Not Available

Not AvailablePH20 hyaluronidase proteins are members of Zona Pellucida Binding Protein family. PH20 hyaluronidase is bifunctional i.e. have hyaluronidase as well as sperm-zona binding activity reportedly. In this study, we performed in silico characterization of novel PH20 protein using partial nucleotide sequences obtained from SNP genotyping of Bubalus bubalis bulls by Sanger dideoxy sequencing method. Possible glycosylation and mannosylation patterns were also predicted in both the PH20 hyaluronidase sequences which may be responsible for its hyaluronidase activity. Further, the potential tertiary structure of PH20 was deduced using Swiss-Model server. The tertiary structure models of PH20 were validated by ProSA server and ramachandran plots. These structural models were assigned PMDB identifiers PM0080458 and PM0080459. Physicochemical characterization revealed that B. bubalis PH20 hyaluronidase are more thermostable and more hydrophobic than that of the cattle PH20 hyaluronidase. The functional annotations were further inferred using gene oOntology based predictions. Present work on structural elucidation of PH20 predicts a reference model for functional genomics studies related to multifunctionality of PH20 hyaluronidase proteins in other species.Not Availabl

Possible solar influence on atmospheric electric field

In this paper a physical mechanism for the electrical coupling of the troposphere, ionosphere and the magnetosphere has been discussed along with the results of analysis of atmospheric electrical field for Colaba, Bombay and geomagnetic data for the 31 year period from 1936-1966. Based on theoretical and observational results possible solar modulation of atmospheric electrification has been investigated

Not Available

Not AvailableThe characteristics of lactation curves and effect of lactation stage, parity and season on milk yield and level of its constituents were investigated in 100 buffaloes varying from parities 1 to 7 at institute farm. Average lactation length overall experimental animals was 323 days. Milk yield,% fat, protein and lactose varied from 4.3 to 9.5 kg, 7.19±0.04 to 8.63±0.07g%, 3.46±0.01 to 3.56 g% and 4.36 to 4.60% respectively. Effect of lactation stage on milk yield, milk fat and lactose content was significant. Milk protein did not vary significantly over the stages of lactation. Lactose increased significantly up to sixth month of lactation, however, change in milk lactose content was not significant thereafter. Milk yield declined significantly during late stage of lactation with a significant concomitant increase in milk fat. Content of milk protein and lactose remained the least variable milk constituents. The study revealed that trend in variation of milk yield and major milk constituents during entire lactation in buffaloes was comparable with cows. Level of milk yield in buffaloes decreased by 9% during hot and humid months due to summer stress and increased by 10.6% during winter in present study. Milk fat level decreased and protein content increased significantly during winter. Milk fat and protein levels were more in advance parities indicating significant effect of parity on milk composition. Data on levels of milk constituents varying over the lactation stages and parities in buffaloes were important phenotype indices for developing genomic selection programme in buffaloes.Not Availabl

Not Available

Not AvailableThe study was undertaken to decipher the microRNA (miRNA) related markers associated with corpus luteum (CL) tropism in buffalo. The data obtained from deep sequencing of CL tissue from different physiological stages was mined in silico for the identification of miRNA-related markers (SSR & SNP). From the present study, 5 annotated and 176 unannotated miRNA were deduced while comparing with Bos taurus genome. In addition, 4 SSRs and 9 SNPs were deduced from the miRNA sequences. These SSRs were on the genes viz. Eukaryotic translation initiation factor 1-like, myocyte enhancer factor 2A, beta casein, T cell receptor gamma cluster 1. The SNP positions on genes viz. PYGO1 (Pygopus family PHD finger 1), LOC100337244 (Multidrug resistance-associated protein 4), FTH1 (Ferritin heavy chain 1), LOC788634 (BOLA class I histocompatibility antigen), PLXND1 (Plexin D1) and UBC (Ubiquitin C) show that these genes play critical role in CL tropism during estrous cycle in buffalo.Not Availabl

Not Available

Not AvailableMachine learning algorithms were employed for predicting the feed conversion efficiency (FCE), using the blood parameters and average daily gain (ADG) as predictor variables in buffalo heifers. It was observed that isotonic regression outperformed other machine learning algorithms used in study. Further, we also achieved the best performance evaluation metrics model with additive regression as the meta learner and isotonic regression as the base learner on 10-fold cross-validation and leaving-one-out cross-validation tests. Further, we created three separate partial least square regression (PLSR) models using all 14 parameters of blood and ADG as independent (explanatory) variables and FCE as the dependent variable, to understand the interactions of blood parameters, ADG with FCE each by inclusion of all FCE values (i), only higher FCE values (negative RFI) (ii), and inclusion of only lower FCE (positive RFI) values (iii). The PLSR model including only the higher FCE values was concluded the best, based on performance evaluation metrics as compared to PLSR models developed by inclusion of the lower FCE values and all types of FCE values. IGF1 and its interactions with the other blood parameters were found highly influential for higher FCE measures. The strength of the estimated interaction effects of the blood parameter in relation to FCE may facilitate understanding of intricate dynamics of blood parameters for growth.Not Availabl

Not Available

Not AvailableMachine learning algorithms were employed for predicting the feed conversion efficiency (FCE), using the blood parameters and average daily gain (ADG) as predictor variables in buffalo heifers. It was observed that isotonic regression outperformed other machine learning algorithms used in study. Further, we also achieved the best performance evaluation metrics model with additive regression as the meta learner and isotonic regression as the base learner on 10-fold cross-validation and leaving-one-out cross-validation tests. Further, we created three separate partial least square regression (PLSR) models using all 14 parameters of blood and ADG as independent (explanatory) variables and FCE as the dependent variable, to understand the interactions of blood parameters, ADG with FCE each by inclusion of all FCE values (i), only higher FCE values (negative RFI) (ii), and inclusion of only lower FCE (positive RFI) values (iii). The PLSR model including only the higher FCE values was concluded the best, based on performance evaluation metrics as compared to PLSR models developed by inclusion of the lower FCE values and all types of FCE values. IGF1 and its interactions with the other blood parameters were found highly influential for higher FCE measures. The strength of the estimated interaction effects of the blood parameter in relation to FCE may facilitate understanding of intricate dynamics of blood parameters for growth.Not Availabl

Not Available

Not AvailableSingle Nucleotide Polymorphism (SNP) is one of the important molecular markers widely used in animal breeding program for improvement of any desirable genetic traits. Considering this, the present study was carried out to identify, annotate and analyze the SNPs related to four important traits of buffalo viz. milk volume, age at first calving, post-partum cyclicity and feed conversion efficiency. We identified 246,495, 168,202, 74,136 and 194,747 genome-wide SNPs related to mentioned traits, respectively using ddRAD sequencing technique based on 85 samples of Murrah Buffaloes. Distribution of these SNPs were highest (61.69%) and lowest (1.78%) in intron and exon regions, respectively. Under coding regions, the SNPs for the four traits were further classified as synonymous (4697) and non-synonymous (3827). Moreover, Gene Ontology (GO) terms of identified genes assigned to various traits. These characterized SNPs will enhance the knowledge of cellular mechanism for enhancing the productivity of water buffalo through molecular breeding.Not Availabl

Not Available

Not AvailableSingle Nucleotide Polymorphism (SNP) is one of the important molecular markers widely used in animal breeding program for improvement of any desirable genetic traits. Considering this, the present study was carried out to identify, annotate and analyze the SNPs related to four important traits of buffalo viz. milk volume, age at first calving, post-partum cyclicity and feed conversion efficiency. We identified 246,495, 168,202, 74,136 and 194,747 genome-wide SNPs related to mentioned traits, respectively using ddRAD sequencing technique based on 85 samples of Murrah Buffaloes. Distribution of these SNPs were highest (61.69%) and lowest (1.78%) in intron and exon regions, respectively. Under coding regions, the SNPs for the four traits were further classified as synonymous (4697) and non-synonymous (3827). Moreover, Gene Ontology (GO) terms of identified genes assigned to various traits. These characterized SNPs will enhance the knowledge of cellular mechanism for enhancing productivity of water buffalo through molecular breeding.Not Availabl

Not Available

Not AvailableThroughout Asian countries including India, water buffalo (Bubalus bubalis) plays a crucial role in socio-economic status of the farmers by providing nutritional security. The concept of genomic selection through genetic markers has been widely used in various livestock species and this is extended to buffalo species as well. Molecular markers have been extensively used in animal breeding for improvements of desirable animal traits. Single Nucleotide Polymorphism (SNP), one of the important molecular markers is widely used in animal breeding program. In this study, SNPs related to four important traits of buffalo i.e., milk volume, age at first calving, post-partum cyclicity and feed conversion efficiency have been identified based on genome sequence data generated using ddRAD (double digest Restriction-site Associated DNA) sequencing technology. These identified SNPs have been compiled as database accessible through Web and can be used in molecular breeding program of buffalo species. This database facilitates easy search of SNPs, Polymorphic Loci and Haplotypes along with their important features like minor and major allele frequencies, observed and expected heterozygosity, observed and expected homozygosity and nucleotide diversity. This database will help to accelerate the molecular breeding program for developing trait specific breeds of buffalo to meet the need of food and nutritional security of the world including India.Network Project on Agricultural Bioinformatics and Computational Biology under Centre for Agricultural Bioinformatics Scheme, ICAR-IASRI, Indian Council for Agricultural Research (ICAR), New Delh