Gene Expression Music Algorithm-Based Characterization of the Ewing Sarcoma Stem Cell Signature

Listening to life: Sonification for enhancing discovery in biological research

Sonification, or the practice of generating sound from data, is a promising alternative or complement to data visualization for exploring research questions in the life sciences. Expressing or communicating data in the form of sound rather than graphs, tables, or renderings can provide a secondary information source for multitasking or remote monitoring purposes or make data accessible when visualizations cannot be used. While popular in astronomy, neuroscience, and geophysics as a technique for data exploration and communication, its potential in the biological and biotechnological sciences has not been fully explored. In this review, we introduce sonification as a concept, some examples of how sonification has been used to address areas of interest in biology, and the history of the technique. We then highlight a selection of biology-related publications that involve sonifications of DNA datasets and protein datasets, sonifications for data collection and interpretation, and sonifications aimed to improve science communication and accessibility. Through this review, we aim to show how sonification has been used both as a discovery tool and a communication tool and to inspire more life-science researchers to incorporate sonification into their own studies.

Using Gene Expression Music Algorithms (GEMusicA) for the Characterization of Human Stem Cells

Gene Expression Music Algorithms (GEMusicA) use the transformation of gene expression data into melodies for the representation of sample-specific gene expression patterns. Quantitative analysis of similarities between melodies can be used for sample classification. The same algorithm can be used as simple and efficient encryption method. Here, we describe the usage of GEMusicA for the analyses of gene expression data from different stem cell types and stem cell-like tumor cells.

Real-time audio and visual display of the Coronavirus genome

BACKGROUND

This paper describes a web based tool that uses a combination of sonification and an animated display to inquire into the SARS-CoV-2 genome. The audio data is generated in real time from a variety of RNA motifs that are known to be important in the functioning of RNA. Additionally, metadata relating to RNA translation and transcription has been used to shape the auditory and visual displays. Together these tools provide a unique approach to further understand the metabolism of the viral RNA genome. This audio provides a further means to represent the function of the RNA in addition to traditional written and visual approaches.

RESULTS

Sonification of the SARS-CoV-2 genomic RNA sequence results in a complex auditory stream composed of up to 12 individual audio tracks. Each auditory motive is derived from the actual RNA sequence or from metadata. This approach has been used to represent transcription or translation of the viral RNA genome. The display highlights the real-time interaction of functional RNA elements. The sonification of codons derived from all three reading frames of the viral RNA sequence in combination with sonified metadata provide the framework for this display. Functional RNA motifs such as transcription regulatory sequences and stem loop regions have also been sonified. Using the tool, audio can be generated in real-time from either genomic or sub-genomic representations of the RNA. Given the large size of the viral genome, a collection of interactive buttons has been provided to navigate to regions of interest, such as cleavage regions in the polyprotein, untranslated regions or each gene. These tools are available through an internet browser and the user can interact with the data display in real time.

CONCLUSION

The auditory display in combination with real-time animation of the process of translation and transcription provide a unique insight into the large body of evidence describing the metabolism of the RNA genome. Furthermore, the tool has been used as an algorithmic based audio generator. These audio tracks can be listened to by the general community without reference to the visual display to encourage further inquiry into the science.

An auditory display tool for DNA sequence analysis

Background

DNA Sonification refers to the use of an auditory display to convey the information content of DNA sequence data. Six sonification algorithms are presented that each produce an auditory display. These algorithms are logically designed from the simple through to the more complex. Three of these parse individual nucleotides, nucleotide pairs or codons into musical notes to give rise to 4, 16 or 64 notes, respectively. Codons may also be parsed degenerately into 20 notes with respect to the genetic code. Lastly nucleotide pairs can be parsed as two separate frames or codons can be parsed as three reading frames giving rise to multiple streams of audio.

Results

The most informative sonification algorithm reads the DNA sequence as codons in three reading frames to produce three concurrent streams of audio in an auditory display. This approach is advantageous since start and stop codons in either frame have a direct affect to start or stop the audio in that frame, leaving the other frames unaffected. Using these methods, DNA sequences such as open reading frames or repetitive DNA sequences can be distinguished from one another. These sonification tools are available through a webpage interface in which an input DNA sequence can be processed in real time to produce an auditory display playable directly within the browser. The potential of this approach as an analytical tool is discussed with reference to auditory displays derived from test sequences including simple nucleotide sequences, repetitive DNA sequences and coding or non-coding genes.

Conclusion

This study presents a proof-of-concept that some properties of a DNA sequence can be identified through sonification alone and argues for their inclusion within the toolkit of DNA sequence browsers as an adjunct to existing visual and analytical tools.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1632-x) contains supplementary material, which is available to authorized users.