Genome-wide identification of ubiquitin proteasome subunits as superior reference genes for transcript normalization during receptacle development in strawberry cultivars.

BACKGROUND: Gene transcripts that show invariant abundance during development are ideal as reference genes (RGs) for accurate gene expression analyses, such as RNA blot analysis and reverse transcription-quantitative real time PCR (RT-qPCR) analyses. In a genome-wide analysis, we selected three "Commonly used" housekeeping genes (HKGs), fifteen "Traditional" HKGs, and nine novel genes as candidate RGs based on 80 publicly available transcriptome libraries that include data for receptacle development in eight strawberry cultivars. RESULTS: The results of the multifaceted assessment consistently revealed that expression of the novel RGs showed greater stability compared with that of the "Commonly used" and "Traditional" HKGs in transcriptome and RT-qPCR analyses. Notably, the majority of stably expressed genes were associated with the ubiquitin proteasome system. Among these, two 26 s proteasome subunits, RPT6A and RPN5A, showed superior expression stability and abundance, and are recommended as the optimal RGs combination for normalization of gene expression during strawberry receptacle development. CONCLUSION: These findings provide additional useful and reliable RGs as resources for the accurate study of gene expression during receptacle development in strawberry cultivars.

Co-expression network analysis uncovers key candidate genes related to the regulation of volatile esters accumulation in Woodland strawberry.

MAIN CONCLUSION: FveERF (FvH4_5g04470.1), FveAP2 (FvH4_1g16370.1) and FveWRKY (FvH4_6g42870.1) might be involved in fruit maturation of strawberry. Overexpression of FveERF could activate the expression of AAT gene and ester accumulation. Volatile esters play an important role in the aroma of strawberry fruits, whose flavor is the result of a complex mixture of various esters. The accumulation of these volatiles is closely tied to changes in metabolism during fruit ripening. Acyltransferase (AAT) is recognized as having a significant effect in ester formation. However, there is little knowledge about the regulation network of AAT. Here, we collected the data of RNA-seq and headspace GC-MS at five time points during fruit maturation of Hawaii4 and Ruegen strawberry varieties. A total of 106 volatile compounds were identified in the fruit of woodland strawberries, including 58 esters, which occupied 41.09% (Hawaii4) or 33.40% (Ruegen) of total volatile concentration. Transcriptome analysis revealed eight transcription factors highly associated with AAT genes. Through the changes in esters and the weight co-expression network analysis (WGCNA), a detailed gene network was established. This demonstrated that ERF gene (FvH4_5g04470.1), AP2 gene (FvH4_1g16370.1) and one WRKY gene (FvH4_6g42870.1) might be involved in expression of AAT genes, especially ERF genes. Overexpression of FveERF (FvH4_5g04470.1) does activate expression of AAT genes and ester accumulation in fruits of strawberry. Our findings provide valuable clues to gain better insight into the ester formation process of numerous fruits.

Mapping of clonal lineages across developmental stages in human neural differentiation.

The cell lineages across developmental stages remain to be elucidated. Here, we developed single-cell split barcoding (SISBAR) that allows clonal tracking of single-cell transcriptomes across stages in an in vitro model of human ventral midbrain-hindbrain differentiation. We developed "potential-spective" and "origin-spective" analyses to investigate the cross-stage lineage relationships and mapped a multi-level clonal lineage landscape depicting the whole differentiation process. We uncovered many previously uncharacterized converging and diverging trajectories. Furthermore, we demonstrate that a transcriptome-defined cell type can arise from distinct lineages that leave molecular imprints on their progenies, and the multilineage fates of a progenitor cell-type represent the collective results of distinct rather than similar clonal fates of individual progenitors, each with distinct molecular signatures. Specifically, we uncovered a ventral midbrain progenitor cluster as the common clonal origin of midbrain dopaminergic (mDA) neurons, midbrain glutamatergic neurons, and vascular and leptomeningeal cells and identified a surface marker that can improve graft outcomes.

Long-Read Sequencing Reveals Alternative Splicing-Driven, Shared Immunogenic Neoepitopes Regardless of SF3B1 Status in Uveal Melanoma.

Tumor-specific neoepitopes are promising targets in cancer immunotherapy. However, the identification of functional tumor-specific neoepitopes remains challenging. In addition to the most common source, single-nucleotide variants (SNV), alternative splicing (AS) represents another rich source of neoepitopes and can be utilized in cancers with low SNVs such as uveal melanoma (UM). UM, the most prevalent adult ocular malignancy, has poor clinical outcomes due to a lack of effective therapies. Recent studies have revealed the promise of harnessing tumor neoepitopes to treat UM. Previous studies have focused on neoepitope targets associated with mutations in splicing factor 3b subunit 1 (SF3B1), a key splicing factor; however, little is known about the neoepitopes that are commonly shared by patients independent of SF3B1 status. To identify the AS-derived neoepitopes regardless of SF3B1 status, we herein used a comprehensive nanopore long-read-sequencing approach to elucidate the landscape of AS and novel isoforms in UM. We also performed high-resolution mass spectrometry to further validate the presence of neoepitope candidates and analyzed their structures using the AlphaFold2 algorithm. We experimentally evaluated the antitumor effects of these neoepitopes and found they induced robust immune responses by stimulating interferon (IFN)γ production and activating T cell-based UM tumor killing. These results provide novel insights into UM-specific neoepitopes independent of SF3B1 and lay the foundation for developing therapies by targeting these actionable neoepitopes.

In situ delivery of biobutyrate by probiotic Escherichia coli for cancer therapy.

Butyrate has a bioactive function to reduce carcinogenesis. To achieve targeted cancer therapy, this study developed bacterial cancer therapy (BCT) with butyrate as a payload. By metabolic engineering, Escherichia coli Nissle 1917 (EcN) was reprogrammed to synthesize butyrate (referred to as biobutyrate) and designated EcN-BUT. The adopted strategy includes construction of a synthetic pathway for biobutyrate and the rational design of central metabolism to increase the production of biobutyrate at the expense of acetate. With glucose, EcN-BUT produced primarily biobutyrate under the hypoxic condition. Furthermore, human colorectal cancer cell was administrated with the produced biobutyrate. It caused the cell cycle arrest at the G1 phase and induced the mitochondrial apoptosis pathway independent of p53. In the tumor-bearing mice, the injected EcN-BUT exhibited tumor-specific colonization and significantly reduced the tumor volume by 70%. Overall, this study opens a new avenue for BCT based on biobutyrate.

A data-driven integrative platform for computational prediction of toxin biotransformation with a case study.

Recently, biogenic toxins have received increasing attention owing to their high contamination levels in feed and food as well as in the environment. However, there is a lack of an integrative platform for seamless linking of data-driven computational methods with 'wet' experimental validations. To this end, we constructed a novel platform that integrates the technical aspects of toxin biotransformation methods. First, a biogenic toxin database termed ToxinDB (http://www.rxnfinder.org/toxindb/), containing multifaceted data on more than 4836 toxins, was built. Next, more than 8000 biotransformation reaction rules were extracted from over 300,000 biochemical reactions extracted from ~580,000 literature reports curated by more than 100 people over the past decade. Based on these reaction rules, a toxin biotransformation prediction model was constructed. Finally, the global chemical space of biogenic toxins was constructed, comprising ~550,000 toxins and putative toxin metabolites, of which 94.7% of the metabolites have not been previously reported. Additionally, we performed a case study to investigate citrinin metabolism in Trichoderma, and a novel metabolite was identified with the assistance of the biotransformation prediction tool of ToxinDB. This unique integrative platform will assist exploration of the 'dark matter' of a toxin's metabolome and promote the discovery of detoxification enzymes.