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
  • [31] Single-molecule DNA-mapping and whole-genome sequencing of individual cells
    Marie, Rodolphe
    Pedersen, Jonas N.
    Baerlocher, Loic
    Koprowska, Kamila
    Podenphant, Marie
    Sabatel, Celine
    Zalkovskij, Maksim
    Mironov, Andrej
    Bilenberg, Brian
    Ashley, Neil
    Flyvbjerg, Henrik
    Bodmer, Walter F.
    Kristensen, Anders
    Mir, Kalim U.
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2018, 115 (44) : 11192 - 11197
  • [32] High-throughput and cost-effective genotyping by low-coverage whole genome sequencing with genotype imputation in Pacific oyster, Crassostrea gigas
    Yang, Ben
    Li, Yongjing
    Li, Qi
    Liu, Shikai
    AQUACULTURE, 2024, 591
  • [33] A comparison of methods for whole-genome QTL mapping using dense markers in four livestock species
    Legarra, Andres
    Croiseau, Pascal
    Sanchez, Marie Pierre
    Teyssedre, Simon
    Salle, Guillaume
    Allais, Sophie
    Fritz, Sebastien
    Moreno, Carole Renee
    Ricard, Anne
    Elsen, Jean-Michel
    GENETICS SELECTION EVOLUTION, 2015, 47
  • [34] Evaluation of tools for identifying large copy number variations from ultra-low-coverage whole-genome sequencing data
    Smolander, Johannes
    Khan, Sofia
    Singaravelu, Kalaimathy
    Kauko, Leni
    Lund, Riikka J.
    Laiho, Asta
    Elo, Laura L.
    BMC GENOMICS, 2021, 22 (01)
  • [35] Preliminary Genomic Characterization of Ten Hardwood Tree Species from Multiplexed Low Coverage Whole Genome Sequencing
    Staton, Margaret
    Best, Teodora
    Khodwekar, Sudhir
    Owusu, Sandra
    Xu, Tao
    Xu, Yi
    Jennings, Tara
    Cronn, Richard
    Arumuganathan, A. Kathiravetpilla
    Coggeshall, Mark
    Gailing, Oliver
    Liang, Haiying
    Romero-Severson, Jeanne
    Schlarbaum, Scott
    Carlson, John E.
    PLOS ONE, 2015, 10 (12):
  • [36] Identification of RP1 as the genetic cause of retinitis pigmentosa in a multi-generational pedigree using Extremely Low-Coverage Whole Genome Sequencing (XLC-WGS)
    Lazaro-Guevara, Jose M.
    Flores-Robles, Bryan-Josue
    Garrido-Lopez, Karen M.
    McKeown, Ryan J.
    Flores-Moran, Adriana E.
    Labrador-Sanchez, Eztizen
    Pinillos-Aransay, Valvanera
    Trasahedo, Estibaliz A.
    Lopez-Martin, Juan-Antonio
    Reyna Soberanis, Laura Sofia
    Yee Melgar, Mariano
    Luis Tellez-Arreola, Jose
    Thebault, Stephanie C.
    GENE, 2023, 851
  • [37] Whole-Genome Shotgun Sequencing of Two β-Proteobacterial Species in Search of the Bulgecin Biosynthetic Cluster
    Horsman, Mark E.
    Marous, Daniel R.
    Li, Rongfeng
    Oliver, Ryan A.
    Byun, Byungjin
    Emrich, Scott J.
    Boggess, Bill
    Townsend, Craig A.
    Mobashery, Shahriar
    ACS CHEMICAL BIOLOGY, 2017, 12 (10) : 2552 - 2557
  • [38] Whole-Genome Sequencing for Tracing the Genetic Diversity of Brucella abortus and Brucella melitensis Isolated from Livestock in Egypt
    Khan, Aman Ullah
    Melzer, Falk
    Sayour, Ashraf E.
    Shell, Waleed S.
    Linde, Joerg
    Abdel-Glil, Mostafa
    El-Soally, Sherif A. G. E.
    Elschner, Mandy C.
    Sayour, Hossam E. M.
    Ramadan, Eman Shawkat
    Mohamed, Shereen Aziz
    Hendam, Ashraf
    Ismail, Rania I.
    Farahat, Lubna F.
    Roesler, Uwe
    Neubauer, Heinrich
    El-Adawy, Hosny
    PATHOGENS, 2021, 10 (06):
  • [39] Whole-genome sequencing for genetic diversity analysis of Iranian Brucella spp. isolated from humans and livestock
    Dadar, Maryam
    Brangsch, Hanka
    Alamian, Saeed
    Neubauer, Heinrich
    Wareth, Gamal
    ONE HEALTH, 2023, 16
  • [40] Moment estimators of relatedness from low-depth whole-genome sequencing data
    Herzig, Anthony F.
    Ciullo, M.
    Consortium, FranceGenRef
    Leutenegger, A-L
    Perdry, H.
    BMC BIOINFORMATICS, 2022, 23 (01)