Profiling of the yak skeletal muscle tissue gene expression and comparison with the domestic cattle by genome array

Of all the mammals of the world, the yak lives at the highest altitude area of more than 3000 m. Comparison between yak and cattle of the low-altitude areas will be informative in studying animal adaptation to higher altitudes. To investigate the molecular mechanism involved in meat quality differences between the two Chinese special varieties Qinghai yak and Qinchuan cattle, 12 chemical–physical characteristics of the longissimus dorsi muscle related to meat quality were compared at the age of 36 months, and the gene expression profiles were constructed by utilizing the bovine genome array. Significant analysis of microarrays was used to identify the differentially expressed genes. Gene ontology and pathway analysis were performed by a free Web-based Molecular Annotation System 2.0. The results reveal ~11 000 probes representing about 10 000 genes that were detected in both the Qinghai yak and Qinchuan cattle. A total of 1922 genes were shown to be differentially expressed, 633 probes were upregulated and 1259 probes were downregulated in the muscle tissue of Qinghai yak that were mainly involved in ubiquitin-mediated proteolysis, muscle growth regulation, glucose metabolism, immune response and so on. Quantitative real-time PCR (qRT-PCR) was performed to validate some differentially expressed genes identified by microarray. Further analysis implied that animals living at a high altitude may supply energy by more active protein catabolism and glycolysis compared with those living in the plain areas. Our results establish the groundwork for further studies on yaks’ meat quality and will be beneficial in improving the yaks’ breeding by molecular biotechnology.     

利用基因芯片技术筛选秦川牛公牛与阉牛肌肉组织差异表达基因

为了筛选秦川牛公牛和阉牛肌肉组织差异表达的基因,探讨二者肉质差异的分子生物学机理,文章利用Affymetrix公司生产的牛基因组芯片技术,分别检测了3头36月龄秦川牛公牛与阉牛背最长肌肌肉组织的mRNA表达水平变化;运用Significance Analysis of Microarrays(SAM)法对秦川牛公牛和阉牛基因表达谱进行了差异分析;并通过分子注释系统平台(MAS2.0)对差异表达基因进行了功能富集类分析和调控通路分析;最后应用实时定量PCR技术对部分差异表达基因进行了验证。基因表达谱分析结果显示,在36月龄秦川牛的肌肉组织中,共检测到约11000个探针,代表大约10000个基因。共筛选出差异表达基因143条,主要涉及胶原纤维的组织和合成、细胞粘附、细胞生长调控、泛素介导的蛋白分解代谢和横纹肌收缩等生物学过程;在分子注释系统数据库中注释到的显著调控通路为细胞外基质受体反应、细胞通讯、焦点粘连和紧密连接等;所验证的差异表达基因的荧光定量PCR结果与芯片结果基本一致。结合已有的文献报道,文章初步认为ECM受体反应、细胞通讯、焦点粘连、紧密接头等调控通路及COL3A1、COL1A1、COL1A2、SPP1、FBN1、MMP2、ECM1、MYH3、MYH8、S100A4、ASPN、CFD等基因可能是参与调控秦川牛阉割前后肉质性状差异的重要调控通路和基因。此外,还筛选出一些尚未在GenBank上登陆的序列,推测可能是未知的新基因,它们在牛肉质代谢过程中的作用还需进一步的研究证明。     

鼠伤寒沙门氏菌baeR过表达株的构建及其耐药性

[背景]鼠伤寒沙门氏菌（Salmonella typhimurium）是一种重要的人兽共患病原菌,其多重耐药性问题日益严重,双组分系统可调控鼠伤寒沙门氏菌的耐药性。[目的]通过构建鼠伤寒沙门氏菌baeR过表达株及回补株探究BaeSR双组分系统对鼠伤寒沙门氏菌耐药性的影响。[方法]在BaeSR双组分系统和AcrB外排泵双缺失株（CRΔbaeSRΔacrB）的基础上构建baeR过表达株（CRpbaeRΔbaeSRΔacrB）及baeR回补株（CRcbaeRΔbaeSRΔacrB）,测定双缺失株、回补株和过表达株的最小抑菌浓度（minimum inhibitory concentration,MIC）,并对其生长特性、生物膜形成能力及运动性进行分析。采用转录组学技术筛选与耐药相关的差异表达基因,RT-qPCR验证耐药相关基因。[结果]构建了鼠伤寒沙门氏菌baeR过表达株和baeR回补株。与双缺失株相比,过表达株对氧氟沙星、恩诺沙星、氟苯尼考、乙酰甲喹、头孢他啶、头孢噻呋、阿莫西林和氨苄西林的MIC分别升高2-256倍,对大观霉素、安普霉素的MIC下降了50%;与双缺失株相比,回补株对头孢他啶...     

The identification of candidate radio marker genes using a coexpression network analysis in gamma‐irradiated rice

Plant physiological and biochemical processes are significantly affected by gamma irradiation stress. In addition, gamma‐ray (GA) differentially affects gene expression across the whole genome. In this study, we identified radio marker genes (RMGs) responding only to GA stress compared with six abiotic stresses (chilling, cold, anoxia, heat, drought and salt) in rice. To analyze the expression patterns of differentially expressed genes (DEGs) in gamma‐irradiated rice plants against six abiotic stresses, we conducted a hierarchical clustering analysis by using a complete linkage algorithm. The up‐ and downregulated DEGs were observed against six abiotic stresses in three and four clusters among a total of 31 clusters, respectively. The common gene ontology functions of upregulated DEGs in clusters 9 and 19 are associated with oxidative stress. In a Pearson's correlation coefficient analysis, GA stress showed highly negative correlation with salt stress. On the basis of specific data about the upregulated DEGs, we identified the 40 candidate RMGs that are induced by gamma irradiation. These candidate RMGs, except two genes, were more highly induced in rice roots than in other tissues. In addition, we obtained other 38 root‐induced genes by using a coexpression network analysis of the specific upregulated candidate RMGs in an ARACNE algorithm. Among these genes, we selected 16 RMGs and 11 genes coexpressed with three RMGs to validate coexpression network results. RT‐PCR assay confirmed that these genes were highly upregulated in GA treatment. All 76 genes (38 root‐induced genes and 38 candidate RMGs) might be useful for the detection of GA sensitivity in rice roots.     

Identification of Gene Expression Changes from Colitis to CRC in the Mouse CAC Model

A connection between colorectal carcinogenesis and inflammation is well known, but the underlying molecular mechanisms have not been elucidated. Chemically induced colitis-associated cancer (CAC) is an outstanding mouse model for studying the link between inflammation and cancer. Additionally, the CAC model is used for examining novel diagnostic, prognostic, and predictive markers for use in clinical practice. Here, a CAC model was established in less than 100 days using azoxymethane (AOM) with dextran sulfate sodium salt (DSS) in BALB/c mice. We examined the mRNA expression profiles of three groups: control untreated mice (K), DSS-induced chronic colitis mice (D), and AOM/DSS-induced CAC (AD) mice. We identified 6301 differentially expressed genes (DEGs) among the three groups, including 93 persistently upregulated genes and 139 persistently downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed that the most persistent DEGs were significantly enriched in metabolic or inflammatory components in the tumor microenvironment. Furthermore, several associated DEGs were identified as potential DEGs by protein-protein interaction (PPI) network analysis. We selected 14 key genes from the DEGs and potential DEGs for further quantitative real-time PCR (qPCR) verification. Six persistently upregulated, 3 persistently downregulated DEGs, and the other 3 genes showed results consistent with the microarray data. We demonstrated the regulation of 12 key genes specifically involved in Wnt signaling, cytokine and cytokine receptor interactions, homeostasis, and tumor-associated metabolism during colitis-associated CRC. Our results suggest that a close relationship between metabolic and inflammatory mediators of the tumor microenvironment is present in CAC.     

Genome-wide analysis reveals the effects of artificial selection on production and meat quality traits in Qinchuan cattle

A new strain of Qinchuan cattle (QNS) has been obtained after more than forty years of selective breeding, and it shows good performance and production traits. To characterize the genetic changes that have resulted from breeding, we sequenced 10 QNS and 10 of the original breed Qinchuan cattle (QCC) for the first time, with average of 12.5-fold depth. A total of 31,242,284 and 29,612,517 SNPs were identified in the QCC and QNS genomes, 47.81% and 44.36% of which were found to be novel, respectively. Furthermore, population structure analysis revealed the selection that these cattle had experienced. Then, 332 and 571 potential selected genes were obtained, associated with enhanced immunity and acclimatization in QCC (CD5, SMARCA2, CATHL2, etc.) and production or meat quality traits in QNS (PLCD3, MB, PPARGC1A, etc.). These results revealed the efforts of selective breeding for Chinese Qinchuan cattle, and will be helpful for future cattle breeding.     

Novel Muscle-Specific Genes TCAP,TNNI1, and FHL1 in Cattle: SNVs,Linkage Disequilibrium,Combined Genotypes,Association Analysis of Growth Performance,and Carcass Quality Traits and Expression Studies

TCAP, TNNI1, and FHL1 regulate muscle growth and development. In this study, four single nucleotide variants (SNVs) were discovered in almost all of the exon and intron regions of the TCAP, TNNI1, and FHL1 genes using DNA pooled sequencing, polymerase chain reaction (PCR)-RFLP, and forced-PCR-RFLP methods in 576 cattle. Four SNVs were significantly associated with the growth performance and carcass quality traits of the cattle. In addition, the haplotype, haplotype frequency, and linkage disequilibrium coefficient of three sequence variants were also evaluated in the cattle population. Haplotype analysis demonstrated that eight haplotypes were present in the Qinchuan cattle population and no haplotypes were present in the Chinese Holstein population; haplotype 1 had the highest frequency in the Qinchuan (42.7%) population. Statistical analyses of 12 combined genotypes indicated that some were significantly associated with the growth performance and carcass quality traits of the Qinchuan cattle population. Moreover, the quantitative real-time polymerase chain reaction results demonstrated that the bovine TCAP, TNNI1, and FHL1 genes were exclusively expressed in muscle tissue. These data support the high potentials of the TCAP, TNNI1, and FHL1 as marker genes to improve the growth performance and carcass quality traits of Qinchuan cattle or other animals selection programs.     

Identification and validation of key genes associated with non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is one of the main causes of death induced by cancer globally. However, the molecular aberrations in NSCLC patients remain unclearly. In the present study, four messenger RNA microarray datasets (GSE18842, GSE40275, GSE43458, and GSE102287) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between NSCLC tissues and adjacent lung tissues were obtained from GEO2R and the overlapping DEGs were identified. Moreover, functional and pathway enrichment were performed by Funrich, while the protein–protein interaction (PPI) network construction were obtained from STRING and hub genes were visualized and identified by Cytoscape software. Furthermore, validation, overall survival (OS) and tumor staging analysis of selected hub genes were performed by GEPIA. A total of 367 DEGs (95 upregulated and 272 downregulated) were obtained through gene integration analysis. The PPI network consisted of 94 nodes and 1036 edges in the upregulated DEGs and 272 nodes and 464 edges in the downregulated DEGs, respectively. The PPI network identified 46 upregulated and 27 downregulated hub genes among the DEGs, and six (such as CENPE, NCAPH, MYH11, LRRK2, HSD17B6, and A2M) of that have not been identified to be associated with NSCLC so far. Moreover, the expression differences of the mentioned hub genes were consistent with that in lung adenocarcinoma and lung squamous cell carcinoma in the TCGA database. Further analysis showed that all the six hub genes were associated with tumor staging except MYH11, while only the upregulated DEG CENPE was associated with the worse OS of patients with NSCLC. In conclusion, the current study showed that CENPE, NCAPH, MYH11, LRRK2, HSD17B6, and A2M might be the key genes contributed to tumorigenesis or tumor progression in NSCLC, further functional study is needed to explore the involved mechanisms.