Patterns of Unwanted Biological and Technical Expression Variation Among 49 Human Tissues

Tissue gene expression studies are impacted by biological and technical sources of variation, which can be broadly classified into wanted and unwanted variation. The latter, if not addressed, results in misleading biological conclusions. Methods have been proposed to reduce unwanted variation, such as normalization and batch correction. A more accurate understanding of all causes of variation could significantly improve the ability of these methods to remove unwanted variation while retaining variation corresponding to the biological question of interest. We used 17,282 samples from 49 human tissues in the Genotype-Tissue Expression data set (v8) to investigate patterns and causes of expression variation. Transcript expression was transformed to z-scores, and only the most variable 2% of transcripts were evaluated and clustered based on coexpression patterns. Clustered gene sets were assigned to different biological or technical causes based on histologic appearances and metadata elements. We identified 522 variable transcript clusters (median: 11 per tissue) among the samples. Of these, 63% were confidently explained, 16% were likely explained, 7% were low confidence explanations, and 14% had no clear cause. Histologic analysis annotated 46 clusters. Other common causes of variability included sex, sequencing contamination, immunoglobulin diversity, and compositional tissue differences. Less common biological causes included death interval (Hardy score), disease status, and age. Technical causes included blood draw timing and harvesting differences. Many of the causes of variation in bulk tissue expression were identifiable in the Tabula Sapiens data set of single-cell expression. This is among the largest explorations of the underlying sources of tissue expression variation. It uncovered expected and unexpected causes of variable gene expression and demonstrated the utility of matched histologic specimens. It further demonstrated the value of acquiring meaningful tissue harvesting metadata elements to use for improved normalization, batch correction, and analysis of both bulk and single-cell RNA-seq data.

Variability Analysis in Judo Para Athletes With Visual Impairments: Match-Outcome Performance in the Tokyo 2020 Paralympic Games With Evidence From the New Classification System

Match-related performance analysis in judo Para athletes with visual impairments is important to coaches and staff to identify technical-tactical profiles of their athletes and opponents but also to identify whether there are similar characteristics in each visual class. Thus, this study explores the match-related performance in judo Para athletes and verifies the relationship between performance using the old and new classification systems. The match-derived variables were analyzed using different statistical methods considering a total of 182 matches from the Tokyo 2020 Paralympic Games. The results indicated that performance was affected by sex and degree of impairment. The new classification system seems suitable for grouping Para judo athletes, as it differentiates performance between the two proposed classes (J1 and J2), since athletes from each group compete separately. Furthermore, different variability index measures were correlated with competitive performance, demonstrating a specific performance profile for each sport class in judo.

Variations in the microbiome due to storage preservatives are not large enough to obscure variations due to factors such as host population, host species, body site, and captivity

The study of the primate microbiome is critical in understanding the role of the microbial community in the host organism. To be able to isolate the main factors responsible for the differences observed in microbiomes within and between individuals, confounding factors due to technical variations need to be removed. To determine whether alterations due to preservatives outweigh differences due to factors such as host population, host species, body site, and habitat, we tested three methods (no preservative, 96% ethanol, and RNAlater) for preserving wild chimpanzee (fecal), wild lemur (fecal), wild vervet monkey (rectal, oral, nasal, otic, vaginal, and penile), and captive vervet monkey (rectal) samples. All samples were stored below - 20°C (short term) at the end of the field day and then at - 80°C until DNA extraction. Using 16S rRNA gene sequencing, we show a significant preservative effect on microbiota composition and diversity. Samples stored in ethanol and RNAlater appear to be less different compared with samples not stored in any preservative (none). Our differential analysis revealed significantly higher amounts of Enterococcaceae and Family XI in no preservative samples, Prevotellaceae and Spirochaetaceae in ethanol and RNAlater preserved samples, Oligosphaeraceae in ethanol-preserved samples, and Defluviitaleaceae in RNAlater preserved samples. While these preservative effects on the microbiome are not large enough to remove or outweigh the differences arising from biological factors (e.g., host species, body site, and habitat differences) they may promote misleading interpretations if they have large enough effect sizes compared to the biological factors (e.g., host population).

Nonrandom RNAseq gene expression associated with RNAlater and flash freezing storage methods

RNA sequencing is a popular next-generation sequencing technique for assaying genome-wide gene expression profiles. Nonetheless, it is susceptible to biases that are introduced by sample handling prior gene expression measurements. Two of the most common methods for preserving samples in both field-based and laboratory conditions are submersion in RNAlater and flash freezing in liquid nitrogen. Flash freezing in liquid nitrogen can be impractical, particularly for field collections. RNAlater is a solution for stabilizing tissue for longer-term storage as it rapidly permeates tissue to protect cellular RNA. In this study, we assessed genome-wide expression patterns in 30-day-old fry collected from the same brood at the same time point that were flash-frozen in liquid nitrogen and stored at -80°C or submerged and stored in RNAlater at room temperature, simulating conditions of fieldwork. We show that sample storage is a significant factor influencing observed differential gene expression. In particular, genes with elevated GC content exhibit higher observed expression levels in liquid nitrogen flash-freezing relative to RNAlater storage. Further, genes with higher expression in RNAlater relative to liquid nitrogen experience disproportionate enrichment for functional categories, many of which are involved in RNA processing. This suggests that RNAlater may elicit a physiological response that has the potential to bias biological interpretations of expression studies. The biases introduced to observed gene expression arising from mimicking many field-based studies are substantial and should not be ignored.

Systematic Selection of Reference Genes for the Normalization of Circulating RNA Transcripts in Pregnant Women Based on RNA-Seq Data

RNA transcripts circulating in peripheral blood represent an important source of non-invasive biomarkers. To accurately quantify the levels of circulating transcripts, one needs to normalize the data with internal control reference genes, which are detected at relatively constant levels across blood samples. A few reference gene candidates have to be selected from transcriptome data before the validation of their stable expression by reverse-transcription quantitative polymerase chain reaction. However, there is a lack of transcriptome, let alone whole-transcriptome, data from maternal blood. To overcome this shortfall, we performed RNA-sequencing on blood samples from women presenting with preterm labor. The coefficient of variation (CV) of expression levels was calculated. Of 11,215 exons detected in the maternal blood whole-transcriptome, a panel of 395 genes, including PPP1R15B, EXOC8, ACTB, and TPT1, were identified to comprise exons with considerably less variable expression level (CV, 7.75-17.7%) than any GAPDH exon (minimum CV, 27.3%). Upon validation, the selected genes from this panel remained more stably expressed than GAPDH in maternal blood. This panel is over-represented with genes involved with the actin cytoskeleton, macromolecular complex, and integrin signaling. This groundwork provides a starting point for systematically selecting reference gene candidates for normalizing the levels of circulating RNA transcripts in maternal blood.