Effect of phytase and xylanase enzymes on growth performance and Mucin2 gene expression in broiler chickens.

BACKGROUND: Development of exogenous enzymes is one of the most important discoveries in animal nutrition. The supplementation of exogenous enzymes in broiler diets allows for supplying nutrient deficiencies and to decrease endogenous losses. OBJECTIVES: The effects of phytase (Hostazym and Phyzyme) and xylanase (Ronozyme) enzymes were investigated on growth performance and Mucin2 gene expression in broilers. METHODS: A completely randomized design was applied, including 7 treatments, 4 replicates and 25 birds per replicates. A total of 700 male Ross (308) broiler chickens were fed with similar diets supplemented by Hostazym and Phyzyme (500 and 1000 FTU/kg) and Ronozyme (100 and 200 EXU/kg). Weight gain (WG), feed intake (FI) and feed conversion ratio (FCR) were determined for three phases and entire rearing period. On 42 days of age, four birds per replicate were slaughtered. Total RNA was extracted from jejunum samples, and Mucin2 gene expression was measured by real-time PCR. RESULTS: Phytase and xylanase enzymes had a significant effect (p < 0.05) on traits (WG and FCR) in grower and finisher phases and whole rearing period, but FI was not affected by enzymes (p > 0.05). Carcass (74.13 g) and breast (27.76 g) weights by Hostazym (1000 FTU/kg) were higher than other treatments (p < 0.05). Weight of liver, bursa and spleen were significantly influenced by enzymes (p < 0.05). Likewise, bursa and spleen weights in Hostazym (1000 FTU/kg feed) and Ronozyme (200 EXU/kg feed) were significantly higher than other treatments (p < 0.05). Mucin2 gene expression was affected by enzymes in whole treatments. The lowest amount of Mucin2 gene expression belonged to Ronozyme (200 and 100 EXU/kg), and the highest was belonging to Hostazym (1000 FTU/kg). CONCLUSIONS: Phytase enzymes have higher effect on broiler performance and Mucin2 gene expression compared to xylanase. High doses of Hostazym (1000 FTU/kg feed) could be supplemented in broiler chicken diets to improve optimum growth and feed efficiency.

Mitochondrial DNA D-loop hyper-variable region 1 variability in Kurdish horse breed.

BACKGROUND: Kurdish horse is one of the most valuable horse genetic resources in the Middle East. OBJECTIVES: To assess the genetic diversity of Kurdish horses, Mitochondrial DNA D-loop hyper-variable region1 (HVR1) was sequenced in 29 non-related Kurdish horses which were sampled from diverse geographic regions of Iran. METHODS: Total DNA was extracted from the collected blood samples by modified salting out method. The HVR1 was amplified by PCR and then sequenced using ABI PRISM BigDyeTM Terminator Cycle Sequencing Ready Reaction Kit. Consequently, the sequences were trimmed to 294 bp using BIOEDIT to become comparable with other reported HVR1 sequences in GeneBank. Sequence alignment was performed using CLUSTALW package. Haplotype and nucleotide diversity were estimated using DNASP5.10 and phylogenetic tree was constructed by neighbour joining method. RESULTS: Fourteen different haplotypes and 22 polymorphic sites were detected. Haplotype diversity, nucleotide diversity and Tajima D values were 0.901 ± 0.001, 0.01153 ± 0.0020 and -1.378, respectively. Kurdish horse showed a high haplotype and low nucleotide diversity. The compositional frequency of consensus sequences for base A was the highest (29.93%) compared to other three nucleotides (C = 28.91%, T = 26.53% and G = 14.63%). As expected, all of the detected Kurdish horse haplotypes belonged to haplogroup K (i.e., Kurdish horses). CONCLUSIONS: According to the phylogenetic analysis, Kurdish horses were genetically more closely related to Tibetan, Chinese, Bulgarian and Iranian native horse breeds, compared to other Asian horse breeds, but some traces of European horse breeds were detected in their maternal lines.

Meta-analysis of genetic parameters for growth traits in meat, wool and dual-purpose sheep breeds in the world using a random-effects model.

BACKGROUND: There is large variation in genetic parameters in literature for growth traits in sheep. Reliable estimation of genetic parameters is required for developing breeding programmes. OBJECTIVES: The aim of this study was to aggregate results of different studies by meta-analysis to improve reliability of estimated parameters. METHODS: In the current study, 221 papers that have been published between 1995 and 2021 were reviewed. Using a random-effects model in the Comprehensive Meta-Analysis software, direct and maternal heritabilities, as well as, genetic and phenotypic correlations between growth traits were estimated in meat (M), wool (W) and dual-purpose (D) sheep breeds. The growth traits in this study were birth weight, 3-month weight, 6-month weight, 9-month weight and yearling weight. RESULTS: The combined direct heritability was the lowest for birth weight (0.190 ± 0.004, 0.198 ± 0.003 and 0.196 ± 0.004 for M, W and D breeds, respectively) and the highest for yearling weight (0.264 ± 0.010, 0.304 ± 0.005 and 0.285 ± 0.020 for M, W and D breeds, respectively). The maternal heritability was the lowest for yearling weight (0.085 ± 0.003, 0.055 ± 0.002 and 0.052 ± 0.005 for M, W and D breeds, respectively) and the highest for 6-month weight (0.240 ± 0.088, 0.164 ± 0.001 and 0.162 ± 0.006 for M, W and D breeds, respectively). The phenotypic and genetic correlations were lower between the weights measured at more distant intervals. The lowest genetic correlation was observed between birth weight and yearling weight (0.290 ± 0.051 for W breeds). CONCLUSIONS: The small standard errors could indicate that the aggregation of results from different studies improved the reliability of estimated parameters and reduced range of 95% confidence intervals. Hence, the results could be used with greater level of confidence in sheep breeding programmes.

Allele Specific Expression (ASE) analysis between Bos Taurus and Bos Indicus cows using RNA-Seq data at SNP level and gene level.

In the current study, allele specific expression analysis was performed in two subspecies cows (Bos taurus and Bos indicus) at SNP and gene levels. RNA-Seq data of 21,078,477 and 20940063 paired end reads from pooling of whole blood samples (Leukocyte) from 40 US Holstein (Bos Taurus) and 45 Cholistani cows (Bos indicus) obtained from SRA database in NCBI. Quality control and trimming of row RNA-Seq data were processed by FASTQC and Trimmomatic softwares. The transcriptome was assembled by TopHat2 software in two cow's population by aligning and mapping the RNA-Seq reads on bovine reference genome. The SNPs were discovered by Samtools software and ASE analysis was performed by Chi-square test. Results showed that 50183 and 137954 SNPs were discovered on the assembled transcriptome of Holstein and Cholistani cow samples, respectively, and 15308 SNPs were common in both breeds. 10158 SNPs from 50183 (20%) in Holstein and 31523 SNPs from 137954 (23%) in Cholistani cows were identified as ASE-SNPs. Reference allele and alternative allele count in Holstein and Cholistani cows were 3041 and 7155, respectively. Among 131 discovered SNPs in 41 genes with different expression in Holstein and Cholistani cows, 31 ASE-SNPs (5 in Holstein; 26 in Cholistani cows) were discovered.