Evidence map›Paper›PMID 35179579›Full record

ArticleGenome biology and evolution2022

Selection of Genome-Wide SNPs for Pooled Allelotyping Assays Useful for Population Monitoring.

Marielle Babineau, Eliza Collis, Angela Ruffell, Rowan Bunch, Jody McNally, Russell E Lyons, Andrew C Kotze, Peter W Hunt

Open access · goldAbstract read
In one paragraph

Article in Genome biology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 98% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Marielle BabineauCSIRO Agriculture and Food, Armidale, New South Wales, Australia.
Eliza CollisSchool of Veterinary Science, The University of Queensland, Gatton, Queensland, Australia.
Angela RuffellCSIRO Agriculture and Food, St-Lucia, Queensland, Australia.
Rowan BunchCSIRO Agriculture and Food, Armidale, New South Wales, Australia.
Jody McNallyCSIRO Agriculture and Food, Armidale, New South Wales, Australia.
Russell E LyonsSchool of Veterinary Science, The University of Queensland, Gatton, Queensland, Australia.
Andrew C KotzeCSIRO Agriculture and Food, St-Lucia, Queensland, Australia.
Peter W HuntCSIRO Agriculture and Food, Armidale, New South Wales, Australia.ORCID 0000-0001-5679-2404
Commonwealth Scientific and Industrial Research Organisation · AUThe University of Queensland · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Parasitic worms are serious pests of humans, livestock, and crops worldwide. Multiple management strategies are employed in order to reduce their impact, and some of these may affect their genome and population allelic frequency distribution. The evolution of chemical resistance, ecological changes, and pest dispersal has allowed an increasing number of pests to become difficult to control with current management methods. Their lifestyle limits the use of ecological and individual-based management of populations. There is a need to develop rapid, affordable, and simple diagnostics to assess the efficacy of management strategies and delay the evolution of resistance to these strategies. This study presents a multilocus, equal-representation, whole-genome pooled single nucleotide polymorphisms (SNPs) selection approach as a monitoring tool for the ovine nematode parasite Haemonchus contortus. The SNP selection method used two reference genomes of different quality, then validated these SNPs against a high-quality recent genome assembly. From over 11 million high-quality SNPs identified, 334 SNPs were selected, of which 262 were species-specific, yielded similar allele frequencies when assessed as multiple individuals or as pools of individuals, and suitable to distinguish mixed nematode isolate pools from single isolate pools. As a proof-of-concept, 21 Australian H. contortus populations with various phenotypes and genotypes were screened. This analysis confirmed the overall low level of genetic differentiation between populations collected from the field, but clearly identifying highly inbred populations, and populations showing genetic signatures associated with chemical resistance. The analysis showed that 66% of the SNPs were necessary for stability in assessing population genetic patterns, and SNP pairs did not show linkage according to allelic frequencies across the 21 populations. This method demonstrates that ongoing monitoring of parasite allelic frequencies and genetic changes can be achieved as a management assessment tool to identify drug-treatment failure, population incursions, and inbreeding signatures due to selection. The SNP selection method could also be applied to other parasite species.

Indexed as

HaemonchusPolymorphism, Single NucleotideAnimalsAustraliaDrug ResistanceGene FrequencySheepallelotypingHaemonchus contortuspest managementpopulation geneticsresistanceSNP discovery

Identifiers

PMID35179579
PMCPMC8911822
OpenAlexW4213134811

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.