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Cha, S. W.

Publications and source records attributed to Cha, S. W..

2 recordsLinked to original sources

Proteogenomic annotation of the Chinese hamster reveals extensive novel translation events and endogenous retroviral elements

A high quality genome annotation greatly facilitates successful cell line engineering. Standard draft genome annotation pipelines are based largely on de novo gene prediction, homology, and RNA-Seq data. However, draft annotations can suffer from incorrectly predictions of translated sequence, incorrect splice isoforms and missing genes. Here we generated a draft annotation for the newly assembled Chinese hamster genome and used RNA-Seq, proteomics, and Ribo-Seq to experimentally annotate the genome. We identified 4,333 new proteins compared to the hamster RefSeq protein annotation and 2,503 novel translational events (e.g., alternative splices, mutations, novel splices). Finally, we used this pipeline to identify the source of translated retroviruses contaminating recombinant products from Chinese hamster ovary (CHO) cell lines, including 131 type-C retroviruses, thus enabling future efforts to eliminate retroviruses by reducing the costs incurred with retroviral particle clearance. In summary, the improved annotation provides a more accurate platform for guiding CHO cell line engineering, including facilitating the interpretation of omics data, defining of cellular pathways, and engineering of complex phenotypes.

bioinformatics↗

The antibody repertoire of colorectal cancer

3Immunotherapy is becoming increasingly important in the fight against cancers, utilizing and manipulating the bodys immune response to treat tumors. Understanding the immune repertoire - the collection of immunological proteins - of treated and untreated cells is possible at the genomic, but technically difficult at the protein level. Standard protein databases do not include the highly divergent sequences of somatic rearranged immunoglobulin genes, and may lead to missed identifications in a mass spectrometry search. We introduce a novel proteogenomic approach, AbScan, to identify these highly variable antibody peptides, by developing a customized antibody database construction method using RNA-seq reads aligned to immunoglobulin (Ig) genes.\n\nAbScan starts by filtering transcript (RNA-seq) reads that match the template for Ig genes. The retained reads are used to construct a repertoire graph using the split de Bruijn graph: a graph structure that improves upon the standard de Bruijn graph to capture the high diversity of Ig genes in a compact manner. AbScan corrects for sequencing errors, and converts the graph to a format suitable for searching with MS/MS search tools. We used AbScan to create an antibody database from 90 RNA-seq colorectal tumor samples. Next, we used proteogenomics analysis to search MS/MS spectra of matched colorectal samples from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) against the AbScan generated database. AbScan identified 1, 940 distinct antibody peptides. Correlating with previously identified Single Amino-Acid Variants (SAAVs) in the tumor samples, we identified 163 pairs (antibody peptide, SAAV) with significant co-occurrence pattern in the 90 samples. The presence of co-expressed antibody and mutated peptides was correlated with survival time of the individuals. Our results suggest that AbScan(https://github.com/csw407/AbScan.git) is an effective tool for a proteomic exploration of the immune response in cancers.\n\n\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@62001corg.highwire.dtl.DTLVardef@1f542faorg.highwire.dtl.DTLVardef@10048d0org.highwire.dtl.DTLVardef@1ac5a75org.highwire.dtl.DTLVardef@66db0f_HPS_FORMAT_FIGEXP M_TBL C_TBL

bioinformatics↗