Literature DB >> 29331471

Symposium review: Novel strategies to genetically improve mastitis resistance in dairy cattle.

P Martin1, H W Barkema2, L F Brito3, S G Narayana4, F Miglior5.   

Abstract

Mastitis is a disease of major economic importance to the dairy cattle sector because of the high incidence of clinical mastitis and prevalence of subclinical mastitis and, consequently, the costs associated with treatment, production losses, and reduced animal welfare. Disease-recording systems compiling data from a large number of farms are still not widely implemented around the world; thus, selection for mastitis resistance is often based on genetically correlated indicator traits such as somatic cell count (SCC), udder depth, and fore udder attachment. However, in the past years, several countries have initiated collection systems of clinical mastitis, based on producers recording data in most cases. The large data sets generated have enabled researchers to assess incidence of this disease and to investigate the genetic background of clinical mastitis itself, as well as its relationships with other traits of interest to the dairy industry. The genetic correlations between clinical mastitis and its previous proxies were estimated more accurately and confirmed the strong relationship of clinical mastitis with SCC and udder depth. New traits deriving from SCC were also studied, with the most relevant findings being associated with mean somatic cell score (SCS) in early lactation, standard deviation of SCS, and excessive test-day SCC pattern. Genetic correlations between clinical mastitis and other economically important traits indicated that selection for mastitis resistance would also improve resistance against other diseases and enhance both fertility and longevity. However, milk yield remains negatively correlated with clinical mastitis, emphasizing the importance of including health traits in the breeding objectives to achieve genetic progress for all important traits. These studies enabled the establishment of new genetic and genomic evaluation models, which are more efficient for selection to mastitis resistance. Further studies that are potential keys for future improvement of mastitis resistance are deep investigation of the bacteriology of mastitis, identification of novel indicator traits and tools for selection, and development of a larger female reference population to improve reliability of genomic evaluations. These cutting-edge studies will result in a better understanding of the genetic background of mastitis resistance and enable a more accurate phenotyping and genetic selection to improve mastitis resistance, and consequently, animal welfare and industry profitability.
Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  clinical mastitis; genetics; mastitis; selection index

Mesh:

Year:  2018        PMID: 29331471     DOI: 10.3168/jds.2017-13554

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  19 in total

Review 1.  Improving Genomic Selection for Heat Tolerance in Dairy Cattle: Current Opportunities and Future Directions.

Authors:  Evans K Cheruiyot; Mekonnen Haile-Mariam; Benjamin G Cocks; Jennie E Pryce
Journal:  Front Genet       Date:  2022-06-13       Impact factor: 4.772

2.  A Preliminary Investigation of Social Network Analysis Applied to Dairy Cow Behavior in Automatic Milking System Environments.

Authors:  Liliana Fadul-Pacheco; Michael Liou; Douglas J Reinemann; Victor E Cabrera
Journal:  Animals (Basel)       Date:  2021-04-24       Impact factor: 2.752

Review 3.  Milk somatic cells, factors influencing their release, future prospects, and practical utility in dairy animals: An overview.

Authors:  Mohanned Naif Alhussien; Ajay Kumar Dang
Journal:  Vet World       Date:  2018-05-02

4.  Can We Breed Cattle for Lower Bovine TB Infectivity?

Authors:  Smaragda Tsairidou; Adrian Allen; Georgios Banos; Mike Coffey; Osvaldo Anacleto; Andrew W Byrne; Robin A Skuce; Elizabeth J Glass; John A Woolliams; Andrea B Doeschl-Wilson
Journal:  Front Vet Sci       Date:  2018-12-07

5.  Prevalence of antibiotic resistant mastitis pathogens in dairy cows in Egypt and potential biological control agents produced from plant endophytic actinobacteria.

Authors:  Fuad Ameen; Shorouk A Reda; Sahar A El-Shatoury; Emad M Riad; Mohamed E Enany; Abdullah A Alarfaj
Journal:  Saudi J Biol Sci       Date:  2019-09-14       Impact factor: 4.219

6.  Th17-related mammary immunity, but not a high systemic Th1 immune response is associated with protection against E. coli mastitis.

Authors:  Nathan Cebron; Sarah Maman; Sarah Walachowski; Blandine Gausserès; Patricia Cunha; Pascal Rainard; Gilles Foucras
Journal:  NPJ Vaccines       Date:  2020-11-24       Impact factor: 7.344

Review 7.  A Critical Appraisal of Probiotics for Mastitis Control.

Authors:  Pascal Rainard; Gilles Foucras
Journal:  Front Vet Sci       Date:  2018-10-10

8.  Hepatic Transcriptome Analysis Identifies Divergent Pathogen-Specific Targeting-Strategies to Modulate the Innate Immune System in Response to Intramammary Infection.

Authors:  Annika Heimes; Johanna Brodhagen; Rosemarie Weikard; Hans-Martin Seyfert; Doreen Becker; Marie M Meyerholz; Wolfram Petzl; Holm Zerbe; Martina Hoedemaker; Laura Rohmeier; Hans-Joachim Schuberth; Marion Schmicke; Susanne Engelmann; Christa Kühn
Journal:  Front Immunol       Date:  2020-04-29       Impact factor: 7.561

9.  Characterization of Holstein and Normande whole milk miRNomes highlights breed specificities.

Authors:  S Le Guillou; A Leduc; J Laubier; S Barbey; M-N Rossignol; R Lefebvre; S Marthey; D Laloë; F Le Provost
Journal:  Sci Rep       Date:  2019-12-30       Impact factor: 4.379

10.  Genome-Wide DNA Methylation Analysis of Mammary Gland Tissues From Chinese Holstein Cows With Staphylococcus aureus Induced Mastitis.

Authors:  Mengqi Wang; Yan Liang; Eveline M Ibeagha-Awemu; Mingxun Li; Huimin Zhang; Zhi Chen; Yujia Sun; Niel A Karrow; Zhangping Yang; Yongjiang Mao
Journal:  Front Genet       Date:  2020-10-19       Impact factor: 4.599

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