处理动植物科学研究中的复杂性——从单一性状到功能性状:我们做到了吗?

Q2 Biochemistry, Genetics and Molecular Biology
High-Throughput Pub Date : 2018-05-28 DOI:10.3390/ht7020016
Jessica Roberts, Aoife Power, Shaneel Chandra, James Chapman, Daniel Cozzolino
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引用次数: 2

摘要

目前对控制家畜、作物和植物质量以及不同物种产量的主要因素的认识是不完整的。例如,尽管在同一时期取得了进展,但基准作物品种却持续了几十年,这可以证明这一点。近年来,已经证明基于DNA标记的分子育种已经导致育种(动物和作物)的进步。然而,这些进展并不像该领域的研究人员最初预期的那样。根据几位科学家的说法,其中一个主要原因是有证据表明,复杂的目标性状,如粮食产量、成分或营养质量,除了遗传因素外,还取决于多种因素。因此,需要提出一些问题:目前的分子遗传学方法是否最适合处理诸如产量或质量之类的复杂性状?目前的复杂性状表型分析工具是否足以区分基因型?我们是否需要改变收集和分析数据的方式?
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Handling Complexity in Animal and Plant Science Research-From Single to Functional Traits: Are We There Yet?

The current knowledge of the main factors governing livestock, crop and plant quality as well as yield in different species is incomplete. For example, this can be evidenced by the persistence of benchmark crop varieties for many decades in spite of the gains achieved over the same period. In recent years, it has been demonstrated that molecular breeding based on DNA markers has led to advances in breeding (animal and crops). However, these advances are not in the way that it was anticipated initially by the researcher in the field. According to several scientists, one of the main reasons for this was related to the evidence that complex target traits such as grain yield, composition or nutritional quality depend on multiple factors in addition to genetics. Therefore, some questions need to be asked: are the current approaches in molecular genetics the most appropriate to deal with complex traits such as yield or quality? Are the current tools for phenotyping complex traits enough to differentiate among genotypes? Do we need to change the way that data is collected and analysed?

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来源期刊
High-Throughput
High-Throughput Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
3.60
自引率
0.00%
发文量
0
审稿时长
9 weeks
期刊介绍: High-Throughput (formerly Microarrays, ISSN 2076-3905) is a multidisciplinary peer-reviewed scientific journal that provides an advanced forum for the publication of studies reporting high-dimensional approaches and developments in Life Sciences, Chemistry and related fields. Our aim is to encourage scientists to publish their experimental and theoretical results based on high-throughput techniques as well as computational and statistical tools for data analysis and interpretation. The full experimental or methodological details must be provided so that the results can be reproduced. There is no restriction on the length of the papers. High-Throughput invites submissions covering several topics, including, but not limited to: -Microarrays -DNA Sequencing -RNA Sequencing -Protein Identification and Quantification -Cell-based Approaches -Omics Technologies -Imaging -Bioinformatics -Computational Biology/Chemistry -Statistics -Integrative Omics -Drug Discovery and Development -Microfluidics -Lab-on-a-chip -Data Mining -Databases -Multiplex Assays
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