Development and application of genome sequencing in studies on poultry production traits and health

• Autorzy: Dunislawska A. , Slawinska A. , Siwek M.
• Języki publikacji: EN

Abstrakty

EN

Next-generation sequencing (NGS) is a novel method widely used in animal science and veterinary research. This technique revolutionized molecular biology and animal genetics research. The unquestionable advantage of NGS is an almost unlimited insight into genetic information. This review discusses the most important applications and achievements in poultry genomics available due to detailed sequence information. Here we present the development of sequencing methods and their further applications in poultry research. The chicken is an important livestock species and a model organism. It is the first non-mammalian amniote whose genome was sequenced by the International Chicken Genome Sequencing Consortium. Therefore, analysis of the chicken genome as a model organism and comparative analysis of genome reference plays an important role in current research. The detailed knowledge of the chicken genome position of genes associated with most important phenotypic traits will contribute to the development of molecular methods for the selection of animals.

Słowa kluczowe

EN

next generation sequencing; NGS zob.next generation sequencing; DNA sequencing; genome sequencing; poultry; chicken; animal production trait; animal health; veterinary research

• Wydawca: -
• Czasopismo: Medycyna Weterynaryjna
• Rocznik: 2019
• Tom: 75
• Numer: 01
• Opis fizyczny: p.30-34,ref.

Twórcy

autor

Dunislawska A.

• Department of Animal Biochemistry and Biotechnology, University of Science and Technology, Mazowiecka 28, 85-084 Bydgoszcz, Poland

autor

Slawinska A.

• Department of Animal Biochemistry and Biotechnology, University of Science and Technology, Mazowiecka 28, 85-084 Bydgoszcz, Poland

autor

Siwek M.

• Department of Animal Biochemistry and Biotechnology, University of Science and Technology, Mazowiecka 28, 85-084 Bydgoszcz, Poland

Bibliografia

• Ahmadian A., Gharizadeh B., Gustafsson A. C., Sterky F., Nyrén P., Uhlén M., Lundeberg J.: Single-Nucleotide Polymorphism Analysis by Pyrosequencing. Anal. Biochem. 2000, 280, 103-110.
• Altmüller J., Budde B. S., Nürnberg P.: Enrichment of target sequences for next-generation sequencing applications in research and diagnostics. Biol. Chem. 2014, 395, 231-237.
• Apopo S., Liu H., Jing L., Du X., Xie S., Gong Y., Xu R., Li S.: Identification and profiling of microRNAs associated with white and black plumage pigmentation in the white and black feather bulbs of ducks by RNA sequencing. Anim. Genet. 2015, 46, 627-635.
• Berghof T. V., Visker M. H., Arts J. A., Parmentier H. K., Poel J. J., Vereijken A. L., Bovenhuis H.: Genomic Region Containing Toll-Like Receptor Genes Has a Major Impact on Total IgM Antibodies Including KLH-Binding IgM Natural Antibodies in Chickens. Front. Immunol. 2017, 8, 1879.
• Boschiero C., Gheyas A. A., Ralph H. K., Eory L., Paton B., Kuo R., Fulton J., Preisinger R., Kaiser P., Burt D. W.: Detection and characterization of small insertion and deletion genetic variants in modern layer chicken genomes. BMC Genomics 2015, 16, 562.
• Brandström M., Ellegren H.: The genomic landscape of short insertion and deletion polymorphisms in the chicken (Gallus gallus) Genome: a high frequency of deletions in tandem duplicates. Genetics 2007, 176, 1691-1701.
• Buermans H. P. J., den Dunnen J. T.: Next generation sequencing technology: Advances and applications. Biochim. Biophys. Acta 2014, 1842, 1932-1941.
• Burt D. W.: Chicken genome: Current status and future opportunities. Genome Res. 2005, 15, 1692-1698.
• Burt D. W.: Emergence of the chicken as a model organism: implications for agriculture and biology. Poult. Sci. 2007, 86, 1460-1471.
• Bushman F., Lewinski M., Ciuffi A., Barr S., Leipzig J., Hannenhalli S., Hoffmann C.: Genome-wide analysis of retroviral DNA integration. Nat. Rev. Microbiol. 2005, 3, 848-858.
• Carter N. P.: Methods and strategies for analyzing copy number variation using DNA microarrays. Nat. Genet. 2007, 39, S16-S21.
• Dalloul R. A., Zimin A. V., Settlage R. E., Kim S., Reed K. M.: Next-generation sequencing strategies for characterizing the turkey genome. Poult. Sci. 2014, 93, 479-484.
• Darris C. E., Tyus J. E., Kelly G., Ropelewski A. J., Nicholas Jr. H. B., Wang X., Nahashon S.: Molecular tools to support metabolic and immune function research in the Guinea Fowl (Numida meleagris). BMC Genomics 2015, 16, 358.
• Feng Y., Zhang Y., Ying C., Wang D., Du C.: Nanopore-based Fourth-generation DNA Sequencing Technology. GBP 2015, 13, 4-16.
• Goodwin S., McPherson J. D., McCombie W. R.: Coming of age: ten years of next-generation sequencing technologies. Nat. Rev. Genet. 2016, 17, 333-351.
• Groenen M. M., Megens H. J., Zare Y., Warren W. C., Hillier L. W., Crooijmans R. P. M., Vereijken A., Okimoto R., Muir W. M., Cheng H. H.: The development and characterization of a 60K SNP chip for chicken. BMC Genomics 12, 274.
• Heather J. M., Chain B.: The sequence of sequencers: The history of sequencing DNA. Genomics 2016, 107, 1-8.
• Hillier L. W., International Chicken Genome Sequencing Consortium: Sequence and comparative analysis of the chicken genome provide uniqueperspectives on vertebrate evolution. Nature 2004, 432, 695-716.
• Hindmarsh P., Leis J.: Retroviral DNA integration. Microbiol. Mol. Biol. Rev. 1999, 63, 836-843.
• Hunt H. D., Jadhao S., Swayne D. E.: Major histocompatibility complex and background genes in chickens influence susceptibility to high pathogenicity avian influenza virus. Avian Dis. 2010, 54, 572-575.
• Kawahara-Miki R., Sano S., Nunome M., Shimmura T., Kuwayama T., Takahashi S., Kawashima T., Matsuda Y., Yoshimura T., Kono T.: Nextgeneration sequencing reveals genomic features in the Japanese quail. Genomics 2013, 101, 345-353.
• Kerstens H. H., Crooijmans R. P., Dibbits B. W., Vereijken A., Okimoto R., Groenen M. A. M.: Structural variation in the chicken genome identified by paired-end next-generation DNA sequencing of reduced representation libraries. BMC Genomics 2011, 12, 94.
• Klemke R. L., Cai S., Giannini A. L., Gallagher P. J., de Lanerolle P., Cheresh D. A.: Regulation of cell motility by mitogen-activated protein kinase. J. Cell Biol. 1997, 137, 481-492.
• Kong H. R., Anthony N. B., Rowland K. C., Khatri B., Kong B. C.: Genome re-sequencing to identify single nucleotide polymorphism markers for muscle color traits in broiler chickens. Asian-Australas. J. Anim. Sci. 2018, 31, 13.
• Monson M. S., Settlage R. E., McMahon K. W., Mendoza K. M., Rawal S., El-Nazami H. S., Coulombe R. A., Reed K. M.: Response of the Hepatic Transcriptome to Aflatoxin B1 in Domestic Turkey (Meleagris gallopavo). PLoS One 2014, 9, e100930.
• Pareek C. S., Smoczynski R., Tretyn A.: Sequencing technologies and genome sequencing. JAG 2011, 52, 413-435.
• Patel R. K., Jain M.: NGS QC Toolkit: A Toolkit for Quality Control of Next Generation Sequencing Data. PLoS One 2012, 7, e30619.
• Ruffier M., Kähäri M., Komorowska M., Keenan S., Laird M., Longden I., Proctor G., Searle S., Staines D., Taylor K., Vullo A., Yates A., Zerbino D., Flicek P.: Ensembl core software resources: storage and programmatic access for DNA sequence and genome annotation. Database (Oxford) 2017, 2017, bax020.
• Sacco M. A., Flannery D. M., Howes K., Venugopal K.: Avian endogenous retrovirus EAV-HP shares regions of identity with avian leukosis virus subgroup J and the avian retrotransposon ART-CH. J. Virol. 2000, 74, 1296-1306.
• Schadt E. E., Turner S., Kasarskis A.: A window into third-generation sequencing. Hum. Mol. Genet. 2010, 19, R227-240.
• Son M. S., Taylor R. K.: Rreparing DNA libraries for multiplexed paired-end deep sequencing for Illumina GA sequencers. Curr. Protoc. Microbiol. 2011, Chapter 1, Unit 1E.4.
• Stoye J. P.: Studies of endogenous retroviruses reveal a continuing evolutionary saga. Nat. Rev. Microbiol. 2012, 10, 395.
• Tuzun E., Sharp A. J., Bailey J. A., Kaul R., Morrison V. A., Pertz L. M., Haugen E., Hayden H., Albertson D., Pinkel D., Olson M. V., Eichler E. E.: Fine-scale structural variation of the human genome. Nat. Genet. 2005, 37, 727-732.
• Wang X., Byers S.: Copy number variation in chickens: a review and future prospects. Microarrays 2014, 3, 24-38.
• Wicker T., Robertson J. S., Schulze S. R., Feltus F. A., Magrini V., Morrison J. A., Mardis E. R., Wilson R. K., Peterson D. G., Paterson A. H., Ivarie R.: The repetitive landscape of the chicken genome. Genome Res. 2005, 15, 126-136.
• Wong G. K. S. and International Chicken Polymorphism Map Consortium: A genetic variation map for chicken with 2.8 million single-nucleotide polymorphisms. Nature 2004, 432, 717-722.
• Wragg D., Mason A. S., Yu L., Kuo R., Lawal R. A., Desta T. T., Mwacharo J. M., Cho C. Y., Kemp S., Burt D. W., Hanotte O.: Genome-wide analysis reveals the extent of EAV-HP integration in domestic chicken. BMC Genomics 2015, 16, 784.
• Yan Y., Yang N., Cheng H. H., Song J., Qu L.: Genome-wide identification of copy number variations between two chicken lines that differ in genetic resistance to Marek’s disease. BMC Genomics 2015, 16, 843.
• Zhang H., Yu J. Q., Yang L. L., Kramer L. M., Zhang X. Y., Na W., Reecy J. M., Li H.: Identification of genome-wide SNP-SNP interactions associated with important traits in chicken. BMC Genomics 2017, 18, 892.
• Zhang Q., Zhu F., Liu L., Zheng C. W., Wang D. H., Hou Z. C., Ning Z. H.: Integrating transcriptome and genome re-sequencing data to identify key genes and mutations affecting chicken eggshell qualities. PLoS One 2015, 10, e0125890.

Identyfikatory

DOI

10.21521/mw.5987