Siavash Manzoori; Amir Hossein Khaltabadi Farahani; Mohammad Hossein Moradi
Volume 25, Issue 1 , April 2023, , Pages 1-11
Abstract
The present study was conducted in order to select effective markers in breed discrimination and compare the performance of SNP marker selection methods with the data of 304 animals from 14 different breeds that were genotyped using the Illumina SNP50K marker panel. Knowledge of genetic structure are ...
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The present study was conducted in order to select effective markers in breed discrimination and compare the performance of SNP marker selection methods with the data of 304 animals from 14 different breeds that were genotyped using the Illumina SNP50K marker panel. Knowledge of genetic structure are very important for better understanding of genetic changes in genomic studies. The information content of each marker is used as an index for selecting markers in reducing the size of marker panels. To estimate the information content of each marker, the following selection methods were used: Fst (pairwise & global), Theta, Delta, D, Gst, G'st, G"st and Principal Component Analysis. In this study, the logarithm of the likelihood ratio was used to select markers. According to the results, all selection methods for identifying markers had similar performance. The number of common markers between the methods was at least 42 markers and at most 499 SNP markers. In general, the F_ST statistical method required a smaller number of markers to achieve a successful assignment. G'st and G"st statistics showed poor performance with more than 350 markers to achieve 95% correct assignment. It should be noted that with only the top 60 selected markers, it is possible to achieve a success rate of more than 70%. According to the results, Wright's paired Fst had better performance than other SNP selection methods. The obtained results lead to the creation of exclusive panels to identify various breeds, which have great economic importance.
amir hossein khaltabadi farahani; hossein mohammadi; hossein moradi
Volume 22, Issue 3 , September 2020, , Pages 325-335
Abstract
The aim of this study was to identify the molecular pathways related to litter size in sheep using gene set enrichment analysis. For this purpose, information of high prolificacy sheep breeds including Wadi, Hu, Icelandic, Finnsheep, and Romanov and low prolificacy including Texel and Rahmani ...
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The aim of this study was to identify the molecular pathways related to litter size in sheep using gene set enrichment analysis. For this purpose, information of high prolificacy sheep breeds including Wadi, Hu, Icelandic, Finnsheep, and Romanov and low prolificacy including Texel and Rahmani were used for genome wide association studies and gene set enrichment analysis. Genome-wide association study was conducted using GenABEL package of R program. Gene set enrichment analysis was performed with the goseq R package to identify the biological pathways associated with candidate genes. We identified different sets of candidate genes related to litter size: BMP5, DHCR24, BMPR1B, ESR1, ESR2 andPLCB1 in Wadi and Romanov; SMAD1, SMAD2, INSR and PTGS2 in Finnsheep and Hu; BMP7, NCOA1 and ERBB4 in Icelandic; BMP4, MSRB and SPP1 in Texel; BMP7, EGFR and KCNMA1 in Rahmani. According to pathway analysis, 30 pathways were associated with the litter size trait. Among biological pathways, the TGF-β signaling, Oxytocin signaling, Estrogen signaling, Prolactin signaling, and Insulin signaling pathways have significant association with ovulation rate and litter size trait. Overall, this study supported previous results from GWAS for litter size, also revealed additional regions in the sheep genome associated with litter size in sheep. These findings could potentially be useful for selective breeding for more litter size in sheep.