PCR-based detection of genes encoding virulence determinants in Staphylococcus aureus from bovine subclinical mastitis cases

The present study was carried out to genotypically characterize Staphylococcus aureus (S. aureus) isolated from bovine mastitis cases. A total of 37 strains of S. aureus were isolated during processing of 552 milk samples from 140 cows. The S. aureus strains were characterized phenotypically, and were further characterized genotypically by polymerase chain reaction using oligonucleotide primers that amplified genes encoding coagulase (coa), clumping factor (clfA), thermonuclease (nuc), enterotoxin A (entA), and the gene segments encoding the immunoglobulin G binding region and the X region of protein A gene spa. All of the isolates yielded an amplicon with a size of approximately 1,042 bp of the clfA gene. The amplification of the polymorphic spa gene segment encoding the immunoglobulin G binding region was observed in 34 isolates and X-region binding was detected in 26 isolates. Amplification of the coa gene yielded three different products in 20, 10, and 7 isolates. The amplification of the thermonuclease gene, nuc, was observed in 36 out of 37 isolates. All of the samples were negative for the entA gene. The phenotypic and genotypic findings of the present strategies might provide an understanding of the distribution of the prevalent S. aureus clones among bovine mastitis isolates, and might aid in the development of steps to control S. aureus infections in dairy herds.     

Combined use of phenotypic and genotypic information in sampling animals for genotyping in detection of quantitative trait loci.

Conventional selective genotyping which is using the extreme phenotypes (EP) was compared with alternative criteria to find the most informative animals for genotyping with respects to mapping quantitative trait loci (QTL). Alternative sampling strategies were based on minimizing the sampling error of the estimated QTL effect (MinERR) and maximizing likelihood ratio test (MaxLRT) using both phenotypic and genotypic information. In comparison, animals were randomly genotyped either within or across families. One hundred data sets were simulated each with 30 half-sib families and 120 daughters per family. The strategies were compared in these datasets with respect to estimated effect and position of a QTL within a previously defined genomic region at genotyping 10, 20 or 30% of the animals. Combined linkage disequilibrium linkage analysis (LDLA) was applied in a variance component approach. Power to detect QTL was significantly higher for both MinERR and MaxLRT compared with EP and random genotyping methods (either across or within family), for all the proportions of genotyped animals. Power to detect significant QTL (alpha = 0.01) with 20% genotyping for MinERR and MaxLRT was 80 and 75% of that obtained with complete genotyping compared with 70 and 38% genotyping for EP within and across families respectively. With 30% genotyping, the powers were 78, 83, 78 and 58% respectively. The estimated variance components were unbiased in EP strategies (within and across family), only when at least 30% was genotyped. To decrease the number of genotyped individuals either MinERR or MaxLRT could be considered. With 20% genotyping in MinERR, the estimated QTL variance components were not significant compared with complete genotype information but all studied strategies at 20% genotyping overestimated the QTL effect. Results showed that combining the phenotypic and genotypic information in selective genotyping (e.g. MinERR and MaxLRT) is better than using only the EPs and the combined methods can be considered as alternative approaches to decrease genotyping costs, with unbiased QTL effects, decreased sampling variance of the QTL variance component and also increased the power of QTL detection.     

Variations for Fusarium head blight resistance associated with genomic diversity in different sources of the resistant wheat cultivar ‘Sumai 3’

Fusarium head blight (FHB), caused by Fusarium graminearum, is a serious disease of wheat (Triticum aestivum L.) associated with contamination by the mycotoxin deoxynivalenol (DON). The FHB-resistant wheat cultivar ‘Sumai 3’ has been used extensively around the world. The existence of variation in FHB resistance among ‘Sumai 3’ accessions has been discussed. In this study, genetic variation among ‘Sumai 3’ accessions collected from six countries were identified using SSR markers; our results demonstrate unique chromosome regions in Sumai 3-AUT and Sumai 3-JPN (‘Sumai 3’ accessions from Austria and Japan, respectively). Field evaluation indicated strong resistance to FHB in Sumai 3-AUT. The polymorphic rate (number of polymorphic markers/number of available markers × 100) based on a DArT array was 12.5% between the two ‘Sumai 3’ accessions. Genotyping for DNA markers flanking FHB-resistant quantitative trait loci (QTLs) revealed genetic variations for the QTL regions on 5AS and 2DS; however, no variation was observed for the QTL regions on 3BS and 6B. Thus, the variation in FHB resistance among ‘Sumai 3’ accessions in the field is due to genetic diversity.     

Rapid genotyping with DNA micro-arrays for high-density linkage mapping and QTL mapping in common buckwheat (Fagopyrum esculentum Moench)

For genetic studies and genomics-assisted breeding, particularly of minor crops, a genotyping system that does not require a priori genomic information is preferable. Here, we demonstrated the potential of a novel array-based genotyping system for the rapid construction of high-density linkage map and quantitative trait loci (QTL) mapping. By using the system, we successfully constructed an accurate, high-density linkage map for common buckwheat (Fagopyrum esculentum Moench); the map was composed of 756 loci and included 8,884 markers. The number of linkage groups converged to eight, which is the basic number of chromosomes in common buckwheat. The sizes of the linkage groups of the P1 and P2 maps were 773.8 and 800.4 cM, respectively. The average interval between adjacent loci was 2.13 cM. The linkage map constructed here will be useful for the analysis of other common buckwheat populations. We also performed QTL mapping for main stem length and detected four QTL. It took 37 days to process 178 samples from DNA extraction to genotyping, indicating the system enables genotyping of genome-wide markers for a few hundred buckwheat plants before the plants mature. The novel system will be useful for genomics-assisted breeding in minor crops without a priori genomic information.     

口蹄疫病毒分子生物学检测方法研究进展

口蹄疫是一种高度传染的病毒性疫病,及早诊断意义重大。分子生物学检测方法在口蹄疫病诊断和病毒分型过程中具有许多优势,已经广泛应用。作者对实时荧光PCR法、多重PCR法、核酸杂交法、基因芯片法、环介导等温扩增法及核酸序列依赖扩增法等进行分析和比较,对各种方法的检测效率、灵敏度、优缺点及国内外的研究情况进行综述,为口蹄疫病毒分子生物学检测方法的应用与深入开发提供参考。     

基于焦磷酸测序技术的基因编辑位点检测方法的建立

为探索建立基因编辑农产品的检测方法,本研究以猪MSTN基因定点编辑位点为靶标,通过设计PCR-焦磷酸测序引物、优化测序碱基次序、构建标准曲线等步骤,建立基于焦磷酸测序技术的基因编辑产品定性和定量检测方法。结果表明,该方法能够准确检测出MSTN基因第3外显子的AG缺失位点,具备基因分型定性判定和等位基因频率定量检测的功能,从而准确检测样品是否为MSTN基因编辑猪产品,以及样品基因编辑产品的含量。     

High‐throughput detection of highly benzimidazole‐resistant allele E198A with mismatch primers in allele‐specific real‐time polymerase chain reaction

BACKGROUND: A point mutation often confers resistance of organisms against medical drugs and agricultural pesticides. Allele‐specific nucleotide polymerase chain reaction (ASPCR) and allele‐specific quantitative real‐time PCR using SYBR Green (ASQPCR) are widely and effectively applied to detect and monitor this type of resistance. However, the former is unsuitable for high‐throughput detection, and the latter often reduces the accuracy of detection. RESULTS: In order to decrease background amplification, a rapid and high‐throughput genotyping method with mismatch primers was developed (ASQPCR‐MP) and applied specifically to survey the frequency of the highly benzimidazole‐resistant MBC^HR mutation (E198A) in the β‐tubulin gene of Sclerotinia sclerotiorum (Lib.) de Bary populations. Genomic DNA from 223 sclerotia was analysed. Similar genotype results were also obtained using ASPCR with mismatch primers and a mycelial growth inhibition assay. It was found that ASQPCR‐MP clearly differentiated MBC^HR and benzimidazole‐sensitive MBC^S phenotypes. Moreover, ASQPCR‐MP took less than 6 h to complete. CONCLUSION: ASQPCR‐MP appears suitable for large epidemiological studies involving resistant genotypes and requiring high‐throughout formats. Copyright © 2009 Society of Chemical Industry     

基于HRM获得与桃Tssd紧密连锁的SNP标记

【目的】植物中,SNP标记具有分布广泛、分辨率高、共显性和多态性高等特点,是遗传研究的常用分子标记。桃全基因组测序完成,获得了大量SNP位点。利用现有的SNP数据进行简单、快速的SNP基因分型是基因定位、品种鉴定和图谱构建等后续研究的基础。文章拟建立采用高分辨率熔解曲线进行不同类型SNP的基因分型方法,以获得与桃温度敏感半矮生型基因紧密连锁的分子标记。【方法】以普通生长型(ST)单株97-32-46为母本,温度敏感半矮生型单株03-94-2(Tssd)为父本进行人工杂交,利用其分离群体96个后代单株为研究材料。在定位目标基因的区间内开发连锁和不同类型的SNP标记的基础上,采用高分辨率熔解曲线进行SNP的基因分型并获得与目标性状紧密连锁的SNP标记。【结果】明确了DNA模板和Mg~(2+)是影响基因分型的关键因子,并确立了反应体系最佳浓度区间。在15μL反应体系中模板DNA的量低于5.0 ng时或Mg~(2+)浓度低于1.6μmol·L~(-1)时则不能完成PCR扩增和基因分型;根据亲本基因型和表型一致的SNP位点设计引物,扩增片段长度在140 bp左右。高分辨率熔解曲线分析可对由单个核苷酸变异引起的4种不同类型的SNP(A/T、A/G、A/C和C/G)进行基因分型,并正确区分了温度敏感半矮生型和普通生长型,与进行Sanger测序鉴定的结果一致。采用96孔板对温度敏感半矮生型和普通生长型各48个分离后代单株进行了PCR扩增和基因分型,确定了遗传距离。分型结果表明高分辨率熔解曲线分析技术可以将96个样杂交后代单株分为温度敏感半矮生型和普通生长型2种,正确地区分了A/A基因型和A/T基因型。在96个样品中仅1个没有成功扩增,在温度敏感半矮生型和普通生长型中各存在1个重组单株。获得与温度敏感半矮生型基因紧密连锁的SNP标记,遗传距离为2.11 cM。【结论】建立了基于高分辨率熔解曲线分析的SNP基因分型。尽管高分辨率熔解曲线分析技术无法区分两种不同纯合类型的SNP变异,但仍不失为区分已知变异SNP的有效方法。在已经获得桃大量SNP的基础上,该体系可用于桃的基因定位、遗传多样性和品种鉴定等研究。     

Use of high‐density SNP data to identify patterns of diversity and signatures of selection in broiler chickens

The development of broiler chickens over the last 70 years has been accompanied by large phenotypic changes, so that the resulting genomic signatures of selection should be detectable by current statistical techniques with sufficiently dense genetic markers. Using two approaches, this study analysed high‐density SNP data from a broiler chicken line to detect low‐diversity genomic regions characteristic of past selection. Seven regions with zero diversity were identified across the genome. Most of these were very small and did not contain many genes. In addition, fifteen regions were identified with diversity increasing asymptotically from a low level. These regions were larger and thus generally included more genes. Several candidate genes for broiler traits were found within these ‘regression regions’, including IGF1, GPD2 and MTNR1AI. The results suggest that the identification of zero‐diversity regions is too restrictive for characterizing regions under selection, but that regions showing patterns of diversity along the chromosome that are consistent with selective sweeps contain a number of genes that are functional candidates for involvement in broiler development. Many regions identified in this study overlap or are close to regions identified in layer chicken populations, possibly due to their shared precommercialization history or to shared selection pressures between broilers and layers.