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Polymorphic characterization and associations of lactoferrin gene with lactation traits in Friesian and Baladi cattle raised in Egypt

M H Khalil, M H Mohamed1, M M Iraqi and S M Zahed1

Department of Animal Production, Faculty of Agriculture at Moshtohor, Benha University, 13736 Tukh, Kalyoubia Governorate, Egypt
1 Animal Production Research Institute, Agricultural Research Center, Ministry of Agriculture and Land Reclamation, Dokki, Giza, Egypt
maher.khalil@fagr.bu.edu.eg

Abstract

The candidate gene approach is a successful approach in identifying genes and could be useful for quickly detection of the associations between genes and lactation traits in dairy cattle. Although lactoferrin gene is highly polymorphic and it has shown some variants related to lactation traits in dairy cattle, the studies concerning their variabilities and associations with economic traits are scarce, particularly those studies performed in developing countries. A total of 494 lactation records from 180 milking cows raised in three experimental herds in Egypt (142 Friesian in Elkarda and Sakha herds and 38 local Baladi in Elserw herd) were used to characterize lactoferrin gene polymorphism in these populations using PCR-RFLP technique and to investigate the association of genotypes of lactoferrin gene with lactation traits. Yields of milk, fat and protein in Friesian breed was recorded for 10 months, while lactation data in local Baladi herd was available only for six months. A mixed model was used in analyzing data of each herd separately. An amplified PCR product of lactoferrin gene was performed at 800 bp and digested using HinfI restriction enzyme. Three genotypes were obtained, involving AA with one band (800 bp), AB with three bands (800, 650 and 150 bp) and BB with two bands (650 and 150 bps). Sakha Friesian herd was in Hardy Weinberg equilibrium for lactoferrin gene, but Elkarada Friesian and Elserw Baladi herds were both in disequilibrium. The gene frequency of B allele was higher than A allele in Elkarada Friesian and Elserw local herds (0.61 and 0.79 vs 0.39 and 0.21), while the reverse was observed in Sakha Friesian herd. The expected heterozygosity (HE) was moderate in Elkarada Friesian herd (0.47) and Sakha Friesian herd (0.26) and low in Elserw local herd (0.18). The polymorphic information content (PIC) and fixation index (FIS) were moderate in Elkarada Friesian herd (0.36 and 0.29) and Elserw local herd (0.27 and 0.37). In Elkarada Friesian herd, the AA genotype was significantly higher in milk yield (2980 kg) and fat yield (59.0 kg) than the BB genotype, while there were insignificant differences among the genotypes for protein yield. In Sakha Friesian herd, cows of AB genotype were significantly higher in milk yield (2996 kg) and protein yield (46.0 kg) than cows of genotype BB. The BB genotype in Elserw local herd had higher significant 180-day milk yield (681kg) and fat yield (17.2 kg), while AA genotype was significantly higher in protein yield (20.0 kg). Analysis across herds and breeds revealed significant molecular associations of lactoferrin gene SNP genotypes (p<0.05) and lactation traits; cows with AA and AB genotypes were significantly higher in milk, fat and protein yields than cows with BB genotype. In practice, the strong associations among genotypes of lactoferrin gene and yields of milk, fat and protein emphasized the potential of this gene to serve as a candidate gene to select for lactation traits in Friesian and Baladi cattle in Egypt.

Keywords: dairy cattle herds, lactoferrin gene, milk yield and components, molecular associations, PCR-RFLP


Introduction

Selection programs in dairy herds using quantitative genetics methodology are time consuming due to the long generation interval. Several genes located in genome regions of identified quantitative trait loci (QTLs) have been regarded as candidate genes affecting regulatory functions in mammary gland development, milk secretion, milk production traits in dairy cattle (Meuwissen and Goddard 1996; Kaminski et al 2006; Pawlik et al 2014; Nanaei et al 2016). Among many different candidate genes, lactoferrin gene is highly polymorphic and it has shown some variants related to udder health, uterine infections, somatic cell count and mastitis resistance in dairy cattle (Kaminski et al 2006; Wojdak-Maksymiec et al 2006; Zhao et al 2008, 2009; Huang et al 2010; Hajibemani et al 2012; Chopra et al 2013; Hemati-Doust et al 2014; Muhaghegh-Dolatabady and Shafaeipour 2014; Zielak-Steciwko et al 2014; Ateya et al 2016; El-Debaky et al 2019). Also, lactoferrin gene plays important regulatory functions in fertility and reproduction problems (Hajibemani et al 2012; Nanaei et al 2016). However, improving the lactoferrin content in bovine milk could be an interesting way to increase mastitis resistance in dairy cattle (Zhao et al 2008, 2009; Chopra et al 2013; Zielak-Steciwko et al 2014; Ateya et al 2016) and could be feasible on the basis of the estimated heritability of lactoferrin content.

Rapid development in molecular genetics has led to detection of many polymorphic sites throughout the cattle genome in recent years, which can be used in marker-assisted selection programs (e.g. Huang et al 2010; Muhaghegh-Dolatabady 2014; Ateya et al 2016). In concept of SNPs analyses of lactoferrin gene in developing countries, several researchers detected three genotypes of defined as A/A, A/B and B/B in different populations of dairy cattle in Egypt (Ateya et al 2016; El-Debaky et al 2019), in Iran (e.g. Hajibeman et al 2012; Hemati Doust et al 2014; Muhaghegh-Dolatabady 2014) and in Poland (Wojdak-Maksymiec et al 2006; Pawlik et al 2014; Zielak-Steciwko et al 2014). The main aims of the study were: (1) To investigate the molecular characterization of lactoferin gene in terms of genotypic and allelic frequencies, Hardy-Weinberg equilibrium, observed and expected heterozygosity, polymorphic information content and fixation index in two Friesian herds and Baladi herd raised in Egypt, and (2) To detect the possible polymorphic associations among genotypes of lactoferrin gene and yields of milk, fat and protein.


Materials and methods

Lactation records and animals used

A total of 494 lactation records for 180 cows in three herds (62 Friesian Sakha, 80 Friesian Elkarada and 38 Baladi Elserw) were collected on the basis of monthly intervals over four years period from 2013 through 2016. Test day (TD) records for milk, fat and protein yields were measured following an alternative am-pm monthly recording scheme. Data available in Friesian herd were mostly for 10 months of lactation, while the available data in local Baladi herd was mostly for six months of lactation. Milking was practiced twice a day at 7 am and 4 pm throughout the lactation period. Fat and protein yields were measured by the automated method of infrared absorption spectrophotometry (Milk-o-Scan; Foss Electric, Hillerφd, Denmark) at the Dairy Services Unit, Animal Production Research Institute, Sakha, Kafr Elsheikh governorate. TD records were transformed to 305 days milk yield in Friesian herd using Fleishman equation (Kong et al 2018).

Genomic DNA isolation and polymorphism detection

Whole peripheral blood samples were collected from the jugular vein of 180 cows of three herds into test tubes containing an anticoagulant (K3EDTA). Genomic DNA was extracted from Whole Blood Genomic DNA Purification Mini Kit (Cat No. #K0781, Thermo Scientific). After salting out, RFLP method was used to digest PCR product by using HinfI restriction enzyme.

Amplification and PCR reactions

The primers were designed on the basis of DNA sequence of lactoferrin gene promoter accepted by the Gene bank (Accession: AY319306) using the oligonucleotide design tool primer 5.0 software. The primer sequences were 462 to 638 bp where the Forward primer was: 5’-CACATTACAAGCAGGATCTTTTGCTG-3’ and the Reverse primer was 3’-CTGGCCAATGAGCCCTATATGTGT-5’ (Matrix Scientific Trade CO., Egypt). On chromosome number 22, PCR amplifications were performed in a 25 μl mixture containing 0.7 μl forward primer, 0.7 μl reverse primer, 1.5 μl of 2.5 mM dNTP (deoxyribonucleotide triphosphate), 2.5 μl 10Śreaction buffer, 1.5 μl of 2.5 mM MgCl2, 2 μl 1 unit of Taq-DNA polymerase, and 2.5 μl of 50 ng/μl genomic DNA as template. The PCR was performed under the following conditions: 94°C for 4 minutes, followed by 35 cycles of denaturing at 94°C for 30 seconds, annealing at 61°C for 45 seconds, extension at 72°C for 45 seconds; a final extension at 72°C for 10 minutes. PCR products were electrophoretically separated on 0.7% agarose gel at a constant 75 V, stained with Ethidium Bromide and excised for sequencing.

Digestion of PCR products

Digestion using HinfI restriction enzyme was performed in 10 μl mixture containing 8.8 μl PCR products, 0.2 μl HinfI 1μl Buffer. The reaction system was performed under the conditions of 37°C for 3 hour and the resulting fragments were separated on 3% agarose gel and detected by electrophoreses unit and UV unit to detect the number of bands. The genetic molecular weights were detected for each genotype using POPGENE software (Yeh et al 1999). All the molecular investigations were carried out in molecular genetics laboratories of Research Labs Park, Faculty of Agriculture, Benha University, Egypt.

Characterization of lactoferrin gene in Friesian and Egyptian Baladi herds

The Hardy Weinberg equilibrium (HWE) and genotypic and allelic frequencies of lactoferrin gene within each population were estimated using POPGENE program, version 1.31 (Yeh et al 1999). The observed (H O) and expected (HE) heterozygosity were estimated using GENALEX software, version 6.5 (Peakall and Smouse 2012). The polymorphism information content (PIC) was calculated using CERVUS software, version 3 (Kalinowski et al 2007). The reduction in heterozygosity due to inbreeding (i.e. fixation index) within each herd (FIS) was calculated using POPGENE program (Yeh et al 1999).

Model for detecting the association between genotypes of lactoferrin gene and lactation traits

The molecular associations between genotypes of lactoferrin gene and yields of milk, fat, and protein were analyzed for each herd separately using the Mixed procedure of SAS, package 9.0 (Kamp et al 2002) according to the following linear mixed model (in matrix notations):

y = Xb + Za a + Zp p + e

Where: y = The vector of lactation observations; X = The incidence matrix relating the fixed effects to y; b = the vector of the fixed effects of year- season of calving, parity and genotypes of lactoferrin gene restricted by HinfI enzyme (three genotypes); Za = the incidence matrix relating the cow direct additive effects to y; a = the vector of the random direct additive effect associated with the incidence matrix Za; Zp = the incidence matrix relating the permanent environmental effects to y; p = the vector of random permanent environmental effects associated with the incidence matrix Zp; e = the vector of random residual effects. All the individuals with known relationships were considered in the analyses using the animal model. Across all herds and breeds, the same model was used after adding the herd effect in the model to detect molecular associations between genotypes of lactoferrin gene and yields of milk, fat, and protein.


Results and discussion

PCR amplification and PCR-RFLP digestion

The PCR products of lactoferrin gene were amplified in the three herds and DNA fragment of 800 bp was digested using HinfI restriction enzyme and the various variants observed are shown in Figure 1. Similar PCR products and bp size for amplification of the lactoferrin gene have been reported by Zhao et al (2008) in Xinjiang Shihezi dairy cattle and both Muhaghegh-Dolatabady and Shfaeipour (2014) and Nanaei et al (2016) in Holstein cattle.

Figure 1. Representative restriction pattern at Lactoferrin /HinfI locus on 3.0% agarose gel

The PCR product yielded banding pattern corresponding to three different genotypes viz., AA genotype is a common homozygote with one band (800 bp), AB genotype is the most common heterozygote with three bands (800, 650 and 150 bp) and BB genotype the uncommon homozygote with two bands (650 and 150 bps). These results agree with Zhao et al (2008) who showed two alleles and three genotypes for HinfI restriction enzyme in 120 Xinjiang Shihezi cows where the allele with 638 bp was defined as A, whilst the allele with 462 bp as B and the related genotypes were defined as AA, AB and BB.

The observed and expected number of alleles, Hardy-Weinberg equilibrium and genotypic and allelic frequencies in each herd

The observed (NO) and expected (NE) numbers of alleles in the three genotypes of lactoferrin gene are presented in Table 1 for each herd separately. For SNP of lactoferrin gene in Elkarada Friesian herd, the highest NE was obtained in AB genotype (38 cow), while the lowest NE was obtained in AA genotype (12 cow). In Sakha Friesian herd, the highest NE was obtained in AA genotype, while the lowest was in AB genotype. But in Elserw local herd, the highest NE was obtained in BB genotype, while the lowest was in AA genotype.

The Chi-square values for Hardy-Weinberg equilibrium (HWE) of lactoferrin gene in the three herds are given in Table 1. The differences among the three genotypes were significant in Elkarada Friesian herd (χ2= 7.17; p<0.01) and Elserw Baladi herd (χ2 = 5.64; p<0.05), indicating that these two herds were not in HWE for lactoferrin gene. But in Sakha Friesian herd, the differences among different genotypes were limited, indicating that this herd was in HWE for lactoferrin gene. Zielak-Steciwko et al (2014) reported that lactoferrin gene was not in HWE in Polish Red-White population (Chi-square = 11.88; P≤ 0.0005), while it was in HWE in Polish Holstein Friesian population (Chi-square = 2.00; P≤ 0.15). In Holstein cattle, Nanaei et al (2016) reported that Chi-square values for all SNPs of lactoferrin gene were in HWE.

Table 1. The observed and expected number of alleles, Chi square values (χ2) for Hardy-Weinberg equilibrium (HWE) and genotypic and allelic frequencies in three dairy cattle herds raised in Egypt

Breed and herd

Number
of cows

Observed number

Expected number

χ2 value
for HWE

p
value

AA

AB

BB

AA

AB

BB

Friesian, Elkarada

80

18

27

35

12.3

38.4

29.3

7.17**

0.0073

Friesian, Sakha

62

17

29

16

15.9

31.2

14.9

0.32ns

0.5685

Baladi, Elserw

38

4

8

26

1.6

12.8

23.6

5.6*

0.0175

Breed and herd

Number
of cows

Genotypic frequency

Gene frequency

AA

AB

BB

A

B

Friesian,Elkarada

80

0.15

0.48

0.37

0.39

0.61

Friesian, Sakha

62

0.26

0.50

0.24

0.51

0.49

Baladi, Elserw

38

0.05

0.33

0.62

0.21

0.79

ns= Non-significant, *= Chi square values is 3.84 and 6.63 for one df at P<.05 and P<.01

The genotypic frequency of lactoferrin gene were 0.15, 0.48 and 0.37 in Elkarada Friesian herd, 0.26, 0.50 and 0.24 in Sakha Friesian herd, and 0.05, 0.33 and 0.62 in Elserw Baladi herd for AA, AB and BB genotypes, respectively (Table 1). The highest genotypic frequency was recorded for AB genotype in both Elkarada and Sakha Friesian herds (0.48 and 0.50) and BB genotype in Elserw Baladi herd (0.62). Accordingly, AB genotype was the highest frequency in Friesian cattle, but in local cattle BB genotype was the highest. The results of the present study agree with those frequencies of 0.38, 0.02 and 0.6 in Holstein-Friesian reported by Wojdak-Maksymiec et al (2006) and 0.18, 0.05 and 0.77 reported by Chopra et al (2013) in Karan Firies cattle for AA, BB and AB genotypes of lactoferrin gene, respectively.Zielak-Steciwko et al (2014) and Nanaei et al (2016) detected two genotypes of lactoferrin gene (AA and AB) with frequencies of 0.326 and 0.674 in Polish Red-White population, 0.674 and 0.325 in Polish Holstein Friesian population and of 0.606 and 0.394 in Iranian Holstein cattle, respectively.

The allelic frequency of B allele was higher than A allele in Elkarada Friesian herd and Elserw Baladi herd (0.61 and 0.79 vs 0.39 and 0.21), while in Sakha Friesian herd, A allele was higher (0.51) than B allele (0.49). Several researchers showed that the B allele is connected with an increase in somatic cell score and in consequence, it affects protein fraction composition in milk (Wojdak-Maksymiec et al 2006; Zhao et al 2009; Sharifzadeh and Doosti 2011). The same trends of allelic frequencies of A and B lactoferrin gene were observed by Wojdak-Maksymiec et al (2006)t o be 0.68 and 0.32 in Holstein-Friesian, 0.57 and 0.43 by Chopra et al (2013) in Karan Fries cattle and 0.775 and 0.169 by Nanaei et al (2016) in Iranian Holstein cattle, respectively.

Heterozygosity, polymorphic information content and fixation index in each herd

The expected (HE) heterozygosity values of lactoferrin gene were higher than observed (HO) in all herds (Table 2). The cause would be due to the potential population dynamics, selection program and nature of the sampling process. The values of HE were of moderate rate in both herds of Elkarada Friesian (0.47) and Sakha Friesian (0.26), while the value was relatively low in Elserw herd (0.18), i.e. the levels of genetic diversity were intermediate in the three herds. Wojdak-Maksymiec et al (2006) reported that the observed heterozygosity were fewer than expected heterozygosity of lactoferrin gene in Holstein-Friesian.

Table 2. The observed (HO) and expected (HE) heterozygosities and their standard errors (SE), polymorphism information content (PIC) and Fixation index (FIS) for polymorphic genotypes of lactoferrin gene in three herds of Friesian and Baladi cattle raised in Egypt

Breed and herd

No. of cows

HO± SE

HE± SE

PIC

FIS

Friesian, Elkarada herd

80

0.34±0.03

0.47±0.03

0.36

0.29

Friesian, Sakha herd

62

0.14±0.04

0.26±0.04

0.37

0.06

Baladi cattle, Elserw herd

38

0.05±0.02

0.18±0.02

0.27

0.37

The polymorphic information content (PIC) of lactoferrin gene given in Table 2 indicate that the values of PIC were moderate in Elkarada and Sakha Friesian herds (0.36 and 0.37), but it was 0.27 in Elserw Baladi herd. However, these results indicate the importance of PIC as genetic parameter that could be used to show the size of intra-population genetic variation.

The fixation index value of lactoferrin gene (F IS; Table 2) was moderate in Elkarada Friesian herd (0.29) and Elserw Baladi herd (0.37), while it was low in Sakha Friesian herd (0.06), i.e. the highest reduction in heterozygosity due to inbreeding was observed in Elserw Baladi herd and the lowest reduction was observed in Sakha Friesian herd. The low estimate of FIS in Sakha Friesian herd indicating that there was low inbreeding in the population, while high values in Elkarada Friesian and Elserw Baladi herds showed that there was high inbreeding within these populations. However, high inbreeding values can be attributed to non-random mating and to that some loci might be linked to some economic traits. Akyuz et al. (2012) found that FIS value of lactoferrin gene was 0.072 in East Anatolian Red cattle.

Polymorphic associations between genotypes of lactoferrin gene and lactation traits

In Elkarada Friesian herd, the AA genotype was significantly higher in 305-day milk and fat yields than the BB genotype, while there were in-significant differences among the genotypes for protein yield (Table 3). The cows of genotype AB in Sakha Friesian herd had higher significant 305-day milk and protein yields than the cows of BB genotype, i.e. selection of cows with AB genotype could improve milk and protein yields of Friesian cattle in Egypt. Nanaei et al (2016) revealed that the genotype AB of lactoferrin gene had shown significantly higher milk fat percentage in comparison with AA and BB genotypes. Zielak-Steciwko et al (2014) reported that milk with AA genotype in Polish Holstein Friesian cows did not show an analogous relation with protein content.

Table 3. Least squares means and their standard errors for milk, fat and protein yields in different genotypes of lactoferrin gene for each herd separately

Trait

Genotype

No. of
records

Mean

SE

p value

Elkarada Friesian herd

Milk yield, kg

AA

58

2942a

139

0.42

AB

104

2980 a

103

0.42

BB

68

2780b

128

0.42

Fat yield, kg

AA

58

59.0 a

4.0

0.063

AB

104

55.8 ab

2.98

0.063

BB

68

46.9 b

3.69

0.063

Protein yield, kg

AA

58

38.2 a

2.68

0.39

AB

104

40.1 a

2.0

0.39

BB

68

35.8a

2.47

0.39

Sakha Friesian herd

Milk yield, kg

AA

41

2681b

170

0.068

AB

89

2996a

115

0.068

BB

64

2604b

136

0.068

Fat yield, kg

AA

41

61.4 a

4.59

0.056

AB

89

61.5 a

3.11

0.056

BB

64

50.6 a

3.67

0.056

Protein yield, kg

AA

41

43.7 a

3.09

<.0001

AB

89

46.0a

2.09

<.0001

BB

64

31.1b

2.47

<.0001

Elserw local herd (6-months lactation)

Milk yield, kg

AA

11

434b

208.8

0.466

AB

23

479b

58.28

0.466

BB

87

681a

39.48

0.466

Fat yield, kg

AA

11

13.0 b

7.08

0.688

AB

23

19.08a

2.89

0.688

BB

87

17.17a

1.33

0.688

Protein yield, kg

AA

11

20.0 a

5.77

0.53

AB

23

17.8ab

2.35

0.53

BB

87

15.5 b

1.09

0.53

a,b Means within each classification, not followed by the same letters differed significantly (P < 0.05)

In Elserw Baladi herd, the cows of BB genotype had higher significant 180-day milk and fat yields than the cows of AA genotype, and the cows of AA genotype was significantly higher for protein yield than the cows of BB genotype (Table 3), i.e. we can select for AA genotype to improve yields of milk, fat and protein in the Egyptian Baladi cattle.

Analysis across herds and breeds revealed significant molecular associations of SNP genotypes of the lactoferrin gene (p<0.05) with lactation traits (Table 4). The cows with AA and AB genotypes were significantly higher in milk, fat and protein yields than cows with BB genotype. This concept have shown that a single polymorphism within lactoferrin gene was associated with important milk performance traits (e.g. yields of milk, fat and protein, etc), supporting the hypothesis of multifunctional role and pleiotropic effect of lactoferrin gene as reported by many researchers (e.g. Chopra et al 2013; Muhaghegh-Dolatabady and Shafaeipour 2014).

Table 4. Least squares means (LSM), their standard errors (SE) and P-values (P) for milk, fat and protein yields in different genotypes of lactoferrin gene in all pooled herds

Trait

Genotypes

AA (N= 101)

AB (N= 205)

BB (N= 188)

LSM

SE

p value

LSM

SE

p value

LSM

SE

p value

Milk yield, kg

2779a

130.8

<.0001

2817a

91.81

<.0001

1943b

95.87

<.0001

Fat yield, kg

58.86a

3.13

<.0001

55.50a

2.19

<.0001

36.33b

2.29

<.0001

Protein yield, kg

39.69a

2.12

<.0001

40.80a

1.49

<.0001

25.16b

1.56

<.0001

a,b Means within each classification, not followed by the same letters differed significantly (P < 0.05)


Conclusions


Acknowledgments

The authors are appreciated the partial funding of this study by Animal Production Research Institute, Agricultural Research Center, Ministry of Agriculture, Giza, Egypt. The authors are also gratefully acknowledged the members of Research Labs Park, Faculty of Agriculture, Benha University, Egypt for their support and help in carrying out the molecular analyses of the experiment.


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