Journal: Horticulture Research

Article Title: Uncovering the genetic architecture of pungency, carotenoids, and flavor in Capsicum chinense via TWAS-mGWAS integration and spatial transcriptomics

doi: 10.1093/hr/uhaf243

Figure Lengend Snippet: Spatially resolved transcriptomic analysis of two contrasting C. chinense accessions, PI 656271 and PI 660973, was performed using Stereo-seq on 5-day post-anthesis (5-dpa) fruits to investigate tissue-specific gene expression patterns. Panel A illustrates the application of spatial transcriptomics to map gene activity within intact fruit tissues. Panel B presents a Uniform Manifold Approximation and Projection (UMAP) plot of spatial transcriptomic spots, where each dot represents an individual spatial location, and colors indicate distinct transcriptional clusters across the fruit sections. Panels C and D display the differential spatial expression of AP2 (APETALA2) transcription factors and PPR (Pentatricopeptide Repeat) genes, respectively, within Modules 1 and 2—gene modules identified as highly spatially correlated and differentially expressed between the two accessions. These spatial expression profiles reveal zone-specific regulatory networks involved in the biosynthesis of capsaicinoids, carotenoids, and volatile metabolites, offering insights into the tissue-level transcriptional control of fruit quality traits in C. chinense .

Article Snippet: Stereo-seq transcriptomics was conducted using the BGI Stereo-seq kit (catalog 211ST114, STOmics), following the manufacturer’s instructions with minor modifications [ ].

Techniques: Gene Expression, Activity Assay, Expressing, Control

Journal: Current epidemiology reports

Article Title: Neighborhoods to Nucleotides – Advances and gaps for an obesity disparities systems epidemiology model

doi: 10.1007/s40471-019-00221-5

Figure Lengend Snippet: Outcomes measured in the Neighborhoods to Nucleotides sample (n=209) across seven domains.

Article Snippet: Epigenomic/Transcriptomic DNA methylation Illumina Infinium MethylationEpic BeadChip Kits (>850,000 methylation sites at single-nucleotide resolution) mRNA & miRNA Illumina Next Generation Sequencing HiSeq4000 Microbiome Diversity 16S rRNA gene amplicon sequencing for calculating alpha diversity (diversity within each sample) such as the Shannon index Dissimilarity Metrics of beta diversity such as UniFrac calculated from the 16S rRNA data Taxonomy Assignment of each 16S rRNA read to a bacterial taxon, at multiple levels (typically from the phylum to the genus) Nutrition 24 hour recall Nutrition Data Systems for Research 24 hour food recalls (total calories, fats, fiber, number of food types e.g. vegetables or fruit) Food frequency VioScreen food frequency questionnaire (instances of food types eaten over past weeks/months) Biomarker Clinical BMI, waist-hip circumference, medications Urine Metabolomics Blood Metabolomics, hormone, adipokines, biomarkers of inflammation, glycemic regulation, lipid metabolism, liver health Behavior Accelerometer Physical activity (bouts, total duration, daily patterns), sedentary behavior (bouts, total duration, daily patterns), sleep time, sleep quality, machine learned behaviors (biking, running, walking, in vehicle) GPS Time spent indoor/outdoor, dynamic exposure measures to all environmental features (e.g., total air pollution participant is exposed to measured by movement) Self-report Questionnaires on health, physical functioning, sleep, etc.

Techniques: DNA Methylation Assay, Methylation, Next-Generation Sequencing, Amplification, Sequencing, Biomarker Assay, Activity Assay

Journal: bioRxiv

Article Title: Multiscale Spatial Transcriptomic Atlas of Human Basal Ganglia Cell-Type and Cellular Community Organization

doi: 10.64898/2025.12.02.691876

Figure Lengend Snippet: ( A ) Overview of study design, donor and sample quality and metadata, tissue sampling strategy, and adjacent-section workflows. ( B ) Stereo-seq dataset from an anterior basal ganglia section (donor case ID 2724): left, spatial map with cell-type assignments; right, UMAP embedding resolving 10 major cell classes from the same section. ( C ) MERFISH+ dataset from an adjacent anterior section. Left, spatial map with cell-type assignments; right, UMAP embedding resolving 10 major cell classes corresponding to Stereo-seq in ( B ). ( D–G , progressively greater magnification) Multi-scale Stereo-seq enlarged views of the boxed region in ( B ), illustrating the resolution span from centimeter-scale tissue anatomy to micron-scale detection of individual transcripts, with corresponding cell-type labels ( D, E ), cell-contour segmentation ( F ), and single-cell detail ( G ). ( H–K , progressively greater magnification) Multi-scale MERFISH+ enlarged views of the boxed region in ( C ), showing transcripts for selected genes (DRD1, DRD2, PENK, CCK, SST, CHAT, MBP) (color coded) and other genes (gray coded) that define cell-types at micron-scale resolution. See color keys at ( K ). Scale bars as indicated

Article Snippet: To fit the 2 cm × 3 cm Stereo-seq chips (STOmics/Complete Genomics, 111ST13231-CG), each large brain section was trimmed and/or subdivided within the cryostat to approximately 18 mm × 28 mm dimensions ( ).

Techniques: Sampling

Journal: eLife

Article Title: Transcriptome analysis illuminates the nature of the intracellular interaction in a vertebrate-algal symbiosis

doi: 10.7554/eLife.22054

Figure Lengend Snippet: ( a ) Intracapsular algae (Population 1) were removed from intact eggs using a syringe and hypodermic needle (photo credit: Roger Hangarter). Embryos were decapsulated and washed, and the liver diverticulum region (dashed line), containing high concentrations of algae (red dots), was isolated and dissociated into a single cell suspension (illustration adapted from ). The dissociated cells were screened for A. maculatum endoderm cells without alga (black arrowheads) and endoderm cells with intracellular alga (green arrowhead). Scale bars on microscope images are 20 µm. ( b ) Isolated endoderm cell, and isolated endoderm cell with intracellular alga. Scale bars on microscope images are 20 µm. ( c ) Representative cDNA distribution (bioanalyzer trace) from a population of 50 manually isolated A. maculatum endoderm cells. Peaks at 35 bp and 10380 bp are markers. Due to evidence of lysed A. maculatum cells observed in the cell suspension fluid after dissociation of A. maculatum embryos (debris seen in dissociated A. maculatum microscope images in ( a ) and ( b )), that fluid was tested for the presence of contaminating mRNA. mRNA was not detected in the surrounding fluid, . Lower limit abundance thresholds , and correction for low sequencing depth in intracelluar algal samples were implemented to obtain the final gene sets used for differential expression analysis. Depth of sequencing was not biased for A. maculatum cell with and without alga samples . Library preparation GC bias affected the completeness of the algal transcriptome obtained from intracapsular and intracellular O. amblystomatis . ( d and e ) Dotplots of log 2 fold change vs. expression level. The blue horizontal lines are plus and minus 4-fold change in expression between samples. The red dots are genes with FDR adjusted p-values<0.05, indicating a significant difference in expression level between conditions. ( d ) Differentially expressed algal transcripts. ( e ) Differentially expressed salamander transcripts. DOI: http://dx.doi.org/10.7554/eLife.22054.003 10.7554/eLife.22054.004 Figure 1—source data 1. Raw counts matrix with counts for all reads mapped to the total evidence assembly (the assembly of all salamander and algal reads from wild-collected samples). The data in this file (after filtering and normalization) was used to generate the dotplots in , – , and . This is the raw data that was used for differential expression analysis. Rows are genes. Column names are as follows: S2a-S5a are counts for salamander cells without algae. S2b-S5b are counts for salamander cells with intracellular algae (samples are paired from the same individuals, such that S2a and S2b came from the same salamander). A1-A3 are intracapsular algae samples. RK_* are cultured algal samples. DOI: http://dx.doi.org/10.7554/eLife.22054.004 10.7554/eLife.22054.005 Figure 1—source data 2. List of 6,726 algal gene IDs used in differential expression analysis. Use to filter raw counts matrix to get final algal gene list. DOI: http://dx.doi.org/10.7554/eLife.22054.005 10.7554/eLife.22054.006 Figure 1—source data 3. List of 46,549 salamander gene IDs used in differential expression analysis. Use to filter raw counts matrix to get final salamander gene list. DOI: http://dx.doi.org/10.7554/eLife.22054.006

Article Snippet: Transcriptome libraries (Illumina’s TruSeq RNA library) for the cultured algae were prepared and sequenced at Genome Quebec on HiSeq 2000 with 100 bp paired-end reads or at Cornell Weill Genomics Resources Core Facility on the MySeq platform with 75 bp paired end reads.

Techniques: Algae, Isolation, Suspension, Microscopy, Sequencing, Expressing, Cell Culture

Journal: eLife

Article Title: Transcriptome analysis illuminates the nature of the intracellular interaction in a vertebrate-algal symbiosis

doi: 10.7554/eLife.22054

Figure Lengend Snippet: ( a ) The GC content distribution of algal transcripts generated using TrueSeq library preparation of total RNA, sequenced on the MySeq platform with approximately 30 million 75 bp paired end reads. 79% of eukaryote BUSCOs were detected in this assembly. The median GC content (green dashed line) is 62%. ( b ) The GC content distribution from ( a ), split by library preparation method. Red bars represent algal transcripts found in transcriptomes generated by both library preparation methods (SMARTer-Netxtera-XT and TruSeq). Blue bars represent transcripts found only in the transcriptome assembly from the TrueSeq library preparation method, that are absent from the transcriptome generated using the SMARTer cDNA synthesis-Nextera-XT library preparation method. There is an apparent bias against high GC content algal transcripts in library prepared using the SMARTer cDNA synthesis-Nextera-XT protocol (Kolgomorov-Smirnov test, p<2.2 × 10 −16 ). Both libraries were sequenced to a similar depth of approximately 30 million reads for the alga-only samples in the total-evidence assembly from the SMARTer-cDNA synthesis-Nextera-XT library and 30 million reads for the TrueSeq library from unialgal cultures. Since sequencing depth was equivalent and GC bias is apparent, the data suggests that GC bias in the SMARTer-cDNA synthesis-Nextera-XT library is what accounts for the low number of detected BUSCOs (49%) in the algal transcriptome generated from wild-collected algal samples associated with salamander eggs and cells. (C.) The distribution of GC content in A. maculatum transcripts (gray bars) is centered around much lower GC content transcripts (median GC content of 43%) compared to that of O. amblystomatis (green bars, median GC content of 62%). The A. maculatum assembly contained 88% of eukaryote BUSCOs. Our evidence points to bias against high GC content transcripts in the SMARTer cDNA synthesis and Nextera-XT library prep method, that becomes significant above 60% GC content. Transcripts with GC content of 60% or greater are in the tail of the salamander GC content distribution, but near the median of the algal GC content distribution. This offers an explanation for the BUSCO results, where the salamander transcriptome from the wild-collected samples is comprehensive, while the algal transcriptome from the same samples and library prep methods is missing around 40% of the algal transcriptome. DOI: http://dx.doi.org/10.7554/eLife.22054.011

Article Snippet: Transcriptome libraries (Illumina’s TruSeq RNA library) for the cultured algae were prepared and sequenced at Genome Quebec on HiSeq 2000 with 100 bp paired-end reads or at Cornell Weill Genomics Resources Core Facility on the MySeq platform with 75 bp paired end reads.

Techniques: Generated, Sequencing