Literature DB >> 33828208

Genomic prediction for growth using a low-density SNP panel in dromedary camels.

Morteza Bitaraf Sani1, Javad Zare Harofte2, Mohammad Hossein Banabazi3, Saeid Esmaeilkhanian4, Ali Shafei Naderi2, Nader Salim5, Abbas Teimoori5, Ahmad Bitaraf2, Mohammad Zadehrahmani6, Pamela Anna Burger7, Vincenzo Landi8, Mohammad Silawi9, Afsaneh Taghipour Sheshdeh9, Mohammad Ali Faghihi9,10.   

Abstract

For thousands of years, camels have produced meat, milk, and fiber in harsh desert conditions. For a sustainable development to provide protein resources from desert areas, it is necessary to pay attention to genetic improvement in camel breeding. By using genotyping-by-sequencing (GBS) method we produced over 14,500 genome wide markers to conduct a genome- wide association study (GWAS) for investigating the birth weight, daily gain, and body weight of 96 dromedaries in the Iranian central desert. A total of 99 SNPs were associated with birth weight, daily gain, and body weight (p-value < 0.002). Genomic breeding values (GEBVs) were estimated with the BGLR package using (i) all 14,522 SNPs and (ii) the 99 SNPs by GWAS. Twenty-eight SNPs were associated with birth weight, daily gain, and body weight (p-value < 0.001). Annotation of the genomic region (s) within ± 100 kb of the associated SNPs facilitated prediction of 36 candidate genes. The accuracy of GEBVs was more than 0.65 based on all 14,522 SNPs, but the regression coefficients for birth weight, daily gain, and body weight were 0.39, 0.20, and 0.23, respectively. Because of low sample size, the GEBVs were predicted using the associated SNPs from GWAS. The accuracy of GEBVs based on the 99 associated SNPs was 0.62, 0.82, and 0.57 for birth weight, daily gain, and body weight. This report is the first GWAS using GBS on dromedary camels and identifies markers associated with growth traits that could help to plan breeding program to genetic improvement. Further researches using larger sample size and collaboration of the camel farmers and more profound understanding will permit verification of the associated SNPs identified in this project. The preliminary results of study show that genomic selection could be the appropriate way to genetic improvement of body weight in dromedary camels, which is challenging due to a long generation interval, seasonal reproduction, and lack of records and pedigrees.

Entities:  

Year:  2021        PMID: 33828208     DOI: 10.1038/s41598-021-87296-7

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  10 in total

Review 1.  The nature, scope and impact of genomic prediction in beef cattle in the United States.

Authors:  Dorian J Garrick
Journal:  Genet Sel Evol       Date:  2011-05-15       Impact factor: 4.297

2.  Best linear unbiased prediction of genomic breeding values using a trait-specific marker-derived relationship matrix.

Authors:  Zhe Zhang; Jianfeng Liu; Xiangdong Ding; Piter Bijma; Dirk-Jan de Koning; Qin Zhang
Journal:  PLoS One       Date:  2010-09-09       Impact factor: 3.240

3.  Prediction of genomic breeding values for growth, carcass and meat quality traits in a multi-breed sheep population using a HD SNP chip.

Authors:  Luiz F Brito; Shannon M Clarke; John C McEwan; Stephen P Miller; Natalie K Pickering; Wendy E Bain; Ken G Dodds; Mehdi Sargolzaei; Flávio S Schenkel
Journal:  BMC Genet       Date:  2017-01-26       Impact factor: 2.797

4.  Genomic Selection for Drought Tolerance Using Genome-Wide SNPs in Maize.

Authors:  Mittal Shikha; Arora Kanika; Atmakuri Ramakrishna Rao; Mallana Gowdra Mallikarjuna; Hari Shanker Gupta; Thirunavukkarasu Nepolean
Journal:  Front Plant Sci       Date:  2017-04-21       Impact factor: 5.753

5.  Genomic predictions for economically important traits in Brazilian Braford and Hereford beef cattle using true and imputed genotypes.

Authors:  Mario L Piccoli; Luiz F Brito; José Braccini; Fernando F Cardoso; Mehdi Sargolzaei; Flávio S Schenkel
Journal:  BMC Genet       Date:  2017-01-18       Impact factor: 2.797

6.  Genome-wide association analysis of egg production performance in chickens across the whole laying period.

Authors:  Zhuang Liu; Ning Yang; Yiyuan Yan; Guangqi Li; Aiqiao Liu; Guiqin Wu; Congjiao Sun
Journal:  BMC Genet       Date:  2019-08-14       Impact factor: 2.797

7.  Genetic architecture of quantitative traits in beef cattle revealed by genome wide association studies of imputed whole genome sequence variants: II: carcass merit traits.

Authors:  Yining Wang; Feng Zhang; Robert Mukiibi; Liuhong Chen; Michael Vinsky; Graham Plastow; John Basarab; Paul Stothard; Changxi Li
Journal:  BMC Genomics       Date:  2020-01-13       Impact factor: 3.969

8.  Deregressing estimated breeding values and weighting information for genomic regression analyses.

Authors:  Dorian J Garrick; Jeremy F Taylor; Rohan L Fernando
Journal:  Genet Sel Evol       Date:  2009-12-31       Impact factor: 4.297

9.  Genome-wide association study of behavioral, physiological and gene expression traits in outbred CFW mice.

Authors:  Clarissa C Parker; Shyam Gopalakrishnan; Peter Carbonetto; Natalia M Gonzales; Emily Leung; Yeonhee J Park; Emmanuel Aryee; Joe Davis; David A Blizard; Cheryl L Ackert-Bicknell; Arimantas Lionikas; Jonathan K Pritchard; Abraham A Palmer
Journal:  Nat Genet       Date:  2016-07-04       Impact factor: 38.330

10.  Multiple association analysis of loci and candidate genes that regulate body size at three growth stages in Simmental beef cattle.

Authors:  Bingxing An; Lei Xu; Jiangwei Xia; Xiaoqiao Wang; Jian Miao; Tianpeng Chang; Meihua Song; Junqing Ni; Lingyang Xu; Lupei Zhang; Junya Li; Huijiang Gao
Journal:  BMC Genet       Date:  2020-03-14       Impact factor: 2.797

  10 in total
  1 in total

1.  Gene-Set Enrichment Analysis for Identifying Genes and Biological Activities Associated with Growth Traits in Dromedaries.

Authors:  Morteza Bitaraf Sani; Zahra Roudbari; Omid Karimi; Mohammad Hossein Banabazi; Saeid Esmaeilkhanian; Nader Asadzadeh; Javad Zare Harofte; Ali Shafei Naderi; Pamela Anna Burger
Journal:  Animals (Basel)       Date:  2022-01-13       Impact factor: 2.752

  1 in total

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