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Journals / Turkish Journal of Biology / 2018 / Cilt: 42 - Sayı: 6

Evaluation of genome scaffolding tools using pooled clone sequencing

Can ALKAN
Elif DAL
Pages
471–476
Publication Date
2022-10-17
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

However, the current scaffolding algorithms are developed only for WGS, and PCS-awarescaffolding algorithms remain an open problem.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:DNA sequencing technologies hold great promise in generating information that will guide scientists to understand howthe genome affects human health and organismal evolution.
📊
Key Findings & Data:Manygenome assembly tools are available, but they differ in terms of their performance and their final output.
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Conclusion & Impact:However, the current scaffolding algorithms are developed only for WGS, and PCS-awarescaffolding algorithms remain an open problem.
🔬Design:Lab & Field Experiment
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

DNA sequencing technologies hold great promise in generating information that will guide scientists to understand howthe genome affects human health and organismal evolution. The process of generating raw genome sequence data becomes cheaperand faster, but more error-prone. Assembly of such data into high-quality finished genome sequences remains challenging. Manygenome assembly tools are available, but they differ in terms of their performance and their final output. More importantly, it remainslargely unclear how to best assess the quality of assembled genome sequences. Here we evaluate the accuracies of several genomescaffolding algorithms using two different types of data generated from the genome of the same human individual: whole genomeshotgun sequencing (WGS) and pooled clone sequencing (PCS). We observe that it is possible to obtain better assemblies if PCS dataare used, compared to using only WGS data. However, the current scaffolding algorithms are developed only for WGS, and PCS-awarescaffolding algorithms remain an open problem.

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Cite This Article

ALKAN, C., DAL, E. (2022). Evaluation of genome scaffolding tools using pooled clone sequencing. Turkish Journal of Biology, Cilt: 42 - Sayı: 6, 471–476. https://ajindex.com/articles/600247

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References (14)

  1. Batzoglou S, Jaffe DB, Stanley K, Butler J, Gnerre S, Mauceli E, Berger B, Mesirov JP, Lander, E (2002). ARACHNE: A whole-genome shotgun assembler. Genome Res 12: 177-189.
  2. Boetzer M, Henkel CV, Jansen HJ, Butler D, Pirovano, W (2011). Scaffolding pre-assembled contigs using SSPACE. Bioinformatics 27: 578-579.
  3. Chaisson M, Pevzner P, Tang H (2004). Fragment assembly with short reads. Bioinformatics 20: 2067-2074.
  4. Donmez N, Brudno M (2013). SCARPA: scaffolding reads with practical algorithms. Bioinformatics 29: 428-434.
  5. ENCODE Project Consortium (2012). An integrated encyclopedia of DNA elements in the human genome. Nature 489: 57-74.
  6. Eslami Rasekh M, Chiatante G, Miroballo M, Tang J, Ventura M, Amemiya CT, Eichler EE, Antonacci F, Alkan C (2017). Discovery of large genomic inversions using long range information. BMC Genomics 18: 65. Gao S, Sung WK, Nagarajan N (2011). Opera: reconstructing optimal genomic scaffolds with high-throughput paired-end sequences. J Comput Biol 18: 1681-1691.
  7. Gnerre S, Maccallum I, Przybylski D, Ribeiro FJ, Burton JN, Walker BJ, Sharpe T, Hall G, Shea TP, Sykes S et al (2011). High-quality draft assemblies of mammalian genomes from massively parallel sequence data. P Natl Acad Sci USA 108: 1513-1518.
  8. Hunt M, Newbold C, Berriman M, Otto TD (2014). A comprehensive evaluation of assembly scaffolding tools. Genome Biology 15: R42. International Human Genome Sequencing Consortium (2004). Finishing the euchromatic sequence of the human genome. Nature 431: 931-945.
  9. Kececioglu JD, Myers EW (1995). Combinatorial algorithms for DNA sequence assembly. Algorithmica 13: 7. Kitzman JO, Mackenzie AP, Adey A, Hiatt JB, Patwardhan RP, Sudmant PH, Ng SB, Alkan C, Qiu R, Eichler EE et al (2011). Haplotype-resolved genome sequencing of a Gujarati Indian individual. Nat Biotechnol 29: 59-63.
  10. Mardis ER (2008). The impact of next-generation sequencing technology on genetics. Trends Genet 24: 133-141.
  11. Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS, Chen YJ, Chen Z et al (2005). Genome sequencing in microfabricated high-density picolitre reactors. Nature 437: 376-380.
  12. Mostovoy Y, Levy-Sakin M, Lam J, Lam ET, Hastie AR, Marks P, Lee J, Chu C, Lin C, Džakula Ž et al (2016). A hybrid approach for de novo human genome sequence assembly and phasing. Nat Methods 13: 587-590.
  13. Mullikin JC, Ning Z (2003). The phusion assembler. Genome Res 13: 81-90.
  14. Sahlin K, Vezzi F, Nystedt B, Lundeberg J, Arvestad L (2014). BESST– efficie