Pre- and post-sequencing recommendations for functional annotation of human fecal metagenomes

Abstract

BackgroundShotgun metagenomes are often assembled prior to annotation of genes which biases the functional capacity of a community towards its most abundant members. For an unbiased assessment of community function, short reads need to be mapped directly to a gene or protein database. The ability to detect genes in short read sequences is dependent on pre-and postsequencing decisions. The objective of the current study was to determine how library size selection, read length and format, protein database, e-value threshold, and sequencing depth impact gene-centric analysis of human fecal microbiomes when using DIAMOND, an alignment tool that is up to 20,000 times faster than BLASTX. ResultsUsing metagenomes simulated from a database of experimentally verified protein sequences, we find that read length, e-value threshold, and the choice of protein database dramatically impact detection of a known target, with best performance achieved with longer reads, stricter e-value thresholds, and a custom database. Using publicly available metagenomes, we evaluated library size selection, paired end read strategy, and sequencing depth. Longer read lengths were acheivable by merging paired ends when the sequencing library was size-selected to enable overlaps. When paired ends could not be merged, a congruent strategy in which both ends are independently mapped was acceptable. Sequencing depths of 5 million merged reads minimized the error of abundance estimates of specific target genes, including an antimicrobial resistance gene. ConclusionsShotgun metagenomes of DNA extracted from human fecal samples sequenced using the Illumina platform should be size-selected to enable merging of paired end reads and should be sequenced in the PE150 format with a minimum sequencing depth of 5 million merge-able reads to enable detection of specific target genes. Expecting the merged reads to be 180-250bp in length, the appropriate e-value threshold for DIAMOND would then need to be more strict than the default. Accurate and interpretable results for specific hypotheses will be best obtained using small databases customized for the research question.

Ectomycorrhizal access to organic nitrogen mediates CO2 fertilization response in a dominant temperate tree

“…S12). Next, we used a direct mapping approach to annotate remaining sequences against the CAZy and Peroxibase reference databases (100 total gene families; Table S2) using 'sensitive' DIAMOND (v. 0.9.29) 90 and BWA-MEM (v.0.7.17) 91 respectively, following best practice for unmerged reads 92 . The compiled decay gene database primarily contained 'core' gene families found to be actively expressed during fungal decay of SOM and microbial biomass 93,94 (CAZy: http://www.cazy.org; http://peroxibase.toulouse.inra.fr/), and is hereafter referred to as the 'CAZy database' (Table S2).…”

Ectomycorrhizal fungal decay traits along a soil nitrogen gradient

“…On average, 21.7% of sequences per sample were removed during this filtering step, yielding a mean of 307 041 274 putative fungal sequences per sample. Next, we used a direct mapping approach to annotate sequences against the CAZy and Peroxibase reference databases (100 total gene families; Table S1) using the 'sensitive' setting in DIAMOND (v.0.9.29) with an Àe value of 1e À4 (Buchfink et al, 2015) and BWA-MEM (v.0.7.17) with standard settings (Li & Durbin, 2009), following recommendations for unmerged reads (Treiber et al, 2020). The compiled gene database primarily contained previously defined 'core' gene families found to be actively expressed during fungal decay of SOM (Peng et al, 2018;Floudas et al, 2020; CAZy: http://www.cazy.org; http://peroxibase.toulouse.…”

“…Ectomycorrhizal (ECM) fungi, in particular, dominate boreal and temperate forest soil microbial communities, providing plant hosts with the majority of their annual nitrogen (N) requirements (c. 70%) (Smith & Read, 2010). Despite being one of the most studied microbial groups, understanding of the distribution of ECM fungal traits remain poorly understood (Courty et al, 2016;van der Linde et al, 2018;Meeds et al, 2021). One prominent ECM fungal functional trait is the acquisition of N bound in soil organic matter (N-SOM), which constitutes the majority of soil N (Vitousek & Howarth, 1991).…”

“…Studies at local, regional, and continental scales consistently identify soil inorganic N availability as a key determinant of ECM fungal community composition (Taylor et al, 2000;Lilleskov et al, 2002a;Peay et al, 2015;van der Linde et al, 2018). Biological market perspectives provide insight into how N availability and fungal N acquisition traits may interact to structure these communities (Koide et al, 2014;Christian & Bever, 2018).…”

“…We identified linkages between 100 individual gene families and soil inorganic N availability using an extension of indicator species (gene) analysis (Baker & King, 2010). Our use of a single and even-aged host (c. 100 yr old) eliminates the potentially confounding effect of host specificity and ontogeny in fungal community assembly (van der Linde et al, 2018;Wasyliw & Karst, 2020).…”