Genetic mapping of quantitative trait loci affecting growth and carcass traits in F2 intercross chickens

Copy number variations affecting growth curve parameters in a crossbred chicken population

Copy number variations (CNVs) are key structural variations in the genome and may contribute to phenotypic differences. In this study, we used a F2 chicken population created from reciprocal crossing between fast-growing Arian broiler line and Urmia native chickens. The chickens were genotyped by 60 K SNP BeadChip, and PennCNV algorithm was used to detect genome-wide CNVs. The growth curve parameters of W0, k, L, Wf, Wi, ti and average GR were used as phenotypic data. The association between CNV and growth curve parameters was carried out using the CNVRanger R/Bioconductor package. Five CNV regions (CNVRs) were chosen for the validation experiment using qPCR. Gene enrichment analysis was done using WebGestalt. The STRING database was used to search for significant pathways. The results identified 966 CNVs and 600 CNVRs including 468 gains, 67 losses, and 65 both events on autosomal chromosomes. Validation of the CNVRs obtained from the qPCR assay were 79 % consistent with the prediction by PennCNV. A total of 43 significant CNVs were obtained for the seven growth curve parameters. The 416 genes annotated for significant CNVs. Six genes out of 416 genes were most related to growth curve parameters. These genes were LCP2, Dock2, CD80, CYFIP1, NIPA1 and NIPA2. Some of these genes in their biological process were associated with the growth, reproduction and development of cells or organs that ultimately lead to the growth of the body. The results of the study could pave the way for better understanding the molecular process of CNVs and growth curve parameters in birds.

Enhancing aggression in Henan gamecocks via augmentation of serotonergic-dopaminergic signaling and attenuation of neuroimmune response

Animal aggression is one of the most conserved behaviors. Excessive and inappropriate aggression was a serious social concern across species. After long-term selection under strict stress conditions, Henan gamecock serves as a good model for studying aggressive behavior. In this research, we constructed a Henan game chicken backcross population containing 25% Rhode Island Red (RIR), and conducted brain transcriptomics and serum metabolomics analyses on Henan gamecock (HGR) through its comparison with its female encounters (HGH) and the male backcross birds (BGR). The study revealed that seven differential metabolites in serum and 172 differentially expressed genes in the brain were commonly shared in both HGR vs. HGH and HGR vs. BGR comparisons. They exhibited the same patterns of modulation in Henan gamecocks, following either HGH < HGR > BGR or HGH > HGR < BGR style. Therein, some neurological genes involving in serotonergic and dopaminergic signaling were upregulated, while the levels of many genes related with neuro-immune function were decreased in Henan gamecock. In addition, many unknown genes specifically or highly expressed in the brain of the Henan gamecock were identified. These genes are potentially key candidates for enhancing the bird's aggression. Multi-omics joint analysis revealed that tyrosine metabolism and neuroactive ligand-receptor interaction were commonly affected. Overall, our results propose that the aggressiveness of Henan gamecocks can be heightened by the activation of the serotonergic-dopaminergic metabolic process in the brain, which concurrently impairs the neuroimmune system. Further research is needed to identify the function of these unknown genes on the bird's aggressive behavior.

A large-scale comparison of the meat quality characteristics of different chicken breeds in South China

Meat quality traits are essential for producing high-quality broilers, but the genetic improvement has been limited by the complexity of measurement methods and the numerous traits involved. To systematically understand the meat quality characteristics of different broiler breeds, this study collected data on slaughter performance, skin color, fat deposition, and meat quality traits of 434 broilers from 12 different breeds in South China. The results showed that there was no significant difference in the live weight and slaughter weight of various broiler breeds at their respective market ages. Commercial broiler breeds such as Xiaobai and Huangma chickens had higher breast muscle and leg muscle rates. The skin and abdominal fat of Huangma chickens cultivated in the consumer market in South China exhibited significantly higher levels of yellowness compared to other varieties. Concerning fat traits, we observed that Wenchang chickens exhibited a strong ability to fat deposition, while the younger breeds showed lower fat deposition. Additionally, there were significant positive correlations found among different traits, including traits related to weight, traits related to fat, and skin color of different parts. Hierarchical clustering analysis revealed that fast-growing and large broiler Xiaobai chickens formed a distinct cluster based on carcass characteristics, skin color, and meat quality traits. Principal component analysis (PCA) was used to extract multiple principal components as substitutes for complex meat quality indicators, establishing a chicken meat quality evaluation model to differentiate between different breeds of chickens. At the same time, we identified 46, 22, and 20 SNP loci and their adjacent genes that were significantly associated with muscle mass traits, fat deposition, and skin color through genome-wide association studies (GWAS). The above results are helpful for systematically understanding the differences and characteristics of meat quality traits among different breeds.

Polymorphisms of CRELD1 and DNAJC30 and their relationship with chicken carcass traits

Carcass traits play important roles in the broiler industry and single nucleotide polymorphism (SNP) can be efficient molecular markers for marker-assisted breeding of chicken carcass traits. Based on our previous RNA-seq data (accession number GSE58755), cysteine rich with epidermal growth factor like domains 1 (CRELD1) and DnaJ heat shock protein family member C30 (DNAJC30) are differentially expressed in breast muscle between white recessive rock chicken (WRR) and Xinghua chicken (XH). In this study, we further characterize the potential function and SNP mutation of CRELD1 and DNAJC30 in chicken for the first time. According to protein interaction network and enrichment analysis, CRELD1 and DNAJC30 may play some roles in chicken muscle development and fat deposition. In WRR and XH, the results of the relative tissue expression pattern demonstrated that CRELD1 and DNAJC30 are not only differentially expressed in breast muscle but also leg muscle and abdominal fat. Therefore, we identified 5 SNP sites of CRELD1 and 7 SNP sites of DNAJC30 and genotyped them in an F₂ chicken population. There are 4 sites of CRELD1 and 3 sites of DNAJC30 are associated with chicken carcass traits like breast muscle weight, body weight, dressed weight, leg weight percentage, eviscerated weight with giblet percentage, intermuscular adipose width, shank length, and girth. These results suggest that the SNP sites of CRELD1 and DNAJC30 can be potential molecular markers to improve the chicken carcass traits and lay the foundation for marker-assisted selection.

Genetic effect of an InDel in the promoter region of the NUDT15 and its effect on myoblast proliferation in chickens

Background

Molecular breeding accelerates the speed of animal breeding. Screening molecular markers that can affect economic traits through genome-wide association studies (GWAS) can provide a theoretical basis for molecular breeding. At present, a large number of molecular markers have been screened in poultry research, but few reports on how molecular markers affect economic traits exist. It is particularly important to reveal the action mechanisms of molecular markers, which can provide more accurate information for molecular breeding.

Results

The aim of this study was to investigate the relationships between two indels (NUDT15-indel-2777 and NUDT15-indel-1673) in the promoter region of NUDT15 and growth and carcass traits in chickens and to explore the regulatory mechanism of NUDT15. Significant differences were found in genotype and allele frequencies among commercial broilers, commercial laying hens and dual-purpose chickens. The results of association analyses showed that these two indel loci could significantly affect growth traits, such as body weight, and carcass traits. Tissue expression profiling at E12 showed that the expression of NUDT15 was significantly higher in skeletal muscle, and time-expression profiling of leg muscle showed that the expression of NUDT15 in myoblasts was significantly higher in the E10 and E12 proliferation stages than in other stages. Promoter activity analysis showed that pro-1673-I and pro-1673-D significantly inhibited promoter activity, and the promoter activity of pro-1673-D was significantly lower than that of pro-1673-I. In addition, when NUDT15 was overexpressed or underwent interference in chicken primary myoblasts (CPMs), NUDT15 could inhibit the proliferation of CPMs.

Conclusion

The results suggest that the studied indels in the promoter region of NUDT15 may regulate the proliferation of CPMs by affecting NUDT15 expression, ultimately affecting the growth and carcass traits of chickens. These indel polymorphisms may be used together as molecular markers for improving economic traits in chickens.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08362-6.

Genome-Wide Association Study of Growth Performance and Immune Response to Newcastle Disease Virus of Indigenous Chicken in Rwanda

A chicken genome has several regions with quantitative trait loci (QTLs). However, replication and confirmation of QTL effects are required particularly in African chicken populations. This study identified single nucleotide polymorphisms (SNPs) and putative genes responsible for body weight (BW) and antibody response (AbR) to Newcastle disease (ND) in Rwanda indigenous chicken (IC) using genome-wide association studies (GWAS). Multiple testing was corrected using chromosomal false detection rates of 5 and 10% for significant and suggestive thresholds, respectively. BioMart data mining and variant effect predictor tools were used to annotate SNPs and candidate genes, respectively. A total of four significant SNPs (rs74098018, rs13792572, rs314702374, and rs14123335) significantly (p ≤ 7.6E-5) associated with BW were identified on chromosomes (CHRs) 8, 11, and 19. In the vicinity of these SNPs, four genes such as pre-B-cell leukaemia homeobox 1 (PBX1), GPATCH1, MPHOSPH6, and MRM1 were identified. Four other significant SNPs (rs314787954, rs13623466, rs13910430, and rs737507850) all located on chromosome 1 were strongly (p ≤ 7.6E-5) associated with chicken antibody response to ND. The closest genes to these four SNPs were cell division cycle 16 (CDC16), zinc finger, BED-type containing 1 (ZBED1), myxovirus (influenza virus) resistance 1 (MX1), and growth factor receptor bound protein 2 (GRB2) related adaptor protein 2 (GRAP2). Besides, other SNPs and genes suggestively (p ≤ 1.5E-5) associated with BW and antibody response to ND were reported. This work offers a useful entry point for the discovery of causative genes accountable for essential QTLs regulating BW and antibody response to ND traits. Results provide auspicious genes and SNP-based markers that can be used in the improvement of growth performance and ND resistance in IC populations based on gene-based and/or marker-assisted breeding selection.

Analysis of four complete linkage sequence variants within a novel lncRNA located in a growth QTL on chromosome 1 related to growth traits in chickens

An increasing number of studies have shown that quantitative trait loci (QTLs) at the end of chromosome 1 identified in different chicken breeds and populations exert significant effects on growth traits in chickens. Nevertheless, the causal genes underlying the QTL effect remain poorly understood. Using an updated gene database, a novel lncRNA (named LncFAM) was found at the end of chromosome 1 and located in a growth and digestion QTL. This study showed that the expression level of LncFAM in pancreas tissues with a high weight was significantly higher than that in pancreas tissues with a low weight, which indicates that the expression level of LncFAM was positively correlated with various growth phenotype indexes, such as growth speed and body weight. A polymorphism screening identified four polymorphisms with strong linkage disequilibrium in LncFAM: a 5-bp indel in the second exon, an A/G base mutation, and 7-bp and 97-bp indels in the second intron. A study of a 97-bp insertion in the second intron using an F2 chicken resource population produced by Anka and Gushi chickens showed that the mutant individuals with genotype II had the highest values for body weight (BW) at 0 days and 2, 4, 6, 8, 10 and 12 weeks, shank girth (SG) at 4, 8 and 12 weeks, chest width (CW) at 4, 8 and 12 weeks, body slant length (BSL) at 8 and 12 weeks, and pelvic width (PW) at 4, 8 and 12 weeks, followed by ID and DD genotypes. The amplification and typing of 2,716 chickens from ten different breeds, namely, the F2 chicken resource population, dual-type chickens, including Xichuan black-bone chickens, Lushi green-shell layers, Dongxiang green-shell layers, Changshun green-shell layers, and Gushi chickens, and commercial broilers, including Ross 308, AA, Cobb and Hubbard broilers, revealed that II was the dominant genotype. Interestingly, only genotype II existed among the tested populations of commercial broilers. Moreover, the expression level in the pancreas tissue of Ross 308 chickens was significantly higher than that in the pancreas tissue of Gushi chickens (P < 0.001), which might be related to the conversion rates among different chickens. The prediction and verification of the target gene of LncFAM showed that LncFAM might regulate the expression of its target gene FAM48A through cis-expression. Our results provide useful information on the mutation of LncFAM, which can be used as a potential molecular breeding marker.

Genome-wide association study reveals the genetic determinism of growth traits in a Gushi-Anka F2 chicken population

Chicken growth traits are economically important, but the relevant genetic mechanisms have not yet been elucidated. Herein, we performed a genome-wide association study to identify the variants associated with growth traits. In total, 860 chickens from a Gushi-Anka F₂ resource population were phenotyped for 68 growth and carcass traits, and 768 samples were genotyped based on the genotyping-by-sequencing (GBS) method. Finally, 734 chickens and 321,314 SNPs remained after quality control and removal of the sex chromosomes, and these data were used to carry out a GWAS analysis. A total of 470 significant single-nucleotide polymorphisms (SNPs) for 43 of the 68 traits were detected and mapped on chromosomes (Chr) 1-6, -9, -10, -16, -18, -23, and -27. Of these, the significant SNPs in Chr1, -4, and -27 were found to be associated with more than 10 traits. Multiple traits shared significant SNPs, indicating that the same mutation in the region might have a large effect on multiple growth or carcass traits. Haplotype analysis revealed that SNPs within the candidate region of Chr1 presented a mosaic pattern. The significant SNPs and pathway enrichment analysis revealed that the MLNR, MED4, CAB39L, LDB2, and IGF2BP1 genes could be putative candidate genes for growth and carcass traits. The findings of this study improve our understanding of the genetic mechanisms regulating chicken growth and carcass traits and provide a theoretical basis for chicken breeding programs.

Multiple ancestral haplotypes harboring regulatory mutations cumulatively contribute to a QTL affecting chicken growth traits

In depth studies of quantitative trait loci (QTL) can provide insights to the genetic architectures of complex traits. A major effect QTL at the distal end of chicken chromosome 1 has been associated with growth traits in multiple populations. This locus was fine-mapped in a fifteen-generation chicken advanced intercross population including 1119 birds and explored in further detail using 222 sequenced genomes from 10 high/low body weight chicken stocks. We detected this QTL that, in total, contributed 14.4% of the genetic variance for growth. Further, nine mosaic precise intervals (Kb level) which contain ancestral regulatory variants were fine-mapped and we chose one of them to demonstrate the key regulatory role in the duodenum. This is the first study to break down the detail genetic architectures for the well-known QTL in chicken and provides a good example of the fine-mapping of various of quantitative traits in any species.

Endocrine and genetic factors affecting egg laying performance in chickens: a review

1. Egg-laying performance reflects the overall reproductive performance of breeding hens. The genetic traits for egg-laying performance have low or medium heritability, and, depending on the period involved, usually ranges from 0.16 to 0.64. Egg-laying in chickens is regulated by a combination of environmental, endocrine and genetic factors. 2. The main endocrine factors that regulate egg-laying are gonadotropin-releasing hormone (GnRH), prolactin (PRL), follicle-stimulating hormone (FSH) and luteinising hormone (LH). 3. In the last three decades, many studies have explored this aspect at a molecular genetic level. Recent studies identified 31 reproductive hormone-based candidate genes that were significantly associated with egg-laying performance. With the development of genome-sequencing technology, 64 new candidate genes and 108 single nucleotide polymorphisms (SNPs) related to egg-laying performance have been found using genome-wide association studies (GWAS), providing novel insights into the molecular genetic mechanisms governing egg production. At the same time, microRNAs that regulate genes responsible for egg-laying in chickens were reviewed. 4. Research on endocrinological and genetic factors affecting egg-laying performance will greatly improve the reproductive performance of chickens and promote the protection, development, and utilisation of poultry. This review summarises studies on the endocrine and genetic factors of egg-laying performance in chickens from 1972 to 2019.

Genome-wide association study for plasma very low-density lipoprotein concentration in chicken

The plasma very low-density lipoprotein (VLDL) concentration is an effective blood biochemical indicator that could be used to select lean chicken lines. In the current study, we used Genome-wide association study (GWAS) method to detect SNPs with significant effects on plasma VLDL concentration. As a result, 38 SNPs significantly associated with plasma VLDL concentration were identified using at least one of the three mixed linear model (MLM) packages, including GRAMMAR, EMMAX and GEMMA. Nearly, all these SNPs with significant effects on plasma VLDL concentration (except Gga_rs16160897) have significantly different allele frequencies between lean and fat lines. The 1-Mb regions surrounding these 38 SNPs were extracted, and twelve important regions were obtained after combining the overlaps. A total of 122 genes in these twelve important regions were detected. Among these genes, LRRK2, ABCD2, TLR4, E2F1, SUGP1, NCAN, KLF2 and RAB8A were identified as important genes for plasma VLDL concentration based on their basic functions. The results of this study may supply useful information to select lean chicken lines.

Quantitative trait loci mapping for the shear force value in breast muscle of F2 chickens

The shear force value is one of the major traits that determine meat quality. In the present study, we performed QTL analysis for chicken breast muscle shear force value at 7 wk of age using 545 single nucleotide polymorphism (SNP) markers developed via restriction-site associated DNA sequencing (RAD-seq). An F2 resource family was generated by mating Oh-Shamo, a native Japanese chicken breed, and the White Plymouth Rock chicken breed. A total of 215 F2 birds were produced. Simple interval mapping revealed one significant main-effect QTL between 6.28 and 8.10 Mb SNPs on the chromosome Z with a logarithm of odds score of 5.53 at the genome-wide 5% level. At this QTL, the confidence interval, phenotypic variance explained, and additive effect were 26 cM, 12.24%, and -0.31 in males and -0.34 in females, respectively. No QTL with epistatic interaction effects were detected. To our knowledge, this is the first report on a QTL affecting the shear force value in the chicken breast muscle, using SNP markers derived from RAD-seq.

Mapping of Quantitative Trait Loci for Growth and Carcass-Related Traits in Chickens Using a Restriction-Site Associated DNA Sequencing Method

In the present study, quantitative trait loci (QTLs) analysis was performed to identify the chromosomal positions of growth and carcass-related trait QTLs using 319 F₂ chickens obtained from intercrosses of an Oh-Shamo male and four White Plymouth Rock females. Body weight was measured weekly until the birds were 7 weeks old. Carcass-related traits were also measured at this timepoint. A genetic linkage map was constructed using 545 single nucleotide polymorphism (SNP) markers that were developed using a restriction-site associated DNA sequencing method. The linkage map included the 23 autosomes and the Z chromosome. Using simple interval QTL mapping, we were able to identify 10 significant and suggestive main-effect QTLs for growth and carcass-related traits present on chromosomes 1, 2, 3, 5, 8, 19, 24, and Z. These loci explained 5.60–16.52% of the phenotypic variances. The chromosomal positions of the 10 QTLs overlapped with those of previously reported QTLs, whereas the targeted traits varied. Our QTLs will aid future breeding programs in improving growth and meat yield of chickens (e.g., via marker-assisted selection), particularly in the Japanese brand chicken industry.

Identification of quantitative trait loci affecting production and biochemical traits in a unique Japanese quail resource population

The objective of the current study was to identify QTL associated with body weight, growth rate, egg quality traits, concentration of selected blood plasma, and yolk lipids as well as concentration of selected macro- and microelements, color, pH, basic chemical composition, and drip loss of breast muscle of Japanese quail (Coturnix japonica). Twenty-two meat-type males (line F33) were crossed with twenty-two laying-type females (line S22) to produce a generation of F1 hybrids. The F2 generation was created by mating 44 randomly chosen F1 hybrids, which were full siblings. The birds were individually weighed from the first to eighth week of age. At the age of 19 wk, 2 to 4 eggs were individually collected from each female and an analysis of the egg quality traits was performed. At slaughter, blood and breast muscles were collected from 324 individuals of the resource population. The basic chemical composition, concentration of chosen macro- and microelements, color, pH, and drip loss were determined in the muscle samples. The concentration of chosen lipids was determined in egg yolk and blood plasma. In total, 30 microsatellite markers located on chromosome 1 and 2 were genotyped. QTL mapping including additive and dominance genetic effects revealed 6 loci on chromosome 1 of the Japanese quail affecting the egg number, egg production rate, egg weight, specific gravity, egg shell weight, concentration of Na in breast muscle. In turn, there were 9 loci on chromosome 2 affecting the body weight in the first, fourth, and sixth week of age, growth rate in the second and seventh week of age, specific gravity, concentration of K and Cu in breast muscle, and the levels of triacylglycerols in blood plasma. In this study, QTL with a potential effect on the Na, K, and Cu content in breast muscles in poultry and on specific gravity in the Japanese quail were mapped for the first time.

Genetic Analysis of a Commercial Egg Laying Line Challenged With Newcastle Disease Virus

In low income countries, chickens play a vital role in daily life. They provide a critical source of protein through egg production and meat. Newcastle disease, caused by avian paramyxovirus type 1, has been ranked as the most devastating disease for scavenging chickens in Africa and Asia. High mortality among flocks infected with velogenic strains leads to a devastating loss of dietary protein and buying power for rural households. Improving the genetic resistance of chickens to Newcastle Disease virus (NDV), in addition to vaccination, is a practical target for improvement of poultry production in low income countries. Because response to NDV has a component of genetic control, it can be influenced through selective breeding. Adding genomic information to a breeding program can increase the amount of genetic progress per generation. In this study, we challenged a commercial egg-laying line with a lentogenic strain of NDV, measured phenotypic responses, collected genotypes, and associated genotypes with phenotypes. Collected phenotypes included viral load at 2 and 6 days post-infection (dpi), antibody levels pre-challenge and 10 dpi, and growth rates pre- and post-challenge. Six suggestive QTL associated with response to NDV and/or growth were identified, including novel and known QTL confirming previously reported associations with related traits. Additionally, previous RNA-seq analysis provided support for several of the genes located in or near the identified QTL. Considering the trend of negative genetic correlation between antibody and Newcastle Disease tolerance (growth under disease) and estimates of moderate to high heritability, we provide evidence that these NDV response traits can be influenced through selective breeding. Producing chickens that perform favorably in challenging environments will ultimately increase the supply of quality protein for human consumption.

Identification of quantitative trait loci for body temperature, body weight, breast yield, and digestibility in an advanced intercross line of chickens under heat stress

Background

Losses in poultry production due to heat stress have considerable negative economic consequences. Previous studies in poultry have elucidated a genetic influence on response to heat. Using a unique chicken genetic resource, we identified genomic regions associated with body temperature (BT), body weight (BW), breast yield, and digestibility measured during heat stress. Identifying genes associated with a favorable response during high ambient temperature can facilitate genetic selection of heat-resilient chickens.

Methods

Generations F18 and F19 of a broiler (heat-susceptible) × Fayoumi (heat-resistant) advanced intercross line (AIL) were used to fine-map quantitative trait loci (QTL). Six hundred and thirty-one birds were exposed to daily heat cycles from 22 to 28 days of age, and phenotypes were measured before heat treatment, on the 1st day and after 1 week of heat treatment. BT was measured at these three phases and BW at pre-heat treatment and after 1 week of heat treatment. Breast muscle yield was calculated as the percentage of BW at day 28. Ileal feed digestibility was assayed from digesta collected from the ileum at day 28. Four hundred and sixty-eight AIL were genotyped using the 600 K Affymetrix chicken SNP (single nucleotide polymorphism) array. Trait heritabilities were estimated using an animal model. A genome-wide association study (GWAS) for these traits and changes in BT and BW was conducted using Bayesian analyses. Candidate genes were identified within 200-kb regions around SNPs with significant association signals.

Results

Heritabilities were low to moderate (0.03 to 0.35). We identified QTL for BT on Gallus gallus chromosome (GGA)14, 15, 26, and 27; BW on GGA1 to 8, 10, 14, and 21; dry matter digestibility on GGA19, 20 and 21; and QTL of very large effect for breast muscle yield on GGA1, 15, and 22 with a single 1-Mb window on GGA1 explaining more than 15 % of the genetic variation.

Conclusions

This is the first study to estimate heritabilities and perform GWAS using this AIL for traits measured during heat stress. Significant QTL as well as low to moderate heritabilities were found for each trait, and these QTL may facilitate selection for improved animal performance in hot climatic conditions.

Quantitative trait loci segregating in crosses between New Hampshire and White Leghorn chicken lines: IV. Growth performance

Reciprocal crosses between the inbred lines New Hampshire (NHI) and White Leghorn (WL77) comprising 579 F2 individuals were used to map QTL for body weight and composition. Here, we examine the growth performance until 20 weeks of age. Linkage analysis provided evidence for highly significant QTL on GGA1, 2, 4, 10 and 27 which had specific effects on early or late growth. The highest QTL effects, accounting for 4.6-25.6% of the phenotypic F2 variance, were found on the distal region of GGA4 between 142 and 170 cM (F ≥ 13.68). The NHI QTL allele increased body mass by 141.86 g at 20 weeks. Using body weight as a covariate in the analysis of body composition traits provided evidence for genes in the GGA4 QTL region affecting fat mass independently of body mass. The QTL effect size differed between sexes and depended on the direction of cross. TBC1D1, CCKAR and PPARGC1A are functional candidate genes in the QTL peak region. Our study confirmed the importance of the distal GGA4 region for chicken growth performance. The strong effect of the GGA4 QTL makes fine mapping and gene discovery feasible.

Changes in variance explained by top SNP windows over generations for three traits in broiler chicken

The purpose of this study was to determine if the set of genomic regions inferred as accounting for the majority of genetic variation in quantitative traits remain stable over multiple generations of selection. The data set contained phenotypes for five generations of broiler chicken for body weight, breast meat, and leg score. The population consisted of 294,632 animals over five generations and also included genotypes of 41,036 single nucleotide polymorphism (SNP) for 4,866 animals, after quality control. The SNP effects were calculated by a GWAS type analysis using single step genomic BLUP approach for generations 1-3, 2-4, 3-5, and 1-5. Variances were calculated for windows of 20 SNP. The top ten windows for each trait that explained the largest fraction of the genetic variance across generations were examined. Across generations, the top 10 windows explained more than 0.5% but less than 1% of the total variance. Also, the pattern of the windows was not consistent across generations. The windows that explained the greatest variance changed greatly among the combinations of generations, with a few exceptions. In many cases, a window identified as top for one combination, explained less than 0.1% for the other combinations. We conclude that identification of top SNP windows for a population may have little predictive power for genetic selection in the following generations for the traits here evaluated.

Genetic analysis of an F2 intercross between two strains of Japanese quail provided evidence for quantitative trait loci affecting carcass composition and internal organs

The purpose of this study was to identify genomic regions, quantitative trait loci (QTL), affecting carcass traits on chromosome 1 in an F2 population of Japanese quail. For this purpose, two white and wild strains of Japanese quail (16 birds) were crossed reciprocally and F1 generation (34 birds) was created. The F2 generation was produced by intercrossing of the F1 birds. Phenotypic data including carcass weight, internal organs and carcass parts were collected on F2 animals (422 birds). The total mapping population (472 birds) was genotyped for 8 microsatellite markers on chromosome 1. QTL analysis was performed with interval mapping method applying the line-cross model. Significant QTL were identified for breast weight at 0 (P < 0.01), 172 (P < 0.05) and 206 (P < 0.01), carcass weight at 91 (P < 0.05), carcass fatness at 0 (P < 0.01), pre-stomach weight at 206 (P < 0.01) and uropygial weight gland at 197 (P < 0.01) cM on chromosome 1. There was also evidence for imprinted QTL affecting breast weight (P < 0.01) on chromosome 1. The proportion of the F2 phenotypic variation explained by the significant additive, dominance and imprinted QTL effects ranged from 1.0 to 7.3%, 1.2 to 3.3% and 1.4 to 2.2%, respectively.

Overview of Genomic Insights into Chicken Growth Traits Based on Genome-Wide Association Study and microRNA Regulation

Over the two past decades, a significant number of studies have observed animal growth traits to examine animal genetic mechanisms due to their ease of measurement and high heritability. Chicken which has a significant impact on fundamental biology is a major source of protein worldwide, making it an ideal model for examining animal growth trait development. The genetic mechanisms of chicken growth traits have been studied using quantitative trait loci mapping through genome-scan and candidate gene approaches, genome-wide association studies (GWAS), comparative genomic strategies, microRNA (miRNA) regulation of growth development analysis, and epigenomic analysis. This review focuses on chicken GWAS and miRNA regulation of growth traits. Several recently published GWAS reports showed that most genome-wide significant single nucleotide polymorphisms are located on chromosomes 1 and 4 in chickens. Chicken growth, particularly skeletal muscle growth and development, is greatly regulated by miRNA. Using dwarf and normal chickens, let-7b was found to be involved in determining chicken dwarf phenotypes by regulating growth hormone receptor gene expression.

Association study of polymorphisms inside the miR-1657 seed region with chicken growth and meat traits

1. Polymorphisms occurring in the seed region of microRNAs (miRNAs) could influence their target gene and lead to phenotypic variation. The purpose of the research was to explore the genetic effects of the rs14934924 (G > A) mutation resident in the conserved seed region of miR-1657 on growth and meat traits of the Gushi-Anka F2 resource population. 2. The NdeI polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method and association analysis were used to analyse the polymorphism. 3. The mutation was associated with body weight at 8 weeks of age, shank girth at 12 weeks of age, breast bone length at 12 weeks of age, pelvis breadth at 4 weeks of age and subcutaneous fat thickness (P < 0·05) and was associated with body weight at 4, 6, 10 and 12 weeks of age (P < 0·01). 4. Our results will be a useful resource for a subsequent study in miRNA function, and provide a basis for molecular techniques in chicken breeding.

Genome-wide association study identifies Loci and candidate genes for body composition and meat quality traits in Beijing-You chickens

Body composition and meat quality traits are important economic traits of chickens. The development of high-throughput genotyping platforms and relevant statistical methods have enabled genome-wide association studies in chickens. In order to identify molecular markers and candidate genes associated with body composition and meat quality traits, genome-wide association studies were conducted using the Illumina 60 K SNP Beadchip to genotype 724 Beijing-You chickens. For each bird, a total of 16 traits were measured, including carcass weight (CW), eviscerated weight (EW), dressing percentage, breast muscle weight (BrW) and percentage (BrP), thigh muscle weight and percentage, abdominal fat weight and percentage, dry matter and intramuscular fat contents of breast and thigh muscle, ultimate pH, and shear force of the pectoralis major muscle at 100 d of age. The SNPs that were significantly associated with the phenotypic traits were identified using both simple (GLM) and compressed mixed linear (MLM) models. For nine of ten body composition traits studied, SNPs showing genome wide significance (P<2.59E-6) have been identified. A consistent region on chicken (Gallus gallus) chromosome 4 (GGA4), including seven significant SNPs and four candidate genes (LCORL, LAP3, LDB2, TAPT1), were found to be associated with CW and EW. Another 0.65 Mb region on GGA3 for BrW and BrP was identified. After measuring the mRNA content in beast muscle for five genes located in this region, the changes in GJA1 expression were found to be consistent with that of breast muscle weight across development. It is highly possible that GJA1 is a functional gene for breast muscle development in chickens. For meat quality traits, several SNPs reaching suggestive association were identified and possible candidate genes with their functions were discussed.

Comparative analysis of quantitative trait loci for body weight, growth rate and growth curve parameters from 3 to 72 weeks of age in female chickens of a broiler-layer cross

Background

Comparisons of quantitative trait loci (QTL) for growth and parameters of growth curves assist in understanding the genetics and ultimately the physiology of growth. Records of body weight at 3, 6, 12, 24, 48 and 72 weeks of age and growth rate between successive age intervals of about 500 F₂ female chickens of the Roslin broiler-layer cross were available for analysis. These data were analysed to detect and compare QTL for body weight, growth rate and parameters of the Gompertz growth function.

Results

Over 50 QTL were identified for body weight at specific ages and most were also detected in the nearest preceding and/or subsequent growth stage. The sum of the significant and suggestive additive effects for bodyweight at specific ages accounted for 23-43% of the phenotypic variation. A single QTL for body weight on chromosome 4 at 48 weeks of age had the largest additive effect (550.4 ± 68.0 g, 11.5% of the phenotypic variation) and a QTL at a similar position accounted 14.5% of the phenotypic variation at 12 weeks of age. Age specific QTL for growth rate were detected suggesting that there are specific genes that affect developmental processes during the different stages of growth. Relatively few QTL influencing Gompertz growth curve parameters were detected and overlapped with loci affecting growth rate. Dominance effects were generally not significant but from 12 weeks of age they exceeded the additive effect in a few cases. No evidence for epistatic QTL pairs was found.

Conclusions

The results confirm the location for body weight and body weight gain during growth that were identified in previous studies and were consistent with QTL for the parameters of the Gompertz growth function. Chromosome 4 explained a relatively large proportion of the observed growth variation across the different ages, and also harboured most of the detected QTL for Gompertz parameters, confirming its importance in controlling growth. Very few QTL were detected for body weight or gain at 48 and 72 weeks of age, probably reflecting the effect of differences in reproduction and random environmental effects.

Genetic dissection of growth traits in a Chinese indigenous × commercial broiler chicken cross

Background

In China, consumers often prefer indigenous broiler chickens over commercial breeds, as they have characteristic meat qualities requested within traditional culinary customs. However, the growth-rate of these indigenous breeds is slower than that of the commercial broilers, which means they have not yet reached their full economic value. Therefore, combining the valuable meat quality of the native chickens with the efficiency of the commercial broilers is of interest. In this study, we generated an F₂ intercross between the slow growing native broiler breed, Huiyang Beard chicken, and the fast growing commercial broiler breed, High Quality chicken Line A, and used it to map loci explaining the difference in growth rate between these breeds.

Results

A genome scan to identify main-effect loci affecting 24 growth-related traits revealed nine distinct QTL on six chromosomes. Many QTL were pleiotropic and conformed to the correlation patterns observed between phenotypes. Most of the mapped QTL were found in locations where growth QTL have been reported in other populations, although the effects were greater in this population. A genome scan for pairs of interacting loci identified a number of additional QTL in 10 other genomic regions. The epistatic pairs explained 6–8% of the residual phenotypic variance. Seven of the 10 epistatic QTL mapped in regions containing candidate genes in the ubiquitin mediated proteolysis pathway, suggesting the importance of this pathway in the regulation of growth in this chicken population.

Conclusions

The main-effect QTL detected using a standard one-dimensional genome scan accounted for a significant fraction of the observed phenotypic variance in this population. Furthermore, genes in known pathways present interesting candidates for further exploration. This study has thus located several QTL regions as promising candidates for further study, which will increase our understanding of the genetic mechanisms underlying growth-related traits in chickens.

Comparison of the genome-wide DNA methylation profiles between fast-growing and slow-growing broilers

INTRODUCTION

Growth traits are important in poultry production, however, little is known for its regulatory mechanism at epigenetic level. Therefore, in this study, we aim to compare DNA methylation profiles between fast- and slow-growing broilers in order to identify candidate genes for chicken growth. Methylated DNA immunoprecipitation-sequencing (MeDIP-seq) was used to investigate the genome-wide DNA methylation pattern in high and low tails of Recessive White Rock (WRR(h); WRR(l)) and that of Xinhua Chickens (XH(h); XH(l)) at 7 weeks of age. The results showed that the average methylation density was the lowest in CGIs followed by promoters. Within the gene body, the methylation density of introns was higher than that of UTRs and exons. Moreover, different methylation levels were observed in different repeat types with the highest in LINE/CR1. Methylated CGIs were prominently distributed in the intergenic regions and were enriched in the size ranging 200-300 bp. In total 13,294 methylated genes were found in four samples, including 4,085 differentially methylated genes of WRR(h) Vs. WRR(l), 5,599 of XH(h) Vs. XH(l), 4,204 of WRR(h) Vs. XH(h), as well as 7,301 of WRR(l) Vs. XH(l). Moreover, 132 differentially methylated genes related to growth and metabolism were observed in both inner contrasts (WRR(h) Vs. WRR(l) and XH(h) Vs. XH(l)), whereas 129 differentially methylated genes related to growth and metabolism were found in both across-breed contrasts (WRR(h) Vs. XH(h) and WRR(l) Vs. XH(l)). Further analysis showed that overall 75 genes exhibited altered DNA methylation in all four contrasts, which included some well-known growth factors of IGF1R, FGF12, FGF14, FGF18, FGFR2, and FGFR3. In addition, we validate the MeDIP-seq results by bisulfite sequencing in some regions.

CONCLUSIONS

This study revealed the global DNA methylation pattern of chicken muscle, and identified candidate genes that potentially regulate muscle development at 7 weeks of age at methylation level.

A genome-wide scan of selective sweeps in two broiler chicken lines divergently selected for abdominal fat content

Background

Genomic regions controlling abdominal fatness (AF) were studied in the Northeast Agricultural University broiler line divergently selected for AF. In this study, the chicken 60KSNP chip and extended haplotype homozygosity (EHH) test were used to detect genome-wide signatures of AF.

Results

A total of 5357 and 5593 core regions were detected in the lean and fat lines, and 51 and 57 reached a significant level (P<0.01), respectively. A number of genes in the significant core regions, including RB1, BBS7, MAOA, MAOB, EHBP1, LRP2BP, LRP1B, MYO7A, MYO9A and PRPSAP1, were detected. These genes may be important for AF deposition in chickens.

Conclusions

We provide a genome-wide map of selection signatures in the chicken genome, and make a contribution to the better understanding the mechanisms of selection for AF content in chickens. The selection for low AF in commercial breeding using this information will accelerate the breeding progress.

Genome-wide association study identified a narrow chromosome 1 region associated with chicken growth traits

Chicken growth traits are important economic traits in broilers. A large number of studies are available on finding genetic factors affecting chicken growth. However, most of these studies identified chromosome regions containing putative quantitative trait loci and finding causal mutations is still a challenge. In this genome-wide association study (GWAS), we identified a narrow 1.5 Mb region (173.5-175 Mb) of chicken (Gallus gallus) chromosome (GGA) 1 to be strongly associated with chicken growth using 47,678 SNPs and 489 F2 chickens. The growth traits included aggregate body weight (BW) at 0-90 d of age measured weekly, biweekly average daily gains (ADG) derived from weekly body weight, and breast muscle weight (BMW), leg muscle weight (LMW) and wing weight (WW) at 90 d of age. Five SNPs in the 1.5 Mb KPNA3-FOXO1A region at GGA1 had the highest significant effects for all growth traits in this study, including a SNP at 8.9 Kb upstream of FOXO1A for BW at 22-48 d and 70 d, a SNP at 1.9 Kb downstream of FOXO1A for WW, a SNP at 20.9 Kb downstream of ENSGALG00000022732 for ADG at 29-42 d, a SNP in INTS6 for BW at 90 d, and a SNP in KPNA3 for BMW and LMW. The 1.5 Mb KPNA3-FOXO1A region contained two microRNA genes that could bind to messenger ribonucleic acid (mRNA) of IGF1, FOXO1A and KPNA3. It was further indicated that the 1.5 Mb GGA1 region had the strongest effects on chicken growth during 22-42 d.

Genetic mapping of quantitative trait loci affecting bodyweight on chromosome 1 in a commercial strain of Japanese quail

This study was conducted to identify quantitative trait loci (QTL) affecting growth on chromosome 1 in quail. Liveweight data were recorded on 300 progeny from three half-sib families created from a commercial strain of Japanese quail. Three half-sib families were genotyped for nine microsatellite loci on chromosome 1 and QTL analysis was conducted applying the least-squares interval mapping approach. Significant QTL affecting bodyweight at 3, 4, 5 and 6 weeks of age, average daily gain, and Kleiber ratio, an indirect criterion for feed efficiency, were mapped at 0–23 cM on chromosome 1. The detected QTL segregated in two of the three half-sib families and the size of the QTL effect ranged from 0.6 to 1.1 in unit of the trait standard deviation. This is the first report of liveweight QTL segregating in a commercial strain of Japanese quail.

Quantitative trait loci underlying hatching weight and growth traits in an F2 intercross between two strains of Japanese quail

A three-generation resource population was developed using two distinct Japanese quail strains, wild and white, to map quantitative trait loci underlying hatching weight and growth traits. Eight pairs of white and wild birds were crossed reciprocally and 34 F1 birds were produced. The F1 birds were intercrossed to generate 422 F2 offspring. All of the animals from three generations (472 birds) were genotyped for eight microsatellite markers on chromosome 1. Liveweight data from hatch to 5 weeks of age were collected on the F2 birds. Quantitative trait loci (QTL) analysis was conducted applying the line-cross model and the least-squares interval mapping approach. The results indicated QTL affecting hatching weight and several growth related traits on chromosome 1. The F2 phenotypic variance explained by the detected additive QTL effects ranged from 1.0 to 3.7 for different traits. Modelling both additive and dominance QTL effects revealed additional QTL with significant dominance mode of action affecting pre-slaughter weight. However, there was no evidence for imprinting (parent-of-origin) effects. The variance due to the reciprocal cross effect ranged between 3.0 and 19.1% for weight at 1 week of age and hatching weight, respectively.

Sequence analysis of a pea comb locus on chicken chromosome 1

To facilitate gene identification, this study aimed to narrow the scope of the genome region affecting chicken comb type by using two bird populations. First, an F2 resource population was generated by crossing Japanese game fowl (Shamo; pea comb, P/p and P/P) with White Plymouth Rock (single comb, p/p). Comb types of the 240 F2 offspring produced by an F1 intercross between eight males and 57 females were segregated at a ratio of 3:1 (pea:single). The pea comb locus was mapped to a chromosomal region on Gallus gallus chromosome 1 that was flanked by microsatellite markers MCW0112, MCW0019 and ABR521. The second population (five-generation, n=1300 animals) was derived from a cross between Shamo and Rhode Island Red (single comb, p/p) that had been genotyped for additional polymorphic single nucleotide polymorphisms and microsatellite markers within this region through development of chicken draft sequences. To close some gaps in these draft sequences, we constructed a bacterial artificial chromosome contig and sequenced it using the shotgun sequencing technique. Chickens selected from pedigrees in these populations were grouped by inheritance of a P or p haplotype at the locus constructed by the additional markers. Finally, this locus was fine-mapped to roughly 60 kb based on the association of haplotypes and comb types. Chicken genome sequences suggest that the most likely polymorphism responsible for the pea comb locus is a duplicated sequence and that the sex determining region Y-box 5 gene, one predicted gene and one expressed sequence tag in a critical region may be associated with the duplicated sequence.

Polymorphism of insulin-like growth factor 1 gene is associated with breast muscle yields in chickens

Insulin-like growth factor-1 (IGF1) plays an important role in muscle development in chickens. In this study, an F2 chicken population of 362 individuals, obtained from an intercross between high breast muscle yield line males and low breast muscle yield (LB) line females, was constructed for investigating the associations between IGF1 gene and breast muscle yields. The IGF1 sequence was investigated in the grandparents. There were no differences in the exon sequences. However, sequence analysis of the IGF1 promoter revealed a known single nucleotide polymorphism (g.570C>A) in LB line grandparents. PCR - restriction fragment length polymorphism was used for screening the F2 population, which was evaluated for body weight (BW), carcass weight (CW), breast muscle weight (BMW), and breast fillet weight (BFW). Significant associations with the polymorphism were detected for BMW, BFW, BMW% and BFW%, although there were no associations between the polymorphism and BW or CW. The allelic effect on BMW, BFW, BMW% and BFW% acted in additive and dominance modes. We confirmed that the g.570C>A polymorphism is significantly associated with breast muscle yields in the F2 population. Therefore, this polymorphism in the IGF1 gene may help improve breast muscle yields by marker-assisted selection.

Fine-mapping of muscle weight QTL in LG/J and SM/J intercrosses

Genetic variation plays a substantial role in variation in strength, but the underlying mechanisms remain poorly understood. The objective of the present study was to examine the mechanisms underlying variation in muscle mass, a predictor of strength, between LG/J and SM/J strains, which are the inbred progeny of mice selected, respectively, for high and low body weight. We measured weight of five hindlimb muscles in LG/J and SM/J males and females, in F(1) and F(2) intercrosses, and in an advanced intercross (AI), F(34), between the two. F(2) mice were genotyped using 162 SNPs throughout the genome; F(34) mice were genotyped at 3,015 SNPs. A twofold difference in muscle mass between the LG/J and SM/J mouse strains was observed. Integrated genome-wide association analysis in the combined population of F(2) and AI identified 22 quantitative trait loci (QTL; genome-wide P < 0.05) affecting muscle weight on Chr 2 (2 QTL), 4, 5, 6 (7 QTL), 7 (4 QTL), 8 (4 QTL), and 11 (3 QTL). The LG/J allele conferred greater muscle weight in all cases. The 1.5-LOD QTL support intervals ranged between 0.3 and 13.4 Mb (median 3.7 Mb) restricting the list of candidates to between 5 and 97 genes. Selection for body weight segregated the alleles affecting skeletal muscle, the most abundant tissue in the body. Combination of analyses in an F(2) and AI was an effective strategy to detect and refine the QTL in a genome-wide manner. The achieved resolution facilitates further elucidation of the underlying genetic mechanisms affecting muscle mass.