Alignment-free Transcriptomic and Metatranscriptomic Comparison Using Sequencing Signatures with Variable Length Markov Chains

Abstract

The comparison between microbial sequencing data is critical to understand the dynamics of microbial communities. The alignment-based tools analyzing metagenomic datasets require reference sequences and read alignments. The available alignment-free dissimilarity approaches model the background sequences with Fixed Order Markov Chain (FOMC) yielding promising results for the comparison of microbial communities. However, in FOMC, the number of parameters grows exponentially with the increase of the order of Markov Chain (MC). Under a fixed high order of MC, the parameters might not be accurately estimated owing to the limitation of sequencing depth. In our study, we investigate an alternative to FOMC to model background sequences with the data-driven Variable Length Markov Chain (VLMC) in metatranscriptomic data. The VLMC originally designed for long sequences was extended to apply to high-throughput sequencing reads and the strategies to estimate the corresponding parameters were developed. The flexible number of parameters in VLMC avoids estimating the vast number of parameters of high-order MC under limited sequencing depth. Different from the manual selection in FOMC, VLMC determines the MC order adaptively. Several beta diversity measures based on VLMC were applied to compare the bacterial RNA-Seq and metatranscriptomic datasets. Experiments show that VLMC outperforms FOMC to model the background sequences in transcriptomic and metatranscriptomic samples. A software pipeline is available at https://d2vlmc.codeplex.com.

Tomato RNA-seq Data Mining Reveals the Taxonomic and Functional Diversity of Root-Associated Microbiota

“…Despite the low sequencing coverage of microbial transcripts, the deep mining of transcriptome datasets we previously generated from tomato plants grown in non-sterile environments [11] allowed the identification of a number of active microbes associated with roots. Our data demonstrate that this approach is feasible even with a high abundance of host sequences (>90%) and a short read length (50 bp), even though the number of microbial reads (excluding rRNAs) harvested was considerably lower than was obtained in other meta-transcriptome studies [57,58]. Notwithstanding these technical constraints, we were able to reconstruct the active microbiota and functional diversity as reported in other works [43].…”

FASTCAR: Rapid alignment-free prediction of sequence alignment identity scores using self-supervised general linear models

“…Almost all of the speed-ups are based on heuristics methods. This shortcoming of alignment algorithms has led the field to develop plenty of faster, alignment-free methods (Blaisdell, 1986;Zharkikh and Rzhetsky, 1993;Wu et al, 2001;Almeida and Vinga, 2002;Lippert et al, 2002;Pham and Zuegg, 2004;Kantorovitz et al, 2007;Dai et al, 2008;Reinert et al, 2010;Sims et al, 2009;Costa et al, 2011;Liu et al, 2011;Zhang and Chen, 2011;Göke et al, 2012;Ren et al, 2013;Ghandi et al, 2014;Haubold, 2014;Leimeister et al, 2014;Pinello et al, 2014;Borozan et al, 2015;Liao et al, 2016). Multiple reviews of alignment-free methods have been published (Vinga and Almeida, 2003;Vinga et al, 2012;Bonham-Carter et al, 2014;Song et al, 2014;Vinga, 2014;Chattopadhyay et al, 2015;Luczak et al, 2017;Zielezinski et al, 2017), indicating the importance and the abundance of such methods.…”

MeShClust2: Application of alignment-free identity scores in clustering long DNA sequences

“…Specialized sequence clustering tools have been developed for error reduction in reads produced by modern sequencing technologies [3][4][5][6] , redundancy detection 7 , finding representative sequences 8 , taxonomic profiling 9 , de-novo genome assembly [10][11][12] , and grouping expressed sequence tags 13 . Additionally, general purpose sequence clustering tools including MeShClust 14 , CD-HIT 5,15 , UCLUST 16 , DNACLUST 9 , d2_cluster 17 , mBKM 18 , and d2-vlmc 19 have shown great applicability to many problems.…”