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Ukrainian Journal of Ecology
Ukrainian Journal of Ecology, 2018, 8(1), 939-947 doi: 10.15421/2018_296
ORIGINAL ARTICLE UDC: 575.113.1:636.223.1
Effects of 5 SNPs on daughters' milk performance traits produced by Ukrainian dairy sires
Olena Fedota1, Nina Lysenko2, Larysa Mitiohlo3, Sergiy Ruban4
1 V. N. Karazin Kharkiv National University, Svobody Sq., 4, Kharkiv, 61022, Ukraine http://orcid.org/0000-0001 -9659-383X, e-mail: [email protected], Tel.: +38-067-961-77-11
2 Kharkiv National Medical University, Nauky Avenue, 4, Kharkiv, 61022, Ukraine https://orcid.org/0000-0002-3388-0038, e-mail: [email protected], Tel.: +38-099-640-90-23 3 Research farm "Nyva", Institute of Animal Breeding and Genetics nd. a. M.V. Zubets of NAAN, State owned enterprise, vul. Sadova, 1, Hristinivka, Hristinivs'kiy dist, Cherkas'ka oblast, 20009, Ukraine 4 National University of Life and Environmental Sciences of Ukraine, Heroiv Oborony Str., 15, Kyiv, 03041, Ukraine
Received: 14.02.2018. Accepted: 20.03.2018
The aim of the study was to estimate the effects of the CAPN316, CAST282, GH L127V, GHR F279Y and A257G on milk yield, fat and protein yield and content on daughters produced by dairy sires. 24 dairy sires were 100% Holstein (14), 100% Brown Swiss (5) and Holstein mixed with another dairy breeds (5). Analyses included data on 32733 daughters for 2014-2017 years. Molecular genetic analysis was performed by PCR-RFLP. Statistical analysis revealed that population was on Hardy-Weinberg equilibrium. SNPs F279Y and A257G were not in linkage disequilibrium (r2 = 0.029, D' = 0.074), because linkage of certain alleles was observed only in 7.4% of cases (D'). C-allele of SNP CAPN316 was strongly associated with protein content, despite C-allele of SNP CAST282 showed negative association with milk, fat and protein yield. Daughter milk performance traits (DMPTs) for SNP CAPN316 corresponded to CC>CG>GG pattern, except variations in milk and fat yield (kg). For SNP CAST282 Milk, fat and protein yield (kg) were significantly higher for CG than for CC genotype. C-allele for SNP L127V showed significant association and differences between genotypes with DYDs for fat yield (kg) - 20.45±5.53 (P<0.01) and content (%) - 0.13±0.06 (P<0.05), T-allele for SNP F279V was not significantly associated with any trait studied and A-allele for SNP A257G significantly associated with milk and fat yield (kg) for DMPTs/DYDs 1988.33±419.93/-269.69±89.92 (P<0.01) and 84.30±15.64/-8.33±3.87 (P<0.05). Results of this study reveal and support known advantages of SNPs studied in panels and selection programs. Keywords: dairy sires; milk production traits; genotype; CAPN316; CAST282; L127V; F279Y; A257G
Вплив 5 SNPs на характеристики молока дочок бугаТв
порщ молочного напрямку
Олена Федота1, Жна Лисенко2, Лариса Мтогло3, Серий Рубан4
1 Харювський на^ональний унверситет iMeHi В. Н. Kapa3iHa, майдан Свободи 4, 61022, Харюв, Украна http://orcid.org/0000-0001 -9659-383X, e-mail: [email protected], Тел.: +38-067-961-77-11 2 Харювський нацюнальний медичний унiверситет, проспект Науки, 4, 61022, Харюв, Украна https://orcid.org/0000-0002-3388-0038, e-mail: [email protected], Тел.: +38-099-640-90-23
3 Досл'дне господарство «Нива» 1нституту розведення i генетики тварин 'шен'1 М.В. Зубця НААН Украни, Державне тдприемство, вул. Садова, 1, с. Христинiвка, Христинiвський р-н, Черкаська обл., 20009, Украна
4 Нацюнальний унверситет б'юресурав i природокористування Украни, вулиця Геров Оборони, 15, Кив,
03041, Укра'/на
Метою дослщження було оцЫити ефекти CAPN316, CAST282, GH L127V, GHR F279Y та A257G на молочнкть, жирномолочнкть та бтковомолочнкть та вмкт жиру та бтку у дочок бугаУв порщ молочного напрямку. 24 бугая належали до порщ: 100% голштинська (14), 100% швщька (5) та голштинськоУ породи, мшаноУ з Ышими породами молочного напрямку (5). Аналiз включав дан 32733 доньок протягом 2014-2017 роюв. Молекулярно-генетичний аналiз проводили за допомогою ПЛР-ПДРФ. Статистичний аналiз показав, що популя^я знаходилась у рiвновазi за Хард^ Вайнбергом. SNP F279Y та A257G не демонстрували нерiвновагу за зчепленням (r2 = 0,029, D' = 0,074), осктьки зв'язок певних алелей спостер^ався лише у 7,4% випадюв (D) С-алель SNP CAPN316 характеризувався високою асо^а^ею iз
вмктом бтку, незважаючи на те, що C-алелi SNP CAST282 показали негативну асо^а^ю з молочнiстю, жирномолочнiстю та бтковомолочнктю. Молочнi характеристики дочок (DMPTs) для SNP CAPN316 вщповщае закономiрностi CC> CG> GG, за винятком молочносп та жирномолочностi (кг). За SNP CAST282 молочнкть, жирномолочнiсть та бтковомолочнкть (кг) були значно вищими для генотипу CG, ыж для СС. С-аллель за SNP L127V показав значну асо^а^ю та рiзницю мiж генотипами з DYDs для жирномолочносп (кг) - 20,45 ± 5,53 (P <0,01) та вмкту жиру (%) - 0,13 ± 0,06 (P <0,05), Т-аллель за SNP F279Vне був значно асоцмовим з будь-якою дослiджуваною рисою, але A-алель за SNP A257G значно асо^ювався з молочнiстю та жирномолочнктью (кг) для DMPTs/DYDs 1988,33 ± 419,93 / -269,69 ± 89,92 (P <0,01) та 84,30 ± 15,64 / -8,33 ± 3,87 (Р <0,05). Результати цього дослщження виявляють та пiдтверджують вiдомi переваги дослщждуваних SNPs для використання в панелях та програмах выбору.
Ключов! слова: буги молочних порiд; молочнi характеристики; генотип; CAPN316; CAST282; L127V; F279Y; A257G
Introduction
The study of SNPs in candidate genes affecting productive and reproductive processes is actual for explaining genetic variation, for understanding their contribution to vital functions and inclusion them into SNP panels used in animal evaluation and breeding. According Cochran et al. (2013), different types of SNPs were evaluated for their relationship to reproductive animal traits: SNPs previously reported to be associated with reproductive traits of dairy or beef cattle or physically close to genetic markers for reproduction, SNPs in genes that are well known to be involved in reproductive processes, and SNPs in genes reported to be differentially expressed between physiological conditions in a variety of tissues associated in reproductive function. As the researchers concluded incorporation of candidate gene SNPs into genomic tests for reproduction would allow selection of causative SNPs or SNPs physically more close to causative SNPs. Such an approach has been successful for improving ability to detect genomic associations with disease (Amos et al., 2011; Cochran at al., 2013). Also an important point in the analysis of gene networks is a loss of information from multiple single nucleotide polymorphisms located within or close to the same gene, ignoring information on linkage disequilibrium and validation of the obtained gene network (Suchocki et al., 2016).
It is known that many female fertility traits in dairy cattle show antagonistic genetic correlations with milk production traits but with low or moderate correlations. This implies that simultaneous genetic selection for increased milk yield and reproductive performance is possible. Simultaneous breeding for both productive and fertile cows would benefit substantially from knowing the genetic and physiological links between production and health to disentangle the effects on these traits (Iso-Touru, et al., 2016; Berry et al., 2016; Aliloo et al., 2015). Given that dairy cattle reproduction is usually performed with sperm produced by a limited number of sires, we need to provide early evaluation of sires' quality based on genotyping of markers for daughters' milk performance.
The calpain system, consisting of p- calpain, m-calpain and their inhibitor calpastatin has a number of different roles in cells, including but not limited to "remodeling" of cytoskeletal attachments to the plasma membrane during cell fusion and cell motility, proteolytic modification of molecules in signal transduction pathways, degradation of enzymes controlling progression through the cell cycle, regulation of gene expression, substrate degradation in some apoptotic pathways, and an involvement in long-term potentiation (Goll et al., 2003). Due to post mortal activity of calpain system in a muscle tissue, resulting in cytoskeleton fibers degradation, SNPs of CAPN1 and CAST genes are used as markers for meat tenderness in beef cattle (Schenkel et al., 2006; Gill et al., 2009). In dairy cattle CAPN1 is primary associated with reproductive characteristics - the ability to ovulate prior to weaning and post-partum anoestrus interval (Collis et al., 2012), and the CAST gene is associated with daughter pregnancy rate (Ortega et al., 2016). Given the association of some SNPs in these genes with udder size, it is possible to assume the relation to quantitative and qualitative parameters of milk. Considering that traditionally dairy sires are evaluated by daughter productivity and presence of calpain system enzymes in sperm that affects semen quality traits (Cui et al., 2016), we consider it is appropriate to evaluate the effect of SNPs CAPN316 and CAST282 in dairy sires on their daughter milk productivity performance.
Growth hormone (GH) interacting with receptor (GHR) is involved in regulation of animal growth and development, it affects the quality parameters of milk and fertility of cows via enhancing lipolysis in adipose tissue (Balogh et al., 2009; Hadi et al., 2015), therefore GH and GHR genes can be considered as standard markers of both dairy and beef cattle productivity. SNPs L127V of the GH gene, F279Y and A257G of the GHR gene (Blott et al., 2003; Viitala et al., 2006) are associated with productive characteristics as milk yield, fat and protein content and somatic cell count, age of reproductive period onset, calving interval, predisposition to mastitis, birth weight, body weight gain and constitution (Hadi et al., 2015; Rahmatalla et al., 2011; Olenski et al., 2010). Additionally, male gonad and accessory organs are sites of both GH production and action (Hull and Harvey, 2014). Therefore, our aim was to analyze the effect of SNPs CAPN316, CAST282, L127V, F279Yand A257G on breeding values of Ukrainian dairy sires for milk production traits and milk performance traits of their daughters.
Materials and methods
The study included 24 dairy sires of 100% Holstein (14), 100% Brown Swiss (5) and Holstein mixed with Simmental or Montbeliarde or Black-and-White or both (5) breeds. Analyses included data on 32733 daughters produced by analyzed sires during 2014-2017 years. Daughter yield deviation (DYD) is a standard measure of animals' genetic merits in routine genetic evaluations worldwide (Szyda et al., 2008). DYDs and characteristics of the daughters' milk performance traits included milk (MY, kg), fat (FY, kg) and protein yield (PY, kg), fat (FP, %) and protein percentage (PP, %). These data were withdrawn from farm records and Catalogue of Dairy and Dual Purpose Sires for Breeding Stock Reproduction (2014-2017), http://www.animalbreedingcenter.org.ua/catalog.
DNA of sires was isolated from whole blood or from frozen sperm. Analyses were performed by PCR/RFLP techniques, published in our previous papers (Ruban et al., 2017, Fedota et al., 2017) using regimens published by Miquel et al. (2009) and Komisarek et al. (2011). Whereas F279Y and A257G are the SNPs in the same gene GHR, located in the 8th and 10th exones, separated with apprixiatelyl 8 kb (Fedota et al., 2017), linkage disequilibrium (r2; Hill and Robertson 1968) was calculated between their pairwise combination. The association between each SNP and all DYDs and daughters' milk parameters of Ukrainian dairy sires for milk production traits was quantified using weighted linear models mixed in R (Maechler et al., 2013) included year of birth and percent Holstein of the individual sire as fixed effects and genotype as a continuous variable. For comparison between two and more groups we used Student's t-test and ANOVA. Pearson's Chi-square test was applied to prove whether a Hardy-Weinberg genetic equilibrium was fulfilled in the population. Allele substitution effects were estimated by regressing the number of copies of SNP allele against the analyzed DYDs or daughters' milk performance traits. P < 0.05 indicated significant difference.
Results
Descriptive data for DYDs and daughters' milk performance traits (DMPTs) by year are summarized in Table 1. Total number of daughters depends on commercial availability or marketing strategy for given sires, although sires number per year was determined by citations in a Catalogue. The variability (CV, %) is higher for DYDs rather than for DMPTs, being the highest for fat and protein content due to wide range of variation for small numbers. Table 1. Basic statistics for DYD and DMPTs of Ukrainian dairy sires by year.
N sires N daughters X s* CV, % Minimum Maximum
2014
DMPTs
Milk yield (kg) 16 2316 8407.00 513.16 6.10 5487 11488
Fat yield (kg) 16 2316 335.19 19.27 5.75 205 454
Protein yield (kg) 14 2218 295.64 13.73 4.64 190 360
Fat content (%) 16 2316 4.01 0.10 2.57 3.56 5.24
Protein content (%) 14 2218 3.39 0.09 2.65 3.09 4.39
BBV (pt) 17 2433 1072.06 54.95 5.13 758 1690
DYDs
Milk yield (kg) 17 2433 942.94 88.13 9.35 309 1667
Fat yield (kg) 17 2433 34.94 4.02 11.51 3 64
Protein yield (kg) 15 2335 32.93 2.94 8.94 18 60
Fat content (%) 17 2433 -0.03 0.04 - -0.57 0.16
Protein content (%) 15 2335 0.01 0.02 -0.25 0.14
2015
DMPTs
Milk yield (kg) 9 10667 7051.11 790.40 11.21 4461 11854
Fat yield (kg) 9 10667 266.33 29.71 11.15 167 429
Protein yield (kg) 6 10549 260.83 26.46 10.14 196 358
Fat content (%) 9 10667 3.78 0.04 1.03 3.62 4.04
Protein content (%) 6 10549 3.19 0.08 2.45 3.02 3.54
BBV (pt) 20 19077 823.95 87.85 10.66 250 1646
DYDs
Milk yield (kg) 20 19077 827.10 114.57 13.85 159 1837
Fat yield (kg) 20 19077 32.70 4.32 13.22 -4 69
Protein yield (kg) 17 18959 28.53 3.85 13.50 8 64
Fat content (%) 20 19077 0.02 0.04 - -0.48 0.29
Protein content (%) 17 18959 0.04 0.03 - -0.19 0.29
2016
DMPTs
Milk yield (kg) 6 1986 6840.67 833.24 12.18 4461 9529
Fat yield (kg) 6 1986 265.50 36.96 13.92 167 402
Protein yield (kg) 4 983 260 29.17 11.22 201 339
Fat content (%) 6 1986 3.85 0.08 2 3.71 4.22
Protein content (%) 4 983 3.23 0.11 3.45 3.09 3.56
BBV (pt) 14 4786 804.21 114.98 14.30 130 1322
DYDs
Milk yield (kg) 14 4786 867.29 140.13 16.16 31 1837
Fat yield (kg) 14 4786 36.79 4.24 11.52 3 56
Protein yield (kg) 12 4688 28.75 4.70 16.35 10 52
Fat content (%) 14 4786 0.06 0.06 -0.51 0.32
Protein content {%) 12 4688 0.05 0.04 - -0.24 0.29
2017
DMPTs
Milk yield (kg) 10 3571 7251.20 603.50 8.32 4461 9529
Fat yield (kg) 10 3571 281.40 26.25 9.33 167 402
Protein yield (kg) 7 3453 274.86 17.29 6.29 211 339
Fat content (%) 10 3571 3.85 0.05 1.32 3.71 4.22
Protein content (%) 7 3453 3.29 0.07 2.21 3.11 3.56
BBV (pt) 17 6437 839 95.70 11.41 158 1894
DYDs
Milk yield (kg) 17 6437 851.59 126.95 14.91 28 1852
Fat yield (kg) 17 6437 35 4.55 13 -1 75
Protein yield (kg) 14 6319 29.71 4.44 14.94 10 68
Fat content (%) 17 6437 0.01 0.05 - -0.51 0.31
Protein content (%) 14 6319 0.04 0.04 - -0.24 0.33
/Vere.'DMPTs - daughter milk performance traits, BBV - bulls' breeding value by national Ukrainian scale, DYDs - daughters' yield deviation.
The allele and genotype frequencies for all SNPs studied are shown in Table 2. Expected genotypic frequencies were similar to the observed ones suggesting that genotype distributions were in the Hardy-Weinberg equilibrium.
Table 2. Genotype frequencies (GF), allele frequencies (AF) and significance of deviation for Hardy-Weinberg equilibrium (HWE) for SNPs CAPN316, CAST282, L127V, F279Yand A257G
SNP Genotype N GF (%) AF (%) HWE
CAPN316 CC 3 0.125 C= 0.355 0.001
CG 11 0.458 C7= 0.645
GG 10 0.417
CAST282 CC 10 0.417 C- 0.667 0.195
CG 12 0.500 G= 0.333
GG 2 0.083
LI27V CC 1 0.111 C= 0.445 0.576
CG 6 0.667 G= 0.555
GG 2 0.222
F279Y TT 7 0.636 T= 0.727 1.482
TA 2 0.182 A = 0.273
AA 2 0.182
A257G AA 8 0.667 A = 0.792 0.298
AG 3 0.250 G= 0.208
GG 1 0.083
Considering that differences between groups was not significant (ANOVA), we performed further analysis for fooled data. There were a number of strong associations between DMPTs, DYDs and SNPs (Table 3).
Table 3. Estimated allele substitution effect (B±SEb) between SNPs CAPN316, CAST282, L127V, F279Y, A257G and daughter milk performance traits and DYDs.
CAPN316 and CAST282
C-alleles of SNPs CAPN316(calpain gene) and CAST282 (calpastatin gene) are associated with meat tenderness (Gill et al., 2009). C-allele frequency for CAPN316was lower, alternatively to CAST282. C-allele of SNP CAPN316was strongly associated with protein content, despite C-allele of SNP CAST282 showed negative association with milk, fat and protein yield (Table 3). Tables 4 and 5 summarize the differences between daughter milk performance traits and DYDs by CAST316 and CAST282 genotypes. DMPT for SNP CAPN316 corresponded to CC>CG>GG pattern, except variations in milk and fat yield (kg). However, significant increased fat yield for genotype CG could be determined by significant increased milk yield, where R2 did not exceed 30%. Significant differences in protein content (%) were observed. DYDs were significant or close to significance level for fat content (%) and
yield (kg), respectively. Data for GG-genotype for CAST282 on DMPT were not provided, therefore we compared only two groups and could not perform association analyses. Milk, fat and protein yield (kg) were significantly higher for CG than for CC genotype. All DYDs traits were similar between genotypes and showed high variation exceeding 10-15% for some genotypes with R2<5%.
Table 4. DMPTs and DYDs by CAPN316 genotype.
Genotype CC CG GG P R7
DMPTs
Milk yield (kg) 5103.40±434.04 8641.06+279.70 7248.44+568.77 0.001 0.294
Fat yield (kg) 210.80+35.08 340.28+10.21 277.11+22.96 0.003 0.264
Protein yield (kg) 292.00 285.67+9.38 269.50+20.70 0.713 0.024
Fat content (%) 4.04+0.30 3.95+0.05 3.80+0.04 0.171 0.089
Protein content(%} 4.39 3.30+0.04 3.21+0.05 0.001 0.574
BBV (pt) 755.60+127.89 913.97+65.99 863.28+77.26 0.517 0.021
DYDs
Milk yield (kg) 822.10+724.08 293.20+59.28 646.00+389.93 0.529 0.021
Fat yield (kg) 760.70+158.66 805.30+82.20 875.96+81.31 N/A 1.000
Protein yield (kg) 39.70+4.91 28.73+3.38 38.64+3.27 0.067 0.084
Fat content (%} 20.50+3.86 30.63+2.54 29.95+3.98 0.312 0.044
Protein content (%) 0.14+0.01 -0.06+0.04 0.07+0.02 0.0039 0.164
Protein content (%) 0.06+0.02 0.04+0.02 0.05+0.02 0.842 0.007
Table 5. DMPT and DYDs by CAST282 genotype.
Genotype CC CG GG P R2
DMPTs
Milk yield (kg) 6939.14+378.2 8290.30+515.09 - 0.040 -
Fat yield (kg) 267.62+16.16 327.35+19.84 - 0.024 -
Protein yield (kg) 249.80+12.16 307.56+10.92 - 0.001 -
Fat content (%) 3.83+0.04 3.96+0.08 - 0.165 -
Protein content (%) 3.23+0.04 3.37+0.08 - 0.150
BBV (pt) 833,23+83.39 914.59+55.89 526.50+56.50 0.299 0.038
DYDs
Milk yield (kg) 222.76+62.12 722.49+313.16 110.00+6.00 0.400 0.029
Fat yield (kg) 828.88+81.93 840.49+75.77 508.00+63.00 0.584 0.017
Protein yield (kg) 37.15+2.72 32.65+3.36 25.50+8.50 0.485 0.023
Fat content (%) 27.60+3.70 30.82+2.49 21.00+3.00 0.552 0.023
Protein content (%) 0.06+0.02 -0.01+0.04 0.06+0.06 0.362 0.032
Protein content (%) 0.04+0.02 0.04+0.02 0.04+0.02 0.997 0.001
L127V, F279Y and A257G
The analysis revealed high frequency for "wild" type alleles for all three polymorphic variants, these are C-allele for L127V (growth hormone gene), T-allele for F279Y and A-allele for A257G (growth hormone receptor gene). Absent data on CC genotype for L127V prohibited to perform association analyses for DMPT. C-allele for L127V showed significant association and differences between genotypes with DYDs for fat yield (kg) and content (%) (Table 6), T-allele for F279V was not significantly associated with any trait studied and A-allele for A257G significantly associated with milk and fat yield (kg) for DMTP and DYDs (Table 3). SNPs F279Y and A257G were not in linkage disequilibrium (r2 = 0.029, D' = 0.074), because linkage of certain alleles was observed only in 7.4% of cases (D'). The significant differences between genotypes by F279Y were observed only for daughters' protein yield (R2 = 60%) and followed AA>TT>TA (Table 7). Considering that data for DMPT were available only for 1 sire with genotype AA the pattern found stay to be dubious. DYD for protein content (%) is close to statistical significance and higher for TTgenotype. The genotypes by A257G followed AA>AG>GG for milk and protein yield (kg) in daughters, demonstration reversed (GG>AG>AA) trend for the same DYDs (Table 8). Both trends can be shifted by uncommon GG genotype.
Table 6. DMPT and DYDs by L127V genotype.
Genotype CC CG GG P R2
DMPTs
Milk yield (kg) - 7329.17±369.19 9042.67±72.33 0.042 -
Fat yield (kg) - 291.75±16.99 364.67±3.33 0.057 -
Protein yield (kg) 261.30±9.81 320.67±2.33 0.008 -
Fat content (%) - 3.97±0.13 4.03±0.01 0.823 -
Protein content (%) - 3.38±0.12 3.54±0.01 0.506 -
BBV (pt) 583.00 632.74±96.35 537.50±73.53 0.905 0.009
DYDs
Milk yield (kg) 116.00 261.32±79.23 124.50±23.41 0.695 0.034
Fat yield (kg) 571.00 620.16±97.38 308.50±48.32 0.374 0.089
Protein yield (kg) 34.00 31.84±2.70 15.50±4.27 0.001 0.462
Fat content (%) 24.00 22.82±3.60 18.00±0.71 0.808 0.022
Protein content (%) 0.12 0.08±0.03 -0.08±0.03 0.084 0.211
Protein content (%) 0.06 0.05±0.02 0.07±0.02 0.900 0.011
rable 7. DMPT and DYDs by F279Y genotype.
Genotype TT TA AA P R2
DMPTs
Milk yield (kg) 8335.18±614.45 7636.00±391.05 11488.00 0.159 0.217
Fat yield (kg) 330.36±22.21 296.17±19.39 454.00 0.115 0.251
Protein yield (kg) 308.67±9.77 247.83±13.48 360.00 0.002 0.603
Fat content (%) 3.98±0.14 3.87±0.10 3.95 0.854 0.021
Protein content (%) 3.46±0.13 3.25±0.08 3.13 0.392 0.134
BBV (pt) 563.74±75.06 806.00±209.92 895.00±312.00 0.263 0.105
DYDs
Milk yield (kg) 627.32±479.30 483.1 7±225.92 231.50±115.50 0.951 0.004
Fat yield (kg) 490.84±76.51 846.1 7±203.69 697.50±126.50 0.132 0.155
Protein yield (kg) 23.47±3.39 33.50±7.20 39.00±5.00 0.207 0.123
Fat content (%) 19.41 ±2.53 28.1 7±7.66 26.00±2.00 0.329 0.096
Protein content (%) 0.06±0.04 -0.01 ±0.03 0.12±0.01 0.512 0.054
Protein content (%) 0.07±0.02 -0.01±0.03 0.04±0.02 0.051 0.237
Table 8. DMPT and DYDs by A257G genotype.
Genotype AA AG GG P R2
DMPTs
Milk yield (kg) 8852.08±463.06 7213.43±673.32 4717.50±256.50 0.001 0.524
Fat yield (kg) 351.33±14.22 280.86±30.43 176.50±9.50 0.001 0.588
Protein yield (kg) 292.42±11.05 276.80±26.89 - 0.526 -
Fat content (%) 4.01±0.13 3.86±0.06 3.74±0.00 0.363 0.096
Protein content (%) 3.34±0.11 3.44±0.07 - 0.588 -
BBV (pt) 632.00±99.38 752.00±79.28 1027.00±111.00 0.134 0.129
DYDs
Milk yield (kg) 732.15±453.96 86.00±22.31 50.40±16.40 0.552 0.040
Fat yield (kg) 550.95±86.90 681.29±148.38 1152.60±145.40 0.014 0.256
Protein yield (kg) 28.50±3.18 22.43±7.41 51.60±4.40 0.006 0.296
Fat content (%) 21.40±3.05 24.40±3.96 24.00 0.889 0.010
Protein content (%) 0.07±0.03 -0.03±0.03 0.14±0.01 0.075 0.164
Protein content (%) 0.05±0.02 0.05±0.02 0.06 0.974 0.002
Discussion
CANP316 and CAST282 were previously found to be associated with meat quality traits: meat tenderness by decreased Warner-Bratzler shear force, overall liking and some carcass traits (Gill et al., 2009, Schenkel et al., 2006) and therefore are predominantly studied in beef cattle breeds (Fedota et al., 2017). For northern Australian beef cattle Collis et al. (2012) revealed association between C-allele of CANP316 (CAPN1:c.947C>G) and decreased ability to ovulate prior to weaning, which may affect
calving interval for cows and fat depth between last two ribs. Their other findings included effect of another SNPs in CAPN and CAST genes (CAPN1:g.6545C>T or CAPN1-4751 and CAST:c.2832A>G) on serum concentration of insulin-like growth factor I (IGF-I, ng/ml). C- alleles for CAPN1-4751 being associated with meat tenderness led to decreased IGF-I concentration contrary to A-allele of CAST:c.2832A>G. IGF-I receptors are present in bovine mammary tissue, whereas serum concentrations of IGF-I in lactating cows increases, as well as close arterial infusion of IGF-I into the mammary gland increases milk yield (Cohick, 1999). Therefore observed effects of SNPs CANP316 and CAST282 on DYDs and daughters' milk performance traits in present study could be mediated via IGF-I concentration. Antagonistic genetic correlations of other production traits in steers with age at puberty in heifers was found by Johnston et al. (2009) for two tropical beef genotypes in northern Australia. Cui et al. (2016) discovered the effect of g.-1256 A> C in the promoter region of CAPN1 on semen quality traits in Chinese Holstein bulls, having greater sperm motility in bulls with the genotype CC than in those with the genotype AA.
The observed increase in protein content (%) for CC genotype of CAPN316 can be explained by the higher Ca2+-mediated activity of cytoplasmic calpain involved in the regulation of apoptosis, cell differentiation, synaptic transmission and metabolism of muscle proteins (Miquel et al., 2009). In presence of highly active calpain, the effect of muscle proteins destruction in the smooth muscle of the vessels can lead to the increased low-molecular proteins concentration excreted in milk. The number of C-alleles for SNP CAST282 is associated with a decrease in calpastatin activity (Schenkel et al., 2006) its effect is mediated through calpain activity regulation, and therefore will be less pronounced. The fat content depends on the metabolism of fatty acids, in particular acetic acid and glycerin, localized in Golgi apparatus. The highest fat content in the milk of daughters of heterozygous bulls for both SNPs can be explained by the intermediate activity of the calpain system. Under low Ca2+ concentration, overactive calpain being inhibited by subactive calpastatin (CC genotype for SNP CAST282), primarily triggers the destruction of the cytoskeleton, which destabilizes the Golgi apparatus and stops the synthesis of fatty acids.
Considering pivotal role of IGF-I in lactation and association between GH, GHR and serum IGF-I concentration (Ge et al., 2003, Mullen et al., 2011) it would appear reasonable that SNPs studied affect milk traits. Ge et al. used IGF-I as predictor of growth traits during aging and proved the association between SNP A257G with mean serum IGF-I concentration. According Mullen et al. (2010) and Balogh et al. (2008) GH is related with IGF via stimulation its release from the liver and is key in the control of nutrient utilization and partitioning. By L127V cows had decreased insulin sensitivity in CG compared to CC cows (Balogh 2008), therefore CG cows had higher 305days lactation yield, than CC cows; GG cows were not presented in population analyzed. Otherwise, our data demonstrate the significant superiority of GG cows over CG for milk, protein and fat yield, higher milk yield (%) for DYDs. In review by Kovacs et al. (2006) there were significant effect of C-allele and CC-genotype on milk traits in general, with higher frequency than G allele or GG genotype. The observed effect on daughters' milk performance traits was supported for Ayrshire, Holstein and Jersey bulls (Sabour et al., 1997) and Canadian HF AI bulls (Sabour & Lin 1996). Therefore we can conclude opposite effect on milk performance traits for daughters of sires studied and lactating cows.
Given the interaction between growth hormone and leptin during the regulation of metabolic processes, the noticed association with milk parameters can be explained as mediated through leptin, which relationship with fat content and other milk characteristics was shown before (Trakovicka et al., 2013).
F279Y and A287G are the SNPs in the GHR, therefore they can modulate effects of GH. The effects of F279Y reported by different authors are discordant, while Komisarek et al. (2011) reported significant advantages of TT over TA genotype for milk, protein and fat yield for Jersey cows, and Rahmatalla et al. (2011) observed positive association between A-allele and milk, lactose yield and negative association with somatic cell count. Blott et al. (2003) noted the association for A-allele with increased milk yield by 67-112 kg per lactation and showed a strong relationship with protein content, totally characterizing increased protein yield in Holstein-Frisian and Jersey breeds.
The absence of SNP A257G effect on the analyzed parameters of daughters may be explained by the weak effect of this polymorphic variant with respect to the progeny productivity. We noted that the daughters of bulls with the AA genotype had higher measures compared to the genotype AG, except protein yield. Olenski et al. (2010) found that A-allele had a positive association with milk quality parameters: fat content - by 0.1%, fat yield - by 18.5 kg and protein yield - by 9.1 kg. Waters et al. (2010) estimated allele substitution effect A/G for all milk performance traits as negative and weak but insignificant, although it was significant for growth performance and size. Hradecka et al. (2008) observed the same trend for daughters of German Holstein sires - AA~AG>GG, with fat yield +22.55 kg and fat content -0.058%, whereas milk yield decreased - AA>AG>GG. Thus, discrepancy between observed effects in daughters of bulls and cows for one allele was noted and it was suggested instability of the observed effect determined by polygenic control of these characteristics.
Conclusion
Therefore, high activity of the calpain-calpastatin system enzymes is not associated with the . The fat content and protein yield is higher in daughters of bulls with genotypes VVfor SNP L127Vand FFfor SNP F279Y.
Our results confirm the significant association of the SNPs studied and milk performance traits in daughter produced by Ukrainian dairy sires. Furthermore, we provided new association of SNPs CAPN316 and CAST282 with milk traits, because these SNPs are predominantly known as markers of meat tenderness and quality. We suggest that mechanisms that underlay in high yield are not associated with improvement of productive characteristics in dairy cattle. The results obtained allow to predict the effects of SNP of individual genes on economically important characteristics of the progeny of the estimated bulls, although it is necessary to conduct further studies for of this SNPs effects on reproductive traits in dairy cattle.
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Citation:
Fedota, O., Lysenko, N., Mitiohlo, L., Ruban, S. (2018). Effects of 5 SNPs on daughters' milk performance traits produced by Ukrainian dairy
sires. Ukrainian Journal of Ecology, 8(1), 939-947. I ("OE^^^MlThk work is licensed under a Creative Commons Attribution 4.0. License
