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Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
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STR-realigner: a realignment method for short tandem repeat regions.

Kaname Kojima1, Yosuke Kawai1, Kazuharu Misawa1

  • 1Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.

BMC Genomics
|December 4, 2016
PubMed
Summary
This summary is machine-generated.

Accurate short tandem repeat (STR) number estimation from sequencing data is challenging. STR-realigner, a novel dynamic programming method, improves STR region size accuracy by considering repeat patterns, outperforming existing tools in simulations and real-world data analysis.

Keywords:
AlignmentHigh-throughput sequencingShort tandem repeat

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Estimating repeat numbers in short tandem repeat (STR) regions from high-throughput sequencing data is crucial for genetic analysis.
  • Traditional alignment methods struggle with STR regions due to high variability, insertions, and deletions, impacting repeat number accuracy.
  • Current strategies rely on read alignment or insert size estimation, both sensitive to alignment quality in repetitive regions.

Purpose of the Study:

  • To develop and evaluate STR-realigner, a novel dynamic programming-based realignment method for accurate STR region size estimation.
  • To improve the accuracy of short tandem repeat (STR) variant calling by addressing alignment challenges in repetitive genomic regions.
  • To assess the performance of STR-realigner against existing tools using both simulated and real sequencing data.

Main Methods:

  • Proposed STR-realigner, a dynamic programming algorithm incorporating repeat patterns as prior knowledge for realignment in STR regions.
  • Allowed for low-penalty size changes in repeat patterns within STR regions to accommodate variations.
  • Evaluated performance using publicly available STR variant calling tools on datasets realigned with STR-realigner, BWA-MEM, ReviSTER, and GATK IndelRealigner.

Main Results:

  • STR-realigner demonstrated superior performance in estimating STR region sizes, achieving lower root mean squared errors compared to other methods on simulated data.
  • Analysis of a parent-offspring trio dataset showed STR-realigner provided the most consistent STR region size estimates, adhering to Mendelian inheritance patterns.
  • Comparison with high-coverage PacBio sequencing data confirmed that STR-realigner achieved the lowest root mean squared error for real sequencing data.

Conclusions:

  • The effectiveness of STR-realigner for improving short tandem repeat (STR) analysis was validated through comprehensive comparisons on both simulated and real whole-genome sequencing datasets.
  • STR-realigner offers a significant advancement in accurately determining STR repeat numbers, crucial for genetic variation studies.
  • The proposed method enhances the reliability of STR variant calling by providing more accurate sequence alignments in challenging repetitive regions.