Study Notes on Chicken Hypothalamic and Ovarian DNA Methylome Alteration in Response to Forced Molting

Citation Information

  • Zhang, T.; Li, C.; Deng, J.; Jia, Y.; Qu, L.; Ning, Z. Chicken Hypothalamic and Ovarian DNA Methylome Alteration in Response to Forced Molting. Animals 2023, 13, 1012. https://doi.org/10.3390/ani13061012

  • Copyright © 2023 by the authors. Licensee MDPI, Basel, Switzerland.

  • License: Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Contributors

  1. Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China

  2. Hubei Shendan Healthy Food Co., Ltd., Xiaogan 432600, China

  3. Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100091, China

  4. National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China

  5. State Key Laboratory of Animal Nutrition, Beijing 100193, China

  • Correspondence: ningzhh@cau.edu.cn

Simple Summary

  • Definition of Forced Molting:

    • Systemic stress response in laying hens caused by artificially imposed measures (i.e., starvation).

    • Consequences: Production suspension, weight loss, and molting.

    • Recovery phase includes a return to normal feeding conditions leading to restored egg-laying rates (ELR) potentially reaching a second peak of production (SPEP).

  • Shift in Understanding:

    • Previous belief that only genes at the transcriptome level regulate this reversible process.

    • Findings suggest interrelation of epigenetic factors and genetics in regulating the process.

Abstract

  • Context: Epigenetic modifications are critical for animal adaptation to external stress.

  • Focus: How DNA methylation influences gene expression during the forced molting of laying hens.

  • Methodology: Analysis of hypothalamus and ovary tissues at five stages via Whole-Genome Bisulfite Sequencing (WGBS).

  • Findings:

    • Methylation levels fluctuate in various genomic regions (exon, intron, UTRs, promoter, intergenic).

    • 16 differentially methylated genes (DMGs) identified that influence cellular aging, immunity, and development during starvation and redevelopment phases.

    • Identification of five hypermethylated DMGs (DSTYK, NKTR, SMOC1, SCAMP3, ATOH8) that inhibit the expression of differentially expressed genes (DEGs), ultimately leading to restoration of reproductive function.

    • Concludes that epigenetic modifications regulate gene expression during forced molting, providing insights for optimizing forced molting technology.

Keywords

  • Forced molting, DNA methylation, Functional regions, Reproductive function, Chicken

Introduction

  • Importance of Poultry Industry in China:

    • Hen egg production timeline:

    • Begins at ~100 days, peaks (90% ELR) at ~150 days, gradually decreasing to 60% by one year.

    • Economic Considerations:

    • Feed-to-egg ratio impacts financial decisions regarding hen culling.

    • Forced molting technology as a crisis intervention to enhance hens' productive lifespan, improve ELR.

  • Forced Molting - Characterization:

    • Systemic stress response from external measures (fasting) results in egg production halt and weight loss.

    • Recovery leads to increase in ELR and egg quality.

  • Challenges:

    • High mortality rates during molting (up to 30%); success defined as <0.2% mortality.

    • Prolonged time to return to productive peak increases feed costs.

  • Physiological Changes:

    • Hypothalamic–ovarian-gonadal axis increases secretions restoring metabolic function and reproductive health.

    • Aging and apoptosis in ovary and oviduct cells result in diminished reproductive capacity and delayed recovery post-molting.

Materials and Methods

Individual Selection and Tissue Collection

  • Experiment Details:

    • Chickens from previous studies based on estimated ELR at five time points.

    • 15 chickens (3 per time point) humanely euthanized; hypothalamic and ovarian tissues collected and frozen at −80°C.

    • Compliance with animal care guidelines (Approval ID: XXCB-20090209).

Animal Experimental Design

  • FM experiment overview based on previous studies.

  • Population: 44,079 Jingfen No. 6 laying hens at Hubei Shendan Company.

  • Sampling Points:

    1. 224 days - Initial peak ELR (0.941).

    2. 456 days - Peak reduction (0.774) followed by 12-day fasting with no water.

    • Environmental conditions: 8L:16D lighting, temperature 18.4°C, humidity 45.9%.

    1. 469 days - Average body weight loss ~30%.

    2. 500 days - Recovery phase (ELR at 0.472).

    3. Peak recovery phase (SPEP at ELR 0.873).

DNA Isolation and WGBS

  • DNA isolation from tissues using QIAamp Fast DNA Tissue Kit; quantification performed via Agilent 2100 spectrophotometer.

  • Bisulfite conversion and library preparation using Accel-NGS Methyl-Seq DNA Library Kit.

  • Sequencing on Illumina HiSeq 4000 platform achieved a coverage depth of 30×.

Data Filtering and Methylation Site Identification

  • Utilized SOAPnuke for quality filtering and BSMAP for mapping to Gallus_gallus-6.0 reference genome.

  • Methylation levels were quantified as ML=racmCmC+umCML = rac{mC}{mC + umC} where:

    • mCmC = methylated cytosines, umCumC = unmethylated cytosines.

Horizontal Distribution of Methylation

  • Analyzed methylation across CG, CHG, CHH contexts; identified distribution irregularities in genomic functional regions.

Differentially Methylated Regions (DMRs) and Functional Enrichment Analysis

  • DMRs identified using a sliding window analysis at various time points with Fisher’s test for significance (FDR < 0.05).

Results

Sequencing Data Statistics

  • Sequencing quality: clean reads > 176G, Q20 > 93%, Q30 > 87%, mapping rate > 84%.

Identification of Methylated C Sites and Distribution

  • Methylation ratio across 30 samples from hypothalamus and ovary tissues varied from 1.42% to 4.81%.

  • CG context methylation dominated at 76.45% to 94.49%, with CHG and CHH contexts considerably lower.

Cluster Analysis Between Samples

  • Cluster analyses indicate greater inter-group differences relative to intra-group differences across selected samples.

Distribution of Methylation Levels in Functional Regions

  • Variation observed in methylation levels within functional regions.

  • The promoter region generally displayed the lowest methylation levels.

DMR Detection

  • Identification of numerous DMRs with significant presence in 5'UTR and 3'UTR regions.

  • Most are hypo-methylated rather than hyper-methylated.

Identification of DMGs and Functional Enrichment Analysis

  • Annotation via Ensemble provided insights into hyper and hypo DMGs across different periods.

  • Identification of age-related DMGs linked to cellular processes such as senescence and development.

Conjoint Analysis of DEGs and DMGs

  • Joint analysis showed correlations between hypermethylated DMGs and reduced transcriptional levels of DEGs, focusing on significant gene candidates such as DSTYK, NKTR, SMOC1, and SCAMP3 associated with cellular development and immunity.

Discussion

  • Findings highlight dynamic changes in DNA methylation throughout FM, suggesting regulatory functions concentrated in specific genomic regions.

  • DMGs play a crucial role in managing aging conditions and enhancing reproductive isolation, establishing a foundation for FM optimization strategies.