Gene synthesis from commercial vendors is typically conducted by using overlap extension PCR from oligos manufactured on microarrays. Here we apply Data-Optimized Assembly Design of Golden-Gate overhangs to rapidly construct genes from oligo pools in three steps and as a result create a workflow that can be employed in any standard molecular biology lab.
This poster describes a novel, ligation-based small RNA library preparation method that is characterized by reduced bias in addition to increased detection of sncRNAs. Libraries can be made in ~3.5 hours using a streamlined protocol with bead-based size-selections and cleanups. The robustness of this method is demonstrated with its compatibility across a broad input range (0.5 ng – 1,000 ng of Total RNA), as well as with challenging sample types, such as formalin-fixed paraffin-embedded (FFPE) RNA. The NEBNext Low-bias Small RNA Library Prep Kit sets a new standard for seeing small RNAs clearly.
Discover pivotal moments in DNA cloning history, showcasing innovations that shaped modern biotechnology.
We present a High Complexity Golden Gate Assembly (HC-GGA) for engineering Pseudomonas phage ɸKMV. The system divides the phage genome into small, cloneable synthetic fragments, which are assembled in a one-pot reaction to generate the complete genome. Through modification of plasmid parts, the system enables efficient and precise genome editing including point mutations, insertions, deletions, and domain swaps.
We developed High Complexity Golden Gate Assemblies (HC-GGA) for engineering three mycobacteriophages. The phage genomes are divided into 1.7 - 5.0kb which can be carried in plasmids. The fragments can then be assembled in a one-pot reaction to generate the complete phage genomes. Through modification of plasmid parts, the system enables efficient and precise genome editing of multiple locations in the genome simultaneously, including point mutations, insertions, deletions, and domain swaps.
RSV, a single-stranded RNA virus, is the leading cause of respiratory illness in infants. Using multiplex targeted amplification sequencing techniques, the presence of RSV in the population can be monitored for mutations that negatively impact treatment efficacy. Here, we describe a newly developed RSV sequencing approach based on amplicon-targeted sequencing for Illumina or Oxford Nanopore Technologies platforms, and featuring the NEBNext RSV Primer Module.
Formalin-fixed, paraffin-embedded samples are a challenging sample type for most NGS library prep methods. We developed a novel method, compatible with both high and low quality FFPE DNA samples, employing three new enzyme mixes, designed specifically for compatibility with FFPE samples. The NEBNext UltraShear FFPE DNA Library Prep Kit includes an enzymatic fragmentation step that improves the library yield, library metrics, and variant calling accuracy.
With the goal of streamlining the processing of a variety of samples of various input amounts, the NEBNext UltraExpress® library prep kits respond to a user-stated need for faster, more efficient, and easily automated workflows. One key optimization is the single-condition workflow, which enables the simultaneous processing of multiple different sample input amounts (within the kit’s stated input range) with a single adaptor concentration and a single recommendation for PCR cycles. These advances have resulted in a single-tube solution, incorporating master-mixed reagents, reduced incubation times, fewer clean-up steps, and the generation of less plastic waste.
DNA methylation is an epigenetic regulator of gene expression with important functions in development and diseases, such as cancer. Typically, the modified cytosines, 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC), are detected by sequencing Illumina libraries generated using a gentle, enzyme-based workflow called NEBNext® EM-seq, or by the harsher bisulfite conversion. Here, we describe an enzymatic method that enables specific detection of 5hmC, using the NEBNext Enzymatic 5hmC-seq (E5hmC-seq) Kit.
NEBNext Enzymatic Methyl-seq (EM-seq) workflows involve base conversion, which can be a challenge for variant detection. In EM-seq, this challenge is overcome using bioinformatic tools. Because methylation information is only preserved on a single strand in EM-seq libraries, the other strand can be used to detect genetic variation. Using this method, we can call germline SNPs with high precision.
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