Selection of reference genes for normalizing gene expression data across seasons in spermatozoa of water buffalo (Bubalus bubalis).

Selection of the most stably expressed reference genes is key to monitoring accurate target gene expression across any tissue or cell type. The mRNA in spermatozoa stores valuable information related to changes in spermatogenesis due to variations in environmental conditions, especially during heat stress, which affects various sperm functions. Semen quality in buffalo bulls is significantly influenced by the seasons. In the study, a panel of nine genes was evaluated to identify the most stably expressed internal control gene (ICG) for the normalization of real-time gene expression data generated across various seasons for Murrah buffalo bulls' spermatozoa. Sperm cells were purified from the semen samples collected during different seasons, with temperature-humidity index (THI) ranging from 80.80 ± 1.47 (hot summer) to 55.88 ± 1.98 (winter), using the BoviPure™ gradient purification method. The RNA isolated from the purified spermatozoa fraction was quality checked prior to reverse transcription and subjected to qPCR (quantitative real-time PCR) based expression analysis. An automated 'endoGene' pipeline was employed to apply the geNorm, NormFinder, and BestKeeper algorithms for data analysis. The result indicated that GAPDH and PP1A were the most stably expressed among the gene panel, whereas ATPSF1 and ACTB were the two least stable expressed reference genes. Further, the most suitable ICGs identified were validated by normalization of real time expression data of heat stress and sperm quality genes, HSFY2 and AKAP4, respectively. The genes identified would help in generating the most reliable results for the expression profiling of the genes dictating sperm quality and heat stress cope-up mechanism in buffalo spermatozoa, collected during different seasons.

Modelling the lactation curve in Alpine × Beetal crossbred dairy goats using random regression models fitted with Legendre polynomial and B-spline functions.

The current study sought to genetically assess the lactation curve of Alpine × Beetal crossbred goats through the application of random regression models (RRM). The objective was to estimate genetic parameters of the first lactation test-day milk yield (TDMY) for devising a practical breeding strategy within the nucleus breeding programme. In order to model variations in lactation curves, 25,998 TDMY records were used in this study. For the purpose of estimating genetic parameters, orthogonal Legendre polynomials (LEG) and B-splines (BS) were examined in order to generate suitable and parsimonious models. A single-trait RRM technique was used for the analysis. The average first lactation TDMY was 1.22 ± 0.03 kg and peak yield (1.35 ± 0.02 kg) was achieved around the 7th test day (TD). The present investigation has demonstrated the superiority of the B-spline model for the genetic evaluation of Alpine × Beetal dairy goats. The optimal random regression model was identified as a quadratic B-spline function, characterized by six knots to represent the central trend. This model effectively captured the patterns of additive genetic influences, animal-specific permanent environmental effects (c2) and 22 distinct classes of (heterogeneous) residual variance. Additive variances and heritability (h2) estimates were lower in the early lactation, however, moderate across most parts of the lactation studied, ranging from 0.09 ± 0.04 to 0.33 ± 0.06. The moderate heritability estimates indicate the potential for selection using favourable combinations of test days throughout the lactation period. It was also observed that a high proportion of total variance was attributed to the animal's permanent environment. Positive genetic correlations were observed for adjacent TDMY values, while the correlations became less pronounced for more distant TDMY values. Considering better fitting of the lactation curve, the use of B-spline functions for genetic evaluation of Alpine × Beetal goats using RRM is recommended.

Optimizing selection strategy for enhancing reproduction efficiency in Indian crossbred goats using milk productivity as a selection criterion.

The present study was aimed at optimizing the selection strategy for enhancing reproductive efficiency and milk productivity of Alpine × Beetal crossbred goats. The data set included 2949 milk trait records across parities and 1389 milk records from first parity and corresponding reproductive traits. The traits included for analysis were 150-day milk yield (150DMY), days in milk (DIM), peak yield (PY) and total milk yield (TMY). The litter size (LS) and litter weight (LW) were used for specifically formulating selection plan using indirect selection. The least squares mean for lactation traits during the first parity were 150DMY: 195.32 ± 2.09 kg, DIM: 236.42 ± 3.04 days, PY: 1.82 ± 0.02 kg, TMY: 269.62 ± 4.52 kg. Notably, Alpine × Beetal goats demonstrated genetic superiority pan India for milk productivity as compared to other native goat breeds. The least squares mean for 150DMY across all parities was 236 ± 3.13 kg. An animal model employing average information restricted maximum likelihood was used for (co)variance component estimation to get the genetic parameters. The analysis revealed total heritability estimates for 150DMY, DIM, PY and TMY as 0.18 ± 0.06, 0.04 ± 0.04, 0.12 ± 0.06 and 0.08 ± 0.05, respectively. Repeatability estimates for 150DMY, DIM, and TMY were 0.28 ± 0.04, 0.21 ± 0.03 and 0.37 ± 0.03, respectively. Bivariate analysis of 150DMY with reproductive traits revealed heritability for LS and LW as 0.05 ± 0.01 and 0.10 ± 0.01, respectively using Gibbs sampling. Strong and positive genetic correlations of 150DMY with other production and reproduction traits was observed, such as DIM (0.72), PY (0.98), TMY (0.88), LS (0.57) and LW (0.33). Moderate heritability and repeatability estimate of 150DMY, along with its positive correlation with production and reproductive traits suggested it as a suitable selection criterion for early selection and overall genetic progress of lactation traits. The genetic trend analysis showed an overall improvement in all these traits, with observed gain of 98.4 g per year for 150DMY, 0.04 days per year for DIM, 0.5 g per year for PY and 220.5 g per year for TMY. We observed that selecting based on 150DMY would lead to a favourable indirect improvement for LW as 79 g and LS 0.04 units per generation. We, therefore, recommend employing 150DMY as the single trait selection criteria to enhance both milk productivity and reproductive potential of Alpine × Beetal goats.

Development and validation of most efficient RNA isolation method from buffalo bull spermatozoa.

BACKGROUND: Being highly fragmented and low in concentration, isolation of good quality RNA from sperm cells is a big challenge. Attempts have been made to evaluate various sperm RNA isolation methods from purified buffalo bull sperm cells. METHODS: Both, non-membrane and membrane-based methods have been evaluated for isolating RNA from Murrah buffalo sperms and compared for their respective efficacies. The traditional TRIzol, TRIzol-heat lysed (H-TRIzol) and cocktail of TCEP-RLT lysis buffer (Qiagen RNeasy mini kit)-TRIzol (C-TRIzol) based isopropanol isolation methods have been evaluated. RESULTS: H-TRIzol yielded best results among conventional methods. The combined T-RLT RNA isolation protocol yielded best quality and quantity compared to other membrane-based methods, due to high lytic property of cocktail of lysis reagents, necessary for complete breakdown of sperm membrane and RNA binding membrane for RNA isolation. Combined lysis performed by treatment with RLT-T and T-RLT differing in order of reagents used were also evaluated. T-RLT combination giving better results compared to RLT-T due to high gDNA contamination and membrane clogging in later protocol steps. CONCLUSION: Overall, in terms of total RNA quantity and quality per million spermatozoa, the heat-lysed TRIzol method (H-TRIzol) performs best among RNA separation techniques employed and is also quite easy to perform. This comparative evaluation of sperm RNA isolation protocols can be useful in deciding the best protocol for isolation of good quality and high concentration sperm RNA from buffalo semen, for transcriptome and other downstream studies.

Influences of maternal factors on the estimate of genetic parameters for goat feed efficiency traits.

The objective of the present study was to estimate the genetic parameters for the feed efficiency traits in Barbari goats. The data records of 9332 progenies born to 413 sires and 2580 dams were collected with respect to the average daily weight gain (ADG), i.e., ADG1 (birth to weaning), ADG2 (weaning to 6 months), ADG3 (6 to 12 months), as well as derived trait Kleiber ratio (KR), i.e., KR1 (ADG1/3MW0.75), KR2 (ADG2/6MW0.75), and KR3 (ADG3/12MW0.75). The data were corrected for fixed covariates like period of kidding, the season of birth, sex, type of birth, and parity. Univariate and multivariate animal models with an average information function of restricted maximum likelihood (REML) were used to estimate genetic factors for these traits. The best model was evaluated based on the likelihood ratio test. The direct heritability estimates were 0.21 ± 0.03, 0.17 ± 0.03, 0.23 ± 0.04, 0.22 ± 0.04, 0.16 ± 0.04, and 0.26 ± 0.04 for ADG1, ADG2, ADG3, KR1, KR2, and KR3, respectively. However, they were inflated due to high and negative estimates of covariance between direct animal and maternal genetic effects. Moderate estimates of heritability augur the scope for improvement for feed efficiency traits. The maternal genetic effects (m2) significantly contributed to 3-12% of the total phenotypic variance. The realized heritability of mass selection, which takes into account direct and maternal genetic variance together, shows a low to moderate estimate of genetic variance for ADG and KR. The genetic correlation ranged from - 0.48 ± 0.11 (ADG1-KR3) to 0.95 ± 0.00 (ADG1-KR1), phenotypic correlation ranged from - 0.28 ± 0.01 (ADG2-KR3) to 0.94 ± 0.01 (ADG1-KR1), maternal genetic correlation ranged from - 0.22 (KR2-KR3) to 0.96 (ADG1-KR1) and - 0.69 (ADG1-KR3) to 0.95 (ADG1-KR1) for the maternal permanent environment, respectively. Kids can be indirectly chosen for higher feed efficiency since ADG and their associated KR have substantial genetic correlations. It is suggested that the KR should be used as a selection criterion for Barbari goats for improving feed efficiency.

Fitting random regression models with Legendre polynomial and B-spline to model the lactation curve for Indian dairy goat of semi-arid tropic.

The present investigation aimed at genetic evaluation of tropical Indian dairy Jamunapari goat using random regression models (RRM) for the estimation of genetic parameters in the first three lactations across test days (TD) and also to come out with a pragmatic breeding plan in the nucleus. Variations in the lactation curves were modelled using 67,172 TD milk yield (TDMY) records. To obtain adequate and parsimonious models for the estimation of genetic parameters, orthogonal Legendre Polynomials (LP) and B-splines (BS) were compared. The analysis was carried out using a single-trait RRM approach. Average TDMY was 0.72, 0.81 and 0.79 kg in 1st to 3rd parities that also had 4th TD peak yield in common. BS function resulted in robust genetic parameters and a smoother curve for lactation as compared to LP. Maternal effects were evaluated and then dropped from the final model, owing to no significant contribution to the genetic variance. The best RRM was a quadratic BS function with six knots for the mean trend, curves of additive genetic, animal permanent environmental (c2 ) and 22 classes of residual variance. Additive variances and heritability (h2 ) estimates were higher in the early lactation. For first parity, the estimates of h2 varied between 0.19 to 0.35 across TD. Moderate h2 estimate suggests further scope for selection using desirable combinations of TD over the lactation. We observed a very high variance due to c2 across TD in three lactations. Genetic correlations were positive and larger between adjacent TDMY and weakened for distant TDMY. Looking into the robust estimates of genetic parameters and better fitting of lactation curve, we suggest the use of B-spline function for regular genetic evaluation of Jamunapari goat.

Estimates of genetic parameters for linear body measurements and prediction of body weight in goat.

The objective of this study is to estimate genetic parameters for linear body measurements along with their correlation to live weight with a focus on devising a scale to predict live weights from body measurement. A total of 142,564 records on body measures and live weights were collected from 8701 Jamunapari goats. Genetic parameters were obtained for body length (L), height at withers (H) and heart girth (G) from birth to adult stage by univariate and multivariate analysis using the average information restricted maximum likelihood method. The best model for body measures at birth included the additive effect of animal and dam along with their covariance and maternal environment, whereas for traits measured later in life, the maternal environment was not significant. After accounting for the direct maternal correlation (ram ), the total heritability estimates for linear body measurements (L,H and G) at the preweaning and postweaning stages of growth ranged from 0.14 to 0.20. Significant genetic variability implies further scope for selection. The genetic correlations of live weight at birth, 3, 6, 9 and 12 months with corresponding L,H and G were high in magnitude indicating scope to select animals for higher weight using morphometric measurements. When weighing scales are unavailable in the field, prediction of weight using L and G was recommended [live weight = (0.291 × L) + (0.306 × G) - 16.8]. We recommend the use of body measurements in the Jamunapari goat breeding program owing to their high genetic correlation with corresponding live weights.

Growth and proliferation of caprine bone marrow mesenchymal stem cells on different culture media.

The growth and proliferation of mesenchymal stem cells are very sensitive in in vitro and a number of factors like media play a significant role in that context. In this study we assessed effect of different media on growth and proliferation of bone marrow derived mesenchymal stem cells (BMMSCs). The BMMSCs were isolated from caprine bone marrow and were subjected to magnetic activated cell sorting against CD90+, CD105+, CD271+and CD34- along with FC blocker. After characterisation, 2 × 104 cells were seeded in 12 well culture plates in four different media viz. MesenCult, MesenPRO, StemPro and complete DMEM (15 % FBS) to study their growth kinetic for 6 days from passage 0 (P0) to passage 3 (P3). The population doubling time (PDT) was derived from growth curve using logarithmic formula. The results showed that the BMMSCs growth and proliferation was highest in MesenCult media in P0 which varied significantly (p < 0.05) from rest of media and from P1 to P3, it was MesenPRO which yielded maximum cells (p < 0.05). The PDT was also in line with growth curve findings. In conclusion, the MesenPRO media had higher growth and proliferation rate from P1 to P3 although MesenCult had higher cell numbers in P0. In conclusion, the use of MesenPRO media could be a better option than conventional media when mesenchymal stem cells are used in clinical applications and other therapeutic purposes taking consideration to its higher growth and proliferation rate. And MesenCult would be a great option to harvest MSCs from P0.

Effect of heat shock protein 70 polymorphism on thermotolerance in Tharparkar cattle.

AIM: Out of various members of heat shock protein (HSP) superfamily which act a molecular chaperon by binding to the denaturing protein thus stabilizing them and preserving their activity, HSP70 are of major importance in thermotolerance development. Thus, present investigation aimed at a screening of HSP70 gene for polymorphisms and possible differences in thermotolerance in Tharparkar breed of cattle. MATERIALS AND METHODS: A 295 bp fragment of HSP70 gene was subjected to polymerase chain reaction-single-strand conformation polymorphism (SSCP) followed by sequencing of different SSCP patterns in 64 Tharparkar cattle. A comparative thermotolerance of identified genotypes was analyzed using heat tolerance coefficients (HTCs) of animals for different seasons. RESULTS: Three SSCP patterns and consequently two alleles namely A and B were documented in one fragment of HSP70 gene. On sequencing, one single-nucleotide polymorphism with G > T substitution was found at a position that led to a change of amino acid aspartate to tyrosine in allele A. It was found that in maintaining near normal average rectal temperature, genotype AA was superior (p≤0.01). Genotype AA, thus, was found to be most thermotolerant genotype with the highest HTC (p≤0.01). CONCLUSION: The polymorphism at HSP70 is expected to be a potent determinant for heat tolerance in cattle, which may aid in selection for thermotolerance in cattle.