Runs of homozygosity (ROHom) are contiguous stretches of homozygous regions of the genome. In contrast, runs of heterozygosity (ROHet) are heterozygosity-rich regions. The detection of these two types of genomic regions (ROHom and ROHet) is influenced by the parameters involved in their identification and the number of available single nucleotide polymorphisms (SNP). The present study aimed to test the effect of chip density in detecting ROHom and ROHet in the Italian Simmental cattle breed. A sample of 897 animals were genotyped at low-density (50k SNP; 397 individuals), medium-density (140k SNP; 348 individuals), or high-density (800k SNP; 152 individuals). The number of ROHom and ROHet per animal (nROHom and nROHet, respectively) and their average length were calculated. ROHom or ROHet shared by more than one animal and the number of times a particular SNP was inside a run were also computed (SNPROHom and SNPROHet). As the chip density increased, the nROHom increased, whereas their average length decreased. In contrast, the nROHet decreased and the average length increased as the chip density increased. The most repeated ROHom harbored no genes, whereas in the most repeated ROHet four genes (SNRPN, SNURF, UBE3A and ATP10A) previously associated with reproductive traits were found. Across the three datasets, 31 SNP, located on Bos taurus autosome (BTA) 6, and 37 SNP (located on BTA21) exceeded the 99th percentile in the distribution of the SNPROHom and SNPROHet, respectively. The genomic region on BTA6 mapped the SLIT2, PACRGL, and KCNIP4 genes, whereas 19 and 18 genes were mapped on BTA16 and BTA21, respectively. Interestingly, most of genes found through the ROHet analysis were previously reported to be related to health, reproduction, and fitness traits. The results of the present study confirm that the detection of ROHom is more reliable when the chip density increases, whereas the ROHet trend seems to be the opposite. Genes and Quantitative Trait Loci (QTL) mapped in the highlighted regions confirm that ROHet can be due to balancing selection, thus related to fitness traits, health, and reproduction, whereas ROHom are mainly involved in production traits. The results of the present study strengthened the usefulness of these parameters in analyzing the genomes of livestock and their biological meaning.

中文翻译：

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基因分型密度对牛纯合性和杂合性检测的影响


纯合性运行 (ROHom) 是基因组纯合区域的连续延伸。相反，杂合性游程 (ROHet) 是杂合性丰富的区域。这两种类型的基因组区域（ROHom 和 RHet）的检测受到其识别中涉及的参数和可用单核苷酸多态性 (SNP) 数量的影响。本研究旨在测试芯片密度在检测意大利西门塔尔牛品种中 ROHom 和 RHet 时的效果。对 897 只动物样本进行了低密度（50k SNP；397 个体）、中密度（140k SNP；348 个体）或高密度（800k SNP；152 个体）的基因分型。计算每只动物的 ROHom 和 ROHet 数量（分别为 nROHom 和 nROHet）及其平均长度。还计算了多个动物共享的 ROHom 或 ROHet，以及特定 SNP 在一次运行中出现的次数（SNPROHom 和 SNPROHet）。随着芯片密度的增加，nROHom 增加，而它们的平均长度减少。相反，随着芯片密度的增加，nROHet 减小，平均长度增加。重复次数最多的 ROHom 不包含任何基因，而在重复次数最多的 ROHet 中，发现了四个先前与生殖性状相关的基因（SNRPN、SNURF、UBE3A 和 ATP10A）。在这三个数据集中，位于牛常染色体 (BTA) 6 上的 31 个 SNP 和位于 BTA21 上的 37 个 SNP 分别超过了 SNPROHom 和 SNPROHet 分布的第 99 个百分位。 BTA6 上的基因组区域映射了 SLIT2、PACRGL 和 KCNIP4 基因，而 BTA16 和 BTA21 上分别映射了 19 和 18 个基因。有趣的是，通过 RHet 分析发现的大多数基因此前都被报道与健康、繁殖和健康特征相关。 本研究的结果证实，当芯片密度增加时，ROHom 的检测更加可靠，而 ROHet 的趋势似乎相反。突出区域中映射的基因和数量性状位点（QTL）证实ROHet可能是由于平衡选择，因此与适应性状、健康和繁殖相关，而ROHom主要涉及生产性状。本研究的结果增强了这些参数在分析牲畜基因组及其生物学意义方面的有用性。