Apollo library prep system overview

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System Overview

Apollo library prep system overview

Unrivaled results with simplified, automated NGS library preparation

Next-generation sequencing (NGS) applications like DNA-seq, RNA-seq, and ChIP-seq enable researchers to delve deeper into the human genome. Although NGS applications allow diverse and detailed analyses, NGS library preparation is encumbered by extensive hands-on and labor-intensive workflows. To address this, the Apollo system provides a complete, walkaway solution with validated protocols and optimized chemistries to produce consistent libraries for DNA-seq, RNA-seq, and ChIP-seq applications.

Convenient library prep—reduce hands-on time with walkaway automation
Flexible throughput—run any batch size up to 96 samples per run
Optimized inputs—conserve precious samples
Reliable results—increase reproducibility and minimize contamination with a completely enclosed, automated system

Flexible, streamlined workflow Optimized input amounts Maximize yield and consistency Minimize waste Product citations

Flexible, streamlined workflow

The Apollo system offers exceptional performance and flexibility. Manual NGS library prep workflows are labor-intensive, occupying researchers for long periods of hands-on time. The Apollo system frees researchers from manual steps by automating the critical portions of the workflow, reducing hands-on time to just 30 minutes, depending on the sample throughput and script used. Automated NGS library prep on the Apollo system allows researchers to perform other experimental or analysis tasks during NGS library preparation.

Flexibility on the Apollo system enables researchers to easily adapt to variable sample throughput needs without wasting reagents. In addition to both DNA- and RNA-seq library prep protocols, this versatile system efficiently performs related protocols for sample preparation and cleanup, such as poly A+ RNA enrichment, rRNA depletion, and PCR cleanup.

Optimized input amounts

Sample input amount and quality are important considerations for any sequencing application. Committing too much of your sample to a workflow or getting a low yield means wasted material, delayed experiments, poor results, or insufficient sequencing material. PrepX kits and related scripts resolve these issues by generating comparable, high-quality NGS libraries regardless of input concentrations within a defined range (Tables I and II).

Input amount	10 ng	100 ng
Adapter reads (%)	0	0
Confidently mapped reads (%)	96.61	96.43
Repetitive reads (%)	1.84	1.80
Low-quality reads (%)	0	0.

Table I. Reliable sequencing coverage and performance. High-quality libraries were prepared using the PrepX DNA library prep kit on the Apollo system from either 10 ng or 100 ng of E. coli genomic DNA. Libraries were sequenced on the Illumina MiSeq® platform (2 x 150 bp).

PrepX kits provide every reagent necessary for library prep in prealiquoted, color-coded, single-use reagent strips. Each PrepX chemistry is compatible with a script with variable throughputs and minimum input requirements, as summarized below.

Cat. #	Apollo reagent kit	Compatible script	Script throughput	Minimum input amount per sample
640101	PrepX Complete ILMN DNA Library Kit, 24 Samples	PrepX ILM 8	1–8	1 ng DNA
640102	PrepX Complete ILMN 32i DNA Library Kit, 96 Samples	PrepX ILM 32i	4–32	1 ng DNA
640096	PrepX RNA-Seq for Illumina Library Kit, 24 Samples	PrepX mRNA 8	1–8	100 pg poly A-enriched RNA; 2 ng rRNA-depleted mRNA
640097	PrepX RNA-Seq for Illumina Library Kit, 48 Samples	PrepX mRNA 48	6–48	100 pg poly A-enriched RNA; 2 ng rRNA-depleted mRNA
640098	PrepX PolyA mRNA Isolation Kit, 96 Samples	PrepX PolyA 8 or PrepX PolyA 48	1–8 or 6–48	100 ng total RNA

*Product availability varies by region.

Table II. Input amounts required for various combinations of PrepX kits and preprogrammed Apollo scripts.

Maximize yield and consistency

Manual NGS library preparation is time-consuming and subject to human error, affecting the quality of your data. Consistency is key when processing multiple samples, and the Apollo system, combined with PrepX chemistries and scripts, allows you to create consistent libraries without variation caused by manual pipetting. Comparison of manual and automated poly A+ RNA enrichment on the Apollo system demonstrates that automation delivers higher poly A+ RNA yield and diversity as compared to the manual method (Figure 1).

Poly A+ RNA enrichment on the Apollo system produces better quality and yield as compared to manual poly A+ RNA enrichment.

PrepX chemistries have been validated to be a seamless solution for consistent sample preparation, cleanup, and NGS library prep (Figure 2). Many of these protocols employ in-tip bead separation for efficient capture of libraries in a highly reproducible manner. Learn more about in-tip bead separation on our application page.

Figure 2. Consistent library size with a PrepX DNA library kit

Minimize waste

Most PrepX reagents are aliquoted into disposable strips for single use in a variety of sample configurations, eliminating pipetting error and excess waste. To make our validated protocols faster, easier, and error-free, the reagents are color-coded and accommodate a variety of sample throughputs.

Product citations

Wertz, M.H. et al. Cell-type-specific miR-431 dysregulation in a motor neuron model of spinal muscular atrophy. Human Molecular Genetics. 25(11):2168–2181 (2016).

Crocker, A. et al. Cell-Type-Specific Transcriptome Analysis in the Drosophila Mushroom Body Reveals Memory-Related Changes in Gene Expression. Cell Reports. 15(7):1580–1596 (2016).

Ellison, D.W. et. al. Complete genome sequences of Zika virus strains isolated from the blood of patients in Thailand in 2014 and the Philippines in 2012. Genome Announcements. 4(3):e00359-16 (2016).

Sanders, H. et al. Mutation Yield of a 34-Gene Solid Tumor Panel in Community-Based Tumor Samples. Molecular Diagnosis & Therapy. 20(3):241–253 (2016).

Denk, F. et al. Persistent Alterations in Microglial Enhancers in a Model of Chronic Pain. Cell Reports. 15(8):1771–1781 (2016).

Muñoz-Gutiérrez, J.F. et al. Transcriptomic Determinants of Scrapie Prion Propagation in Cultured Ovine Microglia. PLoS One. 11(1):e0147727 (2016).

Sherman, K.E. et al. Viral dynamic modeling of Hepatitis C and resistance-associated variants in haemophiliacs. Haemophilia. 22(4):543–548 (2016).

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