Repetitive DNA and next-generation sequencing: computational challenges and solutions

By Todd J. Treangen, Steven L. Salzberg. Nature reviews genetics, 2011

1,724 citations recorded by the source corpus.

Repetitive DNA sequences are abundant in a broad range of species, from bacteria to mammals, and they cover nearly half of the human genome. Repeats have always presented technical challenges for sequence alignment and assembly programs. Next-generation sequencing projects, with their short read lengths and high data volumes, have made these challenges more difficult. From a computational perspective, repeats create ambiguities in alignment and assembly, which, in turn, can produce biases and errors when interpreting results. Simply ignoring repeats is not an option, as this creates problems of its own and may mean that important biological phenomena are missed. We discuss the computational problems surrounding repeats and describe strategies used by current bioinformatics systems to solve them.

Subfields: Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/2501576dc02c6ca1504b045885eb1cec8d4d3f16

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

In Plant Science

Citations in the corpus

A protocol for RNA methylation differential analysis with MeRIP-Seq data and exomePeak R/Bioconductor package. (2014, background): “As in many other NGS based techniques, an important issue is how to best deal with the widespread repetitive elements [13] in a broad range of species (around 50% of the human genome) that can lead to multi-reads (reads that could be mapped to multiple genomic locations) and the mapping ambiguities ”
Current challenges and best-practice protocols for microbiome analysis (2019, background): “computational resources for high-volume data (Figure 2) [65, 66].”
lobSTR: A short tandem repeat profiler for personal genomes (2012, background): “Despite the plurality of applications, STR variations are not routinely analyzed in whole-genome sequencing studies, mainly due to a lack of adequate tools (Treangen and Salzberg 2011).”
Completing bacterial genome assemblies with multiplex MinION sequencing (2017, background): “Polishing an assembly relies on read alignment, but short reads can suffer from non-specific alignment in repeat regions [30].”
Memory scaling: A systems architecture perspective (2013, background): “For example, next-generation genome sequencing technologies produce massive amounts of sequence data that overwhelms memory storage and bandwidth requirements of today’s high-end desktop and laptop systems [71, 3, 74] yet researchers have the goal of enabling low-cost personalized medicine.”
Improved data analysis for the MinION nanopore sequencer (2015, background): “The high level of homology between adjacent copies (95%–100% sequence identity) is likely to result in recombination or replication errors, leading to alleles with different numbers of repeats that are often difficult to represent accurately by standard short-read assembly 17 .”
RNA Sequencing Data: Hitchhiker's Guide to Expression Analysis (2018, background): “1000 Long Read Transcriptome Sequencing The short read length of Illuminabased RNAseq complicates unambiguous placement of reads to the genome, especially in repeat regions [198] , and adds difficulties to the assembly, identification and quantification of expressed isoforms [199–201] .”
GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly (2017, methodology): “Whilst most tools consider only the best alignment for each read, some methods [11, 16] consider multiple potential alignment locations to better handle repetitive sequence [17].”
SNP Discovery through Next-Generation Sequencing and Its Applications (2012, methodology): “The presence of repeat elements, paralogs, and incomplete or inaccurate reference genome sequences can create ambi-guities in SNP calling [63].”
Big Data Analytics in Healthcare (2015, background): “The advent of high-throughput sequencing methods has enabled researchers to study genetic markers over a wide range of population [22, 128], improve efficiency by more than five orders of magnitude since sequencing of the human genome was completed [129], and associate genetic causes of the phenotyp”