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Manoharan, L.

Publications and source records attributed to Manoharan, L..

3 recordsLinked to original sources

HAPP: High-Accuracy Pipeline for Processing deep metabarcoding data

We introduce HAPP, a high-accuracy pipeline for processing deep metabarcoding data, leveraging data richness to enhance the signal-to-noise-ratio. Starting with denoised amplicon sequence variants, the pipeline consists of four steps: (1) additional chimera removal, using UCHIME and a strict sample-based approach; (2) taxonomic annotation, combining k-mer matching (SINTAX) to a reference library with phylogenetic placement (EPA-NG) on a reference tree; (3) OTU clustering using SWARM, an open-source algorithm with precision and recall comparable to RESL used in circumscribing BOLD BINs; and (4) noise filtering (NUMTs and sequencing errors), using a new algorithm introduced here, NEEAT, which combines "echo" signals across samples with detection of unusual evolutionary signatures among clusters with similar DNA sequences. HAPP computations are parallelized across taxa, making analyses tractable on very large datasets. The performance of HAPP was validated through extensive benchmarks, involving CO1 data from BOLD and Malaise trap data, demonstrating significant improvements over the state of the art.

bioinformatics↗

Data of the Insect Biome Atlas: a metabarcoding survey of the terrestrial arthropods of Sweden and Madagascar

We present the data from the Insect Biome Atlas project (IBA), characterizing the terrestrial arthropod faunas of Sweden and Madagascar. Over 12 months, weekly Malaise trap samples were collected at 203 locations within 100 sites in Sweden and at 50 locations within 33 sites in Madagascar; this was complemented by soil and litter samples from each site. The field samples comprise 4,749 Malaise trap, 192 soil and 192 litter samples from Sweden and 2,566 Malaise trap and 190 litter samples from Madagascar. Samples were processed using mild lysis or homogenization, followed by DNA metabarcoding of COI (418 bp). The data comprise 698,378 non-chimeric sequence variants from Sweden and 687,866 from Madagascar, representing 33,989 (33,046 Arthropoda) and 77,599 (77,380 Arthropoda) operational taxonomic units, respectively. These are the most comprehensive data presented on these faunas so far, allowing unique analyses of the size, composition, spatial turnover and seasonal dynamics of the sampled communities. They also provide an invaluable baseline against which to gauge future changes.

ecology↗

Targeted metagenomics using probe capture detects a larger diversity of nitrogen and methane cycling genes in complex microbial communities than traditional metagenomics

Microorganisms are key players in the global cycling of nitrogen (N) and carbon (C), controlling their availability and fluxes, including the emissions of the powerful greenhouse gases nitrous oxide (N2O) and methane (CH4). Characterizing the microbial functional guilds driving these processes is crucial for understanding ecosystem functioning and predicting their responses to environmental changes. Standard sequence-based characterization methods often reveal only a limited fraction of their diversity in nature because of their low relative abundance, the insufficient sequencing depth of traditional metagenomes of complex communities, and limitations in coverage of PCR-based assays. Here, we developed and tested a targeted metagenomics approach based on probe capture and hybridization to simultaneously characterize the diversity of multiple key metabolic genes involved in inorganic N and CH4 cycling. We designed comprehensive probe libraries for each of the 14 target marker genes comprising 264,000 unique probes. These probes were used to selectively enrich the target genes in shotgun metagenomic libraries. In validation experiments with the mock communities of known microorganisms, targeted metagenomics yielded gene profiles similar to those of the original communities. Only GC content had a small effect on probe efficiency, as low GC targets were less efficiently detected than those with high GC, within the mock communities. Furthermore, the relative abundances of the marker genes obtained using targeted or traditional shotgun metagenomics from agricultural and wetland soils were significantly correlated, indicating that the targeted approach did not introduce significant quantitative bias. In addition, using archaeal amoA genes as a case-study, targeted metagenomics identified substantially higher taxonomic diversity and a larger number of sequence reads per sample, yielding diversity estimates 28 or 1.24 times higher than shotgun metagenomics or amplicon sequencing, respectively. Notably, shotgun metagenomics detected only three out of the 84 amoA gene phylotypes detected using targeted metagenomics. Our results show that targeted metagenomics complements current approaches to characterize key microbial populations and functional guilds in biogeochemical cycles in different ecosystems, enabling more detailed, simultaneous characterization of multiple functional genes. Manuscript contribution to the fieldMetagenomic sequencing often yields limited numbers of sequences of rare microbial taxa or functional genes, preventing in-depth analyses of specific populations and functional groups. Amplicon-based approaches enable the higher diversity coverage of target populations, but the drawback is the difficulty in designing unbiased primers that cover the highest intra-group diversity. Targeted metagenomics overcomes these challenges and results in similar community structure as traditional amplicon sequencing, while expanding the sequence space in a less biased metagenomic-based approach. Therefore, targeted metagenomics is an invaluable tool for studying the diversity of specific populations within complex natural microbiomes. Here, we present and evaluate a probe library designed for targeted metagenomics of nitrogen and methane cycling genes in complex communities.

microbiology↗