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ABSTRACTRhesus macaque (RM, Macaca mulatta), as an important model animal, commonly suffers from chronic diarrheal disease, challenging the breeding of RMs. Gut microbiomes play key roles in maintaining intestinal health of RMs. However, it is still unclear about more features of gut microbiome as responsible for intestinal health of RMs. In this study, we performed de novo assembly of metagenome-assembled genomes (MAGs) based on fecal metagenomes from chronic diarrheal RMs and asymptomatic individuals. In total of 731 non-redundant MAGs with at least 80% completeness were reconstructed in this study. More than 97% MAGs were novel genomes compared with more than 250,000 reference genomes. MAGs of Campylobacterand Helicobacteraceae from RM guts mainly carried flagella-associated virulence genes and chemotaxis-associated virulence genes, which might mediate motility and adhesion of bacteria. Comparing to MAGs of Campylobacterfrom humans, distributions and functions of these MAGs of Campylobacterfrom RMs exhibited significant differences. Most members of Bacteroidota, Spirochaetota, Helicobacteraceae, Lactobacillaceae and Anaerovibriosignificantly decreased in guts of chronic diarrhea RMs. More than 92% MAGs in this study were not contained in 2,985 MAGs previously reported from other 22 non-human primates (NHPs), expanding the microbial diversity in guts of NHPs. The distributions and functions of gut microbiome were prominently influenced by host phylogeny of NHPs. Our results could help to more clearly understand about the diversity and function of RMs gut microbiome.

Repeat number variations of coding simple sequence repeats (coding SSRs) generate phenotype diversity for environmental adaptation and rapid adaptive evolution. Despite the positive potential of coding SSR mutations, the repeat variations have also been shown to cause hereditary disorders and severe diseases. However, there have been few reports on the analysis of SSR polymorphism in genome-wide coding regions. We identified 1016 coding SSRs, of which 283 SSRs (27.9%) were polymorphic with 2 to 8 alleles, using 33 re-sequenced giant panda genomes. The 283 polymorphic coding SSRs were mapped on 260 genes, which were assigned into 547 GO terms. Functional analysis of 260 genes showed that four significantly enriched pathways: thyroid hormone signaling pathway, pancreatic secretion, gastric acid secretion, and thyroid hormone synthesis, were relevant to digestion and metabolism. The comparison analysis of gene functions exhibited positive regulation of transcription, DNA-templated term (GO:0045893), the poly(A) RNA-binding term (GO:0008270), and zinc ion–binding term (GO:0044822) which were only significantly enriched in genes containing polymorphic coding SSRs. This indicates coding SSR polymorphism may be involved in binding and regulation functions that can affect the expression of their downstream genes and contribute to diverse phenotypes. Our results provide a solid foundation for further study regarding the effect of coding SSR polymorphism on the adaptation, adaptive evolution, and abnormal traits of the giant panda.

Background: The CpG islands (CGIs) are clusters of CpGs in CG-rich regions, which confer a critical role in the regulation of transcription. Although multiple programs are developed for searching CGIs, but all of them have drawbacks, such as low accuracy or long running time. Objective: The aim of this study was to develop a new CGIs search tool, namely CpGIScan (CpG Islands Scan), which improves upon previous programs. Method: In this work, a CpG island is defined by three types of parameters: the window length, the guanine and cytosine (G + C) frequency, and the ratio of the observed over the expected CpGs (CpG o/e). The algorithm in CpGIScan is based on the sliding window method. To reduce the time required to identify CGIs, multithread technology is employed in our program. CpGIScan was compared to existing widely used tools to benchmark its performance. Results: Evaluations on a set of test sequences show that CpGIScan has high sensitivity and specificity. In addition, CpGIScan is at least 4 times faster than existing tools. It has a large performance advantage over previous tools when searching CpG islands from the bulk genomes. CpGIScan is written in C++ and provided under the GNU CPL license. It is freely available at https://github.com/jianzuoyi/CpGIScan. Conclusion: CpGIScan was specifically developed for ultrafast identifying CGIs in large sequences sets. It takes the advantages of previous tools and significantly improves the computational efficiency. CpGIScan will be of value to researchers for generating an initial genome-wide map of CpG islands.

The gray wolf (Canis lupus) is a widely distributed top predator and ancestor of the domestic dog. To address questions about wolf relationships to each other and dogs, we assembled and analyzed a data set of 34 canine genomes. The divergence between New and Old World wolves is the earliest branching event and is followed by the divergence of Old World wolves and dogs, confirming that the dog was domesticated in the Old World. However, no single wolf population is more closely related to dogs, supporting the hypothesis that dogs were derived from an extinct wolf population. All extant wolves have a surprisingly recent common ancestry and experienced a dramatic population decline beginning at least ∼30 thousand years ago (kya). We suggest this crisis was related to the colonization of Eurasia by modern human hunter–gatherers, who competed with wolves for limited prey but also domesticated them, leading to a compensatory population expansion of dogs. We found extensive admixture between dogs and wolves, with up to 25% of Eurasian wolf genomes showing signs of dog ancestry. Dogs have influenced the recent history of wolves through admixture and vice versa, potentially enhancing adaptation. Simple scenarios of dog domestication are confounded by admixture, and studies that do not take admixture into account with specific demographic models are problematic.