Optimizing microbial community metagenomic hybrid assembly correction and polishing approaches informed by reference-independent analyses

Abstract

AbstractHybrid metagenomic assembly, leveraging both long- and short-read sequencing technologies, of microbial communities is becoming an increasingly accessible approach yet offers challenges that existing benchmarks and pipelines do not comprehensively handle well. One specific methodological knowledge gap is selecting the ideal number of iterations of long read correction and/or short read polishing, and in particular which the features of an assembly to examine to empirically determine them. To account for biological and technological variation, in this study the microbial communities of two laboratory-scale bioreactors were sequenced with both short and long read platforms and assembled with two different, commonly used software packages. Following assembly, long read error correction was iterated ten times, with subsequent ten rounds of short read polishing after common (0 and 2) and extensive (5 and 10) correction iterations. Several assembly characteristics were tracked for each assembly and iteration of correction and polishing: gene fragmentation, short read recruitment, automated binning yields, as well as observed beta-diversity. While long read correction was necessary, the greatest improvements occurred within the first few iterations of short read polishing, and extensive correction and polishing did not tangibly improve assembly quality. Furthermore, essentially all tracked characteristics followed the same patterns; simpler statistics can serve as decent proxies for more complex analyses to save computational resources assessing assembly quality. Hybrid sequencing approaches will likely remain relevant due to the low costs of short read sequencing, therefore it is imperative users are equipped to estimate assembly quality prior to downstream gene- and genome-centric analyses.