Dataset Information

STR-realigner: a realignment method for short tandem repeat regions.

ABSTRACT: In the estimation of repeat numbers in a short tandem repeat (STR) region from high-throughput sequencing data, two types of strategies are mainly taken: a strategy based on counting repeat patterns included in sequence reads spanning the region and a strategy based on estimating the difference between the actual insert size and the insert size inferred from paired-end reads. The quality of sequence alignment is crucial, especially in the former approaches although usual alignment methods have difficulty in STR regions due to insertions and deletions caused by the variations of repeat numbers.We proposed a new dynamic programming based realignment method named STR-realigner that considers repeat patterns in STR regions as prior knowledge. By allowing the size change of repeat patterns with low penalty in STR regions, accurate realignment is expected. For the performance evaluation, publicly available STR variant calling tools were applied to three types of aligned reads: synthetically generated sequencing reads aligned with BWA-MEM, those realigned with STR-realigner, those realigned with ReviSTER, and those realigned with GATK IndelRealigner. From the comparison of root mean squared errors between estimated and true STR region size, the results for the dataset realigned with STR-realigner are better than those for other cases. For real data analysis, we used a real sequencing dataset from Illumina HiSeq 2000 for a parent-offspring trio. RepeatSeq and lobSTR were applied to the sequence reads for these individuals aligned with BWA-MEM, those realigned with STR-realigner, ReviSTER, and GATK IndelRealigner. STR-realigner shows the best performance in terms of consistency of the size of estimated STR regions in Mendelian inheritance. Root mean squared error values were also calculated from the comparison of these estimated results with STR region sizes obtained from high coverage PacBio sequencing data, and the results from the realigned sequencing data with STR-realigner showed the least (the best) root mean squared error value.The effectiveness of the proposed realignment method for STR regions was verified from the comparison with an existing method on both simulation datasets and real whole genome sequencing dataset.

SUBMITTER: Kojima K

PROVIDER: S-EPMC5135796 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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STR-realigner: a realignment method for short tandem repeat regions.

Kojima Kaname K Kawai Yosuke Y Misawa Kazuharu K Mimori Takahiro T Nagasaki Masao M

BMC genomics 20161203 1

<h4>Background</h4>In the estimation of repeat numbers in a short tandem repeat (STR) region from high-throughput sequencing data, two types of strategies are mainly taken: a strategy based on counting repeat patterns included in sequence reads spanning the region and a strategy based on estimating the difference between the actual insert size and the insert size inferred from paired-end reads. The quality of sequence alignment is crucial, especially in the former approaches although usual align ...[more]

PMID: 27912743

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Project description:Background and Objective: Short Tandem Repeats (STR) show considerable differences among individuals in the population from which they used for identification. There are various methods for analysis of these STR loci, and capillary electrophoresis method already used as an international standard. Due to the high costs of this process, this study aimed to set up a Multiplex PCR method in some standard STR loci so that we can use its PCR product in STR analysis with different methods of HPLC, GC-Mass, and Capillary Electrophoresis. Materials and Methods: 8 typical STR loci in the identification selected according to their size in the two groups of four (CSF1PO, VWA, D18S51, PentaD and TPOX, Amelogenin, FGA, SE33) from NIST (National Institute of Standards and Technology). The above SSR primers prepared from Genbank and Monoplex PCR was designed based on their size. Then, with the changes in temperature conditions, magnesium ion, primers concentration, and setting-up, Hot Start Multiplex PCR of four markers was carried out. PCR product investigated on the agarose gel electrophoresis (3%) and the results of genotyping analyzed by Genetic Analyzer. Results: The Results showed that all STR loci under study are detectable as Monoplex PCR at a temperature of 62°-66° and 1.5 mM magnesium ion. Moreover, Multiplex PCR results showed that when the concentration of primer and temperature measured by the fixed concentration of magnesium, CSF1PO, and D18S51 loci bands are weaker than desired. Using a standard buffer and set Magnesium conditions against changes in the primer concentration and temperature, when Taq polymerase enzyme is added to test tubes at a temperature of 94°, Multiplex PCR bands are visible desirably. Capillary electrophoresis genotyping results obtained in all eight loci and the Locus FGA had the most allelic diversity and the loci TPOX and CSF1PO had the lowest allelic diversity. TPOX and CSF1PO loci had the lowest allelic frequencies, and FGA locus had the most allelic frequency. Moreover, about the determination of statistical indicators of identification using PowerStats V12 software, CSF1PO locus allocated the most RMP (0.219) and FGA locus the highest heterozygosity (100%) and the highest polymorphic rate (PIC) (0.82). Conclusion: The setup performed in this study showed that with two-step multiplex PCR procedure of four markers, PCR can be carried out for eight loci without additional real-time products that this shows proper conditions that we can use their PCR product in analyzing SRTs with different methods of HPLC, GC-Mass, and Capillary Electrophoresis. Besides, the FGA locus was raised as the best loci for identification in the study population concerning the high PD index and high polymorphism.

Project description:BACKGROUND:Whole-genome sequencing is performed routinely as a means to identify polymorphic genetic loci such as short tandem repeat loci. We have developed a simple tool, called pSTR Finder, which is freely available as a means of identifying putative polymorphic short tandem repeat (STR) loci from data generated from genome-wide sequences. The program performs cross comparisons on the STR sequences generated using the Tandem Repeats Finder based on multiple-genome samples in a FASTA format. These comparisons generate reports listing identical, polymorphic, and different STR loci when comparing two samples. METHODS:The web site http://forensic.mc.ntu.edu.tw:9000/PSTRWeb/Default has been developed as a means to identify polymorphic STR loci within complex mass genome sequences. The program was developed to generate a series of user-friendly reports. RESULTS:As proof of concept for the program, four FASTA genome sequence samples of human chromosome X (AC_000155.1, CM000685.1, NC_018934.2, and CM000274.1) were obtained from GenBank and were analyzed for the presence of putative STR regions. The sequences within AC-000155.1 were used as an initial reference sequence from which there were 5443 identical and 4305 polymorphic STR loci identified using a repeat unit of 1-6 and 10 bp as the flanking sequence either side of the putative STR loci. A reliability test was used to compare five FASTA samples, which had sections of DNA sequence removed to mimic partial or fragmented DNA sequences, to determine whether pSTR Finder can efficiently and consistently find identical, polymorphic, and different STR loci. CONCLUSIONS:From the mass of DNA sequence data, the project was found to reproducibly identify polymorphic STR loci and generate user-friendly reports detailing the number and location of these potential polymorphic loci. This freely available program was found to be a useful tool to find polymorphic STR within whole-genome sequence data in forensic genetic studies.

Dataset Information

STR-realigner: a realignment method for short tandem repeat regions.

Publications

STR-realigner: a realignment method for short tandem repeat regions.

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