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Science Letters:Two ancient rounds of polyploidy in rice genome
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作者 张扬 徐国华 +1 位作者 郭兴益 樊龙江 《Journal of Zhejiang University-Science B(Biomedicine & Biotechnology)》 SCIE CAS CSCD 2005年第2期87-90,共4页
An ancient genome duplication (PPP1) that predates divergence of the cereals has recently been recognized. We report here another potentially older large-scale duplication (PPP2) event that predates monocot-dicot dive... An ancient genome duplication (PPP1) that predates divergence of the cereals has recently been recognized. We report here another potentially older large-scale duplication (PPP2) event that predates monocot-dicot divergence in the genome of rice (Oryza sativa L.), as inferred from the age distribution of pairs of duplicate genes based on recent genome data for rice. Our results suggest that paleopolyploidy was widespread and played an important role in the evolution of rice. 展开更多
关键词 Oryza sativa POLYPLOIDY Genome evolution Age distribution of duplicate genes Monocot-dicot divergence
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植物内生固氮菌系统发育进化新进展 被引量:10
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作者 黄淑芬 郜晨 +2 位作者 刘丽辉 谭志远 彭桂香 《微生物学通报》 CAS CSCD 北大核心 2018年第1期181-190,共10页
在植物内生固氮菌系统发育进化关系研究中,常用的方法有形态学与蛋白质水平法、数值分类和自动化鉴定法、化学分类法、分子遗传学方法等。本文简要介绍了常用方法的关键技术,并归纳了它们的优缺点。生物学的研究进入基因组时代后,随着... 在植物内生固氮菌系统发育进化关系研究中,常用的方法有形态学与蛋白质水平法、数值分类和自动化鉴定法、化学分类法、分子遗传学方法等。本文简要介绍了常用方法的关键技术,并归纳了它们的优缺点。生物学的研究进入基因组时代后,随着高通量DNA测序技术在微生物学领域应用的迅速发展,全基因组测序被应用到微生物系统发育进化研究中,然而目前并未发现对已测全基因组序列的植物内生固氮菌进行系统总结。本文在对已测序植物内生固氮菌进行归纳的基础上,又详细研究了基于基因组数据的几种具有代表性的新方法(ANI分析法、最大唯一匹配指数法、核心基因组分析、组分矢量法、基因流动性分析),并结合目前系统发育进化研究常用方法,对植物内生固氮菌系统发育进化研究趋势进行总结和展望,旨在使植物内生固氮菌的系统发育进化关系研究在精确度、可靠性等方面有所突破。 展开更多
关键词 内生固氮菌 系统发育进化 高通量测序 基因组分析方法
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Navigating the currents of seascape genomics: how spatial analyses can augment population genomic studies 被引量:1
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作者 Cynthia RIGINOS Eric D. CRANDALL +2 位作者 Libby LIGGINS Pim BONGAERTS Eric A, TREML 《Current Zoology》 SCIE CAS CSCD 2016年第6期581-601,共21页
Population genomic approaches are making rapid inroads in the study of non-model organisms, including marine taxa. To date, these marine studies have predominantly focused on rudimentary metrics describing the spatial... Population genomic approaches are making rapid inroads in the study of non-model organisms, including marine taxa. To date, these marine studies have predominantly focused on rudimentary metrics describing the spatial and environmental context of their study region (e.g., geographical distance, average sea surface temperature, average salinity). We contend that a more nuanced and considered approach to quantifying seascape dynamics and patterns can strengthen population genomic investigations and help identify spatial, temporal, and environmental factors associated with differing selective regimes or demographic histories. Nevertheless, approaches for quantifying marine landscapes are complicated. Characteristic features of the marine environment, including pelagic living in flowing water (experienced by most marine taxa at some point in their life cycle), require a well-designed spatial-temporal sampling strategy and analysis. Many genetic summary statistics used to describe populations may be inappropriate for marine species with large population sizes, large species ranges, stochastic recruitment, and asymmetrical gene flow. Finally, statistical approaches for testing associations between seascapes and population genomic patterns are still maturing with no single approach able to capture all relevant considerations. None of these issues are completely unique to marine systems and therefore similar issues and solutions will be shared for many organisms regardless of habitat. Here, we outline goals and spatial approaches for land- scape genomics with an emphasis on marine systems and review the growing empirical literature on seascape genomics. We review established tools and approaches and highlight promising new strategies to overcome select issues including a strategy to spatially optimize sampling. Despite the many challenges, we argue that marine systems may be especially well suited for identifying candidate genomic regions under environmentally mediated selection and that seascape genomic approaches are especially useful for identifying robust locus-by-environment associations. 展开更多
关键词 adaptation genetic-environment association landscape OCEANOGRAPHY population genomics remote sensing seascape genetics.
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