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Distribution patterns and variation analysis of simple sequence repeats in different genomic regions of bovid genomes

机译:牛基因组不同基因组区域中简单序列重复序列的分布模式和变异分析

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As the first examination of distribution, guanine-cytosine (GC) pattern, and variation analysis of microsatellites (SSRs) in different genomic regions of six bovid species, SSRs displayed nonrandomly distribution in different regions. SSR abundances are much higher in the introns, transposable elements (TEs), and intergenic regions compared to the 3′-untranslated regions (3′UTRs), 5′UTRs and coding regions. Trinucleotide perfect SSRs (P-SSRs) were the most frequent in the coding regions, whereas, mononucleotide P-SSRs were the most in the introns, 3′UTRs, TEs, and intergenic regions. Trifold P-SSRs had more GC-contents in the 5′UTRs and coding regions than that in the introns, 3′UTRs, TEs, and intergenic regions, whereas mononucleotide P-SSRs had the least GC-contents in all genomic regions. The repeat copy numbers (RCN) of the same mono- to hexanucleotide P-SSRs showed significantly different distributions in different regions (P tri-??tetra-??penta-??hexanucleotide P-SSRs in the same regions. The analysis of coefficient of variability (CV) of SSRs showed that the CV variations of RCN of the same mono- to hexanucleotide SSRs were relative higher in the intronic and intergenic regions, followed by the CV variation of RCN in the TEs, and the relative lower was in the 5′UTRs, 3′UTRs, and coding regions. Wide SSR analysis of different genomic regions has helped to reveal biological significances of their distributions.
机译:作为对六个牛科物种不同基因组区域的分布,鸟嘌呤-胞嘧啶(GC)模式和微卫星(SSRs)变异分析的首次检查,SSRs在不同区域显示出非随机分布。与3'非翻译区(3'UTR),5'UTR和编码区相比,内含子,转座因子(TEs)和基因间区的SSR丰度更高。三核苷酸完美SSR(P-SSRs)在编码区域中最常见,而单核苷酸P-SSR在内含子,3'UTR,TE和基因间区域中最常见。三倍体P-SSR在5'UTR和编码区中的GC含量高于内含子,3'UTR,TE和基因间区,而单核苷酸P-SSR在所有基因组区域中的GC含量最少。相同的单核苷酸至六核苷酸的P-SSR的重复拷贝数(RCN)在不同区域中显示出显着不同的分布(在相同区域中的Ptri-β>Δtetra-β>βpenta-β>β六核苷酸P-SSR。对SSR变异系数(CV)的分析表明,同一单核苷酸至六核苷酸SSR的RCN的CV变异在内含子和基因间区域相对较高,其次是TE中RCN的CV变异,以及相对较低的是5'UTR,3'UTR和编码区,对不同基因组区域的广泛SSR分析有助于揭示其分布的生物学意义。

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