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利用高通量测序技术在大山雀 Parus major 中进行全基因组 SNP 检测。

Genome-wide SNP detection in the great tit Parus major using high throughput sequencing.

机构信息

Animal Breeding and Genomics Centre, Wageningen University, The Netherlands.

出版信息

Mol Ecol. 2010 Mar;19 Suppl 1:89-99. doi: 10.1111/j.1365-294X.2009.04486.x.

Abstract

Identifying genes that underlie ecological traits will open exiting possibilities to study gene-environment interactions in shaping phenotypes and in measuring natural selection on genes. Evolutionary ecology has been pursuing these objectives for decades, but they come into reach now that next generation sequencing technologies have dramatically lowered the costs to obtain the genomic sequence information that is currently lacking for most ecologically important species. Here we describe how we generated over 2 billion basepairs of novel sequence information for an ecological model species, the great tit Parus major. We used over 16 million short sequence reads for the de novo assembly of a reference sequence consisting of 550 000 contigs, covering 2.5% of the genome of the great tit. This reference sequence was used as the scaffold for mapping of the sequence reads, which allowed for the detection of over 20 000 novel single nucleotide polymorphisms. Contigs harbouring 4272 of the single nucleotide polymorphisms could be mapped to a unique location on the recently sequenced zebra finch genome. Of all the great tit contigs, significantly more were mapped to the microchromosomes than to the intermediate and the macrochromosomes of the zebra finch, indicating a higher overall level of sequence conservation on the microchromosomes than on the other types of chromosomes. The large number of great tit contigs that can be aligned to the zebra finch genome shows that this genome provides a valuable framework for large scale genetics, e.g. QTL mapping or whole genome association studies, in passerines.

摘要

确定生态特征背后的基因将为研究基因-环境相互作用如何影响表型以及测量基因的自然选择提供新的可能性。进化生态学已经追求这些目标几十年了,但现在随着下一代测序技术的出现,这些目标变得可行,因为该技术极大地降低了获取基因组序列信息的成本,而这些信息目前对于大多数具有重要生态学意义的物种来说都是缺乏的。在这里,我们描述了如何为生态模型物种大山雀(Parus major)生成超过 20 亿个碱基对的新序列信息。我们使用超过 1600 万个短序列读取来从头组装一个参考序列,该参考序列由 550000 个序列组成,覆盖了大山雀基因组的 2.5%。该参考序列被用作序列读取映射的支架,这使得可以检测到超过 20000 个新的单核苷酸多态性。可以将包含 4272 个单核苷酸多态性的序列映射到最近测序的斑胸草雀基因组上的一个独特位置。在所有大山雀序列中,被映射到微染色体的序列明显多于被映射到斑胸草雀中间染色体和大染色体的序列,这表明微染色体的整体序列保守性高于其他类型的染色体。大量可以与斑胸草雀基因组对齐的大山雀序列表明,该基因组为大规模遗传学提供了一个有价值的框架,例如 QTL 图谱或全基因组关联研究,适用于雀形目鸟类。

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