Fish genomes and their evolution under the influence of ecology

IF 3.1 3区 环境科学与生态学 Q2 ECOLOGY Ecological Complexity Pub Date : 2022-03-01 DOI:10.1016/j.ecocom.2022.100980
Swarajpal Singh Randhawa, Ravindra Pawar
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引用次数: 1

Abstract

Environmental interactions and the effects of such interactions on the evolution of genome attributes is an intriguing area of ongoing research. Several earlier studies have delved into how the genome size (GS) and the guanine-cytosine content (GC) of genomes are shaped by species’ ecology while largely disregarding other genome attributes, such as number of chromosomes (CR), number of genes (GE), and protein count (PC) from such comparisons. The present study was designed at understanding the influence of ecology––climate, habitat, and depth––on genome attributes by using the most current data on 579 whole fish genomes available at NCBI. Given the diverse and intricate roles of GS and GC in species adaptations to temperature, salinity, and hydrostatic pressure, the focus was on finding if and how the genomes responded to these stressors and if any common patterns existed in the genome-level responses. Our analyses exhibited some significant and intriguing trends for fishes as a whole while indicating strong effects of ecology on GS, GC, CR, and PC. Also, some very unique trends were observed on regressing GS and GC values across temperature, salinity, and depth clines. Accordingly, a very strong decline in the GS and a concomitant increase in GC were observed in species through the tropics/sub tropics to the temperate/poles, from freshwater to the marine habitats, and from the pelagic to bathydemersal depths. Observed patterns strongly support the notion that smaller GS and larger GC are associated with species inhabiting more stable environments and vice versa. The results also signify the effect of these patterns on protein flexibility and its role in tolerating stressful conditions. Observed patterns are discussed in the light of latitudinal biodiversity gradient, habitat complexity, and energy and metabolic expenditure hypothesis.

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生态学影响下的鱼类基因组及其进化
环境相互作用以及这种相互作用对基因组属性进化的影响是一个有趣的研究领域。一些早期的研究已经深入研究了基因组大小(GS)和基因组的鸟嘌呤-胞嘧啶含量(GC)是如何被物种生态塑造的,而在很大程度上忽略了其他基因组属性,如染色体数量(CR)、基因数量(GE)和蛋白质计数(PC)。本研究旨在通过使用NCBI提供的579条全鱼基因组的最新数据,了解生态-气候,栖息地和深度-对基因组属性的影响。考虑到GS和GC在物种适应温度、盐度和静水压力中的复杂作用,研究的重点是发现基因组是否以及如何对这些压力源做出反应,以及基因组水平的反应是否存在任何共同模式。我们的分析显示了鱼类整体的一些重要和有趣的趋势,同时表明了生态对GS, GC, CR和PC的强烈影响。此外,在温度、盐度和深度曲线上,GS和GC值的回归也有一些非常独特的趋势。因此,从热带/亚热带到温带/两极,从淡水到海洋栖息地,从远洋到深海,在物种中观测到GS的强烈下降和伴随的GC的增加。观察到的模式强烈支持这样的观点,即较小的GS和较大的GC与物种生活在更稳定的环境有关,反之亦然。结果还表明这些模式对蛋白质灵活性的影响及其在耐受压力条件中的作用。根据纬度生物多样性梯度、生境复杂性和能量代谢消耗假说对观测模式进行了讨论。
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来源期刊
Ecological Complexity
Ecological Complexity 环境科学-生态学
CiteScore
7.10
自引率
0.00%
发文量
24
审稿时长
3 months
期刊介绍: Ecological Complexity is an international journal devoted to the publication of high quality, peer-reviewed articles on all aspects of biocomplexity in the environment, theoretical ecology, and special issues on topics of current interest. The scope of the journal is wide and interdisciplinary with an integrated and quantitative approach. The journal particularly encourages submission of papers that integrate natural and social processes at appropriately broad spatio-temporal scales. Ecological Complexity will publish research into the following areas: • All aspects of biocomplexity in the environment and theoretical ecology • Ecosystems and biospheres as complex adaptive systems • Self-organization of spatially extended ecosystems • Emergent properties and structures of complex ecosystems • Ecological pattern formation in space and time • The role of biophysical constraints and evolutionary attractors on species assemblages • Ecological scaling (scale invariance, scale covariance and across scale dynamics), allometry, and hierarchy theory • Ecological topology and networks • Studies towards an ecology of complex systems • Complex systems approaches for the study of dynamic human-environment interactions • Using knowledge of nonlinear phenomena to better guide policy development for adaptation strategies and mitigation to environmental change • New tools and methods for studying ecological complexity
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