Dataset Information

Breakpoint analysis of balanced chromosome rearrangements by next-generation paired-end sequencing.

ABSTRACT: Characterisation of breakpoints in disease-associated balanced chromosome rearrangements (DBCRs), which disrupt or inactivate specific genes, has facilitated the molecular elucidation of a wide variety of genetic disorders. However, conventional methods for mapping chromosome breakpoints, such as in situ hybridisation with fluorescent dye-labelled bacterial artificial chromosome clones (BAC-FISH), are laborious, time consuming and often with insufficient resolution to unequivocally identify the disrupted gene. By combining DNA array hybridisation with chromosome sorting, the efficiency of breakpoint mapping has dramatically improved. However, this can only be applied when the physical properties of the derivative chromosomes allow them to be flow sorted. To characterise the breakpoints in all types of balanced chromosome rearrangements more efficiently and more accurately, we performed massively parallel sequencing using Illumina 1G analyser and ABI SOLiD systems to generate short sequencing reads from both ends of DNA fragments. We applied this method to four different DBCRs, including two reciprocal translocations and two inversions. By identifying read pairs spanning the breakpoints, we were able to map the breakpoints to a region of a few hundred base pairs that could be confirmed by subsequent PCR amplification and Sanger sequencing of the junction fragments. Our results show the feasibility of paired-end sequencing of systematic breakpoint mapping and gene finding in patients with disease-associated chromosome rearrangements.

SUBMITTER: Chen W

PROVIDER: S-EPMC2987311 | biostudies-literature | 2010 May

REPOSITORIES: biostudies-literature

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Breakpoint analysis of balanced chromosome rearrangements by next-generation paired-end sequencing.

Chen Wei W Ullmann Reinhard R Langnick Claudia C Menzel Corinna C Wotschofsky Zofia Z Hu Hao H Döring Andreas A Hu Yuhui Y Kang Hui H Tzschach Andreas A Hoeltzenbein Maria M Neitzel Heidemarie H Markus Susanne S Wiedersberg Eberhard E Kistner Gerd G van Ravenswaaij-Arts Conny M A CM Kleefstra Tjitske T Kalscheuer Vera M VM Ropers Hans-Hilger HH

European journal of human genetics : EJHG 20091202 5

Characterisation of breakpoints in disease-associated balanced chromosome rearrangements (DBCRs), which disrupt or inactivate specific genes, has facilitated the molecular elucidation of a wide variety of genetic disorders. However, conventional methods for mapping chromosome breakpoints, such as in situ hybridisation with fluorescent dye-labelled bacterial artificial chromosome clones (BAC-FISH), are laborious, time consuming and often with insufficient resolution to unequivocally identify the ...[more]

PMID: 19953122

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Project description:BackgroundAdapter trimming is a prerequisite step for analyzing next-generation sequencing (NGS) data when the reads are longer than the target DNA/RNA fragments. Although typically used in small RNA sequencing, adapter trimming is also used widely in other applications, such as genome DNA sequencing and transcriptome RNA/cDNA sequencing, where fragments shorter than a read are sometimes obtained because of the limitations of NGS protocols. For the newly emerged Nextera long mate-pair (LMP) protocol, junction adapters are located in the middle of all properly constructed fragments; hence, adapter trimming is essential to gain the correct paired reads. However, our investigations have shown that few adapter trimming tools meet both efficiency and accuracy requirements simultaneously. The performances of these tools can be even worse for paired-end and/or mate-pair sequencing.ResultsTo improve the efficiency of adapter trimming, we devised a novel algorithm, the bit-masked k-difference matching algorithm, which has O(kn) expected time with O(m) space, where k is the maximum number of differences allowed, n is the read length, and m is the adapter length. This algorithm makes it possible to fully enumerate all candidates that meet a specified threshold, e.g. error ratio, within a short period of time. To improve the accuracy of this algorithm, we designed a simple and easy-to-explain statistical scoring scheme to evaluate candidates in the pattern matching step. We also devised scoring schemes to fully exploit the paired-end/mate-pair information when it is applicable. All these features have been implemented in an industry-standard tool named Skewer (https://sourceforge.net/projects/skewer). Experiments on simulated data, real data of small RNA sequencing, paired-end RNA sequencing, and Nextera LMP sequencing showed that Skewer outperforms all other similar tools that have the same utility. Further, Skewer is considerably faster than other tools that have comparative accuracies; namely, one times faster for single-end sequencing, more than 12 times faster for paired-end sequencing, and 49% faster for LMP sequencing.ConclusionsSkewer achieved as yet unmatched accuracies for adapter trimming with low time bound.

Dataset Information

Breakpoint analysis of balanced chromosome rearrangements by next-generation paired-end sequencing.

Publications

Breakpoint analysis of balanced chromosome rearrangements by next-generation paired-end sequencing.

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