Background The complex interactions between host genetics and the gut microbiome are well documented. However, the specific impacts of gene expression patterns and microbial composition on each other remain to be further explored. Results Here, we investigated this complex interplay in a sizable population of 705 hens, employing integrative analyses to examine the relationships among the host genome, mucosal gene expression, and gut microbiota. Specific microbial taxa, such as the cecal family Christensenellaceae, which showed a heritability of 0.365, were strongly correlated with host genomic variants. We proposed a novel concept of regulatability (<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40168_2025_2054_Article_IEq1.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="16" /> </InlineMediaObject> <EquationSource Format="TEX">${r}_{b}^{2}$</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mi>r</mi> <mrow> <mi>b</mi> </mrow> <mn>2</mn> </msubsup> </math></EquationSource> </InlineEquation>), which was derived from h2, to quantify the cumulative effects of gene expression on the given phenotypes. The duodenal mucosal transcriptome emerged as a potent influencer of duodenal microbial taxa, with much higher <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40168_2025_2054_Article_IEq2.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="16" /> </InlineMediaObject> <EquationSource Format="TEX">${r}_{b}^{2}$</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mi>r</mi> <mrow> <mi>b</mi> </mrow> <mn>2</mn> </msubsup> </math></EquationSource> </InlineEquation> values (0.17 ± 0.01, mean ± SE) than h2 values (0.02 ± 0.00). A comparative analysis of chickens and humans revealed similar average microbiability values of genes (0.18 vs. 0.20) and significant differences in average <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40168_2025_2054_Article_IEq3.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="16" /> </InlineMediaObject> <EquationSource Format="TEX">${r}_{b}^{2}$</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mi>r</mi> <mrow> <mi>b</mi> </mrow> <mn>2</mn> </msubsup> </math></EquationSource> </InlineEquation> values of microbes (0.17 vs. 0.04). Besides, cis (<InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40168_2025_2054_Article_IEq4.gif" Format="GIF" Height="20" Rendition="HTML" Resolution="72" Type="Linedraw" Width="25" /> </InlineMediaObject> <EquationSource Format="TEX">${h}_{\text{cis}}^{2}$</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mi>h</mi> <mrow> <mtext>cis</mtext> </mrow> <mn>2</mn> </msubsup> </math></EquationSource> </InlineEquation>) and trans heritability (<InlineEquation ID="IEq5"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40168_2025_2054_Article_IEq5.gif" Format="GIF" Height="20" Rendition="HTML" Resolution="72" Type="Linedraw" Width="38" /> </InlineMediaObject> <EquationSource Format="TEX">${h}_{\text{trans}}^{2}$</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mi>h</mi> <mrow> <mtext>trans</mtext> </mrow> <mn>2</mn> </msubsup> </math></EquationSource> </InlineEquation>) were estimated to assess the effects of genetic variations inside and outside the cis window of the gene on its expression. Higher <InlineEquation ID="IEq6"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40168_2025_2054_Article_IEq6.gif" Format="GIF" Height="20" Rendition="HTML" Resolution="72" Type="Linedraw" Width="38" /> </InlineMediaObject> <EquationSource Format="TEX">${h}_{\text{trans}}^{2}$</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mi>h</mi> <mrow> <mtext>trans</mtext> </mrow> <mn>2</mn> </msubsup> </math></EquationSource> </InlineEquation> values than <InlineEquation ID="IEq7"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40168_2025_2054_Article_IEq7.gif" Format="GIF" Height="20" Rendition="HTML" Resolution="72" Type="Linedraw" Width="25" /> </InlineMediaObject> <EquationSource Format="TEX">${h}_{\text{cis}}^{2}$</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mi>h</mi> <mrow> <mtext>cis</mtext> </mrow> <mn>2</mn> </msubsup> </math></EquationSource> </InlineEquation> values and a greater prevalence of trans-regulated genes than cis-regulated genes underscored the significant role of loci outside the cis window in shaping gene expression levels. Furthermore, our exploration of the regulatory effects of duodenal mucosal genes and the microbiota on 18 complex traits enhanced our understanding of the regulatory mechanisms, in which the CHST14 gene and its regulatory relationships with Lactobacillus salivarius jointly facilitated the deposition of abdominal fat by modulating the concentration of bile salt hydrolase, and further triglycerides, total cholesterol, and free fatty acids absorption and metabolism. Conclusions Our findings highlighted a novel concept of <InlineEquation ID="IEq8"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40168_2025_2054_Article_IEq8.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="16" /> </InlineMediaObject> <EquationSource Format="TEX">${r}_{b}^{2}$</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mi>r</mi> <mrow> <mi>b</mi> </mrow> <mn>2</mn> </msubsup> </math></EquationSource> </InlineEquation> to quantify the phenotypic variance attributed to gene expression and emphasize the superior role of intestinal mucosal gene expressions over host genomic variations in elucidating host‒microbe interactions for complex traits. This understanding could assist in devising strategies to modulate host–microbe interactions, ultimately improving economic traits in chickens. Graphical Abstract The host genome, hepatic and duodenal transcriptomes, and gut microbiome were integrated to elucidate the regulatory mechanisms underlying the complex phenotypes of chickens. Heritability estimation and GWASs from the genome, regulatability estimation from the transcriptome, and microbiability estimation from the microbiome were collectively calculated for the host phenotypes. By integrating genome and transcriptome data, the cis- and trans-heritability of genes were estimated, and methods such as eQTL mapping and SMR were used to elucidate the genetic regulatory mechanisms of phenotypes. By integrating genome and microbiome data, we conducted microbial heritability estimation and GWASs to explore the extent to which the host genome shapes the microbiota. By integrating transcriptome and microbiome data, we estimated the microbiability of genes and the regulatability of the microbiota, exploring the degree of interaction between host gene expression and the gut microbiota. By combining all the analytical methods mentioned above, a more advanced and comprehensive understanding of the extent and manner of host and microbiota interactions that regulate host phenotypes can be achieved. <MediaObject ID="MOESM6"> <VideoObject FileRef="MediaObjects/40168_2025_2054_MOESM6_ESM.mp4" VideoID="FJkP-WwXS51f6sFHx5DLbM"> <Caption Language="En" xml:lang="en"> <CaptionContent> Video Abstract </CaptionContent> </Caption> </VideoObject> </MediaObject>

Deciphering the coordinated roles of the host genome, duodenal mucosal genes, and microbiota in regulating complex traits in chickens

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2025年3月1日

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Fangren Lan,
Xiqiong Wang,
Qianqian Zhou,
Xiaochang Li,
Jiaming Jin,
Wenxin Zhang,
Chaoliang Wen,
Guiqin Wu,
Guangqi Li,
Yiyuan Yan,
Ning Yang,
Congjiao Sun

摘要

Background

The complex interactions between host genetics and the gut microbiome are well documented. However, the specific impacts of gene expression patterns and microbial composition on each other remain to be further explored.

Results

Here, we investigated this complex interplay in a sizable population of 705 hens, employing integrative analyses to examine the relationships among the host genome, mucosal gene expression, and gut microbiota. Specific microbial taxa, such as the cecal family Christensenellaceae, which showed a heritability of 0.365, were strongly correlated with host genomic variants. We proposed a novel concept of regulatability ( ${r}_{b}^{2}$ $r_{b}^{2}$ ), which was derived from h², to quantify the cumulative effects of gene expression on the given phenotypes. The duodenal mucosal transcriptome emerged as a potent influencer of duodenal microbial taxa, with much higher ${r}_{b}^{2}$ $r_{b}^{2}$ values (0.17 ± 0.01, mean ± SE) than h² values (0.02 ± 0.00). A comparative analysis of chickens and humans revealed similar average microbiability values of genes (0.18 vs. 0.20) and significant differences in average ${r}_{b}^{2}$ $r_{b}^{2}$ values of microbes (0.17 vs. 0.04). Besides, cis ( ${h}_{\text{cis}}^{2}$ $h_{cis}^{2}$ ) and trans heritability ( ${h}_{\text{trans}}^{2}$ $h_{trans}^{2}$ ) were estimated to assess the effects of genetic variations inside and outside the cis window of the gene on its expression. Higher ${h}_{\text{trans}}^{2}$ $h_{trans}^{2}$ values than ${h}_{\text{cis}}^{2}$ $h_{cis}^{2}$ values and a greater prevalence of trans-regulated genes than cis-regulated genes underscored the significant role of loci outside the cis window in shaping gene expression levels. Furthermore, our exploration of the regulatory effects of duodenal mucosal genes and the microbiota on 18 complex traits enhanced our understanding of the regulatory mechanisms, in which the CHST14 gene and its regulatory relationships with Lactobacillus salivarius jointly facilitated the deposition of abdominal fat by modulating the concentration of bile salt hydrolase, and further triglycerides, total cholesterol, and free fatty acids absorption and metabolism.

Conclusions

Our findings highlighted a novel concept of ${r}_{b}^{2}$ $r_{b}^{2}$ to quantify the phenotypic variance attributed to gene expression and emphasize the superior role of intestinal mucosal gene expressions over host genomic variations in elucidating host‒microbe interactions for complex traits. This understanding could assist in devising strategies to modulate host–microbe interactions, ultimately improving economic traits in chickens.

Graphical Abstract

The host genome, hepatic and duodenal transcriptomes, and gut microbiome were integrated to elucidate the regulatory mechanisms underlying the complex phenotypes of chickens. Heritability estimation and GWASs from the genome, regulatability estimation from the transcriptome, and microbiability estimation from the microbiome were collectively calculated for the host phenotypes.

By integrating genome and transcriptome data, the cis- and trans-heritability of genes were estimated, and methods such as eQTL mapping and SMR were used to elucidate the genetic regulatory mechanisms of phenotypes. By integrating genome and microbiome data, we conducted microbial heritability estimation and GWASs to explore the extent to which the host genome shapes the microbiota. By integrating transcriptome and microbiome data, we estimated the microbiability of genes and the regulatability of the microbiota, exploring the degree of interaction between host gene expression and the gut microbiota.

By combining all the analytical methods mentioned above, a more advanced and comprehensive understanding of the extent and manner of host and microbiota interactions that regulate host phenotypes can be achieved.

Video Abstract