Differential transcriptome profiling of <i>Bartonella</i> spp. influenced by the species divergence factors.

To reveal the differences in transcript levels of <i>Bartonella</i> spp. from different species and hosts and their impacts on phylogenetic relationships, we focus on 27 strains from four <i>Bartonella</i> species (<i>B. henselae</i>, <i>B. koehlerae</i>, <i>B. clarridgeiae</i> and <i>B. quintana</i>) and three hosts (<i>Felis catus</i>, <i>Homo sapiens</i> and <i>Macaca mulatta</i>) to conduct the transcriptome sequencing using Illumina high-throughput sequencing technology. Gene expression differences between strains from different species and hosts are analyzed, and the results of phylogenetic analysis at the transcriptome and genome levels are compared. The results show significant differences in gene transcription between strains from different species and hosts. Twelve genes are screened, including <i>virB10</i>, <i>bepC</i> and <i>virB4</i>, which may facilitate host-specific recognition. Furthermore, phylogenetic analysis based on SNPs within the core genes of the transcriptome demonstrate species-specific clustering patterns among strains. Further analysis indicate that host factors influence the genetic divergence of strains, while geographic factors exert a small impact on this process. These findings are congruent with the phylogenetic analysis of SNPs in the core genes of the genome. Our study uses differential transcriptome analysis to reveal the genetic divergence and phylogenetic relationships of <i>Bartonella</i> species. And the observed regular differences between strains from different species and hosts are found to correspond with the results of traditional genome analysis. Thus, our results indicate the utility of transcriptome data in efficiently investigating the genetic divergence between species.

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Journal
PubMed
Published
2025-03-01
DOI
https://doi.org/10.16288/j.yczz.24-201
Primary Topic
Gene expression and cancer classification
Type
article
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article

Differential transcriptome profiling of Bartonella spp. influenced by the species divergence factors.

Qiyong Liu, Miao Yu, Yujun Qiang, Pengbo Liu et al.
PubMed
Gene expression and cancer classification
article

Differential transcriptome profiling of Bartonella spp. influenced by the species divergence factors.

Qiyong Liu, Miao Yu, Yujun Qiang, Pengbo Liu, Dongmei Li, Wen Zhang, Na Han, Min Chen
article en

Abstract

To reveal the differences in transcript levels of <i>Bartonella</i> spp. from different species and hosts and their impacts on phylogenetic relationships, we focus on 27 strains from four <i>Bartonella</i> species (<i>B. henselae</i>, <i>B. koehlerae</i>, <i>B. clarridgeiae</i> and <i>B. quintana</i>) and three hosts (<i>Felis catus</i>, <i>Homo sapiens</i> and <i>Macaca mulatta</i>) to conduct the transcriptome sequencing using Illumina high-throughput sequencing technology. Gene expression differences between strains from different species and hosts are analyzed, and the results of phylogenetic analysis at the transcriptome and genome levels are compared. The results show significant differences in gene transcription between strains from different species and hosts. Twelve genes are screened, including <i>virB10</i>, <i>bepC</i> and <i>virB4</i>, which may facilitate host-specific recognition. Furthermore, phylogenetic analysis based on SNPs within the core genes of the transcriptome demonstrate species-specific clustering patterns among strains. Further analysis indicate that host factors influence the genetic divergence of strains, while geographic factors exert a small impact on this process. These findings are congruent with the phylogenetic analysis of SNPs in the core genes of the genome. Our study uses differential transcriptome analysis to reveal the genetic divergence and phylogenetic relationships of <i>Bartonella</i> species. And the observed regular differences between strains from different species and hosts are found to correspond with the results of traditional genome analysis. Thus, our results indicate the utility of transcriptome data in efficiently investigating the genetic divergence between species.

PubMedVol. 47(3)
National Institute for Communicable Disease Control and Prevention (CN)
Openalex Percentile: Top 96%
Gene expression and cancer classification
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