Genome assembly is the process of reconstructing the full DNA sequence of an organism from many short or long fragments generated by sequencing technologies. Modern research focuses on improving accuracy, completeness and speed while coping with large, complex genomes that contain repetitive regions, structural variants and sequencing errors.

Short read sequencing produces highly accurate but brief fragments that are difficult to place uniquely in repetitive DNA. Long read technologies provide much longer stretches that bridge repeats and structural variants but typically have higher error rates. Current assembly strategies often combine these data types: long reads build a continuous backbone and short reads polish errors.

Two main computational paradigms dominate. Overlap based methods compare reads directly to build a graph of overlaps, which works well with long reads. De Bruijn graph methods break reads into k length substrings and connect them into paths that represent the genome, a strategy efficient for large short read datasets. Both face challenges resolving repeats, heterozygosity and sequencing artifacts.

Recent research emphasizes reference free, de novo assemblies rather than mapping reads to an existing genome. This allows the discovery of novel sequences and structural variants, and avoids biases from a single reference genome. Advances in algorithms, data structures and hardware acceleration are making chromosome scale and even telomere to telomere assemblies increasingly common.

Genome assembly now underpins population genomics, medical genetics, evolutionary biology and conservation. High quality assemblies reveal gene content, regulatory elements and structural variation, enabling more precise association of genotype with phenotype and accelerating biological discovery.