Screening of Genes and Key Pathways Related to Egg-Laying in Kangle Yellow Chickens Based on Liver Transcriptome Sequencing

doi:10.7668/hbnxb.20194898

Abstract

Abstract:

The purpose of this study was to screen the candidate genes and key pathways related to traits at first laying through transcriptomic analysis of liver tissues on laying and non-laying Kangle yellow chickens,and to provide a theoretical basis for studying the molecular mechanisms of laying traits regulation in the liver of chickens.It also provides certain reference for the selection and breeding of Kangle yellow chickens.Three individuals of liver tissues at 154 days of age that had started laying (Group H) and had not started laying (Group L) were selected.Total RNA was extracted using the TRIzol method,and transcriptome sequencing was performed using the Illumina sequencing platform.Differentially expressed genes between the two groups were identified.The differentially expressed genes were subjected to functional enrichment and protein-protein interaction analysis.Nine candidate genes were randomly selected,and their expression levels were verified by qRT-PCR in the livers of the nine individuals.A total of 21 465 genes were detected to be expressed in the liver tissues,and a total of 227 differentially expressed genes were identified,among which 48 were up-regulated and 179 were down-regulated.The qRT-PCR validation results showed that the expression trends of nine genes in the two groups of individuals were basically consistent with the RNA-Seq results,and they showed a decreasing or increasing trend in the H,M(to be laid),and L three groups.Six candidate genes for the age at egg-laying trait were initially identified,namely VTG1,VTG2,VTG3,APOV1,RBP,and RNF186.The five crucial signaling pathways were fat digestion and absorption,cholesterol metabolism,ECM-receptor interaction,estrogen signaling pathway,D-glutamine and D-glutamate metabolism.Six genes and five key signaling pathways were preliminarily identified related to the traits at the first laying of Kangle yellow chicken.

Key words: Kangle yellow chicken, Liver, Candidate gene, Key pathway, Transcriptome sequencing, Egg-laying trait

CLC Number:

S831.2

MA Jinge, ZENG Peijun, WAN Shumin, XIONG Xinwei, WANG Zhangfeng, LIU Jing, XU Jiguo, RAO Yousheng. Screening of Genes and Key Pathways Related to Egg-Laying in Kangle Yellow Chickens Based on Liver Transcriptome Sequencing[J]. Acta Agriculturae Boreali-Sinica, 2025, 40(3): 207-214. doi: 10.7668/hbnxb.20194898.

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Figures/Tables 6

Tab.1 Primer sequence information

引物名称 Primer name	序列号 Accession numbers	引物序列(5'—3') Primer sequence(5'—3')		长度/bp Length
VTG1	NM_001004408.3	F:GAATTCCCGGGCAACTGCTA	R:TGCAAGTTTCTGCCTTGCTTC	157
VTG2	NM_001031276.2	F:ACAGCAAGGTCATTCGAGCA	R:CTCGGATGCCAACCTCTACC	171
VTG3	NM_001398307.1	F:TTGCTCAGTCGTGGGTCATC	R:CGAGTGTGGAGTCAGATGGG	216
APOV1	NM_205483.3	F:GAAAGCAGGACAGCAGGTCTC	R:GCCAGTCACGACGTTCTCTG	161
ITGB5	NM_204483.2	F:CCCGGCAGAGGTCTCAAC	R:GCTCAAGGGGACGTTCTTCA	225
RNF186	XM_004947482.5	F:TGCAGCATCTCTCGCTATGG	R:GAGCTTTGGGACCCGGTAAA	151
RBP	XM_046922434	F:GGCAGCTCAGTAAATCCTGTGA	R:CCGTCAGCCAGTTATGAGCA	195
LOC419888	XM_025143816.3	F:CTGCAACTGCTGTAGGACTCTT	R:GGCTCAGCAAGACAGTACCC	128
CETP	NM_001034814.3	F:ACGGTCACTATCCAAGCTGC	R:ACGGACTGGTCATTTCCACTT	119
β-actin	NM_205518.2	F:GCCGAGAGAGAAATTGTGCGTGAC	R:ACCACAGGACTCCATACCCAAGAAAG	210

Tab.2 Basic features of transcriptome sequencing

样品 Sample	过滤后reads Clean reads	高质量(≥Q30)数据占比/% Ratio of high-quality(≥Q30)data	序列总数 Total reads	比对百分比/% Mapped reads percentage
H-LIV-1	21 558 777	94.33	43 177 554	92.64
H-LIV-2	20 277 431	92.96	40 554 862	92.00
H-LIV-3	24 731 384	94.14	49 462 768	92.17
L-LIV-1	23 403 738	94.97	46 807 476	93.57
L-LIV-2	21 418 718	94.89	4 287 436	92.27
L-LIV-3	21 699 178	94.31	43 398 356	92.20

Fig.1 GO annotation classification of differentially expressed genes in group H and L The horizontal axis represents GO classification,while the vertical axis represents the number of genes,different colors represent different primary classifications.1.Single-organism process;2.Cellular process;3.Biological regulation;4.Metabolic process;5.Multicellular organismal process;6.Response to stimulus;7.Developmental process;8.Localization;9.Signaling;10.Cellular component organization or biogenesis;11.Immune system process;12.Multi-organism process;13.Reproduction;14.Reproductive process;15.Behavior;16.Growth;17.Locomotion;18.Rhythmic process;19.Detoxification;20.Biological adhesion;21.Presynaptic process involved in chemical synaptic transmission;22.Cell;23.Cell part;24.Organelle;25.Membrane;26.Organelle part;27.Membrane part;28.Macromolecular complex;29.Membrane-enclosed lumen;30.Extracellular region;31.Extracellular region part;32.Other organism;33.Other organism part;34.Synapse part;35.Synapse;36.Supramolecular complex;37.Cell junction;38.Binding;39.Catalytic activity;40.Transporter activity;41.Molecular transducer activity;42.Nucleic acid binding transcription factor activity;43.Signal transducer activity;44.Molecular function regulator;45.Transcription factor activity,protein binding;46.Structural molecule activity.

Fig.2 KEGG enrichment histogram of differentially expressed genes between group H and L 1.Fat digestion and absorption;2.Cholesterol metabolism;3.ECM-receptor interaction;4.Estrogen signaling pathway;5.D-Glutamine and D-glutamate metabolism;6.Butanoate metabolism;7.Glycosphingolipid biosynthesis-lacto and neolacto series;8.Vitamin digestion and absorption;9.Porphyrin and chlorophyll metabolism;10.Drug metabolism-cytochrome P450;11.Ferroptosis;12.PPAR signaling pathway;13.Metabolism of xenobiotics by cytochrome P450;14.Drug metabolism-other enzymes;15.Retrograde endocannabinoid signaling;16.Arginine and proline metabolism;17.Retinol metabolism;18.Nucleotide excision repair;19.Lysosome;20.Glutathione metabolism.

Fig.3 Protein interaction network of differentially expressed genes between group H and L The gene with larger node and the darker color represented it interacted with more genes.

Fig.4 qRT-PCR validation of candidate genes Different letters indicated a significant difference (P<0.05).

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