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To obtain chicken CD40L protein, the cDNA was prepared from chicken splenic cells and used as a template to clone and amplify CD40L by PCR. The target gene was cloned into pFastBac vector to construct a pFastBac-chCD40L donor plasmid. Recombinant plasmid was transformed into DH10Bac and recombinant Bacmid-chCD40L was obtained. The Bacmid-chCD40L plasmid was transfected into sf9 insect cells to obtain His-chCD40L protein. In addition, the target gene was cloned into pQM01 vector to construct a pQM01-chCD40L plasmid, recombinant plasmid was transfected into HEK 293T cells to obtain Strep-chCD40L protein. The chCD40L protein was purified by affinity chromatography, and the concentration of purified chCD40L protein was determined to be 0.01 mg/mL. Primary cells were isolated from the bursal tissue of 3-week old SPF chickens, and the chCD40L protein was added to the culture medium to stimulate cells. The chCD40L could bind to CD40 on B cells as examined by Western blotting, indirect immunofluorescence assay and flow cytometry, suggesting that chCD40L protein is biologically active. We successfully obtained chicken CD40L protein of biological activity, which laid the foundation in the in vitro culture of primary B lymphocytes for the isolation and diagnosis of virulent IBDV.

miR-223 is an important miRNA. It plays important roles in lipid metabolism by targeting related genes in mammals. It may be related to fatty liver in laying hens and its functions and target genes need further study. Through bioinformatics, we found that 349 genes were predicted as target genes of miR-223. Lipid-related gene DAGLA was among the predicted target genes. Dual-luciferase reporter assays showed that DAGLA was the target gene of miR-223 and the site mutation assays validated the target site of miR-223 in DAGLA. Overexpression of miR-223 in chicken hepatocytes LMH decreased the mRNA and protein expression of DAGLA, while knockdown of miR-223 increased expression of DAGLA in LMH cells, further indicating that miR-223 targets DAGLA and downregulates its expression. Since the target site of miR-223 in chicken DAGLA is not conserved, these findings suggest that miR-223 plays a specific role in chicken liver by regulating expression of target gene DAGLA., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Bone size is an important trait for chickens because of its association with osteoporosis in layers and meat production in broilers. Here, we employed high density genotyping platforms to detect candidate genes for bone traits. Estimates of the narrow heritabilities ranged from 0.37 ± 0.04 for shank length to 0.59 ± 0.04 for tibia length. The dominance heritability was 0.12 ± 0.04 for shank length. Using a linear mixed model approach, we identified a promising locus within NCAPG on chromosome 4, which was associated with tibia length and mass, femur length and area, and shank length. In addition, three other loci were associated with bone size or mass at a Bonferroni-corrected genome-wide significance threshold of 1%. One region on chicken chromosome 1 between 168.38 and 171.82 Mb harbored HTR2A , LPAR6 , CAB39L , and TRPC4 . A second region that accounted for 2.2% of the phenotypic variance was located around WNT9A on chromosome 2, where allele substitution was predicted to be associated with tibia length. Four candidate genes identified on chromosome 27 comprising SPOP , NGFR , GIP , and HOXB3 were associated with tibia length and mass, femur length and area, and shank length. Genome partitioning analysis indicated that the variance explained by each chromosome was proportional to its length.

Follicular development has a major impact on reproductive performance. Most previous researchers focused on molecular mechanisms of follicular development. The genetic architecture underlying the number of follicle, however, has yet not to be thoroughly defined in chicken. Here we report a genome-wide association study for the genetic architecture determining the numbers of follicles in a large F 2 resource population. The results showed heritability were low to moderate (0.05-0.28) for number of pre-ovulatory follicles (POF), small yellow follicles (SYF) and atresia follicles (AF). The highly significant SNPs associated with SYF were mainly located on GGA17 and GGA28. Only four significant SNPs were identified for POF on GGA1. The variance partitioned across chromosomes and chromosome lengths had a linear relationship for SYF (R 2  = 0.58). The enriched genes created by the closest correspondent significant SNPs were found to be involved in biological pathways related to cell proliferation, cell cycle and cell survival. Two promising candidate genes, AMH and RGS3, were suggested to be prognostic biomarkers for SYF. In conclusion, this study offers the first evidence of genetic variance and positional candidate genes which influence the number of SYF in chicken. These identified informative SNPs may facilitate selection for an improved reproductive performance of laying hens.

Skeletal problems in layer chickens are gaining attention due to animal welfare and economic losses in the egg industry. The genetic improvement of bone traits has been proposed as a potential solution to these issues; however, genetic architecture is not well understood. We conducted a genome-wide association study (GWAS) on bone quality using a sample of 1534 hens genotyped with a 600 K Chicken Genotyping Array. Using a linear mixed model approach, a novel locus close to GSG1L, associated with femur bone mineral density (BMD), was uncovered in this study. In addition, nine SNPs in genes were associated with bone quality. Three of these genes, RANKL, ADAMTS and SOST, were known to be associated with osteoporosis in humans, which makes them good candidate genes for osteoporosis in chickens. Genomic partitioning analysis supports the fact that common variants contribute to the variations of bone quality. We have identified several strong candidate genes and genomic regions associated with bone traits measured in end-of-lay cage layers, which accounted for 1.3-7.7% of the phenotypic variance. These SNPs could provide the relevant information to help elucidate which genes affect bone quality in chicken.

The comb, as a secondary sexual character, is an important trait in chicken. Indicators of comb length (CL), comb height (CH), and comb weight (CW) are often selected in production. DNA-based marker-assisted selection could help chicken breeders to accelerate genetic improvement for comb or related economic characters by early selection. Although a number of quantitative trait loci (QTL) and candidate genes have been identified with advances in molecular genetics, candidate genes underlying comb traits are limited. The aim of the study was to use genome-wide association (GWA) studies by 600 K Affymetrix chicken SNP arrays to detect genes that are related to comb, using an F2 resource population. For all comb characters, comb exhibited high SNP-based heritability estimates (0.61-0.69). Chromosome 1 explained 20.80% genetic variance, while chromosome 4 explained 6.89%. Independent univariate genome-wide screens for each character identified 127, 197, and 268 novel significant SNPs with CL, CH, and CW, respectively. Three candidate genes, VPS36, AR, and WNT11B, were determined to have a plausible function in all comb characters. These genes are important to the initiation of follicle development, gonadal growth, and dermal development, respectively. The current study provides the first GWA analysis for comb traits. Identification of the genetic basis as well as promising candidate genes will help us understand the underlying genetic architecture of comb development and has practical significance in breeding programs for the selection of comb as an index for sexual maturity or reproduction.

Background: Feed contributes to over 60 % of the total production costs in the poultry industry. Increasing feed costs prompt geneticists to include feed intake and efficiency as selection goals in breeding programs. In the present study, we used an F2 chicken population in a genome-wide association study (GWAS) to detect potential genetic variants and candidate genes associated with daily feed intake (FI) and feed efficiency, including residual feed intake (RFI) and feed conversion ratio (FCR)., Methods: A total of 1534 F2 hens from a White Leghorn and Dongxiang reciprocal cross were phenotyped for feed intake and efficiency between 37 and 40 weeks (FI1, RFI1, and FCR1) and between 57 and 60 weeks (FI2, RFI2, and FCR2), and genotyped using the chicken 600 K single nucleotide polymorphism (SNP) genotyping array. Univariate, bivariate, and conditional genome-wide association studies (GWAS) were performed with GEMMA, a genome-wide efficient mixed model association algorithm. The statistical significance threshold for association was inferred by the simpleM method., Results: We identified eight genomic regions that each contained at least one genetic variant that showed a significant association with FI. Genomic regions on Gallus gallus (GGA) chromosome 4 coincided with known quantitative trait loci (QTL) that affect feed intake of layers. Of particular interest, eight SNPs on GGA1 in the region between 169.23 and 171.55 Mb were consistently associated with FI in both univariate and bivariate GWAS, which explained 3.72 and 2.57 % of the phenotypic variance of FI1 and FI2, respectively. The CAB39L gene can be considered as a promising candidate for FI1. For RFI, a haplotype block on GGA27 harbored a significant SNP associated with RFI2. The major allele of rs315135692 was favorable for a lower RFI, with a phenotypic difference of 3.35 g/day between opposite homozygous genotypes. Strong signals on GGA1 were detected in the bivariate GWAS for FCR., Conclusions: The results demonstrated the polygenic nature of feed intake. GWAS identified novel variants and confirmed a QTL that was previously reported for feed intake in chickens. Genetic variants associated with feed efficiency may be used in genomic breeding programs to select more efficient layers.

Laying records on 1,534 F2 hens, derived from a reciprocal cross between White Leghorns and Dongxiang blue-shelled chickens, were used to estimate genetic parameters for residual feed intake (RFI), feed conversion ratio (FCR), daily feed intake (FI), metabolic BW (MBW), BW gain (BWG), and daily egg mass (EM) at 37 to 40 (T1) and 57 to 60 wk age (T2), respectively. Genetic analysis was subsequently conducted with the AI-REML method using an animal model. Estimates for heritability of RFI, FCR, and FI were 0.21, 0.19, and 0.20 in T1, and 0.29, 0.13, and 0.26 in T2, respectively. In T1 and T2, RFI showed high and positive genetic correlations with FCR (0.51, 0.43) and FI (0.72, 0.84), whereas the genetic correlation between FI and FCR was very low (-0.09, 0.11). Genetically, negative correlations were found between RFI and its component traits (-0.01 to -0.47). In addition, high genetic correlations, from 0.76 to 0.94, were observed between T1 and T2 for RFI, FCR, and FI, suggesting that feed efficiency traits in the 2 stages had a similar genetic background. The results indicate that selection for low RFI could reduce FI without significant changes in EM, while selection on FCR will increase EM. The present study lays the foundation for genetic improvement of feed efficiency during the laying period of chickens., (© The Author 2015. Published by Oxford University Press on behalf of Poultry Science Association.)

To determine the genetic architecture underlying spent hen carcase traits, especially in late laying, we used 1512 hens generated from Dongxiang Blue-Shelled and White Leghorn chickens to implement genome-wide association studies by high-density arrays. A total of 266 loci that mapped to (Gallus gallus chromosome) GGA1, GGA4 and GGA27 were detected. After linkage disequilibrium analysis, five SNPs were considered as candidate markers because they located on or near the genes CKAP2, RB1, CCKAR, NCAPG and IGF2BP1. The heritability of all carcase traits was high, and SNP effects ranged from 3.24% to 8.72%. These findings provide new insights into the genetic architecture of carcase traits in spent layer hens. Resource population generated from two breeds were used to measure carcass traits in spent hens. A total of 266 loci association with carcass traits located on GGA1, GGA4, and GGA27. Five putative candidate genes CKAP2, RB1, CCKAR, NCAPG and IGFBP1 were obtained after gene annotation. [ABSTRACT FROM AUTHOR]

Small intestine length is an important physiological index that is effected by nutrient intake and thus plays roles in growth and egg-laying in chickens. Although there are some studies about small intestine length, little information is available regarding the genetic architecture of small intestine. The current study was conducted to investigate the genetic architecture of small intestine length. A total of 1435 F2 hens from a White Leghorn and Dongxiang reciprocal cross were phenotyped for the duodenum lengths (DL), jejunum length (JL) and ileum length (IL), and genotyped using a chicken 600 K single nucleotide polymorphism (SNP) genotyping array. SNP-based heritability estimation was performed by SAS algorithm and univariate genome-wide association studies (GWAS) were performed by GEMMA, a genome-wide efficient mixed-model association algorithm. The JL and IL exhibited high SNP-based heritability estimation (0.43 and 0.49, respectively), while the heritability estimation was moderate for the DL (0.36). Three independent univariate genome-wide screens for these small intestine lengths identified 202, 298 and 119 SNPs that were significantly associated with the DL, JL and IL, respectively. The significant genomic regions indicated that ~170Mb on GGA1 is an important region for these small intestine lengths. In this region, 78 SNPs were associated with them, of which 4 were involved in cell proliferation and development, corresponding to RB1 (rs313207223), CKAP2 (rs312737959) and SIAH3 (rs312771221, rs15494052) genes. Small intestine length exhibited good SNP-based heritability estimation and the GWAS results indicated that an important genomic region was located on GGA1. [ABSTRACT FROM AUTHOR]

Molecular genetic tools provide a method for improving the breeding selection of chickens (Gallus gallus). Although some studies have identified genes affecting egg quality, little is known about the genes responsible for oviduct development. To address this issue, here we used a genome-wide association (GWA) study to detect genes or genomic regions that are related to oviduct development in a chicken F2 resource population by employing high-density 600 K single-nucleotide polymorphism (SNP) arrays. For oviduct length and weight, which exhibited moderate heritability estimates of 0.35 and 0.39, respectively, chromosome 1 (GGA1) explained 9.45% of the genetic variance, while GGA4 to GGA8 and GGA11 explained over 1% of the variance. Independent univariate genome-wide screens for oviduct length and weight detected 69 significant SNPs on GGA1 and 49 suggestive SNPs on GGA1, GGA4, and GGA8. One hundred and fourteen suggestive SNPs were associated with oviduct length, while 73 SNPs were associated with oviduct weight. The significant genomic regions affecting oviduct weight ranged from 167.79–174.29 Mb on GGA1, 73.16–75.70 Mb on GGA4, and 4.88–4.92 Mb on GGA8. The genes CKAP2, CCKAR, NCAPG, IGFBP3, and GORAB were shown to have potential roles in oviduct development. These genes are involved in cell survival, appetite, and growth control. Our results represent the first GWA analysis of genes controlling oviduct weight and length. The identification of genomic loci and potential candidate genes affecting oviduct development greatly increase our understanding of the genetic basis underlying oviduct development, which could have an impact on the selection of egg quality. [ABSTRACT FROM AUTHOR]

The density of contour feathers is an important trait as it is closely related to heat dissipation in birds. Thus, identification of the major genes that control this trait will be useful to improve heat tolerance in chicken. So far, no GWAS study for the density of contour feathers in birds has been previously published; therefore, this study was aimed to identify genomic regions controlling the density of contour feathers. A total of 1252 hens were genotyped, using the 600 K Affymetrix Axiom Chicken Genotyping Array. The association analyses were performed using the GenABEL package in the R program. In brief, 146 significant SNP markers were mainly located on chromosome 1 and were identified to associate with the density of contour feathers in the current GWAS analysis. Moreover, we identified several within/nearby candidate genes (SUCLA2, DNAJC15, DHRS12, MLNR, and RB1) that are either directly or indirectly involved in the genetic control of the density of contour feathers in chicken. This study laid the foundation for studying the mechanism that underlies the density of chicken feathers. Furthermore, it is feasible to shear the back feathers of live chickens and measure the density of the feathers to improve heat tolerance in breeding practice. [ABSTRACT FROM AUTHOR]