RNA‐seq analysis reveals new candidate genes for drip loss in a Pietrain × Duroc × Landrace × Yorkshire population

Drip loss, one of the most important meat quality traits, is characterized by low heritability. To date, the genetic factors affecting the drip loss trait have not been clearly elucidated. The objective of this study was to identify critical candidate genes affecting drip loss. First, we generated a Pietrain × Duroc × Landrace × Yorkshire commercial pig population and obtained phenotypic values for the drip loss trait. Furthermore, we constructed two RNA libraries from pooled samples of longissimus dorsi muscles with the highest (H group) and lowest (L group) drip loss and identified the differentially expressed genes (DEGs) between these extreme phenotypes using RNA‐seq technology. In total, 25 883 genes were detected in the H and L group libraries, and none was specifically expressed in only one library. Comparative analysis of gene expression levels found that 150 genes were differentially expressed, of which 127 were upregulated and 23 were downregulated in the H group relative to the L group. In addition, 68 drip loss quantitative trait loci (QTL) overlapping with 63 DEGs were identified, and these QTL were distributed mainly on chromosomes 1, 2, 5 and 6. Interestingly, the triadin (TRDN) gene, which is involved in muscle contraction and fat deposition, and the myostatin (MSTN) gene, which has a role in muscle growth, were localized to more than two drip loss QTL, suggesting that both are critical candidate genes responsible for drip loss.     

miR-22 regulates C2C12 myoblast proliferation and differentiation by targeting TGFBR1

Recently, miR-22 was found to be differentially expressed in different skeletal muscle growth period, indicated that it might have function in skeletal muscle myogenesis. In this study, we found that the expression of miR-22 was the most in skeletal muscle and was gradually up-regulated during mouse myoblast cell (C2C12 myoblast cell line) differentiation. Overexpression of miR-22 repressed C2C12 myoblast proliferation and promoted myoblast differentiation into myotubes, whereas inhibition of miR-22 showed the opposite results. During myogenesis, we predicted and verified transforming growth factor beta receptor 1 (TGFBR1), a key receptor of the TGF-β/Smad signaling pathway, was a target gene of miR-22. Then, we found miR-22 could regulate the expression of TGFBR1 and down-regulate the Smad3 signaling pathway. Knockdown of TGFBR1 by siRNA suppressed the proliferation of C2C12 cells but induced its differentiation. Conversely, overexpression of TGFBR1 significantly promoted proliferation but inhibited differentiation of the myoblast. Additionally, when C2C12 cells were treated with different concentrations of transforming growth factor beta 1 (TGF-β1), the level of miR-22 in C2C12 cells was reduced. The TGFBR1 protein level was significantly elevated in C2C12 cells treated with TGF-β1. Moreover, miR-22 was able to inhibit TGF-β1-induced TGFBR1 expression in C2C12 cells. Altogether, we demonstrated that TGF-β1 inhibited miR-22 expression in C2C12 cells and miR-22 regulated C2C12 cell myogenesis by targeting TGFBR1.     

一起荷斯坦奶牛乳头瘤病诊断及其病毒基因型分析

牛乳头瘤病毒是一种能够引起牛发生皮肤乳头状瘤、纤维素瘤、膀胱和食道癌的DNA病毒,现已在牛群中广泛传播,对牛养殖业造成了重大经济损失.为了诊断甘肃某荷斯坦奶牛场300多头泌乳期奶牛乳头突发疣状物的病因,本研究采用流行病学调查、临床观察、组织病理学、分子生物学检测方法和基因测序技术,对患有疣状物的奶牛进行综合诊断.结果 表明,乳头患疣状物奶牛的其它部位无类似生长物,无发烧、疼痛等异常临床症状,组织病理学HE检测疣状物呈现角化过度和细胞空泡化现象,这与牛乳头瘤病毒感染的组织病理变化相似,并且用PCR方法获得了牛乳头状瘤病毒L1基因,测序比对结果显示为乳头瘤病毒7型基因,核苷酸同源性达98％以上.因此,本次荷斯坦奶牛乳头突发疣状物为乳头瘤病毒7型感染引起的,这是甘肃地区首次发现该基因型乳头瘤病毒,应引起奶牛场与防疫部门的重视.     

3A蛋白104–115位氨基酸缺失口蹄疫A型标记病毒的构建

【目的】构建一株含3A非结构蛋白104–115位氨基酸缺失的口蹄疫A型标记病毒,分析其生物学特性和发展标记疫苗的潜力。【方法】采用融合PCR技术,在当前流行毒株A/Sea-97/CHA/2014全长感染性克隆p QAHN中引入3A104–115位氨基酸的缺失,构建全长重组质粒。全长质粒经NotI线化后转染表达T7RNA聚合酶的稳定细胞系,拯救标记病毒。RT-PCR、序列分析、间接免疫荧光和Western blotting鉴定标记病毒。噬斑表型和一步生长曲线分析标记病毒的生物学特性,并用实验室开发的针对3A优势表位(AEKNPLE)的阻断ELISA方法分析其区分亲本和标记病毒感染的动物。【结果】成功拯救到一株含3A 104–115位氨基酸缺失的口蹄疫A型标记病毒,3A表位的缺失没有影响标记病毒的噬斑表型和一步生长曲线。3A单抗阻断ELISA可以明显区分标记病毒和亲本病毒感染的动物。【结论】本研究构建的3A蛋白104–115位氨基酸缺失的标记病毒可以作为发展口蹄疫鉴别诊断疫苗的候选毒株,用于我国未来口蹄疫A型的有效防控。     

一类一级饱和反应系统的极限环

本文研究生化反应中一类饱和反应的数学模型：应用微分方程定性理论,完整地解决了该系统极限环的存在性、唯一性和不存在性等问题．     

Genome-Wide Association of Carbon and Nitrogen Metabolism in the Maize Nested Association Mapping Population

Carbon (C) and nitrogen (N) metabolism are critical to plant growth and development and are at the basis of crop yield and adaptation. We performed high-throughput metabolite analyses on over 12,000 samples from the nested association mapping population to identify genetic variation in C and N metabolism in maize (Zea mays ssp. mays). All samples were grown in the same field and used to identify natural variation controlling the levels of 12 key C and N metabolites, namely chlorophyll a, chlorophyll b, fructose, fumarate, glucose, glutamate, malate, nitrate, starch, sucrose, total amino acids, and total protein, along with the first two principal components derived from them. Our genome-wide association results frequently identified hits with single-gene resolution. In addition to expected genes such as invertases, natural variation was identified in key C₄ metabolism genes, including carbonic anhydrases and a malate transporter. Unlike several prior maize studies, extensive pleiotropy was found for C and N metabolites. This integration of field-derived metabolite data with powerful mapping and genomics resources allows for the dissection of key metabolic pathways, providing avenues for future genetic improvement.Carbon (C) and nitrogen (N) metabolism are the basis for life on Earth. The production, balance, and tradeoffs of C and N metabolism are critical to all plant growth, yield, and local adaptation (Coruzzi and Bush, 2001; Coruzzi et al., 2007). In plants, there is a critical balance between the tissues that are producing energy (sources) and those using it (sinks), as the identities and locations of these vary through time and developmental stage (Smith et al., 2004). While a great deal of research has focused on the key genes and proteins involved in these processes (Wang et al., 1993; Kim et al., 2000; Takahashi et al., 2009), relatively little is known about the natural variation within a species that fine-tunes these processes in individual plants.In addition, a key aspect of core C metabolism involves the nature of plant photosynthesis. While the majority of plants use standard C₃ photosynthetic pathways, some, including maize (Zea mays) and many other grasses, use C₄ photosynthesis to concentrate CO₂ in bundle sheath cells to avoid wasteful photorespiration (Sage, 2004). Under some conditions (such as drought or high temperatures), C₄ photosynthesis is much more efficient than C₃ photosynthesis. Since these conditions are expected to become more prevalent in the near future due to climate change, various research groups are working to convert C₃ crop species to C₄ metabolism in order to boost crop production and food security (Sage and Zhu, 2011). Beyond this, better understanding of both C₃ and C₄ metabolic pathways will aid efforts to breed crops for superior yield, N-use efficiency, and other traits important for global food production.In the last two decades, quantitative trait locus (QTL) mapping, first with linkage analysis and later with association mapping, has been used to dissect C and N metabolism in several species, including Arabidopsis (Arabidopsis thaliana; Mitchell-Olds and Pedersen, 1998; Keurentjes et al., 2008; Lisec et al., 2008; Sulpice et al., 2009), tomato (Solanum lycopersicum; Schauer et al., 2006), and maize (Hirel et al., 2001; Limami et al., 2002; Zhang et al., 2006, 2010a, 2010b). These studies identified key genetic regions underlying variation in core C and N metabolism, many of which include candidate genes known to be involved in these processes.Previous studies of genetic variation for C and N metabolism are limited by the fact that they identified trait loci only through linkage mapping in artificial families or through association mapping across populations of unrelated individuals. Linkage mapping benefits from high statistical power due to many individuals sharing the same genotype at any given location, but it suffers from low resolution due to the limited number of generations (and hence recombination events) since the initial founders. Association mapping, in turn, enjoys high resolution due to the long recombination histories of natural populations but suffers from low power, since most genotypes occur in only a few individuals. In addition, many of these studies focused on C and N in artificial settings (e.g. greenhouses or growth chambers) instead of field conditions, running the risk that important genetic loci could be missed if the conditions do not include important (and potentially unknown) natural environmental variables.To address these issues and improve our understanding of C and N metabolism in maize, we used a massive and diverse germplasm resource, the maize nested association mapping (NAM) population (Buckler et al., 2009; McMullen et al., 2009), to evaluate genetic variation underlying the accumulation of 12 targeted metabolites in maize leaf tissue under field conditions. This population was formed by mating 25 diverse maize lines to the reference line, B73, and creating a 200-member biparental family from each of these crosses. The entire 5,000-member NAM population thus combines the strengths of both linkage and association mapping (McMullen et al., 2009), and it has been used to identify QTLs for important traits such as flowering time (Buckler et al., 2009), disease resistance (Kump et al., 2011; Poland et al., 2011), and plant architecture (Tian et al., 2011; Peiffer et al., 2013). Most importantly, this combination of power and resolution frequently resolves associations down to the single-gene level, even when using field-based data.The metabolites we profiled are key indicators of photosynthesis, respiration, glycolysis, and protein and sugar metabolism in the plant (Sulpice et al., 2009). By taking advantage of a robotized metabolic phenotyping platform (Gibon et al., 2004), we performed more than 100,000 assays across 12,000 samples, with two independent samples per experimental plot. Raw data and the best linear unbiased predictors (BLUPs) of these data were included as part of a study of general functional variation in maize (Wallace et al., 2014), but, to our knowledge, this is the first in-depth analysis of these metabolic data. We find strong correlations among several of the metabolites, and we also find extensive pleiotropy among the different traits. Many of the top QTLs are also near or within candidate genes relating to C and N metabolism, thus identifying targets for future breeding and selection. These results provide a powerful resource for those working with core C and N metabolism in plants and for improving maize performance in particular.     

口蹄疫病毒非结构蛋白3AB双抗体夹心ELISA方法的建立

抗原纯净度是口蹄疫(Foot-and-mouthdisease,FMD)灭活疫苗质量检验的一项重要内容,一般采用疫苗2–3次免疫动物后,检测非结构蛋白(Non-structuralprotein,NSP)抗体是否阳转,判断疫苗抗原的纯净度。文中旨在建立定量检测FMD灭活疫苗抗原中NSP3AB含量的ELISA方法,为疫苗质量控制提供参考方法。利用口蹄疫病毒(Foot-and-mouthdiseasevirus,FMDV)NSP3A单克隆抗体和辣根过氧化物酶(Horseradish peroxidase,HRP)标记的3B单克隆抗体,建立定量检测NSP3AB含量的双抗体夹心ELISA检测方法。采用原核表达并纯化的3AB蛋白作为标准品,标准品系列稀释,绘制标准曲线,以标准品与未加抗原的阴性对照吸光值(OD)的比值大于2.0的标准品最低浓度为最低检测限。标准品浓度介于4.7–600.0 ng/mL之间时,测得的OD值与浓度呈线性相关,回归曲线呈直线,相关系数R2=0.99,确定最低检测限为4.7ng/mL。检测12份未纯化灭活抗原中3AB蛋白含量介于9.3–200.0ng/mL之间;而纯化后的...