Livestock are a vital part of the Indian economy. With 537 million total livestock population, India stands at first position globally. Of the 303 million total bovine population of the country, 193 million i.e. 36% is constituted by cattle. The exotic/crossbred comprises 51 million (27%) of the total cattle population, out of which 39% alone is contributed by Holstein Friesian crossbred cattle. In the state of Punjab, out of all the cattle population 83% is contributed by exotic/crossbred animals, a large share of which comes from Holstein Friesian crossbred cattle (Breed-wise Report of Livestock and Poultry- Based on 20th Livestock Census). The point of these numbers is to emphasise the dominance of the crossbred population, whose average milk yield (in Punjab) is 13.49 kg/d in 2022–23. (Basic Animal Husbandry Statistics, 2023, DAHD). There is a need for improvement.
Noticeable advances have been made in dairy cattle breeding in the past few decades. Conventional breeding practices are constrained by sex-limited, low heritability and late expressed traits. Now, utilisation of genetic markers allied with traditional breeding strategies for improved selection of genetically superior breeding animals is on the rise. Genetic markers are beneficial for evaluating the genetic basis of observed phenotypic differences (Teneva and Petrovic, Reference Teneva and Petrovic2010). These are any detectable sequences of DNA present on chromosomes linked with individual or species-specific variations which can be used to determine traits of interest. The genetic architecture of traits has proven to be an important tool to heighten genetic improvement. As molecular markers are reported to be more reliable in determining the genetic structure, these are widely used to achieve the purpose of continuation of the existence of species along with preserving the genetic diversity among livestock (Grechko, Reference Grechko2002). Many different genomic regions active on milk yield traits in dairy cattle breeds have been mapped in the last decade (Khatkar et al., Reference Khatkar, Thomson, Tammen and Raadsma2004). Milk composition traits which are of economic relevance in dairy cattle are controlled by several genes. Therefore, their improvement is of significance for animal breeders. In many studies, the relationship between different alleles of the candidate gene and phenotypic traits in the population have been investigated (Kwon and Goate, Reference Kwon and Goate2000).
STATs (signal transducers and activators of transcription) encompass a 7-member family of latent cytoplasmic transcription factors (STATs 1, 2, 3, 4, 5a, 5b and 6) which facilitate the actions of many cytokines and peptide hormones within target cells (Darnell, Reference Darnell1997). They were first found during the interferon signalling pathway study. These get their name as transcription factors as they allow the proteins to control turning on and off these genes by attaching to the regulatory regions, (Meyer et al., Reference Meyer, Marg, Lemke, Wiesner and Vinkemeier2003). STAT genes have a general structure showing a functional modular domain type arrangement, where STAT1 and STAT3 genes are attached to DNA in a clamp-like fashion including a coiled domain of 4 β sheets. These precede the DNA-binding domain facilitating numerous protein–protein interactions. STAT1, STAT4 and both STAT5s show N-domain interactions among two activated STAT dimers which aid in the creation of stable tetramers. All STAT genes, other than STAT2, form greater-order tetramer complexes. STAT1 is an interesting protein with varying transcriptional functions. On being activated, it allows the expression of numerous genes but also supresses the transcription of some of the genes. Therefore, it is involved in both synergistic activation as well as the inhibition of gene expression. STAT1 is highly regulated during the development and differentiation of mammary gland and hence is significant in the process. Reports suggest that STAT1 plays an essential role in development and differentiation process of the mammary gland (Boutinaud and Jammes, Reference Boutinaud and Jammes2004). It is located on chromosome number 2 in bovines and is found to be associated with milk composition traits as well as contributing to improved milk yield. Band et al. (Reference Band, Larson, Rebeiz, Green, Heyen, Donovan, Windish, Steining, Mahyuddin, Womack and Lewin2000) reported that it is linked with milk fat and protein synthesis as well as fat metabolism along with regulation of gene transcription. Ashwell et al. (Reference Ashwell, Heyen, Sonstegard, Van Tassell, Da, Van-Raden, Ron, Weller and Lewin2004) reported the 3′UTR region of STAT1 to be associated with milk fat yield related polymorphism. Significant associations between microsatellite markers and production traits in the vicinity of STAT1 have been observed in whole-genome scans. Ron et al. Reference Ron, Feldmesser, Golik, Tager, Kliger, Reiss, Domochovsky, Alus, Seroussi, Ezra and Weller2004 reported that STAT1 is regulated in the process of mammary gland development and apoptosis and is involved as an oncogene in the mammary gland. Cobanoglu et al. (Reference Cobanoglu, Zaitoun, Chang, Shook and Khatib2006) reported a highly significant association between STAT1 gene polymorphism and milk production traits in Holstein dairy cattle where they found CC and CT genotypes to be associated with higher milk, fat and protein yield of dairy cattle. Khandare et al. (Reference Khandare, Kale, Koringa, Patil and Dhok2020) reported monomorphic as well as polymorphic SNP sites within STAT1 gene in association with milk traits in Gaolao cattle of India. Deng et al. (Reference Deng, Pang, Zhu, Liao, Zhang, Yang and Liang2015) also reported that SNPs in STAT1 possess a significant association with milk production traits.
Crossbreeding, being the most rapid and effective approach for genetic improvement of non-descript zebu cattle, is one of the major steps followed in the country resulting in an increase of milk production by 5–8 fold (Wakchaure et al., Reference Wakchaure, Ganguly, Para, Praveen, Kumar and Sharma2015). The upgrading and genetic improvement of the indigenous cattle in the country for better milk quantity and quality is mainly done by crossbreeding with Jersey and Holstein Friesian cattle breeds. Although being one of most important gene of STAT family, very little work has been done on STAT1 in respect of crossbred cattle. The Holstein Friesian crossbred cattle pertaining to Northern India are our study population, with the objective of identifying polymorphism(s), if any, and to study the relationship between STAT1 gene and milk fat and protein yields in these crossbred animals. Our data should aid in better animal selection which will certainly help in understanding the advanced role of this gene in milk related traits of the animals.
Materials and methods
The study had approval from the Institutional Animal Ethics Committee of Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana (Punjab), INDIA (GADVASU/2021/IAEC/60/14).
Animal records
The milk composition data pertaining to 535 HF crossbred cows were collected for a span of 12 years (2009–2020) from the records and history sheets maintained at Livestock Farm, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana (India). Ludhiana is the most densely populated city of the state of Punjab. It is situated between 30°-34' and 31°-01' north latitude and between 75°-18' and 76°-20' east latitude. As per Koppen climate classification, Ludhiana has a humid subtropical climate. The relative humidity ranges from 46 to 82%. The average temperature ranges from a highest of 42.5°C to a lowest of 16.7°C. The average annual precipitation in the city is around 890 mm each year. Out of these animals, first lactation records of 222 adult HF crossbred cows were used for this study. These records were subjected to correction for non-genetic factors. The non-genetic factors taken into consideration were season of calving, period of calving, interaction of season and period of calving and age at first calving. Season of calving was classified into 5 seasons: Spring (March to Mid-April), Summer (Mid-April to June), Rainy (July to September), Pre-Winter (October to November) and Winter (December to February). Period of calving was classified into 4 January to December two-year periods: 2009 to 2011, 2012 to 2014, 2015 to 2017 and 2018 to 2020. Age at first calving was divided into 3 groups: AG1 (<26.04 months), AG2 (from 26.04 to 31.08 months) and AG3 (>31.08 months).
For comparative analysis, two groups comprising of animals with high milk fat and protein yield (225 and 163 kg, respectively) and low milk fat and protein yield (147 and 141 kg, respectively) were formed. Out of 222 cows, two groups of animals (20 in each group) with highest and lowest milk fat and protein yield in the respective groups, making a total of 40 animals were selected for blood sample collection and further laboratory analysis.
Genotyping
Approximately 5 ml blood was taken by jugular venepuncture into EDTA tubes using aseptic measures and stored at 4°C. Genomic DNA was extracted using Qiagen DNA extraction kit (QIAamp DNA Blood Mini Kit). DNA quality was checked using gel electrophoresis assembly method. The concentration range (ng/μl) and purity (absorbance at 260–280 nm) of the DNA samples were measured using a spectrophotometer (Nanodrop). The 314 bp fragment of STAT1 gene was amplified using the reported set of forward and reverse primers; STATF: 5′-GCCTCAAGTTTGCCAGTGGC-3′ and STATR: 5′-GGCTCCCTTGATAGAACTGT-3′ (Cobanoglu et al., Reference Cobanoglu, Gurcan, Cankaya, Kul and Abaci2016). The amplification was performed in a 25 μl reaction volume. This comprised of 12.5 μl of Go Taq Green PCR Master Mix (Promega), 0.5 μl each of forward and reverse primers, 1 μl of genomic DNA, 10.5 μl of nuclease free water. The PCR amplification programme used consisted of the following time & temperature combinations: Initial denaturation at 95°C for 5 min (1 cycle) followed by 30 cycles each of denaturation, annealing and extension at 95, 55 and 72°C for 45, 30 and 30 s respectively. This was followed by a final extension at 72°C for 5 min (1 cycle). After amplification, the PCR products were stored at 4°C. Agarose gel electrophoresis was carried out to check the amplified PCR products. The gel was then viewed under gel documentation system. The PCR products were digested using BspHI restriction enzyme at 37°C for 1 h. The RE digests were inactivated by incubation at 65°C for 15 min and stored at 4°C thereafter. The PCR products were subjected to Sangers Sequencing. The available sequence with accession number XM_025000697.1 at NCBI for Bos taurus was used as the reference sequence for STAT1 gene. The chromatograms received were first checked for the gene specificity using BLAST software. These were then viewed and interpreted using Finch TV and Clustal Omega (Multiple Sequence Alignment Tool: https://www.ebi.ac.uk/Tools/msa/clustalo/) for detection of SNP.
Statistical analysis
General linear model procedure of statistical analysis system software programme SAS, 2011 (version 9.3) was used for statistical analysis of corrected data (for genetic and non-genetic factors). Association between the genotypes obtained with milk composition traits was studied using least square analysis for fixed effect model with the assumption that the various components that were being fitted into the model were linear, independent and additive.
Statistical model used for least square analysis for the estimation of genetic factors:
$$Y_{no} = {\rm \mu } + M_n + e_{no}$$where, Y nois the character variable ofO thcow, μ is the overall mean of population, M n is the random effect of n thsire and e no is the residual term = ~NID (0,
$\sigma _e^2 $).
Results
Clear bands at 314 bp of STAT1 gene PCR products were observed on a 2% agarose gel after subjecting them to gel electrophoresis (online Supplementary Fig. S1). This confirmed that the extracted DNA is of good quality. The PCR-RFLP results and the sequence alignment tool, Clustal Omega revealed two SNPs at nucleotide position of 201 and 260 of the STAT1 amplicon. All the genotypes were scored based on the banding pattern observed in gel electrophoresis. At position 201, AA and Aa genotypes were observed where, AA genotype was found to be homozygous for two positions i.e. at 2 015 954 and 2 602 015 954 bp DNA fragments. Aa genotype was observed at 3 142 605 954 bp DNA fragments. At position 260, BB and Bb genotypes were observed where, BB genotype was found to be homozygous at one position i.e. at 2 015 954 bp DNA fragments. The Bb genotype was found to be heterozygous for two positions i.e. at 3 142 605 954 and 2 602 015 954 bp DNA fragments. (online Supplementary Fig. S2). Clustal Omega interpretations and results for the two observed SNPs are shown in (online Supplementary Fig. S3). This revealed that SNP at position 201 and 260 aligned that with positions 3173 and 3232 respectively of the reference sequence. The coding sequence (CDS) region of STAT1 gene ranges from 308 to 2557 bp. Thus, these SNPs were found to be located in the 3″ untranslated region (3″UTR) of the gene. At both positions; 3173 and 3232 of the 3″ UTR, ‘C’ nucleotide has been substituted by ‘T’ nucleotide (online Supplementary Fig. S3). The very close proximity of the two SNPs observed here is suggestive of the presence of linkage of alleles A and B in the studied population.
The genotype frequencies for AA and Aa were observed to be 0.8 and 0.2% and for BB and Bb were observed to be 0.25 and 0.75%, respectively (Table 1). The presence of these different genotypes was also confirmed by DNA sequence analysis for STAT1/BspHI. The association study using least square analysis showed a significant association of AA and Aa genotypes for SNP (201, C to T) and BB and Bb genotypes (260, C to T) for STAT1 with milk fat yield as well as milk protein yields (Table 1).
Observed frequencies of the obtained genotypes and least square means and standard errors for 305-day milk fat and protein yields of the different genotypes for STAT1 gene
Least square means with different superscripts for the same site differ significantly (P < 0.05) while those with same superscripts show no significant difference.
Discussion
The STAT1 gene is involved in mammary gland function and development. This study reports the association between STAT1 gene and milk fat and protein yields in Holstein Friesian crossbred cattle. The cattle population chosen for blood sample collection and laboratory analysis was maintained in a uniform environment of the livestock farm complex of Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab where standardised feeding and managemental conditions were followed. Hence, all the animals can easily be considered to be of a homogeneous distribution. The animal grouping based on high and low milk fat and protein yields aimed at analysing any differences among the animals of these groups in relation to STAT1/BspHI as this gene plays a vital role in fat and protein metabolism. Various researchers have conducted experiments using the pooled DNA sequencing approach for detection of polymorphism as well as for the proper estimation of allele frequencies. In prior studies, the pooled DNA samples have been used to detect SNPs in coding and noncoding regions in different genes related to milk production traits (Khatib et al., Reference Khatib, Heifetz and Dekkers2005, Reference Khatib, Leonard, Schutzkus, Luo and Chang2006). In our study, using the DNA sequence-based method, 2 SNPs (C to T) have been detected in the 314 bp fragment of STAT1 gene.
In our experiment, the PCR-RFLP and DNA sequencing results revealed the presence of two SNPs at position 201 and 260 (C to T) of the 314 bp STAT1 gene fragment. This also revealed the presence of a total of four genotypes (AA, Aa; BB, Bb). Two genotypes were observed at each SNP locus instead of the usual three. This can be attributed to the fact that both the observed SNPs lie in very close proximity to each other. This leads to observance of overlapping of the DNA bands in gel electrophoresis picture. Hence, banding pattern common to both the SNPs were observed. This further leads to observance of the AA genotype associated with SNP at 201 being homozygous for two positions while for SNP at 260, the genotype Bb was observed to be heterozygous for two positions. All these results are suggestive of presence of linkage between alleles A and B. Such proximity of the SNPs becomes predominantly the reason for easily heritable patterns in the population. Cobanoglu et al. (Reference Cobanoglu, Gurcan, Cankaya, Kul and Abaci2016) in their study on Turkish cattle using the similar restriction enzyme BspHI reported a DNA fragment at a similar position to our study i.e. at 201 position. They identified 314, 201 and 113 bp fragments for CT genotype, 201 and 113 bp for CC genotype and an intact 314 bp band for TT genotype. Similarly, Askari et al. (Reference Askari, Ansari-Mahyari, Rahimi-Mianji and Asadollahpour-Nanaei2013) reported 201 260 and 54 bp DNA fragments for the 7 genotypes found in their experiment. Ashwell et al. (Reference Ashwell, Heyen, Sonstegard, Van Tassell, Da, Van-Raden, Ron, Weller and Lewin2004) and Ron et al. (Reference Ron, Feldmesser, Golik, Tager, Kliger, Reiss, Domochovsky, Alus, Seroussi, Ezra and Weller2004) in their experiments reported quantitative trait loci affecting milk fat percentage in linkage with microsatellites (38.0 to 60.3 cM) and one affecting milk protein percentages respectively (61.7 to 70 cM). The observed genotypic frequencies for AA, Aa; BB, Bb in our study, were 0.8, 0.2%; 0.25, 0.75% respectively. The frequency of the genotype TT in Holstein cattle has been reported in the range of 7.92–10.63% (Cobanoglu et al., Reference Cobanoglu, Zaitoun, Chang, Shook and Khatib2006; Khatib et al., Reference Khatib, Huang, Mikheil, Schutzkus and Monson2009). Similarly, the minor allele T was observed at a frequency of 15.27%. The frequency of the rare genotype TT was found to be 2.15% by Rychtářova et al. (Reference Rychtářová, Sztankóová, Kyselová, Zink, Štípková, Vacek and Štolc2014).
In this study, we observed a significant association of AA and Aa genotypes for SNP (201, C to T) and BB and Bb genotypes (260, C to T) for STAT1 gene with milk fat yield as well as milk protein yield for all the animals of the studied population. Animals of both the groups, i.e. high and low milk fat and protein yields showed a significant association with all the genotypes observed in the study. This is indicative of the essential role of this gene in relation to milk fat and protein metabolism. The results of this study are consistent with another study on STAT1 gene using PagI restriction enzyme-based PCR-RFLP method in two studied cattle populations by Cobanoglu et al. (Reference Cobanoglu, Zaitoun, Chang, Shook and Khatib2006) where, in one they found that the CC & CT genotypes were observed to be significantly associated with increases in milk fat, and protein yields while in the other population C allele was associated with significant increases in milk fat and protein percentages. Similarly, Askari et al. (Reference Askari, Ansari-Mahyari, Rahimi-Mianji and Asadollahpour-Nanaei2013) in their experiment on Esfahan Holstein cattle reported 7 homozygous genotypes where the frequencies of A, B, C & D alleles were observed to be 0.021, 0.101, 0.332 and 0.546, respectively. They also reported a significant association of all the STAT1/Pag1 genotypes with milk fat percentage. Similarly, Rychtarova et al. (Reference Rychtářová, Sztankóová, Kyselová, Zink, Štípková, Vacek and Štolc2014) observed significant differences between CC and CT genotypes of STAT1 gene for protein percentage as well as in estimated breeding values for fat and protein percentages in Czech Fleckvieh cattle population. However, Cobanoglu et al. (Reference Cobanoglu, Gurcan, Cankaya, Kul and Abaci2016) in their study on STAT1/BspHI polymorphism reported three genotypes, with non-significant effects in Holstein cows. Contrary to this, significant effects were observed for Jersey cows in respect of test day fat and protein yields. Also, Ardicli et al. (Reference Ardicli, Soyudal, Samli, Dincel and Balci2018) reported non-significant differences among STAT1 genotypes with milk fat and protein contents in Holstein cows of Turkey. Vafaee and Mashhadi (Reference Vafaee and Mashhadi2016) also stated a non-significant association of milk fat and protein yields with three genotypes they found in Brown Swiss cattle. Khandare et al. (Reference Khandare, Kale, Koringa, Patil and Dhok2020) reported one monomorphic and three polymorphic sites in respect of milk traits in Gaolao cattle of India using STAT1 gene variants and PagI restriction enzyme. STAT1 gene has also been explored a little in the buffalo population. Kumar et al. (Reference Kumar, Vohra, Ratwan and Chakravarty2015) studied STAT1/HaeIII relationship with milk production traits and reported monomorphic sites in the 3′UTR region of Murrah, Gojri and Chhattisgarhi buffalo breeds of India. Hasan et al. (Reference Hasan, Khaerunnisa and Daulay2021) in their experimental study on Indonesian water buffaloes found polymorphisms at two loci of the STAT1 gene in association with milk production traits. Deng et al. (Reference Deng, Pang, Zhu, Liao, Zhang, Yang and Liang2015) reported that SNPs in STAT1 possess a significant association with milk production traits.
In conclusion, we report two STAT1 SNPs and two genotypes associated with each SNP in HF cross-bred cows. Also, linkage between the two observed alleles was found. Least square analysis showed a significant association of all genotypes with milk fat and protein yields. The slight differences in the patterns observed in this study and those reported by other authors can be attributed to the fact that crossbreeding through artificial insemination method of Bos taurus with indigenous cattle is on the rise. We conclude that this gene can be used as a potential candidate for various marker-assisted selection programmes in HF crossbred cattle in sub-tropical climates.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S0022029924000530
Acknowledgements
The contribution of the Guru Angad Dev Veterinary and Animal Sciences University for providing the necessary resources and the support and valuable inputs of all the authors for completion of the study are highly appreciated.
