System analysis of the sequencing quality of human whole exome samples on BGI NGS platform

Human exome sequencing is a classical method used in most medical genetic applications. The leaders in the field are the manufacturers of enrichment kits based on hybridization of cRNA or cDNA biotinylated probes specific for a genomic region of interest. Recently, the platforms manufactured by the Chinese company MGI Tech have become widespread in Europe and Asia. The reliability and quality of the obtained data are already beyond any doubt. However, only a few kits compatible with these sequencers can be used for such specific tasks as exome sequencing. We developed our own solution for library pre-capture pooling and exome enrichment with Agilent probes. In this work, using a set of the standard benchmark samples from the Platinum Genome collection, we demonstrate that the qualitative and quantitative parameters of our protocol which we called “RSMU_exome” exceed those of the MGI Tech kit. Our protocol allows for identifying more SNV and indels, generates fewer PCR duplicates, enables pooling of more samples in a single enrichment procedure, and requires less raw data to obtain results comparable with the MGI Tech's protocol. The cost of our protocol is also lower than that of MGI Tech's solution.

Modified NEBNext® VarSkip Short SARS-CoV-2 Library Prep Kit for Illumina Platforms - adapted for wastewater samples v1

PURPOSE: This method was developed at the FDA’s Center for Food Safety and Applied Nutrition for GenomeTrakr’s pandemic response project, monitoring SARS-CoV-2 variants in wastewater. Protocols developed for this project cover wastewater collection, concentration, RNA extraction, RT-qPCR, library prep, genome sequencing, quality control checks, and data submission to NCBI. This modified protocol details methods for cDNA synthesis and library preparation for sequencing of wastewater samples containing SARS-CoV-2. The protocol is based primarily on the NEBNext® ARTIC SARS-CoV-2 Library Prep Kit (Illumina®), NEB #E7650S/L 24/96 reactions, with a few modifications. Primarily, VarSkip Short primers are used in place of the ARTIC V3 primers. These primers are available in the NEBNext®ARTIC SARS-CoV-2 FS Library Prep Kit (Illumina®); however, for optimal variant detection from wastewater, sequenced fragments should be as large as possible, so we discourage fragmentation prior to end prep. There are a couple of decision points in this protocol. Examining cDNA amplicon samples on an Agilent TapeStation system or similar fragment analyzer is extremely helpful in making these decisions.

NCBI submission protocol for SARS-CoV-2 wastewater data: SRA, BioSample, and BioProject v2

PURPOSE: This method was developed at the FDA’s Center for Food Safety and Applied Nutrition for GenomeTrakr’s pandemic response project, monitoring SARS-CoV-2 variants in wastewater; however, this protocol was written to be broadly applicable for all wastewater sequence data submissions to NCBI. Protocols developed for this project cover wastewater collection, concentration, RNA extraction, RT-qPCR, library prep, genome sequencing, quality control checks, and data submission to NCBI. This protocol covers the last step of making your data public at NCBI. Specifically, it provides the steps to establish a new NCBI submission environment for your laboratory, including the creation of new BioProject(s) and submission groups. Once these are step up, the protocol then walks through the process for submitting raw reads to SRA and sample metadata to BioSample through the Submission portal. For new submitters, there's quite a bit of groundwork that needs to be established before a laboratory can start its first data submission. We recommend that one person in the laboratory take a few days to get everything set up in advance of when you expect to do your first data submission. If you need a pipeline for frequent or large volume submissions, follow Step 1 in this protocol to get your NCBI submission environment established, then contact [email protected] to set up an account for submitting through the API. Version updates: V2: minor edits to the BioSample and SRA templates V3: Many minor edits were made to make the protocol more broadly applicable to submitters outside of FDA's wastewater project. Updates were also made to both metadata templates, including a new attribute to the SRA metadata template, called "enrichment_kit". There are now three custom attributes we recommend populating to more specifically capture relevant methods for ww sequencing: enrichment approach, primer set, and library prep kit.

NCBI submission protocol for SARS-CoV-2 wastewater data: SRA, BioSample, and BioProject v2

PURPOSE: This method was developed at the FDA’s Center for Food Safety and Applied Nutrition for GenomeTrakr’s pandemic response project, monitoring SARS-CoV-2 variants in wastewater​​. Protocols developed for this project cover wastewater collection, concentration, RNA extraction, RT-qPCR, library prep, genome sequencing, quality control checks, and data submission to NCBI. This protocol covers the last step of making your data public at NCBI. Specifically, it provides the steps to establish a new NCBI submission environment for your laboratory, including the creation of new BioProject(s) and submission groups. Once these are step up, the protocol then walks through the process for submitting raw reads to SRA and sample metadata to BioSample through the Submission portal. For new submitters, there's quite a bit of groundwork that needs to be established before a laboratory can start its first data submission. We recommend that one person in the laboratory take a few days to get everything set up in advance of when you expect to do your first data submission. If you need a pipeline for frequent or large volume submissions, follow Step 1 in this protocol to get your NCBI submission environment established, then contact [email protected] to set up an account for submitting through the API. Version updates: V2: minor edits to the BioSample and SRA templates

Direct genome-wide identification of G-quadruplex structures by whole-genome resequencing

We present a user-friendly and transferable genome-wide DNA G-quadruplex (G4) profiling method that identifies G4 structures from ordinary whole-genome resequencing data by seizing the slight fluctuation of sequencing quality. In the human genome, 736,689 G4 structures were identified, of which 45.9% of all predicted canonical G4-forming sequences were characterized. Over 89% of the detected canonical G4s were also identified by combining polymerase stop assays with next-generation sequencing. Testing using public datasets of 6 species demonstrated that the present method is widely applicable. The detection rates of predicted canonical quadruplexes ranged from 32% to 58%. Because single nucleotide variations (SNVs) influence the formation of G4 structures and have individual differences, the given method is available to identify and characterize G4s genome-wide for specific individuals.

Discordance of PIK3CA and TP53 Mutations Between Breast Cancer Brain Metastases and Matched Primary Tumors

Purpose: There is limited knowledge of the biology of breast cancer (BC) brain metastasis (BM). We primarily aimed to determine the mutations in BCBM and to compare the mutational pattern with the matched primary breast cancer (BC). Secondary aims were to determine mutations in each subgroup (Luminal, HER2+ and TNBC) of BCBM and to determine survival according to specific mutations. Patients and methods: We investigated 57 BCBMs, including 46 cases with matched primary tumors (PT) by targeted Next Generation Sequencing (NGS) using the Cancer Hotspot Panel v2 (ThermoFisher Scientific) covering 207 targeted regions in 50 cancer related genes. Subtype according to immunohistochemistry was re-evaluated. Results: NGS results fulfilling sequencing quality criteria were obtained from 52 BM and 41 PT, out of which 37 were matched pairs. Pathogenic mutations were detected in 66% of PTs (27/41), and 62% of BMs (32/52). TP53 mutations were most frequent; 49% (20/41) of PTs and 48% (25/52) in BMs, followed by PIK3CA mutations; 22% (9/42) in PTs and 25% (13/52) in BMs. Mutations in CDH1, EGFR, HRAS, RB1 CDKN2A and PTEN were detected in single pairs or single samples. Mutational pattern was discordant in 24% of matched pairs. Conclusions: We show a discordance of PIK3CA and TP53 mutations of roughly 25% indicating the need to develop methods to assess mutational status in brain metastasis where analysis of cell-free DNA from cerebrospinal fluid (CSF) has shown promising results.

qc3C: Reference-free quality control for Hi-C sequencing data

Hi-C is a sample preparation method that enables high-throughput sequencing to capture genome-wide spatial interactions between DNA molecules. The technique has been successfully applied to solve challenging problems such as 3D structural analysis of chromatin, scaffolding of large genome assemblies and more recently the accurate resolution of metagenome-assembled genomes (MAGs). Despite continued refinements, however, preparing a Hi-C library remains a complex laboratory protocol. To avoid costly failures and maximise the odds of successful outcomes, diligent quality management is recommended. Current wet-lab methods provide only a crude assay of Hi-C library quality, while key post-sequencing quality indicators used have—thus far—relied upon reference-based read-mapping. When a reference is accessible, this reliance introduces a concern for quality, where an incomplete or inexact reference skews the resulting quality indicators. We propose a new, reference-free approach that infers the total fraction of read-pairs that are a product of proximity ligation. This quantification of Hi-C library quality requires only a modest amount of sequencing data and is independent of other application-specific criteria. The algorithm builds upon the observation that proximity ligation events are likely to create k-mers that would not naturally occur in the sample. Our software tool (qc3C) is to our knowledge the first to implement a reference-free Hi-C QC tool, and also provides reference-based QC, enabling Hi-C to be more easily applied to non-model organisms and environmental samples. We characterise the accuracy of the new algorithm on simulated and real datasets and compare it to reference-based methods.

RT-qPCR Detection of SARS-CoV-2 from Wastewater Using the AB 7500 v1

This method was developed at the FDA’s Center for Food Safety and Applied Nutrition for GenomeTrakr’s pandemic response project, monitoring SARS-CoV-2 variants in wastewater​​. Protocols developed for this project cover wastewater collection, concentration, RNA extraction, RT-qPCR detection, library prep, genome sequencing, quality control checks, and data submission to NCBI. This protocol describes triplex and duplex assays for the RT-qPCR detection of the nucleocapsid region of the SARS-CoV-2 genome. These assays, along with the murine norovirus (MNV; extraction control) and crAssphage (human indicator) RT-qPCR assay (RT-qPCR Detection of Process Controls (Murine noroviurs and crAssphage) from Wastewater (protocols.io)), were developed for use on the AB 7500 platform using software version 2.0 or 2.3. All assays incorporate an internal amplification control (IC) to prevent the reporting of false negatives due to inhibition or failure of the RT-qPCR. These multiplexed detection assays were developed for the qualitative determination SARS-CoV-2 nucleocapsid gene extracted from wastewater. Valid sample results are contingent upon the detection of the MNV extraction control from the sample being tested.

RT-qPCR Detection of Process Controls (Murine noroviurs and crAssphage) from Wastewater using AB 7500 v1

This method was developed at the FDA’s Center for Food Safety and Applied Nutrition for GenomeTrakr’s pandemic response project, monitoring SARS-CoV-2 variants in wastewater​​. Protocols developed for this project cover wastewater collection, concentration, RNA extraction, RT-qPCR detection, library prep, genome sequencing, quality control checks, and data submission to NCBI. This protocol describes the murine norovirus (MNV; extraction control) and crAssphage (human indicator) RT-qPCR assay developed for use on the AB 7500 platform using software version 2.0 or 2.3. The assay incorporates an internal amplification control (IC) to prevent the reporting of false negatives due to inhibition or failure of the RT-qPCR. This multiplexed detection assay was developed for the determination crAssphage extracted from wastewater, as an endogenous control, and MNV as an extraction control. The assay is designed to be used in conjunction with the SARS-CoV-2 RT-qPCR detection assay. Valid sample results for SARS-CoV-2 detection are contingent upon the detection of the MNV extraction control from the sample being tested.