Scavenger receptor B1 facilitates the endocytosis of Escherichia coli via TLR4 signaling in mammary gland infection.

SCARB1 belongs to class B of Scavenger receptors (SRs) that are known to be involved in binding and endocytosis of various pathogens. SRs have emerging role in regulating innate immunity and host-pathogen interactions by acting in co-ordination with Toll-like receptors.Query Little is known about the function of SCARB1 in milk-derived mammary epithelial cells (MECs). This study reports the role of SCARB1 in infection and its potential association in TLR4 signaling on bacterial challenge in Goat mammary epithelial cells (GMECs). The novelty in the establishment of MEC culture lies in the method that aims to enhance the viability of the cells with intact characteristics upto a higher passage number. We represent MEC culture to be used as a potential infection model for deeper understanding of animal physiology especially around the mammary gland. On E.coli challenge the expression of SCARB1 was significant in induced GMECs at 6 h. Endoribonuclease-esiRNA based silencing of SCARB1 affects the expression of TLR4 and its pathways i.e. MyD88 and TRIF pathways on infection. Knockdown also affected the endocytosis of E.coli in GMECs demonstrating that E.coli uses SCARB1 function to gain entry in cells. Furthermore, we predict 3 unique protein structures of uncharacterized SCARB1 (Capra hircus) protein. Overall, we highlight SCARB1 as a main participant in host defence and its function in antibacterial advances to check mammary gland infections. Video Abstract.

Morphometric indices of native sheep breeds of the Himalayan region of India using multivariate principal component analysis.

This study was performed to analyze the morphometric traits and indices in 3000 animals of five registered sheep breeds in the Himalayan region under a multivariate approach. Data were recorded under field conditions with equal coverage of the five breeds, viz., Karnah, Gurez, Poonchi, Bakerwal and Changthangi on body length (BL), height at withers (HW), chest girth (CG), ear length (EL), and tail length (TL). Furthermore, four derived traits (indices) were studied, which included an index of body frame (IBF), an index of thorax development (ITD), a Baron-Crevat index (BCI), and an index of body weight (IBW). Multivariate principal component analysis (PCA) was undertaken on nine morphometric traits. Kaiser's criterion was used to reduce the number of principal components for further analysis and interpretation. The adequacy of sampling was evaluated using Kaiser-Meyer-Olkin (KMO) test and Bartlett's test of sphericity. The mean BL ranged from 52.15 (Changthangi) to 71.13 (Gurez). The estimates of HW, CG, EL and TL were highest in Gurez (63.49), Bakerwal (84.82), Bakerwal (7.26), and Karnah (8.18) breeds, respectively. Among the derived traits, the highest IBF was observed in the Gurez breed with an estimate of 112.22. Upon multivariate PCA on the dataset, the first four principal components were able to explain 92.117% of the total variance. The KMO test, Bartlett's test of sphericity and estimated communalities showed the appropriateness of PCA on the evaluated traits. Four eigenvalues were greater than one and were extracted for further analysis. Morphometric traits were highly correlated, except for EL and TL that showed lower correlation estimates with other traits. The Changthangi population showed the lowest estimates of BL, HW, CG and rectangular body frame. The present study ascertained important morphometric traits/indices that can help in developing selection criteria and formulating sustainable breeding and conservation plans vis-à-vis the unique sheep breeds of the temperate Himalayas.

Comparative RNA-Seq analysis reveals insights in Salmonella disease resistance of chicken; and database development as resource for gene expression in poultry.

Salmonella, one of the major infectious diseases in poultry, causes considerable economic losses in terms of mortality and morbidity, especially in countries that lack effective vaccination programs. Besides being resistant to diseases, indigenous chicken breeds are also a potential source of animal protein in developing countries. For understanding the disease resistance, an indigenous chicken line Kashmir faverolla, and commercial broiler were selected. RNA-seq was performed after challenging the chicken with Salmonella Typhimurium. Comparative differential expression results showed that following infection, a total of 3153 genes and 1787 genes were differentially expressed in the liver and spleen, respectively. The genes that were differentially expressed included interleukins, cytokines, NOS2, Avß-defensins, toll-like receptors, and other immune-related gene families. Most of the genes and signaling pathways involved in the innate and adaptive immune responses against bacterial infection were significantly enriched in the Kashmir faverolla. Pathway analysis revealed that most of the enriched pathways were MAPK signaling pathway, NOD-like receptor signaling pathway, TLR signaling pathway, PPAR signaling pathway, endocytosis, etc. Surprisingly some immune-related genes like TLRs were upregulated in the susceptible chicken breed. On postmortem examination, the resistant birds showed small lesions in the liver compared to large necrotic lesions in susceptible birds. The pathological manifestations and RNA sequencing results suggest a balancing link between resistance and infection tolerance in Kashmir faverolla. Here we also developed an online Poultry Infection Database (https://skuastk.org/pif/index.html), the first publicly available gene expression resource for disease resistance in chickens. The available database not only shows the data for gene expression in chicken tissues but also provides quick search, visualization and download capacity.

Climate plays a dominant role over land management in governing soil carbon dynamics in North Western Himalayas.

The soil carbon (C) dynamics is strongly influenced by climate and land-use patterns in the Himalayas. Therefore, soils under five prominent land use [e.g., maize (Zea mays), horticulture, natural forest, grassland, and wasteland] were sampled down up to 30 cm depth under two climatic conditions viz., temperate and subtropical to assess the impacts of climate and landuse on soil C dynamics. Results demonstrated that irrespective of land use, temperate soil contains 30.66% higher C than subtropical soils. Temperate soils under natural forests had the higher total organic carbon (TOC, 21.90 g kg-1), Walkley-Black carbon (WBC, 16.42 g kg-1), contents, and stocks (TOC, 66.92 Mg ha-1 and WBC, 50.24 Mg ha-1), and total soil organic matter (TSOM, 3.78%) concentration as compared to other land uses like maize, horticulture, grassland, and wasteland. Under both climatic conditions, maize land use had the lowest TOC 9.63, 6.55 g kg-1 and WBC 7.22, 4.91 g kg-1 at 0-15 and 15-30 cm soil depth, respectively. Horticulture land use had 62.58 and 62.61% higher TOC and WBC over maize-based land use under subtropical and temperate climatic conditions at 0-30 cm soil depth, respectively. However, soils of maize land use under temperate conditions had ∼2 times more TOC than in subtropical conditions. The study inferred that the C-losses is more in the subtropical soil than in temperate soils. Hence, the subtropical region needs more rigorous adoption of C conservation farming practices than the temperate climatic setting. Although, the adoption of C storing and conserving practices is crucial under both climatic settings to arrest land degradation. Horticultural land uses along with conservation effective soil management practices may be encouraged to restore more soil C and to improve the livelihood security of the hill populace in the North Western Himalayas.

Comparison of various models for the estimation of heritability and breeding values.

The exploration of additive genetic variance for the selection of animals is the central paradigm in quantitative genetics and it is important to use appropriate animal models considering important factors. This study compares various factor effects for heritability and breeding values estimations on data collected on the Corriedale. Overall, the heritability estimates were the highest for birthweight (BW). Both the additive genetic variance and the heritability values were reduced upon adding more random effects. Year-effect as random reduced the heritability except for BW. The highest average accuracy for breeding values for birth, weaning, 6, 9, and 12-month-weights for were 0.656, 0.567, 0.519, 0.486, and 0.515. These were observed for models having sex or sex and parity as fixed effects. It is concluded that fixed and random factors have a significant impact on genetic-factors and breeding-value accuracies and should be considered during selection programs and make the selection program more effective.

Comparative transcriptomics unravels new genes imparting scab resistance in apple (Malus x domestica Borkh.).

Apple scab is caused by an ascomycete fungus, Venturia inaequalis (Cke.) Wint., which is one of the most severe disease of apple (Malus × Domestica Borkh.) worldwide. The disease results in 30-40% fruit loss annually and even complete loss in some places. Owing to the evolving susceptibility of resistant apple genotypes harboring R-genes to new variants of V. inaequalis, a comparative transcriptome analysis using Illumina (HiSeq) platform of three scab-resistant (Florina, Prima, and White Dotted Red) and three susceptible (Ambri, Vista Bella, and Red Delicious) apple genotypes was carried out to mine new scab resistance genes. The study led to the identification of 822 differentially expressed genes in the tested scab-resistant and scab-susceptible apple genotypes. The most upregulated genes uniformly expressed in resistant varieties compared to susceptible ones were those coding for 17.3 kDa class II heat shock protein-like, chaperone protein ClpB1, glutathione S-transferase L3-like protein, B3 domain-containing protein At3g18960-like, transcription factor bHLH7, zinc finger MYM-type protein 1-like, and nine uncharacterized proteins, besides three lncRNAs. The genes that were downregulated in susceptible and upregulated in resistant cultivars were those coding for non-specific lipid transfer protein GPI-anchored 1, rust resistance kinase Lr10-like, disease resistance protein RPS6-like, and many uncharacterized proteins. DESeq2 analysis too revealed 20 DEGs that were upregulated in scab-resistant cultivars. Furthermore, a total of 361 genes were significantly upregulated in scab-susceptible variety, while 461 were found downregulated (P value < 0.05 and Log2 (FC) > 1). The differentially expressed genes (DEGs) were related to various pathways, i.e., metabolic, protein processing, biosynthesis of secondary metabolites, plant hormone signal transduction, autophagy, ubiquitin-mediated proteolysis, plant-pathogen interaction, lipid metabolism, and protein modification pathways. Real-time expression of a set of selected twelve DEGs further validated the results obtained from RNA-seq. Overall, these findings lay the foundation for investigating the genetic basis of apple scab resistance and defense pathways that might have a plausible role in governing scab resistance in apple against V. inaequalis.

Comparative milk proteome analysis of Kashmiri and Jersey cattle identifies differential expression of key proteins involved in immune system regulation and milk quality.

BACKGROUND: Exploration of the bioactive components of bovine milk has gained global interest due to their potential applications in human nutrition and health promotion. Despite advances in proteomics profiling, limited studies have been carried out to fully characterize the bovine milk proteome. This study explored the milk proteome of Jersey and Kashmiri cattle at day 90 of lactation using high-resolution mass spectrometry based quantitative proteomics nano-scale LC-MS/Q-TOF technique. Data are available via ProteomeXchange with identifier PXD017412. RESULTS: Proteins from whey were fractionated by precipitation into high and low abundant proteins. A total of 81 high-abundant and 99 low-abundant proteins were significantly differentially expressed between Kashmiri and Jersey cattle, clearly differentiating the two breeds at the proteome level. Among the top differentiating proteins, the Kashmiri cattle milk proteome was characterised by increased concentrations of immune-related proteins (apelin, acid glycoprotein, CD14 antigen), neonatal developmental protein (probetacellulin), xenobiotic metabolising enzyme (flavin monooxygenase 3 (FMO3), GLYCAM1 and HSP90AA1 (chaperone) while the Jersey milk proteome presented higher concentrations of enzyme modulators (SERPINA1, RAC1, serine peptidase inhibitor) and hydrolases (LTF, LPL, CYM, PNLIPRP2). Pathway analysis in Kashmiri cattle revealed enrichment of key pathways involved in the regulation of mammary gland development like Wnt signalling pathway, EGF receptor signalling pathway and FGF signalling pathway while a pathway (T-cell activation pathway) associated with immune system regulation was significantly enriched in Jersey cattle. Most importantly, the high-abundant FMO3 enzyme with an observed 17-fold higher expression in Kashmiri cattle milk seems to be a characteristic feature of the breed. The presence of this (FMO3) bioactive peptide/enzyme in Kashmiri cattle could be economically advantageous for milk products from Kashmiri cattle. CONCLUSION: In conclusion, this is the first study to provide insights not only into the milk proteome differences between Kashmiri and Jersey cattle but also provides potential directions for application of specific milk proteins from Kashmiri cattle in special milk preparations like infant formula.

ABC of multifaceted dystrophin glycoprotein complex (DGC).

Dystrophin protein in association with several other cellular proteins and glycoproteins leads to the formation of a large multifaceted protein complex at the cell membrane referred to as dystrophin glycoprotein complex (DGC), that serves distinct functions in cell signaling and maintaining the membrane stability as well as integrity. In accordance with this, several findings suggest exquisite role of DGC in signaling pathways associated with cell development and/or maintenance of homeostasis. In the present review, we summarize the established facts about the various components of this complex with emphasis on recent insights into specific contribution of the DGC in cell signaling at the membrane. We have also discussed the recent advances made in exploring the molecular associations of DGC components within the cells and the functional implications of these interactions. Our review would help to comprehend the composition, role, and functioning of DGC and may lead to a deeper understanding of its role in several human diseases.

SSR based genetic diversity of pigmented and aromatic rice (Oryza sativa L.) genotypes of the western Himalayan region of India.

A set of 24 of SSR markers were used to estimate the genetic diversity in 16 rice genotypes found in Western Himalayas of Kashmir and Himachal Pradesh, India. The level of polymorphism among the genotypes of rice was evaluated from the number of alleles and PIC value for each of the 24 SSR loci. A total of 68 alleles were detected across the 16 genotypes through the use of these 24 SSR markers The number of alleles per locus generated varied from 2 (RM 338, RM 452, RM 171) to 6 (RM 585, RM 249, RM 481, RM 162). The PIC values varied from 0.36 (RM 1) to 0.86 (RM 249) with an average of 0.62 per locus. Based on information generated, the genotypes got separated in six different clusters. Cluster 1 comprised of 4 genotypes viz; Zag 1, Zag 13, Pusa sugandh 3, and Zag 14, separated from each other at a similarity value of 0.40. Cluster second comprised of 3 landraces viz; Zag 2. Zag 4 and Zag10 separated from each other at a similarity value of 0.45. Cluster third comprised of 3 genotypes viz; Grey rice, Mushk budji and Kamad separated from each other at a similarity value of 0.46. Cluster fourth had 2 landraces viz; Kawa kreed and Loual anzul, and was not sub clustered. Fifth cluster had 3 genotypes viz; Zag 12, Purple rice and Jhelum separated from each other at a similarity value of 0.28. Cluster 6 comprised of a single popular variety i.e. Shalimar rice 1 with independent lineage.

Keratin as an effective coating material for in vitro stem cell culture, induced differentiation and wound healing assays.

The utilization of stem cells in tissue engineering holds great promise as efficient tools for tissue regeneration and in treating numerous musculoskeletal diseases. However, several limiting factors, such as precise delivery and control of differentiation of these stem cells as well as mimicking the microenvironment required to modulate stem cell behaviour in-vivo, have given rise to an urgent need for the development of new biomaterials which could be tailored to enhance cell renewal and/or direct cell fates. Keratin-rich biological materials offer several advantages, such as biocompatibility, tailorable mechanical properties, huge bioavailability, non-toxicity, non-immunogenic, and intrinsic tissue repair and/or regeneration capabilities, which makes them highly valued. In the present work, we report the preparation of keratin-based bio-materials from goat hair waste and its effectiveness as a coating material for in vitro culture and induced differentiation of mesenchymal stem cells (MSC's) and primary goat fibroblast cells. Since no known keratinase enzymes are expressed as such in human and/or animal systems, these keratin biomaterials could be used to slow the rate of degradation and deliver keratin-loaded stem cell scaffolds to induce their directed differentiation in vivo. The generated keratin materials have been characterized for surface morphology, protein structures, size and other properties using SDS-PAGE, LC/MS-MS, SEM, FTIR etc. Also, in vitro cell culture assays such as cell adhesion, viability using MTT, live dead assays, differentiation assays and in vitro scratch/wound healing assays were performed. Our results provide important data supporting tissue engineering applications of these keratinous biomaterials by combining the unique biological characteristics of goat hair-derived keratin material with the regenerative power of stem cells and their combinatorial use in applications such as disease treatment and injury repair as well as their use in the preparation of wound healing products, such as dressings and bandages, for management of clinical care in animals.

Development of a multi-use decision support system for scientific management and breeding of sheep.

As the challenges of food insecurity and population explosion become more pressing, there is a dire need to revamp the existing breeding and animal management systems. This can be achieved by the introduction of technology for efficiency and the improvement of the genetic merit of animals. A fundamental requirement for animal breeding is the availability of accurate and reliable pedigreed data and tools facilitating sophisticated computations. Keeping this in view, Smart Sheep Breeder (SSB) was developed using the waterfall methodology and multiple programming languages. It is a multi-use online artificial intelligence (AI) based and internet of things (IoT) compatible decision support system (DSS). It is capable of automatic performance recording, farm data management, data mining, biometrical analysis, e-governance, and decision-making in sheep farms. A centralized database was also developed capable of ranking sheep across multiple farms based on genetic merit and effective dissemination of germplasm. The system in India is available as a web-based tool and android application which facilitates performance recording and generates customized reports on various aspects of sheep production. SSB uses artificial intelligence and biometrical genetic algorithms to calculate breeding values, and inbreeding coefficients, construct selection indices and generate pedigree, and history sheets as well as more than 40 types of custom-tailored animal and farm reports and graphs. The algorithms used were validated using on farms using farm data and also by comparison with established methods and software. Smart Sheep Breeder could thus prove to be indispensable for the present farming systems which could be used by sheep farm managers and breeders across India.

Comparison of artificial intelligence algorithms and their ranking for the prediction of genetic merit in sheep.

As the amount of data on farms grows, it is important to evaluate the potential of artificial intelligence for making farming predictions. Considering all this, this study was undertaken to evaluate various machine learning (ML) algorithms using 52-year data for sheep. Data preparation was done before analysis. Breeding values were estimated using Best Linear Unbiased Prediction. 12 ML algorithms were evaluated for their ability to predict the breeding values. The variance inflation factor for all features selected through principal component analysis (PCA) was 1. The correlation coefficients between true and predicted values for artificial neural networks, Bayesian ridge regression, classification and regression trees, gradient boosting algorithm, K nearest neighbours, multivariate adaptive regression splines (MARS) algorithm, polynomial regression, principal component regression (PCR), random forests, support vector machines, XGBoost algorithm were 0.852, 0.742, 0.869, 0.915, 0.781, 0.746, 0.742, 0.746, 0.917, 0.777, 0.915 respectively for breeding value prediction. Random forests had the highest correlation coefficients. Among the prediction equations generated using OLS, the highest coefficient of determination was 0.569. A total of 12 machine learning models were developed from the prediction of breeding values in sheep in the present study. It may be said that machine learning techniques can perform predictions with reasonable accuracies and can thus be viable alternatives to conventional strategies for breeding value prediction.

Genome wide expression analysis of circular RNAs in mammary epithelial cells of cattle revealed difference in milk synthesis.

Milk is an excellent source of nutrients for humans. Therefore, in order to enhance the quality and production of milk in cattle, it is interesting to examine the underlying mechanisms. A number of new investigations and research have found that, circRNA; a specific class of non-coding RNAs, is linked with the development of mammary gland and lactation. In the present study, genome wide identification and expression of the circRNAs in mammary epithelial cells of two distinct cattle breeds viz Jersey and Kashmiri at peak lactation was conducted. We reported 1554 and 1286 circRNA in Jersey and Kashmiri cattle, respectively, with 21 circRNAs being differentially expressed in the two breeds. The developmental genes of the established differentially expressed circRNAs were found to be largely enriched in antioxidant activity, progesterone, estradiol, lipid, growth hormone, and drug response. Certain pathways like MAPK, IP3K and immune response pathways were found significantly enriched in KEGG analysis. These results add to our understanding of the controlling mechanisms connected with the lactation process, as well as the function of circRNAs in bovine milk synthesis. Additionally, the comparative analysis of differentially expressed circRNAs showed significant conservation across different species.

Identification of potential key genes and pathways associated with the Pashmina fiber initiation using RNA-Seq and integrated bioinformatics analysis.

Pashmina goat (Capra hircus) is an economically important livestock species, which habitats the cold arid desert of the Ladakh region (India), and produces a princely animal fiber called Pashmina. The Pashmina goat has a double coat fleece as an adaptation to the very harsh cold winters the outer long coarse hair (guard hair) produced from primary hair follicles and the inner fine Pashmina fiber produced from secondary hair follicles. Pashmina fiber undergoes a circannual and synchronized growth cycle. In the present study, we analyzed transcriptome profiles from 10 different Pashmina goats during anagen and telogen to delineate genes and signaling pathways regulating active (anagen) and regressive (telogen) phases of the follicle growth. During anagen, 150 genes were expressed at significantly higher levels with log (FC) > 2 and padj < 0.05. The RNA seq results were subjected to qRT-PCR validation. Among the nine genes selected, the expression of HAS1, TRIB2, P2RX1. PRG4, CNR2, and MMP25 were significantly higher (p < 0.05) in the anagen phase, whereas MC4R, GIPC2, and CDO1 were significantly expressed (p < 0.05) in the telogen phase which supports and validates the gene expression pattern from the RNA-sequencing. Differentially expressed genes revealed that Pashmina fiber initiation is largely controlled by signaling pathways like Wnt, NF-Kappa, JAK-STAT, Hippo, MAPK, Calcium, and PI3K-Akt. Expression of genes from the Integrin family, Cell adhesion molecules, and ECM-receptors were observed to be at much higher levels during anagen. We identified key genes (IL36RN, IGF2, ITGAV, ITGA5, ITCCR7, CXCL5, C3, CCL19, and CXCR3) and a collagen cluster which might be tightly correlated with anagen-induction. The regulatory network suggests the potential role of RUNX3, NR2F1/2, and GATA family transcription factors in anagen-initiation and maintaining fiber quality in Pashmina goats.

Changthangi Pashmina Goat Genome: Sequencing, Assembly, and Annotation.

Pashmina goats produce the world's finest and the most costly animal fiber (Pashmina) with an average fineness of 11-13 microns and have more evolved mechanisms than any known goat breed around the globe. Despite the repute of Pashmina goat for producing the finest and most sought-after animal fiber, meager information is available in the public domain about Pashmina genomics and transcriptomics. Here we present a 2.94 GB genome sequence from a male Changthangi white Pashmina goat. We generated 294.8 GB (>100X coverage) of the whole-genome sequence using the Illumina HiSeq 2500 sequencer. All cleaned reads were mapped to the goat reference genome (2,922,813,246 bp) which covers 97.84% of the genome. The Unaligned reads were used for de novo assembly resulting in a total of 882 MB non-reference contigs. De novo assembly analysis presented in this study provides important insight into the adaptation of Pashmina goats to cold stress and helps enhance our understanding of this complex phenomenon. A comparison of the Pashmina goat genome with a wild goat genome revealed a total of 2,823 high impact single nucleotide variations and small insertions and deletions, which may be associated with the evolution of Pashmina goats. The Pashmina goat genome sequence provided in this study may improve our understanding of complex traits found in Pashmina goats, such as annual fiber cycling, defense mechanism against hypoxic, survival secret in extremely cold conditions, and adaptation to a sparse diet. In addition, the genes identified from de novo assembly could be utilized in differentiating Pashmina fiber from other fibers to avoid falsification at marketing practices.

Comparative transcriptome analysis of mammary epithelial cells at different stages of lactation reveals wide differences in gene expression and pathways regulating milk synthesis between Jersey and Kashmiri cattle.

Jersey and Kashmiri cattle are important dairy breeds that contribute significantly to the total milk production of the Indian northern state of Jammu and Kashmir. The Kashmiri cattle germplasm has been extensively diluted through crossbreeding with Jersey cattle with the goal of enhancing its milk production ability. However, crossbred animals are prone to diseases resulting to unsustainable milk production. This study aimed to provide a comprehensive transcriptome profile of mammary gland epithelial cells at different stages of lactation and to find key differences in genes and pathways regulating milk traits between Jersey and Kashmiri cattle. Mammary epithelial cells (MEC) isolated from milk obtained from six lactating cows (three Jersey and three Kashmiri cattle) on day 15 (D15), D90 and D250 in milk, representing early, mid and late lactation, respectively were used. RNA isolated from MEC was subjected to next-generation RNA sequencing and bioinformatics processing. Casein and whey protein genes were found to be highly expressed throughout the lactation stages in both breeds. Largest differences in differentially expressed genes (DEG) were between D15 vs D90 (1,805 genes) in Kashmiri cattle and, D15 vs D250 (3,392 genes) in Jersey cattle. A total of 1,103, 1,356 and 1,397 genes were differentially expressed between Kashmiri and Jersey cattle on D15, D90 and D250, respectively. Antioxidant genes like RPLPO and RPS28 were highly expressed in Kashmiri cattle. Differentially expressed genes in both Kashmiri and Jersey were enriched for multicellular organismal process, receptor activity, catalytic activity, signal transducer activity, macromolecular complex and developmental process gene ontology terms. Whereas, biological regulation, endopeptidase activity and response to stimulus were enriched in Kashmiri cattle and, reproduction and immune system process were enriched in Jersey cattle. Most of the pathways responsible for regulation of milk production like JAK-STAT, p38 MAPK pathway, PI3 kinase pathway were enriched by DEG in Jersey cattle only. Although Kashmiri has poor milk production efficiency, the present study suggests possible physicochemical and antioxidant properties of Kashmiri cattle milk that needs to be further explored.

Comparative transcriptome analysis reveals the genetic basis of coat color variation in Pashmina goat.

The genetics of coat color variation remains a classic area. Earlier studies have focused on a limited number of genes involved in color determination; however, the complete set of trait determinants are still not well known. In this study, we used high-throughput sequencing technology to identify and characterize intricate interactions between genes that cause complex coat color variation in Changthangi Pashmina goats, producer of finest and costly commercial animal fiber. We systematically identified differentially expressed mRNAs and lncRNAs from black, brown and white Pashmina goat skin samples by using RNA-sequencing technique. A pairwise comparison of black, white and brown skin samples yielded 2479 significantly dysregulated genes (2422 mRNA and 57 lncRNAs). Differentially expressed genes were enriched in melanin biosynthesis, melanocyte differentiation, developmental pigmentation, melanosome transport activities GO terms. Our analysis suggested the potential role of lncRNAs on color coding mRNAs in cis and trans configuration. We have also developed online data repository as a component of the study to provide a central location for data access, visualization and interpretation accessible through http://pcd.skuastk.org/ .

TM-Aligner: Multiple sequence alignment tool for transmembrane proteins with reduced time and improved accuracy.

Membrane proteins plays significant role in living cells. Transmembrane proteins are estimated to constitute approximately 30% of proteins at genomic scale. It has been a difficult task to develop specific alignment tools for transmembrane proteins due to limited number of experimentally validated protein structures. Alignment tools based on homology modeling provide fairly good result by recapitulating 70-80% residues in reference alignment provided all input sequences should have known template structures. However, homology modeling tools took substantial amount of time, thus aligning large numbers of sequences becomes computationally demanding. Here we present TM-Aligner, a new tool for transmembrane protein sequence alignment. TM-Aligner is based on Wu-Manber and dynamic string matching algorithm which has significantly improved its accuracy and speed of multiple sequence alignment. We compared TM-Aligner with prevailing other popular tools and performed benchmarking using three separate reference sets, BaliBASE3.0 reference set7 of alpha-helical transmembrane proteins, structure based alignment of transmembrane proteins from Pfam database and structure alignment from GPCRDB. Benchmarking against reference datasets indicated that TM-Aligner is more advanced method having least turnaround time with significant improvements over the most accurate methods such as PROMALS, MAFFT, TM-Coffee, Kalign, ClustalW, Muscle and PRALINE. TM-Aligner is freely available through http://lms.snu.edu.in/TM-Aligner/ .

Molecular characterization of RNA binding motif protein 3 (RBM3) gene from Pashmina goat.

Pashmina goat inhabits the high altitude cold arid desert of Ladakh, India. This goat is known for its finest and costliest under fiber. Though the under fiber may be a part of its complex thermoregulation mechanism, the genetics of its adaptability under cold conditions is not known. As an attempt to understand its adaptive genetics, and the role of RNA-binding proteins at the cellular response, this study was conducted to characterize the RBM3 gene in Pashmina goat and its expression during hypothermia. The ORF of Pashmina RBM3 gene was 273 bp. Phylogenetic analysis revealed that Pashmina RBM3 is closely related to Bos taurus RBM3. Pashmina RBM3 was characterized by comparative modeling studies. The final 3-D model contained two α-helices and four ß-sheets. qRT-PCR data showed that Pashmina RBM3 gene expression was significantly higher (P < 0.05) at moderate (30 °C) hypothermic stress conditions as compared with deep (15 °C) hypothermia.