Transcriptomics technologies: Difference between revisions

Revision as of 09:32, 2 August 2021

Revision as of 09:09, 3 September 2021

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=== Before transcriptomics ===

Studies of individual [[Primary transcript|transcripts]] were being performed several decades before any transcriptomics approaches were available. [[CDNA library|Libraries]] of [[Antheraea polyphemus|silkmoth]] mRNA transcripts were collected and converted to [[complementary DNA]] (cDNA) for storage using [[reverse transcriptase]] in the late 1970s.<ref name="#519770">{{cite journal | vauthors = Sim GK, Kafatos FC, Jones CW, Koehler MD, Efstratiadis A, Maniatis T | title = Use of a cDNA library for studies on evolution and developmental expression of the chorion multigene families | journal = Cell | volume = 18 | issue = 4 | pages = 1303–16 | date = December 1979 | pmid = 519770 | doi = 10.1016/0092-8674(79)90241-1 | doi-access = free }}</ref> In the 1980s, low-throughput sequencing using the [[Sanger sequencing|Sanger]] method was used to sequence random transcripts, producing [[expressed sequence tag]]s (ESTs).<ref name="ref2047873">{{cite journal | vauthors = Adams MD, Kelley JM, Gocayne JD, Dubnick M, Polymeropoulos MH, Xiao H, Merril CR, Wu A, Olde B, Moreno RF | display-authors = 6 | title = Complementary DNA sequencing: expressed sequence tags and human genome project | journal = Science | volume = 252 | issue = 5013 | pages = 1651–6 | date = June 1991 | pmid = 2047873 | doi = 10.1126/science.2047873 | bibcode = 1991Sci...252.1651A | s2cid = 13436211 }}</ref><ref name="#6956902">{{cite journal | vauthors = Sutcliffe JG, Milner RJ, Bloom FE, Lerner RA | title = Common 82-nucleotide sequence unique to brain RNA | journal = Proceedings of the National Academy of Sciences of the United States of America | volume = 79 | issue = 16 | pages = 4942–6 | date = August 1982 | pmid = 6956902 | pmc = 346801 | bibcode = 1982PNAS...79.4942S | doi = 10.1073/pnas.79.16.4942 | doi-access = free }}</ref><ref name="#6687628">{{cite journal | vauthors = Putney SD, Herlihy WC, Schimmel P | title = A new troponin T and cDNA clones for 13 different muscle proteins, found by shotgun sequencing | journal = Nature | volume = 302 | issue = 5910 | pages = 718–21 | date = April 1983 | pmid = 6687628 | doi = 10.1038/302718a0 | bibcode = 1983Natur.302..718P | s2cid = 4364361 }}</ref><ref name="#9448457" /> The [[Sanger sequencing|Sanger method of sequencing]] was predominant until the advent of [[DNA sequencing#High-throughput methods|high-throughput methods]] such as [[sequencing by synthesis]] (Solexa/Illumina). [[Expressed sequence tag|ESTs]] came to prominence during the 1990s as an efficient method to determine the [[gene annotation|gene content]] of an organism without [[Whole genome sequencing|sequencing]] the entire [[genome]].<ref name="#9448457">{{cite journal | vauthors = Marra MA, Hillier L, Waterston RH | title = Expressed sequence tags—ESTablishing bridges between genomes | journal = Trends in Genetics | volume = 14 | issue = 1 | pages = 4–7 | date = January 1998 | pmid = 9448457 | doi = 10.1016/S0168-9525(97)01355-3 }}</ref> Amounts of individual transcripts were quantified using [[Northern blotting]], [[Reverse northern blot|nylon membrane arrays]], and later [[Reverse transcription polymerase chain reaction|reverse transcriptase quantitative PCR]] (RT-qPCR) methods,<ref name="#414220">{{cite journal | vauthors = Alwine JC, Kemp DJ, Stark GR | title = Method for detection of specific RNAs in agarose gels by transfer to diazobenzyloxymethyl-paper and hybridization with DNA probes | journal = Proceedings of the National Academy of Sciences of the United States of America | volume = 74 | issue = 12 | pages = 5350–4 | date = December 1977 | pmid = 414220 | pmc = 431715 | doi = 10.1073/pnas.74.12.5350 | bibcode = 1977PNAS...74.5350A | doi-access = free }}</ref><ref name="#2479917">{{cite journal | vauthors = Becker-André M, Hahlbrock K | title = Absolute mRNA quantification using the polymerase chain reaction (PCR). A novel approach by a PCR aided transcript titration assay (PATTY) | journal = Nucleic Acids Research | volume = 17 | issue = 22 | pages = 9437–46 | date = November 1989 | pmid = 2479917 | pmc = 335144 | doi = 10.1093/nar/17.22.9437 }}</ref> but these methods are laborious and can only capture a tiny subsection of a transcriptome.<ref name="#19715439" /> Consequently, the manner in which a transcriptome as a whole is expressed and regulated remained unknown until higher-throughput techniques were developed.

=== Early attempts ===

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=== Development of contemporary techniques ===

{| class="wikitable floatright" style="width:500px"

|+ '''Comparison of contemporary methods'''<ref name="#25149683">{{cite journal | vauthors = Mantione KJ, Kream RM, Kuzelova H, Ptacek R, Raboch J, Samuel JM, Stefano GB | title = Comparing bioinformatic gene expression profiling methods: microarray and RNA-Seq | journal = Medical Science Monitor Basic Research | volume = 20 | pages = 138–42 | date = August 2014 | pmid = 25149683 | pmc = 4152252 | doi = 10.12659/MSMBR.892101 }}</ref><ref name="#24454679">{{cite journal | vauthors = Zhao S, Fung-Leung WP, Bittner A, Ngo K, Liu X | title = Comparison of RNA-Seq and microarray in transcriptome profiling of activated T cells | journal = PLOS ONE | volume = 9 | issue = 1 | pages = e78644 | date = 2014 | pmid = 24454679 | pmc = 3894192 | doi = 10.1371/journal.pone.0078644 | bibcode = 2014PLoSO...978644Z | doi-access = free }}</ref><ref name="#19015660" />

|

!RNA-Seq

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[[Serial analysis of gene expression]] (SAGE) was a development of EST methodology to increase the throughput of the tags generated and allow some quantitation of transcript abundance.<ref name="#7570003" /> [[Complementary DNA|cDNA]] is generated from the [[RNA]] but is then digested into 11&nbsp;bp "tag" fragments using [[restriction enzyme]]s that cut DNA at a specific sequence, and 11&nbsp;base pairs along from that sequence. These cDNA tags are then [[Ligation (molecular biology)|joined]] head-to-tail into long strands (>500&nbsp;bp) and sequenced using low-throughput, but long read-length methods such as [[Sanger sequencing]]. The sequences are then divided back into their original 11 bp tags using computer software in a process called [[deconvolution]].<ref name="#7570003" /> If a high-quality [[reference genome]] is available, these tags may be matched to their corresponding gene in the genome. If a reference genome is unavailable, the tags can be directly used as diagnostic markers if found to be [[Gene expression profiling|differentially expressed]] in a disease state.<ref name="#7570003" />

The [[cap analysis gene expression]] (CAGE) method is a variant of SAGE that sequences tags from the [[5’ end]] of an mRNA transcript only.<ref name="#14663149">{{cite journal | vauthors = Shiraki T, Kondo S, Katayama S, Waki K, Kasukawa T, Kawaji H, Kodzius R, Watahiki A, Nakamura M, Arakawa T, Fukuda S, Sasaki D, Podhajska A, Harbers M, Kawai J, Carninci P, Hayashizaki Y | title = Cap analysis gene expression for high-throughput analysis of transcriptional starting point and identification of promoter usage | journal = Proceedings of the National Academy of Sciences of the United States of America | volume = 100 | issue = 26 | pages = 15776–81 | date = December 2003 | pmid = 14663149 | pmc = 307644 | doi = 10.1073/pnas.2136655100 | bibcode = 2003PNAS..10015776S | doi-access = free }}</ref> Therefore, the [[Transcription (genetics)#Initiation|transcriptional start site]] of genes can be identified when the tags are aligned to a reference genome. Identifying gene start sites is of use for [[Promoter (genetics)|promoter]] analysis and for the [[Molecular cloning|cloning]] of full-length cDNAs.

SAGE and CAGE methods produce information on more genes than was possible when sequencing single ESTs, but sample preparation and data analysis are typically more labour-intensive.<ref name="#14663149" />

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The sensitivity of an RNA-Seq experiment can be increased by enriching classes of RNA that are of interest and depleting known abundant RNAs. The mRNA molecules can be separated using oligonucleotides probes which bind their [[Polyadenylation|poly-A tails]]. Alternatively, ribo-depletion can be used to specifically remove abundant but uninformative [[ribosomal RNA]]s (rRNAs) by hybridisation to probes tailored to the [[taxon|taxon's]] specific rRNA sequences (e.g. mammal rRNA, plant rRNA). However, ribo-depletion can also introduce some bias via non-specific depletion of off-target transcripts.<ref name="#24981968">{{cite journal | vauthors = Lahens NF, Kavakli IH, Zhang R, Hayer K, Black MB, Dueck H, Pizarro A, Kim J, Irizarry R, Thomas RS, Grant GR, Hogenesch JB | title = IVT-seq reveals extreme bias in RNA sequencing | journal = Genome Biology | volume = 15 | issue = 6 | pages = R86 | date = June 2014 | pmid = 24981968 | pmc = 4197826 | doi = 10.1186/gb-2014-15-6-r86 }}</ref> Small RNAs, such as [[micro RNA]]s, can be purified based on their size by [[gel electrophoresis]] and extraction.

Since mRNAs are longer than the read-lengths of typical high-throughput sequencing methods, transcripts are usually fragmented prior to sequencing.<ref name="#22140562">{{cite journal|vauthors=Knierim E, Lucke B, Schwarz JM, Schuelke M, Seelow D|date=2011|title=Systematic comparison of three methods for fragmentation of long-range PCR products for next generation sequencing|journal=PLOS ONE|volume=6|issue=11|pages=e28240|bibcode=2011PLoSO...628240K|doi=10.1371/journal.pone.0028240|pmc=3227650|pmid=22140562|doi-access=free}}</ref> The fragmentation method is a key aspect of sequencing library construction. [[DNA fragmentation|Fragmentation]] may be achieved by [[hydrolysis|chemical hydrolysis]], [[Atomizer nozzle|nebulisation]], [[sonication]], or [[Reverse transcriptase|reverse transcription]] with [[DNA sequencing#Chain-termination methods|chain-terminating nucleotides]].<ref name="#22140562" /> Alternatively, fragmentation and cDNA tagging may be done simultaneously by using [[Transposase|transposase enzymes]].<ref>{{cite journal | vauthors = Routh A, Head SR, Ordoukhanian P, Johnson JE | title = ClickSeq: Fragmentation-Free Next-Generation Sequencing via Click Ligation of Adaptors to Stochastically Terminated 3'-Azido cDNAs | journal = Journal of Molecular Biology | volume = 427 | issue = 16 | pages = 2610–6 | date = August 2015 | pmid = 26116762 | doi = 10.1016/j.jmb.2015.06.011 | pmc = 4523409 }}</ref>

During preparation for sequencing, cDNA copies of transcripts may be amplified by [[Polymerase chain reaction|PCR]] to enrich for fragments that contain the expected 5’ and 3’ adapter sequences.<ref name="#27156886">{{cite journal | vauthors = Parekh S, Ziegenhain C, Vieth B, Enard W, Hellmann I | title = The impact of amplification on differential expression analyses by RNA-seq | journal = Scientific Reports | volume = 6 | pages = 25533 | date = May 2016 | pmid = 27156886 | pmc = 4860583 | doi = 10.1038/srep25533 | bibcode = 2016NatSR...625533P }}</ref> Amplification is also used to allow sequencing of very low input amounts of RNA, down to as little as 50 [[Orders of magnitude (mass)#picogram|pg]] in extreme applications.<ref name="#25649271">{{cite journal | vauthors = Shanker S, Paulson A, Edenberg HJ, Peak A, Perera A, Alekseyev YO, Beckloff N, Bivens NJ, Donnelly R, Gillaspy AF, Grove D, Gu W, Jafari N, Kerley-Hamilton JS, Lyons RH, Tepper C, Nicolet CM | title = Evaluation of commercially available RNA amplification kits for RNA sequencing using very low input amounts of total RNA | journal = Journal of Biomolecular Techniques | volume = 26 | issue = 1 | pages = 4–18 | date = April 2015 | pmid = 25649271 | pmc = 4310221 | doi = 10.7171/jbt.15-2601-001 }}</ref> [[RNA spike-in|Spike-in controls]] of known RNAs can be used for quality control assessment to check library preparation and sequencing, in terms of [[GC-content]], fragment length, as well as the bias due to fragment position within a transcript.<ref name="#21816910">{{cite journal | vauthors = Jiang L, Schlesinger F, Davis CA, Zhang Y, Li R, Salit M, Gingeras TR, Oliver B | title = Synthetic spike-in standards for RNA-seq experiments | journal = Genome Research | volume = 21 | issue = 9 | pages = 1543–51 | date = September 2011 | pmid = 21816910 | pmc = 3166838 | doi = 10.1101/gr.121095.111 }}</ref> [[Unique molecular identifiers]] (UMIs) are short random sequences that are used to individually tag sequence fragments during library preparation so that every tagged fragment is unique.<ref name="#22101854">{{cite journal | vauthors = Kivioja T, Vähärautio A, Karlsson K, Bonke M, Enge M, Linnarsson S, Taipale J | title = Counting absolute numbers of molecules using unique molecular identifiers | journal = Nature Methods | volume = 9 | issue = 1 | pages = 72–4 | date = November 2011 | pmid = 22101854 | doi = 10.1038/nmeth.1778 | s2cid = 39225091 }}</ref> UMIs provide an absolute scale for quantification, the opportunity to correct for subsequent amplification bias introduced during library construction, and accurately estimate the initial sample size. UMIs are particularly well-suited to single-cell RNA-Seq transcriptomics, where the amount of input RNA is restricted and extended amplification of the sample is required.<ref name="#19349980">{{cite journal | vauthors = Tang F, Barbacioru C, Wang Y, Nordman E, Lee C, Xu N, Wang X, Bodeau J, Tuch BB, Siddiqui A, Lao K, Surani MA | title = mRNA-Seq whole-transcriptome analysis of a single cell | journal = Nature Methods | volume = 6 | issue = 5 | pages = 377–82 | date = May 2009 | pmid = 19349980 | doi = 10.1038/nmeth.1315 | s2cid = 16570747 }}</ref><ref name="#24363023">{{cite journal | vauthors = Islam S, Zeisel A, Joost S, La Manno G, Zajac P, Kasper M, Lönnerberg P, Linnarsson S | title = Quantitative single-cell RNA-seq with unique molecular identifiers | journal = Nature Methods | volume = 11 | issue = 2 | pages = 163–6 | date = February 2014 | pmid = 24363023 | doi = 10.1038/nmeth.2772 | s2cid = 6765530 }}</ref><ref name="#24531970">{{cite journal | vauthors = Jaitin DA, Kenigsberg E, Keren-Shaul H, Elefant N, Paul F, Zaretsky I, Mildner A, Cohen N, Jung S, Tanay A, Amit I | title = Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types | journal = Science | volume = 343 | issue = 6172 | pages = 776–9 | date = February 2014 | pmid = 24531970 | pmc = 4412462 | doi = 10.1126/science.1247651 | bibcode = 2014Sci...343..776J }}</ref>

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Transcriptomics allows identification of genes and [[Metabolic pathways|pathways]] that respond to and counteract [[Biotic stress|biotic]] and [[Abiotic stress|abiotic environmental stresses.]]<ref name="#26759178" /><ref name="Govind_2009" /> The non-targeted nature of transcriptomics allows the identification of novel transcriptional networks in complex systems. For example, comparative analysis of a range of [[Cicer arietinum|chickpea]] lines at different developmental stages identified distinct transcriptional profiles associated with [[drought]] and [[salinity]] stresses, including identifying the role of [[Alternative splicing|transcript isoforms]] of [[Apetala 2|AP2]]-[[Ethylene-responsive element binding protein|EREBP]].<ref name="#26759178">{{cite journal | vauthors = Garg R, Shankar R, Thakkar B, Kudapa H, Krishnamurthy L, Mantri N, Varshney RK, Bhatia S, Jain M | title = Transcriptome analyses reveal genotype- and developmental stage-specific molecular responses to drought and salinity stresses in chickpea | journal = Scientific Reports | volume = 6 | pages = 19228 | date = January 2016 | pmid = 26759178 | pmc = 4725360 | doi = 10.1038/srep19228 | bibcode = 2016NatSR...619228G }}</ref> Investigation of gene expression during [[biofilm]] formation by the [[Fungus|fungal]] pathogen ''[[Candida albicans]]'' revealed a co-regulated set of genes critical for biofilm establishment and maintenance.<ref name="#15075282">{{cite journal | vauthors = García-Sánchez S, Aubert S, Iraqui I, Janbon G, Ghigo JM, d'Enfert C | title = Candida albicans biofilms: a developmental state associated with specific and stable gene expression patterns | journal = Eukaryotic Cell | volume = 3 | issue = 2 | pages = 536–45 | date = April 2004 | pmid = 15075282 | pmc = 387656 | doi = 10.1128/EC.3.2.536-545.2004 }}</ref>

Transcriptomic profiling also provides crucial information on mechanisms of [[drug resistance]]. Analysis of over 1000 isolates of ''[[Plasmodium falciparum]]'', a virulent parasite responsible for malaria in humans,<ref name="Rich et al">{{cite journal | vauthors = Rich SM, Leendertz FH, Xu G, LeBreton M, Djoko CF, Aminake MN, Takang EE, Diffo JL, Pike BL, Rosenthal BM, Formenty P, Boesch C, Ayala FJ, Wolfe ND | title = The origin of malignant malaria | journal = Proceedings of the National Academy of Sciences of the United States of America | volume = 106 | issue = 35 | pages = 14902–7 | date = September 2009 | pmid = 19666593 | pmc = 2720412 | doi = 10.1073/pnas.0907740106 | bibcode = 2009PNAS..10614902R | doi-access = free }}</ref> identified that upregulation of the [[unfolded protein response]] and slower progression through the early stages of the asexual intraerythrocytic [[Plasmodium falciparum#Lifecycle|developmental cycle]] were associated with [[Artemisinin#Resistance|artemisinin resistance]] in isolates from [[Southeast Asia]].<ref name="#25502316">{{cite journal | vauthors = Mok S, Ashley EA, Ferreira PE, Zhu L, Lin Z, Yeo T, Chotivanich K, Imwong M, Pukrittayakamee S, Dhorda M, Nguon C, Lim P, Amaratunga C, Suon S, Hien TT, Htut Y, Faiz MA, Onyamboko MA, Mayxay M, Newton PN, Tripura R, Woodrow CJ, Miotto O, Kwiatkowski DP, Nosten F, Day NP, Preiser PR, White NJ, Dondorp AM, Fairhurst RM, Bozdech Z | display-authors = 6 | title = Drug resistance. Population transcriptomics of human malaria parasites reveals the mechanism of artemisinin resistance | journal = Science | volume = 347 | issue = 6220 | pages = 431–5 | date = January 2015 | pmid = 25502316 | pmc = 5642863 | doi = 10.1126/science.1260403 | bibcode = 2015Sci...347..431M }}</ref>

=== Gene function annotation ===