Accurate Classification of Differential Expression Patterns in a Bayesian Framework With Robust Normalization for Multi-Group RNA-Seq Count Data

Buccal Swab Samples from Japanese Brown Cattle Fed with Limonite Reveal Altered Rumen Microbiome

The areas of the Mount Aso grasslands in Kumamoto, Japan, are the primary location for the breeding of the Kumamoto strain of Japanese Brown cattle (JBRK). Although Aso limonite, deposited by volcanic ash and magma, has been commonly fed to pregnant JBRK in this area, the mechanisms of its salutary effects on pregnant JBRK have not yet been elucidated. Approximately 100 days before the expected day of calf delivery, seven JBRK (four supplemented with limonite and three controls without limonite) were assigned to this study, from which a buccal swab was collected at the highest rumination every 30 days for 90 days. DNA extracted from these swabs was then analyzed using a 16S rRNA gene amplicon sequence analysis. Statistically significant differences between the two groups were discovered through beta-diversity analysis, though results from alpha-diversity analysis were inconclusive. The microbiota identified were classified into six clusters, and three of the main clusters were core-rumen bacteria, primarily cellulose digestion in cluster 1, oral bacteria in cluster 2, and non-core-rumen bacteria in cluster 3. In the limonite group, core-rumen bacteria decreased while non-core-rumen bacteria increased, suggesting that limonite feeding alters rumen microbiota, particularly activation of non-core-rumen microbiota.

Heterogeneous gene expression during early arteriovenous fistula remodeling suggests that downregulation of metabolism predicts adaptive venous remodeling

Clinical outcomes of arteriovenous fistulae (AVF) for hemodialysis remain inadequate since biological mechanisms of AVF maturation and failure are still poorly understood. Aortocaval fistula creation (AVF group) or a sham operation (sham group) was performed in C57BL/6 mice. Venous limbs were collected on postoperative day 7 and total RNA was extracted for high throughput RNA sequencing and bioinformatic analysis. Genes in metabolic pathways were significantly downregulated in the AVF, whereas significant sex differences were not detected. Since gene expression patterns among the AVF group were heterogenous, the AVF group was divided into a 'normal' AVF (nAVF) group and an 'outliers' (OUT) group. The gene expression patterns of the nAVF and OUT groups were consistent with previously published data showing venous adaptive remodeling, whereas enrichment analyses showed significant upregulation of metabolism, inflammation and coagulation in the OUT group compared to the nAVF group, suggesting the heterogeneity during venous remodeling reflects early gene expression changes that may correlate with AVF maturation or failure. Early detection of these processes may be a translational strategy to predict fistula failure and reduce patient morbidity.

Enhanced clustering-based differential expression analysis method for RNA-seq data

RNA-seq is a tool for measuring gene expression and is commonly used to identify differentially expressed genes (DEGs). Gene clustering has been widely used to classify DEGs with similar expression patterns, but rarely used to identify DEGs themselves. We recently reported that the clustering-based method (called MBCdeg1 and 2) for identifying DEGs has great potential. However, these methods left room for improvement. This study reports on the improvement (named MBCdeg3). We compared a total of six competing methods: three conventional R packages (edgeR, DESeq2, and TCC) and three versions of MBCdeg (i.e., MBCdeg1, 2, and 3) corresponding to three different normalization algorithms. As MBCdeg3 performs well in many simulation scenarios of RNA-seq count data, MBCdeg3 replaces MBCdeg1 and 2 in our previous report. •MBCdeg3 is a method for both identification and classification of DEGs from RNA-seq count data.•MBCdeg3 is available as a function of R, which is common in the field of expression analysis.•MBCdeg3 performs well in a variety of simulation scenarios for RNA-seq count data.

Autonomous differentiation of transgenic cells requiring no external hormone application: the endogenous gene expression and phytohormone behaviors

The ectopic overexpression of developmental regulator (DR) genes has been reported to improve the transformation in recalcitrant plant species because of the promotion of cellular differentiation during cell culture processes. In other words, the external plant growth regulator (PGR) application during the tissue and cell culture process is still required in cases utilizing DR genes for plant regeneration. Here, the effect of Arabidopsis BABY BOOM (BBM) and WUSCHEL (WUS) on the differentiation of tobacco transgenic cells was examined. We found that the SRDX fusion to WUS, when co-expressed with the BBM-VP16 fusion gene, significantly influenced the induction of autonomous differentiation under PGR-free culture conditions, with similar effects in some other plant species. Furthermore, to understand the endogenous background underlying cell differentiation toward regeneration, phytohormone and RNA-seq analyses were performed using tobacco leaf explants in which transgenic cells were autonomously differentiating. The levels of active auxins, cytokinins, abscisic acid, and inactive gibberellins increased as cell differentiation proceeded toward organogenesis. Gene Ontology terms related to phytohormones and organogenesis were identified as differentially expressed genes, in addition to those related to polysaccharide and nitrate metabolism. The qRT-PCR four selected genes as DEGs supported the RNA-seq data. This differentiation induction system and the reported phytohormone and transcript profiles provide a foundation for the development of PGR-free tissue cultures of various plant species, facilitating future biotechnological breeding.

Translating Ribosome Affinity Purification (TRAP) and Bioinformatic RNA-Seq Analysis in Post-metamorphic Xenopus laevis

Recent technical advances provide the ability to isolate and purify mRNAs from genetically distinct cell types so as to provide a broader view of gene expression as they relate to gene networks. These tools allow the genome of organisms undergoing different developmental or diseased states and environmental or behavioral conditions to be compared. Translating ribosome affinity purification (TRAP), a method using transgenic animals expressing a ribosomal affinity tag (ribotag) that targets ribosome-bound mRNAs, allows for the rapid isolation of genetically distinct populations of cells. In this chapter, we provide stepwise methods for carrying out an updated protocol for using the TRAP method in the South African clawed frog Xenopus laevis. A discussion of the experimental design and necessary controls and their rationale, along with a description of the bioinformatic steps involved in analyzing the Xenopus laevis translatome using TRAP and RNA-Seq, is also provided.

Effects of enhanced insect feeding on the faecal microbiota and transcriptome of a family of captive common marmosets (Callithrix jacchus)

Common marmosets have been widely used in biomedical research for years. Nutritional control is an important factor in managing their health, and insect intake would be beneficial for that purpose because common marmosets frequently feed on insects in natural habitats. Here, we examined the effect of enhanced insect feeding on the gut by analysing the faecal microbiota and transcripts of captive marmosets. A family consisting of six marmosets was divided into two groups. During the seven-day intervention period, one group (the insect feeding group, or Group IF) was fed one cricket and one giant mealworm per marmoset per day, while the other (the control group, or Group C) was not fed these insects. RNA was extracted from faecal samples to evaluate the ecology and transcripts of the microbiota, which were then compared among time points before (Pre), immediately after (Post), and two weeks after the intervention (Follow_up) using total RNA sequencing. The gut microbiota of marmosets showed Firmicutes, Actinobacteria, Bacteroidetes, and Proteobacteria as dominant phyla. Linear discriminant analysis showed differential characteristics of microbiota with and without insect feeding treatment. Further analysis of differentially expressed genes revealed increases and decreases in Bacteroidetes and Firmicutes, respectively, corresponding to the availability of insects under both Post and Follow_up conditions. Significant changes specific to insect feeding were also detected within the transcriptome, some of which were synchronized with the fluctuations in the microbiota, suggesting a functional correlation or interaction between the two. The rapid changes in the microbiota and transcripts may be achieved by the microbiota community originally developed in the wild through marmosets' feeding ecology. The results were informative for identifying the physiological impact of insect feeding to produce a better food regimen and for detecting transcripts that are currently unidentifiable.

Seasonal and geographical differences in the ruminal microbial and chloroplast composition of sika deer (Cervus nippon) in Japan

To understand the nutritional status of culled wild sika deer (Cervus nippon), we compared the ruminal microbes of deer living in habitats differing in food composition (Nagano winter, Nagano spring, and Hokkaido winter) using next-generation sequencing. Twenty-nine sika deer were sampled. Alpha and beta diversity metrics determined via 16S and 18S rRNA amplicon-seq analysis showed compositional differences. Prevotella, Entodinium, and Piromyces were the dominant genera of bacteria, fungi and protozoa, respectively. Moreover, 66 bacterial taxa, 44 eukaryotic taxa, and 46 chloroplastic taxa were shown to differ significantly among the groups by the linear discriminant analysis effect size (LEfSe) technique. Total RNA-seq analysis yielded 397 significantly differentially expressed transcripts (q < 0.05), of which 48 (q < 0.01) were correlated with the bacterial amplicon-seq results (Pearson correlation coefficient > 0.7). The ruminal microbial composition corresponded with the presence of different plants because the amplicon-seq results indicated that chloroplast from broadleaf trees and Stramenopiles-Alveolates-Rhizaria (SAR) were enriched in Nagano, whereas chloroplast from graminoids, Firmicutes and the dominant phylum of fungi were enriched in Hokkaido. These results could be related to the severe snow conditions in Hokkaido in winter and the richness of plants with leaves and acorns in Nagano in winter and spring. The findings are useful for understanding the nutritional status of wild sika deer.

Machine Learning in Epigenomics: Insights into Cancer Biology and Medicine

The recent deluge of genome-wide technologies for the mapping of the epigenome and resulting data in cancer samples has provided the opportunity for gaining insights into and understanding the roles of epigenetic processes in cancer. However, the complexity, high-dimensionality, sparsity, and noise associated with these data pose challenges for extensive integrative analyses. Machine Learning (ML) algorithms are particularly suited for epigenomic data analyses due to their flexibility and ability to learn underlying hidden structures. We will discuss four overlapping but distinct major categories under ML: dimensionality reduction, unsupervised methods, supervised methods, and deep learning (DL). We review the preferred use cases of these algorithms in analyses of cancer epigenomics data with the hope to provide an overview of how ML approaches can be used to explore fundamental questions on the roles of epigenome in cancer biology and medicine.

Differential expression analysis using a model-based gene clustering algorithm for RNA-seq data

Background

RNA-seq is a tool for measuring gene expression and is commonly used to identify differentially expressed genes (DEGs). Gene clustering is used to classify DEGs with similar expression patterns for the subsequent analyses of data from experiments such as time-courses or multi-group comparisons. However, gene clustering has rarely been used for analyzing simple two-group data or differential expression (DE). In this study, we report that a model-based clustering algorithm implemented in an R package, MBCluster.Seq, can also be used for DE analysis.

Results

The input data originally used by MBCluster.Seq is DEGs, and the proposed method (called MBCdeg) uses all genes for the analysis. The method uses posterior probabilities of genes assigned to a cluster displaying non-DEG pattern for overall gene ranking. We compared the performance of MBCdeg with conventional R packages such as edgeR, DESeq2, and TCC that are specialized for DE analysis using simulated and real data. Our results showed that MBCdeg outperformed other methods when the proportion of DEG (P_DEG) was less than 50%. However, the DEG identification using MBCdeg was less consistent than with conventional methods. We compared the effects of different normalization algorithms using MBCdeg, and performed an analysis using MBCdeg in combination with a robust normalization algorithm (called DEGES) that was not implemented in MBCluster.Seq. The new analysis method showed greater stability than using the original MBCdeg with the default normalization algorithm.

Conclusions

MBCdeg with DEGES normalization can be used in the identification of DEGs when the P_DEG is relatively low. As the method is based on gene clustering, the DE result includes information on which expression pattern the gene belongs to. The new method may be useful for the analysis of time-course and multi-group data, where the classification of expression patterns is often required.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04438-4.

Dynamics of the cell fate specifications during female gametophyte development in Arabidopsis

The female gametophytes of angiosperms contain cells with distinct functions, such as those that enable reproduction via pollen tube attraction and fertilization. Although the female gametophyte undergoes unique developmental processes, such as several rounds of nuclear division without cell plate formation and final cellularization, it remains unknown when and how the cell fate is determined during development. Here, we visualized the living dynamics of female gametophyte development and performed transcriptome analysis of individual cell types to assess the cell fate specifications in Arabidopsis thaliana. We recorded time lapses of the nuclear dynamics and cell plate formation from the 1-nucleate stage to the 7-cell stage after cellularization using an in vitro ovule culture system. The movies showed that the nuclear division occurred along the micropylar–chalazal (distal–proximal) axis. During cellularization, the polar nuclei migrated while associating with the forming edge of the cell plate, and then, migrated toward each other to fuse linearly. We also tracked the gene expression dynamics and identified that the expression of MYB98pro::GFP–MYB98, a synergid-specific marker, was initiated just after cellularization in the synergid, egg, and central cells and was then restricted to the synergid cells. This indicated that cell fates are determined immediately after cellularization. Transcriptome analysis of the female gametophyte cells of the wild-type and myb98 mutant revealed that the myb98 synergid cells had egg cell–like gene expression profiles. Although in myb98, egg cell–specific gene expression was properly initiated in the egg cells only after cellularization, but subsequently expressed ectopically in one of the 2 synergid cells. These results, together with the various initiation timings of the egg cell–specific genes, suggest complex regulation of the individual gametophyte cells, such as cellularization-triggered fate initiation, MYB98-dependent fate maintenance, cell morphogenesis, and organelle positioning. Our system of live-cell imaging and cell type–specific gene expression analysis provides insights into the dynamics and mechanisms of cell fate specifications in the development of female gametophytes in plants.

The female gametophytes of angiosperms contain cells with distinct functions, such as those that enable reproduction via pollen tube attraction and fertilization. Live-cell imaging and transcriptome analysis of single female gametophyte cell reveal novel insights into the dynamics and mechanisms of cell fate specifications in the model plant Arabidopsis.

Dynamics of the cell fate specifications during female gametophyte development in Arabidopsis

The female gametophytes of angiosperms contain cells with distinct functions, such as those that enable reproduction via pollen tube attraction and fertilization. Although the female gametophyte undergoes unique developmental processes, such as several rounds of nuclear division without cell plate formation and final cellularization, it remains unknown when and how the cell fate is determined during development. Here, we visualized the living dynamics of female gametophyte development and performed transcriptome analysis of individual cell types to assess the cell fate specifications in Arabidopsis thaliana. We recorded time lapses of the nuclear dynamics and cell plate formation from the 1-nucleate stage to the 7-cell stage after cellularization using an in vitro ovule culture system. The movies showed that the nuclear division occurred along the micropylar-chalazal (distal-proximal) axis. During cellularization, the polar nuclei migrated while associating with the forming edge of the cell plate, and then, migrated toward each other to fuse linearly. We also tracked the gene expression dynamics and identified that the expression of MYB98pro::GFP-MYB98, a synergid-specific marker, was initiated just after cellularization in the synergid, egg, and central cells and was then restricted to the synergid cells. This indicated that cell fates are determined immediately after cellularization. Transcriptome analysis of the female gametophyte cells of the wild-type and myb98 mutant revealed that the myb98 synergid cells had egg cell-like gene expression profiles. Although in myb98, egg cell-specific gene expression was properly initiated in the egg cells only after cellularization, but subsequently expressed ectopically in one of the 2 synergid cells. These results, together with the various initiation timings of the egg cell-specific genes, suggest complex regulation of the individual gametophyte cells, such as cellularization-triggered fate initiation, MYB98-dependent fate maintenance, cell morphogenesis, and organelle positioning. Our system of live-cell imaging and cell type-specific gene expression analysis provides insights into the dynamics and mechanisms of cell fate specifications in the development of female gametophytes in plants.