Hossein Mohammadi; Amir Hossein Khaltabadi Farahani; Mohammad Hossein Moradi; mohammad shamsollahi
Volume 25, Issue 2 , July 2023, , Pages 133-143
Abstract
Introduction: The selection of animals by humans left detectable signatures on the genome of modern goat. The identification of these signals can help us to improve the genetic characteristics of economically important traits in goat. Over the last decade, interest in detection of genes or genomic regions ...
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Introduction: The selection of animals by humans left detectable signatures on the genome of modern goat. The identification of these signals can help us to improve the genetic characteristics of economically important traits in goat. Over the last decade, interest in detection of genes or genomic regions that are targeted by selection has been growing. Identifying signatures of selection can provide valuable insights about the genes or genomic regions that are or have been under selection pressure, which in turn leads to a better understanding of genotype-phenotype relationships. A run of homozygosity (ROH) is a consecutive tract of homozygous genotypes in an individual that indicates it has inherited the same ancestral haplotype from both parents. Run of homozygosity one of the most methods were used to detecting the genomic inbreeding. The locations of ROHs which are under positive selection, or laboring favorable allele in population, tend to be fixed in the genome and formation of ROH Island during long times. Genomic regions enriched with ROH may be indicative of selection sweeps and are known as ROH islands. As detecting the ROH Islands, the genomic regions contain economic traits could be detectable.
Materials and Methods: In this research, the amount of genomic inbreeding and the effective size of the population were investigated using the information obtained from 879 goats of different breeds including Beetal, Daira Deen Panah, Nachi, Barbari, Teddi, Pahari, and Pothwari. In order to determine the genotype of the samples, Illumina caprine Bead Chip 50K were used. The genomic information of goat breeds was extracted from the figshare database. Quality control was conducted using the Plink software. The markers or individuals were excluded from the further study based on the following criteria: unknown chromosomal or physical location, call rate <0.95, missing genotype frequency >0.05, minor allele frequency (MAF) < 0.05, and a P-value for Hardy–Weinberg equilibrium test less than 10-3. After quality control, 36,861 SNPs from Goat SNP chip 50K on 827 goats were remained for the future analysis. Inbreeding coefficient was calculated using four methods including, genomic relationship matrix (FGRM), excess of homozygosity (FHOM), correlation between uniting gametes (FUNI) using the GCTA 1.0 software and run of homozygosity (FROH) using the PLINK 1.9 software. The effective population size (Ne) was calculated from linkage disequilibrium data with SNeP software (version 1.1). GeneCards (http://www.genecards.org) and UniProtKB (http://www.uniprot.org) databases were also used to interpret the function of the obtained genes.
Results and Discussion: The lowest and highest inbreeding coefficient calculated by three methods (FGRM, FHOM, and FUNI) were related to Beetal and Barbari breed, respectively. The highest (0.159) and lowest (0.028) amount of FROH was estimated in the Barbari and Pothwari breeds, respectively. The average length of ROH ranged from 70.2 to 391.4 Mb, and the average number of ROH fragments varied between 8.19 and 48.65. Also, the highest and lowest number of ROH were observed on chromosome 2 and 29, respectively. The size of Ne in in the current generations (fifth generation) of the studied breeds was ranged from 35 to 365. The highest Ne was estimated in the Beetal breed (365 heads) and the lowest in the Barbari breed (35 heads). The average inbreeding coefficient in Beetal, Teddi, Pahari, Nachi, Barbari, Daira Deen Panah and Pothwari breeds was obtained 0.035, 0.081, 0.031, 0.052, 0.15, 0.11 and 0.02, respectively. In addition, the Ne of most of the studied populations has been decreased. The results of this study revealed that, the selection processes in different goat breeds for economic traits during several years, has led to the formation of many ROH islands in goat genome, therefore scanning these regions at the genome level can be an alternative strategy to identify genes and associated loci with economic traits.
Conclusions: our findings contribute to the understanding of genetic diversity and population demography, and help design and implement breeding and conservation strategies for study goat breeds. Therefore, it is necessary to economize production and planning a suitable mating scheme to control inbreeding and genetically conserve the remaining pure animals of these breeds.
Siavash Manzoori; Amir Hossein Khaltabadi Farahani; Mohammad Hossein Moradi; Mehdi Kazemi bon-Chenari
Volume 24, Issue 3 , October 2022, , Pages 259-270
Abstract
The aim of this research was to compare the efficiency and performance of the advanced artificial neural network method with the principal component analysis method in discriminating different horse breeds. In this study, two methods of perceptron neural network (Olden) and the principal component analysis ...
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The aim of this research was to compare the efficiency and performance of the advanced artificial neural network method with the principal component analysis method in discriminating different horse breeds. In this study, two methods of perceptron neural network (Olden) and the principal component analysis (PCA), were used to identify a subset of SNP markers with the highest breed discrimination potential and to investigate how to assign animals to their breed groups. The results showed that the network method (Olden), is able to separate all the 37 horse breeds with a small subset of SNP markers (8,000 markers) with a same capability to all genomic markers (98% accuracy). The PCA selection method was only able to identify and separate breeds with diverse geographical originations. According to the obtained results, the PCA method is not error-free and depends upon changes and modifications to run on genomic data. The results of this study provide practical approaches in the design of economic arrays for discriminating the different horse breeds.
Hossein Mohammadi; Amir Hossein khalababdi farahani; Mohammad Hossein Moradi
Volume 24, Issue 2 , July 2022, , Pages 117-126
Abstract
The aim of the present study was to evaluate the genetic architecture, genomic regions and candidate genes associated with body weight gain, feed intake and feed conversion ratio in Japanese quails. For detection the informative genomic windows, genotyping data on 920 quails was used in a single-step ...
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The aim of the present study was to evaluate the genetic architecture, genomic regions and candidate genes associated with body weight gain, feed intake and feed conversion ratio in Japanese quails. For detection the informative genomic windows, genotyping data on 920 quails was used in a single-step genome-wide association study. The BLUPf90 family software was used to perform related analyses. Theresults was calculated based on the proportion of additive genetic variance (agv) explained by genomic region with an average size of 1.5-Mb of adjacent SNPs. Windows with accounting for more than 1% of the agv were used to identify genomic regions and to search for candidate genes. A total of 13 significant windows over 8 chromosomes were explained 23% of the agv for the body weight gain and including SMYD1, ADGRG6 and CFL2 candidate genes. A peak on CJA2 explained the largest proportion of variance. For feed intake, we identified 20 informative windows across 8 chromosomes and including ACSL, PPA2, FGF2 and RBL2 candidate genes. These regions explained 38% of the agv and a peak on CJA4 explained of agv. Also, for the feed conversion ratio, 12 significant windows were identified on 7 chromosomes and explained 23.7% of agv, contained ATRNL1 and PTPN4 candidate genes. Four genomic regions had a pleiotropic effect. Considering the identification of new genome regions and the key role of the mentioned genes related to feed intake, the single step method can be validated for GWAS in feed efficiency traits.
Hossein Mohammadi; Amir Hossein khaltabadi farahani; Mhammad hossein Moradi; Abouzar Najafi
Volume 23, Issue 4 , January 2022, , Pages 481-490
Abstract
Understanding the genetic control of temperament as a complex trait and correlated with economic traits is one of the breeding goals in beef cattle industry. The aim of the current study was genome wide association studies (GWAS) based on Gene set enrichment analysis for detecting the loci associated ...
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Understanding the genetic control of temperament as a complex trait and correlated with economic traits is one of the breeding goals in beef cattle industry. The aim of the current study was genome wide association studies (GWAS) based on Gene set enrichment analysis for detecting the loci associated with temperament traits in Brahman cattle breed. Therefore, 1370 Brahman cattle and phenotype records associated with temperament traits including Exit velocity, Pen Score, and Temperament Score were used. The evaluation of genome-wide association was carried out using PLINK package 1.90. The gene enrichment analysis was performed by the goseq R package for identifying biological pathways of nearby genes in selected candidate regions and finally, GO, Metacyc, KEEG, Reactome and panther databases were applied for bioinformatics analysis. By Gene set enrichment analysis, the biological pathways and candidate genes of neurotransmitter secretion (NRXN3 and CACNG3), Dopamine Neurotransmitter Release Cycle (PPFIA2), regulation of neuron projection development (GRID2), neuron projection (SLC8A1 and KCNQ2), Axonal growth inhibition (RTN4R), Neurotrophin signaling pathway (MAP2K2, MAP3K5 and PSEN1) and Focal adhesion (TLN2) were identified. The detected candidate genes played an important role in differentiation of synapse, neurotransmitters, neurological diseases and disorders, oxidative and environmental stresses, hormone receptors and glucose homeostasis. Considering the confirmation of the previous region of genome wide association and the identification of new genomic regions, the findings of this study can be useful in the genetic selection of higher production cattle through calm animals.