Yuhuan Meng

Genome sequencing and comparison of two nonhuman primate animal models, the cynomolgus and Chinese rhesus macaques

The nonhuman primates most commonly used in medical research are from the genus Macaca. To better understand the genetic differences between these animal models, we present high-quality draft genome sequences from two macaque species, the cynomolgus/crab-eating macaque and the Chinese rhesus macaque. Comparison with the previously sequenced Indian rhesus macaque reveals that all three macaques maintain abundant genetic heterogeneity, including millions of single-nucleotide substitutions and many insertions, deletions and gross chromosomal rearrangements. By assessing genetic regions with reduced variability, we identify genes in each macaque species that may have experienced positive selection. Genetic divergence patterns suggest that the cynomolgus macaque genome has been shaped by introgression after hybridization with the Chinese rhesus macaque. Macaque genes display a high degree of sequence similarity with human disease gene orthologs and drug targets. However, we identify several putatively dysfunctional genetic differences between the three macaque species, which may explain functional differences between them previously observed in clinical studies.

Identifying Candidate Genes for Type 2 Diabetes Mellitus and Obesity through Gene Expression Profiling in Multiple Tissues or Cells

Type 2 Diabetes Mellitus (T2DM) and obesity have become increasingly prevalent in recent years. Recent studies have focused on identifying causal variations or candidate genes for obesity and T2DM via analysis of expression quantitative trait loci (eQTL) within a single tissue. T2DM and obesity are affected by comprehensive sets of genes in multiple tissues. In the current study, gene expression levels in multiple human tissues from GEO datasets were analyzed, and 21 candidate genes displaying high percentages of differential expression were filtered out. Specifically, DENND1B, LYN, MRPL30, POC1B, PRKCB, RP4-655J12.3, HIBADH, and TMBIM4 were identified from the T2DM-control study, and BCAT1, BMP2K, CSRNP2, MYNN, NCKAP5L, SAP30BP, SLC35B4, SP1, BAP1, GRB14, HSP90AB1, ITGA5, and TOMM5 were identified from the obesity-control study. The majority of these genes are known to be involved in T2DM and obesity. Therefore, analysis of gene expression in various tissues using GEO datasets may be an effective and feasible method to determine novel or causal genes associated with T2DM and obesity.

An Effort to Use Human-Based Exome Capture Methods to Analyze Chimpanzee and Macaque Exomes

Non-human primates have emerged as an important resource for the study of human disease and evolution. The characterization of genomic variation between and within non-human primate species could advance the development of genetically defined non-human primate disease models. However, non-human primate specific reagents that would expedite such research, such as exon-capture tools, are lacking. We evaluated the efficiency of using a human exome capture design for the selective enrichment of exonic regions of non-human primates. We compared the exon sequence recovery in nine chimpanzees, two crab-eating macaques and eight Japanese macaques. Over 91% of the target regions were captured in the non-human primate samples, although the specificity of the capture decreased as evolutionary divergence from humans increased. Both intra-specific and inter-specific DNA variants were identified; Sanger-based resequencing validated 85.4% of 41 randomly selected SNPs. Among the short indels identified, a majority (54.6%–77.3%) of the variants resulted in a change of 3 base pairs, consistent with expectations for a selection against frame shift mutations. Taken together, these findings indicate that use of a human design exon-capture array can provide efficient enrichment of non-human primate gene regions. Accordingly, use of the human exon-capture methods provides an attractive, cost-effective approach for the comparative analysis of non-human primate genomes, including gene-based DNA variant discovery.

The correlation coefficient of GC content of the genome-wide genes is positively correlated with animal evolutionary relationships

In this study, we present a new method for evaluating animal evolutionary relationships. We used the GC% levels of genome‐wide genes to determine the correlation between the GC% content and evolutionary relationship. The correlation coefficients of the GC% content of the orthologous genes of the paired animal species were calculated for a total of 21 species, and the evolutionary branching dates of these 21 species were derived from fossil records. The correlation coefficient of the GC% content of the orthologous genes of the species pair under study served as an indicator of their evolutionary relationship. Moreover, there was a decreasing linear relationship between the correlation coefficient and evolutionary branching date (R 2 = 0.930).

Genome-Wide Analysis of Positively Selected Genes in Seasonal and Non-Seasonal Breeding Species

Some mammals breed throughout the year, while others breed only at certain times of year. These differences in reproductive behavior can be explained by evolution. We identified positively-selected genes in two sets of species with different degrees of relatedness including seasonal and non-seasonal breeding species, using branch-site models. After stringent filtering by sum of pairs scoring, we revealed that more genes underwent positive selection in seasonal compared with non-seasonal breeding species. Positively-selected genes were verified by cDNA mapping of the positive sites with the corresponding cDNA sequences. The design of the evolutionary analysis can effectively lower the false-positive rate and thus identify valid positive genes. Validated, positively-selected genes, including CGA, DNAH1, INVS, and CD151, were related to reproductive behaviors such as spermatogenesis and cell proliferation in non-seasonal breeding species. Genes in seasonal breeding species, including THRAP3, TH1L, and CMTM6, may be related to the evolution of sperm and the circadian rhythm system. Identification of these positively-selected genes might help to identify the molecular mechanisms underlying seasonal and non-seasonal reproductive behaviors.

RNA-seq analysis of the hypothalamic transcriptome reveals the networks regulating physiopathological progress in the diabetic GK rat.

The Goto-Kakizaki (GK) rat is an animal model of non-obese type 2 diabetes (T2D). The GK rat was generated through the introduction of various genetic mutations from continuous inbreeding; these rats develop diabetes spontaneously. The mutated genes in GK rats may play key roles in the regulation of diabetes. The hypothalamus plays a central role in systematic energy homeostasis. Here, the hypothalamic transcriptomes in GK and Wistar rats at 4, 8 and 12 weeks were investigated by RNA-seq, and multiple variants and gene expression profiles were obtained. The number of variants identified from GK rats was significantly greater than that of Wistar rats, indicating that many variants were fixed and heritable in GK rats after selective inbreeding. The differential gene expression analysis indicated that GK rats had a dysfunctional hypothalamic melanocortin system and attenuation of the hypothalamic glucose-sensing pathway. In addition, we generated integrated gene network modules by combining the protein-protein interaction (PPI) network, co-expression network and mutations in GK and Wistar rats. In the modules, GK-specific genes, such as Bad, Map2k2, Adcy3, Adcy2 and Gstm6, may play key roles in hypothalamic regulation in GK rats. Our research provides a comprehensive map of the abnormalities in the GK rat hypothalamus, which reveals the new mechanisms of pathogenesis of T2D.

Ancestry, Plasmodium cynomolgi prevalence and rhesus macaque admixture in cynomolgus macaques ( Macaca fascicularis ) bred for export in Chinese breeding farms

Most cynomolgus macaques (Macaca fascicularis) used in the United States as animal models are imported from Chinese breeding farms without documented ancestry. Cynomolgus macaques with varying rhesus macaque ancestry proportions may exhibit differences, such as susceptibility to malaria, that affect their suitability as a research model.