Characterization of the human ESC transcriptome by hybrid sequencing

Although transcriptional and posttranscriptional events are detected in RNA-Seq data from second-generation sequencing, fulllength mRNA isoforms are not captured. On the other hand, thirdgeneration sequencing, which yields much longer reads, has current limitations of lower raw accuracy and throughput. Here, we combine second-generation sequencing and third-generation sequencing with a custom-designed method for isoform identification and quantification to generate a high-confidence isoform dataset for human embryonic stem cells (hESCs). We report 8,084 RefSeq-annotated isoforms detected as full-length and an additional 5,459 isoforms predicted through statistical inference. Over one-third of these are novel isoforms, including 273 RNAs from gene loci that have not previously been identified. Further characterization of the novel loci indicates that a subset is expressed in pluripotent cells but not in diverse fetal and adult tissues; moreover, their reduced expression perturbs the network of pluripotency- associated genes. Results suggest that gene identification, even in well-characterized human cell lines and tissues, is likely far from complete

The impacts of tobacco control legislation on public view of e-cigarette usage in Macao—The co-word analysis of Macao daily

IntroductionMacao has been certified as a “Healthy City” by the World Health Organization, and has been adhering to the principle of combining prevention with proper medical care to build its medical system. As tobacco epidemic is a risk factor leading to a series of non-communicable diseases, the Macao SAR Government has continuously improved tobacco control measures.MethodsThe data for this study were derived from a news report on “e-cigarettes” published in Macao Daily. Co-word analysis and thematic analysis were conducted to analyze the development of tobacco control legislation against e-cigarettes. Co-word analysis examined the association and frequency of keywords, while thematic analysis identified prevalent themes within the data.ResultsThe study identified three stages of legislation against e-cigarettes: the pre-implementation stage, the early implementation stage, and the epidemic period. Each stage exhibited distinct characteristics and attention toward specific groups, particularly “teenagers” and “students,” increased significantly. Thematic analysis further highlighted the potential issues of drug use and smuggling associated with e-cigarettes.DiscussionThe findings suggest that the Macao SAR Government should prioritize the development of healthy behaviors among adolescents in the context of e-cigarette control. Additionally, considering regional cooperation to promote the “Healthy Bay Area” could be beneficial. Social media platforms and effective data management should be utilized as tools in these efforts

Systematic assessment of long-read RNA-seq methods for transcript identification and quantification

The Long-read RNA-Seq Genome Annotation Assessment Project (LRGASP) Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. The consortium generated over 427 million long-read sequences from cDNA and direct RNA datasets, encompassing human, mouse, and manatee species, using different protocols and sequencing platforms. These data were utilized by developers to address challenges in transcript isoform detection and quantification, as well as de novo transcript isoform identification. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. When aiming to detect rare and novel transcripts or when using reference-free approaches, incorporating additional orthogonal data and replicate samples are advised. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis

Neurodegeneration of the retina in mouse models of Alzheimer’s disease: what can we learn from the retina?

Alzheimer’s disease (AD) is an age-related progressive neurodegenerative disease commonly found among elderly. In addition to cognitive and behavioral deficits, vision abnormalities are prevalent in AD patients. Recent studies investigating retinal changes in AD double-transgenic mice have shown altered processing of amyloid precursor protein and accumulation of β-amyloid peptides in neurons of retinal ganglion cell layer (RGCL) and inner nuclear layer (INL). Apoptotic cells were also detected in the RGCL. Thus, the pathophysiological changes of retinas in AD patients are possibly resembled by AD transgenic models. The retina is a simple model of the brain in the sense that some pathological changes and therapeutic strategies from the retina may be observed or applicable to the brain. Furthermore, it is also possible to advance our understanding of pathological mechanisms in other retinal degenerative diseases. Therefore, studying AD-related retinal degeneration is a promising way for the investigation on (1) AD pathologies and therapies that would eventually benefit the brain and (2) cellular mechanisms in other retinal degenerations such as glaucoma and age-related macular degeneration. This review will highlight the efforts on retinal degenerative research using AD transgenic mouse models

A structure-based comparative proteomics study of protein family and function in bacillus anthracis

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A comparative evaluation of hybrid error correction methods for error-prone long reads

Abstract Background Third-generation sequencing technologies have advanced the progress of the biological research by generating reads that are substantially longer than second-generation sequencing technologies. However, their notorious high error rate impedes straightforward data analysis and limits their application. A handful of error correction methods for these error-prone long reads have been developed to date. The output data quality is very important for downstream analysis, whereas computing resources could limit the utility of some computing-intense tools. There is a lack of standardized assessments for these long-read error-correction methods. Results Here, we present a comparative performance assessment of ten state-of-the-art error-correction methods for long reads. We established a common set of benchmarks for performance assessment, including sensitivity, accuracy, output rate, alignment rate, output read length, run time, and memory usage, as well as the effects of error correction on two downstream applications of long reads: de novo assembly and resolving haplotype sequences. Conclusions Taking into account all of these metrics, we provide a suggestive guideline for method choice based on available data size, computing resources, and individual research goals

A Statistical Method for Observing Personal Diploid Methylomes and Transcriptomes with Single-Molecule Real-Time Sequencing

We address the problem of observing personal diploid methylomes, CpG methylome pairs of homologous chromosomes that are distinguishable with respect to phased heterozygous variants (PHVs), which is challenging due to scarcity of PHVs in personal genomes. Single molecule real-time (SMRT) sequencing is promising as it outputs long reads with CpG methylation information, but a serious concern is whether reliable PHVs are available in erroneous SMRT reads with an error rate of ∼15%. To overcome the issue, we propose a statistical model that reduces the error rate of phasing CpG site to 1%, thereby calling CpG hypomethylation in each haplotype with >90% precision and sensitivity. Using our statistical model, we examined GNAS complex locus known for a combination of maternally, paternally, or biallelically expressed isoforms, and observed allele-specific methylation pattern almost perfectly reflecting their respective allele-specific expression status, demonstrating the merit of elucidating comprehensive personal diploid methylomes and transcriptomes