Indian Journal of Animal Research

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Research Article

Indian Journal of Animal Research, volume 54 issue 3 (march 2020) : 275-281

Identification of Genetic Variants in ABCG2 Gene Influencing Milk Production Traits in Dairy Cattle

Arun Pratap Singh1,*, A.K. Chakravarty2, M.A. Mir2, Ashwani Arya3, Manvendra Singh4
1Department of Livestock Production and Management, Krishi Vigyan Kendra, Ajmer-305 206, Rajasthan, India.
2Animal Genetics and Breeding Division, ICAR- National Dairy Research Institute, Karnal-132 001, Haryana, India.
3Krishi Vigyan Kendra, Mahoba-210 423, Uttar Pradesh, India.
4Krishi Vigyan Kendra, Banda-210 001, Uttar Pradesh, India.
Cite article:- Singh Pratap Arun, Chakravarty A.K., Mir M.A., Arya Ashwani, Singh Manvendra (2019). Identification of Genetic Variants in ABCG2 Gene Influencing Milk Production Traits in Dairy Cattle . Indian Journal of Animal Research. 54(3): 275-281. doi: 10.18805/ijar.B-3770.

ABSTRACT

This study was performed to investigate the polymorphisms in the ABCG2 (ATP-binding cassette sub-family G member 2) gene and to reveal the association of genotypes with breeding value (BV) for first lactation milk yield and milk composition traits of Karan Fries (HF crossbred) cattle. The traits were adjusted against the significant effect of non-genetic factors. PCR-RFLP analysis of ABCG2 (exon 14) gene revealed three genotypes. AA genotype in ABCG2 gene had significant effect on BV for average test day fat percentage. The identified potential genetic marker could be used for the development of Marker Assisted Selection (MAS) strategy for higher milk yield and milk composition traits in Karan Fries Cattle.

INTRODUCTION

The application of Marker Assisted Selection (MAS) has the strength to enhance genetic improvement in livestock by direct selection of genes as well as genomic regions that affect economic traits through genomic selection (Dekkers and Hospital, 2002). Marker-based selection is a well known tool for early selection of dairy animals, with higher intensity and accuracy of selection. The advantage of marker based selection over the conventional selection is to select the male animals for milk yield and milk composition traits which are limited to female animals.
       
Candidates genes, markers and quantitative trait loci (QTL) can be used to select desirable animals at an early age, based on their genotypes (Banos et al., 2008). Many candidates genes have been chosen for economically important traits in dairy cattle based on their physiological role in traits of interest or on their being located in genome regions containing previously identified QTLs for these traits. Information of the association between polymorphisms in these candidate genes and traits of economic importance is essential for their effective use in MAS. The ABCG2 (ATP-binding cassette sub-family G member 2) gene is one candidate gene among promising candidates for milk production traits. ABCG2 is a member of the ATP-binding cassette (ABC) superfamily, which transports various xenobiotics and cytostatic drugs across the plasma membrane (Litman et al., 2000). It has been demonstrated that the ABCG2 is liable for the active secretion of clinically essential substrates into mouse milk and that mice that are homozygous for an ABCG2 knock-out mutation lack this function (Jonker et al., 2005). The expression of this gene in the mammary gland is increased significantly during lactation, compared with the dry period (Farke et al., 2008). The bovine ABCG2 gene (NCBI Accession Number AC_00163.1 and Gene ID 536203) is located in the narrow region of chromosome 6 (BTA 6) and spans over 117474 base pairs (bp) long consisting of fifteen introns and sixteen exons encoding 658 amino acids (aa), harbouring the QTL with a large impact on milk production traits (Ron et al., 2006; Olsen et al., 2005). Analysing the sequence variation of SNP (A to C) in exon 14 of the ABCG2 gene, causing the substitution of tyrosine to serine at position 581 (ABCG2-Y581S), has been demonstrated to be the solo polymorphism that meet the segregation status of the QTL based on the allele substitution effect (Cohen-Zinder et al., 2005). The objective of this study was therefore to examine the effect of polymorphisms in the ABCG2 gene on milk production traits in Karan Fries dairy cattle to provide useful markers for higher average test day fat percent in Karan Fries cattle in genetic selection programmes.

MATERIALS AND METHODS

Ethical approval
 
The present study was approved by Institutional Animal Ethics Committee of ICAR- National Dairy Research Institute, Karnal, Haryana.

Description of the study area
 
Karnal is situated at an altitude of 235 to 252 meters (748 feet) above the mean sea level at 29.68°N latitude and 76.98°E longitude in eastern zone of Haryana which comes under the Trans-Gangetic plain agro climatic zone of India. The climate that prevails is subtropical in nature. The temperature in summer months (April to June) ranges between 24°C - 44°C. Karnal experiences moderate rainfall in the months of July and lasts till September. Winters are extremely cold. The temperature ranges from 4°C to 32°C in winter months (October, November, December and January).
 
Standardization and Normalisation of data
 
The records of Karan Fries cows of known pedigree and with normal lactation were included in the present study. The normal lactation was considered as a period of milk production by a cow for at least 100 days, the milk production in lactation was recorded a minimum of 500 kg and the cows calved and dried under normal physiological conditions. Out of 1679 Karan Fries cows, Information of 300 Karan Fries cows were not considered for this study due to various reasons like abortion, still birth and other reproductive problems.
 
Experimental animals and their management
 
The data of first lactation production records of 1379 Karan Fries cows sired by 102 bulls spread over a period of 28 years (1989-2016), were also collected from Record Cell, Animal Genetics and Breeding Division of ICAR-National Dairy Research Institute, Karnal. Blood (8-10 ml) samples were collected aseptically by jugular vein puncture using vacutainers containing EDTA as anticoagulant from randomly selected Karan Fries cattle after obtaining permission from Institute Animal Ethics Committee. 189 animals for PCR-RFLP were used for assessing the effect of SNP markers on breeding values of KF animals for milk yield and milk composition traits.
 
Data source
 
Data on records of 1379 Karan Fries cows from 102 sires, spread over a period of 28 years (1989-2016), maintained at ICAR-National Dairy Research Institute, Karnal were analyzed for first lactation traits viz; First lactation 305-day milk yield (FL305MY-kg), Average test day milk yield (ATDMY-kg), Average test day fat percentage (ATDFP-%), LFY – Lactation fat yield (kg).
 
Average test day milk yield (kg):
 
 
 Average test day fat %:
 
 

Average test day fat yield (g)
 
 
 
Lactation fat yield (kg)
 
LFY = ATDFY × Lactational (305 days or less) milk yield.

Sires having five or more progeny were evaluated on the basis of first lactation records. The study was classified into nine periods viz; 1(1989-1991); 2(1992-1994); 3(1995-1997); 4(1998-2000); 5(2001-2003); 6(2004-2006); 7(2007-2009); 8(2010-2012) and 9(2013-16). Each year was sub-classified into four seasons, depending on prevalent meteorological factors, feed and fodder availability as recorded in CSSRI, Karnal (Singh, 1983). Age at first calving of Karan Fries cows was classified into three age groups using mean and one standard deviation after normalizing the distribution of AFC in the population as 1{≤ 872 (219)}; 2{872-1203 (958)} and 3{≤ 1203 (202)}.
 
DNA isolation
 
Genomic DNA was isolated by Phenol-chloroform method, as described by Sambrook and Russel (2001) with minor modifications was used for DNA isolation from Karan Fries cattle. The quality and quantity of DNA was checked by agarose gel electrophoresis and UV spectrophotometer. The stock solutions were stored at -20°C and used for further analysis. The working solution was prepared by diluting the stock to 100 ng/µL for utilizing as DNA template in PCR.
 
PCR amplification
 
Sequences of the primers used in the PCR for the fragments containing ABCG2-Y581S was as presented in Table 1 (Kgwatalala et al., 2009). PCR reaction was performed in a final volume of 25 μl containing 100 ng of template DNA, 10 pmole of each primer, 10X PCR buffer (20 mM Tris –HCl pH 8.4,50 mM KCl) 1mM Mgcl2, 2.0 mM of dNTPs and 1ml of Taq DNA polymerase (Amnion Biosciences Pvt Ltd, India). This solution was initially denatured at 94°C for 5 min, followed by 35 cycles of denaturation (94°C for 1 min), annealing (58°C for 1 min), elongation (72°C for 1 min) and a final extension at 72°C for 5 min. The amplified products were detected in 1.5% agarose gel electrophoresis. Aliquots of 5 μl of PCR products were applied to the gel. Constant Voltage of 100 V for 1 hour was used for products separation. After electrophoresis, the gel was stained with Ethidium Bromide and images were obtained in UV tech gel document systems (Gel doc 1000, Bio-Rad, USA).
 

Table 1: Primers and PCR-RFLP conditions used for the analysed polymorphism.


 
ABCG2 gene polymorphism
 
Preliminary selection of the restriction enzymes to be used was done using NEBcutterV2.0 by submitting Bos taurus reference sequence of ABCG2 (Accession No: ENSBTAG00000017704). The PCR products were digested with 5 U (Table 1) restriction enzymes (Fermentas, Germany), in 20 μL of reaction volume for 7 h at 37°C for the fragments containing the ABCG2-Y581S, then subjected to electrophoretic separation in 2.5% ethidium bromide- stained agarose gel. The A allele of the ABCG2-Y581S polymorphism was characterized by a single 292-bp fragment, while the C allele was identified by the presence of two fragments of 268 and 24 bp. Tests of Hardy-Weinberg equilibrium for each locus were conducted separately using the software POPGENE (Yeh et al., 2000).
 
SNP identification
 
Sequence data were analysed using Bio edit software Clustal W multiple alignments for detecting single nucleotide polymorphisms (SNPs) by comparing the observed sequence with the Bos taurus reference sequence of ABCG2 gene reference sequence (Ensembl RefSeq: ENSBTAG00000017704).
 
Statistical analysis
 
The effect of non-genetic factors on normalised production traits were studied by least-squares analysis for nonorthogonal data, using fixed linear model (Harvey, 1990). The following models were used with assumptions that different components being fitted into the model were independent and additive. The model for First lactation traits was considered as:
 
                                Yijkl = μ + Pi + Sj + (AG)k + eijkl
 
Where,
Yijkl = observation on lth cow in kth age group of first calving, calved in jth season and ith period of calving; μ = overall mean; Pi = fixed effect of ith period of calving (1 to 9); Sj = fixed effect of jth season of calving (1 to 4); (AG)k = fixed effect of kth age group of animals at first calving (1 to 3) and eijkl= random error ~ NID (0, σ2 e). The difference of means between any two subclasses of period, season and age group will be tested for significance using Duncan’s Multiple Range Test (DMRT) as modified by Kramer (1957).
       
The single trait animal model was considered for estimation of breeding values of KF animals for milk yield and milk composition traits using WOMBAT software (Meyer, 2007) as under:
               
Where,
Yijk = kth observation of jth random effect of ith fixed effect
bi =   Vector of observation of fixed effects (seasons, periods & age groups)
uj   =  Vector of additive genetic effect (Random animal effect)
X  = Design matrix/ Incidence matrix of fixed effect
Z  = Design matrix/ Incidence matrix of random effect
eijk= Vector of residual errors
       
Based on the available records pertaining to milk yield and its constituents on Karan Fries cattle maintained at ICAR-National Dairy Research Institute, Karnal, an attempt was made to find the association of different genotypes of ABCG2 gene with the milk and its constituents were studied. The effect of genotype on individual trait was explored using the, PROC GLM (SAS 4.3) with the help of the following model.

                                Yij  = µ + Gi +eij
Where,
Yij = Breeding value of jth trait under effect ith genotype of SNP
m = Overall mean
Gi = Fixed effect of ith genotype of SNPs
eij  =  Random error ~ NID (0, σ2e)

RESULTS AND DISCUSSION

Non-genetic parameters
 
Average, analysis of variance (ANOVA) of first lactation traits are presented in Tables 2 and 3.
 

Table 2: Mean, standard error and coefficients of variation of first lactation traits of Karan Fries cattle.


 

Table 3: Analysis of variance (M.S values) of first lactation milk yield and milk composition traits of Karan Fries cattle.


 
First lactation 305 days or less milk yield in Karan Fries cattle
 
Average FL305MY was estimated as 3381.31± 37.29 kg with coefficient of variation as 31.16 %. The results are in agreement with Divya (2012), Singh (2014) and Tripathy (2017) who observed similar estimate. However, the present estimate was lower than the report of Kokate (2009) but was higher than the result of Nehra, 2011. Overall least-squares mean of FL305MY was estimated as 3131.31 ± 35.26. Period of calving had significant effect (p<0.01) on FL305MY (Fig 1). Similar result was found by Tripathy, 2017. Season of calving had significant effect (p<0.05) on FL305MY (Fig 1) and was observed by Kokate (2009), Nehra (2011) and Tripathy (2017).
 

Fig 1: Period and season wise variation of First lactation 305-day or less milk yield (kg).


 
Average test day milk yield in Karan Fries cattle
 
ATDMY was estimated as 12.30± 0.13 kg with coefficient of variation as 23.21 % and was almost in agreement to the value 10.94 ± 0.08 found by Tripathy et al., (2017). Higher estimates than the present study in Holstein Friesian cattle was reported by Rekik et al., (2009). Overall least-squares mean for ATDMY was estimated as 11.00 ± 0.10 kg. Period (p<0.01) and season (p<0.05) of calving had significant effect on ATDMY (Fig 2). Mishra (2001) reported significant effect of period and season of calving on ATDMY in Karan Fries cattle.
 

Fig 2: Period and season wise variation of Average test day milk yield (kg).


 
Average test day fat percentage in Karan Fries cattle
 
ATDFP was estimated as 5.07± 0.08 % with coefficient of variation as 8.63 %. Lower estimate of Average lactational fat percentage was reported by Mishra (2001) and Sarkar et al., (2006) in Karan Fries and Radhika et al., (2012) in HF crossbred cattle. Overall least-squares mean for ATDFP was estimated as 4.17 ± 0.007. Period of calving and age group had highly significant effect (p<0.01) whereas, season of calving was non-significant on ATDFP (Fig 3). Significant effect of age of calving in HF cattle was reported by Verma et al., (2014) and season of calving in various breeds of cattle were reported by Missanjo et al., (2010) and Nyamushambaa et al., (2013). Average lactational fat yield in Karan Fries cattle in the present study was observed as 140.54± 4.14 kg with the coefficients of variation 29.56 % (Table 2, Fig 4).
 

Fig 3: Period and age group wise variation of average test day fat percentage (%).


 

Fig 4: Period wise variation of lactation fat yield (kg).


 
Restriction patterns with PstI
 
PCR-RFLP analysis of each PCR products was carried out using PstI, restriction enzyme reported by Cohen-Zinder et al., (2005) for primer pairs for exon 14 of ABCG2 gene for all 189 animals included in the study. The restriction fragments were resolved in 2.5-3.0% agarose gel and visualized in gel documentation system. Restriction fragment sizes and corresponding genotypes of ABCG2 gene are given in Table 4. Genotyping was done according to the band patterns and for each allele and genotype, gene and genotypic frequencies were calculated. PstI-RFLP for targeted region showed polymorphic pattern (Fig 5) with three genotypes; CC (268bp and 24bp), AC (292bp, 268bp and 24bp) and AA (292bp). Genotypic frequencies of AA, AC and CC were 0.83, 0.15 and 0.02 whereas the allelic frequencies for A and C allele were 0.91 and 0.19, respectively (Table 5). Soltani-Ghombavani et al., (2016) in Iranian Holstein cattle also observed a much higher frequency of A allele compared with C allele (97% vs. 3%) of the ABCG2-Y581S locus. Development of crossbred cattle started, by crossing Tharparkar (T) as a Zebu breed and three exotic breeds, namely, Holstein Friesian (H), Brown Swiss (B) and Jersey (J) at National Dairy Research Institute, Karnal. Based on the performance of different genetic groups and adaptability the Breeding Committee of the Institute declared the crosses of Tharparkar and Holstein Friesian as Karan Fries (KF) with 50% to 75% of exotic inheritance of Holstein Friesian in 1982. Since then the KF animals are being maintained and improved at the NDRI through inter-se mating under progeny testing programme. The results observed in the present study support the findings of Ron et al., (2006) who reported that the ABCG2C allele was present only in Bos taurus breed suggesting that ABCG2A is the ancestral allele, and the Y581S substitution occurred after the separation of Bos indicus and Bos taurus lineages.
 

Fig 5: Pst1 PCR-RFLP patterns of ABCG2 gene in Karan Fries cattle.


 

Table 4: Restriction fragment sizes and corresponding genotypes of ABCG2 gene in Karan Fries cattle using Pstl restriction enzyme.


 

Table 5: Genotypic and allelic frequencies of ABCG2 gene using PCR-RFLP in Karan Fries cattle.


 
Association of genotypes with breeding values for first lactation milk yield and milk composition traits
 
The association of ABCG2 gene with milk yield and composition traits are presented in Table 6. The SNP at ABCG2-Y581S locus amplified by primer 14 corresponded to three genotypes among which AA genotype had significant effect (p<0.036) on ATDFP with mean 4.42±0.03. Yue et al., (2011) observed two novel SNPs (45599 A>C and 45610 A>G) in intron 7 of ABCG2 gene in Chinese Holstein cattle. They observed a significant (P<0.05) association between ABCG2 gene polymorphism and milk production traits. Fontanesi et al., (2015) also observed that c.1742 A>C polymorphism in sires of Reggiana cattle breed is responsible for higher fat. The results observed in the present study support the findings of Cohen-Zinder et al., (2005), who observed that animals having A allele have higher fat and protein yield. Mousavizadeh et al., (2013) demonstrated that non-synonymous nucleotide substitution in exon 14, which is associated with fat percentage in Holstein cattle, was observed at only a 2% frequency. Additionally, Tantia et al., (2006) indicated that the presence of fixed alleles of the ABCG2 gene is responsible for higher milk fat yields and higher fat percentages in Indian cattle (B. indicus). According to Olsen et al., (2007) using physical mapping and combined linkage disequilibrium mapping, the QTL region of ABCG2 gene has been fine-mapped and it has been found that the ABCG2-Y581S is the only marker in perfect linkage disequilibrium with the QTL (Olsen et al., 2007). The ABCG2-Y581S has been shown to be associated with milk production traits in Polish Holstein-Friesians (Komisarek and Dorynek, 2009). Yurchenko et al., (2018) found genomic signatures of selective sweeps near key genes related to economically important traits, such as the milk production (e.g., ABCG2), growth (e.g., XKR4), and reproduction (e.g., CSF2).
 

Table 6: Effect of polymorphism of ABCG2 gene on breeding values for first lactation milk yield and milk composition traits in different genotypes.

CONCLUSION

The present study demonstrated the association of polymorphisms at the ABCG2 loci with BV for average test day fat percentage in Karan Fries Cattle. The A variant of the ABCG2 gene was associated with higher BV for average test day fat percentage. Regarding the associations reported in this study, this polymorphism has the potential to be used as marker for higher average test day fat percent in Karan Fries cattle in genetic selection programmes through Marker Assisted Selection.

ACKNOWLEDGMENT

The authors are thankful to Director ICAR-National Dairy Research Institute, Karnal for providing necessary facilities.

CONFLICT OF INTEREST

No conflict of interest exists.

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