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Microbial Genome-wide Association Studies (mGWAS) Service

Microbial Genome-wide Association Studies (mGWAS) Service

Overview

Microbial Genome-Wide Association Studies (mGWAS) is a new area of research that identifies genetic variation in microbial genomes associated with host variation or microbial phenotypes. CD Genomics is dedicated to genomic and population genetic analysis, and we use our experience in GWAS to help our clients understand how variation in microbial genomes affects host or pathogen phenotypes, such as drug resistance, virulence, host specificity, and prognosis.

Our Advantages

Professional, comprehensive and customized analysis process
State-of-the-art sequencing platforms, including NGS and long-read sequencing
Years of experience in biomarker discovery and microbial interactions
Well-established workflow for interpreting GWAS results

Tell Us About Your Project

We are dedicated to providing outstanding customer service and being reachable at all times.

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End-to-end solution for your microbial GWAS research

The microbiome has emerged as an important non-genetic component influencing host phenotype and its impact on the host may go beyond the analysis of host genetics. Microbial Genome-Wide Association Studies (mGWAS) allows revealing the characteristics and mutations of microbiota associated with the host. mGWAS utilizes and develops human GWAS research methods to resolve the interactions and associations between variation (such as single nucleotide polymorphisms (SNP) and INDEL, gene presence-absence, copy number variation (CNV) and sequence inversions (SI)) and phenotypes in the microbial genome with the host and environment.

Our mGWAS service offers many great benefits and conveniences, such as a high-throughput bioinformatics pipeline and established reference database, as well as providing sequencing control at a cost per sample. The use of this strategy demonstrates a significantly different characterization of the microbiota and greatly deepens our understanding of its role in various body regions of human health and disease.

mGWAS Workflow

Microbial Genome-wide Association Studies (mGWAS) Service

Our high-throughput mGWAS service can be used to advance

Investigation of the relationship between host genotypes and identified pathways and individual differences in microbiome composition
Investigation of host-microbe interactions
Correlation studies between disease states and microbiome composition
Investigation of the role of the microbiome in host traits, disease susceptibility and resistance, and treatment response

Bioinformatic Analysis

ANALYSIS CONTENTS	DETAILS
Variant calling, evaluation and annotation	SNPs are called using HaplotypeCaller and filtered using VariantFiltration with parameter.
Enrichment of Gene Ontology (GO) term and KEGG pathway	Enrichment of Gene Ontology (GO) term and KEGG pathway are performed for candidate genes according to EnrichmentPipeline.
Definition of abundant and rare microbial OTUs	Briefly, the OTUs with relative abundances ≥0.1% across more than 50% of samples were defined as abundant OTUs (AT), whereas the OTUs with relative abundances <0.01% across more than 30% of samples but never abundant (≥0.1%) more than 30% samples were defined as rare OTUs (RT).
The microbial co-occurrence network analysis	Evaluation of correlation between host phylogenetic distance and target microbiota distance

Sample Requirements

Specimens from human, animal, natural and industrial environments, as well as DNA and PCR products.
1. 1.8 < OD260/280 < 2.0, OD260/230 ≥ 1.8, no degradation or contamination.
2. Illumina platform: prokaryotic/eukaryotic DNA/cDNA amount ≥ 2 μg, viral DNA/cDNA amount ≥ 1 ug
3. PacBio platform: bacterial DNA amount ≥ 5 μg, fungal DNA amount ≥ 10 μg

Deliverables: Raw sequencing data (FASTQ), trimmed and stitched sequences, quality-control dashboard, statistic data, and your designated bioinformatics report.

Reference

San J E, Baichoo S, Kanzi A, et al. Current affairs of microbial genome-wide association studies: approaches, bottlenecks and analytical pitfalls. Frontiers in microbiology, 2020, 10: 3119.