Transcriptomics technologies: Difference between revisions

Revision as of 14:19, 24 October 2022

Revision as of 03:43, 2 January 2023

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===Isolation of RNA===

All transcriptomic methods require RNA to first be isolated from the experimental organism before transcripts can be recorded. Although biological systems are incredibly diverse, [[RNA extraction]] techniques are broadly similar and involve mechanical [[Cell disruption|disruption of cells]] or tissues, disruption of [[RNAse|RNase]] with [[Chaotropic agent|chaotropic salts]],<ref name="#2440339">{{cite journal | vauthors = Chomczynski P, Sacchi N | title = Single-step method of RNA isolation by acid guanidinium thiocyanate-phenol-chloroform extraction | journal = Analytical Biochemistry | volume = 162 | issue = 1 | pages = 156–9 | date = April 1987 | pmid = 2440339 | doi = 10.1016/0003-2697(87)90021-2 }}</ref> disruption of macromolecules and nucleotide complexes, separation of RNA from undesired [[biomolecule]]s including DNA, and concentration of the RNA via [[ethanol precipitation|precipitation]] from solution or [[Spin column-based nucleic acid purification|elution from a solid matrix]].<ref name="#2440339" /><ref name="#17406285">{{cite journal | vauthors = Chomczynski P, Sacchi N | title = The single-step method of RNA isolation by acid guanidinium thiocyanate-phenol-chloroform extraction: twenty-something years on | journal = Nature Protocols | volume = 1 | issue = 2 | pages = 581–5 | date = 2006 | pmid = 17406285 | doi = 10.1038/nprot.2006.83 | s2cid = 28653075 }}</ref> Isolated RNA may additionally be treated with [[DNAse|DNase]] to digest any traces of DNA.<ref name="#1699561">{{cite journal | vauthors = Grillo M, Margolis FL | title = Use of reverse transcriptase polymerase chain reaction to monitor expression of intronless genes | journal = BioTechniques | volume = 9 | issue = 3 | pages = 262, 264, 266–8 | date = September 1990 | pmid = 1699561 }}</ref> It is necessary to enrich messenger RNA as total RNA extracts are typically 98% [[ribosomal RNA]].<ref name="#9664454">{{cite book | vauthors = Bryant S, Manning DL | title = RNA Isolation and Characterization Protocols | chapter = Isolation of messenger RNA | series = Methods in Molecular Biology | volume = 86 | pages = 61–4 | date = 1998 | pmid = 9664454 | doi = 10.1385/0-89603-494-1:61 | isbn = 978-0-89603-494-5 }}</ref> Enrichment for transcripts can be performed by [[Polyadenylation|poly-A]] affinity methods or by depletion of ribosomal RNA using sequence-specific probes.<ref name="#24888378">{{cite journal | vauthors = Zhao W, He X, Hoadley KA, Parker JS, Hayes DN, Perou CM | title = Comparison of RNA-Seq by poly (A) capture, ribosomal RNA depletion, and DNA microarray for expression profiling | journal = BMC Genomics | volume = 15 | pages = 419 | date = June 2014 | issue = 1 | pmid = 24888378 | pmc = 4070569 | doi = 10.1186/1471-2164-15-419 }}</ref> Degraded RNA may affect downstream results; for example, mRNA enrichment from degraded samples will result in the depletion of [[5' end|5’ mRNA ends]] and an uneven signal across the length of a transcript. [[Snap freezing#Scientific use|Snap-freezing]] of tissue prior to RNA isolation is typical, and care is taken to reduce exposure to RNase enzymes once isolation is complete.<ref name="#17406285" />

===Expressed sequence tags===

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==== Quality control ====

Sequence reads are not perfect, so the accuracy of each base in the sequence needs to be estimated for downstream analyses. Raw data is examined to ensure: quality scores for base calls are high, the GC content matches the expected distribution, short sequence motifs ([[k-mers]]) are not over-represented, and the read duplication rate is acceptably low.<ref name="#26813401" /> Several software options exist for sequence quality analysis, including FastQC and FaQCs.<ref>{{Cite web|url=http://www.bioinformatics.babraham.ac.uk/projects/fastqc/|title=FastQC: A Quality Control tool for High Throughput Sequence Data|publisher=Babraham Bioinformatics|date=2010|access-date=2017-05-23 | vauthors = Andrews S }}</ref><ref name="#25408143">{{cite journal | vauthors = Lo CC, Chain PS | title = Rapid evaluation and quality control of next generation sequencing data with FaQCs | journal = BMC Bioinformatics | volume = 15 | pages = 366 | date = November 2014 | issue = 1 | pmid = 25408143 | pmc = 4246454 | doi = 10.1186/s12859-014-0366-2 }}</ref> Abnormalities may be removed (trimming) or tagged for special treatment during later processes.

==== Alignment ====

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The use of transcriptomics is also important to investigate responses in the marine environment.<ref name=":0"> {{Cite journal |last1=Page |first1=Tessa M. |last2=Lawley |first2=Jonathan W. |date=2022 |title=The Next Generation Is Here: A Review of Transcriptomic Approaches in Marine Ecology |journal=Frontiers in Marine Science |volume=9 |doi=10.3389/fmars.2022.757921 |issn=2296-7745|doi-access=free }}</ref> In marine ecology, "[[Stress (biology)|stress]]" and "[[adaptation]]" have been among the most common research topics, especially related to anthropogenic stress, such as [[global change]] and [[pollution]].<ref name=":0" /> Most of the studies in this area have been done in [[Animal|animals]], although [[Invertebrate|invertebrates]] have been underrepresented.<ref name=":0" /> One issue still is a deficiency in functional genetic studies, which hamper [[Gene annotation|gene annotations]], especially for non-model species, and can lead to vague conclusions on the effects of responses studied.<ref name=":0" />

=== Gene function annotation ===

All transcriptomic techniques have been particularly useful in [[Gene annotation|identifying the functions of genes]] and identifying those responsible for particular phenotypes. Transcriptomics of ''Arabidopsis'' [[ecotype]]s that [[Hyperaccumulator|hyperaccumulate metals]] correlated genes involved in [[Bioinorganic chemistry#Metal ion transport and storage|metal uptake]], tolerance, and [[homeostasis]] with the phenotype.<ref name="#19192189">{{cite journal | vauthors = Verbruggen N, Hermans C, Schat H | title = Molecular mechanisms of metal hyperaccumulation in plants | journal = The New Phytologist | volume = 181 | issue = 4 | pages = 759–76 | date = March 2009 | pmid = 19192189 | doi = 10.1111/j.1469-8137.2008.02748.x | url = https://dipot.ulb.ac.be/dspace/bitstream/2013/58126/3/58126.pdf }}</ref> Integration of RNA-Seq datasets across different tissues has been used to improve annotation of gene functions in commercially important organisms (e.g. [[Cucumis sativus|cucumber]])<ref name="#22047402">{{cite journal | vauthors = Li Z, Zhang Z, Yan P, Huang S, Fei Z, Lin K | title = RNA-Seq improves annotation of protein-coding genes in the cucumber genome | journal = BMC Genomics | volume = 12 | pages = 540 | date = November 2011 | pmid = 22047402 | pmc = 3219749 | doi = 10.1186/1471-2164-12-540 }}</ref> or threatened species (e.g. [[koala]]).<ref name="#25214207">{{cite journal | vauthors = Hobbs M, Pavasovic A, King AG, Prentis PJ, Eldridge MD, Chen Z, Colgan DJ, Polkinghorne A, Wilkins MR, Flanagan C, Gillett A, Hanger J, Johnson RN, Timms P | title = A transcriptome resource for the koala (Phascolarctos cinereus): insights into koala retrovirus transcription and sequence diversity | journal = BMC Genomics | volume = 15 | pages = 786 | date = September 2014 | issue = 1 | pmid = 25214207 | pmc = 4247155 | doi = 10.1186/1471-2164-15-786 }}</ref>

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 }}</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 }}</ref> RNA-Seq can also be used to identify previously unknown [[protein coding region]]s in existing sequenced genomes.