善,另5例7项指标改善;全部病例峰值摄氧量（%pred）提高>15%以上,16例>20%,13例>25%,10例>30%。结论: CPET能安全客观定量地评估人体整体功能状态和治疗效果、指导制定个体化精准运动强度。个体化精准运动整体方案强化管控三个月能安全有效逆转长期心脑血管代谢等慢病患者的整体功能状态和异常指标。     

A comprehensive landscape genomics approach for seed sourcing strategies in landscapes under varying degrees of habitat disturbance

As most ecosystems around the world are threatened by anthropogenic degradation and climate change, there is an increasing urgency to implement restoration strategies aiming at ensuring ecosystem self‐sustainability and resilience. An initial step towards that goal relies on selecting the most suitable seed sources for a successful revegetation, which can be extremely challenging in highly degraded landscapes. The most common seed sourcing strategy is to select local seeds because it is assumed that plants experience strong adaptations to their natal sites. An alternative strategy is the selection of climate‐adapted genotypes to future conditions. While considering future climatic projections is important to account for spatial shifts in climate to inform assisted gene flow and translocations, to restore highly degraded landscapes we need a comprehensive approach that first accounts for species adaptations to current at‐site environmental conditions. In this issue of Molecular Ecology Resources, Carvalho et al. present a novel landscape genomics framework to identify the most appropriate seed sourcing strategy for moderately and highly degraded sites by integrating genotype, phenotype and environmental data in a spatially explicit context for two native plant species with potential to help restore iron‐rich Amazonian savannas. This framework is amenable to be applicable and adapted to a broad range of restoration initiatives, as the dichotomy between focusing on the current or future climatic conditions should depend on the goals and environmental circumstances of each restoration site.     

Single cell human genomic analyses: a way to refine the knowledge of cellular heterogeneity origins in individual subject

Single cell genomics performed on individual human subjects' tumors, neural tissues, and sperm samples revealed the existence of genetic heterogeneity arising through either mutations in exomes, deletions, recombinations, and duplications of DNA sequences, as well as aneuploidy. These genetic changes happen during cell cycles followed by cell division. The aim of this review is to strictly focus on single cell human genomics and intends to deliver information that can help to refine fundamental knowledge relating to genetic causes of cellular heterogeneity origins in both healthy and disease states. Allogenic heterogeneity as well as heterogeneity origins of cells possessing the same genome with different gene expression patterns is not the subject of this review. Future research still requires: a) improvement for complete and errorless DNA acquisition and sequencing of not only selected parts of the genome, and b) analyses of more samples that contain millions of cells. These data will deliver a more precise comparative representation of genetic diversity among single cells in an individual human subject. Consequently, we will be able to better distinguish between the role of genetic, versus epigenetic, and stochastic factors in the cellular diversity of over 30 trillion cells present in a human body.     

Proteome-Scale Analysis of Biochemical Activity

ABSTRACT

During the last 10 years, there has been a large increase in the number of genome sequences available for study, altering the way that the biology of organisms is studied. In particular, scientific attention has increasingly focused on the proteome, and specifically on the role of all the proteins encoded by the genome. We focus here on several aspects of this problem. We describe several technologies in widespread use to clone genes on a genome-wide scale, and to express and purify the proteins encoded by these genes. We also describe a number of methods that have been developed to analyze various biochemical properties of the proteins, with attention to the methodology and the limitations of the approaches, followed by a look at possible developments in the next decade.