Comparison of SureSelect and Nextera Exome Capture Performance in Single-Cell Sequencing.

BACKGROUND: Advances in single-cell sequencing provide unprecedented opportunities for clinical examination of circulating tumor cells, cancer stem cells, and other rare cells responsible for disease progression and drug resistance. On the genomic level, single-cell whole exome sequencing (scWES) started to gain popularity with its unique potentials in characterizing mutational landscapes at a single-cell level. Currently, there is little known about the performance of different exome capture kits in scWES. Nextera rapid capture (NXT; Illumina, Inc.) has been the only exome capture kit recommended for scWES by Fluidigm C1, a widely accessed system in single-cell preparation. RESULTS: In this study, we compared the performance of NXT following Fluidigm's protocol with Agilent SureSelectXT Target Enrichment System (AGL), another exome capture kit widely used for bulk sequencing. We created DNA libraries of 192 single cells isolated from spheres grown from a melanoma specimen using Fluidigm C1. Twelve high-yield cells were selected to perform dual-exome capture and sequencing using AGL and NXT in parallel. After mapping and coverage analysis, AGL outperformed NXT in coverage uniformity, mapping rates of reads, exome capture rates, and low PCR duplicate rates. For germline variant calling, AGL achieved better performance in overlap with known variants in dbSNP and transition-transversion ratios. Using calls from high coverage bulk sequencing from blood DNA as the golden standard, AGL-based scWES demonstrated high positive predictive values, and medium to high sensitivity. Lastly, we evaluated somatic mutation calling by comparing single-cell data with the matched blood sequence as control. On average, 300 mutations were identified in each cell. In 10 of 12 cells, higher numbers of mutations were identified using AGL than NXT, probably caused by coverage depth. When mutations are adequately covered in both AGL and NXT data, the two methods showed very high concordance (93-100% per cell). CONCLUSIONS: Our results suggest that AGL can also be used for scWES when there is sufficient DNA, and it yields better data quality than the current Fluidigm's protocol using NXT.

Draft genome sequence of Bacillus velezensis strains AOA1 and AKS2, the potential plant growth-promoting rhizobacteria.

This report describes the draft genome sequence of Bacillus velezensis strains AOA1 and AKS2 isolated from maize rhizosphere soil in South Africa. Bacillus velezensis plays important biological roles as plant growth promoting rhizobacterium (PGPR). Bacillus velezensis strains also exhibit numerous biotechnological application potentials in agriculture and diverse industrial settings.

Single-Cell Genomics of Microbial Dark Matter.

Single-cell genomics allows bypassing the culturing step and to directly access environmental microbes one cell at a time. The method has been successfully applied to explore archaeal and bacterial candidate phyla, referred to as microbial dark matter. Here I summarize the single-cell genomics workflow, including sample preparation and preservation, high-throughput fluorescence-activated cell sorting, cell lysis and amplification of environmental samples. Furthermore I describe phylogenetic screening based on 16S rRNA genes and suggest a suitable library preparation and sequencing approach.

Impact of three Illumina library construction methods on GC bias and HLA genotype calling.

Next-generation sequencing (NGS) is increasingly recognized for its ability to overcome allele ambiguity and deliver high-resolution typing in the HLA system. Using this technology, non-uniform read distribution can impede the reliability of variant detection, which renders high-confidence genotype calling particularly difficult to achieve in the polymorphic HLA complex. Recently, library construction has been implicated as the dominant factor in instigating coverage bias. To study the impact of this phenomenon on HLA genotyping, we performed long-range PCR on 12 samples to amplify HLA-A, -B, -C, -DRB1, and -DQB1, and compared the relative contribution of three Illumina library construction methods (TruSeq Nano, Nextera, Nextera XT) in generating downstream bias. Here, we show high GC% to be a good predictor of low sequencing depth. Compared to standard TruSeq Nano, GC bias was more prominent in transposase-based protocols, particularly Nextera XT, likely through a combination of transposase insertion bias being coupled with a high number of PCR enrichment cycles. Importantly, our findings demonstrate non-uniform read depth can have a direct and negative impact on the robustness of HLA genotyping, which has clinical implications for users when choosing a library construction strategy that aims to balance cost and throughput with data quality.