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.

Morphometric characteristics and microsatellite markers based diversity and differentiation recognizes the first prospective cattle breed from the Jharkhand state of India

India is bestowed with immense cattle biodiversity with 50 registered breeds. However, the majority (59.3%) is yet not characterized. Identification and characterization are the gateways to the management of prized indigenous resources. Present research described a unique cattle population of Jharkhand state, managed under a traditional low-input, low-output system. It was characterized by morphological traits, performance parameters, and management practices. Animals have the characteristic pre-scapular location of the hump. Genetic variation within this population and its differentiation with the six closely distributed cattle breeds were evaluated using FAO recommended microsatellite markers. Jharkhandi cattle have substantial genetic variation based on gene diversity (>0.6) and the average number of alleles per locus (>8). The population did not suffer from a genetic bottleneck in the recent past. Pairwise Nei's genetic distance, phylogenetic relationship, population differentiation, and the correct assignment of all the animals to self group substantiated its separate genetic identity. Since gene flow (Nm = 2.8-7.32) was identified and admixture was indicated by the Bayesian analysis there is a pressing need for scientific management of this population. Results endow authorities with critical information for registering a new Indian cattle breed (Medini) that contributes to the food security, livelihood, and economic sustainability of rural tribal households.

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.

Characterization of a unique Sikkimese yak population of India: a multivariate approach

Native Sikkimese yak in Sikkim state of India is a pastoral treasure being raised through centuries-old transhumance practices and has evolved in response to natural and man-made selection. Currently, the population of Sikkimese yak is at risk with about five thousand total headcounts. Characterization is essential for taking appropriate decisions for conservation of any endangered population. In an attempt to phenotypically characterize the Sikkimese yaks, this study recorded phenotypic morphometric traits information, viz., body length (LG), height at withers (HT), heart girth (HG), paunch girth (PG), horn length (HL), horn circumference (HC), distance between horns (DbH), ear length (EL), face length (FL), face width (FW), and tail length with switch (TL), on 2154 yaks of both sexes. Multiple correlation estimation highlighted that HG and PG, DbH and FW, and EL and FW were highly correlated. Using principal component analysis, LG, HT, HG, PG, and HL were found to be the most important traits for phenotypic characterization of Sikkimese yak animals. Discriminant analysis based on different locations of Sikkim hinted at the existence of two separate clusters, however, broadly, phenotypic uniformity could be observed. Subsequent genetic characterization can offer greater insights and can pave the way for future breed registration and conservation of the population.

Locus minimization in breed prediction using artificial neural network approach

Molecular markers, viz. microsatellites and single nucleotide polymorphisms, have revolutionized breed identification through the use of small samples of biological tissue or germplasm, such as blood, carcass samples, embryos, ova and semen, that show no evident phenotype. Classical tools of molecular data analysis for breed identification have limitations, such as the unavailability of referral breed data, causing increased cost of collection each time, compromised computational accuracy and complexity of the methodology used. We report here the successful use of an artificial neural network (ANN) in background to decrease the cost of genotyping by locus minimization. The webserver is freely accessible (http://nabg.iasri.res.in/bisgoat) to the research community. We demonstrate that the machine learning (ANN) approach for breed identification is capable of multifold advantages such as locus minimization, leading to a drastic reduction in cost, and web availability of reference breed data, alleviating the need for repeated genotyping each time one investigates the identity of an unknown breed. To develop this model web implementation based on ANN, we used 51,850 samples of allelic data of microsatellite-marker-based DNA fingerprinting on 25 loci covering 22 registered goat breeds of India for training. Minimizing loci to up to nine loci through the use of a multilayer perceptron model, we achieved 96.63% training accuracy. This server can be an indispensable tool for identification of existing breeds and new synthetic commercial breeds, leading to protection of intellectual property in case of sovereignty and bio-piracy disputes. This server can be widely used as a model for cost reduction by locus minimization for various other flora and fauna in terms of variety, breed and/or line identification, especially in conservation and improvement programs.

Biometry of frozen–thawed sperm from eight breeds of Indian buffaloes (Bubalus bubalis)

Sperm morphometry, in combination with other objective traits, can be useful for developing a fertility index. The objective of the present study was to measure various biometric end points of frozen-thawed sperm from eight breeds of Indian buffaloes (Murrah, Surti, Tarai, Mehsana, Jaffrabadi, Bhadawari, Pandharpuri and Nili-Ravi). The sperm head of Pandharpuri buffaloes had the greatest length (10.21 microm), width (6.05 microm), area (52.31 microm(2)) and perimeter (31.86 microm). The ratio of sperm width to length was also greatest (0.61) in Pandharpuri as well as in two other breeds, viz. Nili-Ravi and Jaffrabadi. Murrah had the smallest sperm head width (4.75 microm), area (41.65 microm(2)) and perimeter (29.17 microm), but its sperm tail was longest (57.02 microm), along with that of Jaffrabadi buffaloes (56.96 microm). Based on mean values of sperm tail length, mid piece length and its width the eight buffalo breeds were categorized into three, four and five groups, respectively. Multivariate analysis and clustering put six breeds (Surti, Tarai, Mehsana, Jaffrabadi, Bhadawari and Nili-Ravi) in one cluster, whereas Murrah and Pandharpuri appeared as separate entities.

Construction of an RAPD linkage map and localization of QTLs for oleic acid level using recombinant inbreds in mustard (Brassica juncea)

RAPD markers were employed for construction of a linkage map and localization of QTLs for oleic acid level using a set of 94 recombinant inbred lines (RILs) of mustard (Brassica juncea L.) as a mapping population. Only 30% of the 235 random primers used were useful in terms of polymorphism detected and the reproducibility of those patterns. Normal Mendelian segregation was observed for the majority of the 130 markers obtained with 71 informative primers; only 13.1% deviated (P < 0.01) from the expected 1:1 ratio. One-hundred and fourteen markers were assigned to 21 linkage groups (LGs) covering a total length of 790.4 cM with an average distance of 6.93 cM between markers. Two quantitative trait loci (QTL) for oleic acid level were mapped to 14- and 10.6-cM marker intervals on two different LGs. Both loci together explained 32.2% of phenotypic variance. One major QTL explained 28.5% of the trait variance observed in this species.