Genome of the Single Human Chromosome 18 as a "Gold Standard" for Its Transcriptome

Gene-centric coverage of the human liver transcriptome: QPCR, Illumina, and Oxford Nanopore RNA-Seq

It has been shown that the best coverage of the HepG2 cell line transcriptome encoded by genes of a single chromosome, chromosome 18, is achieved by a combination of two sequencing platforms, Illumina RNA-Seq and Oxford Nanopore Technologies (ONT), using cut-off levels of FPKM > 0 and TPM > 0, respectively. In this study, we investigated the extent to which the combination of these transcriptomic analysis methods makes it possible to achieve a high coverage of the transcriptome encoded by the genes of other human chromosomes. A comparative analysis of transcriptome coverage for various types of biological material was carried out, and the HepG2 cell line transcriptome was compared with the transcriptome of liver tissue cells. In addition, the contribution of variability in the coverage of expressed genes in human transcriptomes to the creation of a draft human transcriptome was evaluated. For human liver tissues, ONT makes an extremely insignificant contribution to the overall coverage of the transcriptome. Thus, to ensure maximum coverage of the liver tissue transcriptome, it is sufficient to apply only one technology: Illumina RNA-Seq (FPKM > 0).

Number of Detected Proteins as the Function of the Sensitivity of Proteomic Technology in Human Liver Cells

Aims:

The main goal of the Russian part of C-HPP is to detect and functionally annotate missing proteins (PE2-PE4) encoded by human chromosome 18. To achieve this goal, it is necessary to use the most sensitive methods of analysis.

Background:

However, identifying such proteins in a complex biological mixture using mass spectrometry (MS)-based methods is difficult due to the insufficient sensitivity of proteomic analysis methods. A possible solution to the problem is the pre-fractionation of a complex biological sample at the sample preparation stage.

Objective:

This study aims to measure the detection limit of SRM SIS analysis using a standard set of UPS1 proteins and find a way to enhance the sensitivity of the analysis and to, detect proteins encoded by the human chromosome 18 in liver tissue samples, and compare the data with transcriptomic analysis of the same samples.

Methods:

Mass spectrometry, data-dependent acquisition, selected reaction monitoring, highperformance liquid chromatography, data-dependent acquisition in combination with pre-fractionation by alkaline reversed-phase chromatography, selected reaction monitoring in combination with prefractionation by alkaline reversed-phase chromatography methods were used in this study.

Results:

The results revealed that 100% of UPS1 proteins in a mixture could only be identified at a concentration of at least 10-9 М. The decrease in concentration leads to protein losses associated with technology sensitivity, and no UPS1 protein is detected at a concentration of 10-13 М. Therefore, the two-dimensional fractionation of samples was applied to improve sensitivity. The human liver tissue was examined by selected reaction monitoring and shotgun methods of MS analysis using onedimensional and two-dimensional fractionation to identify the proteins encoded by human chromosome 18. A total of 134 proteins were identified. The overlap between proteomic and transcriptomic data in human liver tissue was ~50%.

Conclusion:

The sample concentration technique is well suited for a standard UPS1 system that is not contaminated with a complex biological sample. However, it is not suitable for use with a complex biological protein mixture. Thus, it is necessary to develop more sophisticated fractionation systems for the detection of all low-copy proteins. This weak convergence is due to the low sensitivity of proteomic technology compared to transcriptomic approaches. Also, total mRNA was used to perform RNA-seq analysis, but not all detected mRNA molecules could be translated into proteins. This introduces additional uncertainty in the data; in the future, we plan to study only translated mRNA molecules-the translatome. Data is available via ProteomeXchange with identifier PXD026997.

DNA sequencing: an overview of solid-state and biological nanopore-based methods

The field of sequencing is a topic of significant interest since its emergence and has become increasingly important over time. Impressive achievements have been obtained in this field, especially in relations to DNA and RNA sequencing. Since the first achievements by Sanger and colleagues in the 1950s, many sequencing techniques have been developed, while others have disappeared. DNA sequencing has undergone three generations of major evolution. Each generation has its own specifications that are mentioned briefly. Among these generations, nanopore sequencing has its own exciting characteristics that have been given more attention here. Among pioneer technologies being used by the third-generation techniques, nanopores, either biological or solid-state, have been experimentally or theoretically extensively studied. All sequencing technologies have their own advantages and disadvantages, so nanopores are not free from this general rule. It is also generally pointed out what research has been done to overcome the obstacles. In this review, biological and solid-state nanopores are elaborated on, and applications of them are also discussed briefly.

[PCR analysis of the expression of chromosome 18 genes in human liver tissue: interindividual variability]

Using human chromosome 18 (Ch18) genes as an example, a PCR analysis of the interindividual variability of gene expression in liver tissue was performed. Although the quantitative profiles of the Ch18 transcriptome, expressed in the number of cDNA copies per single cell, showed a high degree of correlation between donors (Pearson correlation coefficients ranged from 0.963 to 0.966), the expression of the significant number of genes (from 13% to 19%, depending on the method of experimental data normalization) varied by more than 4-fold when comparing donors pairwise. At the same time, the proportion of differentially expressed genes increased with a decrease in the level of their expression. It is shown that the higher quantitative variability of low-abundance transcripts is mainly not technical, but biological. Bioinformatic analysis of the interindividual variability of the differential expression of chromosome 18 genes in human liver tissue did not reveal any statistically significant groups of genes related to certain biological processes that indicated a rather transient nature of the interindividual variability of their expression, probably reflecting the response of cells of an individual to specific external stimuli.

Oxford Nanopore MinION Direct RNA-Seq for Systems Biology

Long-read direct RNA sequencing developed by Oxford Nanopore Technologies (ONT) is quickly gaining popularity for transcriptome studies, while fast turnaround time and low cost make it an attractive instrument for clinical applications. There is a growing interest to utilize transcriptome data to unravel activated biological processes responsible for disease progression and response to therapies. This trend is of particular interest for precision medicine which aims at single-patient analysis. Here we evaluated whether gene abundances measured by MinION direct RNA sequencing are suited to produce robust estimates of pathway activation for single sample scoring methods. We performed multiple RNA-seq analyses for a single sample that originated from the HepG2 cell line, namely five ONT replicates, and three replicates using Illumina NovaSeq. Two pathway scoring methods were employed-ssGSEA and singscore. We estimated the ONT performance in terms of detected protein-coding genes and average pairwise correlation between pathway activation scores using an exhaustive computational scheme for all combinations of replicates. In brief, we found that at least two ONT replicates are required to obtain reproducible pathway scores for both algorithms. We hope that our findings may be of interest to researchers planning their ONT direct RNA-seq experiments.

Analyzing Modern Biomolecules: The Revolution of Nucleic-Acid Sequencing - Review

Recent developments have revolutionized the study of biomolecules. Among them are molecular markers, amplification and sequencing of nucleic acids. The latter is classified into three generations. The first allows to sequence small DNA fragments. The second one increases throughput, reducing turnaround and pricing, and is therefore more convenient to sequence full genomes and transcriptomes. The third generation is currently pushing technology to its limits, being able to sequence single molecules, without previous amplification, which was previously impossible. Besides, this represents a new revolution, allowing researchers to directly sequence RNA without previous retrotranscription. These technologies are having a significant impact on different areas, such as medicine, agronomy, ecology and biotechnology. Additionally, the study of biomolecules is revealing interesting evolutionary information. That includes deciphering what makes us human, including phenomena like non-coding RNA expansion. All this is redefining the concept of gene and transcript. Basic analyses and applications are now facilitated with new genome editing tools, such as CRISPR. All these developments, in general, and nucleic-acid sequencing, in particular, are opening a new exciting era of biomolecule analyses and applications, including personalized medicine, and diagnosis and prevention of diseases for humans and other animals.