RT Journal Article
SR Electronic
T1 Comparison of the two up-to-date sequencing technologies for genome assembly: HiFi reads of Pacbio Sequel II system and ultralong reads of Oxford Nanopore
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.02.13.948489
DO 10.1101/2020.02.13.948489
A1 Dandan Lang
A1 Shilai Zhang
A1 Pingping Ren
A1 Fan Liang
A1 Zongyi Sun
A1 Guanliang Meng
A1 Yuntao Tan
A1 Jiang Hu
A1 Xiaokang Li
A1 Qihua Lai
A1 Lingling Han
A1 Depeng Wang
A1 Fengyi Hu
A1 Wen Wang
A1 Shanlin Liu
YR 2020
UL http://biorxiv.org/content/early/2020/02/14/2020.02.13.948489.abstract
AB The availability of reference genomes has revolutionized the study of biology. Multiple competing technologies have been developed to improve the quality and robustness of genome assemblies during the last decade. The two widely-used long read sequencing providers – Pacbio (PB) and Oxford Nanopore Technologies (ONT) – have recently updated their platforms: PB enable high throughput HiFi reads with base-level resolution with >99% and ONT generated reads as long as 2 Mb. We applied the two up-to-date platforms to one single rice individual, and then compared the two assemblies to investigate the advantages and limitations of each. The results showed that ONT ultralong reads delivered higher contiguity producing a total of 18 contigs of which 10 were assembled into a single chromosome compared to that of 394 contigs and three chromosome-level contigs for the PB assembly. The ONT ultralong reads also prevented assembly errors caused by long repetitive regions for which we observed a total 44 genes of false redundancies and 10 genes of false losses in the PB assembly leading to over/under-estimations of the gene families in those long repetitive regions. We also noted that the PB HiFi reads generated assemblies with considerably less errors at the level of single nucleotide and small InDels than that of the ONT assembly which generated an average 1.06 errors per Kb assembly and finally engendered 1,475 incorrect gene annotations via altered or truncated protein predictions.