Age-associated changes in the shell gland transcriptomics and eggshell quality of broiler breeder hens

Abstract

The egg production cycle of broiler breeder hens is comparatively shorter than that of laying hens, and as they age, their egg productivity and eggshell quality decline. Eggshell formation occurs in the shell gland, which is influenced by several factors, including aging. The objectives of this study were to 1) determine the age-associated changes in eggshell quality and mineral compositions, and 2) identify differentially expressed genes (DEGs) and biological pathways in the shell glands (young vs aged). The shell gland tissues were collected from broiler breeder hens at peak-lay (35 weeks of age; termed as “young”) and late-lay phases (50 weeks of age; termed as “aged”) at 10–15 h post-ovulation (uncalcified egg present in the shell glands). To delineate the genes and biological pathways associated with eggshell biomineralization, total RNAs extracted from the shell glands of young and aged hens (n = 6/group) were analyzed using RNA sequencing and validated using quantitative PCR. The ultrastructure quality of eggshells (n = 10 eggs/group) was analyzed using a Scanning Electron Microscope (SEM), and the elemental composition of eggshells was measured using SEM-Energy Dispersive Spectrometry. The strength, thickness, and palisade layer of the eggshells were significantly greater in younger hens, while the mammillary knobs were wider in older hens. Additionally, the levels of sulfur and potassium in the eggshells were higher in the younger hens compared to the older ones. Although the young hens exhibited a higher concentration of calcium in their eggshells, the difference was not statistically significant. RNA-Seq data identified highly up-regulated genes in young hens specific to eggshell biomineralization, such as SPP1 (binds to hydroxyapatite), OTOP2 (maintains high concentration of cytosolic Ca²⁺), PKD2 (helps in releasing Ca²⁺), SLC22A15 (transports organic ions), and STAB2 (binds to gram-positive and gram-negative bacteria), which are downregulated in aged hens. The DEGs showed significant enrichment for biological pathways associated with the transport of monoatomic and inorganic cations across the cell membrane (SLC6A6, KCNK7, UCP3, SCNN1A, PKD2, OTOP2), molecular functions related to the transport of potassium ions and the activity of monoatomic cation channels (KCNK7, PKD2, OTOP2), and the cellular components involved in the luminal side of the endoplasmic reticulum membrane (CALR, PKD2). These findings suggest that aging downregulates the shell gland transcriptomes involved in eggshell biomineralization, reducing ion transport required for eggshell formation and resulting in poor eggshell quality.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-026-12801-z.

Introduction

The increasing global population is driving up the demand for animal-sourced proteins. By 2050, poultry meat is projected to experience the highest demand [1]. Broiler breeder hens play a crucial role in supplying fertile eggs for day-old broiler chicks. Selective breeding has enhanced both the growth rates and hyperphagic tendencies of broiler chickens, and breeder hens similarly exhibit overeating, which can result in increased fat deposition and endocrine dysfunctions in an ad libitum feeding system [2]. Breeder hens often develop multiple ovarian follicles per day, leading to double ovulation and a rapid decline in ovarian reserves [2]. The production cycle of broiler breeder hens is relatively shorter than that of commercial egg layers, with egg-laying commencing around 25 weeks of age, peak production occurring between 30 and 35 weeks, and a decline starting after 50 to 55 weeks [3, 4]. The number of day-old chicks produced is the primary indicator of broiler breeders’ reproductive efficiency. As reported by the USDA (2024), approximately 12 billion eggs are incubated each year. A modest 1% decrease in hatchability can result in the loss of approximately 120 million day-old chicks, leading to substantial economic repercussions. This ongoing trend of declining hatchability may further exacerbate these economic losses [5]. Hatchability rates were 85% in January 2012, 81.75% in January 2018, and dropped to a low of 79.7% in January 2024 [6, 7]. This declining trend highlights the urgent need to address hatchability issues, which are significantly affected by egg quality and the age of broiler breeder hens [8, 9].

Egg quality is assessed through external factors, such as the eggshell, and internal factors, such as the albumen and yolk. Eggshell quality is crucial for structural strength, providing nutrients for embryo development and hatchability. Their complex structure controls water loss and gas exchange, which enhances hatchability. Furthermore, eggshells act as a mineral reservoir for the developing embryo [10]; therefore, their appropriate composition could be instrumental in hatchability. Thinner eggshells heat up faster than thicker ones, leading to uneven hatching times. Weaker-shelled eggs need careful handling, transport, and storage to reach the incubator safely [7–9].

The egg formation in hens starts in the ovary (yolk), and as it descends through the oviduct, it receives the rest of the egg components. The segments of the oviduct, the infundibulum (receives the ova), magnum (synthesizes and secretes albumin), isthmus (secretes eggshell membrane), shell gland (deposits eggshell), and vagina (that holds the egg before oviposition), make a complete egg at the end of 24–26 h [11]. Eggshell biomineralization in the shell gland combines minerals with organic matter, molding them into mineral-rich eggshells. A study focused on layer hens has revealed that minerals are actively transported to the shell gland through circulation. This process is facilitated by specific genes, including OTOP2, CALCB, STC, and ATP2C2, as well as various pathways [12]. The minerals are primarily transported in ionic form through the apical membrane of uterine cells into the uterine fluid. After the formation of amorphous calcium carbonate in the extracellular intrauterine milieu, their transport to the point of eggshell deposition has been theorized to occur via vesicles [13]. Calcium is transported from the intestine and bones into the blood, then to the uterine tissues, which are also regulated by various hormones [14–16]. The mechanisms of eggshell biomineralization in the uterus of broiler breeder hens are not well understood. Additionally, the age-related variations in uterine gene expression and their effects on eggshell quality and ultrastructure remain unclear. We hypothesized that analyzing the uterine transcriptome and the ultrastructure of eggshells from young and older hens would provide insights into the genetic and structural factors that influence egg quality, which could help identify breeder hens that produce higher-quality eggs.

Methodology

Experimental design and tissue collection

All animal experimentations were carried out in accordance with the guidelines approved by the Institutional Animal Care and Use Committee of the University of Hawaii. Sixty Cobb-500 broiler breeder hens were raised in a broiler breeder facility following the guidelines set out by the Cobb rearing system. Hens were selected from two different age groups. The breeders at their peak production (30–35 weeks) were designated as the “Young” (n = 30) group, while those in a declining phase (50–55 weeks) were considered as the “Aged” (n = 30) group. Hens were euthanized by cervical dislocation using the Koechner Euthanizing Device (KED) [17, 18]. Sixty uterine samples were collected for analysis. Out of these, 18 young breeder hens and 12 aged breeder hens were estimated to have eggs under biomineralization in their uteri based on the presence of a calcifying egg (10–15 h post-ovulation) [12]. Six samples from each group were randomly selected for RNA sequencing. The collected samples were immediately submerged in an RNA-later solution (Invitrogen, Carlsbad, CA) for safe transport and handling, and remained submerged at room temperature for three days. After discarding the RNA later solution, the samples were stored at −80 °C until analysis. Twelve fresh eggs were collected from each group to evaluate eggshell quality, ultramicroscopic properties, and biomineralization.

Measurement of eggshell strength

Shell-egg samples were collected as freshly laid and then stored at 4 °C for 48 h before assessing the shell strength. The assessment involved a static compression test using a texture analyzer (TA-XTplus; Texture Technologies, Hamilton, MA). The instrument was equipped with a 7.6 mm-diameter aluminum compression disc (TA-30, Texture Technologies) and a 5 kg load cell. The egg was placed on its side in an egg holder to measure compression strength, and a test speed of 2 mm/s and a trigger force of 0.001 kg were applied to break the eggshell [19]. Egg weight and eggshell weight were measured to evaluate their gross changes.

Evaluation of ultrastructure visualization and minerals measurement

The equator part of the eggshells was broken into smaller square pieces measuring 0.5 × 0.5 mm. Each piece, with a straight edge, was boiled in a 2% sodium hydroxide solution for 10 min. After boiling, the pieces were dried at room temperature on a desiccant for 24 h. The dried pieces were then mounted vertically on aluminum stubs using carbon paint. Finally, a gold–palladium sputter coater was used to coat the mounted eggshells. An angled stub holder was used to visualize the inner (mammillary) and outer (cuticular) layers in cross-section. A Scanning Electron Microscope (SEM) scale was used to measure the thickness of the eggshell and underlying layers.

An Energy-Dispersive Spectroscopy (EDS) system mounted on an SEM was used to estimate mineral concentrations across different layers of the eggshells. Three different regions in the eggshell thickness were used to determine mineral concentration. The method followed for eggshell preparation and visualization was developed by Mahato et al. (2024).

RNA isolation and quality assessment for RNA-Sequencing

Total RNA was isolated from the frozen tissues (100 mg) using TRIzol reagent (Invitrogen, Carlsbad, CA). The isolated RNA concentration and integrity were measured using NanoDrop One Microvolume UV–Vis Spectrophotometer (Thermo Fisher Scientific, USA) and Agarose gel electrophoresis (1.5%). An Agilent 2100 Bioanalyzer (Agilent Technologies, Massy, France) was used to determine RNA quality. Samples with RIN > 7 (RNA integrity number) were chosen for RNA sequencing and quantitative real-time PCR.

Library preparation

RNA samples were processed and sequenced at the University of Hawaii Cancer Center Genomics and Bioinformatics Shared Resource. The library preparation process follows a similar method used by Sah et al. (2018), where mRNA NGS libraries were prepared with NEBNext Ultra II Directional RNA Library Prep Kit (New England Biolabs), cDNA was adenylated at its 3’ ends, followed by ligation of indexing adapters specific for each sample. The DNA fragments were enriched using 12 PCR cycles. Libraries were pooled and denatured in freshly prepared 0.2N NaOH, then diluted with HT1 buffer to a final concentration of 1.8 pM. As a sequencing control, the library pool was spiked with 1% (v/v) of 1.8 pM denatured PhiX library and loaded onto the reagent cartridge. The sequencing run was performed on NextSeq 500 (Illumina) in paired-end mode with a read length of 76 bp. FASTQ files generated via Illumina BaseSpace were used for downstream analysis.

RNA-sequencing data analysis

Quality control of paired-end RNA-seq raw reads was performed using FastQC in a Linux environment to assess sequence quality, base composition, and adapter contamination. Adapter sequences and low-quality based (Phred score < 30) were trimmed using Trimmomatic [20], and reads with low average quality (Phred score < 30) or short length (< 20) after trimming were discarded. The resulting high-quality clean reads were aligned to the Gallus gallus reference genome (assembly bGalGal.mat.broiler.GRCg7b) using the splice-aware aligner HISAT2 [21]. Gene-level read counts were generated using HTseq-count [22] with the corresponding genome annotation file. Differential expression analysis comparing young and aged broiler breeder hens was conducted using DESeq2 [23] in RStudio. Genes with |log₂FoldChange|> 1 and padj ≤ 0.05 were considered differentially expressed Genes (DEGs). Further, filtering was performed on the raw data using a threshold of ≥ 20 read counts to define individual and group expression. Genes expressed exclusively in either the Young or Aged groups were classified as differentially expressed, while genes with ≥ 20 read counts in both groups were considered commonly expressed. The number of uniquely expressed genes may vary depending on the threshold used.

Gene Ontology and pathway analysis

DEGs were then used for Gene Ontology (GO) and pathway analysis in open data sources in DAVID [24] and Enrichr [25] where the Gallus gallus gene set served as the background. DEGs were uploaded in Enrichr to annotate three GO aspects: biological processes (BP), cellular components (CC), and molecular functions (MF). A - P-value <0.05 and a gene count > 2 were used as criteria. The networks were generated using IPA (QIAGEN Inc., https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis).

Quantitative real-time RT-PCR (qPCR)

The most significantly up-regulated and down-regulated genes predicted to be involved in eggshell biomineralization were selected for qPCR validation. Gene-specific primers were designed using NCBI's primer blast tool (primer sequences are shown in Supplementary Table 1).

The first strand cDNA was synthesized by reverse transcription of 1 μg total RNA (20 μL reaction of RT mixture) using High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA). cDNAs were further diluted with nuclease-free water (1:10), and 3μL per qPCR reaction was used. Gene expression was analyzed using PowerUp SYBR Green Master Mix (Applied Biosystems, Foster City, CA) on a QuantStudio 3 real-time PCR system (Applied Biosystems, Foster City, CA). Each 10 μL of PCR reaction mixture consists of 5 μL of PowerUp SYBR Green Mastermix, 1 μL of each forward and reverse primers, and 3 μL of cDNA. PCR reactions were carried out following the standard cycling mode. A melting curve was also generated to confirm the sequence-specific PCR product. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH), beta-actin (B-actin), and TATA-Box Binding Protein (TBP) were evaluated as candidate reference genes; based on their stability, TBP was used as the reference gene. All candidate genes were analyzed in duplicate, and expression levels were determined using normalized cycle threshold (Ct) values. The relative fold change for each gene was calculated using a 2^-ΔΔCt method and presented as the mean ± standard error.

Statistical Analysis

Statistical analysis was performed using R-studio. Data normality was tested using a Shapiro–Wilk test, and a log transformation was used to transform the data. A Student's t-test or a Welch two-sample t-test was performed, depending on the variability of the two groups (young and aged) being compared, as determined by the Levene test. Alternatively, a non-parametric, one-sided Mann–Whitney U test was performed. Eggshell elemental concentrations were compared across eggshell thickness regions (UP, LP, and M) (three groups) using One-way ANOVA; alternatively, the Kruskal–Wallis Test was used for non-normally distributed data.

Results

Eggshell quality

The eggshell characteristics indicate the external quality of the egg. This study conducted a thorough analysis and comparison of eggshell parameters between the young and aged groups. Young birds produced lighter eggs (P < 0.001) (Fig. 1A), while the eggshell weight remained constant at both time points (Fig. 1B). The eggshell strength significantly decreased (P < 0.001) in the older group (Fig. 1C), indicating a 30% loss in strength (5014g vs 3479 g). The evaluation of eggshells using a scanning electron microscope revealed that the inner mammillary layer and the outer effective thickness (comprising the cuticle and palisade) constituted the overall thickness of the eggshell (Fig. 2A). Overall thickness and palisade thickness were significantly lower (P < 0.05) in the aged (3.6% & 3.9%) (Figs. 2B and C). Age doesn’t affect mammillary thickness (P > 0.05), while the mammillary width was considerably higher (12%) (P = 0.02) in the aged breeder group. The knobs at the innermost layer of the eggshells were divided into two categories: normal knobs (Type-A) and B-type knobs. Knobs that are conical in shape, with rough surfaces and extend to the palisade are type-A, while those spherical-shaped, with smooth surfaces, and without extension to the palisade are B-type knobs. The representative mammillary knob count is presented in Figs. 3A and C. The normal type (Fig. 3B) and B-type knob (Fig. 3D) numbers (knob count/0.5mm²) were not affected by the age groups (P > 0.05).

Fig. 1.

Comparison of eggshell quality between young and aged. A egg weight, B Shell weight, and C shell strength. The X-axis represents experimental groups, and the Y-axis represents weight in grams; the error bar represents standard error (* indicates a significant value at the level of 0.05)

Fig. 2.

Comparison of eggshell ultrastructure between young and aged. A Ultramicroscopic structure of an eggshell thickness showing various regions, B Overall thickness, C Palisade thickness, D Mammillary thickness, and E Mammillary width. X-axis showing experimental groups, and Y-axis represents thickness measured in µm; the error bar represents standard error (* indicates significant value at the level of 0.05)

Fig. 3.

Ultramicroscopic view of innermost eggshell layer and knob counts; A Normal knob counting (type-A) (purple circles); B bar graphs showing normal-type knob count young vs aged; C B-type knob counting (purple circles); D bar graph showing B-type knob count young vs aged. The X-axis represents experimental groups, while the Y-axis represents knob count numbers (Knob number/0.5mm²); the error bar represents standard error

Eggshell elemental analysis

The eggshell elements were classified into three categories, namely, macro-minerals (Na, Mg, P, S, K, and Ca), micro-minerals (Mn, Fe, Cu, and Zn), and non-mineral elementals (Al, Si, V, and Ni). Among these, the average eggshell calcium composition was the highest (> 95% w/w), and V (Vanadium) was the lowest in concentration (< 0.05% w/w). In the comparison between young and aged groups, only Sulfur and potassium were significantly higher in young breeder hens (P < 0.05) (Fig. 4).

Fig. 4.

Eggshell composition of macro, micro, and non-mineral elements. The X-axis represents various eggshell elements divided into three groups, and the Y-axis represents the percentage (weight/weight). The superscripts a and b indicate a significant difference at p < 0.05 and are used for multiple comparisons; the error bar represents the standard error

The concentration of elements was compared among different regions (Upper Palisade (UP), Lower Palisade (LP), and Mammillary layer (M)) of the eggshell thickness (Table 1), showing that the calcium was significantly higher in the lower palisade. Phosphorus levels were highest in the upper palisade region for both young and aged hens, indicating a consistent deposition pattern. In contrast, potassium levels were higher in both the upper and lower palisade regions for young hens, while in aged hens, elevated potassium concentrations were observed only in the upper palisade. This suggests that the deposition patterns of potassium differ between young and aged hens. Magnesium concentrations varied between the young and aged groups in different eggshell layer level. In the aged group, the higher concentration was found in the M region, followed by the UP and LP regions. In contrast, the young group had a lower concentration in the LP region of the eggshells. Elemental concentrations of micro- and non-mineral components are shown in Tables 2 and 3, and their concentrations were low compared to macro minerals.

Table 1.

Macro mineral concentration (Na- Sodium, Mg- Magnesium, P- Phosphorus, S- Sulfur, K- Potassium, Ca- Calcium) of eggshell compared between three regions (UP-Upper palisade, LP-Lower palisade, and M- Mammillary region). One-way ANOVA was used to identify significant differences (* indicates p < 0.05). The superscript a, b, and c indicate a significant difference through column in each group (young and aged) and are used for multiple testing

Group		Na	Mg	P	S	K	Ca
Young	UP	1.39 ± 0.21	1.40 ± 0.10a	0.330 ± 0.032a	0.041 ± 0.015	0.124 ± 0.008a	95.03 ± 0.37b
	LP	0.93 ± 0.24	0.71 ± 0.04b	0.103 ± 0.021b	0.044 ± 0.015	0.095 ± 0.015a	96.61 ± 0.39a
	M	1.07 ± 0.15	1.40 ± 0.18a	0.053 ± 0.021b	0.041 ± 0.013	0.044 ± 0.015b	95.37 ± 0.47b
	Avg	1.13 ± 0.12	1.17 ± 0.09	0.162 ± 0.029	0.042 ± 0.008	0.088 ± 0.01	95.67 ± 0.27
UP/LP/M	P value	0.11	0.0005*	0.0003*	0.9	0.001*	0.03*
Aged	UP	1.27 ± 0.19a	1.43 ± 0.12b	0.28 ± 0.05a	0.043 ± 0.01	0.129 ± 0.009a	95.16 ± 0.49b
	LP	0.73 ± 0.15b	0.78 ± 0.07c	0.09 ± 0.01b	0.035 ± 0.012	0.066 ± 0.014b	96.82 ± 0.43a
	M	1.07 ± 0.17ab	1.95 ± 0.21a	0.16 ± 0.1b	0.026 ± 0.009	0.041 ± 0.016b	94.55 ± 0.69b
	Avg	1.02 ± 0.11	1.380.13	0.18 ± 0.04	0.035 ± 0.006	0.079 ± 0.011	95.51 ± 0.36
UP/LP/M	P value	0.04*	0.00007*	0.02*	0.55	0.0005*	0.021*

Table 2.

Micro mineral concentration (Mn- Manganese, Fe- iron, Cu- Copper, and Zn- Zinc) of eggshell was compared between three regions (UP-Upper palisade, LP-Lower palisade, and M- Mammillary region) One way ANOVA was used to identify the significant variation

Group		Mn	Fe	Cu	Zn
Young	UP	0.015 ± 0.01	0.030 ± 0.014	0.026 ± 0.013	0.021 ± 0.007
	LP	0.028 ± 0.015	0.038 ± 0.012	0.006 ± 0.006	0.021 ± 0.006
	M	0.034 ± 0.013	0.014 ± 0.007	0.044 ± 0.019	0.019 ± 0.010
	Avg	0.026 ± 0.007	0.027 ± 0.007	0.025 ± 0.008	0.020 ± 0.004
UP/LP/M	p value	0.52	0.31	0.185	0.71
Aged	UP	0.039 ± 0.015	0.038 ± 0.019	0.02 ± 0.014	0.015 ± 0.01
	LP	0.019 ± 0.009	0.016 ± 0.006	0.028 ± 0.01	0.028 ± 0.011
	M	0.021 ± 0.012	0.029 ± 0.009	0.014 ± 0.011	0.038 ± 0.016
	Avg	0.026 ± 0.007	0.028 ± 0.007	0.020 ± 0.007	0.027 ± 0.007
UP/LP/M	p value	0.66	0.56	0.204	0.38

Table 3.

Micro mineral concentration (Al- Aluminum, Si- Silicon, V- Vanadium, and Ni- Nickel) of eggshell was compared between three regions (UP-Upper palisade, LP-Lower palisade, and M- Mammillary region) One way ANOVA was used to identify the significant variation

Group		Al	Si	V	Ni
Young	UP	0.87 ± 0.1	0.59 ± 0.22	0.030 ± 0.013	0.091 ± 0.020
	LP	0.83 ± 0.11	0.52 ± 0.26	0.010 ± 0.007	0.048 ± 0.020
	M	1.17 ± 0.27	0.66 ± 0.28	0.024 ± 0.011	0.058 ± 0.023
	Avg	0.96 ± 0.1	0.59 ± 0.14	0.021 ± 0.006	0.066 ± 0.012
UP/LP/M	P value	0.59	0.67	0.634	0.185
Aged	UP	0.77 ± 0.09	0.7 ± 0.26	0.016 ± 0.008	0.093 ± 0.027
	LP	0.75 ± 0.09	0.6 ± 0.3	0.009 ± 0.005	0.039 ± 0.023
	M	0.97 ± 0.26	1.05 ± 0.42	0.005 ± 0.005	0.081 ± 0.022
	Avg	0.83 ± 0.1	0.78 ± 0.19	0.010 ± 0.004	0.071 ± 0.014
UP/LP/M	P value	0.59	0.29	0.34	0.21

DEGs in young broiler breeder uterine tissue

RNA-seq data were analyzed to find the transcriptomic variation among young (35 weeks) broiler breeder hens when they are in peak production and aged (50 weeks) when they are in declining production. Raw FASTQ reads were filtered using FastQC, and an Ensemble alignment for avian genome assembly was used to annotate, resulting in the annotation of 29,558 gene transcripts. From the DESeq2 analysis of young versus aged samples, 75 up-regulated and 43 down-regulated differentially expressed genes (DEGs) were identified, as illustrated in a volcano plot (Fig. 5A). The top differentially expressed genes of the individual samples are shown in the Heat Map (Fig. 5B). The number of uniquely expressed genes in young and aged hens is shown in the supplementary file, represented by a Venn diagram in sheet 4.

Fig. 5.

A Differentially Expressed Genes (DEGs) Young vs Aged (Selection based on Padj < 0.05 and log2FoldChange> |1|) and Volcano plot showing up-regulated (red), down-regulated (blue), and insignificant genes (black) B Heatmap of the top highly up-regulated and down-regulated genes expressed in individual samples

The most up-regulated and the most down-regulated genes that are predicted to be involved in eggshell biomineralization are listed in Tables 4 and 5, respectively. Among them, TM4SF19 is the most highly up-regulated gene in young broiler hens, followed by KAT2B, SPP1, SEPTIN3, NDUFAF5, ARVCF, SMIM45, NPTN, OTOP2, PKD, DMRTB1, USH1G, MLLT1, SLC22A15, etc. Similarly, XIRP1 is the most highly down-regulated gene followed by NXNL2, ETNK2, PLA2G15, NELFA, HS3ST3B1, TAPBPL, CLP1, SCNN1A, CLNS1A, GFRA1, SLC43A2, HPRT1, MMS22L, CDC5L, LAMB4, CNTRL, USHBp1, RPL9.

Table 4.

The top 30 most upregulated genes in the uterus of young broiler breeders in comparison to aged hens. The p adj < 0.05 and log2fold change >|1| were considered significant

Gene Name	Description	log2FC
TM4SF19	Transmembrane 4 L six family member 19	7.22
KAT2B	Lysine acetyltransferase 2B	5.23
SPP1	Secreted phosphoprotein 1	4.96
SEPTIN3	Septin 3	4.44
NDUFAF5	NADH:ubiquinone oxidoreductase complex assembly factor 5	4.09
ARVCF	Armadillo repeat deleted in velocardiofacial syndrome	3.92
SMIM45	Small integral membrane protein 45	3.73
NPTN	Neuroplastin	3.44
OTOP2	Otopetrin 2	3.32
PKD2	Polycystin 2, transient receptor potential cation channel	3.31
DMRTB1	DMRT like family B with proline rich C-terminal 1	3.12
USH1G	USH1 protein network component sans	3.06
MLLT1	MLLT1 super elongation complex subunit	3.04
SLC22A15	Solute carrier family 22 member 15	3.03
DCBLD2	Discoidin, CUB and LCCL domain containing 2	3.02
TFCP2L1	Transcription factor CP2 like 1	2.97
ELOVL	ELOVL fatty acid elongase 5	2.82
CLIP1	CAP-Gly domain containing linker protein 1	2.79
DERA	Deoxyribose-phosphate aldolase	2.68
ST3GAL3	ST3 beta-galactoside alpha-2,3-sialyltransferase 3	2.66
CMKLR1	Chemerin chemokine-like receptor 1	2.57
STAB2	Stabilin 2	2.53
LTN1	Listerin E3 ubiquitin protein ligase 1	2.46
SLA	Src like adaptor	2.41
VGLL2	Vestigial like family member 2	2.39
ELL	Elongation factor for RNA polymerase II	2.39
KANK4	KN motif and ankyrin repeat domains 4	2.24
TSKU	Tsukushi, small leucine rich proteoglycan	2.22
PDHA2	Pyruvate dehydrogenase (lipoamide) alpha 2	2.18
ALDH1L2	Aldehyde dehydrogenase 1 family member L2	2.12

Table 5.

The top 30 most down-regulated genes in the uterus of young broiler breeder hens in comparison to aged hens. The p adj < 0.05 and log2fold change >|1| were considered significant

Gene Name	Gene description	log2FC
XIRP1	Xin actin binding repeat containing 1	−4.21
NXNL2	Nucleoredoxin like 2	−3.48
ETNK2	Ethanolamine kinase 2	−3.47
PLA2G15	Phospholipase A2 group XV	−3.09
NELFA	Negative elongation factor complex member A	−2.62
HS3ST3B1	Heparan sulfate-glucosamine 3-sulfotransferase 3A1	−2.49
TAPBPL	TAP binding protein like	−2.32
CLP1	Cleavage and polyadenylation factor I subunit 1	−2.14
SCNN1A	Sodium channel epithelial 1 alpha subunit	−2.12
CLNS1A	Chloride nucleotide-sensitive channel 1A	−2.08
GFRA1	GDNF family receptor alpha 1	−2.03
SLC43A2	Solute carrier family 43 member 2	−2.03
HPRT1	Hypoxanthine phosphoribosyltransferase 1	−2.03
MMS22L	MMS22 like, DNA repair protein	−2.00
CDC5L	Cell division cycle 5 like	−1.98
LAMB4	Laminin subunit beta 4	−1.91
CNTRL	Centriolin	−1.82
KCNK7	Potassium two pore domain channel subfamily K member 1	−1.80
USHBP1	USH1 protein network component harmonin binding protein 1	−1.79
RPL9	Ribosomal protein L9	−1.79
RAB11A	RAB11A, member RAS onco family	−1.63
TSSC4	Tumor suppressing subtransferable candidate 4	−1.62
HNF1A	HNF1 homeobox A	−1.61
MGME1	Mitochondrial genome maintenance exonuclease 1	−1.55
PSMD10	Proteasome 26S subunit, non-ATPase 10	−1.55
TMEM62	Transmembrane protein 62	−1.55
DALRD3	DALR anticodon binding domain containing 3	−1.52
MMP11	Matrix metallopeptidase 11	−1.41
NCEH1	Neutral cholesterol ester hydrolase 1	−1.41
TIE1	Tyrosine kinase with immunoglobulin like and EGF like domains 1	−1.41

Functional annotation and pathways enrichment analysis of DEGs

The GO terms Monoatomic cation transmembrane transport, Inorganic cation transmembrane transport, Organic cation transport, Sodium ion transport, and Carboxylic acid transport are enriched as BP, which are related to genes SLC6A6, KCNK7, UCP3, SCNN1A, PKD, OTOP2, and SLC43A2 (Table 6). Similarly, Cellular Component terms involve the luminal side of the endoplasmic reticulum membrane and the cation channel complex and are governed by genes CALR, PKD2, and SCNN1A. The genes SLC6A6, SLC43A2, SLC19A2, KCNK7, PKD2, SCNN1A, OTOP2, and UCP3 are closely associated with MF GO terms carboxylic acid transmembrane transporter activity, Potassium ion transmembrane transporter activity, Sodium channel activity, monoatomic cation channel activity, and proton transmembrane transporter activity (Table 6). IPA top canonical pathways show that the BEX2 Signaling Pathway (HNF1A, LEF1, SPP1) is the most enriched pathway with equal chances of activation and inhibition. The HOTAIR regulatory Pathway (HNF1A, LEF1, SPP1, STK38) is the second most enriched pathway and is predicted to be activated. These pathways are followed by Guanine and Guanosine Salvage I (HPRT1) and the role of OCT4 in Mammalian Embryonic Stem Cell Pluripotency (MEF2A, SPP1) (Table 7) with an equal chance of activation or inhibition.

Table 6.

Gene Ontology enrichment analysis of differentially expressed genes in the uterus of young and aged broiler breeder hens. 118 differentially expressed genes were subjected to Enrichr database for Gene Ontology (GO) enrichment analysis. All GO terms with a modified Fisher Exact P-value < 0.05 and the threshold gene count of 2, and the odd ratio > 2 were considered enriched

Gene Ontological term: Biological Processes	Genes involved	Odd ratio
Monoatomic Cation Transmembrane Transport (GO:0098655)	SLC6A6; KCNK7; UCP3; SCNN1A; PKD2; OTOP2	3.9
Inorganic Cation Transmembrane Transport (GO:0098662)	SLC6A6; KCNK7; UCP3; SCNN1A; PKD2; OTOP2	3.8
Sodium Ion Transmembrane Transport (GO:0035725)	SLC6A6; SCNN1A; PKD2	6.6
Organic Cation Transport (GO:0015695)	SLC22A18; SLC19A2	11.9
Sodium Ion Transport (GO:0006814)	SLC6A6; SCNN1A; PKD2	6.1
Gene Ontological term: Cellular Components	Gene involved	Odd ratio
Lumenal Side Of Endoplasmic Reticulum Membrane (GO:0098553)	CALR; PKD2	13.8
Cation Channel Complex (GO:0034703)	SCNN1A; PKD2	6.8
Gene Ontological term: Molecular Function	Gene involved	Odd ratio
Carboxylic Acid Transmembrane Transporter Activity (G:0046943)	SLC6A6; SLC43A2; SLC19A2	9.3
Potassium Ion Transmembrane Transporter Activity (GO:0015079)	KCNK7; PKD2	11.9
Sodium Channel Activity (GO:0005272)	SCNN1A; PKD2	9.9
Monoatomic Cation Channel Activity (GO:0005261)	KCNK7; PKD2; OTOP2	5.1
Proton Transmembrane Transporter Activity (GO:0015078)	UCP3; OTOP2	8.0

Table 7.

Significant canonical pathways involved in the eggshell formation in the broiler breeder hen uterus. All differentially expressed genes were used in Ingenuity Pathway Analysis, and significant canonical pathways based on IPA scores were identified

Ingenuity Canonical Pathways	Molecules	-log10(p-value)	Ratio
BEX2 Signaling Pathway	HNF1A,LEF1,SPP1	2.15	3.66E-02
HOTAIR Regulatory Pathway	HNF1A,LEF1,SPP1,STK38	2.11	2.45E-02
Guanine and Guanosine Salvage I	HPRT1	1.85	3.33E-01
Role of OCT4 in Mammalian Embryonic Stem Cell Pluripotency	MEF2A,SPP1	1.69	4.35E-02
Phototransduction Pathway	GNGT2,GUCY2F	1.56	3.70E-02
NAD Biosynthesis III, NAD Salvage Pathway III	NMNAT1	1.55	1.67E-01
MSP-RON Signaling In Cancer Cells Pathway	ELK3,HNF1A,LEF1	1.53	2.14E-02
Acetyl-CoA Biosynthesis I (Pyruvate Dehydrogenase Complex)	PDHA1	1.48	1.43E-01
Colorectal Cancer Metastasis Signaling	HNF1A,LEF1,RHOT1,STAT1	1.39	1.48E-02
Insulin Secretion Signaling Pathway	HNF1A,PDHA1,SCNN1A,STAT1	1.39	1.47E-02
Phosphatidylethanolamine Biosynthesis II	ETNK2	1.38	1.11E-01
Chronic Myeloid Leukemia Signaling	HNF1A,LEF1,MECOM,SPP1	1.36	1.44E-02
Basal Cell Carcinoma Signaling	HNF1A,LEF1	1.33	2.78E-02

In the IPA gene network named Auditory disease, Neurological disease, organismal injury, and abnormalities include significantly enriched molecules ACTR1A, ASPSCR1, CALR, CDC5L, CNTRL, DMRTB1, GMCL1, GNGT2, GUCY2F, HNF1A, HPRT1, KAT2B, MECOM, NDUFAF5, NMNAT1, PPIL2, RAB11A, RBM14, SCNN1A, STAB2, STK38, TFCP2L1, TRMT6, TSSC4, USH1G, and USHBP1 (Fig. 6).

Fig. 6.

Gene networks highlighting candidate genes and their interactions in broiler breeder hens, potentially regulating calcium ion transport during eggshell biomineralization, derived from QIAGEN’s Ingenuity Pathway Analysis. Gene Network: Hematological system development and function, hematopoiesis, tissue morphology. Differentially expressed genes in breeder broiler hens were used in IPA, and significant gene networks based on IPA scores were identified

The enriched pathways for the differentially expressed genes in a young broiler breeder’s uterus were analyzed using the open-source, open-access, manually curated, and peer-reviewed pathway database “Reactome” [26]. Differentially expressed genes were uploaded to the Enrichr system, with chicken genes as the background. A threshold gene count of 2 and a Fisher's Exact P-value < 0.05 were the criteria for the enriched pathways. “Organic Cation Transport,” “Organic Cation/Anion/Zwitterion Transport,” “Transport of Small Molecules,” “Transport of Bile Salts and Organic Acids, Metal Ions and Amine Compounds,” and “Ca^2 + Pathway” are related to mineral and ion transport (Table 8).

Table 8.

Significant Reactome pathways involved in the eggshell formation in the broiler breeder hen uterus. 118 differentially expressed genes were used in Enrichr, and significant Reactome pathways based on modified Fisher Exact P-value < 0.05, and gene count of ≥ 2 were considered enriched

Term	Genes	Odds Ratio
Organic Cation Transport R-HSA-549127	SLC22A15;SLC22A18	43.2
Organic Cation/Anion/Zwitterion Transport R-HSA-549132	SLC22A15;SLC22A18	26.6
Transport Of Small Molecules R-HSA-382551	PSMD10;TRPC;SLC6A6;NCEH1;SLC22A15;GNGT2; SLC43A2;SLC22A18;SCNN1A;RAB11A	2.6
Transport Of Bile Salts and Organic Acids, Metal Ions and Amine Compounds R-HSA-425366	SLC6A6;SLC22A15;SLC22A18	6.2
Ca2 + Pathway R-HSA-4086398	GNGT2;LEF1	5.8

Validation of DEGs using qPCR

Analysis of RNA-Seq data identified differentially expressed genes in the uterus of broiler breeder hens. To determine their unique expression in young broiler breeder uterine tissue, twenty-three candidate genes predicted to be involved in eggshell biomineralization were selected for qPCR validation. Housekeeping genes GAPDH, Beta-actin, and TBP were analyzed; among them, TBP was the most stable and therefore used for normalization. 2^−ΔΔCt values were calculated and analyzed, and eight genes were identified as significantly altered due to age (Fig. 7). The RNA-seq results followed a similar trend to the qPCR fold-change data (Supplementary Excel file 2: DEGs and qPCR values).

Fig. 7.

Validation of gene expression in young and aged breeder broiler hens using qPCR. Data represented as the mean ± SE. The X-axis represents the experimental groups (Young, Aged), and the Y-axis shows the relative fold change in gene expression, normalized to TBP, a housekeeping gene. The error bar represents standard error, and asterisk indicates significant change of gene expression due to the age

Discussion

Eggshell quality (Thickness and strength)

The integrity of an eggshell is crucial for withstanding the challenges of handling and storage. Even a minor crack can render the egg unsuitable for hatchery use, underscoring the need for stronger shells to ensure the production of high-quality chicks. While egg weight increases with age, shell weight remains relatively constant, which is in line with a previous study [27]. The results of this study indicate that eggshell thickness and strength are significantly greater in eggs from younger hens compared to those from older hens. This observation may be attributed to the notably higher palisade thickness and reduced mammillary width in the younger eggshell group. Furthermore, a positive correlation has been established between eggshell thickness and strength, suggesting that an increase in thickness, potentially resulting from enhanced palisade development, contributes to improved structural integrity [28, 29].

Mammillary knobs are essential components of the eggshell, as they directly contact the inner membrane and contribute to its strength. Keratan sulfate plays a crucial role in eggshell formation and significantly influences knob density [30]. Calcite crystals initially form around the keratan sulfate, leading to knob development, and as they grow, adjacent knobs merge, promoting upward growth. Narrower knobs are linked to greater density and more interstitial space, enhancing the eggshell's structural integrity [31]. Wider knobs typically have fewer connections to the shell membrane, but the older and younger groups in this study did not show a significant difference in the number of knobs, yet the younger group maintained their strength. These knobs are primarily elliptical shaped; breaking the eggshell can reveal either axis of the knob. A lower concentration of Sulphur might be affecting the calcite crystal orientation and the breaking axis, exposing the wider axis of the elliptical knobs in aged hens. Cracks in the eggshell start at the mammillary layer [32], varying Sulphur might be affecting the breaking strength by changing the breaking axis. While normal knobs contribute to shell strength, the function of B-type knobs is still unclear. These knobs are exposed to shell membranes, which may provide essential minerals for the developing embryo, potentially leading to higher-quality day-old chicks from younger hens. Further research is needed to confirm this. In contrast, a higher count of B-type knobs in older commercial layer hens may indicate aging [33].

The eggshell elements are essential for maintaining the integrity [34, 35]. Calcium makes up more than 95% of minerals. Despite the variation in strength, Calcium concentration in young and aged breeder hens’ eggshells was similar, indicating the involvement of various factors in eggshell strength [36]. Breeders might have been using all available calcium sources to prevent shell calcium deficiency. As bone is the richest source of calcium, osteoporosis is observed in aged laying hens. Despite attempts to balance all minerals during eggshell formation, breeder hens may lack adequate sources of other minerals, leading to deficiencies in the aged group.

This study found that while eggshell thickness varied, shell weight remained consistent, suggesting that both groups contained equal amounts of eggshell material. Thus, calcium concentration alone may not determine eggshell strength. Phosphorus serves as a crystallization inhibitor [37]. Its highest concentration in the outer layer of the eggshell was found in both young and aged birds, indicating the completion of biomineralization. A critical level of phosphorus is necessary for this process to terminate [38]. In this study, both Young and aged birds showed an increase in phosphorus at the end of biomineralization, indicating termination of crystallization.

Eggshells contain sulfur in two main proteoglycans: keratan sulfate, which initiates eggshell formation, and dermatan sulfate, which aids in growth and calcite crystal orientation [39]. In vitro studies have shown that varying sulfur concentrations in the calcite mixture can affect crystal orientation [40]. Stronger eggshells in younger groups may be due to higher sulfur concentrations affecting this orientation. Potassium is involved in the Na⁺/K⁺ ATPase pump, which facilitates calcium secretion into the extracellular intrauterine lumen, which is essential for calcium carbonate formation and is supported by the sodium-calcium exchanger (NCX) [41]. The Na +/K + ATPase pump expels sodium ions that are imported into the cell. Higher potassium levels in younger individuals may indicate more efficient calcium secretion in the shell gland. Additionally, potassium supplementation improves acid–base balance in laying hens, enhancing eggshell quality [42]. Dietary supplements containing trace minerals such as manganese, copper, and zinc enhance fracture toughness and eggshell-breaking strength [43]. In hens, higher manganese supplementation enhances genetic expression related to glycosylation and glycan metabolism (MGAT5, FMOD, GALNT2, GALNT18, and GCNT3), thereby contributing to the formation of mammillary nucleation points and increasing the number of mammillary knobs. The non-mineral elements are present in trace amounts (< 1%) and have unknown functions. This study found that as breeders transition from peak to declining production, eggshell thickness decreases by 3%, and mammillary width increases by 12%. In addition, the decrease in sulfur and potassium concentrations could potentially lead to a 30% decline in eggshell strength. Further research is needed to investigate how variations in sulfur concentration influence crystal orientation, width, and the angles between crystal clusters.

Genes and pathways associated with calcium mobilization and deposition (TM4SF19, SPP1, NPTN, OTOP2, CMKLR1)

To delineate the mechanism of eggshell biomineralization, we analyzed the genes and pathways associated with calcium transport, biomineralization, and deposition around the egg. Calcium necessary for eggshell formation is transported and secreted in the intrauterine lumen. Birds demonstrate efficient biomineralization, absorbing calcium from the small intestine and bones. Osteoclasts, bone macrophages, resorb calcium, making it available in the bloodstream. The TM4SF19 gene encodes a protein that regulates osteoclast differentiation, influencing calcium reabsorption and bone resorption [44]. Higher TM4SF19 expression in young breeder hens indicates increased calcium handling compared to older breeders, whose lower expression may be a protective response to osteoporosis in longer production cycles.

The SPP1 (Secreted Phosphoprotein 1) gene in chickens is exclusively expressed in uterine tissues and is linked to the formation of bone and eggshell organic matrices. It has a high affinity for hydroxyapatite, contributing to eggshell strength. Upregulation of SPP1 in younger ducks correlates with increased eggshell strength [45], making it a key indicator of durability. The gene encodes a sulfur-containing protein that contains cysteine and threonine. The higher sulfur concentration in younger eggshells further supports the gene’s role in enhancing strength. NPTN, a neuroplastin involved in the expression of the Plasma Membrane Calcium ATPase (PMCA) gene, plays a crucial role in hearing and the function of hair cells. Lower NPTN levels reduce PMCA expression, raising intracellular calcium levels [46]. In contrast, higher NPTN expression in young breeder eggshell glands increases PMCA expression, thereby facilitating the secretion of extracellular calcium into the uterus [47]. Additionally, NPTN has an immunoglobulin-like domain that may provide antimicrobial protection for the egg contents [48].

Mechanoreceptors and calcium secretion (PKD2, USH1G)

PKD2 is a non-selective cation channel with high calcium (Ca ^+ +) permeability found in human term syncytiotrophoblasts [49]. It has been suggested that, along with PKD1, PKD2 acts as a mechanosensory receptor in mouse embryonic kidneys, triggering calcium release from the endoplasmic reticulum through calcium-induced calcium release (CICR) [50]. In young breeders, upregulation of PKD2 in uterine tissue may enhance calcium sequestration. Additionally, layer hens show upregulation of the CALCB gene, which is involved in calcium release [12]. In developing chicken embryos, it is hypothesized that the PKD2 expression decreases due to increased intracellular calcium levels [10]. USH1G is linked to hearing and vision disorders [51] and is regulated by SANS, a scaffold protein that maintains the mechanotransduction complex in the ear [52]. The displacement of hair cells by sound waves activates calcium and potassium channels [53]. USH1G expression in uterine tissue may facilitate calcium influx during egg development. Its upregulation in young breeders’ eggshell glands compared to older ones may indicate greater calcium movement, which positively impacts eggshell quality.

The OTOP2 domain proteins include OTOP1, OTOP2, and OTOP3, which are essential for intracellular calcium trafficking [54]. OTOP2 has been suggested to increase calcium levels in the laying hen uterus, aiding in eggshell biomineralization [12]. Upregulation of OTOP2 in young uterine RNA sequencing might enhance intracellular calcium translocation, benefiting the biomineralization process. Further study is needed to validate this hypothesis and elucidate the role of OTOP2 in regulating eggshell biomineralization in the shell gland. Mesenchymal Stem Cells (MSCs) are multipotent cells found in various tissues that can differentiate into adipose tissue, osteoblasts, and connective tissue [55]. The CMKLR1 gene has been linked to directing MSCs towards osteoblasts in humans [56]. Research shows that CMKLR1 knockout mice have lower bone mineral density (BMD) than wild-type mice, which is associated with higher testosterone levels [57]. In older hens, decreased CMKLR1 expression in the shell gland may disrupt calcium uptake and transport, resulting in compromised eggshell formation and reduced shell quality. Further study is needed to understand the mechanism by which CMKLR1 mediates eggshell biomineralization.

Energy production and transcription regulation (ELL and MLLT1)

Transcription and translation are essential processes in gene expression, in which DNA is transcribed into RNA with the help of components such as RNA polymerase II. The genes ELL and MLLT1, which are integral to the Super Elongation Complex (SEC), play a significant role in RNA transcription [58]. Increased expression of ELL and MLLT1 indicates a more active SEC, leading to faster genetic responses to stress, hormones, or mechanical stretch. In eggshells, phosphorus concentration is higher in the upper palisade layer, with a notable increase in young eggs compared to older ones [38]. This rise could be linked to the rapid activation of phosphorus-secreting genes. The upregulation of ELL and MLLT1 in young breeders suggests enhanced control of phosphorus pathways, contributing to eggshell biomineralization.

Defense and antioxidation (ARVCF, SLC22A15)

ARVCF is a protein from the p120ctn (p120 catenin) family that interacts with cadherin proteins, specifically zona occludens (ZO-1 and ZO-2) and E-cadherins, forming complexes at cell–cell contact sites [59]. ZO proteins help bind actin filaments and signaling molecules, promoting cell–cell adhesion [60]. Cadherin proteins are crucial for embryo implantation, and deficiencies in CHD6 can lead to infertility [61]. ARVCF’s collaboration with catenins and cadherins suggests it plays a role in retaining eggs in the uterus, allowing calcium secretion before descent to the cloaca. As an egg swells in the uterus, higher ARVCF expression may enhance the adhesion between the uterine wall and eggshell membrane. This connection might support calcite crystal formation around the egg and improve the efficiency of eggshell biomineralization, resulting in thicker shells in young breeders. Stronger cell–cell adhesion also protects the shell gland from microbial infiltration and reduces energy expenditure on defensive chemicals. Additionally, this adhesion is linked to the domestication of animals and the plumage coloration of hens [62]. The aged animals have higher reactive oxygen species than antioxidants. The SLC22A15 gene encodes for the Organic Cation Transporter 2 (OCTN2), which transports carnitine into cells [63]. Carnitine is an antioxidant that enhances energy supply to uterine cells and has positive effects on human implantation, thereby improving fertility [64, 65]. In laying hens, carnitine supplementation mitigates the adverse effects of high stocking density [66]. Increased SLC22A15 expression in young breeders suggests efficient free-radical removal, which may increase energy and improve eggshell quality.

Conclusion

The eggshells of young breeders have thicker palisades, narrower mammillary regions, and higher sulfur and potassium concentrations, which support their strength, while micro minerals and non-minerals did not differ between shell regions. Uterine tissue RNA sequencing revealed DEGs and associated pathways; the putative functions have been divided into four categories: 1) Calcium mobilization and deposition (TM4SF19, SPP1, NPTN, OTOP2); 2) mechanoreceptors and calcium secretion (PKD2, USH1G); and 3) energy production and transcription regulation (ELL and MLLT1) 4) defense, and antioxidation (ARVCF, SLC22A15). Organic cation/anion/zwitterion transport (SLC22A15, SLC22A18) was the most enriched Reactome pathway obtained using Enrichr. The summary Fig. 8, shows the model that identified genes and predicted biological pathways involved in eggshell biomineralization and calcium transport in the broiler breeder hen shell gland. The TM4SF19 increases calcium release, while CMKLR1 might decrease the calcium erosion. PKD2 may activate Calcium-Induced Calcium Release (CICR), thereby releasing calcium from the endoplasmic reticulum into the cytosol. USH1G may act as a mechanoreceptor, increasing calcium influx upon stretching of the uterine tissue. ARVCF acts as an adherent junction protein, maintaining the tonic state of uterine tissue and reducing bacterial invasion. The SLC22A15 gene facilitates the intracellular transport of carnitine, thereby reducing the accumulation of free oxidative reagents. The PMCA might facilitate the transport of intracellular calcium into the extracellular intrauterine milieu for biomineralization (Created in BioRender. https://BioRender.com/4kk5ci8). The study identified ultramicroscopic characteristics of eggshells, differentially expressed genes (DEGs), and associated biological pathways that may serve as markers for selecting high-quality egg-producing breeder hens. The investigation into eggshell thickness and elemental composition yields novel findings that warrant further exploration to elucidate how various elements affect the orientation and strength of calcite crystals.

Fig. 8.

The proposed hypothetical model indicates identified genes and predicted biological pathways involved in eggshell biomineralization and calcium transport in the broiler breeder hen shell gland. (Created in BioRender. https://BioRender.com/4kk5ci8)

Abbreviations

ACTR1A

Actin Related Protein 1A

Al

Aluminium

ANOVA

Analysis of Varience

ARVCF

Armadillo Repeat Protein Deleted In Velo-Cardio-Facial Syndrome

ASPSCR1

Alveolar Soft Part Sarcoma Chromosomal Region Candidate Gene 1 Protein

ATP2C2

ATPase Secretory Pathway Ca^2 + Transporting 2

B-actin

Beta-actin

BEX2

Brain Expressed X-Linked 2

BMD

Bone mineral density

BP

Biological pathways

CA

California

Ca

Calcium

CALCB

Calcitonin Related Polypeptide Beta

CALR

Calreticulin

CC

Cellular components

CDC5L

Cell Division Cycle 5 Like

cDNA

Complementary deoxyribo nucleic acid

CHD6

Chromodomain Helicase DNA Binding Protein 6

CICR

Calcium-induced calcium release

CLNS1A

Chloride Nucleotide-Sensitive Channel 1A

CLP1

Cleavage Factor Polyribonucleotide Kinase Subunit 1

CMKLR1

Chemerin Chemokine-Like Receptor 1

CNTRL

Centriolin

Ct

Cycle threshold

Cu

Copper

DAVID

Database for annotation, visualization, and integrated discovery

DEGs

Differentially Expressed Genes

DMRTB1

DMRT Like Family B With Proline Rich C-Terminal 1

ELL

Elongation Factor For RNA Polymerase II

ETNK2

Ethanolamine Kinase 2

Fe

Iron

FMOD

Fibromodulin

GALNT18

Polypeptide N-Acetylgalactosaminyltransferase 18

GALNT2

Polypeptide N-Acetylgalactosaminyltransferase 2

GAPDH

Glyceraldehyde 3-phosphate dehydrogenase

GCNT3

Glucosaminyl (N-Acetyl) Transferase 3, Mucin Type

GFRA1

Glial Cell Line-Derived Neurotrophic Factor Receptor Alpha 1

GMCL1

Germ Cell-Less 1, spermatogenesis associated

GNGT2

G Protein Subunit Gamma Transducin 2

GO

Gene ontology

GUCY2F

Guanylate Cyclase 2F, Retinal

HNF1A

Hepatic Nuclear Factor 1 homeobox A

HOTAIR

HOX Transcript Antisense RNA

HPRT1

Hypoxanthine Phosphoribosyltransferase 1

HS3ST3B1

Heparan Sulfate-Glucosamine 3-Sulfotransferase 3B1

IPA

Ingenuity pathway analysis

K

Potassium

KAT2B

K(Lysine) Acetyltransferase 2B

KAT2B

Lysine Acetyltransferase 2B

KCNK7

Potassium Two Pore Domain Channel Subfamily K Member 7

KED

Koechner euthanizing device

LAMB4

Laminin Subunit Beta 4

LEF1

Lymphoid Enhancer Binding Factor 1

LP

Lower palisade

M

Mammillary

MECOM

MDS1 And EVI1 Complex Locus

MEF2A

Myocyte Enhancer Factor 2A

MF

Molecular function

Mg

Magnesium

MGAT5

Alpha-1,6-Mannosylglycoprotein 6-Beta-N-Acetylglucosaminyltransferase

MLLT1

MLLT1 Super Elongation Complex Subunit

MMS22L

Methyl Methanesulfonate-Sensitivity Protein 22-Like, DNA repair protein

Mn

Manganese

MSCs

Mesenchymal Stem Cells

Na

Sodium

NASS

National agricultural stastitics services

NCX

Sodium calcium exchanger

NDUFAF5

NADH:Ubiquinone Oxidoreductase Complex Assembly Factor 5

NELFA

Negative Elongation Factor Complex Member A

NGS

Next generation sequencing

Ni

Nickel

NMNAT1

Nicotinamide Nucleotide Adenylyltransferase 1

NPTN

Neuroplastin

NXNL2

Nucleoredoxin Like 2

OCT4

POU class 5 homeobox 1

OCTN2

Organic Cation/Carnitine Transporter 2

OTOP2

Otopetrin 2

P

Phosphorus

PCR

Polymerase chain reaction

PKD2

Polycystic kidney Disease 2

PLA2G15

Phospholipase A2 Group XV

PPIL2

Peptidylprolyl Isomerase Like 2

RAB11A

Ras-Related Protein Rab-11A

RBM14

RNA Binding Motif Protein 14

RIN

RNA integrity number

RNA-seq

Ribonucleic acid sequencing

RPL9

Ribosomal Protein L9

S

Sulphur

SCNN1A

Sodium Channel Epithelial 1 Subunit Alpha

SEC

Super elongation complex

SEM

Scanning Electron Microscope

SEM-EDS

SEM-Energy Dispersive Spectrometry

SEPTIN3

Septin 3

Si

Silicon

SLC19A2

Solute Carrier Family 19 Member 2

SLC22A15

Solute carrier family 22 member 15

SLC43A2

Solute Carrier Family 43 Member 2

SLC6A6

Solute carrier family 6 member 6

SMIM45

Small Integral Membrane Protein 45

SPP1

Secreted Phosphoprotein 1

STAB2

Stabilin 2

STC

Stanniocalcin

STK38

Serine/Threonine Kinase 38

TAPBPL

TAP Binding Protein Like

TBP

TATA-box binding protein

TFCP2L1

Transcription Factor CP2 Like 1

TM4SF19

Transmembrane 4 L Six Family Member 19

TRMT6

TRNA Methyltransferase 6 Non-Catalytic Subunit

TSSC4

Tumor Suppressing Subtransferable Candidate 4

UCP3

Uncoupling Protein 3

UP

Upper palisade

USDA

United states department of agriculture

USH1G

USH1 Protein Network Component Sans

USHBP1

USH1 Protein Network Component Harmonin Binding Protein 1

UV

Ultra violate

V

Vanadium

Zn

Zinc

ZO

Zona occldin

Authors’ contributions

PM conducted the experiments, collected samples, analyzed samples, and Drafted the manuscript. VK helped in primary RNA-seq data analysis (quality check, trimming, annotation, counts, and DEGs). KM helped in animal experimentation and sample collection. PR helped in eggshell strength analysis. RJ helped with experiment design and manuscript reviewing. BM designed the experiment, assisted with sample collection, data interpretation, and manuscript review. All the authors read and approved the manuscript.

Funding

This work was supported by NIFA/USDA (2022–67016-36373) to Birendra Mishra.

Data availability

The dataset generated and analyzed in the current study is available in the NCBI database (accession no.: [GSE296109]( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE296109 )).

Declarations

Ethics approval and consent to participate

All the animal experimentation was carried out following the guidelines approved by the Institutional Animal Care and Use Committee of the University of Hawaii at Manoa (Approval No 17–2605-6).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.