EAGER: Genome construction in non-model organisms using recombinant populations
EAGER: Genome construction in non-model organisms using recombinant populations
批准号:
1249633
负责人:
Matthew Hahn
金额:
$25.39万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-08-01 至 2015-07-31
中文摘要
全基因组序列信息改变了传统模式生物的研究,现在下一代测序技术正处于其应用于非模式生物的转折点。在数据丰富但缺乏序列的生物系统中工作的研究人员渴望将这些技术应用于他们自己的物种。然而,在这些幼稚的系统中产生有用的、高质量的全基因组序列所涉及的挑战是巨大的。非模型系统可能具有许多直接阻碍基因组组装的生物学特征,因此受益于基因组工具的能力有限。这项研究旨在开发一种新的基因组组装方法,将下一代测序与利用个体之间的遗传杂交形成的重组群体相结合。如果这种方法的全部潜力能够被证明,它将把基因组使能的科学的力量带到广泛的非模式生物手中。大量的生物学知识隐藏在地球上每一个生物体的基因构成中。这些生物的秘密可能掌握着理解生物多样性起源和许多其他生物学谜题的答案的关键。这项研究将提供新的工具,可用于解锁任何物种中包含的遗传信息。因此,所开发的方法将对大量研究人员大有裨益。
英文摘要
Whole genome sequence information has transformed research in traditional model organisms, and now next-generation sequencing technology is at a turning point in its application to non-model organisms. Researchers working in data-rich, but sequence-poor, organismal systems are eager to apply these technologies to their own species. However, the challenges involved in generating useful, high quality, whole genome sequences in these naive systems are substantial. Non-model systems can have many biological features that directly hamper genome assembly, and therefore suffer from limited capacity to benefit from genomic tools. This research aims to develop a new approach to genome assembly, one that combines next-generation sequencing with recombinant populations made using genetic crosses between individuals. If the full potential of the method can be demonstrated, it will bring the power of genome-enabled science within reach of a large range of non-model organisms.A tremendous amount of biological knowledge lies hidden within the genetic make-up of every organism on earth. The secrets of these organisms potentially hold the keys to understanding the origins of biodiversity and the answers to many other biological puzzles. This research will provide new tools that can be used to unlock the genetic information contained within any species. The methods developed will therefore be of great benefit to a large number of researchers.
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