Investigating the genetic determination of clutch traits in Chinese local chicken breed

doi:10.21203/rs.3.rs-1868044/v1

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Research Article

Investigating the genetic determination of clutch traits in Chinese local chicken breed

https://doi.org/10.21203/rs.3.rs-1868044/v1

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Journal Publication

published 16 Nov, 2023

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Background: Egg-laying rate is the trait with the highest economic weight in breeding programs for laying hens. Egg-laying rate is associated with a clutch, which is defined as consecutive days of oviposition. Clutch traits can be used to describe the individual laying pattern and has been considered as a trait for selection. However, little is known about the uniformity of clutch traits.

Methods: In this study, after estimating the genetic parameters for age at first egg (afe), body weight at first egg (bwfe), longest clutch until 52 week of age (maxC), the first week when the longest clutch starts (fwlCs), the last week of longest clutch ends (lwlCe), number of clutches (numC), the longest number of days without egg-laying until 52 week of age (lndwel), we identified single nucleotide polymorphisms (SNPs) and potential candidate genes associated with clutch traits in Laiwu Black chicken (a native Chinese breed). The restricted maximum likelihood (REML)method was employed for estimation of genetic parameters of clutch pattern in 399 Laiwu Black hens, using the GCTA software.

Results: The results showed that SNP-based heritability estimates of clutch traits ranged from 0.06 to 0.59. A genome-wide association study (GWAS) was performed based on a mixed linear model (MLM) implemented in the EMMAX software. Genotyping data were obtained from whole genome re-sequencing data (399 individuals were re-sequenced at 7× coverage). After quality control, a total of 10,810,544 SNPs remained to be analyzed. The GWAS results revealed that 401 significant SNPs responsible for clutch traits were scattered on chicken chromosomes 1-14, 17-19, 21-25, 28 and Z. Among the annotated genes, neural EGFL like 2 (NELL2), SET And MYND domain containing 3 (SMYD3), and phospholipase D1 (PLCL1)were the most promising candidates for clutch traits in Laiwu Black chicken.

Conclusion: The clutch traits showed moderate to high heritability, and the GWAS results identified an array of genes associated with the clutch traits. The findings of this study provide critical insight into the genetic basis of clutch traits.

Chicken

Genome

GWAS

Laying rate

Clutch traits

Egg-laying rate, which equals the number of eggs laid divided by the number of days in the recording period, is the trait with the highest economic weight in breeding programs for laying hens. Egg-laying rate is associated with a clutch, which is defined as consecutive days of oviposition. Successive clutches are separated by one or more days of pause. The length and number of clutches are controlled by the ovulatory cycle directly observed by the oviposition cycle and controlled by the circadian rhythm and the internal cycle of follicular growth and maturation[1, 2]. Egg-laying is characterized by two temporal oviposition traits, namely oviposition time and oviposition interval (i.e., the time period between two consecutive ovipositions in the same clutch). Long-term selection has decreased the genetic variability in the egg-laying rate[3]. Since the clutch number and oviposition traits are more basic biological traits than the egg-laying rate, the evaluation of clutch traits can provide further insight into the difference between highly productive birds and inferior layers, compared to a simple total egg number count or rate of laying. As a more basic biological trait, clutch pattern may be more heritable. Studies performed in individual cages have shown that the clutch number, mean oviposition time, and mean oviposition interval were more heritable than the laying rate and were favorably genetically correlated with the laying rate[1, 3–7].

Clutch size can be used to describe the individual laying pattern and has been considered as a trait for selection [4, 6, 8, 9]. The laying rate could be improved by selecting for these traits in breeding programs. However, little is known about the uniformity of oviposition traits [4], which could also be used to improve the laying rate. Thus, the clutch traits can be used as selection indicators to improve egg production in poultry breeding.

In recent years, the development and use of local chicken breeds has increased, but there has been little analysis of the genetic parameters of egg-laying traits of local chicken breeds, especially clutch traits. Its principle and feasibility as a breeding index for improving egg production are discussed, in order to improve the knowledge of breeding laying hens and promote the development of local chicken breeds. In this study, we performed the estimation of genetic parameters and a genome-wide association study (GWAS) to examine the genetic architecture of clutch traits in a Chinese local chicken breeds. This study provides novel insights into the genetic architecture underlying chicken clutch traits and is of significance for the application of genomics in practical chicken breeding.

Ethics statement

The work was approved by the animal experiments performed in this study were approved by the Science Research Department of the Shandong Academy of Agricultural Sciences (SAAS) (Ji’nan, China). (Approval number: SAAS-2019-029).

399 Laiwu Black chicken were obtained from an experimental farm of the Poultry Institute, Shandong Academy of Agricultural Sciences (PI, SAAS, Ji’nan, China). All eggs were incubated by a normal procedure and chickens were reared in cages under continuous lighting using standard conditions of temperature, humidity on the PI, SAAS, farm. All chickens were sold after 52 weeks of age.

Phenotype

Data were obtained from an egg production line (399 chickens), namely the Laiwu Black chicken breed (pink eggshell). Within generation records were summarized until the same age for all hatches. Days with two eggs were split into 2 d of one egg if there was no eggs the preceding or subsequent day, otherwise both eggs were counted on the same day. All eggs were counted as parts of clutches, including those with defects. A clutch was defined as the number of eggs laid on consecutive days without a break. Starting with the first egg laid by a hen, the following parameters were calculated: number of clutches (numC), longest clutch until 52 week of age (maxC), the first week when the longest clutch starts (fwlCs), the last week when the longest clutch ends (lwlCe) and the longest number of days without egg-laying until 52 week of age (lndwel). To investigate genetic variance component with standard traits used for selection, the age at first egg (afe), body weight at first egg (bwfe) were also included in the analysis.

Genotype

A total of 399 blood samples were collected from Laiwu Black chickens. For all birds, blood was collected from wing veins and rapidly frozen and stored at -20°C. Total genomic DNA was extracted using the conventional phenol-chloroform method, and the quality and quantity of the DNA were determined using a NanoDrop ND-2000 spectrophotometer (Thermo Fisher Scientific Inc., Waltham, MA, USA) and by agarose gel electrophoresis.

Each DNA sample of adequate quality was used to generate paired-end libraries by standard procedures. All libraries were sequenced on DNBSEQ™ Sequencing System (BGI Genomics, Shenzhen, China). Raw data were processed using SOAPnuke[10] and to ensure the quality of the data used in further analysis low-quality reads and PCR duplications reads were removed. After quality control, the average clean read sequence coverage was 7x. This depth ensured the accuracy of variant calling and genotyping and met the requirements for population genetic analysis.

The Burrows-Wheeler aligner[11] was used to map clean reads to the chicken reference genome (ftp://ftp.ensembl.org/pub/release-96/fasta/gallus_gallus/dna/). The Samtools v1.2 software [12] was used to sort reads, and the MarkDuplicates program implemented in Picard tools v1.13 (http://broadinstitute.github.io/picard/) was used to remove duplicate reads resulting from polymerase chain reaction (PCR) amplification. Reads mapped to two or more places were likewise screened out. The Genome Analysis Toolkit[13] Haplotype Caller was used for single nucleotide polymorphism (SNP) calling through local re-assembly of haplotypes for the population. SNPs were then screened before further analysis using the GATK Variant Filtration tool with the following settings: QD < 2.0, ReadPosRankSum < -8.0, FS > 60.0, QUAL < 50.0, DP < 200.

Data quality control and imputation of SNPs

SNPs with an inheritance or genotyping error, a minor allele frequency < 5%, a call rate < 95%, and not assigned to GGA1-GGA28, GGZ and GGW were screened out. Ultimately, after quality control, 10,810,544 SNPs distributed on 30 chicken chromosomes remained. Accordingly, a total of 10,810,544 SNPs and 399 chickens were used for the analysis.

Principal component analysis (PCA)

Principal component analysis (PCA) was performed on all SNPs using Plink (v 1.9) software[14] for the analysis of population structure. Plots of the first, second and third PCs from the PCA were plotted using R packages.

Estimation of genetic parameters

SNP-based heritability (h² SNP) was calculated using the GCTA v1.93.2 beta software [15] based on the genetic relationship matrix (GRM) between pairs of individuals [16]. The restricted maximum likelihood (REML) method was used for genetic parameter estimation. The genetic-statistical model was defined as follows:

$${Y}_{i}={X}_{i}{b}_{i}+{Z}_{i}{u}_{i}+{e}_{i}$$

where ${Y}_{i}$ is a vector of clutch traits; ${X}_{i}$ and ${Z}_{i}$ are incidence matrices for ${b}_{i}$ and ${u}_{i},$respectively; b_i is a vector of fixed effect; ${u}_{i}$ is a vector of polygenic effects with a variance-covariance structure of $u ~N\left(0,G{\sigma }_{u}^{2}\right);$ G is the GRM between individuals; ${\sigma }_{u}^{2}$is the polygenic variance; ${e}_{i}$ is a vector of random residual effects with ${e}_{i} ~N(0,I{\sigma }_{e}^{2})$; I is an identity matrix of dimension n × n (with a sample size n= 399).

Genome-wide association studies

Briefly, we started by filtering out SNPs with an inheritance or genotyping error, a minor allele frequency < 5%, and a call rate < 95%. Eventually, after quality control of genotypes, a total of 10,810,544 SNPs and 399 individuals were left for analysis. Linkage disequilibrium (LD) pruning was then performed with a window size of 25 SNPs, a step of five SNPs, and r2 threshold of 0.2, identifying 1,462,803 independent SNPs and LD blocks. The sample structure was visualized by PCA using eigenvalues as coordinates. The Efficient Mixed-Model Association eXpedited (EMMAX) tool was then applied to all informative SNPs using the BN kinship matrix for genome-wide association mapping[17]. The top three principal components contributing to the majority of the population structure variations were included in the model to control the population structure. The EMMAX algorithm is efficient for controlling population stratification, especially the between-generation genotype differences central to the present study[17, 18], taking into account that population structure helps minimize false positives and increases statistical power. After this analysis, a Manhattan plot was generated from the calculated -log10 (P-value) for each SNP. The threshold for genome-wide significance was determined based on 5% Bonferroni correction with the estimated 640,054 independent SNPs, giving a value of 0.05/1,462,803 = 3.42E-8 [-log10 (P-value) = 7.47], while the threshold for suggestive significance was 1/1,462,803 = 6.84E-7 [-log10(P-value) = 6.16]. The Manhattan and quantile-quantile (Q-Q) plots for traits were generated using the “CMplot” package in R.

Bioinformatics analysis of candidate genes

Using the VEP software [19] (http://asia.ensembl.org/Tools/VEP), SNPs were assigned to genes if they were within the genomic sequence of a gene or within a flanking region of 5 kb up- or downstream of a gene, to include SNPs located in gene regulatory regions. The Ensembl GRCg6a database was used as a reference (http://asia.ensembl.org/Gallus_gallus/Info/Index).We then identified the biological functions of these genes in PubMed (https://pubmed.ncbi.nlm.nih.gov).To elucidate the biological functions of the genes, we performed the pathway enrichment analysis using the KOBAS 3.0 online platform [20]. The significance of the pathways enriched in genes was calculated considering a P-value of < 0.05 as significant.

Summary of sequencing and genome variants

In this study, we whole-genome re-sequenced 399 chicken samples. A total of 2.14 Tb of high-quality sequencing data was aligned against the reference chicken genome (GRCg6a) (Table S1). The average mapping rate for all individuals was approximately 99.17%, the average coverage (>=1X) for all individuals was approximately 94.64%, and the average depth was approximately 7.41X (Table S2). Following the screening criteria listed in the “Materials and methods” section, a total of 10,810,544 genome-wide population SNPs were obtained.

Phenotype and genetic parameter statistics

Descriptive statistics of the afe and clutch traits across the entire egg-laying period are shown in Table 1. The mean value of the afe in this population was 138 days, which meant that hens started laying eggs at about 20 weeks of age. The SNP-based heritability estimate was high for the afe (0.76±0.16) and maxC trait (0.59±0.16), but relatively low (0.06) to moderate (0.36) for other clutch traits.

Table 1 Descriptive statistics for the afe, bwfe and clutch traits

Trait	N	Mean	SD	Max	Min
afe (d)	397	138.19	10.41	171	104
bwfe (g)	397	1440.57	136.36	2177	1037
maxC (d)	395	13.01	10.39	75	2
fwlCs (week)	395	24.49	4.67	42	17
lwlCe (week)	395	26.12	4.66	43	18
numC (n)	395	33.51	10.21	56	2
lndwel (d)	395	11.27	16.46	136	1

Abbreviations: afe: age at first egg; bwfe: body weight at first egg; maxC: longest clutch until 52 week of age; fwlCs: the first week when the longest clutch starts; lwlCe: the last week when the longest clutch ends; numC: number of clutches; lndwel: the longest day with no egg laid until 52 week of age; N, number of animals; SD, standard deviation; Max, maximum; Min, minimum.

Table 2 SNP-based heritability estimates for clutch traits

Trait	V_g	V_e	V_p	h²
afe	74.09±17.6	23.64±15.42	97.73±7.14	0.76±0.16
bwfe	6117.72±2636.70	11754.48±2720.40	17872.2±1278.28	0.34±0.15
maxC	56.95±16.77	38.98±15.58	95.93±6.94	0.59±0.16
fwlCs	3.37±2.86	18.27±3.26	21.64±1.56	0.16±0.13
lwlCe	1.33±2.36	20.3±2.94	21.64±1.56	0.06±0.11
numC	34.79±13.38	61.16±13.74	95.95±6.88	0.36±0.14
lndwel	50.25±32.7	216.28±37.11	266.53±19.15	0.19±0.12

Genome-wide association study

Association tests for the afe, bwfe and clutch traits were performed using a univariate linear mixed model. A total of 401 unique candidate SNPs (P value < 6.84E-07) located on 24 chromosomes were identified (Additional file 1: Table S1). According to gene functions, 36 phenotype-related SNPs were selected from all the significant SNPs and were annotated in detail.

Five of them scattered on two different chromosomes were likely associated with the afe (Table 3), five of them scattered on three different chromosomes were likely associated with bwfe (Table 4), while the remaining 26 significant SNPs were related to clutch traits (Table 5). The Manhattan plots for the afe, bwfe and clutch traits are shown in Figure 2, Figure 3, and Figure 4, respectively.

Table 3 GWAS and annotations of suggestive SNPs for the afe

Chr	BP	ALT/REF	Bata	P value	Consequence	Candidate/ Nearest gene
1	7413930	C/T	-8.50	1.3E-07	intron	FRMD4A
1	30524767	A/G	8.98	2.6E-07	intron	NELL2
6	19003506	T/A	-4.10	4.6E-07	intron	PTPN20
6	19039248	A/G	-3.86	1.4E-07	intron	MAPK8
6	19039251	T/C	-3.81	1.4E-07	intron	MAPK8

Abbreviations: Chr, chromosome; BP: physical position; Beta, the estimated coefficient.

Table 4 GWAS and annotations of suggestive SNPs for the bwfe

CHR	BP	ALT/REF	Bata	P value	Consequence	Candidate/ Nearest gene
1	149332781	G/A	-53.86	4.2E-07	intron	GPC5
1	171732987	G/A	64.88	3.9E-07	intron	CKAP2
1	171732987	G/A	64.88	3.9E-07	upstream	VPS36
1	171732996	G/C	63.62	3.7E-07	intron	CKAP2
1	171732996	G/C	63.62	3.7E-07	upstream	VPS36
8	16338421	A/T	69.53	1.8E-07	intron	SH3GLB1
18	7998007	T/G	-100.42	5.7E-07	intron	MAP2K6

Abbreviations: Chr, chromosome; BP: physical position; Beta, the estimate coefficient.

Table 5 GWAS and annotations of suggestive SNPs for the clutch traits

Trait	CHR	BP	ALT/REF	Bata	P value	Consequence	Candidate/ Nearest gene
maxC	1	35178616	G/A	-8.18	7.5E-08	upstream	IFNG
maxC	1	40548144	C/T	-7.04	1.1E-07	intron	PPFIA2
maxC	3	16867987	C/G	-5.92	1.1E-07	intron	GPCPD1
maxC	3	34132127	C/T	-7.01	2.0E-07	intron	SMYD3
maxC	4	50279449	T/C	-7.39	1.7E-07	intron	SLC4A4
maxC	4	56572493	A/T	-5.96	4.5E-07	intron	CAMK2D
maxC	4	56956942	G/A	-7.89	9.8E-08	intron	ANK2
maxC	8	6861178	A/G	-9.73	6.4E-09	intron	RASAL2
maxC	9	13586651	A/G	-7.34	2.1E-07	intron	FGF12
maxC	9	19708862	A/G	-7.79	2.3E-07	intron	PLD1
maxC	10	18641056	C/A	-7.44	4.7E-10	intron	MEGF11
maxC	10	18921595	A/G	-6.12	9.4E-08	intron	MAP2K1
maxC	12	15204994	T/C	-7.71	6.8E-08	intron	SUCLG2
fwlCs	1	1855087	A/G	-2.26	2.0E-07	intron	VWA8
fwlCs	4	6253543	T/C	-1.86	2.9E-08	intron	HTT
fwlCs	10	8627801	A/G	-1.72	3.0E-07	intron	PKLR
fwlCs	14	9583801	T/C	-2.23	4.7E-07	upstream	SOX8
lwlCe	1	167312472	A/G	-2.21	2.5E-07	intron	VWA8
lwlCe	4	82097182	A/C	-2.39	4.8E-07	upstream	MSANTD1
lndwel	1	39566858	C/T	-14.198	1.5E-09	intron	PAWR
lndwel	3	82310311	C/T	-17.162	1.3E-09	intron	ASRGL1
lndwel	7	10368909	C/T	-14.099	7.1E-09	upstream	PLCL1
lndwel	12	7864695	C/T	-13.236	2.2E-08	intron	CACNA2D3
lndwel	Z	1719462	G/A	-11.475	8.4E-11	upstream	SKOR2

Abbreviations: Chr, chromosome; BP: physical position; Beta, the estimated coefficient; maxC: longest clutch until 52 week of age; fwlCs: the first week when the longest clutch starts; lwlCe: the last week when the longest clutch ends; numC: number of clutches; lndwel: the longest day with no egg laid until 52 week of age.

Annotation of candidate SNPs

The candidate genes associated with the afe are listed in Table3, including FERM domain containing 4A (FRMD4A), neural EGFL like 2 (NELL2), protein tyrosine phosphatase non-receptor type 20 (PTPN20), and mitogen-Activated protein kinase 8 (MAPK8). In addition, the candidate genes associated with the bwfe are listed in Table4, including glypican 5 (GPC5), cytoskeleton associated protein 2 (CKAP2), vacuolar protein sorting 36 homolog (VPS36), SH3 domain containing GRB2 like, endophilin B1 (SH3GLB1), and mitogen-activated protein kinase kinase 6 (MAP2K6).

Annotations of suggestive SNPs for clutch traits are shown in Table5. A total of 355 genes containing significant SNPs, and 24 candidate genes associated with clutch traits according to their functions were identified. Some genes, such as glycerophosphocholine phosphodiesterase 1 (GPCPD1), SET And MYND domain containing 3 (SMYD3), solute carrier family 4 member 3 (SLC4A4), fibroblast growth factor 12 (FGF12), phospholipase D1 (PLD1), mitogen-activated protein kinase kinase 1 (MAP2K1), von Willebrand factor A domain containing 8 (VWA8), Myb/SANT DNA binding domain containing 1 (MSANTD1), huntingtin (HTT), pro-apoptotic WT1 regulator (PAWR), asparaginase like 1 (ASRGL1), phospholipase C like 1 (PLCL1), calcium voltage-gated channel auxiliary subunit alpha2delta 3 (CACNA2D3), and SKI family transcriptional corepressor 2 (SKOR2), which have been shown to be related to egg number, egg production, litter size, or reproductive traits, are worth a deeper exploration.

Signaling Pathways Associated with annotated genes

Using VEP tools, 138 genes were annotated through 401 unique candidate SNPs, then the pathway enrichment analysis was performed. As expected, among these candidate gene-enriched pathways, some reproduction-related pathways were identified, including the gonadotropin-releasing hormone (GNRH) signaling pathway, ErbB signaling pathway and Oocyte meiosis, etc., as shown in Figure 5.

Clutch traits are one of the important reproductive performance indicators of hens, which are affected by follicle development. The growth of follicles is affected by factors, such as species, age, environment, hormone levels, nutrition, etc. When ovulation is interrupted for a day or a few days, hens experience intermittent egg-laying. Related research shows that clutch size can be used to describe the individual laying pattern and has been considered as a trait for selection[4, 8] . However, to date, the genetic architectures underlying chicken clutch traits are not completely known. Through the estimation of genetic parameters and a GWAS, this study preliminarily revealed the genetic architectures of clutch traits in chickens.

Estimates of Genetic Parameters

Estimates of genetic parameters for clutch related traits revealed that the afe had the highest heritability estimate (0.76). In the literature, the afe has been reported as a trait with moderate heritability (0.36-0.55)[4, 21-23], which is in agreement with our estimates. Our results also showed that the number of clutches had a moderate heritability estimate (0.36), which is similar to related studies showing that the heritability of the number of clutches and average clutch length is around 0.15-0.68.[3, 9, 24, 25]

Genome-wide association study of afe and bwfe traits

The afe of chicken is an indicator that is related to reproduction and growth [26]. There is a negative correlation between the afe (sexual maturity) and the number of eggs produced, that is, the earlier the afe, the more eggs are laid. However, if hens start laying eggs early when they are underweight, it will have a very negative impact on egg production in the later laying cycles[27-30]. In this study, the NELL2 and MAPK8 genes were associated with the afe of the chicken. Some genes regulate hormone levels, including GNRH, oxytocin (OXT), growth hormone (GH), and thyroid hormone (TH). All these hormones play a crucial role in the female reproductive system [31-36]. NELL2 not only affects the synthesis and secretion of GNRH [37], but has also been shown to be involved in maintaining the normal female reproductive cycle of mammals [38]. Pulsatile GNRH regulates the gonadotropin subunit genes in a differential manner, with faster frequencies favoring Lhb expression and slower frequencies favoring Fshb expression. The GNRH-induced Egr1 gene expression is mediated by MAPK8/9 and MAPK1/3, and both of them are critical for Lhb gene transcription[39]. The internal regulation axis (NELL2-GNRH-MAPK8 axis) regulates the afe trait of chicken. The CKAP2 and MAP2K6 genes have been associated with the bwfe. CKAP2 encodes cytoskeleton associated protein 2 that is involved in cell proliferation and cell survival[40] , and which is essential for maintaining genomic stability [41]. A previous study showed that the oviduct mass remains unchanged during the laying period in zebra finches [42], and studies suggested that CKAP2 may participate in the hyperplasia and hypertrophy of the oviduct before the laying of the first egg [43]. MAP2K6 promotes adipogenesis through the regulation of peroxisome proliferator-activated receptor gamma (PPARG) and CCAAT/enhancer-binding protein beta (CEBPB)[44].

Genes associated with clutch

As the main factor affecting the reproductive performance of birds, lighting regime has been applied to modern poultry production. By adopting a suitable light regime, producers can make the start of production of poultry earlier or later, thereby adjusting the egg production rate and laying time. Hens have regular laying intervals under continuous light conditions, have high production efficiency for a certain period of time, and show no laying interruptions. In this study, the ASRGL1 gene was identified as a candidate gene associated with clutch traits. ASRGL1 is a ubiquitously-expressed aspariginase enzyme present in the mammalian uterus and is highly expressed in the brain and testes [45, 46]. ASRGL1 knockout mice exhibited impaired visual function, and showed degeneration and apoptosis of photoreceptor cells [47]. This gene may affect the visual function of chickens and thus affect the clutch traits of chickens.

The change of the clutch cycle is not only directly affected by the external environmental photoperiod and temperature, but the nutrient intake also affects the c clutch cycle change. Delayed ovulation time may be affected by the different ways in which laying hens metabolize material and energy throughout the day. Hens mainly focus on energy metabolism during the day and protein synthesis at night, and thus hens need a sufficient amount of protein throughout the day for optimal egg-laying performance[48]. The MEGF11 and SUCLG2 genes were identified as maxC-related genes. According the GWAS and functional annotations, the MEGF11 gene is associated with feed efficiency [49]. and the SUCLG2 gene is involved in the propanoate metabolic pathway and has been significantly associated with growth in pigs [50]. Moreover, the latter study suggested that SUCLG2 plays a key role in the regulation of POU1F1, which is known to be involved in the expression of growth hormone and prolactin genes[51, 52].

The reproduction of birds is mediated by a series of complex internal and external environments. Seasons, lighting, and environmental stress all have an impact on their reproduction. The internal reproductive axis (Hypothalamic-pituitary-gonadal axis, HPG) regulates their main reproductive activities. Related study found that prolactin (PRL) levels in hens were low in the early part of the clutch cycle, while PRL levels increased in the later part of the cycle. PRL levels were inversely correlated with clutch cycle[53]. Generally, 4 hours before ovulation is the peak of LH secretion, and the time of LH release of different breeds leads to different ovulation times. When progesterone injection to hens can also accelerate the ovulation process, indicating that the occurrence and change of endocrine laws can affect the performance of continuous production [54].In this study, Some genes such as SMYD3, PAWR, PLCL1 which have been proved to be related to HPG. SMYD3 is a SET domain-containing protein with histone methyltransferase activity on histone H3-K4. RNA interference-directed down-regulation of SMYD3 reveals that SMYD3 is required for ER-regulated gene transcription in estrogen signaling pathway[55]. It has been reported that PAWR, a pro-apoptotic gene regulates apoptosis in rat follicles and FSH acts by suppressing PAWR expression in the ovary by activating PKCζ-dependent anti-apoptotic pathway[56, 57]. The phospholipase C-like proteins PLCL1 and PLCL2 are thought to act as sequesters of inositol triphosphates and reduce the signal to release calcium from the intracellular calcium storage[58]. In female reproduction, loss of both PLCl1 and PLCL2 results in subfertility, abnormal estrous cycle, and smaller uteri in mice [59]. PLCl1 and PLCL2 double-knockout mice apparently grew normally and became fertile; however, mutant female mice had an apparently smaller uterus by gross anatomical observation and had more estrous days during the cycles. Levels of serum LH and FSH were measured for 5-6 consecutive days and were found to be significantly higher in the mutant[59].

Signaling Pathways Associated with the clutch traits

The regulation of the clutch traits may be mediated through complex interactions among multiple pathways. According to the pathway enrichment analysis, several well-known pathways associated with reproduction were found to be enriched, including GNRH signaling pathway, ErbB signaling pathway and Oocyte meiosis pathway, etc. GNRH, a hypothalamic neuropeptide, is a main regulator of male and female reproductive function, which is required for reproduction. GNRH is secreted from the hypothalamus and acts on G-protein coupled receptors in the anterior pituitary. GNRH regulates the production and release of LH and FSH gonadotropins, controlling gametogenesis and steroidogenesis[60, 61]. The ErbB receptors signal through Akt, MAPK, and many other pathways to regulate cell proliferation, migration, differentiation, apoptosis, and cell motility. Related studies have found a crosstalk mechanism between GH and PRL and ErbB receptor family signaling[62]. Meiosis is one of the defining events in gametogenesis. Male and female germ cells both undergo one round of meiotic cell division during their development in order to reduce the ploidy of the gametes, and thereby maintain the ploidy of the species after fertilization [63].

We performed genetic parameter estimation and a GWAS in a Chinese native chicken population to examine genetic architectures underlying clutch traits. The clutch traits showed moderate to high heritability. The NELL2 gene may affect the afe through the NELL2-GNRH-MAPK8 axis in chickens. Moreover, the SMYD3 and PLCL1 genes, which were identified by annotating genome-wide significant SNPs, can be considered as candidates genes associated with clutch traits. The findings of this study provide a better insight into the genetic basic of clutch traits, but further functional validation is still needed in other populations.

afe age at first egg

bwfe body weight at first egg

maxC longest clutch until 52 week of age

fwlCs the first week when the longest clutch starts

lwlCs the last week of longest clutch ends

numC number of clutches

lndwel the longest number of days without egg-laying until 52 week of age

SNP single nucleotide polymorphism

REML restricted maximum likelihood

GWAS genome-wide association study

MLM mixed linear model

NELL2 neural EGFL like 2

SMYD3 SET And MYND domain containing 3

PLCL1 phospholipase D1

PCR polymerase chain reaction

PCA Principal component analysis

GRM genetic relationship matrix

EMMAX Efficient Mixed-Model Association eXpedited

Ethics approval and consent to participate

Consent for publication

Not applicable

Availability of data and materials

The genome sequence data reported in this article is being uploaded to the genome sequence file of the BIG Data Center of the Beijing Institute of Genomics, Chinese Academy of Sciences, and is publicly available from http://bigd.big.ac.cn (CRA007364).

Competing interests

The authors declare that they have no competing interests.

Funding

This research was supported by the Agricultural Stock Breeding Project of Shandong Province (2019LZGC019), Agricultural Scientific and Technological Innovation Project of Shandong Academy of Agricultural Sciences (CXGC2022C04), Agricultural Breed Project of Shandong Province (2020LZGC013), Shandong Provincial Natural Science Foundation (ZR2020MC169), China Agriculture Research System of MOF and MARA (CARS-41), Agricultural Scientific and Technological Innovation Project of Shandong Academy of Agricultural Sciences (CXGC2022D04), The Key Research Program of Shandong province (2021CXGC0010805), China Agriculture Research System of MOF and MARA(CARS-40).

Authors' contributions

YZ, JW (Jianxia Wang) and DC conceived and designed the study. JW (Jie Wang) performed statistical analyses and wrote the paper. QL, YZ, HH (Haixia Han), and WL participated in data analyses. JW (Jie Wang), ZL, JL, FL, HH (Heguo Han), and DL participated in the design of the study and contributed to acquisition of data. All authors read and approved the final manuscript.

Acknowledgements

The authors would like to thank Dingli Cao at the Poultry Institute, Shandong Academy of Agricultural Sciences for animal care and sample collection.

Authors' information (optional)

¹ Poultry Breeding Engineering Technology Center of Shandong Province, Poultry Institute, Shandong Academy of Agricultural Sciences, Jinan, 250023, Shandong, China

²Shandong Animal Husbandry General Station, Jinan, 250023, China

³Lijin County center for animal disease control, Lijin, 257400, China

⁴Administrative Examination and Approval Service Bureau of Lijin County, Lijin, 257400, China

Jie Wang¹, Zhansheng Liu², Dingguo Cao¹, Jie Liu¹, Fuwei Li¹, Heguo Han³, Haixia Han¹, Qiuxia Lei¹, Wei Liu¹, Dapeng Li¹, Jianxia Wang⁴, Yan Zhou¹^*

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Investigating the genetic determination of clutch traits in Chinese local chicken breed

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Abstract

Figures

Background

Material And Methods

Ethics statement

Phenotype

Genotype

Data quality control and imputation of SNPs

Principal component analysis (PCA)

Estimation of genetic parameters

Genome-wide association studies

Bioinformatics analysis of candidate genes

Results

Discussion

Conclusions

Abbreviations

Declarations

References

Supplementary Files

Status:

Journal Publication

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