Enzymes present a sustainable alternative to traditional chemical industries, drug synthesis, and bioremediation applications. Because catalytic residues are the key amino acids that drive enzyme func...

Background Whole metagenome shotgun sequencing (WMS) is widely used to profile microbial function. However, technical variability in sequencing and analysis often obscures true biological patterns. Large-scale studies are particularly susceptible to batch effects, such as differences in sequencing depth and platform and annotation strategies, as well as sample-to-flow-cell assignments. However, the relative effects of these factors on functional inference in such studies have yet to be systematically evaluated. We analyzed oral-rinse WMS data from a study cohort including 671 Nigerian youths aged 9-18, sequenced on two Illumina platforms. Microbial molecular functionality encoded in these data were annotated using the mi-faser/Fusion pipeline, to capture the broad functional repertoire, and HUMAnN 3/EC numbers pipeline to characterize curated enzymatic activities. We then quantified how technical factors and batch effects shaped the recovery of microbial functionality. Results Three findings of our work were most salient. First, we observed that the choice of annotation strategy traded off between breadth and specificity of functional coverage. Second, we found that low-prevalence functions were disproportionately lost at shallow sequencing depths, indicating that in e.g. case-control studies with few representatives of the minor class, sequencing depth could critically impact study resolution. Finally, using our newly developed model relating sequencing depth to functional recovery, we demonstrated that increasing sequencing depth does not directly or proportionally improve functional recall. That is, at as little as 10% of this study’s sequencing depth, 30% of the estimated complete microbiome functional repertoire was detectable. However, even at the full depth used in this study, we were only able to recover an estimated 60% of that complete functional repertoire. Conclusions Together, these findings and our depth-to-function mapping framework provide practical guidelines for the design and interpretation of WMS studies. Coordinating sequencing depth planning with annotation strategy, experimental design, and rigorous batch control is thus essential for robust detection of microbial functions and for ensuring reproducible microbiome insights. ### Competing Interest Statement Dr. Osazuwa-Peters was a scientific advisor to Navigating Cancer and has received consulting fees from Merck for consultation on HPV vaccination. National Institute of Dental and Craniofacial Research, R01-DE032216

With more eukaryotic genomes available for study researchers have been able to identify a growing number of horizontal gene transfer (HGT) candidates. We compiled 9,511 protein coding genes that were ...

Given the sequence of a protein, the Gene Neighbourhood Analysis Tool (GNAT) identifies homologues within microbial (bacterial, archaeal, or fungal) or viral databases, aligns and clusters their genom...

Motivation Long-Read Sequencing (LRS) promises great improvements in the detection of structural genome variants (SVs). However, existing methods are lacking in key areas such as the reliable detectio...

Although existing next-generation sequencing (NGS) tools, such as Aldy and Cyrius, have been applied for allele typing, they cannot achieve complete accuracy due to various genomic challenges includin...

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Fluorescent in situ sequencing involves imaging-based sequencing by synthesis in intact cells or tissues to reveal target nucleotide sequences inside each cell. Often, the target sequences are barcode...

### Competing Interest Statement The authors have declared no competing interest.

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RNA-seq data analysis relies on many different tools, each tailored to specific applications and coming with unique assumptions and limitations. Indeed, tools for differential transcript usage or rare...

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