EWA CZERNIAWSKA-PIĄTKOWSKA, MAŁGORZATA
SZEWCZUK
Abstract
The studies were carried out on 255 cows in
The cows of the genotypes with 75.1% to 100% of HF
blood were the best in terms of milk yield (6251 kg). The differences were
significant (p 0≤.05; p ≤ 0.01).
Genetic variability of polymorphic milk protein
patterns was found. In the genotype group with 75.1% to 100% of HF blood, the
highest frequency of the CSN3 A gene was found (0.882), while the frequency of
the CSN3 B gene (0.385), desired for cheese making industry, was the highest in
the group of cows having 25.1% to 50% of HF genes.
Within CSN3 kappa-casein of milk, the allele A
frequencies were higher in relation to the allele B in all the genotype groups
of cows.
Key Words: milk performance, cattle, kappa-casein, beta-lactoglobulin, polymorphism
Zusammenfassung
Titel der Arbeit: Milchleistung und Polymorphismus von
κ-Kasein- und ß-Laktoglobulingenen bei schwarzbunten Kühen mit
verschiedenem Anteil an der Rasse
Holstein-Friesian.
Die
Untersuchungen wurden an 255 in den Jahren 1997-2002 gehaltenen Kühen in der Wojewodschaft Wielkopolskie
durchgeführt. Die Tiere standen im Stall mit einer Kettenanbindehaltung.
Die beste Milchleistung wiesen die Kühe mit dem Genotyp von 75,1 bis 100%
HF-Genanteil auf. Die Unterschiede waren signifikant (p ≤ 0,05; p ≤ 0,01).
Es
wurde eine genetische Differenzierung von polymorphen
Milcheiweißanordnungen festgestellt. In der Genotypgruppe mit einem
HF-Anteil von 75,1 bis 100% wurde die größte Frequenz von Gen CSN3 A
(0,882) festgestellt. Die höchste Frequenz von Gen CSN3
B (0,385), vorteilhaft bei der Käseverarbeitung, wurde in der Gruppe von
Kühen mit dem HF-Anteil 25,1-50,0% ermittelt.
Beim
κ-Kasein CSN3 war in allen
Genotypgruppen die Häufigkeit von Allel A größer.als die des Allels B.
Schlüsselworte: Milchleistung, Rind, κ-Kasein, ß-Laktoglobulin, Polymorphismus
Occurrence of different genetic variants of kappa-casein and beta-lactoglobulin may be associated with quantitative differences in cow milk composition and with a different milk technological quality. Progress in identification of genes that have strong phenotypic effects, including BLG and CSN3, creates possibilities to apply new efficient methods of genetic improvement of livestock populations. Selection decisions should follow a detailed analysis of the genetic structure of the herd; such analyses, however, are still uncommon in the breeding practice.
The aim of this study was to analyse milk performance in association with kappa-casein and beta-lactoglobulin polymorphic variants in BW cows with various share of Holstein-Friesian blood.
The studies
were carried out on 255 cows in
The numerical data presented in Tables have been taken from the farm breeding records.
The material was divided into genotype groups of cows by the share of Holstein-Friesian blood (Table1). 305-d lactations have been taken into consideration. The analysis of the herd's milking performance was performed in respect to the following traits: yield (kg) of milk, fat, and protein, as well as percentage fat and protein.
The results
were processed statistically by means of one-way ANOVA. The means (M), standard
deviations (SD), and coefficients of variability (CV) were calculated. The
statistics were computed using
The material for analysing milk proteins genes polymorphism (PCR-RFLP) was blood collected from external jugular vein in the cows with different share of Holstein-Friesian blood. The DNA was isolated using MasterPureTM Genomic DNA Purification Kit (Epicentre Technologies). Identification of particular alleles of the CSN3 and BLG genes was performed according to methodology by SCHLEE et al. (1992) and BRAUNSCHWEIG et al. (1999).
Basing on the results, we have estimated the frequency of the alleles and genotypes for polymorphic variants of the CSN3 and BLG. In order to see whether the specific population is in genetic equilibrium, the chi-squared test was applied (RUSZCZYC, 1978).
The data presented in Table 2 depict the effect of cows' genotypes, defined as the share of Holstein-Friesian blood, on the level of milk yield. The highest milk yield, 6251 kg, was achieved by cows with a large proportion of HF genes (75.1-100%), while the lowest, 5663 kg, was recorded for the cows with prevailing BW genes in their genotype. In the absolute values, the difference was 588 kg and was statistically significant. A slightly lower difference, 350 kg, though significant at p < 0.05, was found between the cows of 50.1-75% and 75.1-100% HF.
The relationships discussed above were also seen in relation to total fat yield. The highest fat yield in the herd, 255 kg, was recorded in the group with 75.1-100% HF blood, whereas the lowest, 231 kg, was found in the cows of the genotype 25.1-50% HF. Differences significant at p < 0.01 were found between the group of cows with 25.1-50% HF and 75.1-100% HF, while those significant at p < 0.05 were found between the genotypic groups 50.1-75% and 75.1-100% HF. A reverse trend was observed in relation to percentage fat content, which was the best in the cows with prevailing BW genes (4.13%), with their lowest levels, 4.03%, significant at p < 0.05, in the milk of the cows with 50.1-75% HF blood. Intermediate values of fat content, 4.05%, were found in the milk of cows with the highest HF genes share, however this was not important in terms of statistical significance.
Total protein yield for lactation and percentage protein in milk represented the other observed indices. The highest protein yield, 204 kg, significant at p < 0.01, was achieved by the cows with 75.1-100% HF. The crossbreds belonging to the groups 25.1-50% HF and 50.1-75% HF achieved protein yield at similar levels, 188 kg. In the cows 25.1-50% HF, the highest percentage protein milk content was found, 3.29%, with the lowest values, 3.23%, of the parameter found in cows of 50.1-75% HF blood. The difference proved significant at p < 0.01.
Table 3 presents frequencies of polymorphic CSN3 and BLG forms in the particular genotype groups of the studied herd.
As to the frequency of CSN3 polymorphic variants, it was found that the allele A is more frequent than the allele B in all the genotype groups of cows. The highest frequency of the allele A was found in the group of cows with more then 75.1% HF blood, and was qA = 0.882, while the lowest, qA = 0.615, was found in the cows with 25.1-50% HF blood. In turn, the frequency of the allele B of CSN3 was the highest, qB = 0.385, in 25.1-50% HF cows. The lowest frequency of kappa-casein was found in the group of cows with 75.1-100% HF, and was qB = 0.118.
The frequency of the allele B of BLG was higher than that of the allele A of BLG. Only within the group of crossbreds with 25.1-50% HF, the frequency of the allele A, 0.571, was higher than that of the allele B, 0.423 (CZERNIAWSKA-PIĄTKOWSKA 2001; FELEŃCZAK et al. 1987). Similar results were reported by LITWIŃCZUK et al. (1998). The highest allele B frequency, 0.750, was found in the cows with 50.1-75% HF.
Table 4 presents the frequencies of kappa-casein polymorphic variants (CSN3) and the observed and expected distribution of genotypes in the studied population of cows with various share of HF genes. In the group with the highest HF blood share (75.1-100%), 76.39% were AA homozygotes. This was a consequence of the high frequency of CSN3 A allele, 0.882. The BB genotype was not found. In the remaining genotype groups of cows, also AA homozygotes prevailed. For the analysed CSN3 alleles pattern, the observed distribution of genotypes corresponded to the expected distribution, which enables concluding that the studied population of cattle with various HF blood share remained in the genetic equilibrium.
Table 5 presents the frequency of the alleles encoding for beta-lactoglobulin (BLG) polymorphism and the observed and expected distribution of genotypes in the studied population of cows with various share of HF genes. In the group of 25.1-50% HF, AA homozygotes prevailed, which comprised 53.85%, which was a consequence of the high frequency of the BLG A allele, 0.577. In the 50.1-75% of HF group, also BB homozygotes prevailed, 62.50%. On the other hand, the group 75.1-100% HF was dominated by AB heterozygotes (52.78%). In the group of crossbreds 25.1-50% HF, significant differences were found in the observed and expected frequency of genotypes.
Improvement of European breeds of dairy cattle through crossing with the Holstein-Friesian breed has its long-term tradition, with its effects well documented in many in-depth analyses and reports. Conclusions reached by many authors (UDAŁA et al. 1998, ZIEMIŃSKI et al. 1999, CHMIELNIK et al. 1994, KUCZAJ et al. 2001a) are concordant that milk yield increases in proportion to HF blood share, irrespective the age of cows; however, the supremacy of the crossbreds is clear only if the housing and feeding conditions are optimal. The results of this study fully confirm this thesis. Total protein and fat yield increase in a similar way, which is chiefly related with a milk yield per lactation being higher in crossbreds. According to GULIŃSKI et al. (1999), elevated level of HF genes by each 25% results in milk yield increase by 200 kg, and in fat yield growth by about 10 kg. These trends can also by found in protein yield, which has been demonstrated by presented in this study analysis of qualitative indices of milk.
The most controversial results are those concerning protein and fat content in milk of the cross-bred cows. On one hand, it is stressed that the HF breed is important for real improvement of content and yield of these two key milk components (KUCZAJ et al. 2001b); on the other hand, however, views have been presented that fat content drop with an increase of the HF blood, especially in primiparous cows, while only slight variations of percentage protein content are recorded (SZULC et al. 1991). The results of our studies prevents us from taking a stand on the discussed issue, since higher content of protein and fat was found in the group of cows having more BW blood, compared to those with intermediate HF blood share (50.1-75%). On the other hand, the cows with more HF blood were characterised with slightly lower, compared to group I, protein and fat content, with the differences being low, statistically non-significant, and thus difficult to interpret. It should be stressed, however, that proteins and fat content, rather than total yield per lactation, determine milk quality and represent major factors of milk physicochemical properties, which is important for technological value of milk. In this context, protein content is particularly important, determined primarily with the level of expression of six genes, which encode for casein and whey proteins. Two genes of the six are particularly worth mentioning, i.e. those encoding kappa-casein and beta-lactoglobulin.
Four alleles of the kappa-casein-encoding gene have been described so far, with the variants A and B, which differ by amino-acid sequences at sites 136 and 148 of the polypeptide chain, being the most important for the composition of casein-type proteins and for the milk value in cheese production. Milk of the CSN3 BB genotype cows has shorter flocculation time in the process of cheese making, creates firmer clot and results higher output of cheese with better protein and fat retention, as compared to milk of the CSN3 AA genotype cows (JUSZCZAK et al. 2001); this genotype, however, is relatively rare (KAMIŃSKI 1993, VAŠIČEK 1995, MICHALAK 1997, GERNAND and HARTUNG 1997, PANICKE et al. 1998, SORIA et al. 2003). In the performed PCR-RFLP analysis, this relationship was not only confirmed, but it was also demonstrated that the frequency of the desired allele B gradually decreases as the HF blood share grows, which was confirmed by KAMIŃSKI and FIGIEL (1993). This adverse effect probably results from intensifying expansion of Holstein-Friesian cattle, which features the lowest frequencies of B allele of the kappa-casein gene (KAMIŃSKI 1994).
Polymorphic variants of the gene encoding beta-lactoglobulin, for which two alleles have been identified (A and B) controlling creation of three genotypes, have also been demonstrated to be important for milk performance of dairy cows. The AA variant determines higher BLG gene expression level (GRAML and PIRCHNER 2003), which is reflected by higher milk concentration of beta-lactoglobulin. This effect, however, is not positive, since relatively higher content of beta-lactoglobulin is hindering for synthesis of caseins, which comprise more than 80% of total milk proteins. Thus, selection prefers individuals of the BB genotype of LBG giving milk of higher resistance of casein clot and of better protein thermostability, which is particularly important in milk processing in high temperature regimes. In our studies, the highest frequency of the B allele of BLG (0.75) was found in the group of cross-bred cows with 50.1-75% of HF (the group was relatively small in number, n = 16), while the lowest in the cows having more BW genes (0.423). High values for BLG B were found also in cows with prevailing HF gene, 0.569, which was reflected in the results by CZERNIAWSKA-PIĄTKOWSKA (2001), who demonstrated that frequency of the positive B allele grows with an HF genes share increase in crossbreds. Studies by KAMIŃSKI et al. (1996), which were carried out on pure-bred HF cattle (higher frequency of polymorphic BLG B variant) and by JUSZCZAK et al. (2001) for Black-and-White and Red-and-White cows (higher frequency of polymorphic BLG A variant) have confirmed the general relationship that high-yielding Holstein-Friesian cattle is characterised by a relatively high frequency of polymorphic BLG B variant, while Black-and-White cattle may show a reversed relationship.
Protein represents the most important milk component, and is crucial in terms of milk technological value. Protein is also the main factor that forms physiochemical properties of milk. Furthermore, high nutritive value of milk proteins leads to permanent pursuit of efficient methods of increasing protein content in cow milk; selection for increased milk protein content, however, is not very effective. Considering the dynamics of cows' milk composition changes in leading milk producing countries, it seems reasonable to introduce identification of polymorphic CASK3 and BLG genes forms into selection programmes in order to improve milk quality.
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Author's
address
EWA CZERNIAWSKA-PIĄTKOWSKA, PhD;
MAŁGORZATA SZEWCZUK, PhD
Department
of Ruminant Animal Science
Agricultural
Akademia Rolnicza
w Szczecinie
ul. Doktora Judyma 10, 71-460 Szczecin
Poland
e-mail Ewa.Czerniawska-Piatkowska@biot.ar.szczecin.pl
e-mail ewaczp@wp.pl
Table 1. Number of cows by genotype group and lactation number
Tabelle 1: Zahl der Kühe in den einzelnen Genotypgruppen im untersuchten Betrieb mit Berücksichtigung der Laktation.
Lactation |
Genotype group |
Total |
||
25-50% HF |
50.1-75.0% HF |
75.1-100% HF |
||
I |
83 |
90 |
82 |
255 |
II |
74 |
73 |
63 |
210 |
III |
36 |
27 |
39 |
102 |
Total |
193 |
190 |
184 |
567 |
Table 2 Effect of genotype on cows' milk performance.
Tabelle 2: Einfluss des Genotyps der Kühe auf ihre Milchleistung .
% HF |
Descriptive statistics |
Yield in kg |
Yield in % |
|||
milk |
fat |
protein |
fat |
protein |
||
|
M |
5663A |
231A |
188A |
4.13a |
3.29A |
|
Min |
2709 |
102 |
94 |
3.23 |
2.80 |
25.0-50.0 |
Max |
9285 |
376 |
304 |
4.98 |
4.07 |
|
SD |
1366.95 |
55.18 |
43.18 |
0.39 |
0.22 |
|
CV% |
24.14 |
23.87 |
23.00 |
9.37 |
6.62 |
|
M |
5901a |
234B |
188B |
4.03a |
3.23A |
|
Min |
2854 |
107 |
90 |
3.16 |
2.77 |
50.1-75.0 |
Max |
9314 |
360 |
306 |
5.08 |
3.77 |
|
SD |
1409.48 |
58.26 |
45.05 |
0.36 |
0.18 |
|
CV% |
23.88 |
24.94 |
23.94 |
8.99 |
5.66 |
|
M |
6251Aa |
255AB |
204AB |
4.05 |
3.26 |
|
Min |
320 |
86 |
80 |
2.59 |
2.80 |
75.1-100 |
Max |
9250 |
409 |
333 |
4.92 |
3.88 |
|
SD |
1436.02 |
59.36 |
43.95 |
0.41 |
0.20 |
|
CV% |
22.97 |
23.24 |
21.56 |
10.07 |
6.14 |
A,B... differences significant at P ≤ 0.01
a ... differences significant at P ≤ 0.05
Table 3 Allelic frequencies of genes encoding CSN3 and BLG milk proteins.
Tabelle 3: Genfrequenz von polymorphen, Milcheiweiß kodierenden CSN3 und BLG Genanordnungen in der untersuchten Herde je nach HF-Genanteil
Genotype group % HF |
CSN3 |
BLG |
||
A |
B |
A |
B |
|
25.1-50 |
0.615 |
0.385 |
0.577 |
0.423 |
50.1-75 |
0.719 |
0.281 |
0.250 |
0.750 |
75.1-100 |
0.882 |
0.118 |
0.431 |
0.569 |
Table 4 Frequencies of genes controlling milk kappa-casein (CSN3) polymorphism and observed vs. expected distribution of genotypes in the studied population of cows.
Tabelle 4: Frequenz der den Polymorphismus des Kappa-Kaseins (CSN3) kontrollierenden Gene sowie beobachtete und theoretische Genotypverteilung in der untersuchten Population der Kühe mit verschiedenem HF-Genanteil.
% HF |
Gene |
Genotypes |
Observed no.
of animals |
% |
Gene frequency |
Genotype
frequency |
Expected no. of animals |
Chi-squared |
25,1-50 |
|
AA |
7 |
53,85 |
A = 0,615 |
0,3782 |
4,92 |
|
CSN3 |
AB |
2 |
15,38 |
B = 0,385 |
0,4736 |
6,16 |
5,919 |
|
|
BB |
4 |
30,77 |
|
0,1482 |
1,93 |
|
|
50,1-75 |
|
AA |
8 |
50,00 |
A = 0,719 |
0,5170 |
8,27 |
|
CSN3 |
AB |
7 |
43,75 |
B = 0,281 |
0,4041 |
6,47 |
0,108 |
|
|
BB |
1 |
6,25 |
|
0,0790 |
1,26 |
|
|
75,1-100 |
|
AA |
55 |
76,39 |
A = 0,882 |
0,7779 |
56,01 |
|
CSN3 |
AB |
17 |
23,61 |
B = 0,118 |
0,2082 |
14,99 |
1,291 |
|
|
BB |
0 |
0,00 |
|
0,0139 |
1,00 |
|
Table 5 Frequencies of genes controlling milk beta-lactoglobulin (BLG) polymorphism and observed vs. expected distribution of genotypes in the studied population of cows.
Tabelle 5: Frequenz der den Polymorphismus des Beta-Laktoglobulin (BLG) kontrollierenden Gene sowie beobachtete und theoretische Genotypverteilung in der untersuchten Population der Kühe mit verschiedenem HF-Genanteil.
% HF |
Gene |
Genotypes |
Observed no.
of animals |
% |
Gene frequency |
Genotype
frequency |
Expected no. of animals |
Chi-squared |
|
25.1-50 |
|
AA |
7 |
53.85 |
A= |
0.577 |
0.3329 |
4.33 |
|
BLG |
AB |
1 |
7.69 |
B= |
0.423 |
0.4881 |
6.35 |
9.227* |
|
|
BB |
5 |
38.46 |
|
|
0.1789 |
2.33 |
|
|
50.1-75 |
|
AA |
2 |
12.50 |
A= |
0.25 |
0.0625 |
1.00 |
|
BLG |
AB |
4 |
25.00 |
B= |
0.75 |
0.3750 |
6.00 |
1.778 |
|
|
BB |
10 |
62.50 |
|
|
0.5625 |
9.00 |
|
|
75.1-100 |
|
AA |
12 |
16.67 |
A= |
0.431 |
0.1858 |
13.37 |
|
BLG |
AB |
38 |
52.78 |
B= |
0.569 |
0.4905 |
35.31 |
0.419 |
|
|
BB |
22 |
30.56 |
|
|
0.3238 |
23.31 |
|
*value significant at P ≤ 0.01