Genetic evaluation of fiber length and fiber diameter from Inner Mongolia White Cashmere goats at different ages

Study of the Influence of Non-Genetic Factors on the Growth and Development Traits and Cashmere Production Traits of Inner Mongolia White Cashmere Goats (Erlangshan Type)

The purpose of this study was to investigate the effects of non-genetic factors on the growth and development performance of Inner Mongolia white cashmere goats (Erlanghan type), such as birth weight (BW), weaning weight (WW), 6-month weight (6 WT), 12-month weight (12 WT), body height (BH), and body length (BL), and wool production performance, such as cashmere fineness (CF), cashmere thickness (CT), and cashmere yield (CY). The research objects were 4654 kids produced by 45 buck goats and 2269 doe goats in the Erlang Mountain Ranch of Beiping Textile Co., Ltd., Inner Mongolia, from 2020 to 2023. Based on the generalized linear model, ANOVA was used to analyze the effects of non-genetic factors, such as birth year (Y), birth month (M), sex (S), birth type (T), birth herd (H), assay flock (F), age at measurement (MA), and the age of doe goats at lambing (DLA), on growth and development traits and cashmere traits. The results show that the birth weight (BW), weaning weight (WW), 6-month weight (6 WT), 12-month weight (12 WT), body length (BL), body height (BH), chest depth (CD), chest width (CW), chest circumference (CC), cannon circumference (CNC), wool length (WL), and cashmere yield (CY) of buck goats were significantly higher than those of doe goats (p < 0.01), and the fineness of the cashmere produced by doe goats was significantly finer than that produced by buck goats (p < 0.01). The birth weight, weaning weight, and 6-month weight of single kids were significantly higher than those of multiple kids (p < 0.01), but the effect on the 12-month weight was not significant (p > 0.05). The age of doe goats at lambing had significant effects on birth weight, weaning weight, and 6-month weight (p < 0.01). Assay flock and age at measurement had significant effects on cashmere fineness, cashmere thickness, and cashmere yield (p < 0.01). This study will provide a basis for the scientific breeding and management of cashmere goats and lay a foundation for the setting of fixed effects in the genetic evaluation model of Inner Mongolia white cashmere goats (Erlangshan type).

Study of genetic parameters for pre-weaning growth traits in inner Mongolia white Arbas cashmere goats

Inner Mongolia Arbas white cashmere goats is a dual-purpose breed for producing cashmere and meat. In recent years, its meat has become more and more popular among consumers because of rich nutrients and delicious flavor. Therefore, it is particularly important to study the genetic and non-genetic factors affecting the early growth traits and estimate variance components of pre-weaning growth traits of Inner Mongolia Albas white cashmere goats. A total of 37487 kidding records such as birth weight (BWT), weaning weight (WWT), average daily gain from birth to weaning (ADG) and Kleiber ratio (KR) from 343 sires and 7296 dams were used in this study. The most appropriate model was chosen on the basis of likelihood ratio test by fitting six models which excluding or including maternal genetic, maternal permanent environmental effects. The parameters were estimated under the most appropriate model using AIREML method by WOMBAT software. With the best model (Model 6), heritability estimates were 0.0435, 0.0911, 0.0932 and 0.2339 for BWT, WWT, ADG and KR traits, respectively. Maternal heritability estimates were 0.0143, 0.0246, 0.0220 and 0.0186 for BWT, WWT, ADG, and KR traits respectively. The correlation between different traits was estimated with the most suitable model by using bivariate analysis method. The direct additive genetic correlation among the traits ranged from -0.026 (BWT~KR) to 0.772 (ADG~KR). The maternal permanent environment correlation is between -0.289 (BWT-KR) ~0.900 (WWT-ADG). Results indicated that maternal effects and direct-maternal genetic covariance should be considered in any program aimed at improving pre-weaning growth traits to have an accurate genetic evaluation. In addition, positive and medium to high genetic correlations generally exist among WWT, ADG and KR due to the existence of genetic variation for early growth traits. The results showed that the genetic progress of these traits could be slowly through selection except for KR.

Convergent Genomic Signatures of Cashmere Traits: Evidence for Natural and Artificial Selection

Convergent evolution provides powerful opportunities to investigate the genetic basis of complex traits. The Tibetan antelope (Pantholops hodgsonii) and Siberian ibex (Capra sibirica) belong to different subfamilies in Bovidae, but both have evolved similar superfine cashmere characteristics to meet the cold temperature in plateau environments. The cashmere traits of cashmere goats underwent strong artificial selection, and some traces of domestication also remained in the genome. Hence, we investigated the convergent genomic signatures of cashmere traits between natural and artificial selection. We compared the patterns of convergent molecular evolution between Tibetan antelope and Siberian ibex by testing positively selected genes, rapidly evolving genes and convergent amino acid substitutions. In addition, we analyzed the selected genomic features of cashmere goats under artificial selection using whole-genome resequencing data, and skin transcriptome data of cashmere goats were also used to focus on the genes involved in regulating cashmere traits. We found that molecular convergent events were very rare, but natural and artificial selection genes were convergent enriched in similar functional pathways (e.g., ECM-receptor interaction, focal adhesion, PI3K-Akt signaling pathway) in a variety of gene sets. Type IV collagen family genes (COL4A2, COL4A4, COL4A5, COL6A5, COL6A6) and integrin family genes (ITGA2, ITGA4, ITGA9, ITGB8) may be important candidate genes for cashmere formation and development. Our results provide a comprehensive approach and perspective for exploring cashmere traits and offer a valuable reference for subsequent in-depth research on the molecular mechanisms regulating cashmere development and fineness.

Accuracy of Genomic Selection for Important Economic Traits of Cashmere and Meat Goats Assessed by Simulation Study

Genomic selection in plants and animals has become a standard tool for breeding because of the advantages of high accuracy and short generation intervals. Implementation of this technology is hindered by the high cost of genotyping and other factors. The aim of this study was to determine an optional marker density panel and reference population size for using genomic selection of goats, with speculation on the number of QTLs that affect the important economic traits of goats. In addition, the effect of buck population size in the reference population on the accuracy of genomic estimated breeding value (GEBV) was discussed. Based on the previous genetic evaluation results of Inner Mongolia White Cashmere Goats, live body weight (LBW, h2 = 0.11) and fiber diameter (FD, h2 = 0.34) were chosen to perform genomic selection in this study. Reasonable genome parameters and generation transmission processes were set, and phenotypic and genotype data of the two traits were simulated. Then, different sizes of the reference population and validation population were selected from progeny. The GEBVs were obtained by six methods, including GBLUP (Genomic Best Linear Unbiased Prediction), ssGBLUP (Single Step Genomic Best Linear Unbiased Prediction), BayesA, BayesB, Bayesian ridge regression, and Bayesian LASSO. The correlation coefficient between the predicted and realized phenotypes from simulation was calculated and used as a measure of the accuracy of GEBV in each trait. The results showed that the medium marker density Panel (45 K) could be used for genomic selection in goats, which can ensure the accuracy of the GEBV. The reference population size of 1,500 can achieve greater genetic progress in genomic selection for fiber diameter and live body weight in goats by comparing with the population size below this level. The accuracy of the GEBV for live body weight and fiber diameter was better when the number of QTLs was 100 and 50, respectively. Additionally, the accuracy of GEBV was discovered to be good when the buck population size was up to 200. Meanwhile, the accuracy of the GEBV for medium heritability traits (FDs) was found to be higher than the accuracy of the GEBV for low heritability traits (LBWs). These findings will provide theoretical guidance for genomic selection in goats by using real data.