Editing Transcriptome (section)

===Mammals===
The transcriptomes of [[stem cell]]s and [[cancer]] cells are of particular interest to researchers who seek to understand the processes of [[cellular differentiation]] and [[carcinogenesis]]. A pipeline using RNA-seq or gene array data can be used to track genetic changes occurring in [[stem cells|stem]] and [[precursor cells]] and requires at least three independent gene expression data from the former cell type and mature cells.<ref>{{cite journal|title=Assessment of stem cell differentiation based on genome-wide expression profiles|journal=[[Philosophical Transactions of the Royal Society B]]|doi=10.1098/rstb.2017.0221|date=5 July 2018|volume=373|issue=1750|pmid=29786556|first1=Patricio|last1=Godoy|first2=Wolfgang|last2=Schmidt-Heck|first3=Birte|last3=Hellwig|first4=Patrick|last4=Nell|first5=David|last5=Feuerborn|first6=Jörg|last6=Rahnenführer|first7=Kathrin|last7=Kattler|first8=Jörn|last8=Walter|first9=Nils|last9=Blüthgen|first10=Jan|last10=G. Hengstler|pages = 20170221|pmc = 5974444|doi-access=free}}</ref>

Analysis of the transcriptomes of human [[oocyte]]s and [[human embryo|embryos]] is used to understand the molecular mechanisms and signaling pathways controlling early embryonic development, and could theoretically be a powerful tool in making proper [[embryo selection]] in [[in vitro fertilisation]].{{citation needed|date=April 2020}} Analyses of the transcriptome content of the placenta in the first-trimester of pregnancy in ''in vitro'' fertilization and embryo transfer (IVT-ET) revealed differences in genetic expression which are associated with higher frequency of adverse perinatal outcomes. Such insight can be used to optimize the practice.<ref>{{cite journal|title=The placental transcriptome of the first-trimester placenta is affected by in vitro fertilization and embryo transfer|journal=Reproductive Biology and Endocrinology|last1=Zhao|first1=L|last2=Zheng|first2=X|last3=Liu|first3=J|last4=Zheng|first4=R|last5=Yang|first5=R|last6=Wang|first6=Y|last7=Sun|first7=L|doi=10.1186/s12958-019-0494-7|pmid=31262321|date=1 July 2019|volume=17|issue=1|page=50|pmc = 6604150|doi-access=free}}</ref> Transcriptome analyses can also be used to optimize cryopreservation of oocytes, by lowering injuries associated with the process.<ref>{{cite journal|title=Probing lasting cryoinjuries to oocyte-embryo transcriptome|journal=PLOS ONE|first1=Binnur|last1=Eroglu|first2=Edyta|last2=A. Szurek|first3=Peter|last3=Schall|first4=Keith|last4=E. Latham|first5=Ali|last5=Eroglu|date=6 April 2020|doi=10.1371/journal.pone.0231108|pmid=32251418|volume=15|issue=4|pages = e0231108|pmc = 7135251|bibcode=2020PLoSO..1531108E|doi-access=free}}</ref>

Transcriptomics is an emerging and continually growing field in [[biomarker]] discovery for use in assessing the safety of drugs or chemical [[risk assessment]].<ref name="David T Szabo">{{cite book|last=Szabo|first=David|title=Transcriptomic biomarkers in safety and risk assessment of chemicals. In Ramesh Gupta, editors:Gupta - Biomarkers in Toxicology, Oxford:Academic Press.|date=2014|isbn=978-0-12-404630-6|pages=1033–1038|doi=10.1016/B978-0-12-404630-6.00062-2|chapter=Transcriptomic biomarkers in safety and risk assessment of chemicals|s2cid=89396307 |url=https://zenodo.org/record/1258664}}</ref>

Transcriptomes may also be used to [[Phylogenetic inference using transcriptomic data|infer phylogenetic relationships]] among individuals or to detect evolutionary patterns of transcriptome conservation.<ref>{{Cite journal|last1=Drost|first1=Hajk-Georg|last2=Gabel|first2=Alexander|last3=Grosse|first3=Ivo|last4=Quint|first4=Marcel|last5=Grosse|first5=Ivo|date=2018-05-01|title=myTAI: evolutionary transcriptomics with R|url= |journal=Bioinformatics|language=en|volume=34|issue=9|pages=1589–1590|doi=10.1093/molbev/msv012|issn=0737-4038|pmc=5925770|pmid=29309527}}</ref>

Transcriptome analyses were used to discover the incidence of antisense transcription, their role in gene expression through interaction with surrounding genes and their abundance in different chromosomes.<ref>{{cite journal|url=https://www.science.org/doi/full/10.1126/science.1112009|title=Antisense Transcription in the Mammalian Transcriptome|first1=Katayama|display-authors=etal|last1=S|journal=[[Science (journal)|Science]]|volume=309|issue=5740|year=2005|pages=1564–6|doi=10.1126/science.1112009|pmid=16141073|bibcode=2005Sci...309.1564R|s2cid=34559885|url-access=subscription}}</ref> RNA-seq was also used to show how RNA isoforms, transcripts stemming from the same gene but with different structures, can produce complex phenotypes from limited genomes.<ref name="scimag">{{cite journal|url=https://www.science.org/content/article/transcriptomics-today-microarrays-rna-seq-and-more|title=Transcriptomics today: Microarrays, RNA-seq, and more|journal=Science Magazine|first=Chris|last=Tachibana|date=31 July 2015|volume=349|issue=6247|pages=544|bibcode=2015Sci...349..544T|access-date=2 May 2020}}</ref>