1
|
Lewerentz F, Vanhala TK, Johansen LB, Paulsson M, Glantz M, de Koning DJ. Re-sequencing of the casein genes in Swedish Red cattle giving milk with diverse protein profiles and extreme rennet coagulation properties. JDS COMMUNICATIONS 2024; 5:299-304. [PMID: 39220839 PMCID: PMC11365307 DOI: 10.3168/jdsc.2023-0412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 01/10/2024] [Indexed: 09/04/2024]
Abstract
Impaired rennet coagulation properties in milk could lead to prolonged processing times and production losses. Heritability for milk coagulation has previously been estimated to be 0.28 to 0.45, indicating that genetic selection can be used to manipulate this trait. The CN proteins are expressed by the genes CSN1S1, CSN2, CSN1S2, and CSN3 and are located on bovine chromosome 6. To better understand the effect of genetic variation in the CN genes on milk coagulation, blood and milk samples from 30 Swedish Red Dairy Cattle (RDC) with divergent coagulation properties were investigated. DNA from the 30 cows was sequenced for the CN genes to determine the theoretical AA sequence and to look for genetic variation in the untranslated regions. The aim is to confirm the protein genetic variants previously reported, while searching for additional genetic variation in the CN genes of 30 RDC. We observed genetic variation in 116 SNPs in the known CN genes where 10% of the SNPs are exon variants and the remaining 90% are intron variants. A total of 2.5% of the SNPs are found in the 5'- or 3'-untranslated region (UTR) regions of the exons; 2% are synonymous variants and 6% are missense variants that concurred with the known protein variants for CSN1S1, CSN2, and CSN3. Furthermore, 6% of the SNPs are splice polypyrimidine tract intron variants. The 2 genetic variants in the 5'- and 3'-UTR in CSN1S1 and CSN3 are found with protein variants CSN1S1C and CSN3B. Because both UTR variants are associated with gain and loss of micro RNA and transcription factors, this could explain differences in expression of the genetic protein variants. Preliminary chi-squared analysis and comparison with previous GWAS studies showed potential connections between the identified SNPs and coagulation properties of milk. By advancing the knowledge of the connection between the DNA sequence and the functional properties of the CN proteins, we hope to learn more about the cheese coagulation properties of milk from RDC.
Collapse
Affiliation(s)
- Frida Lewerentz
- Department of Process and Life Science Engineering, Division of Food and Pharma, Lund University, SE-221 00 Lund, Sweden
| | - Tytti K. Vanhala
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, SE-750 07 Uppsala, Sweden
| | | | - Marie Paulsson
- Department of Process and Life Science Engineering, Division of Food and Pharma, Lund University, SE-221 00 Lund, Sweden
| | - Maria Glantz
- Department of Process and Life Science Engineering, Division of Food and Pharma, Lund University, SE-221 00 Lund, Sweden
| | - Dirk-Jan de Koning
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, SE-750 07 Uppsala, Sweden
| |
Collapse
|
2
|
de Oliveira LF, Veroneze R, Sousa KRS, Mulim HA, Araujo AC, Huang Y, Johnson JS, Brito LF. Genomic regions, candidate genes, and pleiotropic variants associated with physiological and anatomical indicators of heat stress response in lactating sows. BMC Genomics 2024; 25:467. [PMID: 38741036 DOI: 10.1186/s12864-024-10365-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 04/29/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Heat stress (HS) poses significant threats to the sustainability of livestock production. Genetically improving heat tolerance could enhance animal welfare and minimize production losses during HS events. Measuring phenotypic indicators of HS response and understanding their genetic background are crucial steps to optimize breeding schemes for improved climatic resilience. The identification of genomic regions and candidate genes influencing the traits of interest, including variants with pleiotropic effects, enables the refinement of genotyping panels used to perform genomic prediction of breeding values and contributes to unraveling the biological mechanisms influencing heat stress response. Therefore, the main objectives of this study were to identify genomic regions, candidate genes, and potential pleiotropic variants significantly associated with indicators of HS response in lactating sows using imputed whole-genome sequence (WGS) data. Phenotypic records for 18 traits and genomic information from 1,645 lactating sows were available for the study. The genotypes from the PorcineSNP50K panel containing 50,703 single nucleotide polymorphisms (SNPs) were imputed to WGS and after quality control, 1,622 animals and 7,065,922 SNPs were included in the analyses. RESULTS A total of 1,388 unique SNPs located on sixteen chromosomes were found to be associated with 11 traits. Twenty gene ontology terms and 11 biological pathways were shown to be associated with variability in ear skin temperature, shoulder skin temperature, rump skin temperature, tail skin temperature, respiration rate, panting score, vaginal temperature automatically measured every 10 min, vaginal temperature measured at 0800 h, hair density score, body condition score, and ear area. Seven, five, six, two, seven, 15, and 14 genes with potential pleiotropic effects were identified for indicators of skin temperature, vaginal temperature, animal temperature, respiration rate, thermoregulatory traits, anatomical traits, and all traits, respectively. CONCLUSIONS Physiological and anatomical indicators of HS response in lactating sows are heritable but highly polygenic. The candidate genes found are associated with important gene ontology terms and biological pathways related to heat shock protein activities, immune response, and cellular oxidative stress. Many of the candidate genes with pleiotropic effects are involved in catalytic activities to reduce cell damage from oxidative stress and cellular mechanisms related to immune response.
Collapse
Affiliation(s)
- Letícia Fernanda de Oliveira
- Department of Animal Science, Federal University of Viçosa, Viçosa, MG, Brazil
- Department of Animal Sciences, Purdue University, West Lafayette, IN, USA
| | - Renata Veroneze
- Department of Animal Science, Federal University of Viçosa, Viçosa, MG, Brazil
| | - Katiene Régia Silva Sousa
- Department of Animal Sciences, Purdue University, West Lafayette, IN, USA
- Department of Oceanography and Limnology, Federal University of Maranhão, São Luís, MA, Brazil
| | - Henrique A Mulim
- Department of Animal Sciences, Purdue University, West Lafayette, IN, USA
| | | | | | - Jay S Johnson
- USDA-ARS Livestock Behavior Research Unit, West Lafayette, IN, USA
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN, USA.
| |
Collapse
|
3
|
Somenzi E, Partel E, Barbato M, Chero Osorio AM, Colli L, Franceschi N, Mantovani R, Pilla F, Komjanc M, Achilli A, Hauffe HC, Ajmone Marsan P. Genetic legacy and adaptive signatures: investigating the history, diversity, and selection signatures in Rendena cattle resilient to eighteenth century rinderpest epidemics. Genet Sel Evol 2024; 56:32. [PMID: 38698323 PMCID: PMC11064358 DOI: 10.1186/s12711-024-00900-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 04/05/2024] [Indexed: 05/05/2024] Open
Abstract
BACKGROUND Rendena is a dual-purpose cattle breed, which is primarily found in the Italian Alps and the eastern areas of the Po valley, and recognized for its longevity, fertility, disease resistance and adaptability to steep Alpine pastures. It is categorized as 'vulnerable to extinction' with only 6057 registered animals in 2022, yet no comprehensive analyses of its molecular diversity have been performed to date. The aim of this study was to analyse the origin, genetic diversity, and genomic signatures of selection in Rendena cattle using data from samples collected in 2000 and 2018, and shed light on the breed's evolution and conservation needs. RESULTS Genetic analysis revealed that the Rendena breed shares genetic components with various Alpine and Po valley breeds, with a marked genetic proximity to the Original Braunvieh breed, reflecting historical restocking efforts across the region. The breed shows signatures of selection related to both milk and meat production, environmental adaptation and immune response, the latter being possibly the result of multiple rinderpest epidemics that swept across the Alps in the eighteenth century. An analysis of the Rendena cattle population spanning 18 years showed an increase in the mean level of inbreeding over time, which is confirmed by the mean number of runs of homozygosity per individual, which was larger in the 2018 sample. CONCLUSIONS The Rendena breed, while sharing a common origin with Brown Swiss, has developed distinct traits that enable it to thrive in the Alpine environment and make it highly valued by local farmers. Preserving these adaptive features is essential, not only for maintaining genetic diversity and enhancing the ability of this traditional animal husbandry to adapt to changing environments, but also for guaranteeing the resilience and sustainability of both this livestock system and the livelihoods within the Rendena valley.
Collapse
Affiliation(s)
- Elisa Somenzi
- DIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del Sacro Cuore, Piacenza, Italy.
| | - Erika Partel
- Unità risorse foraggere e produzioni zootecniche, Centro Trasferimento Tecnologico, Fondazione Edmund Mach, S. Michele all'Adige, Trento, Italy
| | - Mario Barbato
- DIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del Sacro Cuore, Piacenza, Italy
- Department of Veterinary Science, Università degli Studi di Messina, Messina, Italy
| | - Ana María Chero Osorio
- Dipartimento di Biologia e Biotecnologie "L. Spallanzani", University of Pavia, Pavia, Italy
| | - Licia Colli
- DIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del Sacro Cuore, Piacenza, Italy
- Centro di Ricerca Sulla Biodiversità e sul DNA Antico, BioDNA, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | - Niccolò Franceschi
- DIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | - Roberto Mantovani
- Department of Agronomy, Food, Natural Resources, Animals, and Environment, University of Padua, Padua, Italy
| | - Fabio Pilla
- Department of Agriculture Environment and Food Science, University of Molise, Campobasso, Italy
| | - Matteo Komjanc
- Unità risorse foraggere e produzioni zootecniche, Centro Trasferimento Tecnologico, Fondazione Edmund Mach, S. Michele all'Adige, Trento, Italy
| | - Alessandro Achilli
- Dipartimento di Biologia e Biotecnologie "L. Spallanzani", University of Pavia, Pavia, Italy
| | - Heidi Christine Hauffe
- Conservation Genomics Research Unit, Research and Innovation Centre, Fondazione Edmund Mach, S. Michele all'Adige, Trento, Italy
| | - Paolo Ajmone Marsan
- DIANA Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Università Cattolica del Sacro Cuore, Piacenza, Italy
- Centro di Ricerca Nutrigenomica e Proteomica-PRONUTRIGEN, Università Cattolica del Sacro Cuore, Piacenza, Italy
| |
Collapse
|
4
|
Atashi H, Chen Y, Vanderick S, Hubin X, Gengler N. Single-step genome-wide association analyses for milk urea concentration in Walloon Holstein cows. J Dairy Sci 2024; 107:3020-3031. [PMID: 38056570 DOI: 10.3168/jds.2023-23902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 11/07/2023] [Indexed: 12/08/2023]
Abstract
The aims of this study were to conduct a single-step genome-wide association to identify genomic regions associated with milk urea (MU) and to estimate genetic correlations between MU and milk yield (MY), milk composition (calcium content [CC], fat percentage [FP], protein percentage [PP], and casein percentage [CNP]), and cheese-making properties (CMP; coagulation time [CT], curd firmness after 30 min from rennet addition [a30], and titratable acidity [TA]). The used data have been collected from 2015 to 2020 on 78,073 first-parity (485,218 test-day records) and 48,766 second-parity (284,942 test-day records) Holstein cows distributed in 671 herds in the Walloon Region of Belgium. Data of 565,533 SNP located on 29 BTA of 6,617 animals (1,712 males) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of ∼216 kb) was calculated, and the top-3 genomic regions explaining the largest rate of the genetic variance were considered promising regions and used to identify potential candidate genes. Mean (SD) MU was 25.38 (8.02) mg/dL and 25.03 (8.06) mg/dL in the first and second lactation, respectively. Mean heritability estimates for daily MU were 0.21 and 0.23 for the first and second lactation, respectively. The genetic correlations estimated between MU and MY, milk composition, and CMP were quite low (ranged from -0.10 [CC] to 0.10 [TA] and -0.05 [CT] to 0.13 [TA] for the first and second lactations, respectively). The top-3 regions associated with MU were located from 80.61 to 80.74 Mb on BTA6, 103.26 to 103.41 Mb on BTA11, and 1.59 to 2.15 Mb on BTA14. Genes including KCNT1, MROH1, SHARPIN, TSSK5, CPSF1, HSF1, TONSL, DGAT1, SCX, and MAF1 were identified as positional candidate genes for MU. The findings of this study can be used for a better understanding of the genomic architecture underlying MU in Holstein cattle.
Collapse
Affiliation(s)
- H Atashi
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium; Department of Animal Science, Shiraz University, 71441-13131 Shiraz, Iran.
| | - Y Chen
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - S Vanderick
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - X Hubin
- Elevéo asbl Awé Group, 5590 Ciney, Belgium
| | - N Gengler
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| |
Collapse
|
5
|
Lopdell TJ, Trevarton AJ, Moody J, Prowse-Wilkins C, Knowles S, Tiplady K, Chamberlain AJ, Goddard ME, Spelman RJ, Lehnert K, Snell RG, Davis SR, Littlejohn MD. A common regulatory haplotype doubles lactoferrin concentration in milk. Genet Sel Evol 2024; 56:22. [PMID: 38549172 PMCID: PMC11234695 DOI: 10.1186/s12711-024-00890-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 03/12/2024] [Indexed: 04/02/2024] Open
Abstract
BACKGROUND Bovine lactoferrin (Lf) is an iron absorbing whey protein with antibacterial, antiviral, and antifungal activity. Lactoferrin is economically valuable and has an extremely variable concentration in milk, partly driven by environmental influences such as milking frequency, involution, or mastitis. A significant genetic influence has also been previously observed to regulate lactoferrin content in milk. Here, we conducted genetic mapping of lactoferrin protein concentration in conjunction with RNA-seq, ChIP-seq, and ATAC-seq data to pinpoint candidate causative variants that regulate lactoferrin concentrations in milk. RESULTS We identified a highly-significant lactoferrin protein quantitative trait locus (pQTL), as well as a cis lactotransferrin (LTF) expression QTL (cis-eQTL) mapping to the LTF locus. Using ChIP-seq and ATAC-seq datasets representing lactating mammary tissue samples, we also report a number of regions where the openness of chromatin is under genetic influence. Several of these also show highly significant QTL with genetic signatures similar to those highlighted through pQTL and eQTL analysis. By performing correlation analysis between these QTL, we revealed an ATAC-seq peak in the putative promotor region of LTF, that highlights a set of 115 high-frequency variants that are potentially responsible for these effects. One of the 115 variants (rs110000337), which maps within the ATAC-seq peak, was predicted to alter binding sites of transcription factors known to be involved in lactation-related pathways. CONCLUSIONS Here, we report a regulatory haplotype of 115 variants with conspicuously large impacts on milk lactoferrin concentration. These findings could enable the selection of animals for high-producing specialist herds.
Collapse
Affiliation(s)
- Thomas J Lopdell
- Research & Development, Livestock Improvement Corporation, Ruakura Road, Hamilton, New Zealand.
| | - Alexander J Trevarton
- School of Biological Sciences, University of Auckland, Private Bag 92019, Auckland, New Zealand
| | - Janelle Moody
- School of Biological Sciences, University of Auckland, Private Bag 92019, Auckland, New Zealand
| | - Claire Prowse-Wilkins
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, Australia
- Faculty of Veterinarian and Agricultural Science, The University of Melbourne, Parkville, VIC, Australia
| | - Sarah Knowles
- Auckland War Memorial Museum, Victoria Street West, Auckland, New Zealand
| | - Kathryn Tiplady
- Research & Development, Livestock Improvement Corporation, Ruakura Road, Hamilton, New Zealand
| | - Amanda J Chamberlain
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, Australia
| | - Michael E Goddard
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, Australia
- Faculty of Veterinarian and Agricultural Science, The University of Melbourne, Parkville, VIC, Australia
| | - Richard J Spelman
- Research & Development, Livestock Improvement Corporation, Ruakura Road, Hamilton, New Zealand
| | - Klaus Lehnert
- School of Biological Sciences, University of Auckland, Private Bag 92019, Auckland, New Zealand
| | - Russell G Snell
- School of Biological Sciences, University of Auckland, Private Bag 92019, Auckland, New Zealand
| | - Stephen R Davis
- Research & Development, Livestock Improvement Corporation, Ruakura Road, Hamilton, New Zealand
| | - Mathew D Littlejohn
- Research & Development, Livestock Improvement Corporation, Ruakura Road, Hamilton, New Zealand
- AL Rae Centre for Genetics and Breeding, Massey University, Palmerston North, New Zealand
| |
Collapse
|
6
|
Leonard AS, Mapel XM, Pausch H. Pangenome-genotyped structural variation improves molecular phenotype mapping in cattle. Genome Res 2024; 34:300-309. [PMID: 38355307 PMCID: PMC10984387 DOI: 10.1101/gr.278267.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 02/01/2024] [Indexed: 02/16/2024]
Abstract
Expression and splicing quantitative trait loci (e/sQTL) are large contributors to phenotypic variability. Achieving sufficient statistical power for e/sQTL mapping requires large cohorts with both genotypes and molecular phenotypes, and so, the genomic variation is often called from short-read alignments, which are unable to comprehensively resolve structural variation. Here we build a pangenome from 16 HiFi haplotype-resolved cattle assemblies to identify small and structural variation and genotype them with PanGenie in 307 short-read samples. We find high (>90%) concordance of PanGenie-genotyped and DeepVariant-called small variation and confidently genotype close to 21 million small and 43,000 structural variants in the larger population. We validate 85% of these structural variants (with MAF > 0.1) directly with a subset of 25 short-read samples that also have medium coverage HiFi reads. We then conduct e/sQTL mapping with this comprehensive variant set in a subset of 117 cattle that have testis transcriptome data, and find 92 structural variants as causal candidates for eQTL and 73 for sQTL. We find that roughly half of the top associated structural variants affecting expression or splicing are transposable elements, such as SV-eQTL for STN1 and MYH7 and SV-sQTL for CEP89 and ASAH2 Extensive linkage disequilibrium between small and structural variation results in only 28 additional eQTL and 17 sQTL discovered when including SVs, although many top associated SVs are compelling candidates.
Collapse
Affiliation(s)
| | - Xena M Mapel
- Animal Genomics, ETH Zurich, 8092 Zurich, Switzerland
| | - Hubert Pausch
- Animal Genomics, ETH Zurich, 8092 Zurich, Switzerland
| |
Collapse
|
7
|
Liu Y, Zhang Y, Zhou F, Yao Z, Zhan Y, Fan Z, Meng X, Zhang Z, Liu L, Yang J, Wu Z, Cai G, Zheng E. Increased Accuracy of Genomic Prediction Using Preselected SNPs from GWAS with Imputed Whole-Genome Sequence Data in Pigs. Animals (Basel) 2023; 13:3871. [PMID: 38136908 PMCID: PMC10740755 DOI: 10.3390/ani13243871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 12/13/2023] [Accepted: 12/14/2023] [Indexed: 12/24/2023] Open
Abstract
Enhancing the accuracy of genomic prediction is a key goal in genomic selection (GS) research. Integrating prior biological information into GS methods using appropriate models can improve prediction accuracy for complex traits. Genome-wide association study (GWAS) is widely utilized to identify potential candidate loci associated with complex traits in livestock and poultry, offering essential genomic insights. In this study, a GWAS was conducted on 685 Duroc × Landrace × Yorkshire (DLY) pigs to extract significant single-nucleotide polymorphisms (SNPs) as genomic features. We compared two GS models, genomic best linear unbiased prediction (GBLUP) and genomic feature BLUP (GFBLUP), by using imputed whole-genome sequencing (WGS) data on 651 Yorkshire pigs. The results revealed that the GBLUP model achieved prediction accuracies of 0.499 for backfat thickness (BFT) and 0.423 for loin muscle area (LMA). By applying the GFBLUP model with GWAS-based SNP preselection, the average prediction accuracies for BFT and LMA traits reached 0.491 and 0.440, respectively. Specifically, the GFBLUP model displayed a 4.8% enhancement in predicting LMA compared to the GBLUP model. These findings suggest that, in certain scenarios, the GFBLUP model may offer superior genomic prediction accuracy when compared to the GBLUP model, underscoring the potential value of incorporating genomic features to refine GS models.
Collapse
Affiliation(s)
- Yiyi Liu
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Yuling Zhang
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Fuchen Zhou
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Zekai Yao
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Yuexin Zhan
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Zhenfei Fan
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Xianglun Meng
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Zebin Zhang
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Langqing Liu
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Jie Yang
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| | - Zhenfang Wu
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
- Guangdong Zhongxin Breeding Technology Co., Ltd., Guangzhou 510642, China
| | - Gengyuan Cai
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
- Guangdong Zhongxin Breeding Technology Co., Ltd., Guangzhou 510642, China
| | - Enqin Zheng
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.L.); (Y.Z.); (F.Z.); (Z.Y.); (Y.Z.); (Z.F.); (X.M.); (Z.Z.); (L.L.); (J.Y.); (Z.W.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510642, China
| |
Collapse
|
8
|
Ma Z, Chang Y, Brito LF, Li Y, Yang T, Wang Y, Yang N. Multitrait meta-analyses identify potential candidate genes for growth-related traits in Holstein heifers. J Dairy Sci 2023; 106:9055-9070. [PMID: 37641329 DOI: 10.3168/jds.2023-23462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 06/20/2023] [Indexed: 08/31/2023]
Abstract
Understanding the underlying pleiotropic relationships among growth and body size traits is important for refining breeding strategies in dairy cattle for optimal body size and growth rate. Therefore, we performed single-trait GWAS for monthly-recorded body weight (BW), hip height, body length, and chest girth from birth to 12 mo of age in Holstein animals, followed by stepwise multiple regression of independent or lowly-linked markers from GWAS loci using conditional and joint association analyses (COJO). Subsequently, we conducted a multitrait meta-analysis to detect pleiotropic markers. Based on the single-trait GWAS, we identified 170 significant SNPs, in which 59 of them remained significant after the COJO analyses. The most significant SNP, located at BTA7:3,676,741, explained 2.93% of the total phenotypic variance for BW6 (BW at 6 mo of age). We identified 17 SNPs with potential pleiotropic effects based on the multitrait meta-analyses, which resulted in 3 additional SNPs in comparison to those detected based on the single-trait GWAS. The identified quantitative trait loci regions overlap with genes known to influence human growth-related traits. According to positional and functional analyses, we proposed HMGA2, HNF4G, MED13L, BHLHE40, FRZB, DMP1, TRIB3, and GATAD2A as important candidate genes influencing the studied traits. The combination of single-trait GWAS and meta-analyses of GWAS results improved the efficiency of detecting associated SNPs, and provided new insights into the genetic mechanisms of growth and development in Holstein cattle.
Collapse
Affiliation(s)
- Z Ma
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China; Beijing Sunlon Livestock Development Co. Ltd., 100029, Beijing, China
| | - Y Chang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907
| | - Y Li
- Beijing Sunlon Livestock Development Co. Ltd., 100029, Beijing, China
| | - T Yang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - Y Wang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China.
| | - N Yang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China.
| |
Collapse
|
9
|
Gualdrón Duarte JL, Yuan C, Gori AS, Moreira GCM, Takeda H, Coppieters W, Charlier C, Georges M, Druet T. Sequenced-based GWAS for linear classification traits in Belgian Blue beef cattle reveals new coding variants in genes regulating body size in mammals. Genet Sel Evol 2023; 55:83. [PMID: 38017417 PMCID: PMC10683324 DOI: 10.1186/s12711-023-00857-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 11/17/2023] [Indexed: 11/30/2023] Open
Abstract
BACKGROUND Cohorts of individuals that have been genotyped and phenotyped for genomic selection programs offer the opportunity to better understand genetic variation associated with complex traits. Here, we performed an association study for traits related to body size and muscular development in intensively selected beef cattle. We leveraged multiple trait information to refine and interpret the significant associations. RESULTS After a multiple-step genotype imputation to the sequence-level for 14,762 Belgian Blue beef (BBB) cows, we performed a genome-wide association study (GWAS) for 11 traits related to muscular development and body size. The 37 identified genome-wide significant quantitative trait loci (QTL) could be condensed in 11 unique QTL regions based on their position. Evidence for pleiotropic effects was found in most of these regions (e.g., correlated association signals, overlap between credible sets (CS) of candidate variants). Thus, we applied a multiple-trait approach to combine information from different traits to refine the CS. In several QTL regions, we identified strong candidate genes known to be related to growth and height in other species such as LCORL-NCAPG or CCND2. For some of these genes, relevant candidate variants were identified in the CS, including three new missense variants in EZH2, PAPPA2 and ADAM12, possibly two additional coding variants in LCORL, and candidate regulatory variants linked to CCND2 and ARMC12. Strikingly, four other QTL regions associated with dimension or muscular development traits were related to five (recessive) deleterious coding variants previously identified. CONCLUSIONS Our study further supports that a set of common genes controls body size across mammalian species. In particular, we added new genes to the list of those associated with height in both humans and cattle. We also identified new strong candidate causal variants in some of these genes, strengthening the evidence of their causality. Several breed-specific recessive deleterious variants were identified in our QTL regions, probably as a result of the extreme selection for muscular development in BBB cattle.
Collapse
Affiliation(s)
- José Luis Gualdrón Duarte
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Avenue de l'Hôpital, 1, Liège, 4000, Belgium.
- Walloon Breeders Association, Rue des Champs Elysées, 4, 5590, Ciney, Belgium.
| | - Can Yuan
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Avenue de l'Hôpital, 1, Liège, 4000, Belgium
| | - Ann-Stephan Gori
- Walloon Breeders Association, Rue des Champs Elysées, 4, 5590, Ciney, Belgium
| | - Gabriel C M Moreira
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Avenue de l'Hôpital, 1, Liège, 4000, Belgium
| | - Haruko Takeda
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Avenue de l'Hôpital, 1, Liège, 4000, Belgium
| | - Wouter Coppieters
- GIGA Genomic Platform, GIGA-R, University of Liège, Avenue de l'Hôpital, 1, 4000, Liège, Belgium
| | - Carole Charlier
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Avenue de l'Hôpital, 1, Liège, 4000, Belgium
| | - Michel Georges
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Avenue de l'Hôpital, 1, Liège, 4000, Belgium
| | - Tom Druet
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Avenue de l'Hôpital, 1, Liège, 4000, Belgium
| |
Collapse
|
10
|
Atashi H, Chen Y, Wilmot H, Bastin C, Vanderick S, Hubin X, Gengler N. Single-step genome-wide association analyses for selected infrared-predicted cheese-making traits in Walloon Holstein cows. J Dairy Sci 2023; 106:7816-7831. [PMID: 37567464 DOI: 10.3168/jds.2022-23206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 05/01/2023] [Indexed: 08/13/2023]
Abstract
This study aimed to perform genome-wide association study to identify genomic regions associated with milk production and cheese-making properties (CMP) in Walloon Holstein cows. The studied traits were milk yield, fat percentage, protein percentage, casein percentage (CNP), calcium content, somatic cell score (SCS), coagulation time, curd firmness after 30 min from rennet addition, and titratable acidity. The used data have been collected from 2014 to 2020 on 78,073 first-parity (485,218 test-day records), 48,766 second-parity (284,942 test-day records), and 21,948 third-parity (105,112 test-day records) Holstein cows distributed in 671 herds in the Walloon Region of Belgium. Data of 565,533 single nucleotide polymorphisms (SNP), located on 29 Bos taurus autosomes (BTA) of 6,617 animals (1,712 males), were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of ∼216 KB) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for positional candidate genes. Heritability estimates for the studied traits ranged from 0.10 (SCS) to 0.53 (CNP), 0.10 (SCS) to 0.50 (CNP), and 0.12 (SCS) to 0.49 (CNP) in the first, second, and third parity, respectively. Genome-wide association analyses identified 6 genomic regions (BTA1, BTA14 [4 regions], and BTA20) associated with the considered traits. Genes including the SLC37A1 (BTA1), SHARPIN, MROH1, DGAT1, FAM83H, TIGD5, MROH6, NAPRT, ADGRB1, GML, LYPD2, JRK (BTA14), and TRIO (BTA20) were identified as positional candidate genes for the studied CMP. The findings of this study help to unravel the genomic background of a cow's ability for cheese production and can be used for the future implementation and use of genomic evaluation to improve the cheese-making traits in Walloon Holstein cows.
Collapse
Affiliation(s)
- H Atashi
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium; Department of Animal Science, Shiraz University, 71441-13131 Shiraz, Iran.
| | - Y Chen
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - H Wilmot
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium; National Fund for Scientific Research (FRS-FNRS), 1000 Brussels, Belgium
| | - C Bastin
- National Fund for Scientific Research (FRS-FNRS), 1000 Brussels, Belgium
| | - S Vanderick
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - X Hubin
- Elevéo asbl Awé Group, 5590 Ciney, Belgium
| | - N Gengler
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| |
Collapse
|
11
|
Sanchez MP, Tribout T, Kadri NK, Chitneedi PK, Maak S, Hozé C, Boussaha M, Croiseau P, Philippe R, Spengeler M, Kühn C, Wang Y, Li C, Plastow G, Pausch H, Boichard D. Sequence-based GWAS meta-analyses for beef production traits. Genet Sel Evol 2023; 55:70. [PMID: 37828440 PMCID: PMC10568825 DOI: 10.1186/s12711-023-00848-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Accepted: 10/04/2023] [Indexed: 10/14/2023] Open
Abstract
BACKGROUND Combining the results of within-population genome-wide association studies (GWAS) based on whole-genome sequences into a single meta-analysis (MA) is an accurate and powerful method for identifying variants associated with complex traits. As part of the H2020 BovReg project, we performed sequence-level MA for beef production traits. Five partners from France, Switzerland, Germany, and Canada contributed summary statistics from sequence-based GWAS conducted with 54,782 animals from 15 purebred or crossbred populations. We combined the summary statistics for four growth, nine morphology, and 15 carcass traits into 16 MA, using both fixed effects and z-score methods. RESULTS The fixed-effects method was generally more informative to provide indication on potentially causal variants, although we combined substantially different traits in each MA. In comparison with within-population GWAS, this approach highlighted (i) a larger number of quantitative trait loci (QTL), (ii) QTL more frequently located in genomic regions known for their effects on growth and meat/carcass traits, (iii) a smaller number of genomic variants within the QTL, and (iv) candidate variants that were more frequently located in genes. MA pinpointed variants in genes, including MSTN, LCORL, and PLAG1 that have been previously associated with morphology and carcass traits. We also identified dozens of other variants located in genes associated with growth and carcass traits, or with a function that may be related to meat production (e.g., HS6ST1, HERC2, WDR75, COL3A1, SLIT2, MED28, and ANKAR). Some of these variants overlapped with expression or splicing QTL reported in the cattle Genotype-Tissue Expression atlas (CattleGTEx) and could therefore regulate gene expression. CONCLUSIONS By identifying candidate genes and potential causal variants associated with beef production traits in cattle, MA demonstrates great potential for investigating the biological mechanisms underlying these traits. As a complement to within-population GWAS, this approach can provide deeper insights into the genetic architecture of complex traits in beef cattle.
Collapse
Affiliation(s)
- Marie-Pierre Sanchez
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
| | - Thierry Tribout
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | | | - Praveen K Chitneedi
- Research Institute for Farm Animal Biology (FBN), 18196, Dummerstorf, Germany
| | - Steffen Maak
- Research Institute for Farm Animal Biology (FBN), 18196, Dummerstorf, Germany
| | - Chris Hozé
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
- Eliance, 75595, Paris, France
| | - Mekki Boussaha
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Pascal Croiseau
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Romain Philippe
- INRAE, USC1061 GAMAA, Université de Limoges, 87060, Limoges, France
| | | | - Christa Kühn
- Research Institute for Farm Animal Biology (FBN), 18196, Dummerstorf, Germany
- Agricultural and Environmental faculty, University Rostock, 18059, Rostock, Germany
- Friedrich-Loeffler-Institut (FLI), 17493, Greifswald, Insel Riems, Germany
| | - Yining Wang
- Lacombe Research and Development Centre, Agriculture and Agri-Food Canada, Lacombe, AB, T4L 1W1, Canada
| | - Changxi Li
- Lacombe Research and Development Centre, Agriculture and Agri-Food Canada, Lacombe, AB, T4L 1W1, Canada
- Department of Agricultural, Food and Nutritional Science, Livestock Gentec, University of Alberta, Edmonton, AB, T6G 2HI, Canada
| | - Graham Plastow
- Department of Agricultural, Food and Nutritional Science, Livestock Gentec, University of Alberta, Edmonton, AB, T6G 2HI, Canada
| | - Hubert Pausch
- Animal Genomics, ETH Zurich, 8092, Zurich, Switzerland
| | - Didier Boichard
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| |
Collapse
|
12
|
Zhou F, Fan X, Xu X, Li Z, Qiu L, Miao Y. Molecular Characteristics and Polymorphisms of Buffalo ( Bubalus bubalis) ABCG2 Gene and Its Role in Milk Fat Synthesis. Animals (Basel) 2023; 13:3156. [PMID: 37835762 PMCID: PMC10571847 DOI: 10.3390/ani13193156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 09/24/2023] [Accepted: 10/04/2023] [Indexed: 10/15/2023] Open
Abstract
The ATP-binding cassette subfamily G member 2 (ABCG2) serves crucial roles in secreting riboflavin and biotin vitamins into the milk of cattle, mice, and humans, as well as in the transportation of xenotoxic and cytostatic drugs across the plasma membrane. However, the specific role of the ABCG2 gene in water buffaloes (Bubalus bubalis), especially its effect on milk fat synthesis in buffalo mammary epithelial cells (BuMECs), remains inadequately understood. In this study, the full-length CDS of the buffalo ABCG2 gene was isolated and identified from the mammary gland in buffaloes. A bioinformatics analysis showed a high degree of similarity in the transcriptional region, motifs, and conservative domains of the buffalo ABCG2 with those observed in other Bovidae species. The functional role of buffalo ABCG2 was associated with the transportation of solutes across lipid bilayers within cell membranes. Among the 11 buffalo tissues detected, the expression levels of ABCG2 were the highest in the liver and brain, followed by the mammary gland, adipose tissue, heart, and kidney. Notably, its expression in the mammary gland was significantly higher during peak lactation than during non-lactation. The ABCG2 gene was identified with five SNPs in river buffaloes, while it was monomorphic in swamp buffaloes. Functional experiments revealed that ABCG2 increased the triglyceride (TAG) content by affecting the expression of liposynthesis-related genes in BuMECs. The results of this study underscore the pivotal role of the ABCG2 gene in influencing the milk fat synthesis in BuMECs.
Collapse
Affiliation(s)
- Fangting Zhou
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (F.Z.); (X.F.); (X.X.); (Z.L.); (L.Q.)
- College of Chemistry, Biology and Environment, Yuxi Normal University, Yuxi 653100, China
| | - Xinyang Fan
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (F.Z.); (X.F.); (X.X.); (Z.L.); (L.Q.)
| | - Xiaoqi Xu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (F.Z.); (X.F.); (X.X.); (Z.L.); (L.Q.)
| | - Zhuoran Li
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (F.Z.); (X.F.); (X.X.); (Z.L.); (L.Q.)
| | - Lihua Qiu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (F.Z.); (X.F.); (X.X.); (Z.L.); (L.Q.)
| | - Yongwang Miao
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China; (F.Z.); (X.F.); (X.X.); (Z.L.); (L.Q.)
| |
Collapse
|
13
|
Sanchez MP, Escouflaire C, Baur A, Bottin F, Hozé C, Boussaha M, Fritz S, Capitan A, Boichard D. X-linked genes influence various complex traits in dairy cattle. BMC Genomics 2023; 24:338. [PMID: 37337145 DOI: 10.1186/s12864-023-09438-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 06/08/2023] [Indexed: 06/21/2023] Open
Abstract
BACKGROUND The search for quantitative trait loci (QTL) affecting traits of interest in mammals is frequently limited to autosomes, with the X chromosome excluded because of its hemizygosity in males. This study aimed to assess the importance of the X chromosome in the genetic determinism of 11 complex traits related to milk production, milk composition, mastitis resistance, fertility, and stature in 236,496 cows from three major French dairy breeds (Holstein, Montbéliarde, and Normande) and three breeds of regional importance (Abondance, Tarentaise, and Vosgienne). RESULTS Estimates of the proportions of heritability due to autosomes and X chromosome (h²X) were consistent among breeds. On average over the 11 traits, h²X=0.008 and the X chromosome explained ~ 3.5% of total genetic variance. GWAS was performed within-breed at the sequence level (~ 200,000 genetic variants) and then combined in a meta-analysis. QTL were identified for most breeds and traits analyzed, with the exception of Tarentaise and Vosgienne and two fertility traits. Overall, 3, 74, 59, and 71 QTL were identified in Abondance, Montbéliarde, Normande, and Holstein, respectively, and most were associated with the most-heritable traits (milk traits and stature). The meta-analyses, which assessed a total of 157 QTL for the different traits, highlighted new QTL and refined the positions of some QTL found in the within-breed analyses. Altogether, our analyses identified a number of functional candidate genes, with the most notable being GPC3, MBNL3, HS6ST2, and DMD for dairy traits; TMEM164, ACSL4, ENOX2, HTR2C, AMOT, and IRAK1 for udder health; MAMLD1 and COL4A6 for fertility; and NRK, ESX1, GPR50, GPC3, and GPC4 for stature. CONCLUSIONS This study demonstrates the importance of the X chromosome in the genetic determinism of complex traits in dairy cattle and highlights new functional candidate genes and variants for these traits. These results could potentially be extended to other species as many X-linked genes are shared among mammals.
Collapse
Affiliation(s)
- Marie-Pierre Sanchez
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, 78350, France.
| | | | | | - Fiona Bottin
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, 78350, France
| | | | - Mekki Boussaha
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, 78350, France
| | | | - Aurélien Capitan
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, 78350, France
| | - Didier Boichard
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, 78350, France
| |
Collapse
|
14
|
Jayawardana JMDR, Lopez-Villalobos N, McNaughton LR, Hickson RE. Genomic Regions Associated with Milk Composition and Fertility Traits in Spring-Calved Dairy Cows in New Zealand. Genes (Basel) 2023; 14:genes14040860. [PMID: 37107618 PMCID: PMC10137527 DOI: 10.3390/genes14040860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 03/27/2023] [Accepted: 03/29/2023] [Indexed: 04/05/2023] Open
Abstract
The objective of this study was to identify genomic regions and genes that are associated with the milk composition and fertility traits of spring-calved dairy cows in New Zealand. Phenotypic data from the 2014–2015 and 2021–2022 calving seasons in two Massey University dairy herds were used. We identified 73 SNPs that were significantly associated with 58 potential candidate genes for milk composition and fertility traits. Four SNPs on chromosome 14 were highly significant for both fat and protein percentages, and the associated genes were DGAT1, SLC52A2, CPSF1, and MROH1. For fertility traits, significant associations were detected for intervals from the start of mating to first service, the start of mating to conception, first service to conception, calving to first service, and 6-wk submission, 6-wk in-calf, conception to first service in the first 3 weeks of the breeding season, and not in calf and 6-wk calving rates. Gene Ontology revealed 10 candidate genes (KCNH5, HS6ST3, GLS, ENSBTAG00000051479, STAT1, STAT4, GPD2, SH3PXD2A, EVA1C, and ARMH3) that were significantly associated with fertility traits. The biological functions of these genes are related to reducing the metabolic stress of cows and increasing insulin secretion during the mating period, early embryonic development, foetal growth, and maternal lipid metabolism during the pregnancy period.
Collapse
Affiliation(s)
- J. M. D. R. Jayawardana
- School of Agriculture and Environment, Massey University, Palmerston North 4410, New Zealand
- Department of Animal Science, Faculty of Animal Science and Export Agriculture, Uva Wellassa University, Badulla 90000, Sri Lanka
| | | | - Lorna R. McNaughton
- Livestock Improvement Corporation, Private Bag 3016, Hamilton 3240, New Zealand
| | | |
Collapse
|
15
|
Chen Y, Atashi H, Grelet C, Mota RR, Vanderick S, Hu H, Gengler N. Genome-wide association study and functional annotation analyses for nitrogen efficiency index and its composition traits in dairy cattle. J Dairy Sci 2023; 106:3397-3410. [PMID: 36894424 DOI: 10.3168/jds.2022-22351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 10/24/2022] [Indexed: 03/09/2023]
Abstract
The aims of this study were (1) to identify genomic regions associated with a N efficiency index (NEI) and its composition traits and (2) to analyze the functional annotation of identified genomic regions. The NEI included N intake (NINT1), milk true protein N (MTPN1), milk urea N yield (MUNY1) in primiparous cattle, and N intake (NINT2+), milk true protein N (MTPN2+), and milk urea N yield (MUNY2+) in multiparous cattle (2 to 5 parities). The edited data included 1,043,171 records on 342,847 cows distributed in 1,931 herds. The pedigree consisted of 505,125 animals (17,797 males). Data of 565,049 SNPs were available for 6,998 animals included in the pedigree (5,251 females and 1,747 males). The SNP effects were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of about 240 kb) was calculated. The top 3 genomic regions explaining the largest rate of the total additive genetic variance of the NEI and its composition traits were selected for candidate gene identification and quantitative trait loci (QTL) annotation. The selected genomic regions explained from 0.17% (MTPN2+) to 0.58% (NEI) of the total additive genetic variance. The largest explanatory genomic regions of NEI, NINT1, NINT2+, MTPN1, MTPN2+, MUNY1, and MUNY2+ were Bos taurus autosome 14 (1.52-2.09 Mb), 26 (9.24-9.66 Mb), 16 (75.41-75.51 Mb), 6 (8.73-88.92 Mb), 6 (8.73-88.92 Mb), 11 (103.26-103.41 Mb), 11 (103.26-103.41 Mb). Based on the literature, gene ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction, 16 key candidate genes were identified for NEI and its composition traits, which are mainly expressed in the milk cell, mammary, and liver tissues. The number of enriched QTL related to NEI, NINT1, NINT2+, MTPN1, and MTPN2+ were 41, 6, 4, 11, 36, 32, and 32, respectively, and most of them were related to the milk, health, and production classes. In conclusion, this study identified genomic regions associated with NEI and its composition traits, and identified key candidate genes describing the genetic mechanisms of N use efficiency-related traits. Furthermore, the NEI reflects not only its composition traits but also the interactions among them.
Collapse
Affiliation(s)
- Y Chen
- TERRA Teaching and Research Center, University of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, Belgium.
| | - H Atashi
- TERRA Teaching and Research Center, University of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, Belgium; Department of Animal Science, Shiraz University, 71441-65186 Shiraz, Iran
| | - C Grelet
- Walloon Agricultural Research Center (CRA-W), 5030 Gembloux, Belgium
| | - R R Mota
- Council on Dairy Cattle Breeding, Bowie, MD 20716
| | - S Vanderick
- TERRA Teaching and Research Center, University of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, Belgium
| | - H Hu
- TERRA Teaching and Research Center, University of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, Belgium
| | | | - N Gengler
- TERRA Teaching and Research Center, University of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, Belgium
| |
Collapse
|
16
|
Lopdell TJ. Using QTL to Identify Genes and Pathways Underlying the Regulation and Production of Milk Components in Cattle. Animals (Basel) 2023; 13:ani13050911. [PMID: 36899768 PMCID: PMC10000085 DOI: 10.3390/ani13050911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 02/23/2023] [Accepted: 02/28/2023] [Indexed: 03/06/2023] Open
Abstract
Milk is a complex liquid, and the concentrations of many of its components are under genetic control. Many genes and pathways are known to regulate milk composition, and the purpose of this review is to highlight how the discoveries of quantitative trait loci (QTL) for milk phenotypes can elucidate these pathways. The main body of this review focuses primarily on QTL discovered in cattle (Bos taurus) as a model species for the biology of lactation, and there are occasional references to sheep genetics. The following section describes a range of techniques that can be used to help identify the causative genes underlying QTL when the underlying mechanism involves the regulation of gene expression. As genotype and phenotype databases continue to grow and diversify, new QTL will continue to be discovered, and although proving the causality of underlying genes and variants remains difficult, these new data sets will further enhance our understanding of the biology of lactation.
Collapse
|
17
|
Teng J, Wang D, Zhao C, Zhang X, Chen Z, Liu J, Sun D, Tang H, Wang W, Li J, Mei C, Yang Z, Ning C, Zhang Q. Longitudinal genome-wide association studies of milk production traits in Holstein cattle using whole-genome sequence data imputed from medium-density chip data. J Dairy Sci 2023; 106:2535-2550. [PMID: 36797187 DOI: 10.3168/jds.2022-22277] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 10/20/2022] [Indexed: 02/16/2023]
Abstract
Longitudinal traits, such as milk production traits in dairy cattle, are featured by having phenotypic values at multiple time points, which change dynamically over time. In this study, we first imputed SNP chip (50-100K) data to whole-genome sequence (WGS) data in a Chinese Holstein population consisting of 6,470 cows. The imputation accuracies were 0.88 to 0.97 on average after quality control. We then performed longitudinal GWAS in this population based on a random regression test-day model using the imputed WGS data. The longitudinal GWAS revealed 16, 39, and 75 quantitative trait locus regions associated with milk yield, fat percentage, and protein percentage, respectively. We estimated the 95% confidence intervals (CI) for these quantitative trait locus regions using the logP drop method and identified 581 genes involved in these CI. Further, we focused on the CI that covered or overlapped with only 1 gene or the CI that contained an extremely significant top SNP. Twenty-eight candidate genes were identified in these CI. Most of them have been reported in the literature to be associated with milk production traits, such as DGAT1, HSF1, MGST1, GHR, ABCG2, ADCK5, and CSN1S1. Among the unreported novel genes, some also showed good potential as candidate genes, such as CCSER1, CUX2, SNTB1, RGS7, OSR2, and STK3, and are worth being further investigated. Our study provided not only new insights into the candidate genes for milk production traits, but also a general framework for longitudinal GWAS based on random regression test-day model using WGS data.
Collapse
Affiliation(s)
- Jun Teng
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China
| | - Dan Wang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China
| | - Changheng Zhao
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China
| | - Xinyi Zhang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China
| | - Zhi Chen
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Jianfeng Liu
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Dongxiao Sun
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Hui Tang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China
| | - Wenwen Wang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China
| | - Jianbin Li
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan 250100, China
| | - Cheng Mei
- Dongying Shenzhou AustAsia Modern Dairy Farm Co. Ltd., Dongying 257200, China
| | - Zhangping Yang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Chao Ning
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China.
| | - Qin Zhang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China.
| |
Collapse
|
18
|
Neumann GB, Korkuć P, Arends D, Wolf MJ, May K, König S, Brockmann GA. Genomic diversity and relationship analyses of endangered German Black Pied cattle (DSN) to 68 other taurine breeds based on whole-genome sequencing. Front Genet 2023; 13:993959. [PMID: 36712857 PMCID: PMC9875303 DOI: 10.3389/fgene.2022.993959] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 11/28/2022] [Indexed: 01/05/2023] Open
Abstract
German Black Pied cattle (Deutsches Schwarzbuntes Niederungsrind, DSN) are an endangered dual-purpose cattle breed originating from the North Sea region. The population comprises about 2,500 cattle and is considered one of the ancestral populations of the modern Holstein breed. The current study aimed at defining the breeds closest related to DSN cattle, characterizing their genomic diversity and inbreeding. In addition, the detection of selection signatures between DSN and Holstein was a goal. Relationship analyses using fixation index (FST), phylogenetic, and admixture analyses were performed between DSN and 68 other breeds from the 1000 Bull Genomes Project. Nucleotide diversity, observed heterozygosity, and expected heterozygosity were calculated as metrics for genomic diversity. Inbreeding was measured as excess of homozygosity (FHom) and genomic inbreeding (FRoH) through runs of homozygosity (RoHs). Region-wide FST and cross-population-extended haplotype homozygosity (XP-EHH) between DSN and Holstein were used to detect selection signatures between the two breeds, and RoH islands were used to detect selection signatures within DSN and Holstein. DSN showed a close genetic relationship with breeds from the Netherlands, Belgium, Northern Germany, and Scandinavia, such as Dutch Friesian Red, Dutch Improved Red, Belgian Red White Campine, Red White Dual Purpose, Modern Angler, Modern Danish Red, and Holstein. The nucleotide diversity in DSN (0.151%) was higher than in Holstein (0.147%) and other breeds, e.g., Norwegian Red (0.149%), Red White Dual Purpose (0.149%), Swedish Red (0.149%), Hereford (0.145%), Angus (0.143%), and Jersey (0.136%). The FHom and FRoH values in DSN were among the lowest. Regions with high FST between DSN and Holstein, significant XP-EHH regions, and RoH islands detected in both breeds harbor candidate genes that were previously reported for milk, meat, fertility, production, and health traits, including one QTL detected in DSN for endoparasite infection resistance. The selection signatures between DSN and Holstein provide evidence of regions responsible for the dual-purpose properties of DSN and the milk type of Holstein. Despite the small population size, DSN has a high level of diversity and low inbreeding. FST supports its relatedness to breeds from the same geographic origin and provides information on potential gene pools that could be used to maintain diversity in DSN.
Collapse
Affiliation(s)
- Guilherme B. Neumann
- Animal Breeding Biology and Molecular Genetics, Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Paula Korkuć
- Animal Breeding Biology and Molecular Genetics, Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Danny Arends
- Animal Breeding Biology and Molecular Genetics, Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt-Universität zu Berlin, Berlin, Germany,Department of Applied Sciences, Northumbria University, Newcastle Upon Tyne, United Kingdom
| | - Manuel J. Wolf
- Institute of Animal Breeding and Genetics, Justus-Liebig-Universität, Giessen, Germany
| | - Katharina May
- Institute of Animal Breeding and Genetics, Justus-Liebig-Universität, Giessen, Germany
| | - Sven König
- Institute of Animal Breeding and Genetics, Justus-Liebig-Universität, Giessen, Germany
| | - Gudrun A. Brockmann
- Animal Breeding Biology and Molecular Genetics, Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt-Universität zu Berlin, Berlin, Germany,*Correspondence: Gudrun A. Brockmann,
| |
Collapse
|
19
|
Prowse-Wilkins CP, Lopdell TJ, Xiang R, Vander Jagt CJ, Littlejohn MD, Chamberlain AJ, Goddard ME. Genetic variation in histone modifications and gene expression identifies regulatory variants in the mammary gland of cattle. BMC Genomics 2022; 23:815. [PMID: 36482302 PMCID: PMC9733386 DOI: 10.1186/s12864-022-09002-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 11/10/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Causal variants for complex traits, such as eQTL are often found in non-coding regions of the genome, where they are hypothesised to influence phenotypes by regulating gene expression. Many regulatory regions are marked by histone modifications, which can be assayed by chromatin immunoprecipitation followed by sequencing (ChIP-seq). Sequence reads from ChIP-seq form peaks at putative regulatory regions, which may reflect the amount of regulatory activity at this region. Therefore, eQTL which are also associated with differences in histone modifications are excellent candidate causal variants. RESULTS We assayed the histone modifications H3K4Me3, H3K4Me1 and H3K27ac and mRNA in the mammary gland of up to 400 animals. We identified QTL for peak height (histone QTL), exon expression (eeQTL), allele specific expression (aseQTL) and allele specific binding (asbQTL). By intersecting these results, we identify variants which may influence gene expression by altering regulatory regions of the genome, and may be causal variants for other traits. Lastly, we find that these variants are found in putative transcription factor binding sites, identifying a mechanism for the effect of many eQTL. CONCLUSIONS We find that allele specific and traditional QTL analysis often identify the same genetic variants and provide evidence that many eQTL are regulatory variants which alter activity at regulatory regions of the bovine genome. Our work provides methodological and biological updates on how regulatory mechanisms interplay at multi-omics levels.
Collapse
Affiliation(s)
- Claire P Prowse-Wilkins
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, Victoria, 3082, Australia.
- Faculty of Veterinary & Agricultural Science, University of Melbourne, Parkville, Victoria, 3010, Australia.
| | - Thomas J Lopdell
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240, New Zealand
| | - Ruidong Xiang
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, Victoria, 3082, Australia
- Faculty of Veterinary & Agricultural Science, University of Melbourne, Parkville, Victoria, 3010, Australia
| | - Christy J Vander Jagt
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, Victoria, 3082, Australia
| | - Mathew D Littlejohn
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240, New Zealand
| | - Amanda J Chamberlain
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, Victoria, 3082, Australia
| | - Michael E Goddard
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, Victoria, 3082, Australia
- Faculty of Veterinary & Agricultural Science, University of Melbourne, Parkville, Victoria, 3010, Australia
| |
Collapse
|
20
|
Atashi H, Bastin C, Wilmot H, Vanderick S, Hubin X, Gengler N. Genome-wide association study for selected cheese-making properties in Dual-Purpose Belgian Blue cows. J Dairy Sci 2022; 105:8972-8988. [PMID: 36175238 DOI: 10.3168/jds.2022-21780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 06/21/2022] [Indexed: 01/05/2023]
Abstract
This study aimed to estimate genetic parameters and identify genomic region(s) associated with selected cheese-making properties (CMP) in Dual-Purpose Belgian Blue (DPBB) cows. Edited data were 46,301 test-day records of milk yield, fat percentage, protein percentage, casein percentage, milk calcium content (CC), coagulation time (CT), curd firmness after 30 min from rennet addition (a30), and milk titratable acidity (MTA) collected from 2014 to 2020 on 4,077 first-parity (26,027 test-day records), and 3,258 second-parity DPBB cows (20,274 test-day records) distributed in 124 herds in the Walloon Region of Belgium. Data of 28,266 SNP, located on 29 Bos taurus autosomes (BTA) of 1,699 animals were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 25 consecutive SNPs (with an average size of ∼2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Heritability estimates for the included CMP ranged from 0.19 (CC) to 0.50 (MTA), and 0.24 (CC) to 0.41 (MTA) in the first and second parity, respectively. The genetic correlation estimated between CT and a30 varied from -0.61 to -0.41 and from -0.55 to -0.38 in the first and second lactations, respectively. Negative genetic correlations were found between CT and milk yield and composition, while those estimated between curd firmness and milk composition were positive. Genome-wide association analyses results identified 4 genomic regions (BTA1, BTA3, BTA7, and BTA11) associated with the considered CMP. The identified genomic regions showed contrasting results between parities and among the different stages of each parity. It suggests that different sets of candidate genes underlie the phenotypic expression of the considered CMP between parities and lactation stages of each parity. The findings of this study can be used for future implementation and use of genomic evaluation to improve the cheese-making traits in DPBB cows.
Collapse
Affiliation(s)
- H Atashi
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium; Department of Animal Science, Shiraz University, 71441-65186 Shiraz, Iran.
| | - C Bastin
- Walloon Breeders Association, 5590 Ciney, Belgium
| | - H Wilmot
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium; National Fund for Scientific Research (FRS-FNRS), Rue d'Egmont 5, B-1000 Brussels, Belgium
| | - S Vanderick
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - X Hubin
- Walloon Breeders Association, 5590 Ciney, Belgium
| | - N Gengler
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| |
Collapse
|
21
|
Tiplady KM, Lopdell TJ, Sherlock RG, Johnson TJ, Spelman RJ, Harris BL, Davis SR, Littlejohn MD, Garrick DJ. Comparison of the genetic characteristics of directly measured and Fourier-transform mid-infrared-predicted bovine milk fatty acids and proteins. J Dairy Sci 2022; 105:9763-9791. [DOI: 10.3168/jds.2022-22089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 07/21/2022] [Indexed: 11/17/2022]
|
22
|
Ros-Freixedes R, Johnsson M, Whalen A, Chen CY, Valente BD, Herring WO, Gorjanc G, Hickey JM. Genomic prediction with whole-genome sequence data in intensely selected pig lines. GENETICS SELECTION EVOLUTION 2022; 54:65. [PMID: 36153511 PMCID: PMC9509613 DOI: 10.1186/s12711-022-00756-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 09/05/2022] [Indexed: 12/03/2022]
Abstract
Background Early simulations indicated that whole-genome sequence data (WGS) could improve the accuracy of genomic predictions within and across breeds. However, empirical results have been ambiguous so far. Large datasets that capture most of the genomic diversity in a population must be assembled so that allele substitution effects are estimated with high accuracy. The objectives of this study were to use a large pig dataset from seven intensely selected lines to assess the benefits of using WGS for genomic prediction compared to using commercial marker arrays and to identify scenarios in which WGS provides the largest advantage. Methods We sequenced 6931 individuals from seven commercial pig lines with different numerical sizes. Genotypes of 32.8 million variants were imputed for 396,100 individuals (17,224 to 104,661 per line). We used BayesR to perform genomic prediction for eight complex traits. Genomic predictions were performed using either data from a standard marker array or variants preselected from WGS based on association tests. Results The accuracies of genomic predictions based on preselected WGS variants were not robust across traits and lines and the improvements in prediction accuracy that we achieved so far with WGS compared to standard marker arrays were generally small. The most favourable results for WGS were obtained when the largest training sets were available and standard marker arrays were augmented with preselected variants with statistically significant associations to the trait. With this method and training sets of around 80k individuals, the accuracy of within-line genomic predictions was on average improved by 0.025. With multi-line training sets, improvements of 0.04 compared to marker arrays could be expected. Conclusions Our results showed that WGS has limited potential to improve the accuracy of genomic predictions compared to marker arrays in intensely selected pig lines. Thus, although we expect that larger improvements in accuracy from the use of WGS are possible with a combination of larger training sets and optimised pipelines for generating and analysing such datasets, the use of WGS in the current implementations of genomic prediction should be carefully evaluated against the cost of large-scale WGS data on a case-by-case basis. Supplementary Information The online version contains supplementary material available at 10.1186/s12711-022-00756-0.
Collapse
|
23
|
Nazar M, Abdalla IM, Chen Z, Ullah N, Liang Y, Chu S, Xu T, Mao Y, Yang Z, Lu X. Genome-Wide Association Study for Udder Conformation Traits in Chinese Holstein Cattle. Animals (Basel) 2022; 12:2542. [PMID: 36230283 PMCID: PMC9559277 DOI: 10.3390/ani12192542] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 09/14/2022] [Accepted: 09/20/2022] [Indexed: 11/16/2022] Open
Abstract
Udder conformation traits are one of the most economic traits in dairy cows, greatly affecting animal health, milk production, and producer profitability in the dairy industry. Genetic analysis of udder structure and scores have been developed in Holstein cattle. In our research, we conducted a genome-wide association study for five udder traits, including anterior udder attachment (AUA), central suspensory ligament (CSL), posterior udder attachment height (PUAH), posterior udder attachment width (PUAW), and udder depth (UD), in which the fixed and random model circulating probability unification (FarmCPU) model was applied for the association analysis. The heritability and the standard errors of these five udder traits ranged from 0.04 ± 0.00 to 0.49 ± 0.03. Phenotype data were measured from 1000 Holstein cows, and the GeneSeek Genomic Profiler (GGP) Bovine 100 K SNP chip was used to analyze genotypic data in Holstein cattle. For GWAS analysis, 984 individual cows and 84,407 single-nucleotide polymorphisms (SNPs) remained after quality control; a total of 18 SNPs were found at the GW significant threshold (p < 5.90 × 10−7). Many candidate genes were identified within 200kb upstream or downstream of the significant SNPs, which include MGST1, MGST2, MTUS1, PRKN, STXBP6, GRID2, E2F8, CDH11, FOXP1, SLF1, TMEM117, SBF2, GC, ADGRB3, and GCLC. Pathway analysis revealed that 58 Gene Ontology (GO) terms and 18 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were enriched with adjusted p values, and these GO terms and the KEGG pathway analysis were associated with biological information, metabolism, hormonal growth, and development processes. These results could give valuable biological information for the genetic architecture of udder conformation traits in dairy Holstein cattle.
Collapse
Affiliation(s)
- Mudasir Nazar
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | | | - Zhi Chen
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Numan Ullah
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Yan Liang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Shuangfeng Chu
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Tianle Xu
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou 225009, China
| | - Yongjiang Mao
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Zhangping Yang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Xubin Lu
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| |
Collapse
|
24
|
Genomic Selection in Chinese Holsteins Using Regularized Regression Models for Feature Selection of Whole Genome Sequencing Data. Animals (Basel) 2022; 12:ani12182419. [PMID: 36139283 PMCID: PMC9495168 DOI: 10.3390/ani12182419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 09/09/2022] [Accepted: 09/12/2022] [Indexed: 11/30/2022] Open
Abstract
Simple Summary Genomic selection (GS) is increasingly widely used in animal breeding, owing to its high efficiency in the genetic improvement of economic traits. In China, GS has been implemented for genetic evaluation of young bulls in dairy cattle breeding programs since 2012. GS is commonly based on single nucleotide polymorphism (SNP) chips. The cost of whole genome sequencing (WGS) has decreased tremendously in recent years, allowing increased studies of WGS-based GS. In this study, based on the imputed WGS data of approximately 8000 Chinese Holsteins, we investigated the performance of GS of milk production traits using the feature selection method of regularized regression. The results showed that WGS-based GS using regularized regression models and the commonly used linear mixed models achieved comparable prediction accuracies. For milk and protein yields, GS using a combination of SNPs selected with a regularized regression model and 50K SNP chip data achieved the best prediction performance, and GS using SNPs selected with a linear mixed model combined with 50K SNP chip data performed best for fat yield. The proposed method of GS based on WGS data, i.e., feature selection using regularization regression models, provides a valuable novel strategy for genomic selection. Abstract Genomic selection (GS) is an efficient method to improve genetically economic traits. Feature selection is an important method for GS based on whole-genome sequencing (WGS) data. We investigated the prediction performance of GS of milk production traits using imputed WGS data on 7957 Chinese Holsteins. We used two regularized regression models, least absolute shrinkage and selection operator (LASSO) and elastic net (EN) for feature selection. For comparison, we performed genome-wide association studies based on a linear mixed model (LMM), and the N single nucleotide polymorphisms (SNPs) with the lowest p-values were selected (LMMLASSO and LMMEN), where N was the number of non-zero effect SNPs selected by LASSO or EN. GS was conducted using a genomic best linear unbiased prediction (GBLUP) model and several sets of SNPs: (1) selected WGS SNPs; (2) 50K SNP chip data; (3) WGS data; and (4) a combined set of selected WGS SNPs and 50K SNP chip data. The results showed that the prediction accuracies of GS with features selected using LASSO or EN were comparable to those using features selected with LMMLASSO or LMMEN. For milk and protein yields, GS using a combination of SNPs selected with LASSO and 50K SNP chip data achieved the best prediction performance, and GS using SNPs selected with LMMLASSO combined with 50K SNP chip data performed best for fat yield. The proposed method, feature selection using regularization regression models, provides a valuable novel strategy for WGS-based GS.
Collapse
|
25
|
Liu D, Xu Z, Zhao W, Wang S, Li T, Zhu K, Liu G, Zhao X, Wang Q, Pan Y, Ma P. Genetic parameters and genome-wide association for milk production traits and somatic cell score in different lactation stages of Shanghai Holstein population. Front Genet 2022; 13:940650. [PMID: 36134029 PMCID: PMC9483179 DOI: 10.3389/fgene.2022.940650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 08/04/2022] [Indexed: 11/13/2022] Open
Abstract
The aim of this study was to investigate the genetic parameters and genetic architectures of six milk production traits in the Shanghai Holstein population. The data used to estimate the genetic parameters consisted of 1,968,589 test-day records for 305,031 primiparous cows. Among the cows with phenotypes, 3,016 cows were genotyped with Illumina Bovine SNP50K BeadChip, GeneSeek Bovine 50K BeadChip, GeneSeek Bovine LD BeadChip v4, GeneSeek Bovine 150K BeadChip, or low-depth whole-genome sequencing. A genome-wide association study was performed to identify quantitative trait loci and genes associated with milk production traits in the Shanghai Holstein population using genotypes imputed to whole-genome sequences and both fixed and random model circulating probability unification and a mixed linear model with rMVP software. Estimated heritabilities (h2) varied from 0.04 to 0.14 for somatic cell score (SCS), 0.07 to 0.22 for fat percentage (FP), 0.09 to 0.27 for milk yield (MY), 0.06 to 0.23 for fat yield (FY), 0.09 to 0.26 for protein yield (PY), and 0.07 to 0.35 for protein percentage (PP), respectively. Within lactation, genetic correlations for SCS, FP, MY, FY, PY, and PP at different stages of lactation estimated in random regression model were ranged from -0.02 to 0.99, 0.18 to 0.99, 0.04 to 0.99, 0.04 to 0.99, 0.01 to 0.99, and 0.33 to 0.99, respectively. The genetic correlations were highest between adjacent DIM but decreased as DIM got further apart. Candidate genes included those related to production traits (DGAT1, MGST1, PTK2, and SCRIB), disease-related (LY6K, COL22A1, TECPR2, and PLCB1), heat stress-related (ITGA9, NDST4, TECPR2, and HSF1), and reproduction-related (7SK and DOCK2) genes. This study has shown that there are differences in the genetic mechanisms of milk production traits at different stages of lactation. Therefore, it is necessary to conduct research on milk production traits at different stages of lactation as different traits. Our results can also provide a theoretical basis for subsequent molecular breeding, especially for the novel genetic loci.
Collapse
Affiliation(s)
- Dengying Liu
- Shanghai Key Laboratory of Veterinary Biotechnology, Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Zhong Xu
- Hubei Key Laboratory of Animal Embryo and Molecular Breeding, Institute of Animal Husbandry and Veterinary, Hubei Provincial Academy of Agricultural Sciences, Wuhan, China
| | - Wei Zhao
- Shanghai Key Laboratory of Veterinary Biotechnology, Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Shiyi Wang
- Shanghai Key Laboratory of Veterinary Biotechnology, Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Tuowu Li
- Shanghai Key Laboratory of Veterinary Biotechnology, Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Kai Zhu
- Shanghai Dairy Cattle Breeding Centre Co, Ltd, Shanghai, China
| | - Guanglei Liu
- Shanghai Dairy Cattle Breeding Centre Co, Ltd, Shanghai, China
| | - Xiaoduo Zhao
- Shanghai Dairy Cattle Breeding Centre Co, Ltd, Shanghai, China
| | - Qishan Wang
- Department of Animal Breeding and Reproduction, College of Animal Science, Zhejiang University, Hangzhou, China
| | - Yuchun Pan
- Department of Animal Breeding and Reproduction, College of Animal Science, Zhejiang University, Hangzhou, China
| | - Peipei Ma
- Shanghai Key Laboratory of Veterinary Biotechnology, Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| |
Collapse
|
26
|
Single Nucleotide Polymorphisms, Gene Expression and Economic Evaluation of Parameters Associated with Mastitis Susceptibility in European Cattle Breeds. Vet Sci 2022; 9:vetsci9060294. [PMID: 35737346 PMCID: PMC9229636 DOI: 10.3390/vetsci9060294] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Revised: 06/07/2022] [Accepted: 06/10/2022] [Indexed: 11/17/2022] Open
Abstract
The objective of this study was to explore single nucleotide polymorphisms (SNPs), gene expression and economic evaluation of parameters associated with mastitis susceptibility in Holstein and Brown Swiss dairy cows. Two hundred and forty Holstein and Brown Swiss dairy cows (120 cows of each breed) were used in this study. The investigated dairy cows in each breed were allocated into two equal-sized groups (60 cows each); mastitis tolerant and affected groups. PCR-DNA sequencing of SELL, ABCG2, SLC11A1, FEZL, SOD1, CAT, GPX1, and AhpC/TSA revealed nucleotide sequence variations in the form of SNPs associated with mastitis tolerance/susceptibility in investigated Holstein and Brown Swiss dairy cows. Levels of SELL, SLC11A1 and FEZL gene expression were significantly up-regulated in mastitic Holstein and Brown Swiss dairy cows than in tolerant ones. Meanwhile, ABCG2, SOD1, CAT, GPX1, and AhpC/TSA genes were significantly downregulated. Regarding the economic parameters, significant differences were recorded for net returns and a reduction in the percentage of net profit, as the higher values of net returns were recorded for tolerant dairy cows than mastitic ones in both breeds; moreover, the net profit was reduced by 39% and 27% in mastitic Holstein and Brown Swiss dairy cows, respectively, when compared to tolerant ones. The results herein confirmed the potential significance of investigated genes as candidates for mastitis tolerance/susceptibility in Holstein and Brown Swiss dairy cows. Mastitis also has detrimental impacts on economic efficiency in dairy farms.
Collapse
|
27
|
Sanchez MP, Tribout T, Fritz S, Wolf V, Laithier C, Brochard M, Boichard D. Opportunities for genomic selection of cheese-making traits in Montbéliarde cows. J Dairy Sci 2022; 105:5206-5220. [PMID: 35450715 DOI: 10.3168/jds.2021-21558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 02/22/2022] [Indexed: 11/19/2022]
Abstract
As part of the From'MIR project, traits related to the composition and cheese-making properties (CMP) of milk were predicted from 6.6 million mid-infrared spectra taken from 410,622 Montbéliarde cows (19,862 with genotypes). Genome-wide association studies of imputed whole-genome sequences highlighted candidate SNPs that were then added to the EuroG10K BeadChip, which is routinely used in genomic selection. In the present study, we (1) assessed the reliability of single-step genomic BLUP breeding values (ssEBVs) for cheese yields, coagulation traits, and casein and calcium content generated from test-day records of the first 3 lactations, (2) estimated realized genetic trends for these traits over the last decade, and (3) simulated different cheese-making breeding objectives and estimated the responses for CMP as well as for other traits currently selected in the Montbéliarde breed. To estimate the reliability of ssEBVs, the available data were split into 2 independent training and validation sets that respectively contained cows with the oldest and the most recent lactation data. The training set included 155,961 cows (12,850 with genotypes) and was used to predict ssEBVs of 2,125 genotyped cows in the validation set. We first tested 4 models that included either lactation (LACT) or test-day (TD) records from the first (1) or the first 3 (3) lactations, giving equal weight to all 50K SNP effects. Mean reliabilities were 61%, 62%, 63%, and 64% for the LACT1, LACT3, TD1, and TD3 models, respectively. Using the most accurate model (TD3), we then compared the reliabilities of 3 scenarios with: SNPs from the Illumina BovineSNP50 BeadChip only, equally weighted (50K); 50K SNPs plus additional candidate SNPs, equally weighted (50K+); and 50K and candidate SNPs with additional weight given to 7 to 14 candidate SNPs, depending on the trait (CAND). The 50K+ and CAND scenarios led to similar mean reliabilities (67%) and both outperformed the 50K scenario (64%), whereas the CAND scenario generated the less biased ssEBVs. To assess genetic trends, SNP effects were estimated with a single-step GBLUP based on the TD3 model and the 50K scenario applied to the whole population (2.6 million performance records from 190,261 cows and 423,348 animals in the pedigree, of which 21,874 were genotyped) and then applied to 50K genotypes of 21,171 males and 311,761 females. We detected a positive genetic trend for all CMP during the last decade, probably due to selection for an increase in milk protein and fat content in Montbéliarde cows. Finally, we compared the selection responses to 3 different breeding objectives: the current Montbéliarde total merit index (TMI) and 2 alternative scenarios that gave a weight of 70% to TMI and the remaining 30% to either milk casein content (TMI-COMP) or a combination of 3 CMP (TMI-Cheese). The TMI-Cheese scenario yielded the best responses for all the CMP analyzed, whereas values in the TMI-COMP scenario were intermediate, with a slight effect on other traits currently included in TMI. Based on these results, a program of genomic evaluation for CMP predicted from mid-infrared spectra was designed and implemented for the Montbéliarde breed.
Collapse
Affiliation(s)
- M P Sanchez
- Université Paris Saclay, INRAE, AgroParisTech, GABI, 78350 Jouy-en-Josas, France.
| | - T Tribout
- Université Paris Saclay, INRAE, AgroParisTech, GABI, 78350 Jouy-en-Josas, France
| | | | - V Wolf
- ECEL Doubs, Territoire de Belfort, 25640 Roulans, France
| | - C Laithier
- Institut de l'Elevage, 75012 Paris, France
| | - M Brochard
- Institut de l'Elevage, 75012 Paris, France; Umotest, 01250 Ceyzériat, France
| | - D Boichard
- Université Paris Saclay, INRAE, AgroParisTech, GABI, 78350 Jouy-en-Josas, France
| |
Collapse
|
28
|
van den Berg I, Ho PN, Nguyen TV, Haile-Mariam M, Luke TDW, Pryce JE. Using mid-infrared spectroscopy to increase GWAS power to detect QTL associated with blood urea nitrogen. Genet Sel Evol 2022; 54:27. [PMID: 35436852 PMCID: PMC9014603 DOI: 10.1186/s12711-022-00719-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 04/05/2022] [Indexed: 11/20/2022] Open
Abstract
Blood urea nitrogen (BUN) is an indicator trait for urinary nitrogen excretion. Measuring BUN level requires a blood sample, which limits the number of records that can be obtained. Alternatively, BUN can be predicted using mid-infrared (MIR) spectroscopy of a milk sample and thus records become available on many more cows through routine milk recording processes. The genetic correlation between MIR predicted BUN (MBUN) and BUN is 0.90. Hence, genetically, BUN and MBUN can be considered as the same trait. The objective of our study was to perform genome-wide association studies (GWAS) for BUN and MBUN, compare these two GWAS and detect quantitative trait loci (QTL) for both traits, and compare the detected QTL with previously reported QTL for milk urea nitrogen (MUN). The dataset used for our analyses included 2098 and 18,120 phenotypes for BUN and MBUN, respectively, and imputed whole-genome sequence data. The GWAS for MBUN was carried out using either the full dataset, the 2098 cows with records for BUN, or 2000 randomly selected cows, so that the dataset size is comparable to that for BUN. The GWAS results for BUN and MBUN were very different, in spite of the strong genetic correlation between the two traits. We detected 12 QTL for MBUN, on bovine chromosomes 2, 3, 9, 11, 12, 14 and X, and one QTL for BUN on chromosome 13. The QTL detected on chromosomes 11, 14 and X overlapped with QTL detected for MUN. The GWAS results were highly sensitive to the subset of records used. Hence, caution is warranted when interpreting GWAS based on small datasets, such as for BUN. MBUN may provide an attractive alternative to perform a more powerful GWAS to detect QTL for BUN.
Collapse
|
29
|
Yoshida GM, Yáñez JM. Increased accuracy of genomic predictions for growth under chronic thermal stress in rainbow trout by prioritizing variants from GWAS using imputed sequence data. Evol Appl 2022; 15:537-552. [PMID: 35505881 PMCID: PMC9046923 DOI: 10.1111/eva.13240] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 04/01/2021] [Accepted: 04/03/2021] [Indexed: 02/07/2023] Open
Abstract
Through imputation of genotypes, genome-wide association study (GWAS) and genomic prediction (GP) using whole-genome sequencing (WGS) data are cost-efficient and feasible in aquaculture breeding schemes. The objective was to dissect the genetic architecture of growth traits under chronic heat stress in rainbow trout (Oncorhynchus mykiss) and to assess the accuracy of GP based on imputed WGS and different preselected single nucleotide polymorphism (SNP) arrays. A total of 192 and 764 fish challenged to a heat stress experiment for 62 days were genotyped using a customized 1 K and 26 K SNP panels, respectively, and then, genotype imputation was performed from a low-density chip to WGS using 102 parents (36 males and 66 females) as the reference population. Imputed WGS data were used to perform GWAS and test GP accuracy under different preselected SNP scenarios. Heritability was estimated for body weight (BW), body length (BL) and average daily gain (ADG). Estimates using imputed WGS data ranged from 0.33 ± 0.05 to 0.55 ± 0.05 for growth traits under chronic heat stress. GWAS revealed that the top five cumulatively SNPs explained a maximum of 0.94%, 0.86% and 0.51% of genetic variance for BW, BL and ADG, respectively. Some important functional candidate genes associated with growth-related traits were found among the most important SNPs, including signal transducer and activator of transcription 5B and 3 (STAT5B and STAT3, respectively) and cytokine-inducible SH2-containing protein (CISH). WGS data resulted in a slight increase in prediction accuracy compared with pedigree-based method, whereas preselected SNPs based on the top GWAS hits improved prediction accuracies, with values ranging from 1.2 to 13.3%. Our results support the evidence of the polygenic nature of growth traits when measured under heat stress. The accuracies of GP can be improved using preselected variants from GWAS, and the use of WGS marginally increases prediction accuracy.
Collapse
Affiliation(s)
| | - José M. Yáñez
- Facultad de Ciencias Veterinarias y PecuariasUniversidad de ChileSantiagoChile
- Núcleo Milenio INVASALConcepciónChile
| |
Collapse
|
30
|
Cheruiyot EK, Haile-Mariam M, Cocks BG, MacLeod IM, Mrode R, Pryce JE. Functionally prioritised whole-genome sequence variants improve the accuracy of genomic prediction for heat tolerance. Genet Sel Evol 2022; 54:17. [PMID: 35183109 PMCID: PMC8858496 DOI: 10.1186/s12711-022-00708-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 02/03/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Heat tolerance is a trait of economic importance in the context of warm climates and the effects of global warming on livestock production, reproduction, health, and well-being. This study investigated the improvement in prediction accuracy for heat tolerance when selected sets of sequence variants from a large genome-wide association study (GWAS) were combined with a standard 50k single nucleotide polymorphism (SNP) panel used by the dairy industry. METHODS Over 40,000 dairy cattle with genotype and phenotype data were analysed. The phenotypes used to measure an individual's heat tolerance were defined as the rate of decline in milk production traits with rising temperature and humidity. We used Holstein and Jersey cows to select sequence variants linked to heat tolerance. The prioritised sequence variants were the most significant SNPs passing a GWAS p-value threshold selected based on sliding 100-kb windows along each chromosome. We used a bull reference set to develop the genomic prediction equations, which were then validated in an independent set of Holstein, Jersey, and crossbred cows. Prediction analyses were performed using the BayesR, BayesRC, and GBLUP methods. RESULTS The accuracy of genomic prediction for heat tolerance improved by up to 0.07, 0.05, and 0.10 units in Holstein, Jersey, and crossbred cows, respectively, when sets of selected sequence markers from Holstein cows were added to the 50k SNP panel. However, in some scenarios, the prediction accuracy decreased unexpectedly with the largest drop of - 0.10 units for the heat tolerance fat yield trait observed in Jersey cows when 50k plus pre-selected SNPs from Holstein cows were used. Using pre-selected SNPs discovered on a combined set of Holstein and Jersey cows generally improved the accuracy, especially in the Jersey validation. In addition, combining Holstein and Jersey bulls in the reference set generally improved prediction accuracy in most scenarios compared to using only Holstein bulls as the reference set. CONCLUSIONS Informative sequence markers can be prioritised to improve the genomic prediction of heat tolerance in different breeds. In addition to providing biological insight, these variants could also have a direct application for developing customized SNP arrays or can be used via imputation in current industry SNP panels.
Collapse
Affiliation(s)
- Evans K Cheruiyot
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia.,Agriculture Victoria Research, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, 3083, Australia
| | - Mekonnen Haile-Mariam
- Agriculture Victoria Research, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, 3083, Australia.
| | - Benjamin G Cocks
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia.,Agriculture Victoria Research, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, 3083, Australia
| | - Iona M MacLeod
- Agriculture Victoria Research, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, 3083, Australia
| | - Raphael Mrode
- International Livestock Research Institute, Nairobi, Kenya.,Scotland's Rural College, Edinburgh, UK
| | - Jennie E Pryce
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia.,Agriculture Victoria Research, AgriBio, Centre for AgriBiosciences, Bundoora, VIC, 3083, Australia
| |
Collapse
|
31
|
Talenti A, Powell J, Hemmink JD, Cook EAJ, Wragg D, Jayaraman S, Paxton E, Ezeasor C, Obishakin ET, Agusi ER, Tijjani A, Amanyire W, Muhanguzi D, Marshall K, Fisch A, Ferreira BR, Qasim A, Chaudhry U, Wiener P, Toye P, Morrison LJ, Connelley T, Prendergast JGD. A cattle graph genome incorporating global breed diversity. Nat Commun 2022; 13:910. [PMID: 35177600 PMCID: PMC8854726 DOI: 10.1038/s41467-022-28605-0] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 01/20/2022] [Indexed: 11/28/2022] Open
Abstract
Despite only 8% of cattle being found in Europe, European breeds dominate current genetic resources. This adversely impacts cattle research in other important global cattle breeds, especially those from Africa for which genomic resources are particularly limited, despite their disproportionate importance to the continent's economies. To mitigate this issue, we have generated assemblies of African breeds, which have been integrated with genomic data for 294 diverse cattle into a graph genome that incorporates global cattle diversity. We illustrate how this more representative reference assembly contains an extra 116.1 Mb (4.2%) of sequence absent from the current Hereford sequence and consequently inaccessible to current studies. We further demonstrate how using this graph genome increases read mapping rates, reduces allelic biases and improves the agreement of structural variant calling with independent optical mapping data. Consequently, we present an improved, more representative, reference assembly that will improve global cattle research.
Collapse
Affiliation(s)
- A Talenti
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK.
| | - J Powell
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - J D Hemmink
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
- The International Livestock Research Institute, PO Box 30709, Nairobi, Kenya
- Centre for Tropical Livestock Genetics and Health, Easter Bush, Midlothian, EH25 9RG, UK
- Centre for Tropical Livestock Genetics and Health, ILRI Kenya, Nairobi, 30709-00100, Kenya
| | - E A J Cook
- The International Livestock Research Institute, PO Box 30709, Nairobi, Kenya
- Centre for Tropical Livestock Genetics and Health, ILRI Kenya, Nairobi, 30709-00100, Kenya
| | - D Wragg
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
- Centre for Tropical Livestock Genetics and Health, Easter Bush, Midlothian, EH25 9RG, UK
| | - S Jayaraman
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - E Paxton
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - C Ezeasor
- Department of Veterinary Pathology and Microbiology, University of Nigeria, Nsukka, Enugu State, Nigeria
| | - E T Obishakin
- Biotechnology Division, National Veterinary Research Institute, Vom, Plateau State, Nigeria
- Biomedical Research Centre, Ghent University Global Campus, Songdo, Incheon, South Korea
| | - E R Agusi
- Biotechnology Division, National Veterinary Research Institute, Vom, Plateau State, Nigeria
- Biomedical Research Centre, Ghent University Global Campus, Songdo, Incheon, South Korea
| | - A Tijjani
- International Livestock Research Institute (ILRI) PO, 5689, Addis Ababa, Ethiopia
- Centre for Tropical Livestock Genetics and Health (CTLGH), ILRI Ethiopia, PO Box 5689, Addis Ababa, Ethiopia
| | - W Amanyire
- School of Biosecurity, Biotechnology and Laboratory Sciences (SBLS), College of Veterinary Medicine, Animal Resources and Biosecurity, Makerere University, P.O Box 7062, Kampala, Uganda
| | - D Muhanguzi
- School of Biosecurity, Biotechnology and Laboratory Sciences (SBLS), College of Veterinary Medicine, Animal Resources and Biosecurity, Makerere University, P.O Box 7062, Kampala, Uganda
| | - K Marshall
- The International Livestock Research Institute, PO Box 30709, Nairobi, Kenya
- Centre for Tropical Livestock Genetics and Health, ILRI Kenya, Nairobi, 30709-00100, Kenya
| | - A Fisch
- Ribeirão Preto College of Nursing, University of Sao Paulo, Ribeirão Preto, SP, Brazil
| | - B R Ferreira
- Ribeirão Preto College of Nursing, University of Sao Paulo, Ribeirão Preto, SP, Brazil
| | - A Qasim
- Faculty of Veterinary and Animal Sciences, Gomal University, Dera Ismail Khan, Pakistan
| | - U Chaudhry
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - P Wiener
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - P Toye
- The International Livestock Research Institute, PO Box 30709, Nairobi, Kenya
- Centre for Tropical Livestock Genetics and Health, ILRI Kenya, Nairobi, 30709-00100, Kenya
| | - L J Morrison
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
- Centre for Tropical Livestock Genetics and Health, Easter Bush, Midlothian, EH25 9RG, UK
| | - T Connelley
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
- Centre for Tropical Livestock Genetics and Health, Easter Bush, Midlothian, EH25 9RG, UK
| | - J G D Prendergast
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK.
- Centre for Tropical Livestock Genetics and Health, Easter Bush, Midlothian, EH25 9RG, UK.
| |
Collapse
|
32
|
Khanal P, Tempelman RJ. The use of milk Fourier-transform mid-infrared spectroscopy to diagnose pregnancy and determine spectral regional associations with pregnancy in US dairy cows. J Dairy Sci 2022; 105:3209-3221. [DOI: 10.3168/jds.2021-21079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 12/21/2021] [Indexed: 11/19/2022]
|
33
|
Lu X, Arbab AAI, Abdalla IM, Liu D, Zhang Z, Xu T, Su G, Yang Z. Genetic Parameter Estimation and Genome-Wide Association Study-Based Loci Identification of Milk-Related Traits in Chinese Holstein. Front Genet 2022; 12:799664. [PMID: 35154251 PMCID: PMC8836289 DOI: 10.3389/fgene.2021.799664] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 12/07/2021] [Indexed: 11/22/2022] Open
Abstract
Accurately estimating the genetic parameters and revealing more genetic variants underlying milk production and quality are conducive to the genetic improvement of dairy cows. In this study, we estimate the genetic parameters of five milk-related traits of cows-namely, milk yield (MY), milk fat percentage (MFP), milk fat yield (MFY), milk protein percentage (MPP), and milk protein yield (MPY)-based on a random regression test-day model. A total of 95,375 test-day records of 9,834 cows in the lower reaches of the Yangtze River were used for the estimation. In addition, genome-wide association studies (GWASs) for these traits were conducted, based on adjusted phenotypes. The heritability, as well as the standard errors, of MY, MFP, MFY, MPP, and MPY during lactation ranged from 0.22 ± 0.02 to 0.31 ± 0.04, 0.06 ± 0.02 to 0.15 ± 0.03, 0.09 ± 0.02 to 0.28 ± 0.04, 0.07 ± 0.01 to 0.16 ± 0.03, and 0.14 ± 0.02 to 0.27 ± 0.03, respectively, and the genetic correlations between different days in milk (DIM) within lactations decreased as the time interval increased. Two, six, four, six, and three single nucleotide polymorphisms (SNPs) were detected, which explained 5.44, 12.39, 8.89, 10.65, and 7.09% of the phenotypic variation in MY, MFP, MFY, MPP, and MPY, respectively. Ten Kyoto Encyclopedia of Genes and Genomes pathways and 25 Gene Ontology terms were enriched by analyzing the nearest genes and genes within 200 kb of the detected SNPs. Moreover, 17 genes in the enrichment results that may play roles in milk production and quality were selected as candidates, including CAMK2G, WNT3A, WNT9A, PLCB4, SMAD9, PLA2G4A, ARF1, OPLAH, MGST1, CLIP1, DGAT1, PRMT6, VPS28, HSF1, MAF1, TMEM98, and F7. We hope that this study will provide useful information for in-depth understanding of the genetic architecture of milk production and quality traits, as well as contribute to the genomic selection work of dairy cows in the lower reaches of the Yangtze River.
Collapse
Affiliation(s)
- Xubin Lu
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China
- Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, Denmark
| | | | | | - Dingding Liu
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Zhipeng Zhang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Tianle Xu
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou, China
| | - Guosheng Su
- Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, Denmark
| | - Zhangping Yang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| |
Collapse
|
34
|
Pedrosa VB, Schenkel FS, Chen SY, Oliveira HR, Casey TM, Melka MG, Brito LF. Genomewide Association Analyses of Lactation Persistency and Milk Production Traits in Holstein Cattle Based on Imputed Whole-Genome Sequence Data. Genes (Basel) 2021; 12:genes12111830. [PMID: 34828436 PMCID: PMC8624223 DOI: 10.3390/genes12111830] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 11/13/2021] [Accepted: 11/17/2021] [Indexed: 12/22/2022] Open
Abstract
Lactation persistency and milk production are among the most economically important traits in the dairy industry. In this study, we explored the association of over 6.1 million imputed whole-genome sequence variants with lactation persistency (LP), milk yield (MILK), fat yield (FAT), fat percentage (FAT%), protein yield (PROT), and protein percentage (PROT%) in North American Holstein cattle. We identified 49, 3991, 2607, 4459, 805, and 5519 SNPs significantly associated with LP, MILK, FAT, FAT%, PROT, and PROT%, respectively. Various known associations were confirmed while several novel candidate genes were also revealed, including ARHGAP35, NPAS1, TMEM160, ZC3H4, SAE1, ZMIZ1, PPIF, LDB2, ABI3, SERPINB6, and SERPINB9 for LP; NIM1K, ZNF131, GABRG1, GABRA2, DCHS1, and SPIDR for MILK; NR6A1, OLFML2A, EXT2, POLD1, GOT1, and ETV6 for FAT; DPP6, LRRC26, and the KCN gene family for FAT%; CDC14A, RTCA, HSTN, and ODAM for PROT; and HERC3, HERC5, LALBA, CCL28, and NEURL1 for PROT%. Most of these genes are involved in relevant gene ontology (GO) terms such as fatty acid homeostasis, transporter regulator activity, response to progesterone and estradiol, response to steroid hormones, and lactation. The significant genomic regions found contribute to a better understanding of the molecular mechanisms related to LP and milk production in North American Holstein cattle.
Collapse
Affiliation(s)
- Victor B. Pedrosa
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (V.B.P.); (S.-Y.C.); (H.R.O.); (T.M.C.)
- Department of Animal Sciences, State University of Ponta Grossa, Ponta Grossa 84030-900, Brazil
| | - Flavio S. Schenkel
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G2W1, Canada;
| | - Shi-Yi Chen
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (V.B.P.); (S.-Y.C.); (H.R.O.); (T.M.C.)
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science & Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Hinayah R. Oliveira
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (V.B.P.); (S.-Y.C.); (H.R.O.); (T.M.C.)
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G2W1, Canada;
| | - Theresa M. Casey
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (V.B.P.); (S.-Y.C.); (H.R.O.); (T.M.C.)
| | - Melkaye G. Melka
- Department of Animal and Food Science, University of Wisconsin River Falls, River Falls, WI 54022, USA;
| | - Luiz F. Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (V.B.P.); (S.-Y.C.); (H.R.O.); (T.M.C.)
- Correspondence:
| |
Collapse
|
35
|
Falchi L, Gaspa G, Cesarani A, Correddu F, Degano L, Vicario D, Lourenco D, Macciotta NPP. Investigation of β-hydroxybutyrate in early lactation of Simmental cows: Genetic parameters and genomic predictions. J Anim Breed Genet 2021; 138:708-718. [PMID: 34180560 PMCID: PMC8518359 DOI: 10.1111/jbg.12637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 05/28/2021] [Indexed: 11/28/2022]
Abstract
Genomic information allows for a more accurate calculation of relationships among animals than the pedigree information, leading to an increase in accuracy of breeding values. Here, we used pedigree-based and single-step genomic approaches to estimate variance components and breeding values for β-hydroxybutyrate milk content (BHB). Additionally, we performed a genome-wide association study (GWAS) to depict its genetic architecture. BHB concentrations within the first 90 days of lactation, estimated from milk medium infrared spectra, were available for 30,461 cows (70,984 records). Genotypes at 42,152 loci were available for 9,123 animals. Low heritabilities were found for BHB using pedigree-based (0.09 ± 0.01) and genomic (0.10 ± 0.01) approaches. Genetic correlation between BHB and milk traits ranged from -0.27 ± 0.06 (BHB and protein percentage) to 0.13 ± 0.07 (BHB and fat-to-protein ratio) using pedigree and from -0.26 ± 0.05 (BHB and protein percentage) to 0.13 ± 0.06 (BHB and fat-to-protein ratio) using genomics. Breeding values were validated for 344 genotyped cows using linear regression method. The genomic EBV (GEBV) had greater accuracy (0.51 vs. 0.45) and regression coefficient (0.98 vs. 0.95) compared to EBV. The correlation between two subsequent evaluations, without and with phenotypes for validation cows, was 0.85 for GEBV and 0.82 for EBV. Predictive ability (correlation between (G)EBV and adjusted phenotypes) was greater when genomic information was used (0.38) than in the pedigree-based approach (0.31). Validation statistics in the pairwise two-trait models (milk yield, fat and protein percentage, urea, fat/protein ratio, lactose and logarithmic transformation of somatic cells count) were very similar to the ones highlighted for the single-trait model. The GWAS allowed discovering four significant markers located on BTA20 (57.5-58.2 Mb), where the ANKH gene is mapped. This gene has been associated with lactose, alpha-lactalbumin and BHB. Results of this study confirmed the usefulness of genomic information to provide more accurate variance components and breeding values, and important insights about the genomic determination of BHB milk content.
Collapse
Affiliation(s)
- Laura Falchi
- Department of Agricultural SciencesUniversity of SassariSassariItaly
| | - Giustino Gaspa
- Department of Agricultural, Forest and Food SciencesUniversity of TorinoTorinoItaly
| | - Alberto Cesarani
- Department of Agricultural SciencesUniversity of SassariSassariItaly
- Department of Animal and Dairy ScienceUniversity of GeorgiaAthensGAUSA
| | - Fabio Correddu
- Department of Agricultural SciencesUniversity of SassariSassariItaly
| | - Lorenzo Degano
- Associazione Nazionale Allevatori Pezzata Rossa (ANAPRI)UdineItaly
| | - Daniele Vicario
- Associazione Nazionale Allevatori Pezzata Rossa (ANAPRI)UdineItaly
| | - Daniela Lourenco
- Department of Animal and Dairy ScienceUniversity of GeorgiaAthensGAUSA
| | | |
Collapse
|
36
|
In silico identification of variations in microRNAs with a potential impact on dairy traits using whole ruminant genome SNP datasets. Sci Rep 2021; 11:19580. [PMID: 34599210 PMCID: PMC8486775 DOI: 10.1038/s41598-021-98639-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 09/03/2021] [Indexed: 11/09/2022] Open
Abstract
MicroRNAs are small noncoding RNAs that have important roles in the lactation process and milk biosynthesis. Some polymorphisms have been studied in various livestock species from the perspective of pathology or production traits. To target variants that could be the causal variants of dairy traits, genetic variants of microRNAs expressed in the mammary gland or present in milk and localized in dairy quantitative trait loci (QTLs) were investigated in bovine, caprine, and ovine species. In this study, a total of 59,124 (out of 28 millions), 13,427 (out of 87 millions), and 4761 (out of 38 millions) genetic variants in microRNAs expressed in the mammary gland or present in milk were identified in bovine, caprine, and ovine species, respectively. A total of 4679 of these detected bovine genetic variants are located in dairy QTLs. In caprine species, 127 genetic variants are localized in dairy QTLs. In ovine species, no genetic variant was identified in dairy QTLs. This study leads to the detection of microRNA genetic variants of interest in the context of dairy production, taking advantage of whole genome data to identify microRNA genetic variants expressed in the mammary gland and localized in dairy QTLs.
Collapse
|
37
|
Ilie DE, Mizeranschi AE, Mihali CV, Neamț RI, Goilean GV, Georgescu OI, Zaharie D, Carabaș M, Huțu I. Genome-Wide Association Studies for Milk Somatic Cell Score in Romanian Dairy Cattle. Genes (Basel) 2021; 12:genes12101495. [PMID: 34680890 PMCID: PMC8535694 DOI: 10.3390/genes12101495] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 09/22/2021] [Accepted: 09/22/2021] [Indexed: 02/07/2023] Open
Abstract
Mastitis is one of the most frequently encountered diseases in dairy cattle, negatively affecting animal welfare and milk production. For this reason, contributions to understanding its genomic architecture are of great interest. Genome-wide association studies (GWAS) have identified multiple loci associated with somatic cell score (SCS) and mastitis in cattle. However, most of the studies have been conducted in different parts of the world on various breeds, and none of the investigations have studied the genetic architecture of mastitis in Romanian dairy cattle breeds up to this point in time. In this study, we report the first GWAS for SCS in dairy cattle breeds from Romania. For GWAS, we used an Axiom Bovine v3 SNP-chip (>63,000 Single Nucleotide Polymorphism -SNPs) and 33,330 records from 690 cows belonging to Romanian Spotted (RS) and Romanian Brown (RB) cattle. The results found one SNP significantly associated with SCS in the RS breed and 40 suggestive SNPs with -log10 (p) from 4 to 4.9 for RS and from 4 to 5.4 in RB. From these, 14 markers were located near 12 known genes (AKAP8, CLHC1, MEGF10, SATB2, GATA6, SPATA6, COL12A1, EPS8, LUZP2, RAMAC, IL12A and ANKRD55) in RB cattle, 3 markers were close to ZDHHC19, DAPK1 and MMP7 genes, while one SNP overlapped the HERC3 gene in RS cattle. Four genes (HERC3, LUZP2, AKAP8 and MEGF10) associated with SCS in this study were previously reported in different studies. The most significant SNP (rs110749552) associated with SCS was located within the HERC3 gene. In both breeds, the SNPs and position of association signals were distinct among the three parities, denoting that mastitis is controlled by different genes that are dependent according to parity. The current results contribute to an expansion in the body of knowledge regarding the proportion of genetic variability explained by SNPs for SCS in dairy cattle.
Collapse
Affiliation(s)
- Daniela Elena Ilie
- The Molecular Research Department, Research and Development Station for Bovine Arad, Bodrogului Street, No. 32, 310059 Arad, Romania; (A.E.M.); (C.V.M.); (R.I.N.); (G.V.G.)
- Faculty of Veterinary Medicine, Banat’s University of Agricultural Sciences and Veterinary Medicine “King Michael I of Romania” from Timisoara, Calea Aradului No. 119, 300645 Timisoara, Romania; (O.I.G.); (I.H.)
- Correspondence:
| | - Alexandru Eugeniu Mizeranschi
- The Molecular Research Department, Research and Development Station for Bovine Arad, Bodrogului Street, No. 32, 310059 Arad, Romania; (A.E.M.); (C.V.M.); (R.I.N.); (G.V.G.)
| | - Ciprian Valentin Mihali
- The Molecular Research Department, Research and Development Station for Bovine Arad, Bodrogului Street, No. 32, 310059 Arad, Romania; (A.E.M.); (C.V.M.); (R.I.N.); (G.V.G.)
| | - Radu Ionel Neamț
- The Molecular Research Department, Research and Development Station for Bovine Arad, Bodrogului Street, No. 32, 310059 Arad, Romania; (A.E.M.); (C.V.M.); (R.I.N.); (G.V.G.)
| | - George Vlad Goilean
- The Molecular Research Department, Research and Development Station for Bovine Arad, Bodrogului Street, No. 32, 310059 Arad, Romania; (A.E.M.); (C.V.M.); (R.I.N.); (G.V.G.)
| | - Ovidiu Ionuț Georgescu
- Faculty of Veterinary Medicine, Banat’s University of Agricultural Sciences and Veterinary Medicine “King Michael I of Romania” from Timisoara, Calea Aradului No. 119, 300645 Timisoara, Romania; (O.I.G.); (I.H.)
| | - Daniela Zaharie
- Faculty of Mathematics and Computer Science, West University of Timișoara, 300223 Timisoara, Romania;
| | - Mihai Carabaș
- Faculty of Automatic Control and Computer Science, Politehnica University of Bucharest, 060042 București, Romania;
| | - Ioan Huțu
- Faculty of Veterinary Medicine, Banat’s University of Agricultural Sciences and Veterinary Medicine “King Michael I of Romania” from Timisoara, Calea Aradului No. 119, 300645 Timisoara, Romania; (O.I.G.); (I.H.)
| |
Collapse
|
38
|
Marina H, Pelayo R, Suárez-Vega A, Gutiérrez-Gil B, Esteban-Blanco C, Arranz JJ. Genome-wide association studies (GWAS) and post-GWAS analyses for technological traits in Assaf and Churra dairy breeds. J Dairy Sci 2021; 104:11850-11866. [PMID: 34454756 DOI: 10.3168/jds.2021-20510] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 07/05/2021] [Indexed: 12/30/2022]
Abstract
This study aimed to perform a GWAS to identify genomic regions associated with milk and cheese-making traits in Assaf and Churra dairy sheep breeds; second, it aimed to identify possible positional and functional candidate genes and their interactions through post-GWAS studies. For 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra), milk samples were collected and analyzed to determine 6 milk production and composition traits and 6 traits related to milk coagulation properties and cheese yield. The genetic profiles of the ewes were obtained using a genotyping chip array that included 50,934 SNP markers. For both milk and cheese-making traits, separate single-breed GWAS were performed using GCTA software. The set of positional candidate genes identified via GWAS was subjected to guilt-by-association-based prioritization analysis with ToppGene software. Totals of 84 and 139 chromosome-wise significant associations for the 6 milk traits and the 6 cheese-making traits were identified in this study. No significant SNPs were found in common between the 2 studied breeds, possibly due to their genetic heterogeneity of the phenotypes under study. Additionally, 63 and 176 positional candidate genes were located in the genomic intervals defined as confidence regions in relation to the significant SNPs identified for the analyzed traits for Assaf and Churra breeds. After the functional prioritization analysis, 71 genes were identified as promising positional and functional candidate genes and proposed as targets of future research to identify putative causative variants in relation to the traits under examination. In addition, this multitrait study allowed us to identify variants that have a pleiotropic effect on both milk production and cheese-related traits. The incorporation of variants among the proposed functional and positional candidate genes into genomic selection strategies represent an interesting approach for achieving rapid genetic gains, specifically for those traits difficult to measure, such as cheese-making traits.
Collapse
Affiliation(s)
- H Marina
- Departamento de Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana s/n, León 24071, Spain
| | - R Pelayo
- Departamento de Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana s/n, León 24071, Spain
| | - A Suárez-Vega
- Departamento de Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana s/n, León 24071, Spain
| | - B Gutiérrez-Gil
- Departamento de Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana s/n, León 24071, Spain
| | - C Esteban-Blanco
- Departamento de Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana s/n, León 24071, Spain
| | - J J Arranz
- Departamento de Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana s/n, León 24071, Spain.
| |
Collapse
|
39
|
Johnsson M, Jungnickel MK. Evidence for and localization of proposed causative variants in cattle and pig genomes. Genet Sel Evol 2021; 53:67. [PMID: 34461824 PMCID: PMC8404348 DOI: 10.1186/s12711-021-00662-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 08/20/2021] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND This paper reviews the localization of published potential causative variants in contemporary pig and cattle reference genomes, and the evidence for their causality. In spite of the difficulties inherent to the identification of causative variants from genetic mapping and genome-wide association studies, researchers in animal genetics have proposed putative causative variants for several traits relevant to livestock breeding. RESULTS For this review, we read the literature that supports potential causative variants in 13 genes (ABCG2, DGAT1, GHR, IGF2, MC4R, MSTN, NR6A1, PHGK1, PRKAG3, PLRL, RYR1, SYNGR2 and VRTN) in cattle and pigs, and localized them in contemporary reference genomes. We review the evidence for their causality, by aiming to separate the evidence for the locus, the proposed causative gene and the proposed causative variant, and report the bioinformatic searches and tactics needed to localize the sequence variants in the cattle or pig genome. CONCLUSIONS Taken together, there is usually good evidence for the association at the locus level, some evidence for a specific causative gene at eight of the loci, and some experimental evidence for a specific causative variant at six of the loci. We recommend that researchers who report new potential causative variants use referenced coordinate systems, show local sequence context, and submit variants to repositories.
Collapse
Affiliation(s)
- Martin Johnsson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, 750 07 Uppsala, Sweden
| | - Melissa K. Jungnickel
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, EH25 9RG Scotland, UK
| |
Collapse
|
40
|
Yan G, Liu X, Xiao S, Xin W, Xu W, Li Y, Huang T, Qin J, Xie L, Ma J, Zhang Z, Huang L. An imputed whole-genome sequence-based GWAS approach pinpoints causal mutations for complex traits in a specific swine population. SCIENCE CHINA-LIFE SCIENCES 2021; 65:781-794. [PMID: 34387836 DOI: 10.1007/s11427-020-1960-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2021] [Accepted: 05/19/2021] [Indexed: 01/08/2023]
Abstract
Sequencing-based genome-wide association studies (GWAS) have facilitated the identification of causal associations between genetic variants and traits in diverse species. However, it is cost-prohibitive for the majority of research groups to sequence a large number of samples. Here, we carried out genotype imputation to increase the density of single nucleotide polymorphisms in a large-scale Swine F2 population using a reference panel including 117 individuals, followed by a series of GWAS analyses. The imputation accuracies reached 0.89 and 0.86 for allelic concordance and correlation, respectively. A quantitative trait nucleotide (QTN) affecting the chest vertebrate was detected directly, while the investigation of another QTN affecting the residual glucose failed due to the presence of similar haplotypes carrying wild-type and mutant allelesin the reference panel used in this study. A high imputation accuracy was confirmed by Sanger sequencing technology for the most significant loci. Two candidate genes, CPNE5 and MYH3, affecting meat-related traits were proposed. Collectively, we illustrated four scenarios in imputation-based GWAS that may be encountered by researchers, and our results will provide an extensive reference for future genotype imputation-based GWAS analyses in the future.
Collapse
Affiliation(s)
- Guorong Yan
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
- Institute of Photomedicine, Shanghai Skin Disease Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
| | - Xianxian Liu
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Shijun Xiao
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Wenshui Xin
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Wenwu Xu
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Yiping Li
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Tao Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Jiangtao Qin
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Lei Xie
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Junwu Ma
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Zhiyan Zhang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Lusheng Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| |
Collapse
|
41
|
Meta-analysis of genome-wide association studies and gene networks analysis for milk production traits in Holstein cows. Livest Sci 2021. [DOI: 10.1016/j.livsci.2021.104605] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
|
42
|
Tiplady KM, Lopdell TJ, Reynolds E, Sherlock RG, Keehan M, Johnson TJJ, Pryce JE, Davis SR, Spelman RJ, Harris BL, Garrick DJ, Littlejohn MD. Sequence-based genome-wide association study of individual milk mid-infrared wavenumbers in mixed-breed dairy cattle. Genet Sel Evol 2021; 53:62. [PMID: 34284721 PMCID: PMC8290608 DOI: 10.1186/s12711-021-00648-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 06/22/2021] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Fourier-transform mid-infrared (FT-MIR) spectroscopy provides a high-throughput and inexpensive method for predicting milk composition and other novel traits from milk samples. While there have been many genome-wide association studies (GWAS) conducted on FT-MIR predicted traits, there have been few GWAS for individual FT-MIR wavenumbers. Using imputed whole-genome sequence for 38,085 mixed-breed New Zealand dairy cattle, we conducted GWAS on 895 individual FT-MIR wavenumber phenotypes, and assessed the value of these direct phenotypes for identifying candidate causal genes and variants, and improving our understanding of the physico-chemical properties of milk. RESULTS Separate GWAS conducted for each of 895 individual FT-MIR wavenumber phenotypes, identified 450 1-Mbp genomic regions with significant FT-MIR wavenumber QTL, compared to 246 1-Mbp genomic regions with QTL identified for FT-MIR predicted milk composition traits. Use of mammary RNA-seq data and gene annotation information identified 38 co-localized and co-segregating expression QTL (eQTL), and 31 protein-sequence mutations for FT-MIR wavenumber phenotypes, the latter including a null mutation in the ABO gene that has a potential role in changing milk oligosaccharide profiles. For the candidate causative genes implicated in these analyses, we examined the strength of association between relevant loci and each wavenumber across the mid-infrared spectrum. This revealed shared association patterns for groups of genomically-distant loci, highlighting clusters of loci linked through their biological roles in lactation and their presumed impacts on the chemical composition of milk. CONCLUSIONS This study demonstrates the utility of FT-MIR wavenumber phenotypes for improving our understanding of milk composition, presenting a larger number of QTL and putative causative genes and variants than found from FT-MIR predicted composition traits. Examining patterns of significance across the mid-infrared spectrum for loci of interest further highlighted commonalities of association, which likely reflects the physico-chemical properties of milk constituents.
Collapse
Affiliation(s)
- Kathryn M. Tiplady
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
- School of Agriculture, Massey University, Ruakura, Hamilton, 3240 New Zealand
| | - Thomas J. Lopdell
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
| | - Edwardo Reynolds
- School of Agriculture, Massey University, Ruakura, Hamilton, 3240 New Zealand
| | - Richard G. Sherlock
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
| | - Michael Keehan
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
| | - Thomas JJ. Johnson
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
| | - Jennie E. Pryce
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083 Australia
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia
| | - Stephen R. Davis
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
| | - Richard J. Spelman
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
| | - Bevin L. Harris
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
| | - Dorian J. Garrick
- School of Agriculture, Massey University, Ruakura, Hamilton, 3240 New Zealand
| | - Mathew D. Littlejohn
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
- School of Agriculture, Massey University, Ruakura, Hamilton, 3240 New Zealand
| |
Collapse
|
43
|
A Large-Scale Genome-Wide Association Study of Epistasis Effects of Production Traits and Daughter Pregnancy Rate in U.S. Holstein Cattle. Genes (Basel) 2021; 12:genes12071089. [PMID: 34356105 PMCID: PMC8304971 DOI: 10.3390/genes12071089] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 07/14/2021] [Accepted: 07/14/2021] [Indexed: 11/22/2022] Open
Abstract
Epistasis is widely considered important, but epistasis studies lag those of SNP effects. Genome-wide association study (GWAS) using 76,109 SNPs and 294,079 first-lactation Holstein cows was conducted for testing pairwise epistasis effects of five production traits and three fertility traits: milk yield (MY), fat yield (FY), protein yield (PY), fat percentage (FPC), protein percentage (PPC), and daughter pregnancy rate (DPR). Among the top 50,000 pairwise epistasis effects of each trait, the five production traits had large chromosome regions with intra-chromosome epistasis. The percentage of inter-chromosome epistasis effects was 1.9% for FPC, 1.6% for PPC, 10.6% for MY, 29.9% for FY, 39.3% for PY, and 84.2% for DPR. Of the 50,000 epistasis effects, the number of significant effects with log10(1/p) ≥ 12 was 50,000 for FPC and PPC, and 10,508, 4763, 4637 and 1 for MY, FY, PY and DPR, respectively, and A × A effects were the most frequent epistasis effects for all traits. Majority of the inter-chromosome epistasis effects of FPC across all chromosomes involved a Chr14 region containing DGAT1, indicating a potential regulatory role of this Chr14 region affecting all chromosomes for FPC. The epistasis results provided new understanding about the genetic mechanism underlying quantitative traits in Holstein cattle.
Collapse
|
44
|
Lu X, Abdalla IM, Nazar M, Fan Y, Zhang Z, Wu X, Xu T, Yang Z. Genome-Wide Association Study on Reproduction-Related Body-Shape Traits of Chinese Holstein Cows. Animals (Basel) 2021; 11:1927. [PMID: 34203505 PMCID: PMC8300307 DOI: 10.3390/ani11071927] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 06/21/2021] [Accepted: 06/25/2021] [Indexed: 12/24/2022] Open
Abstract
Reproduction is an important production activity for dairy cows, and their reproductive performance can directly affect the level of farmers' income. To better understand the genomic regions and biological pathways of reproduction-related traits of dairy cows, in the present study, three body shape traits-Loin Strength (LS), Rump Angle (RA), and Pin Width (PW)-were selected as indicators of the reproductive ability of cows, and we conducted genome-wide association analyses on them. The heritability of these three traits was medium, ranging from 0.20 to 0.38. A total of 11 significant single-nucleotide polymorphisms (SNPs) were detected associated with these three traits. Bioinformatics analysis was performed on genes close to the significant SNPs (within 200 Kb) of LS, RA, and PW, and we found that these genes were totally enriched in 20 gene ontology terms and six KEGG signaling pathways. Finally, the five genes CDH12, TARP, PCDH9, DTHD1, and ARAP2 were selected as candidate genes that might affect LS. The six genes LOC781835, FSTL4, ATG4C, SH3BP4, DMP1, and DSPP were selected as candidate genes that might affect RA. The five genes USP6NL, CNTN3, LOC101907665, UPF2, and ECHDC3 were selected as candidate genes that might affect the PW of Chinese Holstein cows. Our results could provide useful biological information for the improvement of body shape traits and contribute to the genomic selection of Chinese Holstein cows.
Collapse
Affiliation(s)
- Xubin Lu
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225002, China; (X.L.); (I.M.A.); (M.N.); (Y.F.); (Z.Z.); (X.W.)
| | - Ismail Mohamed Abdalla
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225002, China; (X.L.); (I.M.A.); (M.N.); (Y.F.); (Z.Z.); (X.W.)
| | - Mudasir Nazar
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225002, China; (X.L.); (I.M.A.); (M.N.); (Y.F.); (Z.Z.); (X.W.)
| | - Yongliang Fan
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225002, China; (X.L.); (I.M.A.); (M.N.); (Y.F.); (Z.Z.); (X.W.)
| | - Zhipeng Zhang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225002, China; (X.L.); (I.M.A.); (M.N.); (Y.F.); (Z.Z.); (X.W.)
| | - Xinyue Wu
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225002, China; (X.L.); (I.M.A.); (M.N.); (Y.F.); (Z.Z.); (X.W.)
| | - Tianle Xu
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou 225009, China;
| | - Zhangping Yang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225002, China; (X.L.); (I.M.A.); (M.N.); (Y.F.); (Z.Z.); (X.W.)
| |
Collapse
|
45
|
Kim S, Lim B, Cho J, Lee S, Dang CG, Jeon JH, Kim JM, Lee J. Genome-Wide Identification of Candidate Genes for Milk Production Traits in Korean Holstein Cattle. Animals (Basel) 2021; 11:ani11051392. [PMID: 34068321 PMCID: PMC8153329 DOI: 10.3390/ani11051392] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 05/07/2021] [Accepted: 05/11/2021] [Indexed: 12/12/2022] Open
Abstract
Simple Summary Milk production traits that are economically important in the dairy industry have been considered the main selection criteria for breeding. The present genome-wide association study was performed to identify chromosomal loci and candidate genes with potential effects on milk production phenotypes in a Korean Holstein population. A total of eight significant quantitative trait locus regions were identified for milk yield (Bos taurus autosome (BTA) 7 and 14), adjusted 305-d fat yield (BTA 3, 5, and 14), adjusted 305-d protein yield (BTA 8), and somatic cell score (BTA 8 and 23) of milk production traits. Furthermore, we discovered three main candidate genes (diacylglycerol O-acyltransferase 1 (DGAT1), phosphodiesterase 4B (PDE4B), and anoctamin 2 (ANO2)) through bioinformatics analysis. These genes may help to understand better the underlying genetic and molecular mechanisms for milk production phenotypes in the Korean Holstein population. Abstract We performed a genome-wide association study and fine mapping using two methods (single marker regression: frequentist approach and Bayesian C (BayesC): fitting selected single nucleotide polymorphisms (SNPs) in a Bayesian framework) through three high-density SNP chip platforms to analyze milk production phenotypes in Korean Holstein cattle (n = 2780). We identified four significant SNPs for each phenotype in the single marker regression model: AX-311625843 and AX-115099068 on Bos taurus autosome (BTA) 14 for milk yield (MY) and adjusted 305-d fat yield (FY), respectively, AX-428357234 on BTA 18 for adjusted 305-d protein yield (PY), and AX-185120896 on BTA 5 for somatic cell score (SCS). Using the BayesC model, we discovered significant 1-Mb window regions that harbored over 0.5% of the additive genetic variance effects for four milk production phenotypes. The concordant significant SNPs and 1-Mb window regions were characterized into quantitative trait loci (QTL). Among the QTL regions, we focused on a well-known gene (diacylglycerol O-acyltransferase 1 (DGAT1)) and newly identified genes (phosphodiesterase 4B (PDE4B), and anoctamin 2 (ANO2)) for MY and FY, and observed that DGAT1 is involved in glycerolipid metabolism, fat digestion and absorption, metabolic pathways, and retinol metabolism, and PDE4B is involved in cAMP signaling. Our findings suggest that the candidate genes in QTL are strongly related to physiological mechanisms related to the fat production and consequent total MY in Korean Holstein cattle.
Collapse
Affiliation(s)
- Sangwook Kim
- Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Gyeonggi-do, Korea; (S.K.); (B.L.)
| | - Byeonghwi Lim
- Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Gyeonggi-do, Korea; (S.K.); (B.L.)
| | - Joohyeon Cho
- Dairy Cattle Genetic Improvement Center, Nonghyup, Goyang 10292, Gyeonggi-do, Korea; (J.C.); (S.L.)
| | - Seokhyun Lee
- Dairy Cattle Genetic Improvement Center, Nonghyup, Goyang 10292, Gyeonggi-do, Korea; (J.C.); (S.L.)
| | - Chang-Gwon Dang
- Animal Genetics and Breeding Division, National Institute of Animal Science, RDA, Cheonan 31000, Chungcheongnam-do, Korea;
| | - Jung-Hwan Jeon
- Animal Welfare Research Team, National Institute of Animal Science, RDA, Wanju 55365, Jeollabuk-do, Korea;
| | - Jun-Mo Kim
- Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Gyeonggi-do, Korea; (S.K.); (B.L.)
- Correspondence: (J.-M.K.); (J.L.); Tel.: +82-31-670-3263 (J.-M.K. & J.L.); Fax: +82-31-675-3108 (J.-M.K. & J.L.)
| | - Jungjae Lee
- Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Gyeonggi-do, Korea; (S.K.); (B.L.)
- Correspondence: (J.-M.K.); (J.L.); Tel.: +82-31-670-3263 (J.-M.K. & J.L.); Fax: +82-31-675-3108 (J.-M.K. & J.L.)
| |
Collapse
|
46
|
Sequence-based GWAS and post-GWAS analyses reveal a key role of SLC37A1, ANKH, and regulatory regions on bovine milk mineral content. Sci Rep 2021; 11:7537. [PMID: 33824377 PMCID: PMC8024349 DOI: 10.1038/s41598-021-87078-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 03/23/2021] [Indexed: 12/14/2022] Open
Abstract
The mineral composition of bovine milk plays an important role in determining its nutritional and cheese-making value. Concentrations of the main minerals predicted from mid-infrared spectra produced during milk recording, combined with cow genotypes, provide a unique opportunity to decipher the genetic determinism of these traits. The present study included 1 million test-day predictions of Ca, Mg, P, K, Na, and citrate content from 126,876 Montbéliarde cows, of which 19,586 had genotype data available. All investigated traits were highly heritable (0.50-0.58), with the exception of Na (0.32). A sequence-based genome-wide association study (GWAS) detected 50 QTL (18 affecting two to five traits) and positional candidate genes and variants, mostly located in non-coding sequences. In silico post-GWAS analyses highlighted 877 variants that could be regulatory SNPs altering transcription factor (TF) binding sites or located in non-coding RNA (mainly lncRNA). Furthermore, we found 47 positional candidate genes and 45 TFs highly expressed in mammary gland compared to 90 other bovine tissues. Among the mammary-specific genes, SLC37A1 and ANKH, encoding proteins involved in ion transport were located in the most significant QTL. This study therefore highlights a comprehensive set of functional candidate genes and variants that affect milk mineral content.
Collapse
|
47
|
Identification of Genomic Regions Associated with Concentrations of Milk Fat, Protein, Urea and Efficiency of Crude Protein Utilization in Grazing Dairy Cows. Genes (Basel) 2021; 12:genes12030456. [PMID: 33806889 PMCID: PMC8004844 DOI: 10.3390/genes12030456] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 03/16/2021] [Accepted: 03/19/2021] [Indexed: 01/01/2023] Open
Abstract
The objective of this study was to identify genomic regions associated with milk fat percentage (FP), crude protein percentage (CPP), urea concentration (MU) and efficiency of crude protein utilization (ECPU: ratio between crude protein yield in milk and dietary crude protein intake) using grazing, mixed-breed, dairy cows in New Zealand. Phenotypes from 634 Holstein Friesian, Jersey or crossbred cows were obtained from two herds at Massey University. A subset of 490 of these cows was genotyped using Bovine Illumina 50K SNP-chips. Two genome-wise association approaches were used, a single-locus model fitted to data from 490 cows and a single-step Bayes C model fitted to data from all 634 cows. The single-locus analysis was performed with the Efficient Mixed-Model Association eXpedited model as implemented in the SVS package. Single nucleotide polymorphisms (SNPs) with genome-wide association p-values ≤ 1.11 × 10−6 were considered as putative quantitative trait loci (QTL). The Bayes C analysis was performed with the JWAS package and 1-Mb genomic windows containing SNPs that explained > 0.37% of the genetic variance were considered as putative QTL. Candidate genes within 100 kb from the identified SNPs in single-locus GWAS or the 1-Mb windows were identified using gene ontology, as implemented in the Ensembl Genome Browser. The genes detected in association with FP (MGST1, DGAT1, CEBPD, SLC52A2, GPAT4, and ACOX3) and CPP (DGAT1, CSN1S1, GOSR2, HERC6, and IGF1R) were identified as candidates. Gene ontology revealed six novel candidate genes (GMDS, E2F7, SIAH1, SLC24A4, LGMN, and ASS1) significantly associated with MU whose functions were in protein catabolism, urea cycle, ion transportation and N excretion. One novel candidate gene was identified in association with ECPU (MAP3K1) that is involved in post-transcriptional modification of proteins. The findings should be validated using a larger population of New Zealand grazing dairy cows.
Collapse
|
48
|
Pegolo S, Yu H, Morota G, Bisutti V, Rosa GJM, Bittante G, Cecchinato A. Structural equation modeling for unraveling the multivariate genomic architecture of milk proteins in dairy cattle. J Dairy Sci 2021; 104:5705-5718. [PMID: 33663837 DOI: 10.3168/jds.2020-18321] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Accepted: 12/31/2020] [Indexed: 01/28/2023]
Abstract
The aims of this study were to investigate potential functional relationships among milk protein fractions in dairy cattle and to carry out a structural equation model (SEM) GWAS to provide a decomposition of total SNP effects into direct effects and effects mediated by traits that are upstream in a phenotypic network. To achieve these aims, we first fitted a mixed Bayesian multitrait genomic model to infer the genomic correlations among 6 milk nitrogen fractions [4 caseins (CN), namely κ-, β-, αS1-, and αS2-CN, and 2 whey proteins, namely β-lactoglobulin (β-LG) and α-lactalbumin (α-LA)], in a population of 989 Italian Brown Swiss cows. Animals were genotyped with the Illumina BovineSNP50 Bead Chip v.2 (Illumina Inc.). A Bayesian network approach using the max-min hill-climbing (MMHC) algorithm was implemented to model the dependencies or independence among traits. Strong and negative genomic correlations were found between β-CN and αS1-CN (-0.706) and between β-CN and κ-CN (-0.735). The application of the MMHC algorithm revealed that κ-CN and β-CN seemed to directly or indirectly influence all other milk protein fractions. By integrating multitrait model GWAS and SEM-GWAS, we identified a total of 127 significant SNP for κ-CN, 89 SNP for β-CN, 30 SNP for αS1-CN, and 14 SNP for αS2-CN (mostly shared among CN and located on Bos taurus autosome 6) and 15 SNP for β-LG (mostly located on Bos taurus autosome 11), whereas no SNP passed the significance threshold for α-LA. For the significant SNP, we assessed and quantified the contribution of direct and indirect paths to total marker effect. Pathway analyses confirmed that common regulatory mechanisms (e.g., energy metabolism and hormonal and neural signals) are involved in the control of milk protein synthesis and metabolism. The information acquired might be leveraged for setting up optimal management and selection strategies aimed at improving milk quality and technological characteristics in dairy cattle.
Collapse
Affiliation(s)
- Sara Pegolo
- Department of Agronomy, Food Natural Resources, Animals and Environment, University of Padua, 35020 Legnaro (PD), Italy.
| | - Haipeng Yu
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg 24061
| | - Gota Morota
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg 24061
| | - Vittoria Bisutti
- Department of Agronomy, Food Natural Resources, Animals and Environment, University of Padua, 35020 Legnaro (PD), Italy
| | - Guilherme J M Rosa
- Department of Animal and Dairy Sciences, University of Wisconsin, Madison 53706; Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison 53792
| | - Giovanni Bittante
- Department of Agronomy, Food Natural Resources, Animals and Environment, University of Padua, 35020 Legnaro (PD), Italy
| | - Alessio Cecchinato
- Department of Agronomy, Food Natural Resources, Animals and Environment, University of Padua, 35020 Legnaro (PD), Italy
| |
Collapse
|
49
|
Luo H, Li X, Hu L, Xu W, Chu Q, Liu A, Guo G, Liu L, Brito LF, Wang Y. Genomic analyses and biological validation of candidate genes for rectal temperature as an indicator of heat stress in Holstein cattle. J Dairy Sci 2021; 104:4441-4451. [PMID: 33589260 DOI: 10.3168/jds.2020-18725] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 11/15/2020] [Indexed: 12/26/2022]
Abstract
Heat stress is a major cause of welfare issues and economic losses to the worldwide dairy cattle industry. Genetic selection for heat tolerance has a great potential to positively affect the dairy industry, as the gains are permanent and cumulative over generations. Rectal temperature (RT) is hypothesized to be a good indicator trait of heat tolerance. Therefore, this study investigated the genetic architecture of RT by estimating genetic parameters, performing genome-wide association studies, and biologically validating potential candidate genes identified to be related to RT in Holstein cattle. A total of 33,013 RT records from 7,598 cows were used in this study. In addition, 1,114 cows were genotyped using the Illumina 150K Bovine BeadChip (Illumina, San Diego, CA). Rectal temperature measurements taken in the morning (AMRT) and in the afternoon (PMRT) are moderately heritable traits, with estimates of 0.09 ± 0.02 and 0.04 ± 0.01, respectively. These 2 traits are also highly genetically correlated (r = 0.90 ± 0.08). A total of 10 SNPs (located on BTA3, BTA4, BTA8, BTA13, BTA14, and BTA29) were found to be significantly associated with AMRT and PMRT. Subsequently, gene expression analyses were performed to validate the key functional genes identified (SPAG17, FAM107B, TSNARE1, RALYL, and PHRF1). This was done through in vitro exposure of peripheral blood mononuclear cells (PBMC) to different temperatures (37°C, 39°C, and 42°C). The relative mRNA expression of 2 genes, FAM107B and PHRF1, significantly changed between the control and heat stressed PBMC. In summary, RT is heritable, and enough genetic variability exists to enable genetic improvement of heat tolerance in Holstein cattle. Important genomic regions were identified and biologically validated; FAM107B and PHRF1 are the main candidate genes identified to influence heat stress response in dairy cattle.
Collapse
Affiliation(s)
- Hanpeng Luo
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - Xiang Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - Lirong Hu
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - Wei Xu
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - Qin Chu
- Institute of Animal Husbandry and Veterinary Medicine, Beijing Academy of Agriculture and Forestry Sciences, 100097, Beijing, China
| | - Aoxing Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China; Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830, Tjele, Denmark
| | - Gang Guo
- Beijing Sunlon Livestock Development Company Limited, 100029, Beijing, China
| | - Lin Liu
- Beijing Dairy Cattle Center, 100192, Beijing, China
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907
| | - Yachun Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China.
| |
Collapse
|
50
|
Influence of the kappa casein genotype on the technological properties of cow milk of Simmental and Alatau breeds. Funct Integr Genomics 2021; 21:231-238. [PMID: 33543401 DOI: 10.1007/s10142-021-00772-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 01/25/2021] [Accepted: 01/30/2021] [Indexed: 12/21/2022]
Abstract
The main objective of dairy farming is to obtain highly productive animals that produce milk with high protein content and have good technological properties. Currently, with the development of molecular genetics and molecular biology, it is possible to identify genes directly or indirectly associated with the milk production of animals. The identification of variants of such genes that are preferable from the standpoint of selection will allow, apart from the conventional selection of animals, to perform selection at the level of deoxyribonucleic acid technologies, i.e. according to genotype. The paper includes the study of milk productivity indicators and physicochemical quality indicators of milk from cows of Simmental and Alatau breeds by loci of the kappa casein gene, and also determines the cheese suitability and technological properties of milk of cows of Simmental and Alatau breeds with different genotypic affiliations for kappa casein for the production of semi-hard cheeses. The determination of polymorphism by the kappa casein gene was carried out with the use of the polymerase chain reaction method for genotyping of the major milk proteins of kappa casein gene. In a comparative aspect, the interrelation of genotypes with milk productivity was studied, the frequencies of allelic polymorphism of cows of Simmental and Alatau breeds in the Republic of Kazakhstan were identified, the nature of milk productivity was determined for each genotype. Scientifically based data on the assessment of biological value, technological properties, cheese suitability of milk of cows of Simmental and Alatau breeds are obtained.
Collapse
|