Tang, W. — Page 10 | Search bioRxiv

bioRxiv2016

Tumor Origin Detection with Tissue-Specific miRNA and DNA methylation Markers

MotivationCancer of unknown primary origin constitutes 3-5% of all human malignancies. Patients with these carcinomas present with metastases without an established primary site, which may not be found even by thorough histological search methods. Patients with cancer of unknown primary origin always have poor prognosis and hardly have efficient treatment since most cancers respond well to specific chemotherapy or hormone drugs. Many studies have proposed classifiers based on miRNAs or mRNAs to predict the tumor origins, but few study focus on high-dimensional DNA methylation profiles.\n\nResultsWe introduced three classifiers with novel feature selection algorithm combined with random forest to effectively identify highly tissue-specific epigenetics biomarkers such as microRNAs and CpG sites, which can help us predict the origin site of tumors. This algorithm, incorporating differential analysis and descending dimension algorithm, was applied on 14 histological tissues and over 5000 samples based on miRNA expression and DNA methylation profiles to assign given primary tumor to its origin tissue. Our study shows all of these three classifiers have an overall accuracy of 87.78% (72.55%-97.54%) based on miRNA datasets and an accuracy of 96.43% (MRMD: 87.85%-99.76%) or 97.06% (PCA: 92.44%-100%) based on DNA methylation datasets on predicting the origin of tumors and suggests that the biomarkers we selected can efficiently predict the origin of tumors and allow the clinicians to avoid adjuvant systemic therapy or to choose less aggressive therapeutic options. We also developed a user-friendly webserver which enables users to predict the origin site of tumors by uploading the miRNAs expression or DNA methylation profiles of those cancers.\n\nAvailabilityThe webserver, data, and code are accessible free of charge at http://server.malab.cn/MMCOP/\n\nContactzouquan@nclab.net\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2016

Contribution of mobile elements to the uniqueness of human genome with more than 15,000 human-specific insertions

Mobile elements (MEs) collectively constituted to at least 51% of the human genome. Due to their past incremental accumulation and ongoing DNA transposition of members from certain subfamilies, MEs serve as a significant source for both inter- and intra-species genetic diversity during primate and human evolution. Since MEs can exert direct impact on gene function via a plethora of mechanism, it is believed that the ME-derived genetic diversity has contributed to the phenotypic differences between human and non-human primates, as well as among human populations and individuals. To define the specific contribution of MEs in making Human sapiens as a biologically unique species, we aim to compile a complete list of MEs that are only uniquely present in the human genome, i.e., human-specific MEs (HS-MEs).\n\nBy making use of the most recent reference genome sequences for human and many other primates and a unbiased more robust and integrative multi-way comparative genomic approach, we identified a total of 15,463 HS-MEs. This list of HS-MEs represents a 120% increase from prior studies with over 8,000 being newly identified as HS-MEs. Collectively, these ~15,000 HS-MEs have contributed to a total of 15 million base pair (Mbp) sequence increase through insertion, generation of target site duplications, and transductions, as well as a 0.5 Mbp sequence loss via insertion- mediated deletions, leading to a net total of 14.5 Mbp genome size increase. Other new observations made with these HS-MEs include: 1) identification of several additional ME subfamilies with significant transposition activities not visible with prior smaller datasets (e.g. L1HS, L1PA2, and HERV-K); 2) A clear similarity of the retrotransposition mechanism among L1, Alus, and SVAs that is distinct from HERVs based on the pre- integration site sequence motifs; 3) Y-chromosome as a strikingly hot target for HS-MEs, particularly for LTRs, which showed an insertion rate 15 times higher than the genome average; 4) among the ME types, SVAs seem to show a very strong bias in inserting into existing SVAs. Among the HS-MEs, more than 8,000 elements were integrated into the vicinity of ~4900 unique genes, in regions including CDS, untranslated exon regions, promoters, and introns of protein coding genes, as well as promoters and exons of non- coding RNAs. In seven cases, MEs participate in protein coding. Furthermore, 1,213 HS-MEs contributed to a total of 3,124 experimentally identified binding sites for 146 of the 161 transcriptional factors in association with 622 genes. All these data suggest that these HS-MEs, despite being very young, already showed sufficient sign for their participation in gene function via regulation of transcription, splicing, and protein coding, with more potential for future participation.\n\nIn conclusion, our results demonstrate that the amount of MEs uniquely occurred in the human genome is much higher than previously known, and we predict that the same is true regarding their impact on human genome evolution and function. The comprehensive list of HS-MEs provides an important reference resource for studying the impact of DNA transposition in human genome evolution and gene function.

evolutionary biology↗