De novo assembly of the genome of a species is essential in the absence of a 
reference genome sequence. Many scalable assembly algorithms use the de Bruijn 
graph (DBG) paradigm to reconstruct genomes, where a table of subsequences of a 
certain length is derived from the reads, and their overlaps are analyzed to 
assemble sequences. Despite longer subsequences unlocking longer genomic 
features for assembly, associated increase in compute resources limits the 
practicability of DBG over other assembly archetypes already designed for longer 
reads. Here, we revisit the DBG paradigm to adapt it to the changing sequencing 
technology landscape and introduce three data structure designs for spaced seeds 
in the form of paired subsequences. These data structures address memory and run 
time constraints imposed by longer reads. We observe that when a fixed distance 
separates seed pairs, it provides increased sequence specificity with increased 
gap length. Further, we note that Bloom filters would be suitable to implicitly 
store spaced seeds and be tolerant to sequencing errors. Building on this 
concept, we describe a data structure for tracking the frequencies of observed 
spaced seeds. These data structure designs will have applications in genome, 
transcriptome and metagenome assemblies, and read error correction.