Sequence Analysis

Sequence analysis encompasses the computational examination of biological polymers—DNA, RNA and proteins—to elucidate their structure, function and evolutionary relationships. At its core lies the comparison of linear chains of nucleotides or amino acids through alignment algorithms, which detect conserved motifs, domains and homologies. Beyond pairwise and multiple sequence alignment, modern workflows integrate de novo assembly of short and long reads, annotation of genes and regulatory elements, detection of variants and structural rearrangements, and reconstruction of phylogenies. Advances in graph pangenomes, population genomics and metagenomics have further expanded the scale and resolution of sequence analyses, enabling comprehensive surveys of genetic diversity, microbial communities and transcriptomic landscapes. These methods underpin diverse applications—from identifying disease-associated mutations and tracking pathogen outbreaks to guiding crop improvement and mapping the tree of life—by transforming raw sequencing data into actionable biological insight.

Research from Nature Portfolio

A first draft of the human pangenome reference has been released as a graph structure derived from dozens of high-quality diploid assemblies. This resource captures both common and novel sequence variation, incorporates over 100 million additional bases relative to the existing reference genome, and enhances small-variant and structural-variant detection by 30–100 percent. By aligning short-read data to the pangenome, studies have demonstrated reduced reference bias and more accurate genotyping across diverse populations.

An ensemble-based alignment strategy has recently been introduced to mitigate bias in multiple sequence alignments. By perturbing hidden Markov models and permuting guide-tree topologies, researchers generate a collection of high-accuracy alignments and assess confidence in inferred homology or phylogeny as the fraction of the ensemble supporting each relationship. Applied to protein families and viral phylogenies, this approach has resolved ambiguous branches with low conventional bootstrap support and revealed potential polyphyly in established taxonomic groups.

Benchmarking of RNA-seq spliced-read aligners has provided a rigorous comparison of tools on large mouse and human datasets. Evaluations of alignment yield, splice-junction accuracy and transcript reconstruction identify strengths and limitations of leading programmes, highlighting the need for continued development of algorithms that balance sensitivity, speed and memory efficiency in analysing complex transcriptomes.

Research from all publishers

Mitochondrial metagenomics has emerged as a powerful approach for recovering mitogenomes from bulk environmental or specimen mixtures without specimen-level sorting. Shotgun sequencing of pooled insect, plant or environmental samples, followed by targeted assembly and curation of mitochondrial contigs, yields hundreds of mitogenomes that can be incorporated into supermatrix or supertree frameworks. These studies demonstrate accurate phylogenetic placement of cryptic taxa, enable community-level biodiversity assessments and facilitate quantitative estimates of biomass and species turnover.

In the realm of microbial transcriptomics, a scalable metatranscriptomic pipeline has been developed to process tens to hundreds of millions of RNA-seq reads within a Docker framework. The workflow automates quality filtering, assembly, taxonomic annotation and enzyme-level profiling, generating consensus activity maps and network visualisations. Benchmarks against existing methods show improved speed and accuracy, supporting large-scale investigations of functional dynamics in host-associated and environmental microbiomes.

Sequence Analysis publication trend

The graph below shows the total number of articles in sequence analysis across all publications each year (not limited to Nature Index journals).

Technical terms

Sequence analysis: Computational examination of DNA, RNA or protein sequences to reveal functional, structural and evolutionary information.

Multiple sequence alignment: Rearrangement of three or more biological sequences into a matrix to identify conserved positions and infer homology.

Genome assembly: Reconstruction of a complete genome sequence by merging overlapping sequencing reads into contiguous segments.

Annotation: The process of identifying and labelling genomic features such as genes, exons, regulatory elements and non-coding RNAs.

Variant calling: Detection and genotyping of sequence polymorphisms, including single nucleotide variants and structural rearrangements, relative to a reference.

Phylogenetic inference: Reconstruction of evolutionary relationships among sequences or taxa, often represented as branching trees.

Pangenome: A graph-based or collective representation of all genomic sequences present within a species or population, encompassing core and accessory elements.

Metagenomics: Sequencing and analysis of genetic material recovered directly from complex microbial communities without prior cultivation.

References

1. A draft human pangenome reference. Nature (2023).
2. Muscle5: High-accuracy alignment ensembles enable unbiased assessments of sequence homology and phylogeny. Nature Communications (2022).
3. Systematic evaluation of spliced alignment programs for RNA-seq data. Nature Methods (2013).
4. Mitochondrial metagenomics: letting the genes out of the bottle. GigaScience (2016).
5. MetaPro: a scalable and reproducible data processing and analysis pipeline for metatranscriptomic investigation of microbial communities. Microbiome (2023).
6. Sequence Analysis.