Identification of SNPs and expression patterns of FZD3 gene and its effect on wool traits in Chinese Merino sheep (Xinjiang Type)

Zhao, Bi; Fu, Xuefeng; Tian, Kechuan; Huang, Xixia; Jiang, Di; Bai, Yan; Xu, Xinming; Tian, Yuezhen; Wu, Weiwei; Sulayman, Ablat; Zeng, Weidan; Tulafu, Hanikezi

doi:10.1016/s2095-3119(19)62735-8

Cited by 9 publications

(7 citation statements)

References 30 publications

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“…Shearing was carried out in June each year, and the first shearing took place at 13 to 15 months of age. The flock management of all animals was consistent with that reported by Zhao et al [31].…”

Section: Phenotype Datasupporting

confidence: 86%

The Effect of Integrating Genomic Information into Genetic Evaluations of Chinese Merino Sheep

Chen

Luo

Zhao

et al. 2020

Animals

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Genomic evaluations are a method for improving the accuracy of breeding value estimation. This study aimed to compare estimates of genetic parameters and the accuracy of breeding values for wool traits in Merino sheep between pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) using Bayesian inference. Data were collected from 28,391 yearlings of Chinese Merino sheep (classified in 1992–2018) at the Xinjiang Gonaisi Fine Wool Sheep-Breeding Farm, China. Subjectively-assessed wool traits, namely, spinning count (SC), crimp definition (CRIM), oil (OIL), and body size (BS), and objectively-measured traits, namely, fleece length (FL), greasy fleece weight (GFW), mean fiber diameter (MFD), crimp number (CN), and body weight pre-shearing (BWPS), were analyzed. The estimates of heritability for wool traits were low to moderate. The largest h2 values were observed for FL (0.277) and MFD (0.290) with ssGBLUP. The heritabilities estimated for wool traits with ssGBLUP were slightly higher than those obtained with PBLUP. The accuracies of breeding values were low to moderate, ranging from 0.362 to 0.573 for the whole population and from 0.318 to 0.676 for the genotyped subpopulation. The correlation between the estimated breeding values (EBVs) and genomic EBVs (GEBVs) ranged from 0.717 to 0.862 for the whole population, and the relative increase in accuracy when comparing EBVs with GEBVs ranged from 0.372% to 7.486% for these traits. However, in the genotyped population, the rank correlation between the estimates obtained with PBLUP and ssGBLUP was reduced to 0.525 to 0.769, with increases in average accuracy of 3.016% to 11.736% for the GEBVs in relation to the EBVs. Thus, genomic information could allow us to more accurately estimate the relationships between animals and improve estimates of heritability and the accuracy of breeding values by ssGBLUP.

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Section: Phenotype Datasupporting

confidence: 86%

The Effect of Integrating Genomic Information into Genetic Evaluations of Chinese Merino Sheep

Chen

Luo

Zhao

et al. 2020

Animals

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“…It could increase the level of trust held by animal breeders in genetic improvement, and is important as confirmation of a scientific hypotheses [ 51 ]. There are many methods used to verify identified candidate genes/QTLs from GWAS results, e.g., SNP chip analysis [ 52 ], qRT-PCR [ 12 ], or association analysis in another population [ 53 ]. RNA-seq with the capabilities of high-throughput sequencing, could help us better understand the translation of genetic loci into biological mechanisms that underlie phenotypic expression of important traits [ 54 ].…”

Section: Discussionmentioning

confidence: 99%

Weighted single-step GWAS and RNA sequencing reveals key candidate genes associated with physiological indicators of heat stress in Holstein cattle

Luo

Brito

et al. 2022

J Animal Sci Biotechnol

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Background The study of molecular processes regulating heat stress response in dairy cattle is paramount for developing mitigation strategies to improve heat tolerance and animal welfare. Therefore, we aimed to identify quantitative trait loci (QTL) regions associated with three physiological indicators of heat stress response in Holstein cattle, including rectal temperature (RT), respiration rate score (RS), and drooling score (DS). We estimated genetic parameters for all three traits. Subsequently, a weighted single-step genome-wide association study (WssGWAS) was performed based on 3200 genotypes, 151,486 phenotypic records, and 38,101 animals in the pedigree file. The candidate genes located within the identified QTL regions were further investigated through RNA sequencing (RNA-seq) analyses of blood samples for four cows collected in April (non-heat stress group) and four cows collected in July (heat stress group). Results The heritability estimates for RT, RS, and DS were 0.06, 0.04, and 0.03, respectively. Fourteen, 19, and 20 genomic regions explained 2.94%, 3.74%, and 4.01% of the total additive genetic variance of RT, RS, and DS, respectively. Most of these genomic regions are located in the Bos taurus autosome (BTA) BTA3, BTA6, BTA8, BTA12, BTA14, BTA21, and BTA24. No genomic regions overlapped between the three indicators of heat stress, indicating the polygenic nature of heat tolerance and the complementary mechanisms involved in heat stress response. For the RNA-seq analyses, 2627 genes were significantly upregulated and 369 downregulated in the heat stress group in comparison to the control group. When integrating the WssGWAS, RNA-seq results, and existing literature, the key candidate genes associated with physiological indicators of heat stress in Holstein cattle are: PMAIP1, SBK1, TMEM33, GATB, CHORDC1, RTN4IP1, and BTBD7. Conclusions Physiological indicators of heat stress are heritable and can be improved through direct selection. Fifty-three QTL regions associated with heat stress indicators confirm the polygenic nature and complex genetic determinism of heat tolerance in dairy cattle. The identified candidate genes will contribute for optimizing genomic evaluation models by assigning higher weights to genetic markers located in these regions as well as to the design of SNP panels containing polymorphisms located within these candidate genes. Graphical Abstract

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“…PCA clearly showed that Aohan fine-wool sheep (AHS) was clearly partitioned from alpine merino sheep (AMS) and Chinese merino sheep (CMS). However, Qinghai fine-wool sheep (QHS) was not completely separated from AMS and CMS, which may be related to the joint breeding of QHS with AMS and CMS ( Di et al, 2011 , Di et al, 2014 ; Li et al, 2016 ; Zhao et al, 2019 ; Wei et al, 2020 ). To resolve their phylogenetic relationships, we constructed a NJ tree among the 120 individuals based on the pairwise genetic distances ( Figure 1B ).…”

Section: Resultsmentioning

confidence: 99%

Selective Sweeps Uncovering the Genetic Basis of Horn and Adaptability Traits on Fine-Wool Sheep in China

et al. 2021

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Long-term natural and artificial selection leads to change in certain regions of the genome, resulting in selection signatures that can reveal genes associated with selected traits, such as horns (i.e., polled/horned), high-quality wool traits, and high-altitude hypoxia adaptability. These are complex traits determined by multiple genes, regulatory pathways, and environmental factors. A list of genes with considerable effects on horn and adaptability traits has not been found, although multiple quantitative trait loci (QTL) have been identified. Selection signatures could be identified using genetic differentiation (FST), polymorphism levels θπ, and Tajima’s D. This study aimed to identify selection signatures in fine-wool sheep and to investigate the genes annotated in these regions, as well as the biological pathways involved in horn and adaptability traits. For this purpose, the whole-genome sequence of 120 individuals from four breeds, which come from different elevations and habitats in China, was used to analyze selection signatures for horn and adaptability traits. Annotation of the consensus regions of FST and θπ ratios revealed a list of identified genes associated with polled/horned and high-altitude hypoxia adaptability traits, such as RXPF2, EERFC4, MSH6, PP1R12A, THBS1, ATP1B2, RYR2, and PLA2G2E. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified genes related primarily to mismatch repair, metabolism, vascular smooth muscle contraction, and cardiac muscle contraction. This is the first study to demonstrate that selection signatures play an important role in the polled/horned and high-altitude hypoxia adaptability traits of fine-wool sheep breeds that have undergone high-intensity selection and adapted to different ecological environments in China. Changes observed in the genome of fine-wool sheep may have acted on genomic regions that affect performance traits and provide a reference for genome design and breeding.

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Identification of SNPs and expression patterns of FZD3 gene and its effect on wool traits in Chinese Merino sheep (Xinjiang Type)

Cited by 9 publications

References 30 publications

The Effect of Integrating Genomic Information into Genetic Evaluations of Chinese Merino Sheep

The Effect of Integrating Genomic Information into Genetic Evaluations of Chinese Merino Sheep

Weighted single-step GWAS and RNA sequencing reveals key candidate genes associated with physiological indicators of heat stress in Holstein cattle

Selective Sweeps Uncovering the Genetic Basis of Horn and Adaptability Traits on Fine-Wool Sheep in China

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