1
|
Bello SF, Adeola AC, Nie Q. The study of candidate genes in the improvement of egg production in ducks – a review. Poult Sci 2022; 101:101850. [PMID: 35544958 PMCID: PMC9108513 DOI: 10.1016/j.psj.2022.101850] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 03/05/2022] [Accepted: 03/08/2022] [Indexed: 11/01/2022] Open
Abstract
Duck is the second-largest poultry species aside from chicken. The rate of egg production is a major determinant of the economic income of poultry farmers. Among the reproductive organs, the ovary is a major part of the female reproductive system which is highly important for egg production. Based on the importance of this organ, several studies have been carried out to identify candidate genes at the transcriptome level, and also the expression level of these genes at different tissues or egg-laying conditions, and single nucleotide polymorphism (SNPs) of genes associated with egg production in duck. In this review, expression profile and association study analyses at SNPs level of different candidate genes with egg production traits of duck were highlighted. Furthermore, different studies on transcriptome analysis, Quantitative Trait Loci (QTL) mapping, and Genome Wide Association Study (GWAS) approach used to identify potential candidate genes for egg production in ducks were reported. This review would widen our knowledge on molecular markers that are associated or have a positive correlation to improving egg production in ducks, for the increasing world populace.
Collapse
|
2
|
Liu H, Zhou Z, Hu J, Guo Z, Xu Y, Li Y, Wang L, Fan W, Liang S, Liu D, Zhang Y, Xie M, Tang J, Huang W, Zhang Q, Hou S. Genetic variations for egg internal quality of ducks revealed by genome-wide association study. Anim Genet 2021; 52:536-541. [PMID: 34013574 DOI: 10.1111/age.13063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Revised: 02/16/2021] [Accepted: 03/17/2021] [Indexed: 11/28/2022]
Abstract
Egg internal quality traits are important traits related to egg production in poultry industry. To better understand the genetic architecture of egg internal quality traits in ducks, we performed genetic parameters estimates and a genome-wide association study (GWAS). The phenotypic values of egg weight, yolk color, albumin height (AH), yolk weight, and Haugh unit (HU) were collected individually from 352 F2 laying ducks produced by reciprocal crosses between mallards and Pekin ducks, and their genotypes were assayed by whole genome re-sequencing. The results showed that the AH and HU traits have a clear coefficient of variance, around 15% for both mallards and Pekin ducks. The pedigree-based genetic parameters estimates rane from 0.26 to 0.71 for all eight egg quality traits, while the highest heritability was 0.71 for egg weight. The GWAS showed that a clear signal was associated with AH and HU traits. The locus zoom analysis and conditional GWAS helped to narrow the candidate region to ~5.8-Mb spanning from 14.7 to 20.5 Mb on Chromosome 5, which harbored 111 candidate genes. MUC6 and LDLRAD3 were finally promised as the major candidate genes affecting albumen composition. Our data revealed the egg internal quality traits for the first time in ducks, which provides a theoretical basis and technological support for improving duck egg internal quality.
Collapse
Affiliation(s)
- Hehe Liu
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.,Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 613000, China
| | - Zhengkui Zhou
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Jian Hu
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Zhanbao Guo
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Yaxi Xu
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Yanying Li
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 613000, China
| | - Lei Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 613000, China
| | - Wenlei Fan
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Suyun Liang
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Dapeng Liu
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Yunsheng Zhang
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Ming Xie
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Jing Tang
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Wei Huang
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Qi Zhang
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Shuisheng Hou
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| |
Collapse
|
3
|
Haqani MI, Nomura S, Nakano M, Goto T, Nagano AJ, Takenouchi A, Nakamura Y, Ishikawa A, Tsudzuki M. Mapping of Quantitative Trait Loci Controlling Egg-Quality and -Production Traits in Japanese Quail ( Coturnix japonica) Using Restriction-Site Associated DNA Sequencing. Genes (Basel) 2021; 12:735. [PMID: 34068239 DOI: 10.3390/genes12050735] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 05/07/2021] [Accepted: 05/08/2021] [Indexed: 02/07/2023] Open
Abstract
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.
Collapse
|
4
|
Liu Z, Sun C, Yan Y, Li G, Shi F, Wu G, Liu A, Yang N. Genetic variations for egg quality of chickens at late laying period revealed by genome-wide association study. Sci Rep 2018; 8:10832. [PMID: 30018363 DOI: 10.1038/s41598-018-29162-7] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Accepted: 07/02/2018] [Indexed: 12/26/2022] Open
Abstract
With the extension of the egg-laying cycle, the rapid decline in egg quality at late laying period has aroused great concern in the poultry industry. Herein, we performed a genome-wide association study (GWAS) to identify genomic variations associated with egg quality, employing chicken 600 K high-density SNP arrays in a population of 1078 hens at 72 and 80 weeks of age. The results indicated that a genomic region spanning from 8.95 to 9.31 Mb (~0.36 Mb) on GGA13 was significantly associated with the albumen height (AH) and the haugh unit (HU), and the two most significant SNPs accounted for 3.12 ~ 5.75% of the phenotypic variance. Two promising genes, MSX2 and DRD1, were mapped to the narrow significant region, which was involved in embryonic and ovary development and found to be related to egg production, respectively. Moreover, three interesting genes, RHOA, SDF4 and TNFRSF4, identified from three significant loci, were considered to be candidate genes for egg shell colour. Findings in our study could provide worthy theoretical basis and technological support to improve late-stage egg quality for breeders.
Collapse
|
5
|
Wang H, Chen L, Jiang Y, Gao S, Chen S, Zheng X, Liu Z, Zhao Y, Li H, Yu J, Wang F, Liu Y, Li C, Zhou X. Association of gene polymorphisms of estrogen receptor, follicle-stimulating hormone β and leptin with follicular cysts in Large White sows. Theriogenology 2017; 103:143-148. [DOI: 10.1016/j.theriogenology.2017.03.030] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Revised: 03/13/2017] [Accepted: 03/14/2017] [Indexed: 12/24/2022]
|
6
|
Zhang Q, Zhu F, Liu L, Zheng CW, Wang de H, Hou ZC, Ning ZH. Integrating transcriptome and genome re-sequencing data to identify key genes and mutations affecting chicken eggshell qualities. PLoS One 2015; 10:e0125890. [PMID: 25974068 DOI: 10.1371/journal.pone.0125890] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2014] [Accepted: 03/24/2015] [Indexed: 12/21/2022] Open
Abstract
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.
Collapse
|
7
|
Zhang Q, Liu L, Zhu F, Ning Z, Hincke MT, Yang N, Hou Z. Integrating de novo transcriptome assembly and cloning to obtain chicken Ovocleidin-17 full-length cDNA. PLoS One 2014; 9:e93452. [PMID: 24676480 DOI: 10.1371/journal.pone.0093452] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2013] [Accepted: 03/04/2014] [Indexed: 01/06/2023] Open
Abstract
Efficiently obtaining full-length cDNA for a target gene is the key step for functional studies and probing genetic variations. However, almost all sequenced domestic animal genomes are not ‘finished’. Many functionally important genes are located in these gapped regions. It can be difficult to obtain full-length cDNA for which only partial amino acid/EST sequences exist. In this study we report a general pipeline to obtain full-length cDNA, and illustrate this approach for one important gene (Ovocleidin-17, OC-17) that is associated with chicken eggshell biomineralization. Chicken OC-17 is one of the best candidates to control and regulate the deposition of calcium carbonate in the calcified eggshell layer. OC-17 protein has been purified, sequenced, and has had its three-dimensional structure solved. However, researchers still cannot conduct OC-17 mRNA related studies because the mRNA sequence is unknown and the gene is absent from the current chicken genome. We used RNA-Seq to obtain the entire transcriptome of the adult hen uterus, and then conducted de novo transcriptome assembling with bioinformatics analysis to obtain candidate OC-17 transcripts. Based on this sequence, we used RACE and PCR cloning methods to successfully obtain the full-length OC-17 cDNA. Temporal and spatial OC-17 mRNA expression analyses were also performed to demonstrate that OC-17 is predominantly expressed in the adult hen uterus during the laying cycle and barely at immature developmental stages. Differential uterine expression of OC-17 was observed in hens laying eggs with weak versus strong eggshell, confirming its important role in the regulation of eggshell mineralization and providing a new tool for genetic selection for eggshell quality parameters. This study is the first one to report the full-length OC-17 cDNA sequence, and builds a foundation for OC-17 mRNA related studies. We provide a general method for biologists experiencing difficulty in obtaining candidate gene full-length cDNA sequences.
Collapse
|
8
|
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] [What about the content of this article? (0)] [Affiliation(s)] [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.
Collapse
Affiliation(s)
- A Wolc
- Department of Animal Science, Iowa State University, Ames, IA, USA; Hy-Line International, Dallas Center, IA, USA
| | | | | | | | | | | | | | | | | | | | | |
Collapse
|
9
|
Fan YF, Hou ZC, Yi GQ, Xu GY, Yang N. The sodium channel gene family is specifically expressed in hen uterus and associated with eggshell quality traits. BMC Genet 2013; 14:90. [PMID: 24059973 PMCID: PMC3851161 DOI: 10.1186/1471-2156-14-90] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2013] [Accepted: 09/10/2013] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Eggshell quality is important for the poultry industry. During eggshell formation a mass of inorganic minerals is deposited. The Sodium Channel (SCNN1) gene family plays an essential role in cation transportation. The objective of this study was to investigate the pattern of expression of members of the SCNN1 gene family, their variation and their effects on eggshell quality. RESULT The highest expression of SCNN1a, SCNN1b, and SCNN1g genes were in the active uterus during eggshell mineralization, while SCNN1d showed its highest expression level in the quiescent uterus (no egg present). Nineteen candidate SNPs from the four genes were genotyped in a population of 338 White Leghorn layers. Association analysis between SNPs (haplotypes/diplotypes) and eggshell traits was performed. Among seven significant SNPs, five SNPs were associated with eggshell strength, eggshell thickness, eggshell percentage or/and egg weight, while the other two SNPs within SCNN1d were only associated with eggshell percentage. These SNPs had a 0.25-6.99% contribution to phenotypic variance, depending on the trait. In haplotype analysis, SCNN1b and SCNN1d were associated with egg weight. The SCNN1b and SCNN1g were significantly associated with eggshell weight while only SCNN1g explained 2.04% of phenotypic variance. All the alleles of the members of SCNN1 gene family were associated with eggshell percentage and eggshell thickness, and others members had an association with eggshell strength except for SCNN1a. The contribution of different haplotypes of the SCNN1 gene family to eggshell phenotypic variance ranged from 0.09% to 5.74%. CONCLUSIONS Our study indicated that the SCNN1 gene family showed tissue expression specificity and was significantly associated with eggshell traits in chicken. This study provides evidence that genetic variation in members of the sodium channel can influence eggshell quality.
Collapse
Affiliation(s)
- Yan-Feng Fan
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, China Agricultural University, Beijing 100193, China.
| | | | | | | | | |
Collapse
|