Revealing Missing Human Protein Isoforms Based on Ab Initio Prediction, RNA-seq and Proteomics

Hu, Zhiqiang; Scott, Hamish S.; Qin, Guangrong; Zheng, Guangyong; Chu, Xixia; Xie, Lu; Adelson, David L.; Oftedal, Bergithe E.; Venugopal, Parvathy; Babic, Milena; Hahn, Christopher; Zhang, Bing; Wang, Xiaojing; Li, Nan; Wei, Chaochun

doi:10.1038/srep10940

Cited by 54 publications

(22 citation statements)

References 67 publications

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“…In one project, ab initio gene prediction was used to generate a set of 8 million candidate transcripts. Subsequent filtering and validation by 26 RNA‐seq data sets and shotgun proteomics revealed 36 novel proteins and more than 31 000 new transcripts . For generating the intropolis resource, this approach was taken even further .…”

Section: Is There Consensus On the Low‐hanging Fruits?mentioning

confidence: 99%

The Protein‐Coding Human Genome: Annotating High‐Hanging Fruits

et al. 2019

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The major transcript variants of human protein-coding genes are annotated to a certain degree of accuracy combining manual curation, transcript data, and proteomics evidence. However, there is considerable disagreement on the annotation of about 2000 genes-they can be protein-coding, noncoding, or pseudogenes-and on the annotation of most of the predicted alternative transcripts. Pure transcriptome mapping approaches seem to be limited in discriminating functional expression from noise. These limitations have partially been overcome by dedicated algorithms to detect alternative spliced micro-exons and wobble splice variants. Recently, knowledge about splice mechanism and protein structure are incorporated into an algorithm to predict neighboring homologous exons, often spliced in a mutually exclusive manner. Predicted exons are evaluated by transcript data, structural compatibility, and evolutionary conservation, revealing hundreds of novel coding exons and splice mechanism re-assignments. The emerging human pan-genome is necessitating distinctive annotations incorporating differences between individuals and between populations.

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Section: Is There Consensus On the Low‐hanging Fruits?mentioning

confidence: 99%

The Protein‐Coding Human Genome: Annotating High‐Hanging Fruits

et al. 2019

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“…Alternative splicing is common, some 95% of multiexon genes could undergo alternative splicing [119][120][121], but it is unclear how many forms are biologically relevant as many of them are extremely rare, restrained to a few cell types and may thus not be the explanation for the majority of complexity of proteome [122]. Combined RNA sequencing and proteomics data along with bioinformatic predictions indicated 72% of human genes to have alternative splice forms that could be translated to proteins [123]. Analysis of functionally distinct splice forms in over 700 human and mouse genes, biased towards literature notions of alternative splicing, indicated that just a small fraction of the transcripts was functionally distinct [124].…”

Section: Protein-coding Rnamentioning

confidence: 99%

Systematics for types and effects of RNA variations

Vihinen

2020

RNA Biology

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Systematics is described for annotation of variations in RNA molecules. The conceptual framework is part of Variation Ontology (VariO) and facilitates depiction of types of variations, their functional and structural effects and other consequences in any RNA molecule in any organism. There are more than 150 RNA related VariO terms in seven levels, which can be further combined to generate even more complicated and detailed annotations. The terms are described together with examples, usually for variations and effects in human and in diseases. RNA variation type has two subcategories: variation classification and origin with subterms. Altogether six terms are available for function description. Several terms are available for affected RNA properties. The ontology contains also terms for structural description for affected RNA type, post-transcriptional RNA modifications, secondary and tertiary structure effects and RNA sugar variations. Together with the DNA and protein concepts and annotations, RNA terms allow comprehensive description of variations of genetic and non-genetic origin at all possible levels. The VariO annotations are readable both for humans and computer programs for advanced data integration and mining.

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“…Most often, transcriptomics studies focus on the expression of protein-coding genes. However, the human transcriptome also includes non-coding RNA, and may contain up to 350,000 different transcripts [ 94 ]. Gene expression data from published transcriptomics studies are generally deposited in the public data repositories Gene Expression Omnibus ( http://www.ncbi.nlm.nih.gov/geo/ ) or Array Express ( https://www.ebi.ac.uk/arrayexpress/ ).…”

Section: Box 1 High-throughput Technologies To Profile the Host Respomentioning

confidence: 99%

Diagnostic ‘omics’ for active tuberculosis

Haas

Roe

Pollara

et al. 2016

BMC Med

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The decision to treat active tuberculosis (TB) is dependent on microbiological tests for the organism or evidence of disease compatible with TB in people with a high demographic risk of exposure. The tuberculin skin test and peripheral blood interferon-γ release assays do not distinguish active TB from a cleared or latent infection. Microbiological culture of mycobacteria is slow. Moreover, the sensitivities of culture and microscopy for acid-fast bacilli and nucleic acid detection by PCR are often compromised by difficulty in obtaining samples from the site of disease. Consequently, we need sensitive and rapid tests for easily obtained clinical samples, which can be deployed to assess patients exposed to TB, discriminate TB from other infectious, inflammatory or autoimmune diseases, and to identify subclinical TB in HIV-1 infected patients prior to commencing antiretroviral therapy. We discuss the evaluation of peripheral blood transcriptomics, proteomics and metabolomics to develop the next generation of rapid diagnostics for active TB. We catalogue the studies published to date seeking to discriminate active TB from healthy volunteers, patients with latent infection and those with other diseases. We identify the limitations of these studies and the barriers to their adoption in clinical practice. In so doing, we aim to develop a framework to guide our approach to discovery and development of diagnostic biomarkers for active TB.

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Revealing Missing Human Protein Isoforms Based on Ab Initio Prediction, RNA-seq and Proteomics

Cited by 54 publications

References 67 publications

The Protein‐Coding Human Genome: Annotating High‐Hanging Fruits

The Protein‐Coding Human Genome: Annotating High‐Hanging Fruits

Systematics for types and effects of RNA variations

Diagnostic ‘omics’ for active tuberculosis

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