CMOS-based cryogenic control of silicon quantum circuits.

The most promising quantum algorithms require quantum processors that host millions of quantum bits when targeting practical applications1. A key challenge towards large-scale quantum computation is the interconnect complexity. In current solid-state qubit implementations, an important interconnect bottleneck appears between the quantum chip in a dilution refrigerator and the room-temperature electronics. Advanced lithography supports the fabrication of both control electronics and qubits in silicon using technology compatible with complementary metal oxide semiconductors (CMOS)2. When the electronics are designed to operate at cryogenic temperatures, they can ultimately be integrated with the qubits on the same die or package, overcoming the 'wiring bottleneck'3-6. Here we report a cryogenic CMOS control chip operating at 3 kelvin, which outputs tailored microwave bursts to drive silicon quantum bits cooled to 20 millikelvin. We first benchmark the control chip and find an electrical performance consistent with qubit operations of 99.99 per cent fidelity, assuming ideal qubits. Next, we use it to coherently control actual qubits encoded in the spin of single electrons confined in silicon quantum dots7-9 and find that the cryogenic control chip achieves the same fidelity as commercial instruments at room temperature. Furthermore, we demonstrate the capabilities of the control chip by programming a number of benchmarking protocols, as well as the Deutsch-Josza algorithm10, on a two-qubit quantum processor. These results open up the way towards a fully integrated, scalable silicon-based quantum computer.

Extinction risk controlled by interaction of long-term and short-term climate change.

Assessing extinction risk from climate drivers is a major goal of conservation science. Few studies, however, include a long-term perspective of climate change. Without explicit integration, such long-term temperature trends and their interactions with short-term climate change may be so dominant that they blur or even reverse the apparent direct relationship between climate change and extinction. Here we evaluate how observed genus-level extinctions of arthropods, bivalves, cnidarians, echinoderms, foraminifera, gastropods, mammals and reptiles in the geological past can be predicted from the interaction of long-term temperature trends with short-term climate change. We compare synergistic palaeoclimate interaction (a short-term change on top of a long-term trend in the same direction) to antagonistic palaeoclimate interaction such as long-term cooling followed by short-term warming. Synergistic palaeoclimate interaction increases extinction risk by up to 40%. The memory of palaeoclimate interaction including the climate history experienced by ancestral lineages can be up to 60 Myr long. The effect size of palaeoclimate interaction is similar to other key factors such as geographic range, abundance or clade membership. Insights arising from this previously unknown driver of extinction risk might attenuate recent predictions of climate-change-induced biodiversity loss.

Molecular Characterization and Event-Specific Real-Time PCR Detection of Two Dissimilar Groups of Genetically Modified Petunia (Petunia x hybrida) Sold on the Market.

Petunia plants with unusual orange flowers were noticed on the European market and confirmed to be genetically modified (GM) by the Finnish authorities in spring 2017. Later in 2017, inspections and controls performed by several official laboratories of national competent authorities in the European Union detected several GM petunia varieties with orange flowers, but also another group of unusually colored flowers. In the latter group, a so far undetected gene coding for a flavonoid 3'5' hydroxylase (F3'5'H) responsible for the purple color was identified by German and Dutch authorities, suggesting that the petunias found on the markets contain different genetic constructs. Here, a strategy is described for the identification of GM petunia varieties. It is based on an initial GMO screening for known elements using (real-time) PCR and subsequent identification of the insertion sites by a gene walking-like approach called ALF (amplification of linearly-enriched fragments) in combination with Sanger and MinION sequencing. The results indicate that the positively identified GM petunias can be traced back to two dissimilar GM events used for breeding of the different varieties. The test results also confirm that the transgenic petunia event RL01-17 used in the first German field trial in 1991 is not the origin of the GM petunias sold on the market. On basis of the obtained sequence data, event-specific real-time PCR confirmatory methods were developed and validated. These methods are applicable for the rapid detection and identification of GM petunias in routine analysis. In addition, a decision support system was developed for revealing the most likely origin of the GM petunia.

Toward on-site food authentication using nanopore sequencing.

•MinION DNA metabarcoding is a promising tool for species identification in food.•MinION and Illumina MiSeq sequencing platforms perform equally accurate.•Species identification with MinION sequencing requires dedicated bioinformatics.

Omics analyses of potato plant materials using an improved one-class classification tool to identify aberrant compositional profiles in risk assessment procedures.

The objective of this study was to quantitatively assess potato omics profiles of new varieties for meaningful differences from analogous profiles of commercial varieties through the SIMCA one-class classification model. Analytical profiles of nine commercial potato varieties, eleven experimental potato varieties, one GM potato variety that had acquired Phytophtora resistance based on a single insert with potato-derived DNA sequences, and its non-GM commercial counterpart were generated. The ten conventional varieties were used to construct the one-class model. Omics profiles from experimental non-GM and GM varieties were assessed using the one-class SIMCA models. No potential unintended effects were identified in the case of the GM variety. The model showed that varieties that were genetically more distant from the commercial varieties were recognized as aberrant, highlighting its potential in determining whether additional evaluation is required for the risk assessment of materials produced from any breeding technique, including genetic modification.

Use of omics analytical methods in the study of genetically modified maize varieties tested in 90 days feeding trials.

Genetically modified (GM) maize and their non-modified counterparts were compared using MON810 varieties, the only GMO event cultivated in Europe. The differences in grain samples were analysed by omics profiles, including transcriptomics, proteomics and metabolomics. Other cultivated maize varieties were analysed as a reference for the variability that will exist between cultivated varieties. The observed differences between modified and non-modified maize varieties do not exceed typical differences between non-modified varieties. The use of these advanced analytical approaches to analyse novel plant materials as compared to the results from animal feeding trials with whole foods is assessed. No indications were observed for changes in the GM varieties that warrant further investigations. Furthermore, it was shown that such indications will be obtained if maize samples of inferior quality are analysed similarly. Omics data provide detailed analytical information of the plant material, which facilitates a risk assessment procedure of new (GM) plant varieties.

Author Correction: ALF: a strategy for identification of unauthorized GMOs in complex mixtures by a GW-NGS method and dedicated bioinformatics analysis.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Case studies on genetically modified organisms (GMOs): Potential risk scenarios and associated health indicators.

Within the frame of the EU-funded MARLON project, background data were reviewed to explore the possibility of measuring health indicators during post-market monitoring for potential effects of feeds, particularly genetically modified (GM) feeds, on livestock animal health, if applicable. Four case studies (CSs) of potential health effects on livestock were framed and the current knowledge of a possible effect of GM feed was reviewed. Concerning allergenicity (CS-1), there are no case-reports of allergic reactions or immunotoxic effects resulting from GM feed consumption as compared with non-GM feed. The likelihood of horizontal gene transfer (HGT; CS-2) of GMO-related DNA to different species is not different from that for other DNA and is unlikely to raise health concerns. Concerning mycotoxins (CS-3), insect-resistant GM maize may reduce fumonisins contamination as a health benefit, yet other Fusarium toxins and aflatoxins show inconclusive results. For nutritionally altered crops (CS-4), the genetic modifications applied lead to compositional changes which require special considerations of their nutritional impacts. No health indicators were thus identified except for possible beneficial impacts of reduced mycotoxins and nutritional enhancement. More generally, veterinary health data should ideally be linked with animal exposure information so as to be able to establish cause-effect relationships.

Exposure of livestock to GM feeds: Detectability and measurement.

This review explores the possibilities to determine livestock consumption of genetically modified (GM) feeds/ingredients including detection of genetically modified organism (GMO)-related DNA or proteins in animal samples, and the documentary system that is in place for GM feeds under EU legislation. The presence and level of GMO-related DNA and proteins can generally be readily measured in feeds, using established analytical methods such as polymerase chain reaction and immuno-assays, respectively. Various technical challenges remain, such as the simultaneous detection of multiple GMOs and the identification of unauthorized GMOs for which incomplete data on the inserted DNA may exist. Given that transfer of specific GMO-related DNA or protein from consumed feed to the animal had seldom been observed, this cannot serve as an indicator of the individual animal's prior exposure to GM feeds. To explore whether common practices, information exchange and the specific GM feed traceability system in the EU would allow to record GM feed consumption, the dairy chain in Catalonia, where GM maize is widely grown, was taken as an example. It was thus found that this system would neither enable determination of an animal's consumption of specific GM crops, nor would it allow for quantitation of the exposure.

Transient left ventricular outflow tract obstruction with systolic anterior motion of the mitral valve: A stunning cause.

Left ventricular outflow tract obstruction (LVOTO) and systolic anterior motion (SAM) of the mitral valve may have various etiologies, of which hypertrophic cardiomyopathy is the most common. More rarely, an acute coronary syndrome, myocardial stunning, and takotsubo cardiomyopathy may give rise to LVOTO and SAM. Here, we present a 70-year-old female patient with a non-ST-elevation acute coronary syndrome treated with percutaneous coronary intervention. Echocardiography the day after, because of dyspnea and hypotension, revealed apical akinesia, LVOTO, and SAM, which proved completely reversible after treatment with a ß-blocker and a 2-month follow-up period. It was concluded that postischemic apical stunning had caused LVOTO and SAM.

Data on screening and identification of genetically modified papaya in food supplements.

This article contains data related to the research article entitled "A case study to determine the geographical origin of unknown GM papaya in routine food sample analysis, followed by identification of papaya events 16-0-1 and 18-2-4" (Prins et al., 2016) [1]. Quantitative real-time PCR (qPCR) with targets that are putatively present in genetically modified (GM) papaya was used as a first screening to narrow down the vast array of candidates. The combination of elements P-nos and nptII was further confirmed by amplification and subsequent sequencing of the P-nos/nptII construct. Next, presence of the candidate GM papayas 16-0-1 and 18-2-4 were investigated by amplification and sequencing of event-spanning regions on the left and right border. This data article reports the Cq values for GM elements, the nucleotide sequence of the P-nos/nptII construct and the presence of GM papaya events 18-2-4 and/or 16-0-1 in five samples that were randomly sampled to be analysed in the framework of the official Dutch GMO monitoring program for food.

A case study to determine the geographical origin of unknown GM papaya in routine food sample analysis, followed by identification of papaya events 16-0-1 and 18-2-4.

During routine monitoring for GMOs in food in the Netherlands, papaya-containing food supplements were found positive for the genetically modified (GM) elements P-35S and T-nos. The goal of this study was to identify the unknown and EU unauthorised GM papaya event(s). A screening strategy was applied using additional GM screening elements including a newly developed PRSV coat protein PCR. The detected PRSV coat protein PCR product was sequenced and the nucleotide sequence showed identity to PRSV YK strains indigenous to China and Taiwan. The GM events 16-0-1 and 18-2-4 could be identified by amplifying and sequencing events-specific sequences. Further analyses showed that both papaya event 16-0-1 and event 18-2-4 were transformed with the same construct. For use in routine analysis, derived TaqMan qPCR methods for events 16-0-1 and 18-2-4 were developed. Event 16-0-1 was detected in all samples tested whereas event 18-2-4 was detected in one sample. This study presents a strategy for combining information from different sources (literature, patent databases) and novel sequence data to identify unknown GM papaya events.

DNA enrichment approaches to identify unauthorized genetically modified organisms (GMOs).

With the increased global production of different genetically modified (GM) plant varieties, chances increase that unauthorized GM organisms (UGMOs) may enter the food chain. At the same time, the detection of UGMOs is a challenging task because of the limited sequence information that will generally be available. PCR-based methods are available to detect and quantify known UGMOs in specific cases. If this approach is not feasible, DNA enrichment of the unknown adjacent sequences of known GMO elements is one way to detect the presence of UGMOs in a food or feed product. These enrichment approaches are also known as chromosome walking or gene walking (GW). In recent years, enrichment approaches have been coupled with next generation sequencing (NGS) analysis and implemented in, amongst others, the medical and microbiological fields. The present review will provide an overview of these approaches and an evaluation of their applicability in the identification of UGMOs in complex food or feed samples.

Tuber proteome comparison of five potato varieties by principal component analysis.

BACKGROUND: Data analysis of omics data should be performed by multivariate analysis such as principal component analysis (PCA). The way data are clustered in PCA is of major importance to develop some classification systems based on multivariate analysis, such as soft independent modeling of class analogy (SIMCA). In a previous study a one-class classifier based on SIMCA was built using microarray data from a set of potatoes. The PCA grouped the transcriptomic data according to varieties. The present work aimed to use PCA to verify the clustering of the proteomic profiles for the same potato varieties. RESULTS: Proteomic profiles of five potato varieties (Biogold, Fontane, Innovator, Lady Rosetta and Maris Piper) were evaluated by two-dimensional gel electrophoresis (2-DE) performed on two immobilized pH gradient (IPG) strip lengths, 13 and 24 cm, both under pH range 4-7. For each strip length, two gels were prepared from each variety; in total there were ten gels per analysis. For 13 cm strips, 199-320 spots were detected per gel, and for 24 cm strips, 365-684 spots. CONCLUSION: All four PCAs performed with these datasets presented clear grouping of samples according to the varieties. The data presented here showed that PCA was applicable for proteomic analysis of potato and was able to separate the samples by varieties. © 2016 Society of Chemical Industry.

Characterization and Transcriptional Profile of Genes Involved in Glycoalkaloid Biosynthesis in New Varieties of Solanum tuberosum L.

Before commercial release, new potato (Solanum tuberosum) varieties must be evaluated for content of toxic compounds such as glycoalkaloids (GAs), which are potent poisons. GA biosynthesis proceeds via the cholesterol pathway to α-chaconine and α-solanine. The goal of this study was to evaluate the relationship between total glycoalkaloid (TGA) content and the expression of GAME, SGT1, and SGT3 genes in potato tubers. TGA content was measured by HPLC-MS, and reverse transcription quantitative polymerase chain reactions were performed to determine the relative expression of GAME, SGT1, and SGT3 genes. We searched for cis-elements of the transcription start site using the PlantPAN database. There was a relationship between TGA content and the relative expression of GAME, SGT1, and SGT3 genes in potato tubers. Putative promoter regions showed the presence of several cis-elements related to biotic and abiotic stresses and light. These findings provide an important step toward understanding TGA regulation and variation in potato tubers.

Selection of reference genes for transcriptional analysis of edible tubers of potato (Solanum tuberosum L.).

Potato (Solanum tuberosum) yield has increased dramatically over the last 50 years and this has been achieved by a combination of improved agronomy and biotechnology efforts. Gene studies are taking place to improve new qualities and develop new cultivars. Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) is a bench-marking analytical tool for gene expression analysis, but its accuracy is highly dependent on a reliable normalization strategy of an invariant reference genes. For this reason, the goal of this work was to select and validate reference genes for transcriptional analysis of edible tubers of potato. To do so, RT-qPCR primers were designed for ten genes with relatively stable expression in potato tubers as observed in RNA-Seq experiments. Primers were designed across exon boundaries to avoid genomic DNA contamination. Differences were observed in the ranking of candidate genes identified by geNorm, NormFinder and BestKeeper algorithms. The ranks determined by geNorm and NormFinder were very similar and for all samples the most stable candidates were C2, exocyst complex component sec3 (SEC3) and ATCUL3/ATCUL3A/CUL3/CUL3A (CUL3A). According to BestKeeper, the importin alpha and ubiquitin-associated/ts-n genes were the most stable. Three genes were selected as reference genes for potato edible tubers in RT-qPCR studies. The first one, called C2, was selected in common by NormFinder and geNorm, the second one is SEC3, selected by NormFinder, and the third one is CUL3A, selected by geNorm. Appropriate reference genes identified in this work will help to improve the accuracy of gene expression quantification analyses by taking into account differences that may be observed in RNA quality or reverse transcription efficiency across the samples.

Safety assessment of plant varieties using transcriptomics profiling and a one-class classifier.

An important part of the current hazard identification of novel plant varieties is comparative targeted analysis of the novel and reference varieties. Comparative analysis will become much more informative with unbiased analytical approaches, e.g. omics profiling. Data analysis estimating the similarity of new varieties to a reference baseline class of known safe varieties would subsequently greatly facilitate hazard identification. Further biological and eventually toxicological analysis would then only be necessary for varieties that fall outside this reference class. For this purpose, a one-class classifier tool was explored to assess and classify transcriptome profiles of potato (Solanum tuberosum) varieties in a model study. Profiles of six different varieties, two locations of growth, two year of harvest and including biological and technical replication were used to build the model. Two scenarios were applied representing evaluation of a 'different' variety and a 'similar' variety. Within the model higher class distances resulted for the 'different' test set compared with the 'similar' test set. The present study may contribute to a more global hazard identification of novel plant varieties.