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通过抽样测序对复杂基因组进行物理图谱绘制:理论分析

Physical mapping of complex genomes by sampled sequencing: a theoretical analysis.

作者信息

Kupfer K, Smith M W, Quackenbush J, Evans G A

机构信息

McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center at Dallas 75235-8591, USA.

出版信息

Genomics. 1995 May 1;27(1):90-100. doi: 10.1006/geno.1995.1010.

Abstract

A method for high-throughput, high-resolution physical mapping of complex genomes and human chromosomes called Genomic Sequence Sampling (GSS) has recently been proposed (Smith et al., 1994, Nature Genet. 7: 40-47). This mapping strategy employs high-density cosmid contig assembly over 200-kb to 1-Mb regions of the target genome coupled with DNA sequencing of the cosmid ends. The relative order and spacing of the sequence fragments is determined from the template contig, resulting in a physical map of 1- to 5-kb resolution that contains a substantial portion of the entire sequence at one-pass accuracy. The purpose of this paper is to determine the theoretical parameters for GSS mapping, to evaluate the effectiveness of the contig-building strategy, and to calculate the expected fraction of the target genome that can be recovered as mapped sequence. A novel aspect of the cosmid fingerprinting and contig-building strategy involves determining the orientation of the genomic inserts relative to the cloning vectors, so that the sampled sequence fragments can be mapped with high resolution. The algorithm is based upon complete restriction enzyme digestion, contig assembly by matching fragments, and end-orientation of individual cosmids by determining the best consistent fit of the labeled cosmid end fragments in the consensus restriction map.

摘要

最近有人提出了一种用于复杂基因组和人类染色体的高通量、高分辨率物理图谱绘制方法,称为基因组序列抽样(GSS)(史密斯等人,1994年,《自然遗传学》7:40 - 47)。这种图谱绘制策略在目标基因组的200 kb至1 Mb区域采用高密度黏粒重叠群组装,并结合黏粒末端的DNA测序。序列片段的相对顺序和间距由模板重叠群确定,从而得到分辨率为1至5 kb的物理图谱,该图谱以单通道精度包含了整个序列的很大一部分。本文的目的是确定GSS图谱绘制的理论参数,评估重叠群构建策略的有效性,并计算能够作为已绘制序列回收的目标基因组的预期比例。黏粒指纹图谱和重叠群构建策略的一个新颖之处在于确定基因组插入片段相对于克隆载体的方向,以便能够高分辨率地绘制抽样的序列片段。该算法基于完全限制性内切酶消化、通过匹配片段进行重叠群组装以及通过在共有限制性图谱中确定标记的黏粒末端片段的最佳一致匹配来确定单个黏粒的末端方向。

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