Evidence map›Paper›PMID 28013457›Full record

ArticleImmunogenetics2017

Selective evolution of Toll-like receptors 3, 7, 8, and 9 in bats.

Haiying Jiang, Juan Li, Linmiao Li, Xiujuan Zhang, Lihong Yuan, Jinping Chen

Open access · bronzeAbstract read
In one paragraph

Article in Immunogenetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 17% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.

  1. A metaanalysis of bat phylogenetics and positive selection based on genomes and transcriptomes from 18 species.Proceedings of the National Academy of Sciences of the United States of America · 2019
    Pooled it
  2. Article
  3. Article
  4. Dampened TLR2-mediated Inflammatory Signaling in Bats.Molecular biology and evolution · 2025
    Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Antiviral effects of interferon-stimulated genes in bats.Frontiers in cellular and infection microbiology · 2023
    Review
  11. Article
  12. Article
  13. Article
  14. 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

6 authors at 1 institution in 1 country.

Haiying JiangGuangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Guangdong Institute of Applied Biological Resources, Guangzhou, China.
Juan LiGuangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Guangdong Institute of Applied Biological Resources, Guangzhou, China.
Linmiao LiGuangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Guangdong Institute of Applied Biological Resources, Guangzhou, China.
Xiujuan ZhangGuangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Guangdong Institute of Applied Biological Resources, Guangzhou, China.
Lihong YuanGuangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Guangdong Institute of Applied Biological Resources, Guangzhou, China.
Jinping ChenGuangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Guangdong Institute of Applied Biological Resources, Guangzhou, China. chenjp@giabr.gd.cn.
Institute of Zoology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous studies have shown that bats are reservoirs of a large number of viruses, many of which cause illness and mortality in humans and other animals. However, these bat-associated pathogens cause little, if any, clinicopathology in bats. This long-term adaptation should be reflected somewhat in the immune system. Toll-like receptors (TLRs) are the first line of immune defense against pathogens in vertebrates. Therefore, this study focuses on the selection of TLRs involved in virus recognition. The coding sequences of TLR3, TLR7, TLR8, and TLR9 were sequenced in ten bats. The selection pressure acting on each gene was also detected using branch- and site-specific methods. The results showed that the ancestor of bats and certain other bat sublineages evolved under positive selection for TLR7, TLR8, and TLR9. The highest proportion of positive selection occurred in TLR9, followed by TLR8 and TLR7. All of the positively selected sites were located in the leucine-rich repeat (LRR) domain, which implied their important roles in pathogen recognition. However, TLR3 evolved under negative selection. Our results are not in line with previous studies which identified more positively selected sites in TLR8 in mammalian species. In this study, the most positively selected sites were found in TLR9. This study encompassed more species that were considered natural reservoirs of viruses. The positive selection for TLR7, TLR8, and TLR9 might contribute to the adaptation of pathogen-host interaction in bats, especially in bat TLR9.

Indexed as

AnimalsChiropteraEvolution, MolecularPhylogenySelection, GeneticToll-Like Receptor 3Toll-Like Receptor 7Toll-Like Receptor 8Toll-Like Receptor 9Toll-Like Receptor 3Toll-Like Receptor 7Toll-Like Receptor 8Toll-Like Receptor 9AdaptationBatSelective evolutionTLRVirus defense

Identifiers

PMID28013457
PMCPMC7079974
OpenAlexW2563491162

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.