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Animals
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Genomic Selection for Quantitative Traits in Animals
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Genomic Selection for Quantitative Traits in Animals

A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Animal Genetics and Genomics".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 9989

Special Issue Editor

Dr. Shogo Tsuruta

E-Mail Website
Guest Editor
Department of Animal and Dairy Science, University of Georgia, Athens, GA, USA
Interests: genomic selection; quantitative traits; genetic parameters; breeding values; genomic predictions; genetic gain

Special Issue Information

Since genomic selection started in 2009 in the US for dairy cattle, millions of animals have been genotyped. When genetic evaluation started with BLUP, genetic improvement was accelerated as accuracy in EBV increased. Now in the genomic era, because of the capacity to utilize SNP marker information as genotypes, more efficient genomic selection became possible. The genetic gain will increase significantly more, as accuracy in genomic EBV is higher using genomic relationships among animals, selection intensity is larger with more genotyped animals, and the generation interval is reduced by genotyping at younger age. In the future, genotyping embryos for many generations in a short period of time using germ cells from embryonic stem cells before having phenotypes will be possible. As a result, the genetic gain will be enormous. Genomic selection has such huge potential. Studies on genomic selection for quantitative traits will be more exciting and important than ever. Any research on genomic selection including theory, practical application, and biological aspects will be welcomed.

Dr. Shogo Tsuruta
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Animals is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Genomic selection
  • quantitative traits
  • genetic parameters
  • breeding values
  • genomic predictions
  • genetic gain

Published Papers (3 papers)

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Research

16 pages, 1930 KiB  
Article
Weighted Single-Step Genomic Best Linear Unbiased Prediction Method Application for Assessing Pigs on Meat Productivity and Reproduction Traits
by Artem Kabanov, Ekaterina Melnikova, Sergey Nikitin, Maria Somova, Oleg Fomenko, Valeria Volkova, Olga Kostyunina, Tatiana Karpushkina, Elena Martynova and Elena Trebunskikh
Animals 2022, 12(13), 1693; https://doi.org/10.3390/ani12131693 - 30 Jun 2022
Cited by 2 | Viewed by 1665
Abstract
Changes in the accuracy of the genomic estimates obtained by the ssGBLUP and wssGBLUP methods were evaluated using different reference groups. The weighting procedure’s reasonableness of application Pwas considered to improve the accuracy of genomic predictions for meat, fattening and reproduction traits in [...] Read more.
Changes in the accuracy of the genomic estimates obtained by the ssGBLUP and wssGBLUP methods were evaluated using different reference groups. The weighting procedure’s reasonableness of application Pwas considered to improve the accuracy of genomic predictions for meat, fattening and reproduction traits in pigs. Six reference groups were formed to assess the genomic data quantity impact on the accuracy of predicted values (groups of genotyped animals). The datasets included 62,927 records of meat and fattening productivity (fat thickness over 6–7 ribs (BF1, mm)), muscle depth (MD, mm) and precocity up to 100 kg (age, days) and 16,070 observations of reproductive qualities (the number of all born piglets (TNB) and the number of live-born piglets (NBA), according to the results of the first farrowing). The wssGBLUP method has an advantage over ssGBLUP in terms of estimation reliability. When using a small reference group, the difference in the accuracy of ssGBLUP over BLUP AM is from −1.9 to +7.3 percent points, while for wssGBLUP, the change in accuracy varies from +18.2 to +87.3 percent points. Furthermore, the superiority of the wssGBLUP is also maintained for the largest group of genotyped animals: from +4.7 to +15.9 percent points for ssGBLUP and from +21.1 to +90.5 percent points for wssGBLUP. However, for all analyzed traits, the number of markers explaining 5% of genetic variability varied from 71 to 108, and the number of such SNPs varied depending on the size of the reference group (79–88 for BF1, 72–81 for MD, 71–108 for age). The results of the genetic variation distribution have the greatest similarity between groups of about 1000 and about 1500 individuals. Thus, the size of the reference group of more than 1000 individuals gives more stable results for the estimation based on the wssGBLUP method, while using the reference group of 500 individuals can lead to distorted results of GEBV. Full article
(This article belongs to the Special Issue Genomic Selection for Quantitative Traits in Animals)
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16 pages, 2570 KiB  
Article
Genetic Parameters of Somatic Cell Score in Florida Goats Using Single and Multiple Traits Models
by Rocío Jimenez-Granado, Antonio Molina, Chiraz Ziadi, Manuel Sanchez, Eva Muñoz-Mejías, Sebastián Demyda-Peyrás and Alberto Menendez-Buxadera
Animals 2022, 12(8), 1009; https://doi.org/10.3390/ani12081009 - 13 Apr 2022
Cited by 8 | Viewed by 1746
Abstract
A total of 1,031,143 records of daily dairy control test of Spanish Florida goats were used for this study. The database was edited, and only the records of the first three lactations were kept. The final database contained 340,654 daily-test somatic cell counts [...] Read more.
A total of 1,031,143 records of daily dairy control test of Spanish Florida goats were used for this study. The database was edited, and only the records of the first three lactations were kept. The final database contained 340,654 daily-test somatic cell counts from 27,749 daughters of 941 males and 16,243 goats. The evolution of this count in the last 14 years was analyzed following French and American international associations’ criteria for the risk of mastitis in goats, and confirmed the slight increase in SCS in the last years and the importance of this problem (50% of dairy control tests show a risk of suffering mastitis). For the genetic analysis, the SCS records were log-transformed to normalize this variable. Two strategies were used for the genetic analysis: a univariate animal model for the SCS assuming that SCS does not vary throughout the parities, and a multi-character animal model, where SCS is not considered as the same character in the different parities. The heritabilities (h2) were higher in the multiple traits models, showings an upward trend from the first to the third parity (h2 between 0.245 to 0.365). The genetic correlations of the same trait, as well as between breeding values (GVs) between different parities, were different from unity. The breeding values (EBVs) obtained for both models were subjected to a PCA: the first eigenvector (λ1) explained most of the variations (between 74% to 90%), while the second λ2 accounted for between 9% to 20% of the variance, which shows that the selection will be proportionally favorable but not equivalent in all parities and that there are some variations in the type of response. Full article
(This article belongs to the Special Issue Genomic Selection for Quantitative Traits in Animals)
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14 pages, 503 KiB  
Article
Application of Genomic Data for Reliability Improvement of Pig Breeding Value Estimates
by Ekaterina Melnikova, Artem Kabanov, Sergey Nikitin, Maria Somova, Sergey Kharitonov, Petr Otradnov, Olga Kostyunina, Tatiana Karpushkina, Elena Martynova, Aleksander Sermyagin and Natalia Zinovieva
Animals 2021, 11(6), 1557; https://doi.org/10.3390/ani11061557 - 27 May 2021
Cited by 5 | Viewed by 4556
Abstract
Replacement pigs’ genomic prediction for reproduction (total number and born alive piglets in the first parity), meat, fatness and growth traits (muscle depth, days to 100 kg and backfat thickness over 6–7 rib) was tested using single-step genomic best linear unbiased prediction ssGBLUP [...] Read more.
Replacement pigs’ genomic prediction for reproduction (total number and born alive piglets in the first parity), meat, fatness and growth traits (muscle depth, days to 100 kg and backfat thickness over 6–7 rib) was tested using single-step genomic best linear unbiased prediction ssGBLUP methodology. These traits were selected as the most economically significant and different in terms of heritability. The heritability for meat, fatness and growth traits varied from 0.17 to 0.39 and for reproduction traits from 0.12 to 0.14. We confirm from our data that ssGBLUP is the most appropriate method of genomic evaluation. The validation of genomic predictions was performed by calculating the correlation between preliminary GEBV (based on pedigree and genomic data only) with high reliable conventional estimates (EBV) (based on pedigree, own phenotype and offspring records) of validating animals. Validation datasets include 151 and 110 individuals for reproduction, meat and fattening traits, respectively. The level of correlation (r) between EBV and GEBV scores varied from +0.44 to +0.55 for meat and fatness traits, and from +0.75 to +0.77 for reproduction traits. Average breeding value (EBV) of group selected on genomic evaluation basis exceeded the group selected on parental average estimates by 22, 24 and 66% for muscle depth, days to 100 kg and backfat thickness over 6–7 rib, respectively. Prediction based on SNP markers data and parental estimates showed a significant increase in the reliability of low heritable reproduction traits (about 40%), which is equivalent to including information about 10 additional descendants for sows and 20 additional descendants for boars in the evaluation dataset. Full article
(This article belongs to the Special Issue Genomic Selection for Quantitative Traits in Animals)
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