Bioinformatic Pipeline Development for Long-Read Sequencing Assembly of Plant Genomes
DOI:
https://doi.org/10.5281/zenodo.22687845Keywords:
long-read sequencing, genome assembly, bioinformatic pipeline, grass pea, Lathyrus sativus, HiFi sequencingAbstract
Reference-quality genome assembly of non-model crop and wild-relative plant species remains disproportionately
difficult relative to well-resourced model organisms, owing to a combination of large genome size, high repeat
content, and residual heterozygosity in outcrossing or wild-collected accessions, all of which complicate assembly
from long-read sequencing data even as the underlying sequencing technology has matured. We present
GRASSEMBLE, a modular bioinformatic pipeline integrating PacBio HiFi read correction, Hi-C scaffolding,
automated haplotype purging and a multi-tool consensus polishing stage, and evaluate it through a case study
assembly of the grass pea (Lathyrus sativus), a drought- and flood-tolerant legume of growing breeding interest
that has lacked a chromosome-scale reference genome. Applied to 42x HiFi coverage and 38x Hi-C coverage
generated from a single accession, GRASSEMBLE produced a 6.61 Gb assembly with contig N50 of 18.4 Mb,
scaffolded into seven pseudomolecules corresponding to the seven grass pea chromosomes and capturing 96.8%
of the estimated genome size. BUSCO completeness against the fabales_odb10 lineage dataset reached 98.1%,
and long terminal repeat assembly index scoring placed the assembly in the reference-quality tier used by recent
plant genome consortia. Comparative benchmarking against three widely used long-read assembly pipelines on
the same input data showed GRASSEMBLE achieving higher contig N50 and comparable or better BUSCO
completeness in every comparison, with the largest relative improvement attributable to the automated haplotype
purging module resolving assembly duplication that persisted through the other pipelines' default settings.
GRASSEMBLE is implemented as a Nextflow workflow with containerised dependencies to support reproducible
deployment on both local high-performance computing clusters and cloud infrastructure, and is released alongside
this case study to support genome assembly efforts in other under-resourced crop and wild-relative species facing
similar heterozygosity and repeat-content challenges.
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