Genetic mapping of quantitative trait loci affecting body weight, egg character and egg production in F2 intercross chickens

Genome-wide association analysis of eggshell color of an F2 generation population reveals candidate genes in chickens

Eggshell color is an important visual characteristic that affects consumer preferences for eggs. Eggshell color, which has moderate to high heritability, can be effectively enhanced through molecular marker selection. Various studies have been conducted on eggshell color at specific time points. However, few longitudinal data are available on eggshell color. Therefore, the objective of this study was to investigate eggshell color using the Commission International de L'Eclairage L*a*b* system with multiple measurements at different ages (age at the first egg and at 32, 36, 40, 44, 48, 52, 56, 60, 66, and 72 weeks) within the same individuals from an F2 resource population produced by crossing White Leghorn and Dongxiang Blue chicken. Using an Affymetrix 600 single nucleotide polymorphism (SNP) array, we estimated the genetic parameters of the eggshell color trait, performed genome-wide association studies (GWASs), and screened for the potential candidate genes. The results showed that pink-shelled eggs displayed a significant negative correlation between L* values and both a* and b* values. Genetic heritability based on SNPs showed that the heritability of L*, a*, and b* values ranged from 0.32 to 0.82 for pink-shelled eggs, indicating a moderate to high level of genetic control. The genetic correlations at each time point were mostly above 0.5. The major-effect regions affecting the pink eggshell color were identified in the 10.3-13.0 Mb interval on Gallus gallus chromosome 20, and candidate genes were selected, including SLC35C2, PCIF1, and SLC12A5. Minor effect polygenic regions were identified on chromosomes 1, 6, 9, 12, and 15, revealing 11 candidate genes, including MTMR3 and SLC35E4. Members of the solute carrier family play an important role in influencing eggshell color. Overall, our findings provide valuable insights into the phenotypic and genetic aspects underlying the variation in eggshell color. Using GWAS analysis, we identified multiple quantitative trait loci (QTLs) for pink eggshell color, including a major QTL on chromosome 20. Genetic variants associated with eggshell color may be used in genomic breeding programs.

Genome-wide association study identifies multiple loci influencing duck serum biochemical indicators in the laying period

1. Laying performance is an important economic trait in poultry. The blood is essential in transporting nutrients to the yolk and albumen and is necessary for egg formation.2. This study calculated the phenotypic relationships of duck egg quality, egg production efficiency and 22 serum parameters in the egg-laying stage. Using a variety of methodologies, a genome-wide association study (GWAS) was carried out to uncover the genetic foundations of the 22 serum biochemical markers of laying ducks.3. Spearman correlation coefficients between the egg production (226-329 per day) and the serum parameters were all weak, being less than 0.3. This analysis was done on 22 serum parameters, with total protein (TP), total triglycerides (TG), calcium (Ca) and phosphorous (P) having the highest correlation coefficients (r = 0.56-0.88). The coefficients for blood markers, such as total cholesterol (CHOL), total bilirubin (TBIL), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) varied from 0.70-0.94.4. Based on single-marker single-trait genome-wide analyses by a mixed linear model program of EMMAX, nine candidate genes were associated with enzyme traits (AST/ALT aspartate transaminase/glutamic-pyruvic transaminase, creatine kinase) and 19 candidate genes were associated with metabolism and protein-related serum parameters (glucose, total bile acid, uric acid (UA), albumin (ALB).5. The mvLMM (multivariate linear mixed model) of GEMMA software was used to carry out multiple trait integrated GWAS. Two candidate genes were found in the TP-TG-CA-P analysis and seven candidate genes in the CHOL_LDL-C_HDL-C_TBIL study. There was a high genetic correlation between the two groups.

Refine localizations of functional variants affecting eggshell color of Lueyang black-boned chicken in the SLCO1B3

Table eggs with color-uniformity shell are visually attractive for consumers. Lueyang black-boned chicken (LBC) lays colorful eggs, which is undesirable for sale of table eggs, but provides a segregating population for mapping functional variants affecting eggshell color. SLCO1B3 was identified as the causative gene for blue eggs in the Dongxiang and Araucana chickens. The aim of this study is to map functional variants associated with chicken eggshell color in the SLCO1B3. Eggshell color of LBC (n = 383) was measured using the L*a*b color space. SLCO1B3 was resequencing using a subset (n = 30) of 383 samples. Linkage disequilibrium among 139 SNP was analyzed. Association of 16 SNP in the SLCO1B3 and 8 in CPOX, ALAS1, and ABCG2 genes with L*a*b were tested by a polygenic model (LMM) and a polygenic/oligogenic mixed model (BSLMM). Chromatin state annotations were retrieved from the UCSC database. Effect of SLCO1B3 variants distributed in mapping and upstream 1.6-kb regions on promoter activities were analyzed using dual-luciferase reporter assay. One hundred and thirty-nine variants maintained low linkage disequilibrium with 80% of r2 less than 0.226. Fifteen SLCO1B3 variants were significantly associated with a*, of which 1B3_SNP108 was showed the strongest association and the largest effect on a*. In the BSLMM, 1B3_SNP108 alone appeared in the Markov chain Monte Carlo as major variants in 100% of posterior inclusion probability. None of variants in CPOX, ALAS1, and ABCG2 were significantly associated with color indexes except that 2 ALAS1 variants were associated with L*. 1B3_SNP108 distributes in the Intron4 where 6 active enhancers and 1 ATAC island were enriched. However, 1B3_SNP108-containing constructs showed negligible activities in the reporter assay. No significant differences of activities between haplotypes were found for five 5'-deleted promoter constructs. The data recognizes 1B3_SNP108 as a valuable marker for breeding of eggshell color. Functional variants are localized in the region adjacent to the 1B3_SNP108 due to low linkage disequilibrium in the LBC. Our findings extend the role of SLCO1B3 from a causative gene for blue eggs to a major regulator driving continuous variation of LBC eggshell color.

Patterns of enrichment and acceleration in evolutionary rates of promoters suggest a role of regulatory regions in cetacean gigantism

BACKGROUND

Cetaceans (whales, porpoises, and dolphins) are a lineage of aquatic mammals from which some species became giants. Only recently, gigantism has been investigated from the molecular point of view. Studies focused mainly on coding regions, and no data on the influence of regulatory regions on gigantism in this group was available. Accordingly, we investigated the molecular evolution of non-coding regulatory regions of genes already described in the literature for association with size in mammals, focusing mainly on the promoter regions. For this, we used Ciiider and phyloP tools. Ciiider identifies significantly enriched transcription factor binding sites, and phyloP estimates the molecular evolution rate of the promoter.

RESULTS

We found evidence of enrichment of transcription binding factors related to large body size, with distinct patterns between giant and non-giant cetaceans in the IGFBP7 and NCAPG promoters, in which repressive agents are present in small cetaceans and those that stimulate transcription, in giant cetaceans. In addition, we found evidence of acceleration in the IGF2, IGFBP2, IGFBP7, and ZFAT promoters.

CONCLUSION

Our results indicate that regulatory regions may also influence cetaceans' body size, providing candidate genes for future research to understand the molecular basis of the largest living animals.

The molecular evolution of genes previously associated with large sizes reveals possible pathways to cetacean gigantism

Cetaceans are a group of aquatic mammals with the largest body sizes among living animals, including giant representatives such as blue and fin whales. To understand the genetic bases of gigantism in cetaceans, we performed molecular evolutionary analyses on five genes (GHSR, IGF2, IGFBP2, IGFBP7, and EGF) from the growth hormone/insulin-like growth factor axis, and four genes (ZFAT, EGF, LCORL, and PLAG1) previously described as related to the size of species evolutionarily close to cetaceans, such as pigs, cows, and sheep. Our dataset comprised 19 species of cetaceans, seven of which are classified as giants because they exceed 10 m in length. Our results revealed signs of positive selection in genes from the growth hormone/insulin-like growth factor axis and also in those related to body increase in cetacean-related species. In addition, pseudogenization of the EGF gene was detected in the lineage of toothless cetaceans, Mysticeti. Our results suggest the action of positive selection on gigantism in genes that act both in body augmentation and in mitigating its consequences, such as cancer suppression when involved in processes such as division, migration, and cell development control.

Genome-Wide Association Studies and Haplotype-Sharing Analysis Targeting the Egg Production Traits in Shaoxing Duck

Age at first egg (AFE) and egg number (EN) are economically important traits related to egg production, as they directly influence the benefits of the poultry industry, but the molecular genetic research that affects those traits in laying ducks is still sparse. Our objective was to identify the genomic regions and candidate genes associated with AFE, egg production at 43 weeks (EP43w), and egg production at 66 weeks (EP66w) in a Shaoxing duck population using genome-wide association studies (GWASs) and haplotype-sharing analysis. Single-nucleotide polymorphism (SNP)-based genetic parameter estimates showed that the heritability was 0.15, 0.20, and 0.22 for AFE, EP43w, and EP66w, respectively. Subsequently, three univariate GWASs for AFE, EP43w, and EP66w were carried out independently. Twenty-four SNPs located on chromosome 25 within a 0.01-Mb region that spans from 4.511 to 4.521 Mb were associated with AFE. There are two CIs that affect EP43w, i.e., twenty-five SNPs were in strong linkage disequilibrium region spanning from 3.186 to 3.247 Mb on chromosome 25, a region spanning from 4.442 to 4.446 Mb on chromosome 25, and two interesting genes, ACAD8 and THYN1, that may affect EP43w in laying ducks. There are also two CIs that affect EP66w, i.e., a 2.412-Mb region that spans from 127.497 to 129.910 Mb on chromosome 2 and a 0.355-Mb region that spans from 4.481 to 4.837 Mb on chromosome 29, and CA2 and GAMT may be the putative candidate genes. Our study also found some haplotypes significantly associated with these three traits based on haplotype-sharing analysis. Overall, this study was the first publication of GWAS on egg production in laying ducks, and our findings will be helpful to provide some candidate genes and haplotypes to improve egg production performance based on breeding in laying duck. Additionally, we learned from a method called bootstrap test to verify the reliability of a GWAS with small experimental samples that users can access at https://github.com/xuwenwu24/Bootstrap-test.

Mapping of Quantitative Trait Loci Controlling Egg-Quality and -Production Traits in Japanese Quail (Coturnix japonica) Using Restriction-Site Associated DNA Sequencing

This research was conducted to identify quantitative trait loci (QTL) associated with egg-related traits by constructing a genetic linkage map based on single nucleotide polymorphism (SNP) markers using restriction-site associated DNA sequencing (RAD-seq) in Japanese quail. A total of 138 F₂ females were produced by full-sib mating of F₁ birds derived from an intercross between a male of the large-sized strain with three females of the normal-sized strain. Eggs were investigated at two different stages: the beginning stage of egg-laying and at 12 weeks of age (second stage). Five eggs were analyzed for egg weight, lengths of the long and short axes, egg shell strength and weight, yolk weight and diameter, albumen weight, egg equator thickness, and yolk color (L*, a*, and b* values) at each stage. Moreover, the age at first egg, the cumulative number of eggs laid, and egg production rate were recorded. RAD-seq developed 118 SNP markers and mapped them to 13 linkage groups using the Map Manager QTX b20 software. Markers were spanned on 776.1 cM with an average spacing of 7.4 cM. Nine QTL were identified on chromosomes 2, 4, 6, 10, 12, and Z using the simple interval mapping method in the R/qtl package. The QTL detected affected 10 egg traits of egg weight, lengths of the long and short axes of egg, egg shell strength, yolk diameter and weight, albumen weight, and egg shell weight at the beginning stage, yellowness of the yolk color at the second stage, and age at first egg. This is the first report to perform a quail QTL analysis of egg-related traits using RAD-seq. These results highlight the effectiveness of RAD-seq associated with targeted QTL and the application of marker-assisted selection in the poultry industry, particularly in the Japanese quail.

Avian eggshell biomineralization: an update on its structure, mineralogy and protein tool kit

BACKGROUND

The avian eggshell is a natural protective envelope that relies on the phenomenon of biomineralization for its formation. The shell is made of calcium carbonate in the form of calcite, which contains hundreds of proteins that interact with the mineral phase controlling its formation and structural organization, and thus determine the mechanical properties of the mature biomaterial. We describe its mineralogy, structure and the regulatory interactions that integrate the mineral and organic constituents during eggshell biomineralization. Main Body. We underline recent evidence for vesicular transfer of amorphous calcium carbonate (ACC), as a new pathway to ensure the active and continuous supply of the ions necessary for shell mineralization. Currently more than 900 proteins and thousands of upregulated transcripts have been identified during chicken eggshell formation. Bioinformatic predictions address their functionality during the biomineralization process. In addition, we describe matrix protein quantification to understand their role during the key spatially- and temporally- regulated events of shell mineralization. Finally, we propose an updated scheme with a global scenario encompassing the mechanisms of avian eggshell mineralization.

CONCLUSION

With this large dataset at hand, it should now be possible to determine specific motifs, domains or proteins and peptide sequences that perform a critical function during avian eggshell biomineralization. The integration of this insight with genomic data (non-synonymous single nucleotide polymorphisms) and precise phenotyping (shell biomechanical parameters) on pure selected lines will lead to consistently better-quality eggshell characteristics for improved food safety. This information will also address the question of how the evolutionary-optimized chicken eggshell matrix proteins affect and regulate calcium carbonate mineralization as a good example of biomimetic and bio-inspired material design.

QTL analysis for early growth in an intercross between native Japanese Nagoya and White Plymouth Rock chicken breeds using RAD sequencing-based SNP markers

An F₂ population of 239 chickens was obtained by an intercross between Nagoya (NAG), a native Japanese breed with low growth, and White Plymouth Rock (WPR), a Western breed with high growth. Using SNP markers obtained by restriction site-associated DNA sequencing, genome-wide QTL analysis was performed and it revealed three QTL for early postnatal growth in the F₂ population at genome-wide 5% significance levels. The most highly significant QTL affecting body weights at 2-4 weeks of age and weight gains at 2-3 and 0-4 weeks was located on GGA4 between 34.0 and 65.6 Mb with LOD scores of 3.9-5.9 and it explained 4.9-9.9% of the total variance of the traits. The analysis provided evidence for significant QTL on GGA2 between 105.6 and 125.2 Mb (LOD = 4.6) and on GGA1 between 51.1 and 61.6 Mb (LOD = 4.0) which had effects on body weight at 3 weeks and body weight gain at 0-1 week respectively. These two genomic regions explained 6.6 and 6.9% of the phenotypic F₂ variance of the corresponding traits respectively. The allele derived from WPR at all QTL increased the corresponding traits. Neither sex-specific nor epistatic QTL was detected. The results showed that the GGA4 QTL affecting multiple traits is a key locus responsible for early growth in our chicken cross, suggesting that this QTL may make a great contribution to genetic improvement of growth performance of the NAG breed with a low growth rate.

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.

Genetic Dissection of Growth Traits in a Unique Chicken Advanced Intercross Line

The advanced intercross line (AIL) that is created by successive generations of pseudo-random mating after the F₂ generation is a valuable resource, especially in agricultural livestock and poultry species, because it improves the precision of quantitative trait loci (QTL) mapping compared with traditional association populations by introducing more recombination events. The growth traits of broilers have significant economic value in the chicken industry, and many QTLs affecting growth traits have been identified, especially on chromosomes 1, 4, and 27, albeit with large confidence intervals that potentially contain dozens of genes. To promote a better understanding of the underlying genetic architecture of growth trait differences, specifically body weight and bone development, in this study, we report a nine-generation AIL derived from two divergent outbred lines: High Quality chicken Line A (HQLA) and Huiyang Bearded (HB) chicken. We evaluate the genetic architecture of the F₀, F₂, F₈, and F₉ generations of AIL and demonstrate that the population of the F₉ generation sufficiently randomized the founder genomes and has the characteristics of rapid linkage disequilibrium decay, limited allele frequency decline, and abundant nucleotide diversity. This AIL yielded a much narrower QTL than the F₂ generations, especially the QTL on chromosome 27, which was reduced to 120 Kb. An ancestral haplotype association analysis showed that most of the dominant haplotypes are inherited from HQLA but with fluctuation of the effects between them. We highlight the important role of four candidate genes (PHOSPHO1, IGF2BP1, ZNF652, and GIP) in bone growth. We also retrieved a missing QTL from AIL on chromosome 4 by identifying the founder selection signatures, which are explained by the loss of association power that results from rare alleles. Our study provides a reasonable resource for detecting quantitative trait genes and tracking ancestor history and will facilitate our understanding of the genetic mechanisms underlying chicken bone growth.

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 analysis of egg production performance in chickens across the whole laying period

BACKGROUND

Egg production is the most economically-important trait in layers as it directly influences benefits of the poultry industry. To better understand the genetic architecture of egg production, we measured traits including age at first egg (AFE), weekly egg number (EN) from onset of laying eggs to 80 weeks which was divided into five stage (EN1: from onset of laying eggs to 23 weeks, EN2: from 23 to 37 weeks, EN3: from 37 to 50 weeks, EN4: from 50 to 61 weeks, EN5: from 61 to 80 weeks) based on egg production curve and total egg number across the whole laying period (Total-EN). Then we performed genome-wide association studies (GWAS) in 1078 Rhode Island Red hens using a linear mixed model.

RESULTS

Estimates of pedigree and SNP-based genetic parameter showed that AFE and EN1 exhibited high heritability (0.51 ± 0.09, 0.53 ± 0.08), while the h2 for EN in other stages varied from low (0.07 ± 0.04) to moderate (0.24 ± 0.07) magnitude. Subsequently, seven univariate GWAS for AFE and ENs were carried out independently, from which a total of 161 candidate SNPs located on GGA1, GGA2, GGA5, GGA6, GGA9 and GGA24 were identified. Thirteen SNP located on GGA6 were associated with AFE and an interesting gene PRLHR that may affect AFE through regulating oxytocin secretion in chickens. Sixteen genome-wide significant SNPs associated with EN3 were in a strong linkage disequilibrium (LD) region spanning from 117.87 Mb to 118.36 Mb on GGA1 and the most significant SNP (rs315777735) accounted for 3.57% of phenotypic variance. Genes POLA1, PDK3, PRDX4 and APOO identified by annotating sixteen genome-wide significant SNPs can be considered as candidates associated with EN3. Unfortunately, our study did not find any candidate gene for the total egg number.

CONCLUSIONS

Findings in our study could provide promising genes and SNP markers to improve egg production performance based on marker-assisted breeding selection, while further functional validation is still needed in other populations.

Investigating the genetic determination of clutch traits in laying hens

Clutch traits were proposed as a more detailed description of egg-laying patterns than simple total egg production. In this study, egg production of 23,809 Rhode Island Red (RIR) and 22,210 White Leghorn (WL) hens was described in terms of number of clutches, average and maximum clutch size, age at first egg, total saleable egg production, and percentage of egg defects. Genetic parameters were estimated using a six-trait animal model. Of the phenotyped birds, 1433 RIR hens and 1515 WL hens were genotyped with line specific 50K Affymetrix Axiom single nucleotide polymorphism chips to perform genome-wide association analyses. Moderate heritabilities were estimated for clutch traits of 0.20 to 0.42 in the RIR line and 0.29 to 0.41 in the WL line. Average and maximum clutch size was positively genetically correlated with total saleable egg number in both lines. Genome-wide association analysis identified seven regions that were associated with egg production in the RIR line and 12 regions in the WL line. The regions identified were line and trait specific, except for one region on chromosome 6 from 28 to 29 Mb that influenced number of clutches and maximum and average clutch size in WL hens. Regions associated with egg production identified here overlapped with 260 genes, with some strong positional candidates based on gene ontology including WASH1, which is involved in oocyte maturation, NPVF, involved in regulation of follicle-stimulating hormone secretion, and FOXO3, involved in oocyte maturation and ovulation from the ovarian follicle. Confirmation of the role of these genes in regulation of egg production pattern will require further studies.

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.

Genomic signatures of 60 years of bidirectional selection for 8-week body weight in chickens

Sixty years, constituting 60 generations, have passed since the founding of the Virginia body weight lines, an experimental population of White Plymouth Rock chickens. Using a stringent breeding scheme for divergent 8-week body weight, the lines, which originated from a common founder population, have responded to bidirectional selection with an approximate 15-fold difference in the selected trait. They provide a model system to study the genetics of complex traits in general and the influences of artificial selection on quantitative genetic architectures in particular. As we reflect on the 60th anniversary of the initiation of the Virginia body weight lines, there is opportunity to discuss the findings obtained using different analytical and experimental genetic and genomic strategies and integrate them with a recent pooled genome resequencing dataset. Hundreds of regions across the genome show differentiation between the 2 lines, reinforcing previous findings that response to selection relied on standing variation across many genes and giving insights into the haplotype complexity underlying regions associated with body weight.

Genome-Wide Association Analysis of Age-Dependent Egg Weights in Chickens

Egg weight (EW) is an economically-important trait and displays a consecutive increase with the hen's age. Because extremely large eggs cause a range of problems in the poultry industry, we performed a genome-wide association study (GWAS) in order to identify genomic variations that are associated with EW. We utilized the Affymetrix 600 K high density SNP array in a population of 1,078 hens at seven time points from day at first egg to 80 weeks age (EW80). Results reveal that a 90 Kb genomic region (169.42 Mb ~ 169.51 Mb) in GGA1 is significantly associated with EW36 and is also potentially associated with egg weight at 28, 56, and 66 week of age. The leading SNP could account for 3.66% of the phenotypic variation, while two promising genes (DLEU7 and MIR15A) can be mapped to this narrow significant region and may affect EW in a pleiotropic manner. In addition, one gene (CECR2 on GGA1) and two genes (MEIS1 and SPRED2 on GGA3), which involved in the processes of embryogenesis and organogenesis, were also considered to be candidates related to first egg weight (FEW) and EW56, respectively. Findings in our study could provide worthy theoretical basis to generate eggs of ideal size based on marker assisted breeding selection.

Genomic Region Containing Toll-Like Receptor Genes Has a Major Impact on Total IgM Antibodies Including KLH-Binding IgM Natural Antibodies in Chickens

Natural antibodies (NAb) are antigen binding antibodies present in individuals without a previous exposure to this antigen. Keyhole limpet hemocyanin (KLH)-binding NAb levels were previously associated with survival in chickens. This suggests that selective breeding for KLH-binding NAb may increase survival by means of improved general disease resistance. Genome-wide association studies (GWAS) were performed to identify genes underlying genetic variation in NAb levels. The studied population consisted of 1,628 adolescent layer chickens with observations for titers of KLH-binding NAb of the isotypes IgM, IgA, IgG, the total KLH-binding (IgT) NAb titers, total antibody concentrations of the isotypes IgM, IgA, IgG, and the total antibodies concentration in plasma. GWAS were performed using 57,636 single-nucleotide polymorphisms (SNP). One chromosomal region on chromosome 4 was associated with KLH-binding IgT NAb, and total IgM concentration, and especially with KLH-binding IgM NAb. The region of interest was fine mapped by imputing the region of the study population to whole genome sequence, and subsequently performing an association study using the imputed sequence variants. 16 candidate genes were identified, of which FAM114A1, Toll-like receptor 1 family member B (TLR1B), TLR1A, Krüppel-like factor 3 (KLF3) showed the strongest associations. SNP located in coding regions of the candidate genes were checked for predicted changes in protein functioning. One SNP (at 69,965,939 base pairs) received the maximum impact score from two independent prediction tools, which makes this SNP the most likely causal variant. This SNP is located in TLR1A, which suggests a fundamental role of TLR1A on regulation of IgM levels (i.e., KLH-binding IgM NAb, and total IgM concentration), or B cells biology, or both. This study contributes to increased understanding of (genetic) regulation of KLH-binding NAb levels, and total antibody concentrations.

Fine mapping of a distal chromosome 4 QTL affecting growth and muscle mass in a chicken advanced intercross line

In our previous research, QTL analysis in an F₂ cross between the inbred New Hampshire (NHI) and White Leghorn (WL77) lines revealed a growth QTL in the distal part of chromosome 4. To physically reduce the chromosomal interval and the number of potential candidate genes, we performed fine mapping using individuals of generations F₁₀ , F₁₁ and F₁₂ in an advanced intercross line that had been established from the initial F₂ mapping population. Using nine single nucleotide polymorphism (SNP) markers within the QTL region for an association analysis with several growth traits from hatch to 20 weeks and body composition traits at 20 weeks, we could reduce the confidence interval from 26.9 to 3.4 Mb. Within the fine mapped region, markers rs14490774, rs314961352 and rs318175270 were in full linkage disequilibrium (D' = 1.0) and showed the strongest effect on growth and muscle mass (LOD ≥ 4.00). This reduced region contains 30 genes, compared to 292 genes in the original region. Chicken 60 K and 600 K SNP chips combined with DNA sequencing of the parental lines were used to call mutations in the reduced region. In the narrowed-down region, 489 sequence variants were detected between NHI and WL77. The most deleterious variants are a missense variant in ADGRA3 (SIFT = 0.02) and a frameshift deletion in the functional unknown gene ENSGALG00000014401 in NHI chicken. In addition, five synonymous variants were discovered in genes PPARGC1A, ADGRA3, PACRGL, SLIT2 and FAM184B. In our study, the confidence interval and the number of potential genes could be reduced 8- and 10- fold respectively. Further research will focus on functional effects of mutant genes.

Genetic Mapping of Quantitative Trait Loci for Egg Production and Egg Quality Traits in Chickens: a Review

Chickens display a wide spectrum of phenotypic variations in quantitative traits such as egg-related traits. Quantitative trait locus (QTL) analysis is a statistical method used to understand the relationship between phenotypic (trait measurements) and genotypic data (molecular markers). We have performed QTL analyses for egg-related traits using an original resource population based on the Japanese Large Game (Oh-Shamo) and the White Leghorn breeds of chickens. In this article, we summarize the results of our extensive QTL analyses for 11 and 66 traits for egg production and egg quality, respectively. We reveal that at least 30 QTL regions on 17 different chromosomes affect phenotypic variation in egg-related traits. Each locus had an age-specific effect on traits, and a variety in effects was also apparent, such as additive, dominance, and epistatic-interaction effects. Although genome-wide association study (GWAS) is suitable for gene-level resolution mapping of GWAS loci with additive effects, QTL mapping studies enable us to comprehensively understand genetic control, such as chromosomal regions, genetic contribution to phenotypic variance, mode of inheritance, and age-specificity of both common and rare alleles. QTL analyses also describe the relationship between genotypes and phenotypes in experimental populations. Accumulation of QTL information, including GWAS loci, is also useful for studies of population genomics approached without phenotypic data in order to validate the identified genomic signatures of positive selection. The combination of QTL studies and next-generation sequencing techniques with uncharacterized genetic resources will enhance current understanding of the relationship between genotypes and phenotypes in livestock animals.

The association of very low-density lipoprotein receptor (VLDLR) haplotypes with egg production indicates VLDLR is a candidate gene for modulating egg production

The very low-density lipoprotein receptor (VLDLR) transports egg yolk precursors into oocytes. However, our knowledge of the distribution patterns of VLDLR variants among breeds and their relationship to egg production is still incomplete. In this study, eight single nucleotide polymorphisms (SNPs) that account for 87% of all VLDLR variants were genotyped in Nick Chick (NC, n=91), Lohmann Brown (LohB, n=50) and Lueyang (LY, n=381) chickens, the latter being an Chinese indigenous breed. Egg production by NC and LY chickens was recorded from 17 to 50 weeks. Only four similar haplotypes were found in NC and LohB, of which two accounted for 100% of all NC haplotypes and 92.5% of LohB haplotypes. In contrast, there was considerable haplotypic diversity in LY. Comparison of egg production in LY showed that hens with NC-like haplotypes had a significantly higher production (p < 0.05) than those without the haplotypes. However, VLDLR expression was not significantly different between the haplotypes. These findings indicate a divergence in the distribution of VLDLR haplotypes between selected and non-selected breeds and suggest that the near fixation of VLDLR variants in NC and LohB is compatible with signature of selection. These data also support VLDLR as a candidate gene for modulating egg production.

Whole genome sequencing of Gyeongbuk Araucana, a newly developed blue-egg laying chicken breed, reveals its origin and genetic characteristics

Chicken, Gallus gallus, is a valuable species both as a food source and as a model organism for scientific research. Here, we sequenced the genome of Gyeongbuk Araucana, a rare chicken breed with unique phenotypic characteristics including flight ability, large body size, and laying blue-shelled eggs, to identify its genomic features. We generated genomes of Gyeongbuk Araucana, Leghorn, and Korean Native Chicken at a total of 33.5, 35.82, and 33.23 coverage depth, respectively. Along with the genomes of 12 Chinese breeds, we identified genomic variants of 16.3 million SNVs and 2.3 million InDels in mapped regions. Additionally, through assembly of unmapped reads and selective sweep, we identified candidate genes that fall into heart, vasculature and muscle development and body growth categories, which provided insight into Gyeongbuk Araucana's phenotypic traits. Finally, genetic variation based on the transposable element insertion pattern was investigated to elucidate the features of transposable elements related to blue egg shell formation. This study presents results of the first genomic study on the Gyeongbuk Araucana breed; it has potential to serve as an invaluable resource for future research on the genomic characteristics of this chicken breed as well as others.

Genome-wide association study reveals novel variants for growth and egg traits in Dongxiang blue-shelled and White Leghorn chickens

This study was designed to investigate the genetic basis of growth and egg traits in Dongxiang blue-shelled chickens and White Leghorn chickens. In this study, we employed a reduced representation sequencing approach called genotyping by genome reducing and sequencing to detect genome-wide SNPs in 252 Dongxiang blue-shelled chickens and 252 White Leghorn chickens. The Dongxiang blue-shelled chicken breed has many specific traits and is characterized by blue-shelled eggs, black plumage, black skin, black bone and black organs. The White Leghorn chicken is an egg-type breed with high productivity. As multibreed genome-wide association studies (GWASs) can improve precision due to less linkage disequilibrium across breeds, a multibreed GWAS was performed with 156 575 SNPs to identify the associated variants underlying growth and egg traits within the two chicken breeds. The analysis revealed 32 SNPs exhibiting a significant genome-wide association with growth and egg traits. Some of the significant SNPs are located in genes that are known to impact growth and egg traits, but nearly half of the significant SNPs are located in genes with unclear functions in chickens. To our knowledge, this is the first multibreed genome-wide report for the genetics of growth and egg traits in the Dongxiang blue-shelled and White Leghorn chickens.

Mixture models detect large effect QTL better than GBLUP and result in more accurate and persistent predictions

BACKGROUND

Accurate evaluation of SNP effects is important for genome wide association studies and for genomic prediction. The genetic architecture of quantitative traits differs widely, with some traits exhibiting few if any quantitative trait loci (QTL) with large effects, while other traits have one or several easily detectable QTL with large effects.

METHODS

Body weight in broilers and egg weight in layers are two examples of traits that have QTL of large effect. A commonly used method for genome wide association studies is to fit a mixture model such as BayesB that assumes some known proportion of SNP effects are zero. In contrast, the most commonly used method for genomic prediction is known as GBLUP, which involves fitting an animal model to phenotypic data with the variance-covariance or genomic relationship matrix among the animals being determined by genome wide SNP genotypes. Genotypes at each SNP are typically weighted equally in determining the genomic relationship matrix for GBLUP. We used the equivalent marker effects model formulation of GBLUP for this study. We compare these two classes of models using egg weight data collected over 8 generations from 2,324 animals genotyped with a 42 K SNP panel.

RESULTS

Using data from the first 7 generations, both BayesB and GBLUP found the largest QTL in a similar well-recognized QTL region, but this QTL was estimated to account for 24 % of genetic variation with BayesB and less than 1 % with GBLUP. When predicting phenotypes in generation 8 BayesB accounted for 36 % of the phenotypic variation and GBLUP for 25 %. When using only data from any one generation, the same QTL was identified with BayesB in all but one generation but never with GBLUP. Predictions of phenotypes in generations 2 to 7 based on only 295 animals from generation 1 accounted for 10 % phenotypic variation with BayesB but only 6 % with GBLUP. Predicting phenotype using only the marker effects in the 1 Mb region that accounted for the largest effect on egg weight from generation 1 data alone accounted for almost 8 % variation using BayesB but had no predictive power with GBLUP.

CONCLUSIONS

In conclusion, In the presence of large effect QTL, BayesB did a better job of QTL detection and its genomic predictions were more accurate and persistent than those from GBLUP.

Identification of Promising Mutants Associated with Egg Production Traits Revealed by Genome-Wide Association Study

Egg number (EN), egg laying rate (LR) and age at first egg (AFE) are important production traits related to egg production in poultry industry. To better understand the knowledge of genetic architecture of dynamic EN during the whole laying cycle and provide the precise positions of associated variants for EN, LR and AFE, laying records from 21 to 72 weeks of age were collected individually for 1,534 F2 hens produced by reciprocal crosses between White Leghorn and Dongxiang Blue-shelled chicken, and their genotypes were assayed by chicken 600 K Affymetrix high density genotyping arrays. Subsequently, pedigree and SNP-based genetic parameters were estimated and a genome-wide association study (GWAS) was conducted on EN, LR and AFE. The heritability estimates were similar between pedigree and SNP-based estimates varying from 0.17 to 0.36. In the GWA analysis, we identified nine genome-wide significant loci associated with EN of the laying periods from 21 to 26 weeks, 27 to 36 weeks and 37 to 72 weeks. Analysis of GTF2A1 and CLSPN suggested that they influenced the function of ovary and uterus, and may be considered as relevant candidates. The identified SNP rs314448799 for accumulative EN from 21 to 40 weeks on chromosome 5 created phenotypic differences of 6.86 eggs between two homozygous genotypes, which could be potentially applied to the molecular breeding for EN selection. Moreover, our finding showed that LR was a moderate polygenic trait. The suggestive significant region on chromosome 16 for AFE suggested the relationship between sex maturity and immune in the current population. The present study comprehensively evaluates the role of genetic variants in the development of egg laying. The findings will be helpful to investigation of causative genes function and future marker-assisted selection and genomic selection in chickens.

Genome-wide association study dissects genetic architecture underlying longitudinal egg weights in chickens

Background

As a major economic trait in chickens, egg weight (EW) receives widespread interests in breeding, production and consumption. However, limited information is available for underlying genetic architecture of longitudinal trend in EW. Herein, we measured EWs at nine time points from onset of laying to 60 week of age, and conducted comprehensive genome-wide association studies (GWAS) in 1,534 F₂ hens derived from reciprocal crosses between White Leghorn and Dongxiang chickens.

Results

Egg weights at all ages except the first egg weight (FEW) exhibited high SNP-based heritability estimates (0.47 ~ 0.60). Strong pair-wise genetic correlations (0.77 ~ 1.00) were found among all EWs. Nine separate univariate genome-wide screens suggested 73 signals showing significant associations with longitudinal EWs. After multivariate and conditional analyses, four variants on three chromosomes remained independent contributions. The minor alleles at two loci exerted consistent and positive substitution effects on EWs, and other two were negative. The four loci together accounted for 3.84 % of the phenotypic variance for FEW and 7.29 ~ 11.06 % for EWs from 32 to 60 week of age. We obtained five candidate genes, of which NCAPG harbors a non-synonymous SNP (rs14491030) causing a valine-to-alanine amino-acid substitution. Genome partitioning analysis indicated a strong linear correlation between the variance explained by each chromosome and its length, which provided evidence that EW follows a highly polygenic nature of inheritance.

Conclusions

Identification of significant genetic causes that together implicate EWs at different ages will greatly advance our understanding of the genetic basis behind longitudinal EWs, and would be helpful to illuminate the future breeding direction on how to select desired egg size.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1945-y) contains supplementary material, which is available to authorized users.

Eggshell color in brown-egg laying hens - a review

The major pigment in eggshells of brown-egg laying hens is protoporphyrin IX, but traces of biliverdin and its zinc chelates are also present. The pigment appears to be synthesized in the shell gland. The protoporphyrin IX synthetic pathway is well defined, but precisely where and how it is synthesized in the shell gland of the brown-egg laying hen is still ambiguous. The pigment is deposited onto all shell layers including the shell membranes, but most of it is concentrated in the outermost layer of the calcareous shell and in the cuticle. Recently, the genes that are involved in pigment synthesis have been identified, but the genetic control of synthesis and deposition of brown pigment in the commercial laying hen is not fully understood. The brown coloration of the shell is an important shell quality parameter and has a positive influence on consumer preference. The extent of pigment deposition is influenced by the housing system, hen age, hen strain, diet, stressors, and certain diseases such as infectious bronchitis. In this article, the physiological and biochemical characteristics of the brown pigment in commercial brown-egg layers are reviewed in relation to its various functions in the poultry industry.

Promising Loci and Genes for Yolk and Ovary Weight in Chickens Revealed by a Genome-Wide Association Study

Because it serves as the cytoplasm of the oocyte and provides a large amount of reserves, the egg yolk has biological significance for developing embryos. The ovary and its hierarchy of follicles are the main reproductive organs responsible for yolk deposition in chickens. However, the genetic architecture underlying the yolk and ovarian follicle weights remains elusive. Here, we measured the yolk weight (YW) at 11 age points from onset of egg laying to 72 weeks of age and measured the follicle weight (FW) and ovary weight (OW) at 73 weeks as part of a comprehensive genome-wide association study (GWAS) in 1,534 F₂ hens derived from reciprocal crosses between White Leghorn (WL) and Dongxiang chickens (DX). For all ages, YWs exhibited moderate single nucleotide polymorphism (SNP)-based heritability estimates (0.25–0.38), while the estimates for FW (0.16) and OW (0.20) were relatively low. Independent univariate genome-wide screens for each trait identified 12, 3, and 31 novel significant associations with YW, FW, and OW, respectively. A list of candidate genes such as ZAR1, STARD13, ACER1b, ACSBG2, and DHRS12 were identified for having a plausible function in yolk and follicle development. These genes are important to the initiation of embryogenesis, lipid transport, lipoprotein synthesis, lipid droplet promotion, and steroid hormone metabolism, respectively. Our study provides for the first time a genome-wide association (GWA) analysis for follicle and ovary weight. Identification of the promising loci as well as potential candidate genes will greatly advance our understanding of the genetic basis underlying dynamic yolk weight and ovarian follicle development and has practical significance in breeding programs for the alteration of yolk weight at different age points.

Genome-wide association study revealed a promising region and candidate genes for eggshell quality in an F2 resource population

Background

Eggshell is subject to quality loss with aging process of laying hens, and damaged eggshells result in economic losses of eggs. However, the genetic architecture underlying the dynamic eggshell quality remains elusive. Here, we measured eggshell quality traits, including eggshell weight (ESW), eggshell thickness (EST) and eggshell strength (ESS) at 11 time points from onset of laying to 72 weeks of age and conducted comprehensive genome-wide association studies (GWAS) in 1534 F₂ hens derived from reciprocal crosses between White Leghorn (WL) and Dongxiang chickens (DX).

Results

ESWs at all ages exhibited moderate SNP-based heritability estimates (0.30 ~ 0.46), while the estimates for EST (0.21 ~ 0.31) and ESS (0.20 ~ 0.27) were relatively low. Eleven independent univariate genome-wide screens for each trait totally identified 1059, 1026 and 1356 significant associations with ESW, EST and ESS, respectively. Most significant loci were in a region spanning from 57.3 to 71.4 Mb of chromosome 1 (GGA1), which together account for 8.4 ~ 16.5 % of the phenotypic variance for ESW from 32 to 72 weeks of age, 4.1 ~ 6.9 % and 2.95 ~ 16.1 % for EST and ESS from 40 to 72 weeks of age. According to linkage disequilibrium (LD) and conditional analysis, the significant SNPs in this region were in extremely strong linkage disequilibrium status. Ultimately, two missense SNPs in GGA1 and one in GGA4 were considered as promising loci on three independent genes including ITPR2, PIK3C2G, and NCAPG. The homozygotes of advantageously effective alleles on PIK3C2G and ITPR2 possessed the best eggshell quality and could partly counteract the negative effect of aging process. NCAPG had certain effect on eggshell quality for young hens.

Conclusions

Identification of the promising region as well as potential candidate genes will greatly advance our understanding of the genetic basis underlying dynamic eggshell quality and has the practical significance in breeding program for the improvement of eggshell quality, especially at the later part of laying cycle.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1795-7) contains supplementary material, which is available to authorized users.

Integrating transcriptome and genome re-sequencing data to identify key genes and mutations affecting chicken eggshell qualities

Eggshell damages lead to economic losses in the egg production industry and are a threat to human health. We examined 49-wk-old Rhode Island White hens (Gallus gallus) that laid eggs having shells with significantly different strengths and thicknesses. We used HiSeq 2000 (Illumina) sequencing to characterize the chicken transcriptome and whole genome to identify the key genes and genetic mutations associated with eggshell calcification. We identified a total of 14,234 genes expressed in the chicken uterus, representing 89% of all annotated chicken genes. A total of 889 differentially expressed genes were identified by comparing low eggshell strength (LES) and normal eggshell strength (NES) genomes. The DEGs are enriched in calcification-related processes, including calcium ion transport and calcium signaling pathways as reveled by gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis. Some important matrix proteins, such as OC-116, LTF and SPP1, were also expressed differentially between two groups. A total of 3,671,919 single-nucleotide polymorphisms (SNPs) and 508,035 Indels were detected in protein coding genes by whole-genome re-sequencing, including 1775 non-synonymous variations and 19 frame-shift Indels in DEGs. SNPs and Indels found in this study could be further investigated for eggshell traits. This is the first report to integrate the transcriptome and genome re-sequencing to target the genetic variations which decreased the eggshell qualities. These findings further advance our understanding of eggshell calcification in the chicken uterus.

Functional classification of 15 million SNPs detected from diverse chicken populations

Next-generation sequencing has prompted a surge of discovery of millions of genetic variants from vertebrate genomes. Besides applications in genetic association and linkage studies, a fraction of these variants will have functional consequences. This study describes detection and characterization of 15 million SNPs from chicken genome with the goal to predict variants with potential functional implications (pfVars) from both coding and non-coding regions. The study reports: 183K amino acid-altering SNPs of which 48% predicted as evolutionary intolerant, 13K splicing variants, 51K likely to alter RNA secondary structures, 500K within most conserved elements and 3K from non-coding RNAs. Regions of local fixation within commercial broiler and layer lines were investigated as potential selective sweeps using genome-wide SNP data. Relationships with phenotypes, if any, of the pfVars were explored by overlaying the sweep regions with known QTLs. Based on this, the candidate genes and/or causal mutations for a number of important traits are discussed. Although the fixed variants within sweep regions were enriched with non-coding SNPs, some non-synonymous-intolerant mutations reached fixation, suggesting their possible adaptive advantage. The results presented in this study are expected to have important implications for future genomic research to identify candidate causal mutations and in poultry breeding.

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.

Polymorphism of avian leukosis virus subgroup E loci showing selective footprints in chicken

Avian leukosis virus subgroup E (ALVE) is a family of endogenous retroviruses in the chicken genome. To investigate the genetic consequences of chicken domestication, we analyzed 18 ALVE loci in red jungle fowls, layers, broilers, and Chinese indigenous chickens. None of the ALVE loci tested were found in red jungle fowls, but 12 were present in domestic chickens. ALVE1 and ALVE16 are found in regions of the genome that harbor quantitative trait loci (QTL) affecting egg production traits. ALVE1 was fixed and ALVE16 was detected only in layers. By contrast, ALVE-b1, ALVE-b5, ALVE-b6, and ALVE-b8 integrated into regions of the genome that harbor QTL affecting meat production traits. Carrier frequencies of these four ALVE loci were high in broilers and low in Chinese local chickens; the loci were not found in the layers. This study demonstrated that insertionally polymorphic ALVE loci can illustrate the selective footprints in the chicken genome.

Genome-wide association study for egg production and quality in layer chickens

Discovery of genes with large effects on economically important traits has for many years been of interest to breeders. The development of SNP panels which cover the whole genome with high density and, more importantly, that can be genotyped on large numbers of individuals at relatively low cost, has opened new opportunities for genome-wide association studies (GWAS). The objective of this study was to find genomic regions associated with egg production and quality traits in layers using analysis methods developed for the purpose of whole genome prediction. Genotypes on over 4500 birds and phenotypes on over 13,000 hens from eight generations of a brown egg layer line were used. Birds were genotyped with a custom 42K Illumina SNP chip. Recorded traits included two egg production and 11 egg quality traits (puncture score, albumen height, yolk weight and shell colour) at early and late stages of production, as well as body weight and age at first egg. Egg weight was previously analysed by Wolc et al. (2012). The Bayesian whole genome prediction model--BayesB (Meuwissen et al. 2001) was used to locate 1 Mb regions that were most strongly associated with each trait. The posterior probability of a 1 Mb window contributing to genetic variation was used as the criterion for suggesting the presence of a quantitative trait locus (QTL) in that window. Depending upon the trait, from 1 to 7 significant (posterior probability >0.9) 1 Mb regions were found. The largest QTL, a region explaining 32% of genetic variance, was found on chr4 at 78 Mb for body weight but had pleiotropic effects on other traits. For the other traits, the largest effects were much smaller, explaining <7% of genetic variance, with regions on chromosomes 2, 12 and 17 explaining above 5% of genetic variance for albumen height, shell colour and egg production, respectively. In total, 45 of 1043 1 Mb windows were estimated to have a non-zero effect with posterior probability > 0.9 for one or more traits.

QTL mapping of egg albumen quality in egg layers

Background

A fresh, good quality egg has a firm and gelatinous albumen that anchors the yolk and restricts growth of microbiological pathogens. As the egg ages, the gel-like structure collapses, resulting in thin and runny albumen. Occasionally thin albumen is found in a fresh egg, giving the impression of a low quality product. A mapping population consisting of 1599 F₂ hens from a cross between White Rock and Rhode Island Red lines was set up, to identify loci controlling albumen quality. The phenotype for albumen quality was evaluated by albumen height and in Haugh units (HU) measured on three consecutive eggs from each F₂ hen at the age of 40 weeks. For the fine-mapping analysis, albumen height and HU were used simultaneously to eliminate contribution of the egg size to the phenotype.

Results

Linkage analysis in a small population of seven half-sib families (668 F₂) with 162 microsatellite markers spread across 27 chromosomes revealed two genome-wide significant regions with additive effects for HU on chromosomes 7 and Z. In addition, two putative genome-wide quantitative trait loci (QTL) regions were identified on chromosomes 4 and 26. The QTL effects ranged from 2 to 4% of the phenotypic variance. The genome-wide significant QTL regions on chromosomes 7 and Z were selected for fine-mapping in the full set composed of 16 half-sib families. In addition, their existence was confirmed by an association analysis in an independent commercial Hy-Line pure line.

Conclusions

We identified four chicken genomic regions that affect albumen quality. Our results also suggest that genes that affect albumen quality act both directly and indirectly through several different mechanisms. For instance, the QTL regions on both fine-mapped chromosomes 7 and Z overlapped with a previously reported QTL for eggshell quality, indicating that eggshell membranes may play a role in albumen quality.

The Human Obesity Gene Map: The 2004 Update

This paper presents the eleventh update of the human obesity gene map, which incorporates published results up to the end of October 2004. Evidence from single-gene mutation obesity cases, Mendelian disorders exhibiting obesity as a clinical feature, transgenic and knockout murine models relevant to obesity, quantitative trait loci (QTLs) from animal cross-breeding experiments, association studies with candidate genes, and linkages from genome scans is reviewed. As of October 2004, 173 human obesity cases due to single-gene mutations in 10 different genes have been reported, and 49 loci related to Mendelian syndromes relevant to human obesity have been mapped to a genomic region, and causal genes or strong candidates have been identified for most of these syndromes. There are 166 genes which, when mutated or expressed as transgenes in the mouse, result in phenotypes that affect body weight and adiposity. The number of QTLs reported from animal models currently reaches 221. The number of human obesity QTLs derived from genome scans continues to grow, and we have now 204 QTLs for obesity-related phenotypes from 50 genome-wide scans. A total of 38 genomic regions harbor QTLs replicated among two to four studies. The number of studies reporting associations between DNA sequence variation in specific genes and obesity phenotypes has also increased considerably with 358 findings of positive associations with 113 candidate genes. Among them, 18 genes are supported by at least five positive studies. The obesity gene map shows putative loci on all chromosomes except Y. Overall, >600 genes, markers, and chromosomal regions have been associated or linked with human obesity phenotypes. The electronic version of the map with links to useful publications and genomic and other relevant sites can be found at http://obesitygene.pbrc.edu.

Whole-genome scan for signatures of recent selection reveals loci associated with important traits in White Leghorn chickens

Chicken is considered to be an excellent model for genetic studies of phenotypic and genomic evolution, with large effective population size, specialized commercial lines, and strong human-driven selection. High-density chicken SNP chips can help to achieve a better understanding of the selection mechanisms in artificially selected populations. We performed the genome-wide tests for the selection signature in 385 White Leghorn hens and mapped positively selected regions to the genome annotations. Ten QTL related to egg production, egg quality, growth, and disease resistance traits were selected for extended haplotype homozygosity tests to give a brief overview of recent selection signatures in chicken QTL. We also reported 185 candidate genes/CDSs showing top P-values and slower decay of haplotype homozygosities. Some of these genes seemed to have significant effects on important economical traits, and most of them have not been reported in chickens. The current study provides a genome-wide map of linkage disequilibrium extents and distributions and selection footprints in the chicken genome. A panel of genes, including PRL, NCKX1, NRF1, LHX2, and SFRP1 associated with egg production, metabolism traits, and response to illumination were identified. In addition, there were more genes identified that have not yet been reported in chickens, and our results provide new clues for further study.

W chromosome expression responds to female-specific selection

The W chromosome is predicted to be subject to strong female-specific selection stemming from its female-limited inheritance and therefore should play an important role in female fitness traits. However, the overall importance of directional selection in shaping the W chromosome is unknown because of the powerful degradative forces that act to decay the nonrecombining sections of the genome. Here we greatly expand the number of known W-linked genes and assess the expression of the W chromosome after >100 generations of different female-specific selection regimens in different breeds of chicken and in the wild ancestor, the Red Jungle Fowl. Our results indicate that female-specific selection has a significant effect on W chromosome gene-expression patterns, with a strong convergent pattern of up-regulation associated with increased female-specific selection. Many of the transcriptional changes in the female-selected breeds are the product of positive selection, suggesting that selection is an important force in shaping the evolution of gene expression on the W chromosome, a finding consistent with both the importance of the W chromosome in female fertility and the haploid nature of the W. Taken together, these data provide evidence for the importance of the sex-limited chromosome in a female heterogametic species and show that sex-specific selection can act to preserve sex-limited chromosomes from degrading forces.

The GTPase activating Rap/RanGAP domain-like 1 gene is associated with chicken reproductive traits

Background

Abundant evidence indicates that chicken reproduction is strictly regulated by the hypothalamic-pituitary-gonad (HPG) axis, and the genes included in the HPG axis have been studied extensively. However, the question remains as to whether any other genes outside of the HPG system are involved in regulating chicken reproduction. The present study was aimed to identify, on a genome-wide level, novel genes associated with chicken reproductive traits.

Methodology/Principal Finding

Suppressive subtractive hybridization (SSH), genome-wide association study (GWAS), and gene-centric GWAS were used to identify novel genes underlying chicken reproduction. Single marker-trait association analysis with a large population and allelic frequency spectrum analysis were used to confirm the effects of candidate genes. Using two full-sib Ningdu Sanhuang (NDH) chickens, GARNL1 was identified as a candidate gene involved in chicken broodiness by SSH analysis. Its expression levels in the hypothalamus and pituitary were significantly higher in brooding chickens than in non-brooding chickens. GWAS analysis with a NDH two tail sample showed that 2802 SNPs were significantly associated with egg number at 300 d of age (EN300). Among the 2802 SNPs, 2 SNPs composed a block overlapping the GARNL1 gene. The gene-centric GWAS analysis with another two tail sample of NDH showed that GARNL1 was strongly associated with EN300 and age at first egg (AFE). Single marker-trait association analysis in 1301 female NDH chickens confirmed that variation in this gene was related to EN300 and AFE. The allelic frequency spectrum of the SNP rs15700989 among 5 different populations supported the above associations. Western blotting, RT-PCR, and qPCR were used to analyze alternative splicing of the GARNL1 gene. RT-PCR detected 5 transcripts and revealed that the transcript, which has a 141 bp insertion, was expressed in a tissue-specific manner.

Conclusions/Significance

Our findings demonstrate that the GARNL1 gene contributes to chicken reproductive traits.

A genome-wide SNP scan reveals novel loci for egg production and quality traits in white leghorn and brown-egg dwarf layers

Availability of the complete genome sequence as well as high-density SNP genotyping platforms allows genome-wide association studies (GWAS) in chickens. A high-density SNP array containing 57,636 markers was employed herein to identify associated variants underlying egg production and quality traits within two lines of chickens, i.e., White Leghorn and brown-egg dwarf layers. For each individual, age at first egg (AFE), first egg weight (FEW), and number of eggs (EN) from 21 to 56 weeks of age were recorded, and egg quality traits including egg weight (EW), eggshell weight (ESW), yolk weight (YW), eggshell thickness (EST), eggshell strength (ESS), albumen height(AH) and Haugh unit(HU) were measured at 40 and 60 weeks of age. A total of 385 White Leghorn females and 361 brown-egg dwarf dams were selected to be genotyped. The genome-wide scan revealed 8 SNPs showing genome-wise significant (P<1.51E-06, Bonferroni correction) association with egg production and quality traits under the Fisher's combined probability method. Some significant SNPs are located in known genes including GRB14 and GALNT1 that can impact development and function of ovary, but more are located in genes with unclear functions in layers, and need to be studied further. Many chromosome-wise significant SNPs were also detected in this study and some of them are located in previously reported QTL regions. Most of loci detected in this study are novel and the follow-up replication studies may be needed to further confirm the functional significance for these newly identified SNPs.

Polymorphisms associated with egg number at 300 days of age in chickens

We looked for variations that could be associated with chicken egg number at 300 days of age (EN300) in seven genes of the hypothalamic-pituitary-gonadal axis, including gonadotrophin-releasing hormone-I (GnRH-I), GnRH receptor (GnRHR), neuropeptide Y (NPY), dopamine D2 receptor (DRD2), vasoactive intestinal polypeptide (VIP), VIP receptor-1 (VIPR-1), prolactin (PRL), and the QTL region between 87 and 105 cM of the Z chromosome. Ten mutations in the seven genes were chosen to do marker-trait association analyses in a population comprising 1310 chickens, which were obtained from a company located in Guangdong Province of China. The C1704887T of VIPR-1 was found to have a highly significant association with EN300. The T5841629C of DRD2 and the C1715301T of VIPR-1 were significantly associated with EN300. A highly significant association was also found between the C1704887T-C1715301T haplotypes of VIPR-1 and EN300. H1H3 had the highest EN300. Four PCR-RFLP variations in the candidate QTL region were selected to investigate their genetic effects on EN300. The haplotypes of T32742468C-G32742603A in this region showed a highly significant association with EN300. Bioinformatics analyses showed that both T32742468C and G32742603A were located in intron 1 of the SH3-domain GRB2-like 2 (SH3GL2) gene. We conclude that five SNPs, including C1704887T and C1715301T of VIPR-1, T5841629C of DRD2, and T32742468C and G32742603A of SH3GL2, would be useful as markers for breeding to increase chicken EN300.

Quantitative trait loci segregating in crosses between New Hampshire and White Leghorn chicken lines: I. egg production traits

A genome scan was performed to detect chromosomal regions that affect egg production traits in reciprocal crosses between two genetically and phenotypically extreme chicken lines: the partially inbred line New Hampshire (NHI) and the inbred line White Leghorn (WL77). The NHI line had been selected for high growth and WL77 for low egg weight before inbreeding. The result showed a highly significant region on chromosome 4 with multiple QTL for egg production traits between 19.2 and 82.1 Mb. This QTL region explained 4.3 and 16.1% of the phenotypic variance for number of eggs and egg weight in the F(2) population, respectively. The egg weight QTL effects are dependent on the direction of the cross. In addition, genome-wide suggestive QTL for egg weight were found on chromosomes 1, 5, and 9, and for number of eggs on chromosomes 5 and 7. A genome-wide significant QTL affecting age at first egg was mapped on chromosome 1. The difference between the parental lines and the highly significant QTL effects on chromosome 4 will further support fine mapping and candidate gene identification for egg production traits in chicken.