Tissue-specific temporal exome capture revealed muscle-specific genes and SNPs in Indian buffalo (Bubalus bubalis)

Whole genome sequencing of buffalo is yet to be completed,and in the near future it may not be possible to identify an exome(coding region of genome) through bioinformatics for designing probes to capture it.In the present study,we employed in solution hybridization to sequence tissue specific temporal exomes(TST exome) in buffalo.We utilized cDNA prepared from buffalo muscle tissue as a probe to capture TST exomes from the buffalo genome.This resulted in a prominent reduction of repeat sequences(up to 40%) and an enrichment of coding sequences(up to 60%).Enriched targets were sequenced on a 454 pyro-sequencing platform,generating 101,244 reads containing 24,127,779 high quality bases.The data revealed 40,100 variations,of which 403 were indels and 39,218 SNPs containing 195 nonsynonymous candidate SNPs in protein-coding regions.The study has indicated that 80% of the total genes identified from capture data were expressed in muscle tissue.The present study is the first of its kind to sequence TST exomes captured by use of cDNA molecules for SNPs found in the coding region without any prior sequence information of targeted molecules.     

Milk microbiome signatures of subclinical mastitis-affected cattle analysed by shotgun sequencing

Aims: Metagenomic analysis of milk samples collected from Kankrej, Gir (Bos indicus) and crossbred (Bos taurus × B. indicus) cattle harbouring subclinical mastitis was carried out by next‐generation sequencing 454 GS‐FLX technology to elucidate the microbial community structure of cattle milk. Methods and Results: Milk samples from Kankrej, Gir and crossbred cattle were subjected to metagenomic profiling by pyrosequencing. The Metagenomic analysis produced 63·07, 11·09 and 7·87 million base pairs (Mb) of sequence data, assembled in 264 798, 56 114 and 36 762 sequences with an average read length of 238, 197 and 214 nucleotides in Kankrej, Gir and crossbred cattle, respectively. Phylogenetic and metabolic profiles by the web‐based tool MG‐RAST revealed that the members of Enterobacteriales were predominant in mastitic milk followed by Pseudomonadales, Bacillales and Lactobacillales. Around 56 different species with varying abundance were detected in the subclinically infected milk. Escherichia coli was found to be the most predominant species in Kankrej and Gir cattle followed by Pseudomonas aeruginosa, Pseudomonas mendocina, Shigella flexneri and Bacillus cereus. In crossbred cattle, Staphylococcus aureus followed by Klebsiella pneumoniae, Staphylococcus epidermidis and E. coli were detected in descending order. Metabolic profiling indicated fluoroquinolones, methicillin, copper, cobalt–zinc–cadmium as the groups of antibiotics and toxic compounds to which the organisms showed resistance. Sequences indicating potential of organisms exhibiting multidrug resistance against antibiotics and resistance to toxic compounds were also present. Interestingly, presence of bacteriophages against Staph. aureus, E. coli, Enterobacter and Yersinia species was also observed. Conclusions: The analysis identified potential infectious organisms in mastitis, resistance of organisms to antibiotics and chemical compounds and the natural resistance potential of dairy cows. Significance and Impact of the Study: The findings of this study may help in formulating strategies for the prevention and treatment of mastitis in dairy animals and consequently in reducing economic losses incurred because of it.     

Metagenomic microbial community profiling of Unnai hot spring by Ion-Torrent based shotgun sequencing

This is the first report on depicting the pioneering microbiota of Unnai hot spring using shotgun metagenome sequencing approach. Community analysis encompassed a total of 688,059 sequences with the total size 125.31 Mbp and 46% G + C content. Sequencing metagenome reported about 992 species belonged to 40 different phyla dominated by Firmicutes (97.49%), Proteobacteria (1.36%), and Actinobacteria (0.31%). In functional analysis, Non-Supervised Orthologous Groups (NOG) annotation revealed the predominance of poorly characterized reads (82.79%). Moreover, the subsystem classification displayed 19% genes assigned to carbohydrates metabolism, 12% genes allocated to clustering-based subsystems, 10% genes belonged to amino acids and its derivatives. The result suggests the huge bacterial diversity which will be useful for further characterizing the economically important bacteria for biotechnological applications.     

Identification of putative SNPs in progressive retinal atrophy affected Canis lupus familiaris using exome sequencing

Progressive retinal atrophy (PRA) is one of the major causes of retinal photoreceptor cell degeneration in canines. The inheritance pattern of PRA is autosomal recessive and genetically heterogeneous. Here, using targeted sequencing technology, we have performed exome sequencing of 10 PRA-affected (Spitz = 7, Cocker Spaniel = 1, Lhasa Aphso = 1 and Spitz-Labrador cross breed = 1) and 6 normal (Spitz = 5, Cocker Spaniel = 1) dogs. The high-throughput sequencing using 454-Roche Titanium sequencer generated about 2.16 Giga bases of raw data. Initially, we have successfully identified 25,619 single nucleotide polymorphisms (SNPs) that passed the stringent SNP calling parameters. Further, we performed association study on the cohort, and the highly significant (0.001) associations were short-listed and investigated in-depth. Out of the 171 significant SNPs, 113 were previously unreported. Interestingly, six among them were non-synonymous coding (NSC) SNPs, which includes CPPED1 A>G (p.M307V), PITRM1 T>G (p.S715A), APP G>A (p.T266M), RNF213 A>G (p.V1482A), C>A (p.V1456L), and SLC46A3 G>A (p.R168Q). On the other hand, 35 out of 113 unreported SNPs were falling in regulatory regions such as 3′-UTR, 5′-UTR, etc. In-depth bioinformatics analysis revealed that majority of NSC SNPs have damaging effect and alter protein stability. This study highlighted the genetic markers associated with PRA, which will help to develop genetic assay-based screening in effective breeding.