BackgroundWe present the first sequencing data using the combinatorial probe-anchor synthesis (cPAS)-based BGISEQ-500 sequencer. Applying cPAS, we investigated the repertoire of human small non-coding RNAs and compared it to other techniques.ResultsStarting with repeated measurements of different specimens including solid tissues (brain and heart) and blood, we generated a median of 30.1 million reads per sample. 24.1 million mapped to the human genome and 23.3 million to the miRBase. Among six technical replicates of brain samples, we observed a median correlation of 0.98. Comparing BGISEQ-500 to HiSeq, we calculated a correlation of 0.75. The comparability to microarrays was similar for both BGISEQ-500 and HiSeq with the first one showing a correlation of 0.58 and the latter one correlation of 0.6. As for a potential bias in the detected expression distribution in blood cells, 98.6% of HiSeq reads versus 93.1% of BGISEQ-500 reads match to the 10 miRNAs with highest read count. After using miRDeep2 and employing stringent selection criteria for predicting new miRNAs, we detected 74 high-likely candidates in the cPAS sequencing reads prevalent in solid tissues and 36 candidates prevalent in blood.ConclusionsWhile there is apparently no ideal platform for all challenges of miRNome analyses, cPAS shows high technical reproducibility and supplements the hitherto available platforms.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-016-0287-1) contains supplementary material, which is available to authorized users.

To develop a routine and effectual procedure of detecting bladder cancer (BlCa), an optimized combination of epigenetic biomarkers that work synergistically with high sensitivity and specificity is necessary. In this study, methylation levels of seven biomarkers (EOMES, GDF15, NID2, PCDH17, POU4F2, TCF21, and ZNF154) in 148 individuals—which including 58 urothelial cell carcinoma (UCC) patients, 20 infected urinary calculi (IUC) patients, 20 kidney cancer (KC) patients,20 prostate cancer (PC) patients, and 30 healthy volunteers (HV)—were quantified by qMSP using the urine sediment DNA. Receiver operating characteristic (ROC) curves were generated for each biomarker. The combining predictors of possible combinations were calculated through logistic regression model. Subsequently, ROC curves of the three best performing combinations were constructed. Then, we validated the three best performing combinations and POU4F2 in another 72 UCC, 21 IUC, 26 KC and 22 PC, and 23 HV urine samples. The combination of POU4F2/PCDH17 has yielded the highest sensitivity and specificity of 90.00% and 93.96% in all the 312 individuals, showing the capability of detecting BlCa effectively among pathologically varied sample groups.

Evidence from the meta-analysis of randomized controlled trials suggested that hepatic resection might improve the overall survival and recurrence-free survival in small HCC patients, whereas increase the complications and hospitalization duration. However, this conclusion should be explained with caution, due to the absence of further subgroup analysis with respect to the outcome in patients with different tumor size (<3 and 3 to 5 cm).

Background RNA-Seq data is inherently nonuniform for different transcripts because of differences in gene expression. This makes it challenging to decide how much data should be generated from each sample. How much should one spend to recover the less expressed transcripts? The sequencing technology used is another consideration, as there are inevitably always biases against certain sequences. To investigate these effects, we first looked at high-depth libraries from a set of well-annotated organisms to ascertain the impact of sequencing depth on de novo assembly. We then looked at libraries sequenced from the Universal Human Reference RNA (UHRR) to compare the performance of Illumina HiSeq and MGI DNBseq™ technologies. Results On the issue of sequencing depth, the amount of exomic sequence assembled plateaued using data sets of approximately 2 to 8 Gbp. However, the amount of genomic sequence assembled did not plateau for many of the analyzed organisms. Most of the unannotated genomic sequences are single-exon transcripts whose biological significance will be questionable for some users. On the issue of sequencing technology, both of the analyzed platforms recovered a similar number of full-length transcripts. The missing “gap” regions in the HiSeq assemblies were often attributed to higher GC contents, but this may be an artefact of library preparation and not of sequencing technology. Conclusions Increasing sequencing depth beyond modest data sets of less than 10 Gbp recovers a plethora of single-exon transcripts undocumented in genome annotations. DNBseq™ is a viable alternative to HiSeq for de novo RNA-Seq assembly.

Bladder cancer (BC) is distinguished by high rate of recurrence after surgery, but the underlying mechanisms remain poorly understood. Here we performed the wholeexome sequencing of 37 BC individuals including 20 primary and 17 recurrent samples in which the primary and recurrent samples were not from the same patient. We uncovered that MLL, EP400, PRDM2, ANK3 and CHD5 exclusively altered in recurrent BCs. Specifically, the recurrent BCs and bladder cancer cells with MLL mutation displayed increased histone H3 tri-methyl K4 (H3K4me3) modification in tissue and cell levels and showed enhanced expression of GATA4 and ETS1 downstream. What's more, MLL mutated bladder cancer cells obtained with CRISPR/Cas9 showed increased ability of drug-resistance to epirubicin (a chemotherapy drug for bladder cancer) than wild type cells. Additionally, the BC patients with high expression of GATA4 and ETS1 significantly displayed shorter lifespan than patients with low expression. Our study provided an overview of the genetic basis of recrudescent bladder cancer and discovered that genetic alterations of MLL were involved in BC relapse. The increased modification of H3K4me3 and expression of GATA4 and ETS1 would be the promising targets for the diagnosis and therapy of relapsed bladder cancer.