Evidence map›Paper›PMID 27506765›Full record

ArticleBMC genomics2016

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

Zhenqiang Xu, Congliang Ji, Yan Zhang, Zhe Zhang, Qinghua Nie, Jiguo Xu, Dexiang Zhang, Xiquan Zhang

Abstract read
In one paragraph

Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

38 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  7. Identifying New Loci and Genes Associated with Feed Efficiency in Broilers.International journal of molecular sciences · 2025
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  13. Animals : an open access journal from MDPI · 2022
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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

8 authors.

Zhenqiang XuGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China.
Congliang JiWen's Nanfang Poultry Breeding Co. Ltd, Guangdong Province, Yunfu, 527400, China.
Yan ZhangWen's Nanfang Poultry Breeding Co. Ltd, Guangdong Province, Yunfu, 527400, China.
Zhe ZhangGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China.
Qinghua NieGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China.
Jiguo XuGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China.
Dexiang ZhangGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China.
Xiquan ZhangGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China. xqzhang@scau.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundResidual 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.

resultsA 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.

conclusionsThe 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.

Indexed as

Animal FeedGene Expression ProfilingGenome-Wide Association StudyTranscriptomeAnimalsChickensDatabases, GeneticHaplotypesHigh-Throughput Nucleotide SequencingLinkage DisequilibriumPhenotypePolymorphism, Single NucleotideQuantitative Trait, HeritableQuantitative Trait LociGenome-wide association studyQuality chickensResidual feed intakeRNA-sequencing

Identifiers

PMID27506765
PMCPMC4979145

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Registered trials

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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.