Literature DB >> 35670911

Another lesson from unmapped reads: in-depth analysis of RNA-Seq reads from various horse tissues.

Artur Gurgul1, Tomasz Szmatoła2, Ewa Ocłoń2, Igor Jasielczuk2, Ewelina Semik-Gurgul3, Carrie J Finno4, Jessica L Petersen5, Rebecca Bellone4,6, Erin N Hales4, Tomasz Ząbek3, Zbigniew Arent2, Małgorzata Kotula-Balak7, Monika Bugno-Poniewierska8.   

Abstract

In recent years, a vast amount of sequencing data has been generated and large improvements have been made to reference genome sequences. Despite these advances, significant portions of reads still do not map to reference genomes and these reads have been considered as junk or artificial sequences. Recent studies have shown that these reads can be useful, e.g., for refining reference genomes or detecting contaminating microorganisms present in the analyzed biological samples. A special case of this is RNA sequencing (RNA-Seq) reads that come from tissue transcriptomes. Unmapped reads from RNA-Seq have received much less attention than those from whole-genome sequencing. In particular, in the horse, an analysis of unmapped RNA reads has not been performed yet. Thus, in this study, we analyzed the unmapped reads originating from the RNA-Seq performed through the Functional Annotation of Animal Genomes (FAANG) project in the horse, using eight different tissues from two mares. We demonstrated that unmapped reads from RNA-Seq could be easily assembled into transcripts relating to many important genes present in the sequences of other mammals. Large portions of these transcripts did not have coding potential and, thus, can be considered as non-coding RNA. Moreover, reads that were not mapped to the reference genome but aligned to the entries in NCBI database of horse proteins were enriched for biological processes that largely correspond to the functions of organ from which RNA was isolated and thus are presumably true transcripts of genes associated with cell metabolism in those tissues. In addition, a portion of reads aligned to the common pathogenic or neutral microbiota, of which the most common was Brucella spp. These data suggest that unmapped reads can be an important target for in-depth analysis that may substantially enrich results of initial RNA-Seq experiments for various tissues and organs.
© 2022. The Author(s), under exclusive licence to Institute of Plant Genetics Polish Academy of Sciences.

Entities:  

Keywords:  Equine; Genome assembly; Misassembled; Transcriptome

Mesh:

Substances:

Year:  2022        PMID: 35670911     DOI: 10.1007/s13353-022-00705-z

Source DB:  PubMed          Journal:  J Appl Genet        ISSN: 1234-1983            Impact factor:   2.653


  30 in total

1.  Fast and sensitive protein alignment using DIAMOND.

Authors:  Benjamin Buchfink; Chao Xie; Daniel H Huson
Journal:  Nat Methods       Date:  2014-11-17       Impact factor: 28.547

2.  Generation of an equine biobank to be used for Functional Annotation of Animal Genomes project.

Authors:  E N Burns; M H Bordbari; M J Mienaltowski; V K Affolter; M V Barro; F Gianino; G Gianino; E Giulotto; T S Kalbfleisch; S A Katzman; M Lassaline; T Leeb; M Mack; E J Müller; J N MacLeod; B Ming-Whitfield; C R Alanis; T Raudsepp; E Scott; S Vig; H Zhou; J L Petersen; R R Bellone; C J Finno
Journal:  Anim Genet       Date:  2018-10-11       Impact factor: 3.169

Review 3.  Detecting and comparing non-coding RNAs in the high-throughput era.

Authors:  Giovanni Bussotti; Cedric Notredame; Anton J Enright
Journal:  Int J Mol Sci       Date:  2013-07-24       Impact factor: 5.923

4.  Brucella abortus: determination of survival times and evaluation of methods for detection in several matrices.

Authors:  Rene Kaden; Sevinc Ferrari; Tomas Jinnerot; Martina Lindberg; Tara Wahab; Moa Lavander
Journal:  BMC Infect Dis       Date:  2018-06-05       Impact factor: 3.090

5.  Uncovering missed indels by leveraging unmapped reads.

Authors:  Mohammad Shabbir Hasan; Xiaowei Wu; Liqing Zhang
Journal:  Sci Rep       Date:  2019-07-31       Impact factor: 4.379

6.  Whole-genome analyses resolve early branches in the tree of life of modern birds.

Authors:  Erich D Jarvis; Siavash Mirarab; Andre J Aberer; Bo Li; Peter Houde; Cai Li; Simon Y W Ho; Brant C Faircloth; Benoit Nabholz; Jason T Howard; Alexander Suh; Claudia C Weber; Rute R da Fonseca; Jianwen Li; Fang Zhang; Hui Li; Long Zhou; Nitish Narula; Liang Liu; Ganesh Ganapathy; Bastien Boussau; Md Shamsuzzoha Bayzid; Volodymyr Zavidovych; Sankar Subramanian; Toni Gabaldón; Salvador Capella-Gutiérrez; Jaime Huerta-Cepas; Bhanu Rekepalli; Kasper Munch; Mikkel Schierup; Bent Lindow; Wesley C Warren; David Ray; Richard E Green; Michael W Bruford; Xiangjiang Zhan; Andrew Dixon; Shengbin Li; Ning Li; Yinhua Huang; Elizabeth P Derryberry; Mads Frost Bertelsen; Frederick H Sheldon; Robb T Brumfield; Claudio V Mello; Peter V Lovell; Morgan Wirthlin; Maria Paula Cruz Schneider; Francisco Prosdocimi; José Alfredo Samaniego; Amhed Missael Vargas Velazquez; Alonzo Alfaro-Núñez; Paula F Campos; Bent Petersen; Thomas Sicheritz-Ponten; An Pas; Tom Bailey; Paul Scofield; Michael Bunce; David M Lambert; Qi Zhou; Polina Perelman; Amy C Driskell; Beth Shapiro; Zijun Xiong; Yongli Zeng; Shiping Liu; Zhenyu Li; Binghang Liu; Kui Wu; Jin Xiao; Xiong Yinqi; Qiuemei Zheng; Yong Zhang; Huanming Yang; Jian Wang; Linnea Smeds; Frank E Rheindt; Michael Braun; Jon Fjeldsa; Ludovic Orlando; F Keith Barker; Knud Andreas Jønsson; Warren Johnson; Klaus-Peter Koepfli; Stephen O'Brien; David Haussler; Oliver A Ryder; Carsten Rahbek; Eske Willerslev; Gary R Graves; Travis C Glenn; John McCormack; Dave Burt; Hans Ellegren; Per Alström; Scott V Edwards; Alexandros Stamatakis; David P Mindell; Joel Cracraft; Edward L Braun; Tandy Warnow; Wang Jun; M Thomas P Gilbert; Guojie Zhang
Journal:  Science       Date:  2014-12-12       Impact factor: 47.728

7.  Full-length transcriptome assembly from RNA-Seq data without a reference genome.

Authors:  Manfred G Grabherr; Brian J Haas; Moran Yassour; Joshua Z Levin; Dawn A Thompson; Ido Amit; Xian Adiconis; Lin Fan; Raktima Raychowdhury; Qiandong Zeng; Zehua Chen; Evan Mauceli; Nir Hacohen; Andreas Gnirke; Nicholas Rhind; Federica di Palma; Bruce W Birren; Chad Nusbaum; Kerstin Lindblad-Toh; Nir Friedman; Aviv Regev
Journal:  Nat Biotechnol       Date:  2011-05-15       Impact factor: 54.908

8.  Multiple secretoglobin 1A1 genes are differentially expressed in horses.

Authors:  Olivier Côté; Brandon N Lillie; Michael Anthony Hayes; Mary Ellen Clark; Laura van den Bosch; Paula Katavolos; Laurent Viel; Dorothee Bienzle
Journal:  BMC Genomics       Date:  2012-12-19       Impact factor: 3.969

9.  Detection and quantification of mitochondrial DNA deletions from next-generation sequence data.

Authors:  Colleen M Bosworth; Sneha Grandhi; Meetha P Gould; Thomas LaFramboise
Journal:  BMC Bioinformatics       Date:  2017-10-16       Impact factor: 3.169

10.  A new method for long-read sequencing of animal mitochondrial genomes: application to the identification of equine mitochondrial DNA variants.

Authors:  Sophie Dhorne-Pollet; Eric Barrey; Nicolas Pollet
Journal:  BMC Genomics       Date:  2020-11-11       Impact factor: 3.969

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