Frontier Company
in Genomic Research

Whole Genome Sequencing 


Whole genome (re)sequencing (WGS) is a method to analyze a specific polymorphism from a species with a known reference genome. It provides the most comprehensive map of an organism’s genetic make-up. The method can discover molecular sarcoma and various genetic polymorphisms (SNPs, insertions, deletions, inversions, complex rearrangements, copy number variation) related to performance and other useful applications. Unlike targeted or exome sequencing, WGS covers all corners of an organism's entire genome, which is arguably the most important molecular data. For bacteria, this approach is highly effective for studying virulence, drug resistance or novel drug targets. Similarly, comparative genomic for eukaryotes through resequencing or de novo assembly is the best approach to obtain high resolution genomic variations.

For whole-genome sequencing, the combination of short inserts and longer reads allow characterization of any genome. For de novo whole-genome sequencing, the unparalleled raw read accuracy of Pacific Bioscience’s next-generation sequencing (NGS) technology provides high quality, long contig assemblies.

Whole Exome Sequencing


Exome Sequencing is a method that selectively analyzes only coding region (Exon), which composes 1-2% of the genome. It is a cheaper and effective way of sequencing compared to whole genome sequencing that analyzes the entire genome. 

The iterative detailing of the data amassed from exome sequencing can be very resourceful for teasing out, with high precision and reliability, single-nucleotide variants and de novo mutations associated with both Mendelian and common diseases. Based on these analysis results, exome sequencing can be effectively used in research for rare disease, cancer genomics, and genetic disorders.



RNA sequencing (RNA-Seq), also called whole transcriptome sequencing (WTS), uses next or third-generation sequencing to reveal the presence and quantity of RNA in a biological sample at a given moment in time.

RNA-Seq is used to analyze the continually changing cellular transcriptome. Specifically, RNA-Seq facilitates the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression over time, or differences in gene expression in different groups or treatments. In addition to mRNA transcripts, RNA-Seq can look at different populations of RNA to include total RNA, small RNA, such as miRNA, tRNA, and ribosomal profiling. RNA-Seq can also be used to determine exon/intron boundaries and verify or amend previously annotated 5′ and 3′ gene boundaries.

Whole Transcriptome Sequencing

Whole transcriptome sequencing is a major advance in the study of gene expression compared to traditional microarray-based approaches in that it provides a comprehensive view of a cellular transcriptional profile at a given biological moment enabling not only qualitative but also quantitative analysis of the transcriptome. 

It also provides information about diverse variations occurring at RNA level of post-transcriptional modifications such as splice variants and isoforms.

Expression Profiling Sequencing

Taken apart the quantitative aspect of whole transcriptome sequencing, expression profiling sequencing gives most comprehensive insight about the transcription level of individual mRNAs which is then further related to the expression level of proteins. 

It is a very cost-effective way of understanding the transcriptions in that it only sequences a small part of mRNA (normally 3’ end with poly (A) tail) and counts the number of sequences. It provides virtually unlimited dynamic range for highly abundant transcripts as well as not missing rare transcripts.

Isoform Sequencing

Empowered by the unique advantage of long reads from PacBio systems, isoform sequencing (Iso-Seq) reveals the splice variants of the transcripts providing the most comprehensive landscape of a transcriptome. The splicing junction of mRNA can be pin-pointed and this can be aligned back to the genome data to show what kind of splice variants are produced, further giving insights about the relation between splicing and a certain phenotype or diseases.

Single-cell RNA Sequencing

Traditional sequencing results are actually the average value from cells of a cluster, but in some very delicate researches we need to understand the nature at single cell level. Single-cell RNA sequencing is designed for this kind of approached.

Small RNA sequencing

Small non-coding RNA, or microRNAs are short, 18-22bp nucleotides which are known to play critical roles in the gene regulation and expression.