Cargando…

Combination analysis of genome-wide association and transcriptome sequencing of residual feed intake in quality chickens

BACKGROUND: Residual feed intake (RFI) is a powerful indicator for energy utilization efficiency and responds to selection. Low RFI selection enables a reduction in feed intake without affecting growth performance. However, the effective variants or major genes dedicated to phenotypic differences in...

Descripción completa

Detalles Bibliográficos
Autores principales: Xu, Zhenqiang, Ji, Congliang, Zhang, Yan, Zhang, Zhe, Nie, Qinghua, Xu, Jiguo, Zhang, Dexiang, Zhang, Xiquan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4979145/
https://www.ncbi.nlm.nih.gov/pubmed/27506765
http://dx.doi.org/10.1186/s12864-016-2861-5
_version_ 1782447277738033152
author Xu, Zhenqiang
Ji, Congliang
Zhang, Yan
Zhang, Zhe
Nie, Qinghua
Xu, Jiguo
Zhang, Dexiang
Zhang, Xiquan
author_facet Xu, Zhenqiang
Ji, Congliang
Zhang, Yan
Zhang, Zhe
Nie, Qinghua
Xu, Jiguo
Zhang, Dexiang
Zhang, Xiquan
author_sort Xu, Zhenqiang
collection PubMed
description BACKGROUND: Residual feed intake (RFI) is a powerful indicator for energy utilization efficiency and responds to selection. Low RFI selection enables a reduction in feed intake without affecting growth performance. However, the effective variants or major genes dedicated to phenotypic differences in RFI in quality chickens are unclear. Therefore, a genome-wide association study (GWAS) and RNA sequencing were performed on RFI to identify genetic variants and potential candidate genes associated with energy improvement. RESULTS: A lower average daily feed intake was found in low-RFI birds compared to high-RFI birds. The heritability of RFI measured from 44 to 83 d of age was 0.35. GWAS showed that 32 of the significant single nucleotide polymorphisms (SNPs) associated with the RFI (P < 10(−4)) accounted for 53.01 % of the additive genetic variance. More than half of the effective SNPs were located in a 1 Mb region (16.3–17.3 Mb) of chicken (Gallus gallus) chromosome (GGA) 12. Thus, focusing on this region should enable a deeper understanding of energy utilization. RNA sequencing was performed to profile the liver transcriptomes of four male chickens selected from the high and low tails of the RFI. One hundred and sixteen unique genes were identified as differentially expressed genes (DEGs). Some of these genes were relevant to appetite, cell activities, and fat metabolism, such as CCKAR, HSP90B1, and PCK1. Some potential genes within the 500 Kb flanking region of the significant RFI-related SNPs detected in GWAS (i.e., MGP, HIST1H110, HIST1H2A4L3, OC3, NR0B2, PER2, ST6GALNAC2, and G0S2) were also identified as DEGs in chickens with divergent RFIs. CONCLUSIONS: The GWAS findings showed that the 1 Mb narrow region of GGA12 should be important because it contained genes involved in energy-consuming processes, such as lipogenesis, social behavior, and immunity. Similar results were obtained in the transcriptome sequencing experiments. In general, low-RFI birds seemed to optimize energy employment by reducing energy expenditure in cell activities, immune responses, and physical activity compared to eating. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2861-5) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-4979145
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-49791452016-08-11 Combination analysis of genome-wide association and transcriptome sequencing of residual feed intake in quality chickens Xu, Zhenqiang Ji, Congliang Zhang, Yan Zhang, Zhe Nie, Qinghua Xu, Jiguo Zhang, Dexiang Zhang, Xiquan BMC Genomics Research Article BACKGROUND: Residual feed intake (RFI) is a powerful indicator for energy utilization efficiency and responds to selection. Low RFI selection enables a reduction in feed intake without affecting growth performance. However, the effective variants or major genes dedicated to phenotypic differences in RFI in quality chickens are unclear. Therefore, a genome-wide association study (GWAS) and RNA sequencing were performed on RFI to identify genetic variants and potential candidate genes associated with energy improvement. RESULTS: A lower average daily feed intake was found in low-RFI birds compared to high-RFI birds. The heritability of RFI measured from 44 to 83 d of age was 0.35. GWAS showed that 32 of the significant single nucleotide polymorphisms (SNPs) associated with the RFI (P < 10(−4)) accounted for 53.01 % of the additive genetic variance. More than half of the effective SNPs were located in a 1 Mb region (16.3–17.3 Mb) of chicken (Gallus gallus) chromosome (GGA) 12. Thus, focusing on this region should enable a deeper understanding of energy utilization. RNA sequencing was performed to profile the liver transcriptomes of four male chickens selected from the high and low tails of the RFI. One hundred and sixteen unique genes were identified as differentially expressed genes (DEGs). Some of these genes were relevant to appetite, cell activities, and fat metabolism, such as CCKAR, HSP90B1, and PCK1. Some potential genes within the 500 Kb flanking region of the significant RFI-related SNPs detected in GWAS (i.e., MGP, HIST1H110, HIST1H2A4L3, OC3, NR0B2, PER2, ST6GALNAC2, and G0S2) were also identified as DEGs in chickens with divergent RFIs. CONCLUSIONS: The GWAS findings showed that the 1 Mb narrow region of GGA12 should be important because it contained genes involved in energy-consuming processes, such as lipogenesis, social behavior, and immunity. Similar results were obtained in the transcriptome sequencing experiments. In general, low-RFI birds seemed to optimize energy employment by reducing energy expenditure in cell activities, immune responses, and physical activity compared to eating. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2861-5) contains supplementary material, which is available to authorized users. BioMed Central 2016-08-09 /pmc/articles/PMC4979145/ /pubmed/27506765 http://dx.doi.org/10.1186/s12864-016-2861-5 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Xu, Zhenqiang
Ji, Congliang
Zhang, Yan
Zhang, Zhe
Nie, Qinghua
Xu, Jiguo
Zhang, Dexiang
Zhang, Xiquan
Combination analysis of genome-wide association and transcriptome sequencing of residual feed intake in quality chickens
title Combination analysis of genome-wide association and transcriptome sequencing of residual feed intake in quality chickens
title_full Combination analysis of genome-wide association and transcriptome sequencing of residual feed intake in quality chickens
title_fullStr Combination analysis of genome-wide association and transcriptome sequencing of residual feed intake in quality chickens
title_full_unstemmed Combination analysis of genome-wide association and transcriptome sequencing of residual feed intake in quality chickens
title_short Combination analysis of genome-wide association and transcriptome sequencing of residual feed intake in quality chickens
title_sort combination analysis of genome-wide association and transcriptome sequencing of residual feed intake in quality chickens
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4979145/
https://www.ncbi.nlm.nih.gov/pubmed/27506765
http://dx.doi.org/10.1186/s12864-016-2861-5
work_keys_str_mv AT xuzhenqiang combinationanalysisofgenomewideassociationandtranscriptomesequencingofresidualfeedintakeinqualitychickens
AT jicongliang combinationanalysisofgenomewideassociationandtranscriptomesequencingofresidualfeedintakeinqualitychickens
AT zhangyan combinationanalysisofgenomewideassociationandtranscriptomesequencingofresidualfeedintakeinqualitychickens
AT zhangzhe combinationanalysisofgenomewideassociationandtranscriptomesequencingofresidualfeedintakeinqualitychickens
AT nieqinghua combinationanalysisofgenomewideassociationandtranscriptomesequencingofresidualfeedintakeinqualitychickens
AT xujiguo combinationanalysisofgenomewideassociationandtranscriptomesequencingofresidualfeedintakeinqualitychickens
AT zhangdexiang combinationanalysisofgenomewideassociationandtranscriptomesequencingofresidualfeedintakeinqualitychickens
AT zhangxiquan combinationanalysisofgenomewideassociationandtranscriptomesequencingofresidualfeedintakeinqualitychickens