Genomic signatures of selection associated with benzimidazole drug treatments in Haemonchus contortus field populations.

Genome-wide methods offer a powerful approach to detect signatures of drug selection. However, limited availability of suitable reference genomes and the difficulty of obtaining field populations with well-defined, distinct drug treatment histories mean there is little information on the signatures of selection in parasitic nematodes and on how best to detect them. This study addresses these knowledge gaps by using field populations of Haemonchus contortus with well-defined benzimidazole treatment histories, leveraging a recently completed chromosomal-scale reference genome assembly. We generated a panel of 49,393 genomic markers to genotype 20 individual adult worms from each of four H. contortus populations: two from closed sheep flocks with an approximate 20 year history of frequent benzimidazole treatment, and two populations with a history of little or no treatment. Sampling occurred in the same geographical region to limit genetic differentiation and maximise the detection sensitivity. A clear signature of selection was detected on chromosome I, centred on the isotype-1 β-tubulin gene. Two additional, but weaker, signatures of selection were detected; one near the middle of chromosome I spanning 3.75 Mbp and 259 annotated genes, and one on chromosome II spanning a region of 3.3 Mbp and 206 annotated genes, including the isotype-2 β-tubulin locus. We also assessed how sensitivity was impacted by sequencing depth, worm number, and pooled versus individual worm sequence data. This study provides the first known direct genome-wide evidence for any parasitic nematode, that the isotype-1 β-tubulin gene is quantitatively the single most important benzimidazole resistance locus. It also identified two additional genomic regions that likely contain benzimidazole resistance loci of secondary importance. This study provides an experimental framework to maximise the power of genome-wide approaches to detect signatures of selection driven by anthelmintic drug treatments in field populations of parasitic nematodes.