Evidence map›Paper›PMID 37264201›Full record

ArticleNature ecology & evolution2023

Single-cell dissection of aggression in honeybee colonies.

Ian M Traniello, Syed Abbas Bukhari, Payam Dibaeinia, Guillermo Serrano, Arian Avalos, Amy Cash Ahmed, Alison L Sankey, Mikel Hernaez, Saurabh Sinha, Sihai Dave Zhao and 2 more

Abstract read
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In one paragraph

Article in Nature ecology & evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
11.0field-weighted citation impact, top 1% 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

16 citing papers in PubMed, 35 citations in OpenAlex.

  1. MilliMap: interactive closed-loop analysis for spatial omics.bioRxiv : the preprint server for biology · 2026
    Article
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  4. The Evolution of Bees: Insights from 'Omic Studies.Genome biology and evolution · 2026
    Review
  5. Article
  6. Article
  7. Review
  8. Article
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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

12 authors at 4 institutions in 2 countries.

Ian M TranielloNeuroscience Program, University of Illinois at Urbana-Champaign (UIUC), Urbana, IL, USA. it4770@princeton.edu.ORCID http://orcid.org/0000-0002-0001-3915
Syed Abbas BukhariCarl R Woese Institute for Genomic Biology, UIUC, Urbana, IL, USA.
Payam DibaeiniaDepartment of Computer Science, UIUC, Urbana, IL, USA.ORCID http://orcid.org/0000-0003-2978-2520
Guillermo SerranoComputational Biology Program, CIMA University of Navarra, Pamplona, Spain.ORCID http://orcid.org/0000-0003-3972-6186
Arian AvalosHoney Bee Breeding, Genetics and Physiology Research Laboratory, Agricultural Research Services, United States Department of Agriculture, Baton Rouge, LA, USA.ORCID http://orcid.org/0000-0002-4011-3099
Amy Cash AhmedCarl R Woese Institute for Genomic Biology, UIUC, Urbana, IL, USA.
Alison L SankeyCarl R Woese Institute for Genomic Biology, UIUC, Urbana, IL, USA.
Mikel HernaezComputational Biology Program, CIMA University of Navarra, Pamplona, Spain.ORCID http://orcid.org/0000-0003-0443-2305
Saurabh SinhaCarl R Woese Institute for Genomic Biology, UIUC, Urbana, IL, USA.ORCID http://orcid.org/0000-0001-6033-7746
Sihai Dave ZhaoCarl R Woese Institute for Genomic Biology, UIUC, Urbana, IL, USA.
Julian CatchenCarl R Woese Institute for Genomic Biology, UIUC, Urbana, IL, USA.ORCID http://orcid.org/0000-0002-4798-660X
Gene E RobinsonNeuroscience Program, University of Illinois at Urbana-Champaign (UIUC), Urbana, IL, USA. generobi@illinois.edu.ORCID http://orcid.org/0000-0003-4828-4068
Urbana University · USUniversidad de Navarra · ESUniversity of Illinois Urbana-Champaign · USAgricultural Research Service · US

Funding

Quantitative Regulatory Genomics: Networks, CIS-Regulatorycodes, and Phenotypic VariationR35GM131819 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI SINHA, SAURABH · 2019 to 2023
$1.8M
NIGMS NIH HHS R35 GM131819
6 · The paper itself

Abstract

Understanding how genotypic variation results in phenotypic variation is especially difficult for collective behaviour because group phenotypes arise from complex interactions among group members. A genome-wide association study identified hundreds of genes associated with colony-level variation in honeybee aggression, many of which also showed strong signals of positive selection, but the influence of these 'colony aggression genes' on brain function was unknown. Here we use single-cell (sc) transcriptomics and gene regulatory network (GRN) analyses to test the hypothesis that genetic variation for colony aggression influences individual differences in brain gene expression and/or gene regulation. We compared soldiers, which respond to territorial intrusion with stinging attacks, and foragers, which do not. Colony environment showed stronger influences on soldier-forager differences in brain gene regulation compared with brain gene expression. GRN plasticity was strongly associated with colony aggression, with larger differences in GRN dynamics detected between soldiers and foragers from more aggressive relative to less aggressive colonies. The regulatory dynamics of subnetworks composed of genes associated with colony aggression genes were more strongly correlated with each other across different cell types and brain regions relative to other genes, especially in brain regions involved with olfaction and vision and multimodal sensory integration, which are known to mediate bee aggression. These results show how group genetics can shape a collective phenotype by modulating individual brain gene regulatory network architecture.

Indexed as

AggressionBeesBehavior, AnimalGenome-Wide Association StudyAnimalsBrainGene Expression RegulationGene Regulatory Networks

Identifiers

PMID37264201
OpenAlexW4379016352

What OpenQuestion holds

Textmetadata
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.