De novo mutations (DNMs) in protein-coding genes are a well-established cause of developmental disorders (DD). However, known DD-associated genes only account for a minority of the observed excess of such DNMs. To identify novel DD-associated genes, we integrated healthcare and research exome sequences on 31,058 DD parent-offspring trios, and developed a simulation-based statistical test to identify gene-specific enrichments of DNMs. We identified 285 significantly DD-associated genes, including 28 not previously robustly associated with DDs. Despite detecting more DD-associated genes than in any previous study, much of the excess of DNMs of protein-coding genes remains unaccounted for. Modelling suggests that over 1,000 novel DD-associated genes await discovery, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of dominant DDs.

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Over 130 X-linked genes have been robustly associated with developmental disorders, and X-linked causes have been hypothesised to underlie the higher developmental disorder rates in males. Here, we evaluate the burden of X-linked coding variation in 11,044 developmental disorder patients, and find a similar rate of X-linked causes in males and females (6.0% and 6.9%, respectively), indicating that such variants do not account for the 1.4-fold male bias. We develop an improved strategy to detect X-linked developmental disorders and identify 23 significant genes, all of which were previously known, consistent with our inference that the vast majority of the X-linked burden is in known developmental disorder-associated genes. Importantly, we estimate that, in male probands, only 13% of inherited rare missense variants in known developmental disorder-associated genes are likely to be pathogenic. Our results demonstrate that statistical analysis of large datasets can refine our understanding of modes of inheritance for individual X-linked disorders.

Two analytical methodologies for the simultaneous analysis of eight sulfonamide antibiotics in animal feeds were developed. Analytes were extracted in a simple and rapid procedure by manual shaking with an ethyl acetate/ultrapure water mixture (99:1, v/v) without further sample cleanup. Mean recoveries ranging from 72.7% to 99.4% with relative standard deviations below 9% were achieved from spiked animal feed samples. Determination was carried out by high-performance liquid chromatography using fluorometric detection with precolumn derivatization. The separation of the derivatized compounds was performed using two different chromatographic columns: a conventional C(18) column and a recently available core-shell particle Kinetex C(18) column. Both methods were validated in-house in six different feed matrices, and the two approaches were compared. The experiments showed that the method using the Kinetex column was superior with regard to speed of analysis and precision, both under repeatability and intermediate reproducibility conditions. The limits of detection and quantification were also greatly improved, below 0.10 and 0.34 μg/g, respectively. Finally, this novel approach was successfully applied to the analysis of real feed samples.

A rapid multiclass method that covers 50 antimicrobials from 13 different families in animal feeds was developed. Samples were extracted using a mixture of methanol, acetonitrile and a McIlvaine buffer combined with sonication. Feed extracts were simply diluted prior to injection, since the clean-up strategies that were tested, based on either solid-phase extraction or dispersive solid-phase extraction, were ineffective at minimizing matrix-related signal suppression/enhancement. Analysis was carried out by liquid chromatography coupled to tandem mass spectrometry using an electrospray ionization source operating in positive and negative modes. For the quantification, matrix-fortified standard calibration curves were used to compensate for matrix effects and losses in sample preparation. The method was validated in-house in pig, poultry and cattle feed matrices and showed satisfactory performance characteristics. Thus, the proposed approach was suitable for application in a routine high-throughput laboratory for the official control of feeds.