GWAS and gene networks for milk-related traits from test-day multiple lactations in Portuguese Holstein cattle

Silva, Alessandra Alves; Silva, Delvan Alves da; Silva, Fabyano Fonseca e; Costa, C. N.; Silva, Hugo Teixeira; Lopes, Paulo Sávio; Veroneze, Renata; Thompson, Gertrude; Carvalheira, J.

doi:10.1007/s13353-020-00567-3

Cited by 13 publications

(6 citation statements)

References 37 publications

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“…The MAPK10 gene (mitogen-activated protein kinase 10) is linked with the inflammatory response and immunity of epithelial cells in the mammary gland. According to Silva et al [ 52 ], MAPK10 is a candidate gene to somatic cell score (SCS). The PRLR gene (prolactin receptor), also known as the SLICK gene, was associated with heat tolerance [ 53 ], because results in short and slick hair that result in better adaptation to high temperatures [ 54 ].…”

Section: Discussionmentioning

confidence: 99%

Characterization of runs of homozygosity, heterozygosity-enriched regions, and population structure in cattle populations selected for different breeding goals

et al. 2022

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Background A decline in the level of genetic diversity in livestock can result in reduced response to selection, greater incidence of genetic defects, and inbreeding depression. In this context, various metrics have been proposed to assess the level of genetic diversity in selected populations. Therefore, the main goals of this study were to: 1) investigate the population structure of 16 cattle populations from 15 different pure breeds or composite populations, which have been selected for different breeds goals; and, 2) identify and compare runs of homozygosity (ROH) and heterozygosity-enriched regions (HER) based on different single nucleotide polymorphism (SNP) panels and whole-genome sequence data (WGS), followed by functional genomic analyses. Results A total of 24,187 ROH were found across all cattle populations, with 55% classified in the 2-4 Mb size group. Fourteen homozygosity islands were found in five populations, where four ROH islands located on BTA1, BTA5, BTA16, and BTA19 overlapped between the Brahman (BRM) and Gyr (GIR) breeds. A functional analysis of the genes found in these islands revealed candidate genes known to play a role in the melanogenesis, prolactin signaling, and calcium signaling pathways. The correlations between inbreeding metrics ranged from 0.02 to 0.95, where the methods based on homozygous genotypes (FHOM), uniting of gametes (FUNI), and genotype additive variance (FGRM) showed strong correlations among them. All methods yielded low to moderate correlations with the inbreeding coefficients based on runs of homozygosity (FROH). For the HER, 3576 runs and 26 islands, distributed across all autosomal chromosomes, were found in regions containing genes mainly related to the immune system, indicating potential balancing selection. Although the analyses with WGS did not enable detection of the same island patterns, it unraveled novel regions not captured when using SNP panel data. Conclusions The cattle populations that showed the largest amount of ROH and HER were Senepol (SEN) and Montana (MON), respectively. Overlapping ROH islands were identified between GIR and BRM breeds, indicating a possible historical connection between the populations. The distribution and pattern of ROH and HER are population specific, indicating that different breeds have experienced divergent selection processes or different genetic processes.

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Section: Discussionmentioning

confidence: 99%

Characterization of runs of homozygosity, heterozygosity-enriched regions, and population structure in cattle populations selected for different breeding goals

et al. 2022

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“…The transfer RNA glycine anticodon CCC (TRNAG-CCC) gene on BBU14 is a member of the ubiquitous molecules genes family that provide the crucial link between the genetic code and AA (Tang et al, 2009). This gene has also been associated with udder health and mastitis in previous studies on Holstein cattle (Wu et al, 2015;Silva et al, 2020a) or dairy buffalo (de Camargo et al, 2015). However, its mechanisms of action in response to mastitis are still unknown.…”

Section: Gwas and Functional Analysesmentioning

confidence: 99%

Genomic studies of milk-related traits in water buffalo (Bubalus bubalis) based on single-step genomic best linear unbiased prediction and random regression models

Lázaro

Tonhati

Oliveira

et al. 2021

Journal of Dairy Science

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Genomic selection has been widely implemented in many livestock breeding programs, but it remains incipient in buffalo. Therefore, this study aimed to (1) estimate variance components incorporating genomic information in Murrah buffalo; (2) evaluate the performance of genomic prediction for milk-related traits using single-and multitrait random regression models (RRM) and the single-step genomic best linear unbiased prediction approach; and (3) estimate longitudinal SNP effects and candidate genes potentially associated with time-dependent variation in milk, fat, and protein yields, as well as somatic cell score (SCS) in multiple parities. The data used to estimate the genetic parameters consisted of a total of 323,140 test-day records. The average daily heritability estimates were moderate (0.35 ± 0.02 for milk yield, 0.22 ± 0.03 for fat yield, 0.42 ± 0.03 for protein yield, and 0.16 ± 0.03 for SCS). The highest heritability estimates, considering all traits studied, were observed between 20 and 280 d in milk (DIM). The genetic correlation estimates at different DIM among the evaluated traits ranged from −0.10 (156 to 185 DIM for SCS) to 0.61 (36 to 65 DIM for fat yield). In general, direct selection for any of the traits evaluated is expected to result in indirect genetic gains for milk yield, fat yield, and protein yield but also increase SCS at certain lactation stages, which is undesirable. The predicted RRM coefficients were used to derive the genomic estimated breeding values (GEBV) for each time point (from 5 to 305 DIM). In general, the tuning parameters evaluated when constructing the hybrid genomic relationship matrices had a small effect on the GEBV accuracy and a greater effect on the bias estimates. The SNP solutions were back-solved from the GEBV predicted from the Legendre random regression coefficients, which were then used to estimate the longitudinal SNP effects (from 5 to 305 DIM). The daily SNP effect for 3 different lactation stages were performed considering 3 different lactation stages for each trait and parity: from 5 to 70, from 71 to 150, and from 151 to 305 DIM. Important genomic regions related to the analyzed traits and parities that explain more than 0.50% of the total additive genetic variance were selected for further analyses of candidate genes. In general, similar potential candidate genes were found between traits, but our results suggest evidence of differential sets of candidate genes underlying the phenotypic expression of the traits across parities. These results contribute to a better understanding of the genetic architecture of milk production traits in dairy buffalo and reinforce the relevance of incorporating genomic information to genetically evaluate longitudinal traits in dairy buffalo. Furthermore, the candidate genes identified can be used as target genes in future functional genomics studies.

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“…The MAPK10 gene (mitogen-activated protein kinase 10) is linked with the in ammatory response and immunity of epithelial cells in the mammary gland. According to Silva et al [51], MAPK10 is a candidate gene to somatic cell score (SCS). The PRLR gene (prolactin receptor), also known as the SLICK gene, was associated with heat tolerance [52], because results in short and slick hair that help in adaptation to high temperatures [53].…”

Section: Homozygosity Islandsmentioning

confidence: 99%

Characterization of Runs of Homozygosity, Heterozygosity-Enriched Regions, and Population Structure in Cattle Populations Selected for Different Breeding Goals

Mulim

Brito

Pinto

et al. 2021

Preprint

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Background: A decline in the level of genetic diversity can result in reduced response to selection, greater incidence of genetic defects, and inbreeding depression. In this context, some metrics have been proposed to assess the levels of populational genetic diversity in selected populations. The main goals of this study were to: 1) investigate the population structure of 16 cattle populations from 15 different pure breeds or composite populations, which have been selected for different breeds goals; and, 2) identify and compare runs of homozygosity (ROH) and heterozygosity-enriched regions (HER) based on different single nucleotide polymorphism (SNP) panels and whole-genome sequence data (WGS), followed by functional genomic analyses. Results: A total of 24,187 ROH were found across all cattle populations, with 55% classified in the 2-4 Mb size group. Fourteen homozygosity islands were found in five populations, where four islands located on BTA1, BTA5, BTA16, and BTA19 overlapped between the Brahman (BRM) and Gyr (GIR) breeds. A functional analysis of the genes found in these islands revealed candidate genes known to play a role in the melanogenesis, prolactin signaling, and calcium signaling pathways. The correlations between inbreeding metrics ranged from 0.02 to 0.95, where the methods based on homozygous genotypes (FHOM), uniting of gametes (FUNI), and genotype additive variance (FGRM) showed strong correlations among them. All methods yielded low to moderate correlations with the inbreeding coefficients based on runs of homozygosity (FROH). For the HER, 3,576 runs and 26 islands, distributed across all autosomal chromosomes, were found in regions containing genes mainly related to the immune system. Although the analyses with WGS did not enable detection of the same island patterns, it unraveled novel regions not captured when using SNP panel data.Conclusions: The cattle populations that showed the largest amount of ROH and HER were Senepol (SEN) and Montana (MON), respectively. Overlapping ROH islands were identified between GIR and BRM breeds, indicating a possible historical connection between the populations. The distribution and pattern of ROH and HER are population specific, indicating that different breeds have experienced divergent selection processes or different genetic processes.

show abstract

GWAS and gene networks for milk-related traits from test-day multiple lactations in Portuguese Holstein cattle

Cited by 13 publications

References 37 publications

Characterization of runs of homozygosity, heterozygosity-enriched regions, and population structure in cattle populations selected for different breeding goals

Characterization of runs of homozygosity, heterozygosity-enriched regions, and population structure in cattle populations selected for different breeding goals

Genomic studies of milk-related traits in water buffalo (Bubalus bubalis) based on single-step genomic best linear unbiased prediction and random regression models

Characterization of Runs of Homozygosity, Heterozygosity-Enriched Regions, and Population Structure in Cattle Populations Selected for Different Breeding Goals

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