A comparison of mRNA sequencing (RNA-Seq) library preparation methods for transcriptome analysis

RNA Sequencing Protocols for Short-Read Sequencing

RNA sequencing (RNA-seq) methodologies allow the discovery of novel variants and transcripts. These comprise three general steps: (1) capture of RNA species of interest, (2) conversion of RNA to complementary DNA (cDNA), and (3) modification of cDNA to fit the sequencing platform. Here we describe four different library preparation protocols for short-read sequencing: cDNA synthesis with poly(A) selection, library preparation with ribosomal depletion, and cDNA synthesis with SMART® (Switching Mechanism at 5' end of RNA Template) technology for low and Pico inputs.

Identification and expression dynamics of CYPome across different developmental stages of Maconellicoccus hirsutus (Green)

Maconellicoccus hirsutus is a highly polyphagous insect pest, posing a substantial threat to various crop sp., especially in the tropical and sub-tropical regions of the world. While extensive physiological and biological studies have been conducted on this pest, the lack of genetic information has hindered our understanding of the molecular mechanisms underlying its growth, development, and xenobiotic metabolism. The Cytochrome P450 gene, a member of the CYP gene superfamily ubiquitous in living organisms is associated with growth, development, and the metabolism of both endogenous and exogenous substances, contributing to the insect's adaptability in diverse environments. To elucidate the specific role of the CYP450 gene family in M. hirsutus which has remained largely unexplored, a de novo transcriptome assembly of the pink mealybug was constructed. A total of 120 proteins were annotated as CYP450 genes through homology search of the predicted protein sequences across different databases. Phylogenetic studies resulted in categorizing 120 CYP450 genes into four CYP clans. A total of 22 CYP450 families and 30 subfamilies were categorized, with CYP6 forming the dominant family. The study also revealed five genes (Halloween genes) associated with the insect hormone biosynthesis pathway. Further, the expression of ten selected CYP450 genes was studied using qRT-PCR across crawler, nymph, and adult stages, and identified genes that were expressed at specific stages of the insects. Thus, the findings of this study reveal the expression dynamics and possible function of the CYP450 gene family in the growth, development, and adaptive strategies of M. hirsutus which can be further functionally validated.

A reliable and quick method for screening alternative splicing variants for low-abundance genes

Alternative splicing (AS) is a universal phenomenon in eukaryotes, and it is still challenging to identify AS events. Several methods have been developed to identify AS events, such as expressed sequence tags (EST), microarrays and RNA-seq. However, EST has limitations in identifying low-abundance genes, while microarray and RNA-seq are high-throughput technologies, and PCR-based technology is needed for validation. To overcome the limitations of EST and shortcomings of high-throughput technologies, we established a method to identify AS events, especially for low-abundance genes, by reverse transcription (RT) PCR with gene-specific primers (GSPs) followed by nested PCR. This process includes two major steps: 1) the use of GSPs to amplify as long as the specific gene segment and 2) multiple rounds of nested PCR to screen the AS and confirm the unknown splicing variants. With this method, we successfully identified three new splicing variants, namely, GenBank Accession No. HM623886 for the bdnf gene (GenBank GeneID: 12064), GenBank Accession No. JF417977 for the trkc gene (GenBank GeneID: 18213) and GenBank Accession No. HM623888 for the glb-18 gene (GenBank GeneID: 172485). In addition to its reliability and simplicity, the method is also cost-effective and labor-intensive. In conclusion, we developed an RT-nested PCR method using gene-specific primers to efficiently identify known and novel AS variants. This approach overcomes the limitations of existing methods for detecting rare transcripts. By enabling the discovery of new isoforms, especially for low-abundance genes, this technique can aid research into aberrant splicing in disease. Future studies can apply this method to uncover AS variants involved in cancer, neurodegeneration, and other splicing-related disorders.

Comparison of RNA-Sequencing Methods for Degraded RNA

RNA sequencing (RNA-Seq) is a powerful technique and is increasingly being used in clinical research and drug development. Currently, several RNA-Seq methods have been developed. However, the relative advantage of each method for degraded RNA and low-input RNA, such as RNA samples collected in the field of clinical setting, has remained unknown. The Standard method of RNA-Seq captures mRNA by poly(A) capturing using Oligo dT beads, which is not suitable for degraded RNA. Here, we used three commercially available RNA-Seq library preparation kits (SMART-Seq, xGen Broad-range, and RamDA-Seq) using random primer instead of Oligo dT beads. To evaluate the performance of these methods, we compared the correlation, the number of detected expressing genes, and the expression levels with the Standard RNA-Seq method. Although the performance of RamDA-Seq was similar to that of Standard RNA-Seq, the performance for low-input RNA and degraded RNA has decreased. The performance of SMART-Seq was better than xGen and RamDA-Seq in low-input RNA and degraded RNA. Furthermore, the depletion of ribosomal RNA (rRNA) improved the performance of SMART-Seq and xGen due to increased expression levels. SMART-Seq with rRNA depletion has relative advantages for RNA-Seq using low-input and degraded RNA.

Identification of KRAS mutation-associated gut microbiota in colorectal cancer and construction of predictive machine learning model

Gut microbiota has demonstrated an increasingly important role in the onset and development of colorectal cancer (CRC). Nonetheless, the association between gut microbiota and KRAS mutation in CRC remains enigmatic. We conducted 16S rRNA sequencing on stool samples from 94 CRC patients and employed the linear discriminant analysis effect size algorithm to identify distinct gut microbiota between KRAS mutant and KRAS wild-type CRC patients. Transcriptome sequencing data from nine CRC patients were transformed into a matrix of immune infiltrating cells, which was then utilized to explore KRAS mutation-associated biological functions, including Gene Ontology items and Kyoto Encyclopedia of Genes and Genomes pathways. Subsequently, we analyzed the correlations among these KRAS mutation-associated gut microbiota, host immunity, and KRAS mutation-associated biological functions. At last, we developed a predictive random forest (RF) machine learning model to predict the KRAS mutation status in CRC patients, based on the gut microbiota associated with KRAS mutation. We identified a total of 26 differential gut microbiota between both groups. Intriguingly, a significant positive correlation was observed between Bifidobacterium spp. and mast cells, as well as between Bifidobacterium longum and chemokine receptor CX3CR1. Additionally, we also observed a notable negative correlation between Bifidobacterium and GOMF:proteasome binding. The RF model constructed using the KRAS mutation-associated gut microbiota demonstrated qualified efficacy in predicting the KRAS phenotype in CRC. Our study ascertained the presence of 26 KRAS mutation-associated gut microbiota in CRC and speculated that Bifidobacterium may exert an essential role in preventing CRC progression, which appeared to correlate with the upregulation of mast cells and CX3CR1 expression, as well as the downregulation of GOMF:proteasome binding. Furthermore, the RF model constructed on the basis of KRAS mutation-associated gut microbiota exhibited substantial potential in predicting KRAS mutation status in CRC patients.IMPORTANCEGut microbiota has emerged as an essential player in the onset and development of colorectal cancer (CRC). However, the relationship between gut microbiota and KRAS mutation in CRC remains elusive. Our study not only identified a total of 26 gut microbiota associated with KRAS mutation in CRC but also unveiled their significant correlations with tumor-infiltrating immune cells, immune-related genes, and biological pathways (Gene Ontology items and Kyoto Encyclopedia of Genes and Genomes pathways). We speculated that Bifidobacterium may play a crucial role in impeding CRC progression, potentially linked to the upregulation of mast cells and CX3CR1 expression, as well as the downregulation of GOMF:Proteasome binding. Furthermore, based on the KRAS mutation-associated gut microbiota, the RF model exhibited promising potential in the prediction of KRAS mutation status for CRC patients. Overall, the findings of our study offered fresh insights into microbiological research and clinical prediction of KRAS mutation status for CRC patients.

Maternal PM2.5 exposure is associated with preterm birth and gestational diabetes mellitus, and mitochondrial OXPHOS dysfunction in cord blood

Maternal exposure to fine particulate matter (PM2.5) is associated with adverse pregnancy and neonatal health outcomes. To explore the mechanism, we performed mRNA sequencing of neonatal cord blood. From an ongoing prospective cohort, Air Pollution on Pregnancy Outcome (APPO) study, 454 pregnant women from six centers between January 2021 and June 2022 were recruited. Individual PM2.5 exposure was calculated using a time-weighted average model. In the APPO study, age-matched cord blood samples from the High PM2.5 (˃15 ug/m3; n = 10) and Low PM2.5 (≤ 15 ug/m3; n = 30) groups were randomly selected for mRNA sequencing. After selecting genes with differential expression in the two groups (p-value < 0.05 and log2 fold change > 1.5), pathway enrichment analysis was performed, and the mitochondrial pathway was analyzed using MitoCarta3.0. The risk of preterm birth (PTB) increased with every 5 µg/m3 increase of PM2.5 in the second trimester (odds ratio 1.391, p = 0.019) after adjusting for confounding variables. The risk of gestational diabetes mellitus (GDM) increased in the second (odds ratio 1.238, p = 0.041) and third trimester (odds ratio 1.290, p = 0.029), and entire pregnancy (odds ratio 1.295, p = 0.029). The mRNA-sequencing of cord blood showed that genes related to mitochondrial activity (FAM210B, KRT1, FOXO4, TRIM58, and FBXO7) and PTB-related genes (ADIPOR1, YBX1, OPTN, NFkB1, HBG2) were upregulated in the High PM2.5 group. In addition, exposure to high PM2.5 affected mitochondrial oxidative phosphorylation (OXPHOS) and proteins in the electron transport chain, a subunit of OXPHOS. These results suggest that exposure to high PM2.5 during pregnancy may increase the risk of PTB and GDM, and dysregulate PTB-related genes. Alterations in mitochondrial OXPHOS by high PM2.5 exposure may occur not only in preterm infants but also in normal newborns. Further studies with larger sample sizes are required.

Next-Generation Sequencing Technology: Current Trends and Advancements

The advent of next-generation sequencing (NGS) has brought about a paradigm shift in genomics research, offering unparalleled capabilities for analyzing DNA and RNA molecules in a high-throughput and cost-effective manner. This transformative technology has swiftly propelled genomics advancements across diverse domains. NGS allows for the rapid sequencing of millions of DNA fragments simultaneously, providing comprehensive insights into genome structure, genetic variations, gene expression profiles, and epigenetic modifications. The versatility of NGS platforms has expanded the scope of genomics research, facilitating studies on rare genetic diseases, cancer genomics, microbiome analysis, infectious diseases, and population genetics. Moreover, NGS has enabled the development of targeted therapies, precision medicine approaches, and improved diagnostic methods. This review provides an insightful overview of the current trends and recent advancements in NGS technology, highlighting its potential impact on diverse areas of genomic research. Moreover, the review delves into the challenges encountered and future directions of NGS technology, including endeavors to enhance the accuracy and sensitivity of sequencing data, the development of novel algorithms for data analysis, and the pursuit of more efficient, scalable, and cost-effective solutions that lie ahead.

Transcriptome Sequencing of Agave amaniensis Reveals Shoot-Related Expression Patterns of Expansin A Genes in Agave

Agave species are widely planted for fiber production. However, the molecular basis of agave fiber development has not been well understood. In this study, we performed a transcriptomic analysis in A. amaniensi, a well-known variety with high-quality fiber production. Approximately 43.87 million clean reads were obtained using Illumina sequencing. The de novo assembly produced 66,746 unigrams, 54% of which were annotated in a public database. In the Nr database, 21,490 unigenes of A. amaniensis were shown to be most closely related to Asparagus officinalis. Nine expansin A orthologs with full coding regions were obtained, which were named EXP1a, EXP1b, EXP2, EXP3, EXP4a, EXP4b, EXP11, EXP12, and EXP13. The maximum likelihood phylogenetic tree revealed the species-specific expansion of expansin genes in Arabidopsis, rice and agave. The expression analysis suggested the negative correlation between the expression of expansin genes and the leaf growth rate, except AhEXP11. Moreover, expansin genes were differentially affected by abiotic and biotic stresses. Notably, AhEXP2 expression level was highly upgraded after the infection of Phytophthora nicotiana. Nutrient deficiency also influent expansin genes expression. Together, our research will benefit future studies related to fiber development, disease resistance and nutrient usage in agave.

Mosaic results after preimplantation genetic testing for aneuploidy may be accompanied by changes in global gene expression

Aneuploidy in preimplantation embryos is a major cause of human reproductive failure. Unlike uniformly aneuploid embryos, embryos diagnosed as diploid-aneuploid mosaics after preimplantation genetic testing for aneuploidy (PGT-A) can develop into healthy infants. However, the reason why these embryos achieve full reproductive competence needs further research. Current RNA sequencing techniques allow for the investigation of the human preimplantation transcriptome, providing new insights into the molecular mechanisms of embryo development. In this prospective study, using euploid embryo gene expression as a control, we compared the transcriptome profiles of inner cell mass and trophectoderm samples from blastocysts with different levels of chromosomal mosaicism. A total of 25 samples were analyzed from 14 blastocysts with previous PGT-A diagnosis, including five low-level mosaic embryos and four high-level mosaic embryos. Global gene expression profiles visualized in cluster heatmaps were correlated with the original PGT-A diagnosis. In addition, gene expression distance based on the number of differentially expressed genes increased with the mosaic level, compared to euploid controls. Pathways involving apoptosis, mitosis, protein degradation, metabolism, and mitochondrial energy production were among the most deregulated within mosaic embryos. Retrospective analysis of the duration of blastomere cell cycles in mosaic embryos revealed several mitotic delays compared to euploid controls, providing additional evidence of the mosaic status. Overall, these findings suggest that embryos with mosaic results are not simply a misdiagnosis by-product, but may also have a genuine molecular identity that is compatible with their reproductive potential.

The Transition from Cancer "omics" to "epi-omics" through Next- and Third-Generation Sequencing

Deciphering cancer etiopathogenesis has proven to be an especially challenging task since the mechanisms that drive tumor development and progression are far from simple. An astonishing amount of research has revealed a wide spectrum of defects, including genomic abnormalities, epigenomic alterations, disturbance of gene transcription, as well as post-translational protein modifications, which cooperatively promote carcinogenesis. These findings suggest that the adoption of a multidimensional approach can provide a much more precise and comprehensive picture of the tumor landscape, hence serving as a powerful tool in cancer research and precision oncology. The introduction of next- and third-generation sequencing technologies paved the way for the decoding of genetic information and the elucidation of cancer-related cellular compounds and mechanisms. In the present review, we discuss the current and emerging applications of both generations of sequencing technologies, also referred to as massive parallel sequencing (MPS), in the fields of cancer genomics, transcriptomics and proteomics, as well as in the progressing realms of epi-omics. Finally, we provide a brief insight into the expanding scope of sequencing applications in personalized cancer medicine and pharmacogenomics.