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Record W4414783359 · doi:10.1093/g3journal/jkaf232

Chromosome scale genomes of two invasive <i>Adelges</i> species enable virtual screening for selective adelgicides

2025· article· en· W4414783359 on OpenAlexfundno aff
Adam M. Glendening, Vidya S Vuruputoor, Tesko Chaganti, Meghan N Myles, David L. Stern, Muhammad Abdelalim, Yu-Pu Juang, Saskia A. Hogenhout, Thomas C. Mathers, Nicole Pauloski, Tim Cernak, Jill Wegrzyn, Karl C. Fetter

Bibliographic record

VenueG3 Genes Genomes Genetics · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilU.S. Forest ServiceNational Science FoundationNature ConservancyAgriculture and Agri-Food CanadaUniversity of California - President's Postdoctoral Fellowship ProgramCenter for Power Optimization of Electro-Thermal SystemsNature Conservancy of CanadaTokodai Institute for Element StrategyUniversity of ConnecticutU.S. Department of AgricultureUK Research and InnovationJohn Innes Foundation
KeywordsTsugaGenomeGeneTaxonParthenogenesisPhylogenetic treeJuvenile

Abstract

fetched live from OpenAlex

Two invasive adelgids are associated with widespread damage to several North American conifer species. Adelges tsugae, hemlock woolly adelgid, was introduced from Japan and reproduces parthenogenetically in North America, where it has rapidly decimated Tsuga canadensis and Tsuga caroliniana (eastern and Carolina hemlocks, respectively). Adelges abietis, eastern spruce gall adelgid, introduced from Europe, forms distinctive pineapple-shaped galls on several native spruce species. While not considered a major forest pest, it weakens trees and increases susceptibility to additional stressors. Broad-spectrum insecticides that are often used to control adelgid populations can have off-target impacts on beneficial insects. Whole-genome sequencing was performed on both species to aid in the development of targeted solutions that may minimize ecological impact. A. abietis was sequenced using barcoded linked-reads from 30 pooled individuals, with Hi-C scaffolding performed using data from a single individual collected from the same host plant. A. tsugae used long-read sequencing from pooled nymphs. The assembled A. tsugae and A. abietis genomes, pooled from several parthenogenetic females, are 220.75 and 253.16 Mb, respectively. Each consists of 8 autosomal chromosomes, as well as 2 sex chromosomes (X1/X2), supporting the XX-XO sex determination system. The genomes are over 96% complete based on BUSCO assessment. Genome annotation identified 11,424 and 12,060 protein-coding genes in A. tsugae and A. abietis, respectively. Comparative analysis of proteins across 31 hemipteran species and 14 arthropod outgroups identified 32,340 putative gene families. Gene family evolution analysis with CAFE revealed lineage-specific expansions in immune-related aminopeptidases (ERAP1) and juvenile hormone binding proteins (JHBP), contractions in juvenile hormone acid methyltransferases (JHAMT), and conservation of nicotinic acetylcholine receptors (nAChRs). These genes were explored as candidate families toward a long-term objective of developing adelgid-selective insecticides. Structural comparisons of proteins across 7 focal species (A. tsugae, A. abietis, Adelges cooleyi, Rhopalosiphum maidis, Apis mellifera, Danaus plexippus, and Drosophila melanogaster) revealed high conservation of nAChR and ERAP1, while JHAMT exhibited species-specific structural divergence. The potential of JHAMT as a lineage-specific target for pest control was explored through virtual screening of drugs and pesticides.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.237
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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