Review of genome sampling methods in sequencing libraries preparation protocols

BackgroundRNA sequencing has become the gold standard for transcriptome analysis but has an inherent limitation of challenging quantification of low-abundant transcripts. In contrast to microarray technology, RNA sequencing reads are proportionally divided in function of transcript abundance. Therefore, low-abundant RNAs compete against highly abundant - and sometimes non-informative - RNA species.ResultsWe developed an easy-to-use strategy based on high-affinity RNA-binding oligonucleotides to block reverse transcription and PCR amplification of specific RNA transcripts, thereby substantially reducing their abundance in the final sequencing library. To demonstrate the broad application potential of our method, we applied it to different transcripts and library preparation strategies, including YRNAs in small RNA sequencing of human blood plasma, mitochondrial rRNAs in both 3′ end sequencing and long-read sequencing, and MALAT1 in single-cell 3′ end sequencing. We demonstrate that the blocking strategy is highly efficient, reproducible, specific, and generally results in better transcriptome coverage and complexity.ConclusionOur method does not require modifications of the library preparation procedure apart from simply adding blocking oligonucleotides to the RT reaction and can thus be easily integrated into virtually any RNA sequencing library preparation protocol.

Compatibility of the ForenSeq™ DNA Signature Prep Kit with laser microdissected cells: An exploration of issues that arise with samples containing low cell numbers

Application of different DNA extraction procedures, library preparation protocols and sequencing platforms: impact on sequencing results

The high cost of library preparation remains a major obstacle to sequencing large numbers of individual genomes. Illumina’s proprietary tagmentation technology allows for rapid and easy preparation of sequencing libraries, but remains prohibitively expensive for many users. Here we propose a modified version of the protocol, which uses Illumina reagents at 1/20th the scale. We show that the scaled-down protocol performs comparably to that of the manufacturer on a non-model insect genome. Surprisingly, the scaled-down protocol also produced 14% fewer PCR duplicates that the full-scale protocol. Since PCR duplicates effectively wasted redundant data, our protocol presented here can help save not just library preparation costs, but sequencing costs as well.

Diagnosis of sepsis and timely identification of pathogens in critically ill patients remains challenging. Plasma metagenomic sequencing to detect microbial cell-free DNA (mDNA) has shown promise, but low abundance of mDNA in plasma limits sensitivity and necessitates high sequencing depth. mDNA is shorter and more fragmented than human cell-free DNA. Here, we evaluated whether combining single-stranded DNA (ssDNA) sequencing library preparation and size selection can enrich mDNA and improve pathogen detection. We prospectively enrolled 48 trauma patients and collected daily blood samples during the first 10 days of intensive care unit (ICU) admission. For patients with culture-proven infections, we extracted plasma DNA, prepared double-stranded DNA (dsDNA) and ssDNA sequencing libraries, and applied size selection to exclude fragments >110 bp. Following sequencing, we performed taxonomic classification, and evaluated differences in mDNA fractions and in sensitivity for pathogen detection (compared to background noise). We analyzed 46 plasma samples from 5 patients who developed culture-proven infections, including 17 samples coincident with positive microbial cultures. Size-selected ssDNA libraries showed the total mDNA fraction 204-fold higher on average than conventional dsDNA libraries (P < 0.0001). However, for pathogen-specific DNA (at the genus level), the highest sensitivity was observed in size-selected dsDNA (82%), compared to dsDNA (41%), ssDNA (71%), and size-selected ssDNA (35%) library preparations. Our results demonstrate that combining ssDNA library preparation together with fragment size selection improves mDNA yield, potentially reducing sequencing requirements. However, at the genus level, this combination also increases background noise, which limits sensitivity for pathogen detection.

Small RNAs (sRNAs) are 20-30 nt long non-coding RNA molecules that regulate essentially all cellular processes. Besides being an intensively studied topic in academic research, sRNAs also hold a promise as clinical biomarkers. While the need for expressional profiling of sRNAs is growing, preparation of sRNA libraries for high-throughput sequencing (HTS) remains technically challenging, due to their small size. The common PAGE-based protocol is time-consuming and inefficient due to material loss, while gel-free protocols generate libraries of insufficient quality. To overcome these shortcomings, we modified the conditions of size-selection by Solid Phase Reversible Immobilization (SPRI) in a way that allows separation of nucleic acids shorter than 100 nt and differing in length by only 20 nt. Implementing the method for preparation of small RNA libraries for HTS resulted in QsRNA-seq, a gel-free, fast and easy-to-perform protocol, amenable to automation, generating very clean libraries that result in high-depth expression data. The protocol also utilizes Unique Molecular Identifiers (UMI) for reduction of library preparation biases and to quantify expression levels. QsRNA-seq provides an excellent solution to the growing needs for small RNA expression profiling for research clinical use.

Current progress in the field of next-generation transcriptome sequencing have contributed significantly to the study of various malignancies including glioblastoma multiforme (GBM). Differential sequencing of transcriptomes of patients and non-tumor controls has a potential to reveal novel transcripts with significant role in GBM. One such candidate group of molecules are long non-coding RNAs (lncRNAs) which have been proved to be involved in processes such as carcinogenesis, epigenetic modifications and resistance to various therapeutic approaches. To maximize the value of transcriptome sequencing, a proper protocol for library preparation from tissue-derived RNA needs to be found which would produce high quality transcriptome sequencing data and increase the number of detected lncRNAs. It is important to mention that success of library preparation is determined by the quality of input RNA, which is in case of real-life tissue specimens very often altered in comparison to high quality RNA commonly used by manufacturers for development of library preparation chemistry. In the present study, we used GBM and non-tumor brain tissue specimens and compared three different commercial library preparation kits, namely NEXTflex Rapid Directional qRNA-Seq Kit (Bioo Scientific), SENSE Total RNA-Seq Library Prep Kit (Lexogen) and NEBNext Ultra II Directional RNA Library Prep Kit for Illumina (NEB). Libraries generated using SENSE kit were characterized by the most normal distribution of normalized average GC content, the least amount of over-represented sequences and the percentage of ribosomal RNA reads (0.3–1.5%) and highest numbers of uniquely mapped reads and reads aligning to coding regions. However, NEBNext kit performed better having relatively low duplication rates, even transcript coverage and the highest number of hits in Ensembl database for every biotype of our interest including lncRNAs. Our results indicate that out of three approaches the NEBNext library preparation kit was most suitable for the study of lncRNAs via transcriptome sequencing. This was further confirmed by highly consistent data reached in an independent validation on an expanded cohort.

Avoiding biases in next generation sequencing (NGS) library preparation is crucial for obtaining reliable sequencing data. Recently, a new library preparation method has been introduced which has eliminated the need for the ligation step. This method, termed SMART (switching mechanism at the 5′ end of the RNA transcript), is based on template switching reverse transcription. To date, there has been no systematic analysis of the additional biases introduced by this method. We analysed the genomic distribution of sequenced reads prepared from genomic DNA using the SMART methodology and found a strong bias toward long (≥12bp) poly dA/dT containing genomic loci. This bias is unique to the SMART-based library preparation and does not appear when libraries are prepared with conventional ligation based methods. Although this bias is obvious only when performing paired end sequencing, it affects single end sequenced samples as well. Our analysis demonstrates that sequenced reads originating from SMART-DNA libraries are heavily skewed toward genomic poly dA/dT tracts. This bias needs to be considered when deciding to use SMART based technology for library preparation.

The reduced representation bisulfite sequencing (RRBS) method has been developed for the high-throughput analysis of DNA methylation based on the sequencing of genomic libraries treated with sodium bisulfite by next-generation approaches. In contrast to whole-genome sequencing, the RRBS approach elaborates specific endonucleases to prepare libraries in order to produce pools of CpG-rich DNA fragments. The original RRBS technology based on the use of the MspI libraries allows one to increase the relative number of CpG islands in the pools of genomic fragments compared to whole-genome bisulfite sequencing. Nevertheless, this technology is rarely used due to the high cost compared with bisulfite methylation analysis with hybridization microarrays and significant residual amount of data represented by the sequences of genomic repeats that complicates the alignment and is not of particular interest for developing DNA methylation markers, which is often the main goal of biomedical research. We have developed an algorithm for estimating the likelihood that recognition sites of restriction endonucleases will be represented in CpG islands and present a method of reducing the effective size of the RRBS library without a significant loss of the CpG islands based on the use of the XmaI endonuclease for library preparation. In silico analysis demonstrates that the optimum range of the XmaI-RRBS fragment lengths is 110-200 base pairs. The sequencing of this library allows one to assess the methylation status of over 125000 CpG dinucleotides, of which over 90000 belong to CpG islands.

e15584 Background: Comprehensive tumor profiling using NGS is fundamentally transforming oncology research. However, converting archival tissue samples into libraries is often challenging due to the low quantity and quality of DNA. Here we present accurate detection of variants in the human exome using the novel chemistry of the xGen Prism DNA library preparation kit, optimized for low-input and degraded samples, with xGen Research Exome v2.0 hybrid-capture enrichment. Methods: The IDT Exome v2 panel was used to carry out targeted sequencing of Prism DNA libraries generated from archival FFPE samples. The unique library preparation is enabled by an engineered mutant ligase and proprietary adapters that prevent chimeras and suppress dimer-formation, thereby maximizing the conversion of input DNA to sequencing libraries. Results: We achieved high yields of library (300-400 ng) from input amounts as low as 25 ng for severely damaged FFPE samples (DIN 1-3), &gt; 90% on-target rates and uniform depth of coverage ( &gt; 96% bases covered at &gt; 20X and &gt; 98% bases covered at &gt; 10X) for FFPE samples across a wide range in quality. We also observed minimal exon drop-outs in difficult-to-target genes for severely damaged FFPE material. To validate the variant calling performance of the Prism-Exome workflow, we used the Horizon OncoSpan FFPE reference control which contains 1-92% AF SNVs and Indels and achieved &gt; 98% sensitivity across ~250 SNVs and Indels. Conclusions: This study demonstrates that the xGen Exome Research v2, when combined with xGen Prism DNA library preparation, provides researchers with a complete human exome FFPE-sequencing solution with robust performance across FFPE samples of varying quality.

High-throughput sequencing (HTS) of antibody repertoire libraries has become a powerful tool in the field of systems immunology. However, numerous sources of bias in HTS workflows may affect the obtained antibody repertoire data. A crucial step in antibody library preparation is the addition of short platform-specific nucleotide adapter sequences. As of yet, the impact of the method of adapter addition on experimental library preparation and the resulting antibody repertoire HTS datasets has not been thoroughly investigated. Therefore, we compared three standard library preparation methods by performing Illumina HTS on antibody variable heavy genes from murine antibody-secreting cells. Clonal overlap and rank statistics demonstrated that the investigated methods produced equivalent HTS datasets. PCR-based methods were experimentally superior to ligation with respect to speed, efficiency, and practicality. Finally, using a two-step PCR based method we established a protocol for antibody repertoire library generation, beginning from inputs as low as 1 ng of total RNA. In summary, this study represents a major advance towards a standardized experimental framework for antibody HTS, thus opening up the potential for systems-based, cross-experiment meta-analyses of antibody repertoires.

Protocol for RNA-seq library preparation from low-volume total RNA by RNA/cDNA hybrid tagmentation

Highly abundant microRNAs (miRNAs) in small RNA sequencing libraries make it difficult to obtain efficient measurements of more lowly expressed species. We present a new method that allows for the selective blocking of specific, abundant miRNAs during preparation of sequencing libraries. This technique is specific with little off-target effects and has no impact on the reproducibility of the measurement of non-targeted species. In human plasma samples, we demonstrate that blocking of highly abundant hsa-miR-16–5p leads to improved detection of lowly expressed miRNAs and more precise measurement of differential expression overall. Furthermore, we establish the ability to target a second abundant miRNA and to multiplex the blocking of two miRNAs simultaneously. For small RNA sequencing, this technique could fill a similar role as do ribosomal or globin removal technologies in messenger RNA sequencing.

Research to date on abiotic stress responses in plants has been largely focused on the plant itself, but current knowledge indicates that microorganisms can interact with and help plants during periods of abiotic stress. In our research, we aim to investigate the interkingdom communication between the plant root and the rhizo-microbiota. Our investigation showed that miRNA plays a pivotal role in this interkingdom communication. Here, we describe a protocol for the analysis of miRNA secreted by the plant root, which includes all of the steps from the isolation of the miRNA to the bioinformatics analysis. Because of their short nucleotide length, Next Generation Sequencing (NGS) library preparation from miRNAs can be challenging due to the presence of dimer adapter contaminants. Therefore, we highlight some strategies we adopt to inhibit the generation of dimer adapters during library preparation. Current screens of miRNA targets mostly focus on the identification of targets present in the same organism expressing the miRNA. Our bioinformatics analysis challenges the barrier of evolutionary divergent organisms to identify candidate sequences of the microbiota targeted by the miRNA of plant roots. This protocol should be of interest to researchers investigating interkingdom RNA-based communication between plants and their associated microorganisms, particularly in the context of holobiont responses to abiotic stresses.

PacBio Sequencing is an effective tool for achieving long read lengths to close gaps in whole genome assemblies. Limited information is available for automated, high-throughput library preparation workflows for PacBio sequencing. This paper describes two high throughput methods, one for producing barcoded genomic DNA libraries and one for barcoded cDNA and subsequent library preparation, as well as pooling and sequencing on the Sequel II instrument. Test sequencing was performed on 380 genomic DNA samples, of which 28 (7.4%) failed sequencing and needed to be repeated. Test sequencing was performed on 384 Threose nucleic acid samples of which 0 failed sequencing and 49 (12.8%) had a genome coverage <90%. These methods were used to generate and report results for ∼2,000 genomic DNA and ∼30,000 cDNA genome sequences from clinical specimens in 2023.