Low-coverage whole-genome sequencing in livestock species for individual traceability and parentage testing

被引:1
|
作者
Casellas, Joaquim [1 ]
de Hijas-Villalba, Melani Martin [1 ]
Vazquez-Gomez, Marta [1 ]
Id-Lahoucine, Samir [2 ]
机构
[1] Univ Autonoma Barcelona, Dept Ciencia Anim & Aliments, Bellaterra 08193, Spain
[2] Scotlands Rural Coll, Anim & Vet Sci Grp, Edinburgh EH9 3JG, Midlothian, Scotland
关键词
Evidential statistics; Paternity; Sequencing; Simulation; Traceability; GENETIC TRACEABILITY; MARKERS; SELECTION; IDENTIFICATION; POLYMORPHISM; ASSOCIATION; ASSIGNMENT; IMPUTATION; GENOTYPE; SINGLE;
D O I
10.1016/j.livsci.2021.104629
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
Procedures for genetic traceability of animal products and parentage testing mainly focus on microsatellites or SNPs panels. Nevertheless, current availability of high-throughput sequencing technologies must be considered as an appealing alternative. This research focused on the evaluation of low-coverage whole-genome sequencing for traceability and paternity testing purposes, within a context of evidential statistics. Analyses were performed on a simulation basis and assumed individuals with 30 100-Mb/100-cM chromosome pairs and similar to 1,000,000 polymorphic SNPs per chromosome. Ten independent populations were simulated under recombination and mutation with effective populations size 100 (generations 1-1000), 10,000 (generation 1001) and 25,000 (generation 1002), and this last generation was retained for analytical purposes. Appropriate both traceability and paternity tests were developed and evaluated on different high-throughput sequencing scenarios accounting for genome coverage depth (0.01x, 0.05x, 0.1x and 0.5x), length of base-pair reads (100, 1000 and 10,000 bp), and sequencing error rate (0%, 1% and 10%). Assuming true sequencing error rates and genotypic frequencies, 0.05x genome coverage depth guaranteed 100% sensitivity and specificity for traceability and paternity tests (n = 1000). Same results were obtained when sequencing error rate was arbitrarily set to 0, or the maximum value assumed during simulation (i.e., 1%). In a similar way, uncertainly about genotypic frecuencies did not impair sensitivity under 0.05x genome coverage, although it reduced specificity for paternity tests up to 85.2%. These results highlighted low-coverage whole-genome sequencing as a promising tool for the livestock and food industry with both technological and (maybe) economic advantages.
引用
收藏
页数:8
相关论文
共 50 条
  • [21] Development of nuclear SSR and chloroplast genome markers in diverse Liriodendron chinense germplasm based on low-coverage whole genome sequencing
    Li, Bin
    Lin, Furong
    Huang, Ping
    Guo, Wenying
    Zheng, Yongqi
    BIOLOGICAL RESEARCH, 2020, 53 (01)
  • [22] Development of SNP Panels from Low-Coverage Whole Genome Sequencing (lcWGS) to Support Indigenous Fisheries for Three Salmonid Species in Northern Canada
    Beemelmanns, Anne
    Bouchard, Raphael
    Michaelides, Sozos
    Normandeau, Eric
    Jeon, Hyung-Bae
    Chamlian, Badrouyk
    Babin, Charles
    Henault, Philippe
    Perrot, Oceane
    Harris, Les N.
    Zhu, Xinhua
    Fraser, Dylan
    Bernatchez, Louis
    Moore, Jean-Sebastien
    MOLECULAR ECOLOGY RESOURCES, 2025, 25 (03)
  • [23] Ultrahigh-Density Linkage Map Construction Using Low-Coverage Whole-Genome Sequencing of a Doubled Haploid Population: Case Study of Torafugu (Takifugu rubripes)
    Zhang, Xiang
    Mizukoshi, Misaki
    Zhang, Hong
    Tan, Engkong
    Igarashi, Yoji
    Suzuki, Yutaka
    Mitsuyama, Susumu
    Kinoshita, Shigeharu
    Saito, Kazuyoshi
    Watabe, Shugo
    Asakawa, Shuichi
    GENES, 2018, 9 (03):
  • [24] Development and evaluation of a haplotype reference panel for low-coverage whole genome sequencing genotype imputation in turbot (Scophthalmus maximus)
    Cao, Junwen
    Huang, Zhihui
    Ma, Aijun
    Jiang, Yuhang
    Zhang, Hao
    Zhang, Rongchao
    Wang, Xinan
    Liu, Zhifeng
    Xu, Rongjing
    AQUACULTURE REPORTS, 2025, 41
  • [25] Identifying risk variants for embryo aneuploidy using ultra-low coverage whole-genome sequencing from preimplantation genetic testing
    Sun, Siqi
    Aboelenain, Mansour
    Ariad, Daniel
    Haywood, Mary E.
    Wageman, Charles R.
    Duke, Marlena
    Bag, Aishee
    Viotti, Manuel
    Katz-Jaffe, Mandy
    McCoy, Rajiv C.
    Schindler, Karen
    Xing, Jinchuan
    AMERICAN JOURNAL OF HUMAN GENETICS, 2023, 110 (12) : 2092 - 2102
  • [26] Improvement of the accuracy of breeding value prediction for egg production traits in Muscovy duck using low-coverage whole-genome sequence data
    Ye, Haoqiang
    Ji, Congliang
    Liu, Xiaoqi
    Bello, Semiu Folaniyi
    Guo, Lijin
    Fang, Xiang
    Lin, Duo
    Mo, Yu
    Lei, Zhilin
    Cai, Bolin
    Nie, Qinghua
    POULTRY SCIENCE, 2025, 104 (02)
  • [27] Whole-genome sequencing and comprehensive variant analysis of a Japanese individual using massively parallel sequencing
    Fujimoto, Akihiro
    Nakagawa, Hidewaki
    Hosono, Naoya
    Nakano, Kaoru
    Abe, Tetsuo
    Boroevich, Keith A.
    Nagasaki, Masao
    Yamaguchi, Rui
    Shibuya, Tetsuo
    Kubo, Michiaki
    Miyano, Satoru
    Nakamura, Yusuke
    Tsunoda, Tatsuhiko
    NATURE GENETICS, 2010, 42 (11) : 931 - U39
  • [28] Selective Whole-Genome Amplification as a Tool to Enrich Specimens with Low Treponema pallidum Genomic DNA Copies for Whole-Genome Sequencing
    Thurlow, Charles M.
    Joseph, Sandeep J.
    Ganova-Raeva, Lilia
    Katz, Samantha S.
    Pereira, Lara
    Chen, Cheng
    Debra, Alyssa
    Vilfort, Kendra
    Workowski, Kimberly
    Cohen, Stephanie E.
    Reno, Hilary
    Sun, Yongcheng
    Burroughs, Mark
    Sheth, Mili
    Chi, Kai-Hua
    Danavall, Damien
    Philip, Susan S.
    Cao, Weiping
    Kersh, Ellen N.
    Pillay, Allan
    MSPHERE, 2022, 7 (03)
  • [29] Extremely low-coverage sequencing and imputation increases power for genome-wide association studies
    Pasaniuc, Bogdan
    Rohland, Nadin
    McLaren, Paul J.
    Garimella, Kiran
    Zaitlen, Noah
    Li, Heng
    Gupta, Namrata
    Neale, Benjamin M.
    Daly, Mark J.
    Sklar, Pamela
    Sullivan, Patrick F.
    Bergen, Sarah
    Moran, Jennifer L.
    Hultman, Christina M.
    Lichtenstein, Paul
    Magnusson, Patrik
    Purcell, Shaun M.
    Haas, David W.
    Liang, Liming
    Sunyaev, Shamil
    Patterson, Nick
    de Bakker, Paul I. W.
    Reich, David
    Price, Alkes L.
    NATURE GENETICS, 2012, 44 (06) : 631 - U41
  • [30] Whole-Genome Sequencing Analysis to Identify Infection with Multiple Species of Nontuberculous Mycobacteria
    Khieu, Visal
    Ananta, Pimjai
    Kaewprasert, Orawee
    Laohaviroj, Marut
    Namwat, Wises
    Faksri, Kiatichai
    PATHOGENS, 2021, 10 (07):