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Researchers like Fei Chen and Jason Buenrostro are creating tools that allow them to examine how genes function inside cells, uncovering any influences that cause diseases. Their discoveries could transform genomics from an obscure area of biology into the cornerstone of healthcare provision.<\/p>\n
Pharmacogenomics is already doing this; for instance, finding the ideal dosage of painkillers may take weeks or even months of trial-and-error to figure out.<\/p>\n
The transcriptome is the collection of RNA molecules in a cell that encode its genes. These messengers serve to control gene expression; that is, whether or not DNA instructions for making proteins are followed through. Investigating a cell’s transcriptome allows researchers to gain a better understanding of its function as well as how disease or environmental conditions might alter it.<\/p>\n
Transcriptomes contain both messenger RNA (mRNA) and non-coding RNA (ncRNA), with the latter providing various cellular functions. To understand an organism’s transcriptome composition, researchers collect mRNA from multiple tissues at certain time points and measure how many of each species exist at any one time point; they then use computational methods to assign each sequence back into the genome using which information can be quantified for each mRNA isoform relative abundance.<\/p>\n
Transcriptome analysis can be completed at three levels: genome, exon or transcript. One approach is microarrays which consist of grids of short nucleotide oligomers designed to hybridize with specific mRNA sequences – with fluorescence intensity at each probe position representing its relative abundance.<\/p>\n
Another approach is using RNA sequencing to measure mRNA abundance in multiple samples. With high-throughput technologies like RNA-Seq, researchers can analyze thousands of individual mRNA reads before comparing results across samples to detect any differences in gene expression among them; this process is known as comparative genomics.<\/p>\n
Transcriptome analyses can also assist in discovering genes with unknown functions or uncovering functional domains of existing genes. A comparative transcriptomics study of Douglas fir tree mRNAs revealed genes involved in heart, muscle, and nerve tissue development; similarly, bacteria transcriptional landscape has been used to identify genes required for adaptation to complex plant environments.<\/p>\n
RNA-based genomics techniques are increasingly being applied in clinical research for diagnosing and treating diseases like cancer and rare disorders. A combination of whole genome\/exome sequencing with RNA transcriptomics has proven particularly successful at improving diagnostic accuracy for certain cancers.<\/p>\n
As the multi-omics industry evolves, data sharing platforms have become an essential element of genomics innovation. They enable teams from across business units and external partners to work collaboratively while still meeting security, governance and cost efficiency criteria – much like having access to an entire collection of books instead of having to build individual libraries across departments which would take more time and often contain outdated information. Think of them like having access to a library card that gives access to many books rather than having to build multiple individual libraries with outdated material!<\/p>\n
Genomic data provides businesses with an invaluable opportunity to develop and test more products and services while also optimizing existing ones. By analyzing customer service data from multiple sources, organizations can identify areas for improvement that maximize customer satisfaction while boosting revenue. Likewise, by combining genomics and other types of data together into more accurate models that predict disease risks or identify suitable medications, and provide personalized care and treatment.<\/p>\n
However, the massive data flow has also raised privacy issues. Due to the individuality of genomics data samples collected for biobanks and genomics databases (such as NIH’s Database of Genotypes and Phenotypes (dbGaP) or UK Biobank), even small samples may reveal identity to researchers. As such, many biobanks or genomics databases such as these require participants to submit research proposals outlining how their data will be utilized before researchers may request access.<\/p>\n
Strict privacy controls are critical in protecting private health data leakage; however, they can slow scientific discovery and limit scope. Therefore, some researchers have turned to emerging privacy-enhancing technologies that may help circumvent such restrictions.<\/p>\n
These tools can assist researchers in de-identifying genomics data so that it remains useful, but still lack the scalability and performance required for genomics analysis. Equinix offers future-proof digital infrastructure supporting agile and scalable federated genomics data sharing to address this shortcoming.<\/p>\n
Equinix global data centers and interconnection ecosystem enable genomics researchers from various locations to collaborate while protecting the security and privacy of their sensitive data. For more information, visit Equinix website.<\/p>\n