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Li W, Jing Z, Cheng Y, Wang X, Li D, Han R, Li W, Li G, Sun G, Tian Y, Liu X, Kang X, Li Z. 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. J Anim Sci 2020; 98:5822640. [PMID: 32309860 DOI: 10.1093/jas/skaa122] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Accepted: 04/16/2020] [Indexed: 12/18/2022] Open
Abstract
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.
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Affiliation(s)
- Wenya Li
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Zhenzhu Jing
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Yingying Cheng
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China
| | - Xiangnan Wang
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Donghua Li
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Ruili Han
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Wenting Li
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Guoxi Li
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Guirong Sun
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Yadong Tian
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Xiaojun Liu
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Xiangtao Kang
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
| | - Zhuanjian Li
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan, China.,Henan Innovative Engineering Research Center of Poultry Germplasm Resource, Zhengzhou
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Developments in understanding and assessment of egg and egg product quality over the last century. WORLD POULTRY SCI J 2019. [DOI: 10.1017/s0043933913000408] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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3
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Wan Y, Wang Z, Wang J, Su H, Guo X, Wu J, Li Q, Ni G, Jiang R. Genetic parameters of the thick-to-thin albumen ratio and egg compositional traits in layer-type chickens. Br Poult Sci 2019; 60:517-521. [PMID: 31185729 DOI: 10.1080/00071668.2019.1631446] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
1. Generating a robust egg albumen is one of the major factors contributing to interior egg quality owing to its nutritive value and superior appearance. However, the genetic factors regulating the proportion of thick albumen are poorly understood. 2. In this study, 1330 eggs were collected from 450 Rhode Island White layers, aged 40 weeks, to measure egg compositional traits for three successive days. The restricted maximum likelihood method was applied to estimate genetic parameters for the thick-to-thin albumen ratio and other egg compositional traits. A univariate animal model was fitted to calculate heritability for each trait. 3. The heritabilities of egg weight, yolk weight, albumen height, Haugh units, percentages of yolk, thick albumen, thin albumen and the thick-to-thin albumen ratio were 0.32, 0.34, 0.28, 0.47, 0.61, 0.39, 0.31, and 0.45, respectively. The percentage of thick albumen was negatively correlated genetically with all traits, and percentage of thin albumen was negatively correlated genetically with all traits except for Haugh units. The thick-to-thin albumen ratio was positively correlated genetically with egg weight, albumen height and Haugh units, with correlations ranging from 0.21 to 0.54. 4. The results indicated that the percentage of thick albumen and the thick-to-thin albumen ratio were found to be moderately to highly heritable, and selection for the thick-to-thin albumen ratio could be conducive to the improvement of egg albumen quality.
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Affiliation(s)
- Y Wan
- College of Animal Science and Technology, Anhui Agricultural University , Hefei , China.,Anhui Key Laboratory of Livestock and Poultry Product Safety Engineering, Institute of Animal Husbandry and Veterinary Medicine, Anhui Academy of Agriculture Science , Hefei , China
| | - Z Wang
- College of Animal Science and Technology, Anhui Agricultural University , Hefei , China
| | - J Wang
- College of Animal Science and Technology, Anhui Agricultural University , Hefei , China
| | - H Su
- College of Animal Science and Technology, Anhui Agricultural University , Hefei , China
| | - X Guo
- College of Animal Science and Technology, Anhui Agricultural University , Hefei , China
| | - J Wu
- Anhui Rongda Poultry Development Co., Ltd ., Xuancheng , China
| | - Q Li
- Anhui Rongda Poultry Development Co., Ltd ., Xuancheng , China
| | - G Ni
- Anhui Rongda Poultry Development Co., Ltd ., Xuancheng , China
| | - R Jiang
- College of Animal Science and Technology, Anhui Agricultural University , Hefei , China
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4
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Qu L, Shen M, Guo J, Wang X, Dou T, Hu Y, Li Y, Ma M, Wang K, Liu H. Identification of potential genomic regions and candidate genes for egg albumen quality by a genome-wide association study. Arch Anim Breed 2019; 62:113-123. [PMID: 31807621 PMCID: PMC6853030 DOI: 10.5194/aab-62-113-2019] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Accepted: 03/05/2019] [Indexed: 11/17/2022] Open
Abstract
Albumen
quality is a leading economic trait in the chicken industry. Major studies have paid
attention to genetic architecture underlying albumen quality. However, the putative
quantitative trait locus (QTL) for this trait is still unclear. In this genome-wide
association study, we used an F2 resource population to study longitudinal albumen
quality. Seven single-nucleotide polymorphism (SNP) loci were found to be significantly
(p<8.43×10-7) related to albumen quality by univariate analysis,
while 11 SNPs were significantly (p<8.43×10-7) associated with
albumen quality by multivariate analysis. A QTL on GGA4 had a pervasive function on
albumen quality, including a SNP at the missense of NCAPG, and a SNP at the
intergenic region of FGFPB1. It was further found that the putative QTLs at
GGA1, GGA2, and GGA7 had the strongest effects on albumen height (AH) at 32 weeks, Haugh
units (HU) at 44 weeks, and AH at 55 weeks. Moreover, novel SNPs on GGA5 and GGA3 were
associated with AH and HU at 32, 44, and 48 weeks of age. These results confirmed the
regions for egg weight that were detected in a previous study and were similar with QTL
for albumen quality. These results showed that GGA4 had the strongest effect on albumen
quality. Only a few significant loci were detected for most characteristics probably
reflecting the attributes of a pleiotropic gene and a minor-polygene in quantitative
traits.
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Affiliation(s)
- Liang Qu
- College of Animal Science & Technology, Nanjing Agricultural University, Nanjing, China.,Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Manman Shen
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China.,College of Animal Science & Technology, Yangzhou University, Yangzhou, China
| | - Jun Guo
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Xingguo Wang
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Taocun Dou
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Yuping Hu
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Yongfeng Li
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Meng Ma
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Kehua Wang
- Jiangsu Institute of Poultry Science, Chinese Academy of Agricultural Science, Yangzhou, China
| | - Honglin Liu
- College of Animal Science & Technology, Nanjing Agricultural University, Nanjing, China
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RNA-Seq reveals seven promising candidate genes affecting the proportion of thick egg albumen in layer-type chickens. Sci Rep 2017; 7:18083. [PMID: 29273734 PMCID: PMC5741707 DOI: 10.1038/s41598-017-18389-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2017] [Accepted: 12/11/2017] [Indexed: 01/07/2023] Open
Abstract
Eggs with a much higher proportion of thick albumen are preferred in the layer industry, as they are favoured by consumers. However, the genetic factors affecting the thick egg albumen trait have not been elucidated. Using RNA sequencing, we explored the magnum transcriptome in 9 Rhode Island white layers: four layers with phenotypes of extremely high ratios of thick to thin albumen (high thick albumen, HTA) and five with extremely low ratios (low thick albumen, LTA). A total of 220 genes were differentially expressed, among which 150 genes were up-regulated and 70 were down-regulated in the HTA group compared with the LTA group. Gene Ontology (GO) analysis revealed that the up-regulated genes in HTA were mainly involved in a wide range of regulatory functions. In addition, a large number of these genes were related to glycosphingolipid biosynthesis, focal adhesion, ECM-receptor interactions and cytokine-cytokine receptor interactions. Based on functional analysis, ST3GAL4, FUT4, ITGA2, SDC3, PRLR, CDH4 and GALNT9 were identified as promising candidate genes for thick albumen synthesis and metabolism during egg formation. These results provide new insights into the molecular mechanisms of egg albumen traits and may contribute to future breeding strategies that optimise the proportion of thick egg albumen.
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6
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Goto T, Tsudzuki M. Genetic Mapping of Quantitative Trait Loci for Egg Production and Egg Quality Traits in Chickens: a Review. J Poult Sci 2017; 54:1-12. [PMID: 32908402 PMCID: PMC7477176 DOI: 10.2141/jpsa.0160121] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2016] [Accepted: 10/24/2016] [Indexed: 12/11/2022] Open
Abstract
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.
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Affiliation(s)
- Tatsuhiko Goto
- Genetics, Ecology and Evolution, School of Life Sciences, University of Nottingham, University Park, Nottingham NG7 2RD, UK
- Japanese Avian Bioresource Project Research Center, Hiroshima University, Higashi-Hiroshima, Hiroshima 739-8528, Japan
- Present address: Department of Life Science and Agriculture, Obihiro University of Agriculture and Veterinary Medicine, Inada-cho, Obihiro, Hokkaido 080-8555, Japan
| | - Masaoki Tsudzuki
- Japanese Avian Bioresource Project Research Center, Hiroshima University, Higashi-Hiroshima, Hiroshima 739-8528, Japan
- Graduate School of Biosphere Science, Hiroshima University, Higashi-Hiroshima, Hiroshima 739-8528, Japan
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7
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Wolc A, Arango J, Jankowski T, Dunn I, Settar P, Fulton JE, O'Sullivan NP, Preisinger R, Fernando RL, Garrick DJ, Dekkers JCM. Genome-wide association study for egg production and quality in layer chickens. J Anim Breed Genet 2014; 131:173-82. [PMID: 24628796 DOI: 10.1111/jbg.12086] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2013] [Accepted: 02/14/2014] [Indexed: 12/21/2022]
Abstract
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.
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Affiliation(s)
- A Wolc
- Department of Animal Science, Iowa State University, Ames, IA, USA; Hy-Line International, Dallas Center, IA, USA
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8
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Mapping of Main-Effect and Epistatic Quantitative Trait Loci for Internal Egg Traits in an F 2 Resource Population of Chickens. J Poult Sci 2014. [DOI: 10.2141/jpsa.0140030] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
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9
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Honkatukia M, Tuiskula-Haavisto M, Arango J, Tabell J, Schmutz M, Preisinger R, Vilkki J. QTL mapping of egg albumen quality in egg layers. Genet Sel Evol 2013; 45:31. [PMID: 23953064 PMCID: PMC3847062 DOI: 10.1186/1297-9686-45-31] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2012] [Accepted: 07/13/2013] [Indexed: 12/01/2022] Open
Abstract
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.
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10
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Wolc A, Arango J, Settar P, Fulton JE, O’Sullivan NP, Preisinger R, Habier D, Fernando R, Garrick DJ, Hill WG, Dekkers JCM. Genome-wide association analysis and genetic architecture of egg weight and egg uniformity in layer chickens. Anim Genet 2012; 43 Suppl 1:87-96. [DOI: 10.1111/j.1365-2052.2012.02381.x] [Citation(s) in RCA: 81] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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Goraga ZS, Nassar MK, Brockmann GA. Quantitative trait loci segregating in crosses between New Hampshire and White Leghorn chicken lines: I. egg production traits. Anim Genet 2011; 43:183-9. [PMID: 22404354 DOI: 10.1111/j.1365-2052.2011.02233.x] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
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.
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Affiliation(s)
- Z S Goraga
- Department for Crop and Animal Sciences, Humboldt Universität zu Berlin, Invalidenstraße 42, Berlin, Germany
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12
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Goto T, Ishikawa A, Onitsuka S, Goto N, Fujikawa Y, Umino T, Nishibori M, Tsudzuki M. Mapping quantitative trait loci for egg production traits in an F2 intercross of Oh-Shamo and White Leghorn chickens. Anim Genet 2011; 42:634-41. [PMID: 22035005 DOI: 10.1111/j.1365-2052.2011.02190.x] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We performed quantitative trait locus (QTL) analyses for egg production traits, including age at first egg (AFE) and egg production rates (EPR) measured every 4 weeks from 22 to 62 weeks of hen age, in a population of 421 F(2) hens derived from an intercross between the Oh-Shamo (Japanese Large Game) and White Leghorn breeds of chickens. Simple interval mapping revealed a main-effect QTL for AFE on chromosome 1 and four main-effect QTL for EPR on chromosomes 1 and 11 (three on chromosome 1 and one on chromosome 11) at the genome-wide 5% levels. Among the three EPR QTL on chromosome 1, two were identified at the early stage of egg laying (26-34 weeks of hen age) and the remaining one was discovered at the late stage (54-58 weeks). The alleles at the two EPR QTL derived from the Oh-Shamo breed unexpectedly increased the trait values, irrespective of the Oh-Shamo being inferior to the White Leghorn in the trait. This suggests that the Oh-Shamo, one of the indigenous Japanese breeds, is an untapped resource that is important for further improvement of current elite commercial laying chickens. In addition, six epistatic QTL were identified on chromosomes 2, 4, 7, 8, 17 and 19, where none of the above main-effect QTL were located. This is the first example of detection of epistatic QTL affecting egg production traits. The main and epistatic QTL identified accounted for 4-8% of the phenotypic variance. The total contribution of all QTL detected for each trait to the phenotypic and genetic variances ranged from 4.1% to 16.9% and from 11.5% to 58.5%, respectively.
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Affiliation(s)
- T Goto
- Graduate School of Biosphere Science, Hiroshima University, Higashi-Hiroshima, Hiroshima, Japan
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13
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Omana DA, Liang Y, Kav NNV, Wu J. Proteomic analysis of egg white proteins during storage. Proteomics 2010; 11:144-53. [PMID: 21182201 DOI: 10.1002/pmic.201000168] [Citation(s) in RCA: 63] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2010] [Revised: 10/02/2010] [Accepted: 10/09/2010] [Indexed: 11/11/2022]
Abstract
Egg storage causes egg white to lose its viscous nature to form a thin liquid, commonly referred to as egg white thinning. To understand the mechanisms underlying egg white thinning, white-shell eggs were used in the present study to determine the proteome-level changes of egg white proteins occurred during storage. Egg white thinning was observed visually after 20 days of storage at ambient temperature (22 ± 2 °C) when the maximum number of proteome-level changes occurred. The proteins that showed significant changes in abundance during storage included ovalbumin, clusterin, ovoinhibitor, ovotransferrin, and prostaglandin D2 synthase. Among these, only the abundance of clusterin was observed to change continuously during the storage period. Hence, it is expected that the increase in the concentrations of clusterin and ovoinhibitor along with the change of ovalbumin content during storage might contribute to egg white thinning. Degradation of ovalbumin/clusterin during egg storage may be due to the combined effect of proteolysis and increase in pH; this may also be partly responsible for egg white thinning phenomenon.
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Affiliation(s)
- Dileep A Omana
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Alberta, Canada
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