The Role of Quality Control in Targeted Next-generation Sequencing Library Preparation

Next-generation sequencing （NGS） is getting routinely used in the diagnosis of hereditary diseases, such as human cardiomyopathies. Hence. it is of utter importance to secure high quality sequencing data, enabling the identification of disease-relevant mutations or the conclusion of negative test results. During the process of sample preparation, each protocol for target enrichment library preparation has its own requirements for quality control （QC）; however, there is little evi- dence on the actual impact of these guidelines on resulting data quality. In this study, we analyzed the impact of QC during the diverse library preparation steps of Agilent SureSelect XT target enrichment and lllumina sequencing. We quantified the parameters for a cohort of around 600 samples, which include starting amount of DNA, amount of sheared DNA, smallest and largest fragment size of the starting DNA; amount of DNA after the pre-PCR, and smallest and largest fragment size of the resulting DNA; as well as the amount of the final library, the corresponding smallest and largest fragment size, and the number of detected variants. Intriguingly, there is a high tolerance for variations in all QC steps, meaning that within the boundaries proposed in the current study, a considerable variance at each step of QC can be well tolerated without compromising NGS quality.

Evaluation of an automated spike-and-wave complex detection algorithm in the EEG from a rat model of absence epilepsy

The aim of this prospective blinded study was to evaluate an automated algorithm for spike-andwave discharge（SWD） detection applied to EEGs from genetic absence epilepsy rats from Strasbourg（GAERS）.Five GAERS underwent four sessions of 20-min EEG recording.Each EEG was manually analyzed for SWDs longer than one second by two investigators and automatically using an algorithm developed in MATLAB（？）.The sensitivity,specificity,positive predictive value（PPV）,and negative predictive value（NPV） were calculated for the manual（reference） versus the automatic（test） methods.The results showed that the algorithm had specificity,sensitivity,PPV and NPV 〉94%,comparable to published methods that are based on analyzing EEG changes in the frequency domain.This provides a good alternative as a method designed to mimic human manual marking in the time domain.

Personalized Computer Simulation of Diastolic Function in Heart Failure

The search for a parameter representing left ventricular relaxation from non-invasive and invasive diagnostic tools has been extensive, since heart failure （HF） with preserved ejection fraction （HF-pEF） is a global health problem. We explore here the feasibility using patient-specific cardiac computer modeling to capture diastolic parameters in patients suffering from different degrees of systolic HF. Fifty eight patients with idiopathic dilated cardiomyopathy have undergone thorough clinical evaluation, including cardiac magnetic resonance imaging （MRI）, heart catheterization, echocardiography, and cardiac biomarker assessment. A previously-introduced framework for creating multi-scale patient-specific cardiac models has been applied on all these patients. Novel parameters, such as global stiffness factor and maximum left ventricular active stress, representing cardiac active and passive tissue properties have been computed for all patients. Invasive pressure measurements from heart catheterization were then used to evaluate ventricular relaxation using the time constant of isovolumic relaxation Tau （τ）. Parameters from heart catheterization and the multi-scale model have been evaluated and compared to patient clinical presentation. The model parameter global stiffness factor, representing diastolic passive tissue properties, is correlated significantly across the patient population with τ. This study shows that multi-modal cardiac models can successfully capture diastolic （dys） function, a prerequisite for future clinical trials on HF-pEF.

SLM2 Is A Novel Cardiac Splicing Factor Involved in Heart Failure due to Dilated Cardiomyopathy

Alternative mRNA splicing is a fundamental process to increase the versatility of the genome.In humans,cardiac mRNA splicing is involved in the pathophysiology of heart failure.Mutations in the splicing factor RNA binding motif protein 20(RBM20) cause severe forms of cardiomyopathy.To identify novel cardiomyopathy-associated splicing factors,RNA-seq and tissue-enrichment analyses were performed,which identified up-regulated expression of Sam68-Like mammalian protein 2(SLM2) in the left ventricle of dilated cardiomyopathy(DCM) patients.In the human heart,SLM2 binds to important transcripts of sarcomere constituents,such as those encoding myosin light chain2(MYL2),troponin 13(TNNI3),troponin T2(TNNT2),tropomyosin 1/2(TPM1/2),and titin(TTN).Mechanistically,SLM2 mediates intron retention,prevents exon exclusion,and thereby mediates alternative splicing of the mRNA regions encoding the variable proline-,glutamate-,valine-,and lysine-rich(PEVK) domain and another part of the I-band region of titin.In summary,SLM2 is a novel cardiac splicing regulator with essential functions for maintaining cardiomyocyte integrity by binding to and processing the mRNAs of essential cardiac constituents such as titin.