Assembly of large genomes using second-generation sequencing.

By Michael C. Schatz, Arthur L. Delcher, Steven L. Salzberg. Genome Research, 2010

511 citations recorded by the source corpus.

Subfields: Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/c1430697669694b8a09c7fb100b08c0681b33adb

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Citations in the corpus

GAGE: A critical evaluation of genome assemblies and assembly algorithms. (2012, background): “ness (Schatz et al. 2010), defined as the percentage of a genome that is covered by unique sequences of lengthK.”
Generations of Sequencing Technologies: From First to Next Generation (2017, unknown): “We distinguish the second generation sequencing technologies which refer to the newest sequencing technologies developed in the NGS environment after the first generation [11,12], they are characterized by the need to prepare amplified sequencing banks before starting the sequencing of amplified DNA”
Hybrid error correction and de novo assembly of single-molecule sequencing reads (2012, unknown): “A comparison of the literature shows that a 10–20× Sanger assembly is better than a 100× Illumina assembly, albeit with prohibitively greater sequencing costs using the older technology 19,23 .”
The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes (2014, background): “This has made it very affordable to sequence, yet extremely challenging to produce finished genomes [47,48].”
Assembling large genomes with single-molecule sequencing and locality-sensitive hashing (2014, unknown): “J S!, S! = ! !(!!) ! !(!!) !! = ! !!!! (6)”
Progress towards a reference genome for sunflower (2011, methodology): “…sunflower genome is very large with abundant repetitive sequences (Cavallini et al. 2009), so an approach based exclusively on whole-genome shotgun (WGS) of second-generation sequence data is unlikely to reliably link, order, and orient sequenced contigs (Rounsley et al. 2009; Schatz et al. 2010).”
Repetitive DNA and next-generation sequencing: computational challenges and solutions (2011, result): “This fact, coupled with the short length of NGS sequences, means that most recent genome assemblies are much more fragmented than assemblies from a few years ago, as evidenced by recent surveys 48,49 .”
Bandage: interactive visualization of de novo genome assemblies (2015, background): “The longest sequences in the graph that can be determined unambiguously are saved as contigs, which are often the final result of de novo assembly (Schatz et al ., 2010).”
Genome structural variation discovery and genotyping (2011, background): “5% of the human genome cannot be covered uniquely even with read lengths of 1 k”
A fast, lock-free approach for efficient parallel counting of occurrences of k-mers (2011, methodology): “Recent sequencing techniques, using shorter reads with a much deeper coverage (Schatz et al., 2010), generate large amounts of sequence and provide with a major challenge for genome assembly and for k-mer counting.”
Why are de Bruijn graphs useful for genome assembly? (2011, unknown): “8.”
A window into third-generation sequencing. (2010, background): “While reasonable assemblies are now feasible using state-of-the-art SGS technologies and algorithms, they are still not capable of achieving the assembly qualities that can be achieved using first-generation Sanger sequencing, with hybrid sequencing approaches that include data generated from multip”
The Genome 10K Project: A Way Forward (2015, unknown): “Rodents (2277, 17) Rabbits, pikas (91, 2) Tree shrews (20, 2) Colugos (2, 1) Primates (376, 18) Tachyglossidae Ornithorhynchidae”
Limitations of next-generation genome sequence assembly (2010, background): “Criticisms of WGS assembly algorithms and characterization of various types of errors associated with them as well as requirements for better assemblies have been previously discusse”
Scaling accurate genetic variant discovery to tens of thousands of samples (2017, methodology): “The four basic steps of variant calling with the HC-RCM including identiﬁcation of the ActiveRegions, assembly of candidate haplotypes using de Bruijn-like graphs, determination of the per-read likelihoods of candidate haplotypes using a pair-HMM, and genotype assignment. widely used tools and that ”