Increased single-nucleotide discrimination of PCR by primer probes bearing hydrophobic 4'C modifications

We report on significantly increased selectivity of real-time PCR through employment of primer probes that bear hydrophobic 4'C modifications at the 3'-terminal nucleotide. The primer probes were designed to bind the target sequences in such a way that the 3'-terminal nucleotide defines whether a matched or a single mismatched basepair is present depending on the respective target sequence. Several commercially available thermostable DNA polymerases belonging to different DNA polymerase families were tested for their efficacy in discriminating between PCR amplification of matched substrates and duplexes that contain a single mismatch. It turned out that, depending on the 4'C modification and the employed DNA polymerase, significantly increased differentiation between single matches and mismatches could be observed with real-time PCR. The degrees of the observed effects varied with the employed 4'C modification and the sequence context studied. The system is robust enough to work faithfully under several buffer conditions. Our approach should be useful for the direct diagnosis of single nucleotide variations within genes, like single nucleotide polymorphisms or mutations, by PCR without the need for further time- and cost-intensive post-PCR analysis.     

ARTP诱变钝顶螺旋藻突变体比较组学研究

微藻作为地球上重要的生物资源,为水圈提供了大量的初级代谢产物,是合成生物学和生物制造研究和应用的重要底盘微生物。其中,钝顶螺旋藻(Spirulina platensis)具有多糖含量高、营养价值高、培养工艺成熟、应用范围广等特点,其诱变育种及比较组学研究可为微藻细胞工厂系统改造技术发展提供重要依据。本课题组前期通过常压室温等离子体(atmospheric and room temperature plasmas,ARTP)诱变方法获得了三株钝顶螺旋藻突变体。本研究在连续光照培养条件下,对三株突变体的重要生理特征进行了表征,发现突变株具有高絮凝表型,且重要化合物含量也与野生型具有一定的差异。进一步,本研究通过对其主要代谢产物的代谢组学分析和全基因组测序,对突变表型产生的机理进行了初步解析。     

And what would you like for lunch Dr Frankenstein? The food supply chain: past history and future visions

A model of the key drivers influencing the food supply chain is tested by considering the historical and current examples of technologies and used to speculate on the probabilities of success of new technologies. The successful technologies are likely to be those that offer benefits to each element of the supply chain. © 2000 Society of Chemical Industry     

An analysis of the Candida albicans genome database for soluble secreted proteins using computer-based prediction algorithms

We sought to identify all genes in the Candida albicans genome database whose deduced proteins would likely be soluble secreted proteins (the secretome). While certain C. albicans secretory proteins have been studied in detail, more data on the entire secretome is needed. One approach to rapidly predict the functions of an entire proteome is to utilize genomic database information and prediction algorithms. Thus, we used a set of prediction algorithms to computationally define a potential C. albicans secretome. We first assembled a validation set of 47 C. albicans proteins that are known to be secreted and 47 that are known not to be secreted. The presence or absence of an N-terminal signal peptide was correctly predicted by SignalP version 2.0 in 47 of 47 known secreted proteins and in 47 of 47 known non-secreted proteins. When all 6165 C. albicans ORFs from CandidaDB were analysed with SignalP, 495 ORFs were predicted to encode proteins with N-terminal signal peptides. In the set of 495 deduced proteins with N-terminal signal peptides, 350 were predicted to have no transmembrane domains (or a single transmembrane domain at the extreme N-terminus) and 300 of these were predicted not to be GPI-anchored. TargetP was used to eliminate proteins with mitochondrial targeting signals, and the final computationally-predicted C. albicans secretome was estimated to consist of up to 283 ORFs. The C. albicans secretome database is available at http://info.med.yale.edu/intmed/infdis/candida/     

Evidence for Multilevel Chemopreventive Activities of Natural Phenols from Functional Genomic Studies of Curcumin,Resveratrol, Genistein,Quercetin, and Luteolin

Herein, I present an updated and contextualized literature review of functional genomic studies of natural phenols in the context of cancer. I suggest multilevel chemopreventive and anticancer mechanisms of action, which are shared by multiple dietary natural phenols. Specifically, I cite evidence that curcumin and resveratrol have multilevel anti-cancer effects through: (1) inducing either p53-dependent or p53-independent apoptosis in cancer cell lines, (2) acting as potent regulators of expression of oncogenic and anti-oncogenic microRNAs, and (3) inducing complex epigenetic changes that can switch off oncogenes/switch on anti-oncogenes. There is no simple reductionist explanation for anti-cancer effects of curcumin and resveratrol. More generally, multilevel models of chemoprevention are suggested for related natural phenols and flavonoids such as genistein, quercetin, or luteolin.     

A Wild Rice Rhizobacterium Burkholderia cepacia BRDJ Enhances Nitrogen Use Efficiency in Rice

Rice domestication has dramatically improved its agronomic traits, albeit with unavoidable significantly reduced genetic diversity. Dongxiang common wild rice, the wild rice species distributed in northernmost China, exhibits excellent resistance against stress and diseases and provides a rich genetic resource for rice breeding. Most of the studies focus on the function of the plant genes, often disregarding the role of the root microbes associated with the plants. In this work, we isolated a Burkholderia strain from the root of Dongxiang wild rice, which we identified as Burkholderia cepacia BRDJ, based on a phylogenetic analysis. This strain promoted the rice growth under greenhouse conditions. The grain yield was higher in a rice line containing a small genomic fragment derived from the Dongxiang wild rice, compared to the indica rice cultivar Zhongzao 35. This new strain also increased the plant biomass under limiting nitrogen conditions. Interestingly, this strain had a differential effect on indica and japonica rice varieties under full nitrogen supply conditions. By genome sequencing and comparison with another two B. cepacia strains, we observed enriched genes related with nitrogen fixation and phytohormone and volatiles biosynthesis that may account for the growth-promoting effects of the BRDJ. BRDJ has the potential to be used as a biofertilizer in promoting nitrogen use efficiency and overall growth in rice.     

Genome of Laudakia sacra Provides New Insights into High-Altitude Adaptation of Ectotherms

Anan’s rock agama (Laudakia sacra) is a lizard species endemic to the harsh high-altitude environment of the Qinghai–Tibet Plateau, a region characterized by low oxygen tension and high ultraviolet (UV) radiation. To better understand the genetic mechanisms underlying highland adaptation of ectotherms, we assembled a 1.80-Gb L. sacra genome, which contained 284 contigs with an N50 of 20.19 Mb and a BUSCO score of 93.54%. Comparative genomic analysis indicated that mutations in certain genes, including HIF1A, TIE2, and NFAT family members and genes in the respiratory chain, may be common adaptations to hypoxia among high-altitude animals. Compared with lowland reptiles, MLIP showed a convergent mutation in L. sacra and the Tibetan hot-spring snake (Thermophis baileyi), which may affect their hypoxia adaptation. In L. sacra, several genes related to cardiovascular remodeling, erythropoiesis, oxidative phosphorylation, and DNA repair may also be tailored for adaptation to UV radiation and hypoxia. Of note, ERCC6 and MSH2, two genes associated with adaptation to UV radiation in T. baileyi, exhibited L. sacra-specific mutations that may affect peptide function. Thus, this study provides new insights into the potential mechanisms underpinning high-altitude adaptation in ectotherms and reveals certain genetic generalities for animals’ survival on the plateau.     

Effect of reproductive management programs that prioritized artificial insemination at detected estrus or timed artificial insemination on the reproductive performance of primiparous Holstein cows of different genetic merit for fertility

Our objective was to compare reproductive outcomes of primiparous lactating Holstein cows of different genetic merit for fertility submitted for insemination with management programs that prioritized artificial insemination (AI) at detected estrus (AIE) or timed AI (TAI). Moreover, we aimed to determine whether subgroups of cows with different fertility potential would present a distinct response to the reproductive management strategies compared. Lactating primiparous Holstein cows (n = 6 commercial farms) were stratified into high (Hi-Fert), medium (Med-Fert), and low (Lo-Fert) genetic fertility groups (FG) based on a Reproduction Index value calculated from multiple genomic-enhanced predicted transmitting abilities. Within herd and FG, cows were randomly assigned either to a program that prioritized TAI and had an extended voluntary waiting period (P-TAI; n = 1,338) or another that prioritized AIE (P-AIE; n = 1,416) and used TAI for cows, not AIE. Cows in P-TAI received first service by TAI at 84 ± 3 d in milk (DIM) after a Double-Ovsynch protocol, were AIE if detected in estrus after a previous AI, and received TAI after an Ovsynch-56 protocol at 35 ± 3 d after a previous AI if a corpus luteum (CL) was visualized at nonpregnancy diagnosis (NPD) 32 ± 3 d after AI. Cows with no CL visualized at NPD received TAI at 42 ± 3 d after AI after an Ovsynch-56 protocol with progesterone supplementation (P4-Ovsynch). Cows in P-AIE were eligible for AIE after a PGF_2α treatment at 53 ± 3 DIM and after a previous AI. Cows not AIE by 74 ± 3 DIM or by NPD 32 ± 3 d after AI received P4-Ovsynch for TAI at 74 ± 3 DIM or 42 ± 3 d after AI. Binary data were analyzed with logistic regression, count data with Poisson regression, continuous data by ANOVA, and time to event data by Cox's proportional hazard regression. Pregnancy per AI (P/AI) to first service was greater for cows in the Hi-Fert (59.8%) than the Med-Fert (53.6%) and Lo-Fert (47.7%) groups, and for the P-TAI (58.7%) than the P-AIE (48.7%) treatment. Overall, P/AI for all second and subsequent AI combined did not differ by treatment (P-TAI = 45.2%; P-AIE = 44.5%) or FG (Hi-Fert = 46.1%; Med-Fert = 46.0%; Lo-Fert = 42.4%). The hazard of pregnancy after calving was greater for the P-AIE than the P-TAI treatment [hazard ratio (HR) = 1.27, 95% CI: 1.17 to 1.37)], and for the Hi-Fert than the Med-Fert (HR = 1.16, 95% CI: 1.05 to 1.28) and Lo-Fert (HR = 1.34, 95% CI: 1.20 to 1.49) groups. More cows in the Hi-Fert (91.2%) than the Med-Fert (88.4%) and Lo-Fert (85.8%) groups were pregnant at 200 DIM. Within FG, the hazard of pregnancy was greater for the P-AIE than the P-TAI treatment for the Hi-Fert (HR = 1.41, 95% CI: 1.22 to 1.64) and Med-Fert (HR = 1.28, 95% CI: 1.12 to 1.46) groups but not for the Lo-Fert group (HR = 1.13, 95% CI: 0.98 to 1.31). We conclude that primiparous Holstein cows of superior genetic merit for fertility had better reproductive performance than cows of inferior genetic merit for fertility, regardless of the type of reproductive management used. In addition, the effect of programs that prioritized AIE or TAI on reproductive performance for cows of superior or inferior genetic merit for fertility depended on the outcomes evaluated. Thus, programs that prioritize AIE or TAI could be used to affect certain outcomes of reproductive performance or management.     

Decision trees for hierarchical multi-label classification

Hierarchical multi-label classification (HMC) is a variant of classification where instances may belong to multiple classes at the same time and these classes are organized in a hierarchy. This article presents several approaches to the induction of decision trees for HMC, as well as an empirical study of their use in functional genomics. We compare learning a single HMC tree (which makes predictions for all classes together) to two approaches that learn a set of regular classification trees (one for each class). The first approach defines an independent single-label classification task for each class (SC). Obviously, the hierarchy introduces dependencies between the classes. While they are ignored by the first approach, they are exploited by the second approach, named hierarchical single-label classification (HSC). Depending on the application at hand, the hierarchy of classes can be such that each class has at most one parent (tree structure) or such that classes may have multiple parents (DAG structure). The latter case has not been considered before and we show how the HMC and HSC approaches can be modified to support this setting. We compare the three approaches on 24 yeast data sets using as classification schemes MIPS’s FunCat (tree structure) and the Gene Ontology (DAG structure). We show that HMC trees outperform HSC and SC trees along three dimensions: predictive accuracy, model size, and induction time. We conclude that HMC trees should definitely be considered in HMC tasks where interpretable models are desired.