Through domestication and human selection, horses have acquired various coat colors, including seven phenotypes: black, brown, dark bay, bay, chestnut, white, and gray. Here we determined the genotypes for melanocortin-1 receptor (MC1R) and agouti signaling protein (ASIP)

Summary Background Due to the thriving development of the modern horse industry and the occurrence of horse related crimes, the demand for methods of individual horse identification, parentage tests and other genetic analyses is increasing. Previous methods had disadvantages that decreased the accuracy of the results, lacked the inclusion of all commonly used short tandem repeats (STR) or increased the experimental cost and time. Objectives We aimed to develop a novel 13‐plex STR typing system to resolve the above issues. Study design Experimental study. Methods Twelve autosomal and most commonly used di‐nucleotide STRs (AHT4, AHT5, ASB2, ASB17, ASB23, HMS2, HMS3, HMS6, HMS7, HTG4, HTG10 and VHL20), and a Y‐chromosomal STR (YJ10) were included. We redesigned the primers of eight STRs to establish a novel multiplex PCR system and tested this system for species specificity, sensitivity and repeatability. Results Full profiles were easily generated in one fast PCR reaction using a low‐cost polymerase, as little as 1 ng of horse DNA template and 13 pairs of primers labelled with fluorescent dyes. No full profile was generated from DNA templates of humans or other commonly encountered animals. We also established an allelic ladder that contained 110 alleles based on 200 horses from 12 breeds and calculated standard population genetic parameters based on 150 Thoroughbreds. Stutter analysis showed that the averages of the stutter ratios were distinctly lower than those of lower allele ratios and the combined probability of paternity exclusion for this system were 0.994659935 (CPEduo) and 0.999854032 (CPEtrio). Main limitations A nonspecific and relatively low peak at 316 bp was frequently observed in locus HMS2, which is a nonexistent allele in all horses and should be ignored. Conclusions Our results indicate that this 13‐plex STR genotyping system is sensitive, species‐specific, cost‐effective and robust for applications in the horse industry and forensic investigation.

The intestinal microbial composition and metabolic functions under normal physiological conditions in the donkey are crucial for health and production performance. However, compared with other animal species, limited information is currently available regarding the intestinal microbiota of donkeys. In the present study, we characterized the biogeography and potential functions of the intestinal digesta- and mucosa-associated microbiota of different segments of the intestine (jejunum, ileum, cecum, and colon) in the donkey, focusing on the differences in the microbial communities between the small and large intestine. Our results show that, Firmicutes and Bacteroidetes dominate in both the digesta- and mucosa-associated microbiota in different intestinal locations of the donkey. Starch-degrading and acid-producing (butyrate and lactate) microbiota, such as Lactobacillus and Sarcina, were more enriched in the small intestine, while the fiber- and mucin-degrading bacteria, such as Akkermansia, were more enriched in the large intestine. Furthermore, metabolic functions in membrane transport and lipid metabolism were more enriched in the small intestine, while functions for energy metabolism, metabolism of cofactors and vitamins, amino acid metabolism were more enriched in the large intestine. In addition, the microbial composition and functions in the digesta-associated microbiota among intestinal locations differed greatly, while the mucosal differences were smaller, suggesting a more stable and consistent role in the different intestinal locations. This study provides us with new information on the microbial differences between the small and large intestines of the donkey and the synergistic effects of the intestinal microbiota with host functions, which may improve our understanding the evolution of the equine digestive system and contribute to the healthy and efficient breeding of donkeys.

Body size is an important trait in companion animals. Recently, a primitive Japanese dog breed, the Shiba Inu, has experienced artificial selection for smaller body size, resulting in the “Mame Shiba Inu” breed. To identify loci and genes that might explain the difference in the body size of these Shiba Inu dogs, we applied whole genome sequencing of pooled samples (pool-seq) on both Shiba Inu and Mame Shiba Inu. We identified a total of 13,618,261 unique SNPs in the genomes of these two breeds of dog. Using selective sweep approaches, including FST, Hp and XP-CLR with sliding windows, we identified a total of 12 genomic windows that show signatures of selection that overlap with nine genes (PRDM16, ZNF382, ZNF461, ERGIC2, ENSCAFG00000033351, CCDC61, ALDH3A2, ENSCAFG00000011141, and ENSCAFG00000018533). These results provide candidate genes and specific sites that might be associated with body size in dogs. Some of these genes are associated with body size in other mammals, but 8 of the 9 genes are novel candidate genes that need further study.

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