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用于扩展细菌人工染色体效用的限制酶切图谱数据库。

A database of restriction maps to expand the utility of bacterial artificial chromosomes.

作者信息

Winden Eamon, Vasquez-Echeverri Alejandro, Calle-Castañeda Susana, Lian Yumin, Hernandez Ortiz Juan Pablo, Schwartz David C

机构信息

Laboratory of Genetics, Department of Chemistry, Laboratory for Molecular and Computational Genomics, University of Wisconsin-Madison, Madison, WI 53705, USA.

Department of Biophysics, Department of Genetics, Department of Chemistry, Laboratory for Molecular and Computational Genomics, University of Wisconsin-Madison, Madison, WI 53705, USA.

出版信息

GigaByte. 2023 Sep 20;2023:gigabyte93. doi: 10.46471/gigabyte.93. eCollection 2023.

DOI:10.46471/gigabyte.93
PMID:37753479
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10518450/
Abstract

While Bacterial Artificial Chromosomes libraries were once a key resource for the genomic community, they have been obviated, for sequencing purposes, by long-read technologies. Such libraries may now serve as a valuable resource for manipulating and assembling large genomic constructs. To enhance accessibility and comparison, we have developed a BAC restriction map database. Using information from the National Center for Biotechnology Information's cloneDB FTP site, we constructed a database containing the restriction maps for both uniquely placed and insert-sequenced BACs from 11 libraries covering the recognition sequences of the available restriction enzymes. Along with the database, we generated a set of Python functions to reconstruct the database and more easily access the information within. This data is valuable for researchers simply using BACs, as well as those working with larger sections of the genome in terms of synthetic genes, large-scale editing, and mapping.

摘要

虽然细菌人工染色体文库曾经是基因组学界的关键资源,但出于测序目的,它们已被长读长技术所取代。现在,此类文库可作为操作和组装大型基因组构建体的宝贵资源。为了提高可访问性和可比性,我们开发了一个BAC限制酶切图谱数据库。利用来自美国国立生物技术信息中心克隆数据库FTP站点的信息,我们构建了一个数据库,其中包含来自11个文库的唯一放置和插入测序BAC的限制酶切图谱,这些文库涵盖了可用限制酶的识别序列。除了该数据库,我们还生成了一组Python函数,用于重建数据库并更轻松地访问其中的信息。这些数据对于仅使用BAC的研究人员以及在合成基因、大规模编辑和图谱绘制方面处理基因组较大片段的研究人员而言很有价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed3e/10518450/46890dcfcf70/gigabyte-2023-93-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed3e/10518450/46890dcfcf70/gigabyte-2023-93-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed3e/10518450/46890dcfcf70/gigabyte-2023-93-g001.jpg

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