High-throughput and Cost-effective Chicken Genotyping Using Next-Generation Sequencing

被引:43
|
作者
Pertille, Fabio [1 ]
Guerrero-Bosagna, Carlos [2 ]
da Silva, Vinicius Henrique [1 ]
Boschiero, Clarissa [1 ]
da Silva Nunes, Jose de Ribamar [1 ]
Ledur, Monica Correa [3 ]
Jensen, Per
Coutinho, Luiz Lehmann [1 ]
机构
[1] Univ Sao Paulo, Anim Sci & Pastures Dept, Anim Biotechnol Lab, Luiz de Queiroz Coll Agr ESALQ, Sao Paulo, Brazil
[2] Linkoping Univ, AVIAN Behav Genom & Physiol Grp, IFM Biol, Linkoping, Sweden
[3] Brazilian Agr Res Corp EMBRAPA Swine & Poultry, Concordia, SC, Brazil
来源
SCIENTIFIC REPORTS | 2016年 / 6卷
基金
巴西圣保罗研究基金会;
关键词
QTL REGION; SNP; DISCOVERY; DENSITY; MAP;
D O I
10.1038/srep26929
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Chicken genotyping is becoming common practice in conventional animal breeding improvement. Despite the power of high-throughput methods for genotyping, their high cost limits large scale use in animal breeding and selection. In the present paper we optimized the CornellGBS, an efficient and cost-effective genotyping by sequence approach developed in plants, for its application in chickens. Here we describe the successful genotyping of a large number of chickens (462) using CornellGBS approach. Genomic DNA was cleaved with the PstI enzyme, ligated to adapters with barcodes identifying individual animals, and then sequenced on Illumina platform. After filtering parameters were applied, 134,528 SNPs were identified in our experimental population of chickens. Of these SNPs, 67,096 had a minimum taxon call rate of 90% and were considered 'unique tags'. Interestingly, 20.7% of these unique tags have not been previously reported in the dbSNP. Moreover, 92.6% of these SNPs were concordant with a previous Whole Chicken-genome re-sequencing dataset used for validation purposes. The application of CornellGBS in chickens showed high performance to infer SNPs, particularly in exonic regions and microchromosomes. This approach represents a cost-effective (similar to US$50/sample) and powerful alternative to current genotyping methods, which has the potential to improve whole-genome selection (WGS), and genome-wide association studies (GWAS) in chicken production.
引用
收藏
页数:12
相关论文
共 50 条
  • [41] RH genotyping by next-generation sequencing
    Khandelwal, Aditi
    Zittermann, Sandra
    Sierocinski, Thomas
    Montemayor, Celina
    ANNALS OF BLOOD, 2023, 8
  • [42] A highly flexible and fast approach for high-throughput genetic testing using next-generation amplicon sequencing
    Vogel, F.
    Bruesehafer, K.
    Koledachkina, T.
    Loewe, R.
    Paknia, O.
    Kandaswamy, K. K.
    Weiss, M.
    Kishore, S.
    Rolfs, A.
    Bauer, P.
    EUROPEAN JOURNAL OF HUMAN GENETICS, 2018, 26 : 657 - 658
  • [43] High-throughput microsatellite marker development in Amur catfish (Silurus asotus) using next-generation sequencing
    Dandan Xu
    Yaoguang Zhang
    Zuogang Peng
    Conservation Genetics Resources, 2013, 5 : 487 - 490
  • [44] Analysis of genetic variability in 134 women with Turner Syndrome using high-throughput next-generation sequencing
    Suntharalingham, Jenifer P.
    Ishida, Miho
    Cameron-Pimblett, Antoinette
    McGlacken-Byrne, Sinead M.
    Del Valle, Ignacio
    Buonocore, Federica
    Brooks, Anthony
    Madhan, Gaganjit Kaur
    Conway, Gerard S.
    Achermann, John C.
    HORMONE RESEARCH IN PAEDIATRICS, 2022, 95 (SUPPL 2): : 301 - 302
  • [45] High-throughput microsatellite marker development in Amur catfish (Silurus asotus) using next-generation sequencing
    Xu, Dandan
    Zhang, Yaoguang
    Peng, Zuogang
    CONSERVATION GENETICS RESOURCES, 2013, 5 (02) : 487 - 490
  • [46] A workflow to increase verification rate of chromosomal structural rearrangements using high-throughput next-generation sequencing
    Quek, Kelly
    Nones, Katia
    Patch, Ann-Marie
    Fink, J. Lynn
    Newell, Felicity
    Cloonan, Nicole
    Miller, David
    Fadlullah, Muhammad Z. H.
    Kassahn, Karin
    Christ, Angelika N.
    Bruxner, Timothy J. C.
    Manning, Suzanne
    Harliwong, Ivon
    Idrisoglu, Senel
    Nourse, Craig
    Nourbakhsh, Ehsan
    Wani, Shivangi
    Steptoe, Anita
    Anderson, Matthew
    Holmes, Oliver
    Leonard, Conrad
    Taylor, Darrin
    Wood, Scott
    Xu, Qinying
    Wilson, Peter
    Biankin, Andrew V.
    Pearson, John V.
    Waddell, Nic
    Grimmond, Sean M.
    BIOTECHNIQUES, 2014, 57 (01) : 31 - 38
  • [47] Next-Generation DNA Barcoding for Fish Identification Using High-Throughput Sequencing in Tai Lake, China
    Mu, Yawen
    Song, Chao
    Yang, Jianghua
    Zhang, Yong
    Zhang, Xiaowei
    WATER, 2023, 15 (04)
  • [48] Miniaturisation of high-throughput plasmid DNA library preparation for next-generation sequencing using multifactorial optimisation
    Suckling, Lorna
    McFarlane, Ciaran
    Sawyer, Chelsea
    Chambers, Stephen P.
    Kitney, Richard I.
    McClymont, David W.
    Freemont, Paul S.
    SYNTHETIC AND SYSTEMS BIOTECHNOLOGY, 2019, 4 (01) : 57 - 66
  • [49] Fungal High-throughput Taxonomic Identification tool for use with Next-Generation Sequencing ( FHiTINGS)
    Dannemiller, Karen C.
    Reeves, Darryl
    Bibby, Kyle
    Yamamoto, Naomichi
    Peccia, Jordan
    JOURNAL OF BASIC MICROBIOLOGY, 2014, 54 (04) : 315 - 321
  • [50] Next-generation sequencing is a robust strategy for the high-throughput detection of zygosity in transgenic maize
    Fritsch, Leonie
    Fischer, Rainer
    Wambach, Christoph
    Dudek, Max
    Schillberg, Stefan
    Schroeper, Florian
    TRANSGENIC RESEARCH, 2015, 24 (04) : 615 - 623