Single nucleotide polymorphisms of the prolactin receptor (PRLR) gene and its association with growth traits in Chinese cattle

The prolactin receptor: A cross-species comparison of gene structure, transcriptional regulation, tissue-specificity, and genetic variation

The conserved and multifaceted functions of prolactin (PRL) are coordinated through varied distribution and expression of its cell-surface receptor (PRLR) across a range of tissues and physiological states. The resultant heterogeneous expression of PRLR mRNA and protein across different organs and cell types supports a wide range of PRL-regulated processes including reproduction, lactation, development, and homeostasis. Genetic variation within the PRLR gene also accounts for several phenotypes impacting agricultural production and human pathology. The goal of this review is to highlight the many elements that control differential expression of the PRLR across tissues, and the various phenotypes that exist across species due to variation in the PRLR gene.

Comprehensive in silico analysis of prolactin receptor (PRLR) gene nonsynonymous single nucleotide polymorphisms (nsSNPs) reveals multifaceted impact on protein structure, function, and interactions

This study delves into the functional and structural implications of non-synonymous single nucleotide polymorphisms (nsSNPs) within the Prolactin Receptor (PRLR) gene. Thirteen deleterious nsSNPs were identified through bioinformatics tools, with SIFT predicting 168 out of 395 nsSNPs as detrimental, exhibiting tolerance index (TI) scores ranging from 0 to 0.05. Polyphen2 assigned likelihood scores >0.99 to all 13 nsSNPs, indicating high probability of harm, while Panther scores classified most nsSNPs as 'probably damaging', with specific mutations like W218R scoring 0.74, suggesting a higher impact. Stability analysis using DDG I-Mutant and DDG Mupro consistently predicted decreased stability for all mutations, with CUPSAT indicating mutations like V125G and W218R significantly decreasing stability. Structural analysis through DynaMut predicted destabilization for all mutations except L196I and L292H. MutPred2 highlighted structural alterations for all nsSNPs except L196I, L293V, R315W, and S353N. Domain analysis revealed key mutations within essential functional domains, with five nsSNPs located within Fibronectin type-III domains. Bayesian analysis through ConSurf identified 9 critical residues, with 11 nsSNPs exhibiting notably high conservation. STRING analysis unveiled a complex interaction network, indicating involvement in vital biological processes like lactation. Molecular dynamics (MD) simulations, spanning 100 nanoseconds, elucidated structural dynamics induced by detrimental missense SNPs. Post-translational modification (PTM) analysis identified specific mutations, such as R351, involved in methylation, while S353 was implicated in phosphorylation and glycosylation. These findings offer comprehensive insights into the molecular and phenotypic effects of deleterious nsSNPs in the PRLR gene, crucial for selective breeding.Communicated by Ramaswamy H. Sarma.

Association analysis of single-nucleotide polymorphism in prolactin and its receptor with productive and body conformation traits in Liaoning cashmere goats

The results of this study showed that the single-nucleotide polymorphism (SNP) sites of the PRL and PRLR genes have a certain association with the milk production performance, body size and cashmere performance of Liaoning cashmere goats (LCGs). Through our designed experiment, the potential SNPs of LCG were detected by sequence alignment, and two SNPs were found on two genes. The CC genotype of the PRL gene is the dominant genotype among the three genotypes. The GG genotype of the PRLR gene is the dominant genotype among the two genotypes. At the same time, the two genotypes also have good performance in cashmere production and body size. Through the screening of haplotype combination, the milk fat rate > 7.6 %, the milk protein rate > 5.6 %, the milk somatic cell number < 1500 × 103 mL-1, the cashmere fineness < 15.75 µm, the chest girth > 105 cm, the chest depth > 33 cm, and the waist height > 67.5 cm are considered as screening indexes for comprehensive production performance of Liaoning cashmere goats. It is concluded that the GCGC type is the dominant haplotype combination. According to our research data, we found that the biological indicators of Liaoning cashmere goat milk are higher than the national standards, so we think it is very significant to study the milk production performance of our experiment. Further research can be done on goat milk production and body conformation traits around PRL gene and PRLR gene.

Association analysis of prolactin and prolactin receptor genes with selected productive and reproductive traits in Egyptian buffalo

A total of 266 records of buffalo raised in two experimental herds in Egypt were assessed to detect prolactin (PRL) and prolactin receptor (PRLR) genes' polymorphism using PCR-Single Strand Conformational Polymorphism (SSCP) and PCR-Restricted Fragment Length Polymorphism (RFLP) techniques as well as to investigate their association with calf birth weight (BW), weaning weight (WW), lactation period (LP), total milk yield (TMY), stillbirth, calving ease (CE), gestation length (GL), postpartum interval to pregnancy (PPIP), calving interval (CI), and age at first calving (AFC). Predicted breeding values were estimated and used in the association with detected genotypes. A monomorphic pattern of the studied PRL 156 bp segment was recorded and absence of its polymorphism in buffalo was corroborated. We also determined polymorphism of PRLR reflected in three loci: PRLR2, PRLR4, and PRLR9. Significant differences among PRLP9 genotypes (AA, AB, and BB) were displayed for all studied traits as well as among PRLR2 genotypes, except for CE, while PRLR4 genotypes significantly differed only in BW, WW, TMY, stillbirth, GL, and AFC. In practice, strong associations among genotypes of the PRLR gene and the traits of interest candidate this gene to be selective in Egyptian buffalo breeding for improving both productive and reproductive traits.

Goat Genomic Resources: The Search for Genes Associated with Its Economic Traits

Goat plays a crucial role in human livelihoods, being a major source of meat, milk, fiber, and hides, particularly under adverse climatic conditions. The goat genomics related to the candidate gene approach is now being used to recognize molecular mechanisms that have different expressions of growth, reproductive, milk, wool, and disease resistance. The appropriate literature on this topic has been reviewed in this article. Several genetic characterization attempts of different goats have reported the existence of genotypic and morphological variations between different goat populations. As a result, different whole-genome sequences along with annotated gene sequences, gene function, and other genomic information of different goats are available in different databases. The main objective of this review is to search the genes associated with economic traits in goats. More than 271 candidate genes have been discovered in goats. Candidate genes influence the physiological pathway, metabolism, and expression of phenotypes. These genes have different functions on economically important traits. Some genes have pleiotropic effect for expression of phenotypic traits. Hence, recognizing candidate genes and their mutations that cause variations in gene expression and phenotype of an economic trait can help breeders look for genetic markers for specific economic traits. The availability of reference whole-genome assembly of goats, annotated genes, and transcriptomics makes comparative genomics a useful tool for systemic genetic upgradation. Identification and characterization of trait-associated sequence variations and gene will provide powerful means to give positive influences for future goat breeding program.

Molecular characterization and an 80-bp indel polymorphism within the prolactin receptor (PRLR) gene and its associations with chicken growth and carcass traits

The prolactin receptor (PRLR), a type I cytokine receptor, must bind prolactin (PRL) to act on target cells to mediate various physiological functions, including reproduction and lactation. This study identified an 80-bp insertion/deletion (indel) polymorphism in the 3'-untranslated region (3'-UTR) of the chicken PRLR gene in 3736 individuals from 15 breeds and analyzed its associations with growth and carcass traits in an F₂ resource population. The results of the association analysis indicated that the 80-bp indel polymorphism was significantly (P < 0.05) or very significantly (P < 0.01) associated with multiple growth and carcass traits, such as body weight, leg weight, and shank length. In addition, we found that during the breeding process of commercial laying hens and commercial broilers, the 80-bp indel locus was artificially selected for the II genotype. Together, our findings reveal that this 80-bp indel polymorphism has potential as a new molecular marker for marker-assisted selection of chicken growth and carcass traits.

Two indel variants of prolactin receptor (PRLR) gene are associated with growth traits in goat

Prolactin receptor (PRLR) gene plays a crucial role in the milk production, reproduction and the growth of mammals. To fully characterize the structure of the mutation and to further study the function of the goat PRLR gene, two insertion/deletion (indel) loci (12 bp; 16-bp; 5-bp) were detected in 1038 Shaanbei white cashmere (SBWC) goats. Associated analysis revealed that the 16-bp indel mutation was significantly associated the body length, body height, chest depth (CD), body length index (BLI), heart girth index and cannon circumference index (CCI) (p < 0.05). The polymorphism of 5-bp indel was significantly associated with CD, heart girth, CCI and BLI (p < 0.05). Overall, individuals with genotype DD showed better phenotypic traits than individuals with other genotypes at the two loci of PRLR gene in SBWC goat. These findings suggested that the two novel indels within the caprine PRLR gene could be considered as effective DNA molecular markers and could provide a valuable theoretical basis for the application of marker-assisted selection in the goat industry.

Changes in the Expression of the Prolactin Receptor (PRLR) Gene in Different Physiological Stages in the Mammary Gland of the Iranian Adani Goat

The actions of prolactin hormone are mediated by prolactin receptor (PRLR), and proliferation and differentiation of secretory mammary epithelium are dependent on the presence of its receptors. To understand the PRLR expression pattern in mammary gland of dairy goat during different lactation stages, in this study, we first estimated the milk yield breeding value by multitrait random regression model and then compared the expression of the gene in different physiological stage of mammary gland between high- and low-breeding value groups. We assayed the transcription level of the gene by quantitative real-time PCR method, and its outcomes were analysed by a statistical model containing breeding value groups, sampling times and their interactions as fixed effects. The results indicated that the expression levels of PRLR gene were significantly upregulated in the drying stage (p < 0.01). The transcription pattern of the gene was significantly different between the two breeding value groups (p < 0.01), so that the amount of PRLR mRNA was significantly higher in the low-breeding value groups of animals in the lactation stage (p < 0.01). Based on the results of this study, it could be suggested that the abundance of PRLR transcripts in mammary gland of goat might be changed by some physiological, environmental and genetic factors. Nucleotide variations in the promoter region might be resulted in various transcription activities of the gene which should be studied in a complementary research.

Go with the flow-biology and genetics of the lactation cycle

Lactation is a dynamic process, which evolved to meet dietary demands of growing offspring. At the same time, the mother's metabolism changes to meet the high requirements of nutrient supply to the offspring. Through strong artificial selection, the strain of milk production on dairy cows is often associated with impaired health and fertility. This led to the incorporation of functional traits into breeding aims to counteract this negative association. Potentially, distributing the total quantity of milk per lactation cycle more equally over time could reduce the peak of physiological strain and improve health and fertility. During lactation many factors affect the production of milk: food intake; digestion, absorption, and transportation of nutrients; blood glucose levels; activity of cells in the mammary gland, liver, and adipose tissue; synthesis of proteins and fat in the secretory cells; and the metabolic and regulatory pathways that provide fatty acids, amino acids, and carbohydrates. Whilst the endocrine regulation and physiology of the dynamic process of milk production seems to be understood, the genetics that underlie these dynamics are still to be uncovered. Modeling of longitudinal traits and estimating the change in additive genetic variation over time has shown that the genetic contribution to the expression of a trait depends on the considered time-point. Such time-dependent studies could contribute to the discovery of missing heritability. Only very few studies have estimated exact gene and marker effects at different time-points during lactation. The most prominent gene affecting milk yield and milk fat, DGAT1, exhibits its main effects after peak production, whilst the casein genes have larger effects in early lactation. Understanding the physiological dynamics and elucidating the time-dependent genetic effects behind dynamically expressed traits will contribute to selection decisions to further improve productive and healthy breeding populations.

Bivariate genome-wide association analysis of the growth and intake components of feed efficiency

Single nucleotide polymorphisms (SNPs) associated with average daily gain (ADG) and dry matter intake (DMI), two major components of feed efficiency in cattle, were identified in a genome-wide association study (GWAS). Uni- and multi-SNP models were used to describe feed efficiency in a training data set and the results were confirmed in a validation data set. Results from the univariate and bivariate analyses of ADG and DMI, adjusted by the feedlot beef steer maintenance requirements, were compared. The bivariate uni-SNP analysis identified (P-value <0.0001) 11 SNPs, meanwhile the univariate analyses of ADG and DMI identified 8 and 9 SNPs, respectively. Among the six SNPs confirmed in the validation data set, five SNPs were mapped to KDELC2, PHOX2A, and TMEM40. Findings from the uni-SNP models were used to develop highly accurate predictive multi-SNP models in the training data set. Despite the substantially smaller size of the validation data set, the training multi-SNP models had slightly lower predictive ability when applied to the validation data set. Six Gene Ontology molecular functions related to ion transport activity were enriched (P-value <0.001) among the genes associated with the detected SNPs. The findings from this study demonstrate the complementary value of the uni- and multi-SNP models, and univariate and bivariate GWAS analyses. The identified SNPs can be used for genome-enabled improvement of feed efficiency in feedlot beef cattle, and can aid in the design of empirical studies to further confirm the associations.

Genetic analysis of prolactin gene in Pakistani cattle

Prolactin (PRL) is a polypeptide hormone, secreted mainly by the anterior pituitary gland. It is involved in many endocrine activities. The key functions of PRL are related to reproduction and lactation in mammals. To ascertain the presence of polymorphisms in the bovine PRL gene (bPRL), the bPRL gene was sequenced. Five mutations were identified in exonic region and eleven in associated intronic regions in 100 cattle from four Pakistani cattle breeds. Haplotype of predicted amino acid changes represent a common alteration at codon 222 from R-Arginine into K-Lysine in all four breeds. Significant statistical variations were observed in the distribution of single nucleotide polymorphism (SNP) in various cattle populations. However, on basis of present study, an association of these SNPs with milk performance traits in four Pakistani cow breeds cannot be truly replicated but at least can be effective DNA markers for some of the breeds studied. Linkage analysis between these SNPs on larger populations can be useful for the association with milk production traits. Furthermore, present study may be used for marker-assisted selection and management in cattle breeding program in local cattle breeds.

Candidate genes and single nucleotide polymorphisms associated with variation in residual feed intake in beef cattle

The candidate gene approach was used to identify genes associated with residual feed intake (RFI) in beef steers. The approach uses prior knowledge of gene functions to predict their biological role in the variation observed in a trait. It is suited to identify genes associated with complex traits where each gene has a relatively small effect. First, positional candidate genes were identified within the genomic positions of previously reported QTL associated with component traits related to RFI such as dry matter intake (DMI), growth, feed conversion ratio (FCR), average daily gain (ADG), and energy balance. Secondly, the positional candidate genes were prioritized into functional candidate genes according to their biological functions and their relationship with the biological processes associated with RFI including carbohydrate, fat and protein metabolism, thermoregulation, immunity and muscle activity. Single nucleotide polymorphisms (SNPs) located within the functional candidate genes were identified using mRNA sequences and prioritized into functional classes such as non-synonymous (nsSNP), synonymous (sSNP) or intronic SNP. A total of 117 nsSNP were considered as functional SNP and genotyped in steers at the University of Alberta ranch in Kinsella. Multiple marker association analysis in ASReml was performed using RFI data obtained from 531 beef steers. Twenty-five SNP were significantly associated with RFI (P < 0.05) accounting for 19.7% of the phenotypic variation. Using SIFT program to predict the effect of the SNP on the function of the corresponding protein, 3 of the 25 SNP were predicted to cause a significant effect on protein function (P < 0.05). One of the 3 SNP was located in the GHR gene and was also associated with a significant effect on the tertiary structure of the GHR protein (P < 0.05) as modeled using SWISSModel software. Least square means for each genotype were estimated and an over-dominance effect was observed for the SNP located in the GHR, CAST, ACAD11 and UGT3A1 genes. In addition, 2 other SNP showed a dominance effect and 3 genes had an additive effect. Gene network analysis performed in Ingenuity pathway analysis (IPA) software (Ingenuity Systems, www.ingenuity.com) indicated that the significant genes were involved in biological pathways such as lipid, protein and energy metabolism, electron transport and membrane signaling. The genes in this study, if validated in other beef cattle populations, may be useful for marker assisted selection for feed efficiency.

Genetic effects of polymorphisms in the prolactin receptor gene on chicken reproductive traits

Prolactin receptor (PRLR) is a single transmembrane protein through which prolactin plays a wide variety of physiological roles in vertebrates. Markers of alleles for the PRLR gene were assessed for the association with six reproductive traits (bodyweight at first egg; egg weight at first egg; age at first egg; number of eggs at 300 days of age; bodyweight at 300 days of age; and egg weight at 300 days of age) in a single generation of the Erlang Mountain Chicken. Five single-nucleotide polymorphisms were detected in the PRLR gene by sequencing pooled DNA samples. Genotypes were identified using PCR-single strand conformational polymorphism and direct PCR-sequencing methods. The GLM procedure was used to estimate the association between genotypes and reproductive traits. The results showed that at the P1 locus, individuals with genotype TT had shorter age at first egg and greater number of eggs at 300 days of age than those with genotype CC (P < 0.01). Our findings suggest that the single-nucleotide polymorphism g.-14A > G at P1 locus could be a potential genetic marker for age at first egg and number of eggs at 300 days of age in the Erlang Mountain Chicken and haplotype ATGTT might be advantageous for reproductive traits.

Mutations in the exon 10 of prolactin receptor gene change the egg production performance in Wanjiang white goose

To select the molecular genetic markers related to egg performance of Wanjiang white goose, prolactin receptor gene (PRLR) was adopted to be a candidate gene in our study. Five pairs of primers (P1-P5) were designed to detect the SNPs of PRLR gene by PCR-SSCP method. The results revealed that polymorphisms were discovered in the PCR products amplified with P4 primers in PRLR exon 10, three genotypes were found: AA, AB and AC. The sequence of AB genotype is the same as original sequence (DQ660982) in NCBI. There are five mutations in AA genotype: C→A at 840 bp, C→T at 862 bp, T→C at 875 bp, T→A at 963 bp, A→T at 989 bp, resulting in amino acid mutations: His→Asn, Thr→Ile, Asn→Lys, Thr→Ser, and synonymous mutation at 875 bp. Sequencing revealed five mutations in AC genotype: G→T at 816 bp, A→T at 861 bp, C→T at 862 bp, T→C at 875 bp, A→G at 948 bp, causing amino acid mutations of Val→Phe, Thr→Phe, synonymous mutations at 875 and 963 bp. Besides, there are an N-glycosylation site (NQSR), three casein kinase II phosphorylation sites including SIIE, SKTE, and SLMD in AA genotype; three casein kinase II phosphorylation sites including SIIE, SKTE, and TLMD in AB genotype; three casein kinase II phosphorylation sites including SIFE, SKTE, and TLMD in AC genotype. The annual egg yielding of AB genotype geese are significantly more than those of AA and AC genotype geese on the average (P<0.05). It is suggested for the first time that PRLR is a promising candidate gene that can affect egg performance in Wanjiang white goose.