What is the primary advantage of shotgun metagenomics over 16S rRNA amplicon sequencing?
AShotgun metagenomics is cheaper per sample
BShotgun metagenomics provides both taxonomic and functional information from all organisms, not just bacteria
CShotgun metagenomics requires no computational analysis
DShotgun metagenomics uses longer reads
16S amplicon sequencing targets a single bacterial/archaeal marker gene, providing taxonomic composition but no functional information and missing eukaryotes and viruses entirely. Shotgun metagenomics sequences all DNA in the sample, enabling identification of all organisms (bacteria, archaea, fungi, viruses), functional profiling of the community's metabolic potential (what genes and pathways are present), and even assembly of individual genomes from the mixture. The tradeoff is higher cost and greater computational complexity.
Question 2 True / False
Metagenome-assembled genomes (MAGs) are always complete, contiguous genomes equivalent to those produced by single-organism sequencing.
TTrue
FFalse
Answer: False
MAGs are reconstructed by binning contigs from a metagenomic assembly based on composition (GC content, tetranucleotide frequency) and coverage patterns across samples. They are typically incomplete (missing some genes), fragmented (many contigs rather than closed chromosomes), and may contain contamination from other organisms' DNA. Quality is assessed using metrics like completeness and contamination (CheckM), with high-quality MAGs defined as >90% complete and <5% contaminated. They are invaluable for studying uncultured organisms but are not equivalent to reference-quality genome assemblies.
Question 3 Short Answer
Explain why assembling genomes from metagenomic data is more challenging than assembling a single organism's genome.
Think about your answer, then reveal below.
Model answer: A metagenomic sample contains DNA from dozens to thousands of species at vastly different abundances. The assembler must simultaneously reconstruct multiple genomes from mixed reads, distinguishing reads from different organisms that may share similar sequences (conserved genes, mobile elements). Low-abundance organisms have insufficient coverage for reliable assembly, while dominant organisms are over-represented. Closely related strains complicate the de Bruijn graph with highly similar but non-identical sequences. After assembly, contigs must be binned — assigned to putative organisms — using composition and coverage signals, introducing additional error.
This is why metagenomic assembly often requires much deeper sequencing than single-organism projects, and why the resulting MAGs are graded by quality. Co-assembly across multiple related samples can improve results by leveraging differential abundance of organisms across conditions.