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Zhu L, Shen S, Pan C, Lan X, Li J. Bovine FRAS1: mRNA Expression Profile, Genetic Variations, and Significant Correlations with Ovarian Morphological Traits, Mature Follicle, and Corpus Luteum. Animals (Basel) 2024; 14:597. [PMID: 38396565 PMCID: PMC10886075 DOI: 10.3390/ani14040597] [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: 01/03/2024] [Revised: 01/29/2024] [Accepted: 02/03/2024] [Indexed: 02/25/2024] Open
Abstract
The amelioration of bovine fertility caused by a multi-factorial problem has always been a hot topic, among which the detection of available target genes is the most crucial. It was hypothesized that the Fraser extracellular matrix complex subunit 1 (FRAS1) gene detected by GWAS is involved in physiological activities such as ovarian development. Herein, unilateral ovaries from 2111 cows were used to examine the mRNA expression profile and polymorphisms of bovine FRAS1 and their associations with fertility-related characteristics. Firstly, it was confirmed that FRAS1 gene transcripts are expressed in various bovine tissues. Then, among five potential insertion-deletion (indel) loci, the 20 bp (named P3-D20-bp) and 15 bp (P4-D15-bp) deletion mutations were confirmed to be polymorphic with linkage equilibrium. Secondly, the P3-D20-bp polymorphism was significantly associated with ovarian weight and corpus luteum diameter in the metaestrus phase and ovarian length in the dioestrum stage. Additionally, both ovarian length and mature follicle diameter in metaestrus are significantly correlated with different genotypes of P4-D15-bp. Thirdly, the transcriptional expression of the FRAS1 gene in groups with a minimum value of ovarian weight or volume was significantly higher than the expression in groups with a maximum value. Instead of that, the more corpus luteum and mature follicles there are, the higher the transcription expression of the FRAS1 gene is. Furthermore, FRAS1 expression in cows with a heterozygous genotype (ID) of P3-D20-bp was significantly higher than others. Eventually, P3-D20-bp deletion could disturb the binding efficiency of WT1-I and Sox2 to FRAS1 sequence according to binding prediction, indicating that mutation may affect gene expression and traits by influencing the binding of transcription factors. Overall, the polymorphisms of P3-D20-bp and P4-D15-bp of the bovine FRAS1 gene significantly correlated to follicle or ovarian traits that could be applied in optimizing female fertility in cow MAS breeding programs.
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Affiliation(s)
| | | | | | - Xianyong Lan
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China; (L.Z.); (S.S.); (C.P.)
| | - Jie Li
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China; (L.Z.); (S.S.); (C.P.)
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2
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Kurta K, Jeuthe H, Naboulsi R, de Koning DJ, Palaiokostas C. Seasonal and age-related changes in sperm quality of farmed arctic charr (Salvelinus alpinus). BMC Genomics 2023; 24:519. [PMID: 37667174 PMCID: PMC10478403 DOI: 10.1186/s12864-023-09614-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 08/22/2023] [Indexed: 09/06/2023] Open
Abstract
BACKGROUND Substantial variation in male fertility is regularly observed in farmed Arctic charr. However, detailed investigations of its fluctuation during a reproductive season and across years are lacking. Furthermore, information about the effect of underlying genetic factors influencing sperm quality is scarce. The current study focused on seasonal and age-related factors that may affect sperm quality characteristics in males reared in natural and delayed photoperiods. Animals were sampled three times for two consecutive years, and sperm quality parameters were recorded using a computer-assisted sperm analysis (CASA) system. Thereafter, high-throughput sequencing technologies were applied, aiming to identify genomic regions related to the variation of sperm quality throughout the reproductive season. RESULTS An across-season variation in the recorded sperm quality parameters was evident. Overall, 29% and 42% of males from the natural and delayed spawning groups had a highly variable total progressive motility. Males at four years of age showed significantly higher sperm motility and velocities during the early October and November recordings compared to the following year when the same animals were five years of age. On the other hand, the opposite was observed regarding sperm concentration during the last sampling. A genome-wide FST scan detected SNP differentiation among males with high and low variability in total progressive motility (PM) on eight chromosomes (FST > 0.17), Genome wide windows with the highest FST contained SNPs in proximity (within 250 kb up- and downstream distance) to 16 genes with sperm quality biological functions in mammalian species. CONCLUSION Our findings provide a detailed view of seasonal, age-related, and genetic effects on sperm quality and can be used to guide decisions on broodstock selection and hatchery management.
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Affiliation(s)
- Khrystyna Kurta
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7090, Uppsala, 750 07, Sweden.
- Department of Medical Biochemistry and Microbiology, Genetics and genomics, Uppsala University, Uppsala, Sweden.
| | - Henrik Jeuthe
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7090, Uppsala, 750 07, Sweden
- Aquaculture Center North, Åvägen 17, Kälarne, 844 61, Sweden
| | - Rakan Naboulsi
- Department of Women's and Children's Health, Karolinska Institute, Tomtebodavägen 18A, Stockholm, 17177, Sweden
| | - Dirk-Jan de Koning
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7090, Uppsala, 750 07, Sweden
| | - Christos Palaiokostas
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7090, Uppsala, 750 07, Sweden
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Atashi H, Chen Y, Wilmot H, Vanderick S, Hubin X, Soyeurt H, Gengler N. Single-step genome-wide association for selected milk fatty acids in Dual-Purpose Belgian Blue cows. J Dairy Sci 2023; 106:6299-6315. [PMID: 37479585 DOI: 10.3168/jds.2022-22432] [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: 06/20/2022] [Accepted: 03/17/2023] [Indexed: 07/23/2023]
Abstract
The aim of this study was to estimate genetic parameters and identify genomic regions associated with selected individual and groups of milk fatty acids (FA) predicted by milk mid-infrared spectrometry in Dual-Purpose Belgian Blue cows. The used data were 69,349 test-day records of milk yield, fat percentage, and protein percentage along with selected individual and groups FA of milk (g/dL milk) collected from 2007 to 2020 on 7,392 first-parity (40,903 test-day records), and 5,185 second-parity (28,446 test-day records) cows distributed in 104 herds in the Walloon Region of Belgium. Data of 28,466 SNPs, located on 29 Bos taurus autosomes (BTA), of 1,699 animals (639 males and 1,060 females) 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 best linear unbiased prediction approach. The proportion of genetic variance explained by each 25-SNP sliding window (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. Average daily heritability estimated for the included milk FA traits ranged from 0.01 (C4:0) to 0.48 (C12:0) and 0.01 (C4:0) to 0.42 (C12:0) in the first and second parities, respectively. Genetic correlations found between milk yield and the studied individual milk FA, except for C18:0, C18:1 trans, C18:1 cis-9, were positive. The results showed that fat percentage and protein percentage were positively genetically correlated with all studied individual milk FA. Genome-wide association analyses identified 11 genomic regions distributed over 8 chromosomes [BTA1, BTA4, BTA10, BTA14 (4 regions), BTA19, BTA22, BTA24, and BTA26] associated with the studied FA traits, though those found on BTA14 partly overlapped. The genomic regions identified differed between parities and lactation stages. Although these differences in genomic regions detected may be due to the power of quantitative trait locus detection, it also suggests that candidate genes underlie the phenotypic expression of the studied traits may vary between parities and lactation stages. These findings increase our understanding about the genetic background of milk FA and can be used for the future implementation of genomic evaluation to improve milk FA profile in Dual-Purpose Belgian Blue cows.
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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 (F.R.S.-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
| | - H Soyeurt
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - N Gengler
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
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Khan MZ, Ma Y, Ma J, Xiao J, Liu Y, Liu S, Khan A, Khan IM, Cao Z. Association of DGAT1 With Cattle, Buffalo, Goat, and Sheep Milk and Meat Production Traits. Front Vet Sci 2021; 8:712470. [PMID: 34485439 PMCID: PMC8415568 DOI: 10.3389/fvets.2021.712470] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 07/19/2021] [Indexed: 12/26/2022] Open
Abstract
Milk fatty acids are essential for many dairy product productions, while intramuscular fat (IMF) is associated with the quality of meat. The triacylglycerols (TAGs) are the major components of IMF and milk fat. Therefore, understanding the polymorphisms and genes linked to fat synthesis is important for animal production. Identifying quantitative trait loci (QTLs) and genes associated with milk and meat production traits has been the objective of various mapping studies in the last decade. Consistently, the QTLs on chromosomes 14, 15, and 9 have been found to be associated with milk and meat production traits in cattle, goat, and buffalo and sheep, respectively. Diacylglycerol O-acyltransferase 1 (DGAT1) gene has been reported on chromosomes 14, 15, and 9 in cattle, goat, and buffalo and sheep, respectively. Being a key role in fat metabolism and TAG synthesis, the DGAT1 has obtained considerable attention especially in animal milk production. In addition to milk production, DGAT1 has also been a subject of interest in animal meat production. Several polymorphisms have been documented in DGAT1 in various animal species including cattle, buffalo, goat, and sheep for their association with milk production traits. In addition, the DGAT1 has also been studied for their role in meat production traits in cattle, sheep, and goat. However, very limited studies have been conducted in cattle for association of DGAT1 with meat production traits in cattle. Moreover, not a single study reported the association of DGAT1 with meat production traits in buffalo; thus, further studies are warranted to fulfill this huge gap. Keeping in view the important role of DGAT1 in animal production, the current review article was designed to highlight the major development and new insights on DGAT1 effect on milk and meat production traits in cattle, buffalo, sheep, and goat. Moreover, we have also highlighted the possible future contributions of DGAT1 for the studied species.
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Affiliation(s)
- Muhammad Zahoor Khan
- State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China
- Faculty of Veterinary and Animal Sciences, Gomal University, Dera Ismail Khan, Pakistan
| | - Yulin Ma
- State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Jiaying Ma
- State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Jianxin Xiao
- State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Yue Liu
- State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Shuai Liu
- State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Adnan Khan
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Ibrar Muhammad Khan
- Anhui Provincial Laboratory of Local Livestock and Poultry Genetical Resource Conservation and Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, China
| | - Zhijun Cao
- State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China
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Korkuć P, Arends D, May K, König S, Brockmann GA. Genomic Loci Affecting Milk Production in German Black Pied Cattle (DSN). Front Genet 2021; 12:640039. [PMID: 33763120 PMCID: PMC7982544 DOI: 10.3389/fgene.2021.640039] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 02/11/2021] [Indexed: 01/14/2023] Open
Abstract
German Black Pied cattle (DSN) is an endangered population of about 2,550 dual-purpose cattle in Germany. Having a milk yield of about 2,500 kg less than the predominant dairy breed Holstein, the preservation of DSN is supported by the German government and the EU. The identification of the genomic loci affecting milk production in DSN can provide a basis for selection decisions for genetic improvement of DSN in order to increase market chances through the improvement of milk yield. A genome-wide association analysis of 30 milk traits was conducted in different lactation periods and numbers. Association using multiple linear regression models in R was performed on 1,490 DSN cattle genotyped with BovineSNP50 SNP-chip. 41 significant and 20 suggestive SNPs affecting milk production traits in DSN were identified, as well as 15 additional SNPs for protein content which are less reliable due to high inflation. The most significant effects on milk yield in DSN were detected on chromosomes 1, 6, and 20. The region on chromosome 6 was located nearby the casein gene cluster and the corresponding haplotype overlapped the CSN3 gene (casein kappa). Associations for fat and protein yield and content were also detected. High correlation between traits of the same lactation period or number led to some SNPs being significant for multiple investigated traits. Half of all identified SNPs have been reported in other studies, previously. 15 SNPs were associated with the same traits in other breeds. The other associated SNPs have been reported previously for traits such as exterior, health, meat and carcass, production, and reproduction traits. No association could be detected between DGAT1 and other known milk genes with milk production traits despite the close relationship between DSN and Holstein. The results of this study confirmed that many SNPs identified in other breeds as associated with milk traits also affect milk traits in dual-purpose DSN cattle and can be used for further genetic analysis to identify genes and causal variants that affect milk production in DSN cattle.
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Affiliation(s)
- Paula Korkuć
- Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Animal Breeding Biology and Molecular Genetics, Humboldt University Berlin, Berlin, Germany
| | - Danny Arends
- Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Animal Breeding Biology and Molecular Genetics, Humboldt University Berlin, Berlin, Germany
| | - Katharina May
- Institute of Animal Breeding and Genetics, Justus-Liebig-University of Giessen, Giessen, Germany
| | - Sven König
- Institute of Animal Breeding and Genetics, Justus-Liebig-University of Giessen, Giessen, Germany
| | - Gudrun A Brockmann
- Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Animal Breeding Biology and Molecular Genetics, Humboldt University Berlin, Berlin, Germany
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6
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Gutierrez-Reinoso MA, Aponte PM, Garcia-Herreros M. Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review. Animals (Basel) 2021; 11:599. [PMID: 33668747 PMCID: PMC7996307 DOI: 10.3390/ani11030599] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 11/23/2020] [Accepted: 11/24/2020] [Indexed: 12/16/2022] Open
Abstract
Genomics comprises a set of current and valuable technologies implemented as selection tools in dairy cattle commercial breeding programs. The intensive progeny testing for production and reproductive traits based on genomic breeding values (GEBVs) has been crucial to increasing dairy cattle productivity. The knowledge of key genes and haplotypes, including their regulation mechanisms, as markers for productivity traits, may improve the strategies on the present and future for dairy cattle selection. Genome-wide association studies (GWAS) such as quantitative trait loci (QTL), single nucleotide polymorphisms (SNPs), or single-step genomic best linear unbiased prediction (ssGBLUP) methods have already been included in global dairy programs for the estimation of marker-assisted selection-derived effects. The increase in genetic progress based on genomic predicting accuracy has also contributed to the understanding of genetic effects in dairy cattle offspring. However, the crossing within inbred-lines critically increased homozygosis with accumulated negative effects of inbreeding like a decline in reproductive performance. Thus, inaccurate-biased estimations based on empirical-conventional models of dairy production systems face an increased risk of providing suboptimal results derived from errors in the selection of candidates of high genetic merit-based just on low-heritability phenotypic traits. This extends the generation intervals and increases costs due to the significant reduction of genetic gains. The remarkable progress of genomic prediction increases the accurate selection of superior candidates. The scope of the present review is to summarize and discuss the advances and challenges of genomic tools for dairy cattle selection for optimizing breeding programs and controlling negative inbreeding depression effects on productivity and consequently, achieving economic-effective advances in food production efficiency. Particular attention is given to the potential genomic selection-derived results to facilitate precision management on modern dairy farms, including an overview of novel genome editing methodologies as perspectives toward the future.
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Affiliation(s)
- Miguel A. Gutierrez-Reinoso
- Facultad de Ciencias Agropecuarias y Recursos Naturales, Carrera de Medicina Veterinaria, Universidad Técnica de Cotopaxi (UTC), Latacunga 05-0150, Ecuador
- Laboratorio de Biotecnología Animal, Departamento de Ciencia Animal, Facultad de Ciencias Veterinarias, Universidad de Concepción (UdeC), Chillán 3780000, Chile
| | - Pedro M. Aponte
- Colegio de Ciencias Biológicas y Ambientales (COCIBA), Universidad San Francisco de Quito (USFQ), Quito 170157, Ecuador
- Campus Cumbayá, Instituto de Investigaciones en Biomedicina “One-health”, Universidad San Francisco de Quito (USFQ), Quito 170157, Ecuador
| | - Manuel Garcia-Herreros
- Instituto Nacional de Investigação Agrária e Veterinária (INIAV), 2005-048 Santarém, Portugal
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Lu H, Wang Y, Bovenhuis H. Phenotypic and genetic effects of season on milk production traits in dairy cattle in the Netherlands. J Dairy Sci 2021; 104:4486-4497. [PMID: 33612205 DOI: 10.3168/jds.2020-19615] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 11/29/2020] [Indexed: 12/13/2022]
Abstract
Milk production systems in several countries show considerable differences between seasons. For example, in the Netherlands, cows are kept inside and fed silage in winter, whereas they are on pasture in summer. The differences between seasons affect milk yield and composition and might influence the genetic background of milk production traits. The objective of this study was to estimate phenotypic and genetic effects of season on milk production traits. For this purpose, 19,286 test-day milk production records of 1,800 first-parity Dutch Holstein-Frisian cows were available, and these cows were genotyped using a 50K SNP panel. Phenotypic effects of season were significant for all milk production traits. Effects of season were large for milk fat yield, fat content, and protein content. Genetic correlations between milk production traits in different seasons showed that genotype by season interaction effects were relatively small for most milk production traits. The genetic background of protein content and lactose content seems to be sensitive to seasonal effects. Furthermore, the genetic correlations between spring and autumn differed significantly from unity for almost all milk production traits. A genome-wide association study for genotype by season interaction identified chromosomal regions on BTA3, BTA14, BTA20, and BTA25 that showed genotype by season interaction effects, including a region containing DGAT1, which showed interaction effects for fat content and protein content.
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Affiliation(s)
- Haibo Lu
- Animal Breeding and Genomics, Wageningen University and Research, 6700AH, Wageningen, the Netherlands
| | - Yachun Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs (MARA), National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, P.R. China
| | - Henk Bovenhuis
- Animal Breeding and Genomics, Wageningen University and Research, 6700AH, Wageningen, the Netherlands.
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8
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Lu H, Bovenhuis H. Phenotypic and genetic effects of pregnancy on milk production traits in Holstein-Friesian cattle. J Dairy Sci 2020; 103:11597-11604. [PMID: 32981723 DOI: 10.3168/jds.2020-18561] [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: 03/19/2020] [Accepted: 07/20/2020] [Indexed: 11/19/2022]
Abstract
Pregnancy is a prerequisite for the initiation of lactation and for maintaining the milk production cycle. Pregnancy affects milk production and therefore should be accounted for in the genetic evaluation. Furthermore, there might be genetic differences in pregnancy effects on milk composition. The objective of this study was to estimate phenotypic and genetic effects of pregnancy on milk production traits. For this purpose, test-day records and conception dates of 1,359 first-parity Holstein-Friesian cows were analyzed. Significant effects of pregnancy on all milk production traits were detected except somatic cell score (e.g., the cumulative effects of pregnancy on milk yield were -247 kg). The pregnancy effects on milk yield, lactose yield, protein yield, fat yield, and fat content were small during early gestation (<150 d) and substantially increased in late gestation. The effects of pregnancy on milk protein yield were relatively stronger than those on fat yield. The effects of pregnancy on milk production traits differed for DGAT1 genotypes. Milk yield, lactose yield, protein yield, and fat yield of DGAT1 AA cows were more affected by pregnancy than that of DGAT1 KK cows (e.g., the cumulative effects of pregnancy on milk yield were negligible for DGAT1 KK cows and were -443 kg for DGAT1 AA cows). These results suggest that DGAT1 KK cows may be more suitable for shortening or omitting the dry period than DGAT1 AA cows.
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Affiliation(s)
- Haibo Lu
- Animal Breeding and Genomics, Wageningen University and Research, PO Box 338, 6700 AH, Wageningen, the Netherlands
| | - Henk Bovenhuis
- Animal Breeding and Genomics, Wageningen University and Research, PO Box 338, 6700 AH, Wageningen, the Netherlands.
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Silva AA, Silva DA, Silva FF, Costa CN, Silva HT, Lopes PS, Veroneze R, Thompson G, Carvalheira J. GWAS and gene networks for milk-related traits from test-day multiple lactations in Portuguese Holstein cattle. J Appl Genet 2020; 61:465-476. [PMID: 32607783 DOI: 10.1007/s13353-020-00567-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Revised: 02/07/2020] [Accepted: 06/09/2020] [Indexed: 02/07/2023]
Abstract
This study focused on the identification of QTL regions, candidate genes, and network related genes based on the first 3 lactations (LAC3) of milk, fat, and protein yields, and somatic cell score (SCS) in Portuguese Holstein cattle. Additionally, the results were compared with those from only first lactation (LAC1) data. The analyses were performed using the weighted single-step GWAS under an autoregressive test-day (TD) multiple lactations model. A total of 11,434,294 and 4,725,673 TD records from LAC3 and LAC1, respectively, including 38,323 autosomal SNPs and 1338 genotyped animals were used in GWAS analyses. A total of 51 (milk), 5 (fat), 24 (protein), and 4 (SCS) genes were associated to previously annotated relevant QTL regions for LAC3. The CACNA2D1 at BTA4 explained the highest proportion of genetic variance respectively for milk, fat, and protein yields. For SCS, the TRNAG-CCC at BTA14, MAPK10, and PTPN3 genes, both at BTA6 were considered important candidate genes. The accessed network refined the importance of the reported genes. CACNA2D1 regulates calcium density and activation/inactivation kinetics of calcium transport in the mammary gland; whereas TRNAG-CCC, MAPK10, and PTPN3 are directly involved with inflammatory processes widely derived from mastitis. In conclusion, potential candidate genes (TRNAG-CCC, MAPK10, and PTPN3) associated with somatic cell were highlighted, which further validation studies are needed to clarify its mechanism action in response to mastitis. Moreover, most of the candidate genes identified were present in both (LAC3 and LAC1) for milk, fat and protein yields, except for SCS, in which no candidate genes were shared between LAC3 and LAC1. The larger phenotypic information provided by LAC3 dataset was more effective to identify relevant genes, providing a better understanding of the genetic architecture of these traits over all lactations simultaneously.
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Affiliation(s)
- Alessandra Alves Silva
- Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil
| | - Delvan Alves Silva
- Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil
| | - Fabyano Fonseca Silva
- Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil
| | | | - Hugo Teixeira Silva
- Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil
| | - Paulo Sávio Lopes
- Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil
| | - Renata Veroneze
- Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil
| | - Gertrude Thompson
- Research Center in Biodiversity and Genetic Resources (CIBIO-InBio), University of Porto, Vairão, Porto, Portugal.,Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto, Portugal
| | - Julio Carvalheira
- Research Center in Biodiversity and Genetic Resources (CIBIO-InBio), University of Porto, Vairão, Porto, Portugal. .,Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto, Portugal.
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10
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Lu H, Wang Y, Bovenhuis H. Genome-wide association study for genotype by lactation stage interaction of milk production traits in dairy cattle. J Dairy Sci 2020; 103:5234-5245. [PMID: 32229127 DOI: 10.3168/jds.2019-17257] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2019] [Accepted: 01/28/2020] [Indexed: 01/14/2023]
Abstract
Substantial evidence demonstrates that the genetic background of milk production traits changes during lactation. However, most GWAS for milk production traits assume that genetic effects are constant during lactation and therefore might miss those quantitative trait loci (QTL) whose effects change during lactation. The GWAS for genotype by lactation stage interaction are aimed at explicitly detecting the QTL whose effects change during lactation. The purpose of this study was to perform GWAS for genotype by lactation stage interaction for milk yield, lactose yield, lactose content, fat yield, fat content, protein yield, and somatic cell score to detect QTL with changing effects during lactation. For this study, 19,286 test-day records of 1,800 first-parity Dutch Holstein cows were available and cows were genotyped using a 50K SNP panel. A total of 7 genomic regions with effects that change during lactation were detected in the GWAS for genotype by lactation stage interaction. Two regions on Bos taurus autosome (BTA)14 and BTA19 were also significant based on a GWAS that assumed constant genetic effects during lactation. Five regions on BTA4, BTA10, BTA11, BTA16, and BTA23 were only significant in the GWAS for genotype by lactation stage interaction. The biological mechanisms that cause these changes in genetic effects are still unknown, but negative energy balance and effects of pregnancy may play a role. These findings increase our understanding of the genetic background of lactation and may contribute to the development of better management indicators based on milk composition.
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Affiliation(s)
- Haibo Lu
- Animal Breeding and Genomics, Wageningen University and Research, PO Box 338, 6700AH, Wageningen, the Netherlands
| | - Yachun Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, P. R. China
| | - Henk Bovenhuis
- Animal Breeding and Genomics, Wageningen University and Research, PO Box 338, 6700AH, Wageningen, the Netherlands.
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Oliveira HR, Lourenco DAL, Masuda Y, Misztal I, Tsuruta S, Jamrozik J, Brito LF, Silva FF, Cant JP, Schenkel FS. Single-step genome-wide association for longitudinal traits of Canadian Ayrshire, Holstein, and Jersey dairy cattle. J Dairy Sci 2019; 102:9995-10011. [PMID: 31477296 DOI: 10.3168/jds.2019-16821] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 07/08/2019] [Indexed: 11/19/2022]
Abstract
Estimating single nucleotide polymorphism (SNP) effects over time is essential to identify and validate candidate genes (or quantitative trait loci) associated with time-dependent variation of economically important traits and to better understand the underlying mechanisms of lactation biology. Therefore, in this study, we aimed to estimate time-dependent effects of SNP and identifying candidate genes associated with milk (MY), fat (FY), and protein (PY) yields, and somatic cell score (SCS) in the first 3 lactations of Canadian Ayrshire, Holstein, and Jersey breeds, as well as suggest their potential pattern of phenotypic effect over time. Random regression coefficients for the additive direct genetic effect were estimated for each animal using single-step genomic BLUP, based on 2 random regression models: one considering MY, FY, and PY in the first 3 lactations and the other considering SCS in the first 3 lactations. Thereafter, SNP solutions were obtained for random regression coefficients, which were used to estimate the SNP effects over time (from 5 to 305 d in lactation). The top 1% of SNP that showed a high magnitude of SNP effect in at least 1 d in lactation were selected as relevant SNP for further analyses of candidate genes, and clustered according to the trajectory of their SNP effects over time. The majority of SNP selected for MY, FY, and PY increased the magnitude of their effects over time, for all breeds. In contrast, for SCS, most selected SNP decreased the magnitude of their effects over time, especially for the Holstein and Jersey breeds. In general, we identified a different set of candidate genes for each breed, and similar genes were found across different lactations for the same trait in the same breed. For some of the candidate genes, the suggested pattern of phenotypic effect changed among lactations. Among the lactations, candidate genes (and their suggested phenotypic effect over time) identified for the second and third lactations were more similar to each other than for the first lactation. Well-known candidate genes with major effects on milk production traits presented different suggested patterns of phenotypic effect across breeds, traits, and lactations in which they were identified. The candidate genes identified in this study can be used as target genes in studies of gene expression.
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Affiliation(s)
- H R Oliveira
- Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada; Department of Animal Sciences, Universidade Federal de Viçosa, Viçosa, Minas Gerais, 36570-000, Brazil.
| | - D A L Lourenco
- Department of Animal and Dairy Science, University of Georgia, Athens 30602
| | - Y Masuda
- Department of Animal and Dairy Science, University of Georgia, Athens 30602
| | - I Misztal
- Department of Animal and Dairy Science, University of Georgia, Athens 30602
| | - S Tsuruta
- Department of Animal and Dairy Science, University of Georgia, Athens 30602
| | - J Jamrozik
- Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada; Canadian Dairy Network, Guelph, ON, N1K 1E5, Canada
| | - L F Brito
- Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada; Department of Animal Sciences, Purdue University, West Lafayette, IN 47907
| | - F F Silva
- Department of Animal Sciences, Universidade Federal de Viçosa, Viçosa, Minas Gerais, 36570-000, Brazil
| | - J P Cant
- Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | - F S Schenkel
- Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada
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