Transcriptomics technologies: Difference between revisions

Revision as of 05:35, 20 May 2024

Revision as of 05:37, 20 May 2024

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Assembly of RNA-Seq reads is not dependent on a [[reference genome]]<ref name="#21572440">{{cite journal | vauthors = Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, Adiconis X, Fan L, Raychowdhury R, Zeng Q, Chen Z, Mauceli E, Hacohen N, Gnirke A, Rhind N, di Palma F, Birren BW, Nusbaum C, Lindblad-Toh K, Friedman N, Regev A | title = Full-length transcriptome assembly from RNA-Seq data without a reference genome | journal = Nature Biotechnology | volume = 29 | issue = 7 | pages = 644–52 | date = May 2011 | pmid = 21572440 | pmc = 3571712 | doi = 10.1038/nbt.1883 }}</ref> and so is ideal for gene expression studies of non-model organisms with non-existing or poorly developed genomic resources. For example, a database of SNPs used in [[Pseudotsuga menziesii|Douglas fir]] breeding programs was created by ''de novo'' transcriptome analysis in the absence of a [[Genome sequencing|sequenced genome]].<ref name="#23445355">{{cite journal | vauthors = Howe GT, Yu J, Knaus B, Cronn R, Kolpak S, Dolan P, Lorenz WW, Dean JF | title = A SNP resource for Douglas-fir: de novo transcriptome assembly and SNP detection and validation | journal = BMC Genomics | volume = 14 | pages = 137 | date = February 2013 | pmid = 23445355 | pmc = 3673906 | doi = 10.1186/1471-2164-14-137 | doi-access = free }}</ref> Similarly, genes that function in the development of cardiac, muscle, and nervous tissue in lobsters were identified by comparing the transcriptomes of the various tissue types without use of a genome sequence.<ref name="#26772543">{{cite journal | vauthors = McGrath LL, Vollmer SV, Kaluziak ST, Ayers J | title = De novo transcriptome assembly for the lobster Homarus americanus and characterization of differential gene expression across nervous system tissues | journal = BMC Genomics | volume = 17 | pages = 63 | date = January 2016 | pmid = 26772543 | pmc = 4715275 | doi = 10.1186/s12864-016-2373-3 | doi-access = free }}</ref> RNA-Seq can also be used to identify previously unknown [[protein coding region]]s in existing sequenced genomes.

==== A transcriptome based aging clock ====

Aging-related preventive interventions are not possible without personal aging speed measurement. The most up to date and complex way to measure aging rate is by using varying biomarkers of human aging is based on the utilization of deep neural networks which may be trained on any type of omics biological data to predict the subject's age. Aging has been shown to be a strong driver of transcriptome changes.<ref name="clock">{{cite journal | vauthors = Meyer DH, Schumacher B | year = 2020 | title = BiT age: A transcriptome-based aging clock near the theoretical limit of accuracy | journal = Aging Cell| volume = 20 | issue = 3 | pages = e13320 | doi = 10.1111/acel.13320 | pmid = 33656257 | pmc = 7963339 | doi-access = free }}</ref><ref>{{cite journal | vauthors = Fleischer JG, Schulte R, Tsai HH, Tyagi S, Ibarra A, Shokhirev MN, Navlakha S | year = 2018 | title = Predicting age from the transcriptome of human dermal fibroblasts | journal = Genome Biology | volume = 19 | issue = 1| page = 221 | doi = 10.1186/s13059-018-1599-6 | pmid = 30567591 | pmc = 6300908 | doi-access = free }}</ref>

=== Non-coding RNA ===