Molecular Characterization of a New Nosema bombycis Strain Detected in Iranian Silkworm Farms.

PURPOSE: Pebrine as the most dangerous disease of silkworm mostly caused by Nosema species has caused huge economic losses. There is no information on the species and the genomic sequences of the pebrine-causing microsporidia in Iran. METHODS: In the present research, we tried to determine the sequences of two regions of rDNA using molecular methods. First, infected larvae and mother moths were collected from several farms in the north of Iran for identification and molecular characterization of microsporidian isolates. After extracting the spores and genomic DNA from the collected samples, two fragments of internal transcribed spacer (ITS) rDNA and small subunit (SSU) rDNA were amplified and sequenced, and registered in NCBI database and then, the phylogenetic tree was drawn. RESULTS: Results showed the obtained sequences (ITS rDNA: Accession No. MZ322002 and SSU rDNA: Accession No. MZ314703) represent a new strain of Nosema bombycis, which differs from the sequences deposited in the NCBI. CONCLUSION: The new N. bombycis strain identified in our study will help in control and management of the pebrine disease by specific detection of the infectious agent.

Exploring novel single nucleotide polymorphisms and haplotypes of the diacylglycerol O-acyltransferase 1 (DGAT1) gene and their effects on protein structure in Iranian buffalo.

BACKGROUND: Diacylglycerol O-acyltransferase 1 (DGAT1) plays a key role in the synthesis of triglycerides. Recent studies have shown that a transition mutation resulting in substitutions of guanine by adenine in the DGAT1 gene in cattle has considerable effects on milk yield and composition. Currently, there is no systematic research reporting on the utilization of this gene segment in Iranian buffalo (Bubalus bubalis). OBJECTIVE: In this study, the genetic differentiation of three indigenous Iranian buffalo populations was investigated in the region spanning exon 3 to exon 17 of the DGAT1 gene. METHODS: A total of 200 buffaloes were genotyped, all the samples were sequenced directly in both directions with forward and reverse sequencing primers. RESULTS: Sequence analysis showed novel SNPs compared to the reference GenBank sequence (DQ886485) at nucleotide positions g.6097A>G, g.7036C>T, g.7338G>A, g.7710C>T, g.8087C>T, g.8259G>A, g.8275G>A, g.8367C>T, and g.8426C>T. No polymorphisms were found within exon 8. Therefore, the K232A position was thought to be a conserved and fixed region for high milk fat content (K allele) in Bos indicus and all buffalo breeds. Comparison with Indian buffalo revealed three exonic SNPs, one of which was nonsynonymous. A unique 22 bp insertion was observed in intron 10 of DGAT1. Linkage disequilibrium analysis allowed the identification of nine haplotypes among the sampled animals. To our knowledge, this is the first report of sequencing analysis of the DGAT1 gene in Iranian buffalo. CONCLUSION: Our results suggest that genetic diversity exists and could be useful in examining the association between the DGAT1 gene and milk production traits in buffalo.

PSSP: Protein splice site prediction algorithm using Bayesian approach.

This study aimed to introduce an algorithm and identify intein motif and blocks involved in protein splicing, and explore the underlying methods in the development of detection of protein motifs. Inteins are mobile protein splicing elements capable of self-splicing post-translationally. They exist in viruses and bacteriophage, notwithstanding this broad phylogenetic distribution, all inteins apportion common structural features. A method was developed to predict intein in a raw sequence, using a ranking and scoring scheme based on amino acid θ value tables. This method aided in the identification and assessment of patterns characterizing the intein sequences. New intein conserved properties are revealed and the known ones are described and localized. We have computed the θ value of each amino acid at block A positions +1 to +13, block B positions l+13 to l+26 and block G positions -7 to +1 for the three categories. The consensus amino acids thus found are listed at the end of each row. We gave statistics for the distance between the blocks, block A to B, block B to F, and block F to G with the average being 66.1, 294, and 10.2 amino acids, respectively. The actual blocks A, B, and G of the one intein found in vacuolar membrane ATPase subunit, a precursor protein, are ranked 1. The results indicate all of the block sequences that are found in nine proteins are ranked at top of the list. The intein sequence is used to search the databases for intein-like proteins. Understanding the functional, structural, and dynamical aspects of inteins is important for intein engineering and the betterment of intein database.

Dynamic modeling of folliculogenesis signaling pathways in the presence of miRNAs expression.

BACKGROUND: TEK signaling plays a very important role in folliculogenesis. It activates Ras/ERK/MYC, PI3K/AKT/mTORC1 and ovarian steroidogenesis activation pathways. These are the main pathways for cell growth, differentiation, migration, adhesion, proliferation, survival and protein synthesis. RESULTS: TEK signaling on each of the two important pathways where levels of pERK, pMYC, pAkt, pMCL1 and pEIF4EBP1 are increased in dominant follicles and pMYC is decreased in dominant follicles. Over activation of ERK and MYC which are the main cell growth and proliferation and over activation of Akt, MCl1, mTORC1 and EIF4EBP1 which are the main cell survival and protein synthesis factors act as promoting factors for folliculogenesis. In case of over expression of hsa-miR-30d-3p and hsa-miR-451a, MYC activity level is considerably increased in subordinate follicles. Our simulation results show that in the presence of has-miR-548v and bta-miR-22-3p, downstream factors of pathways are inhibited. CONCLUSIONS: Our work offers insight into the design of natural biological procedures and makes predictions that can guide further experimental studies on folliculogenesis pathways. Moreover, it defines a simple signal processing unit that may be useful for engineering synthetic biology and genes circuits to carry out cell-based computation.

miRNA-mRNA network involved in folliculogenesis interactome: systems biology approach.

At later phases of folliculogenesis, the mammalian ovarian follicle contains layers of granulosa cells surrounding an antral cavity. To better understand the molecular basis of follicular growth and granulosa cell maturation, we study transcriptome profiling of granulosa cells from small (<5 mm) and large (>10 mm) bovine follicles using simultaneous method of Affymetrix microarrays (24,128 probe sets) and RNA-Seq data sets. This study proposes a computational method to discover the functional miRNA-mRNA regulatory modules, that is, groups of miRNAs and their target mRNAs that are believed to take part cooperatively in post-transcriptional gene regulation under specific conditions. The reconstructed network was named Integrated miRNA-mRNA Bipartite Network. 277 genes and 6 key modules were disclosed through clustering for mRNA master list. The 66 genes are among the genes that belong to at least two modules. All these genes, being involved in at least one of the phenomena, namely cell survival, proliferation, metastasis and apoptosis, have an overexpression pattern (P < 0.01). For miRNA master list, a total of 172 sequences were differentially expressed (P < 0.01) between dominant (large) and each of subordinate (small) follicles. Within the follicle, these miRNAs were predominantly expressed in mural granulosa cells. Finally, predicted and validated targets of these miRNAs enriched in dominant (large) follicles were identified, which are mapped to signaling pathways involved in follicular cell proliferation, steroidogenesis, PI3K/AKT/mTOR and Ras/Raf/MEK/ERK. The identification of miRNAs and their target mRNAs and the construction of their regulatory networks may give new insights into biological procedures.

Random Regression Models Using Legendre Polynomials to Estimate Genetic Parameters for Test-day Milk Protein Yields in Iranian Holstein Dairy Cattle.

The objective of this study was to estimate the genetic parameters of milk protein yields in Iranian Holstein dairy cattle. A total of 1,112,082 test-day milk protein yield records of 167,269 first lactation Holstein cows, calved from 1990 to 2010, were analyzed. Estimates of the variance components, heritability, and genetic correlations for milk protein yields were obtained using a random regression test-day model. Milking times, herd, age of recording, year, and month of recording were included as fixed effects in the model. Additive genetic and permanent environmental random effects for the lactation curve were taken into account by applying orthogonal Legendre polynomials of the fourth order in the model. The lowest and highest additive genetic variances were estimated at the beginning and end of lactation, respectively. Permanent environmental variance was higher at both extremes. Residual variance was lowest at the middle of the lactation and contrarily, heritability increased during this period. Maximum heritability was found during the 12th lactation stage (0.213±0.007). Genetic, permanent, and phenotypic correlations among test-days decreased as the interval between consecutive test-days increased. A relatively large data set was used in this study; therefore, the estimated (co)variance components for random regression coefficients could be used for national genetic evaluation of dairy cattle in Iran.