Full Text:   <247>

Summary:  <34>

Suppl. Mater.: 

CLC number: 

On-line Access: 2024-04-07

Received: 2023-06-21

Revision Accepted: 2023-10-10

Crosschecked: 2024-04-07

Cited: 0

Clicked: 341

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Natalia V. DEMENTIEVA

https://orcid.org/0000-0003-0210-9344

Darren K. GRIFFIN

https://orcid.org/0000-0001-7595-3226

Michael N. ROMANOV

https://orcid.org/0000-0003-3584-4644

-   Go to

Article info.
Open peer comments

Journal of Zhejiang University SCIENCE B 2024 Vol.25 No.4 P.324-340

http://doi.org/10.1631/jzus.B2300443


Large-scale genome-wide SNP analysis reveals the rugged (and ragged) landscape of global ancestry, phylogeny, and demographic history in chicken breeds


Author(s):  Natalia V. DEMENTIEVA, Yuri S. SHCHERBAKOV, Olga I. STANISHEVSKAYA, Anatoly B. VAKHRAMEEV, Tatiana A. LARKINA, Artem P. DYSIN, Olga A. NIKOLAEVA, Anna E. RYABOVA, Anastasiia I. AZOVTSEVA, Olga V. MITROFANOVA, Grigoriy K. PEGLIVANYAN, Natalia R. REINBACH, Darren K. GRIFFIN, Michael N. ROMANOV

Affiliation(s):  Russian Research Institute of Farm Animal Genetics and Breeding ‒ Branch of the L. K. Ernst Federal Research Centre for Animal Husbandry, Pushkin, St. Petersburg, 196601, Russia; more

Corresponding email(s):   dementevan@mail.ru, Griffin@kent.ac.uk, m.romanov@kent.ac.uk

Key Words:  Chicken genome diversity, Single nucleotide polymorphism (SNP) analysis, Gene pool, Global ancestry, Phylogeny, Demographic history


Natalia V. DEMENTIEVA, Yuri S. SHCHERBAKOV, Olga I. STANISHEVSKAYA, Anatoly B. VAKHRAMEEV, Tatiana A. LARKINA, Artem P. DYSIN, Olga A. NIKOLAEVA, Anna E. RYABOVA, Anastasiia I. AZOVTSEVA, Olga V. MITROFANOVA, Grigoriy K. PEGLIVANYAN, Natalia R. REINBACH, Darren K. GRIFFIN, Michael N. ROMANOV. Large-scale genome-wide SNP analysis reveals the rugged (and ragged) landscape of global ancestry, phylogeny, and demographic history in chicken breeds[J]. Journal of Zhejiang University Science B, 2024, 25(4): 324-340.

@article{title="Large-scale genome-wide SNP analysis reveals the rugged (and ragged) landscape of global ancestry, phylogeny, and demographic history in chicken breeds",
author="Natalia V. DEMENTIEVA, Yuri S. SHCHERBAKOV, Olga I. STANISHEVSKAYA, Anatoly B. VAKHRAMEEV, Tatiana A. LARKINA, Artem P. DYSIN, Olga A. NIKOLAEVA, Anna E. RYABOVA, Anastasiia I. AZOVTSEVA, Olga V. MITROFANOVA, Grigoriy K. PEGLIVANYAN, Natalia R. REINBACH, Darren K. GRIFFIN, Michael N. ROMANOV",
journal="Journal of Zhejiang University Science B",
volume="25",
number="4",
pages="324-340",
year="2024",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B2300443"
}

%0 Journal Article
%T Large-scale genome-wide SNP analysis reveals the rugged (and ragged) landscape of global ancestry, phylogeny, and demographic history in chicken breeds
%A Natalia V. DEMENTIEVA
%A Yuri S. SHCHERBAKOV
%A Olga I. STANISHEVSKAYA
%A Anatoly B. VAKHRAMEEV
%A Tatiana A. LARKINA
%A Artem P. DYSIN
%A Olga A. NIKOLAEVA
%A Anna E. RYABOVA
%A Anastasiia I. AZOVTSEVA
%A Olga V. MITROFANOVA
%A Grigoriy K. PEGLIVANYAN
%A Natalia R. REINBACH
%A Darren K. GRIFFIN
%A Michael N. ROMANOV
%J Journal of Zhejiang University SCIENCE B
%V 25
%N 4
%P 324-340
%@ 1673-1581
%D 2024
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B2300443

TY - JOUR
T1 - Large-scale genome-wide SNP analysis reveals the rugged (and ragged) landscape of global ancestry, phylogeny, and demographic history in chicken breeds
A1 - Natalia V. DEMENTIEVA
A1 - Yuri S. SHCHERBAKOV
A1 - Olga I. STANISHEVSKAYA
A1 - Anatoly B. VAKHRAMEEV
A1 - Tatiana A. LARKINA
A1 - Artem P. DYSIN
A1 - Olga A. NIKOLAEVA
A1 - Anna E. RYABOVA
A1 - Anastasiia I. AZOVTSEVA
A1 - Olga V. MITROFANOVA
A1 - Grigoriy K. PEGLIVANYAN
A1 - Natalia R. REINBACH
A1 - Darren K. GRIFFIN
A1 - Michael N. ROMANOV
J0 - Journal of Zhejiang University Science B
VL - 25
IS - 4
SP - 324
EP - 340
%@ 1673-1581
Y1 - 2024
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.B2300443


Abstract: 
The worldwide chicken gene pool encompasses a remarkable, but shrinking, number of divergently selected breeds of diverse origin. This study was a large-scale genome-wide analysis of the landscape of the complex molecular architecture, genetic variability, and detailed structure among 49 populations. These populations represent a significant sample of the world’s chicken breeds from Europe (Russia, Czech Republic, France, Spain, UK, etc.), Asia (China), North America (USA), and Oceania (Australia). Based on the results of breed genotyping using the Illumina 60K single nucleotide polymorphism (SNP) chip, a bioinformatic analysis was carried out. This included the calculation of heterozygosity/homozygosity statistics, inbreeding coefficients, and effective population size. It also included assessment of linkage disequilibrium and construction of phylogenetic trees. Using multidimensional scaling, principal component analysis, and ADMIXTURE-assisted global ancestry analysis, we explored the genetic structure of populations and subpopulations in each breed. An overall 49-population phylogeny analysis was also performed, and a refined evolutionary model of chicken breed formation was proposed, which included egg, meat, dual-purpose types, and ambiguous breeds. Such a large-scale survey of genetic resources in poultry farming using modern genomic methods is of great interest both from the viewpoint of a general understanding of the genetics of the domestic chicken and for the further development of genomic technologies and approaches in poultry breeding. In general, whole genome SNP genotyping of promising chicken breeds from the worldwide gene pool will promote the further development of modern genomic science as applied to poultry.

大规模全基因组SNP分析揭示了鸡品种的全球祖先、种群发展和种群历史的复杂(和多样)的遗传图谱

Natalia V. DEMENTIEVA1, Yuri S. SHCHERBAKOV1, Olga I. STANISHEVSKAYA1, Anatoly B. VAKHRAMEEV1,Tatiana A. LARKINA1, Artem P. DYSIN1, Olga A. NIKOLAEVA1, Anna E. RYABOVA1, Anastasiia I. AZOVTSEVA1,Olga V. MITROFANOVA1, Grigoriy K. PEGLIVANYAN1, Natalia R. REINBACH1, Darren K. GRIFFIN2,Michael N. ROMANOV2,3
1Russian Research Institute of Farm Animal Genetics and Breeding - Branch of the L. K. Ernst Federal Research Centre for Animal Husbandry, Pushkin, St. Petersburg, 196601, Russia
2School of Biosciences, University of Kent, Canterbury, CT2 7NJ, UK
3L. K. Ernst Federal Research Center for Animal Husbandry, Dubrovitsy, Podolsk, Moscow Oblast, 142132, Russia
摘要:全球范围内的鸡品种基因库中涵盖了数量庞大且多样化起源的多种品系,不过这个数量正逐渐减少。本研究采用了大规模的全基因组分析,探究了49个种群的复杂分子结构、遗传变异性以及详细结构组成。这些种群来自于欧洲(如俄罗斯、捷克共和国、法国、西班牙、英国等)、亚洲(如中国)、北美(如美国)和大洋洲(如澳大利亚),代表了世界各地的鸡品种。我们使用Illumina 60K单核苷酸多态性(SNP)芯片对品种进行了基因型分析,然后进行了生物信息学分析。这一分析包括了杂合子/纯合子统计、近交系数和有效种群大小的计算,以及连锁不平衡的评估和系统发生树的构建。通过多维缩放、主成分分析和ADMIXTURE辅助全球祖先分析,我们探索了每个品种种群和亚群的遗传结构。此外,还进行了总体的49个种群的系统发生分析,并提出了一种精细化的鸡品种形成演化模型,其中包括蛋、肉、兼用型和混合的品种。利用现代基因组方法对家禽养殖中的遗传资源进行如此大规模的调查,不仅对于普遍了解家鸡遗传学的角度具有重要意义,而且对于进一步发展家禽育种中的基因组技术和方法也是至关重要的。总而言之,对来自全球基因库的有发展潜力的鸡品种进行全基因组SNP基因分型,将促进现代基因组学在家禽育种中的进一步发展。

关键词:鸡基因组多样性;单核苷酸多态性分析(SNP);基因库;全球原始祖先;种群发展史;种群大小历史

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]AbdelmanovaAS, DotsevAV, RomanovMN, et al., 2021. Unveiling comparative genomic trajectories of selection and key candidate genes in egg-type Russian White and meat-type White Cornish chickens. Biology, 10(9):876.

[2]AlexanderDH, NovembreJ, LangeK, 2009. Fast model-based estimation of ancestry in unrelated individuals. Genome Res, 19(9):1655-1664.

[3]AnderssonL, 2001. Genetic dissection of phenotypic diversity in farm animals. Nat Rev Genet, 2(2):130-138.

[4]BarbatoM, Orozco-terWengelP, TapioM, et al., 2015. SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data. Front Genet, 6:109.

[5]BaumungR, WieczorekM, 2015. Status and trends of animal genetic resources. In: Scherf BD, Pilling D (Eds.), The Second Report on the State of the World’s Animal Genetic Resources for Food and Agriculture. FAO Commission on Genetic Resources for Food and Agriculture Assessments, Rome, Italy, p.25-42.

[6]BeissingerTM, GholamiM, ErbeM, et al., 2016. Using the variability of linkage disequilibrium between subpopulations to infer sweeps and epistatic selection in a diverse panel of chickens. Heredity, 116(2):158-166.

[7]BiscariniF, CozziP, GaspaG, et al., 2019. detectRUNS: detect runs of homozygosity and runs of heterozygosity in diploid genomes. Version 0.9.6. The Comprehensive R Archive Network.

[8]BondarenkoY, KhvostikV, 2020. Improving the productivity of domestic meat and egg chickens. Bull Sumy Natl Agrar Univ Ser Livest, 2(41):29-32.

[9]BondarenkoYV, KutnyukPI, 1995. Some results of genetic monitoring of embryonic defects in poultry populations. In: Gene Pool of Animal Breeds and Methods of its Use: Materials of the International Scientific and Practical Conference Dedicated to the 110th Anniversary of the Birth of Academician N.D. Potemkin. Kharkov, Ukraine, 5-6 December 1995. Ministry of Agriculture and Food of Ukraine, Kharkov Zooveterinary Institute, RIO KhZVI, Kharkov, Ukraine, p.63-64 (in Russian).

[10]BondarenkoYV, PodstreshnyAP, 1996. Genetic monitoring of chicken populations. In: Abstracts of the 2nd International Conference on Molecular Genetic Markers of Animals (Kiev, Ukraine, 15-17 May 1996). Agrarna Nauka, Kiev, Ukraine, p.47-48 (in Russian).

[11]BondarenkoYV, ZharkovaIP, RomanovMN, 1986. Study of down colour genotype in the collection flock geese at the All-Union Poultry Research and Technological Institute. Naučno-tehničeskij BûLletenʹ ‒ Ukrainskij Naučno-issledovatelʹskij Institut Pticevodstva, 21:3-7 (in Russian).

[12]ChristensenOF, LundMS, 2010. Genomic prediction when some animals are not genotyped. Genet Sel Evol, 42:2.

[13]CortiE, MoiseyevaIG, RomanovMN, 2010. Five-toed chickens: their origin, genetics, geographical spreading and history. Izv Timiryazev S-Kh Akad, (7):156-170.

[14]DementevaNV, RomanovMN, KudinovAA, et al., 2017. Studying the structure of a gene pool population of the Russian White chicken breed by genome-wide SNP scan. Sel'skokhozyaistvennaya Biol, 52(6):1166-1174.

[15]DementevaNV, KudinovAA, MitrofanovaOV, et al., 2018. Genome-wide association study of reproductive traits in a gene pool breed of the Russian White chickens. Reprod Domest Anim, 53(Suppl 2):123-124.

[16]DementievaNV, FedorovaES, KrutikovaAA, et al., 2020a. Genetic variability of indels in the prolactin and dopamine receptor D2 genes and their association with the yield of allanto-amniotic fluid in Russian White laying hens. Tarım Bilim Derg ‒ J Agric Sci, 26(3):373-379.

[17]DementievaNV, KudinovAA, LarkinaTA, et al., 2020b. Genetic variability in local and imported germplasm chicken populations as revealed by analyzing runs of homozygosity. Animals, 10(10):1887.

[18]DementievaNV, ShcherbakovYS, MitrofanovaOV, et al., 2022a. Analysis of the accumulation of homozygosity regions in chickens of the Pushkin breed using data from whole genome genotyping. Ecol Genet, 20(1):31-39.

[19]DementievaNV, ShcherbakovYS, TyshchenkoVI, et al., 2022b. Comparative analysis of molecular RFLP and SNP markers in assessing and understanding the genetic diversity of various chicken breeds. Genes, 13(10):1876.

[20]FedorovaES, DementievaNV, ShcherbakovYS, et al., 2022. Identification of key candidate genes in runs of homozygosity of the genome of two chicken breeds, associated with cold adaptation. Biology, 11(4):547.

[21]FelícioAM, BoschieroC, BalieiroJCC, et al., 2013. Identification and association of polymorphisms in CAPN1 and CAPN3 candidate genes related to performance and meat quality traits in chickens. Genet Mol Res, 12(1):472-482.

[22]FelsensteinJ, 1989. PHYLIP—Phylogeny Inference Package (Version 3.2). Cladistics, 5:164-166.

[23]FelsensteinJ, 2005. PHYLIP (Phylogeny Inference Package) Version 3.6. Department of Genome Sciences, University of Washington, Seattle, USA.

[24]GaoCQ, WangKJ, HuXY, et al., 2023. Conservation priority and run of homozygosity pattern assessment of global chicken genetic resources. Poult Sci, 102(11):103030.

[25]GroenenMAM, MegensHJ, ZareY, et al., 2011. The development and characterization of a 60K SNP chip for chicken. BMC Genomics, 12:274.

[26]GuoY, OuJH, ZanYJ, et al., 2022. Researching on the fine structure and admixture of the worldwide chicken population reveal connections between populations and important events in breeding history. Evol Appl, 15(4):553-564.

[27]JensenJ, MantysaariEA, MadsenP, et al., 1997. Residual maximum likelihood estimation of (co)variance components in multivariate mixed linear models using average information. J Ind Soc Agric Stat, 49:215-236.

[28]KudinovAA, DementievaNV, MitrofanovaOV, et al., 2019. Genome-wide association studies targeting the yield of extraembryonic fluid and production traits in Russian White chickens. BMC Genomics, 20:270.

[29]KulibabaR, TereshchenkoA, 2015.Transforming growth factor β1, pituitary-specific transcriptional factor 1 and insulin-like growth factor I gene polymorphisms in the population of the Poltava clay chicken breed: association with productive traits. Agric Sci Pract, 2(1):67-72.

[30]LarkinaTA, BarkovaOY, PeglivanyanGK, et al., 2021. Evolutionary subdivision of domestic chickens: implications for local breeds as assessed by phenotype and genotype in comparison to commercial and fancy breeds. Agriculture, 11(10):914.

[31]LetunicI, BorkP, 2019. Interactive Tree Of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Res, 47(W1):W256-W259.

[32]LiDY, LiY, LiM, et al., 2019. Population genomics identifies patterns of genetic diversity and selection in chicken. BMC Genomics, 20:263.

[33]MastrangeloS, Ben-JemaaS, PeriniF, et al., 2023. Genome-wide mapping of signatures of selection using a high-density array identified candidate genes for growth traits and local adaptation in chickens. Genet Sel Evol, 55:20.

[34]MohammadabadiMR, NikbakhtiM, MirzaeeHR, et al., 2010. Genetic variability in three native Iranian chicken populations of the Khorasan province based on microsatellite markers. Genetika, 46(4):572-576.

[35]MoiseevaI, 1995. Fowl genetic resources in Russia. Ptitsevodstvo, 5:12-15 (in Russian).

[36]MoiseyevaIG, 1996. The state of poultry genetic resources in Russia. Anim Genet Resour, 17:73-86.

[37]MoiseyevaIG, BannikovaLV, AltukhovYP, 1993. State of poultry breeding in Russia: genetic monitoring. Mezhdunar S-Kh Zh, 5-6:66-69.

[38]MoiseyevaIG, RomanovMN, NikiforovAA, et al., 2003. Evolutionary relationships of Red Jungle Fowl and chicken breeds. Genet Sel Evol, 35(5):403.

[39]MoiseyevaIG, KovalenkoAT, MosyakinaTV, et al., 2006. Origin, history, genetics and economic traits of the Poltava chicken breed. Elektronnyi Zhurnal [Electronic J], Issue 4. https://web.archive.org/web/20120205195904/http://www.lab-cga.ru/articles/Jornal04/Statia2.htm [Accessed on Sept. 29, 2023] (in Russian).

[40]MoiseyevaIG, NikiforovAA, RomanovMN, et al., 2007a. Origin, history, genetics and economic traits of the Yurlov Crower chicken breed. Elektronnyi Zhurnal [Electronic J]. https://web.archive.org/web/20120210170800/http://www.lab-cga.ru/articles/Yurlovskaya/Yurlovskaya.htm [Accessed on Sept. 29, 2023] (in Russian).

[41]MoiseyevaIG, RomanovMN, KovalenkoAT, et al., 2007b. The Poltava chicken breed of Ukraine: its history, characterization and conservation. Anim Genet Resour, 40:71-78.

[42]MoiseyevaIG, CortiE, RomanovMN, 2009a. Polydactyly in chickens. In: Fisinin VI (Ed.), Advances in Modern Poultry Science. Proceedings of the 16th International Conference (Sergiyev Posad, Russia, 19-21 May 2009). WPSA, RAAS, Poultry Science and Technology Institute, Sergiyev Posad, Russia, p.51-53 (in Russian).

[43]MoiseyevaIG, RomanovMN, AlexandrovAV, et al., 2009b. Evolution and genetic diversity of old domestic hen’s breed‒Yurlovskaya golosistaya: system analysis of variability forms. Izv Timiryazev S-Kh Akad, (3):132-147 (in Russian).

[44]MoiseyevaIG, SevastyanovaAA, AlexandrovAV, et al., 2011. Singing breeds of hens. Priroda, 4:10-18 (in Russian).

[45]MoiseyevaIG, SevastyanovaAA, AlexandrovAV, et al., 2016. Orloff chicken breed: history, current status and studies. Izv Timiryazev S-Kh Akad, (1):78-96 (in Russian).

[46]OyunNY, MoiseyevaIG, SevastianovaAA, et al., 2015a. Mitochondrial DNA polymorphism in different populations of Spangled Orloff chickens. Genetika, 51(9):1057-1065 (in Russian).

[47]OyunNY, MoiseyevaIG, SevastianovaAA, et al., 2015b. Mitochondrial DNA polymorphism in different populations of Orloff Spangled chicken breed. Russ J Genet, 51(9):908-915.

[48]PattersonN, PriceAL, ReichD, 2006. Population structure and eigenanalysis. PLoS Genet, 2(12):e190.

[49]PeriniF, CendronF, WuZ, et al., 2023. Genomics of dwarfism in Italian local chicken breeds. Genes, 14(3):633.

[50]PlemyashovКV, SmaragdovMG, RomanovMN, 2021a. Genomic assessment of breeding bulls. In: Pozyabin SV, Kochish II, Romanov MN (Eds.), Materials of the 3rd International Scientific and Practical Conference on Molecular Genetic Technologies for Analysis of Gene Expression Related to Animal Productivity and Disease Resistance. Moscow, Russia, 30 September 2021. Sel'skokhozyaistvennye Tekhnologii, Moscow, Russia, p.363-367 (in Russian).

[51]PlemyashovКV, SmaragdovMG, RomanovMN, 2021b. Molecular genetic polymorphism in animal populations and its application in intensive breeding of dairy cattle—a review. In: Pozyabin SV, Kochish II, Romanov MN (Eds.), Materials of the 3rd International Scientific and Practical Conference on Molecular Genetic Technologies for Analysis of Gene Expression Related to Animal Productivity and Disease Resistance. Moscow, Russia, 30 September 2021. Sel'skokhozyaistvennye Tekhnologii, Moscow, Russia, p.368-378 (in Russian).

[52]PocrnicI, ObšteterJ, GaynorRC, et al., 2023. Assessment of long-term trends in genetic mean and variance after the introduction of genomic selection in layers: a simulation study. Front Genet, 14:1168212.

[53]PurcellS, NealeB, Todd-BrownK, et al., 2007. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet, 81(3):559-575.

[54]QanbariS, SeidelM, StromTM, et al., 2015. Parallel selection revealed by population sequencing in chicken. Genome Biol Evol, 7(12):3299-3306.

[55]RenXF, GuanZ, ZhaoXR, et al., 2023. Systematic selection signature analysis of Chinese gamecocks based on genomic and transcriptomic data. Int J Mol Sci, 24(6):5868.

[56]RomanovMN, BondarenkoYV, 1994. Introducing the Ukrainian indigenous poultry ‒ the Poltava chickens. Fancy Fowl, 14(2):8-9.

[57]RomanovMN, WeigendS, 1999. Genetic diversity in chicken populations based on microsatellite markers. In: Dekkers JCM, Lamont SJ, Rothschild MF (Eds.), Proceedings of the Conference “From Jay Lush to Genomics: Visions for Animal Breeding and Genetics”. Iowa State University, Department of Animal Science, Ames, IA, USA, p.174.

[58]RomanovMN, SazanovAA, MoiseyevaIG, et al., 2009. Poultry. In: Cockett NE, Kole C (Eds.), Genome Mapping and Genomics in Animals. Springer-Verlag, Berlin, Heidelberg, p.75-141.

[59]RomanovMN, AbdelmanovaAS, FisininVI, et al., 2023. Selective footprints and genes relevant to cold adaptation and other phenotypic traits are unscrambled in the genomes of divergently selected chicken breeds. J Anim Sci Biotechnol, 14:35.

[60]RoméH, VarenneA, HéraultF, et al., 2015. GWAS analyses reveal QTL in egg layers that differ in response to diet differences. Genet Sel Evol, 47:83.

[61]RyabokonYO, PabatVO, MykytyukDM, et al., 2005. Catalog of Poultry Breeding Resources of Ukraine. Poultry Research Institute, Kharkiv, Ukraine (in Ukrainian).

[62]SaitouN, NeiM, 1987. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol, 4(4):406-425.

[63]SallamM, WilsonPW, AnderssonB, et al., 2023. Genetic markers associated with bone composition in Rhode Island Red laying hens. Genet Sel Evol, 55:44.

[64]SulimovaGE, StolpovskyYA, KashtanovSN, et al., 2005. Methods of managing the genetic resources of domesticated animals. In: Rysin LP (Ed.), Fundamentals of Biological Resource Management: Collection of Scientific Articles. Partnership of Scientific Publications KMK LLC, Moscow, Russia, p.331-342 (in Russian).

[65]TagirovMT, TereshchenkoLV, TereshchenkoAV, 2006. Substantiation of the possibility of using primary germ cells as material for the preservation of poultry genetic resources. Ptakhivnytstvo, 58:464-473 (in Russian).

[66]TanXD, LiuRR, LiW, et al., 2022. Assessment the effect of genomic selection and detection of selective signature in broilers. Poult Sci, 101(6):101856.

[67]TereshchenkoOV, PankovaSM, KaterynychOO, 2015. Directions of development of poultry industry. Vìsnik Agrar Nauk, 93:27-30.

[68]Tixier-BoichardM, CoquerelleG, Vilela-LamegoC, et al., 1999. Contribution of data on history, management and phenotype to the description of the diversity between chicken populations sampled within the AVIANDIV project. In: Preisinger R (Ed.), Proceedings of the Poultry Genetics Symposium. Working Group 3 of WPSA, Lohmann Tierzucht, Cuxhaven, Germany, p.15-21.

[69]VakhrameevAB, NarushinVG, LarkinaTA, et al., 2023. Disentangling clustering configuration intricacies for divergently selected chicken breeds. Sci Rep, 13:3319.

[70]VanRadenPM, 2008. Efficient methods to compute genomic predictions. J Dairy Sci, 91(11):4414-4423.

[71]WangMS, ZhangJJ, GuoX, et al., 2021. Large-scale genomic analysis reveals the genetic cost of chicken domestication. BMC Biol, 19:118.

[72]WeigendS, RomanovMN, RathD, 2004a. Methodologies to identify, evaluate and conserve poultry genetic resources. In: XXII World’s Poultry Congress & Exhibition, Book of Abstracts. WPSA ‒ Turkish Branch, Istanbul, Turkey, p.84.

[73]WeigendS, RomanovMN, Ben-AriG, et al., 2004b. Overview on the use of molecular markers to characterize genetic diversity in chickens. In: XXII World’s Poultry Congress & Exhibition, Book of Abstracts. WPSA‒Turkish Branch, Istanbul, Turkey, p.192.

[74]WeirBS, CockerhamCC, 1984. Estimating F-statistics for the analysis of population structure. Evolution, 38(6):1358-1370.

[75]WickhamH, 2009. ggplot2: Elegant Graphics for Data Analysis. Springer, New York, NY, USA.

[76]WraggD, MwacharoJM, AlcaldeJA, et al., 2012. Analysis of genome-wide structure, diversity and fine mapping of Mendelian traits in traditional and village chickens. Heredity, 109:6-18.

[77]Zakharov-GesekhusIA, StolpovskyYA, UkhanovSV, et al., 2007. Monitoring the gene pools of animal populations in connection with selection tasks and the study of phylogeny. In: Farm Animals. Russian Academy of Sciences, Moscow, Russia, p.122-124 (in Russian).

[78]ZhangGX, ZhaoXH, WangJY, et al., 2012. Effect of an exon 1 mutation in the myostatin gene on the growth traits of the Bian chicken. Anim Genet, 43(4):458-459.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE