De novo genome assembly and transcriptome analysis for the drought and salt resistant Solanum sitiens

Molitor, C.; Kurowski, T. J.; Fidalgo de Almeida, P. M.; Eerolla, P.; Spindlow, D. J.; Kashyap, S. P.; Singh, B.; Prasanna, H. C.; Thompson, A. J.; Mohareb, F. R.

doi:10.1101/2020.06.14.151043

bioRxiv · 10.1101/2020.06.14.151043

De novo genome assembly and transcriptome analysis for the drought and salt resistant Solanum sitiens

Molitor, C.·Kurowski, T. J.·Fidalgo de Almeida, P. M.·Eerolla, P.·Spindlow, D. J.·Kashyap, S. P.·Singh, B.·Prasanna, H. C.·Thompson, A. J.·Mohareb, F. R.

View original source ↗Export metadata ↓

Abstract

Solanum sitiens is a self-incompatible wild relative of tomato, characterised by salt and drought resistance traits, with the potential to contribute to crop improvement in cultivated tomato. This species has a distinct morphology, classification and ecotype compared to other stress resistant wild tomato relatives such as S. pennellii and S. chilense. Therefore, the availability of a high-quality reference genome for S. sitiens will facilitate the genetic and molecular understanding of salt and drought resistance. Here, we present a de novo genome and transcriptome assembly for S. sitiens (Accession LA1974). A hybrid assembly strategy was followed using Illumina short reads ([~]159X coverage) and PacBio long reads ([~]44X coverage), generating a total of [~]262 Gbp of DNA sequence; in addition, [~]2,670 Gbp of BioNano data was obtained. A reference genome of 1,245 Mbp, arranged in 1,481 scaffolds with a N50 of 1,826 Mbp was generated. Genome completeness was estimated at 95% using the Benchmarking Universal Single-Copy Orthologs (BUSCO) and the K-mer Analysis Tool (KAT); this is within the range of current high-quality reference genomes for other tomato wild relatives. Additionally, we identified three large inversions compared to S. lycopersicum, containing several drought resistance related genes, such as beta-amylase 1 and YUCCA7. In addition, [~]63 Gbp of RNA-Seq were generated to support the prediction of 31,164 genes from the assembly, and perform a de novo transcriptome. Some of the protein clusters unique to S. sitiens were associated with genes involved in drought and salt resistance, including GLO1 and FQR1. This first reference genome for S. sitiens will provide a valuable resource to progress QTL studies to the gene level, and will assist molecular breeding to improve crop production in water-limited environments.

Source connections

Published article ↗

Explore related subjects

bioinformatics Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Molitor, C., Kurowski, T. J., Fidalgo de Almeida, P. M., Eerolla, P., Spindlow, D. J., Kashyap, S. P., Singh, B., Prasanna, H. C., Thompson, A. J., Mohareb, F. R.. 2020-06-15. De novo genome assembly and transcriptome analysis for the drought and salt resistant Solanum sitiens. https://doi.org/10.1101/2020.06.14.151043

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

StableProt: Structure-Aware Deep Learning for Protein Thermostability (Tm) and Environmental Adaptation (OGT) Prediction

Predicting protein melting temperature (Tm) and organismal optimal growth temperature (OGT) is essential for enzyme engineering, biocatalyst design, and metagenomic bioprospecting, yet computational prediction faces several fundamental bottlenecks: sequence-only representations miss tertiary packing; dual-task coupling induces destructive gradient conflict; natural database skew (>87% mesophiles) drives mesophilic collapse; and existing tools produce uncalibrated point predictions. To address these challenges, we present StableProt, a structure-aware framework that couples amino acid sequences with Foldseek 3Di structural tokens via a frozen SaProt backbone to capture 3D contacts. Disjoint heads condition thermodynamic stability on ecological context without gradient conflict, while targeted 14% mesophilic subsampling expands thermophile representation to eliminate mesophilic collapse. Calibrated ensemble modeling reduces calibration error to 1.92%, providing dependable 95% confidence intervals. Evaluating models across 10{degrees}C temperature intervals reveals severe baseline collapse at thermal extremes, whereas StableProt maintains robust accuracy across regimes. On ProThermDB and zero-shot FireProtDB, StableProt achieves state-of-the-art probabilistic accuracy (CRPS = 4.52{degrees}C and 8.71{degrees}C) while recovering 92.0% of hyperthermophiles ([≥]80{degrees}C), and in prospective validation, its calibrated intervals capture both enzyme stability (75.3% coverage) and host environmental growth temperatures (78.1% coverage). StableProt is freely accessible as an interactive web server at https://stableprot.dixitlab.org/.

bioinformatics↗

bioRxiv2026

RoDPAA: A Robust Dissimilarity-Based Principal Angle Analysis Framework for Multi-View Microbiome Data Integration

Multiview microbiome studies profile the same participants across body sites or molecular layers, but integration is hampered by sparse, compositional data, modest sample sizes and methods that recognize only exact sharing. We present RoDPAA (Robust Dissimilarity-based Principal Angle Analysis), a framework that represents each view through any data-appropriate dissimilarity, such as Bray--Curtis, without log-ratio transformation or likelihood assumptions. RoDPAA aligns view-specific signal subspaces through principal angles, captures complete and partial sharing, and tests by permutation how many components are shared, using only eigendecomposition and little tuning. In Gaussian simulations, RoDPAA matched JIVE and MOFA given true ranks, ran faster and alone recovered the shared dimension in every replicate. In two inflammatory bowel disease (IBD) cohorts with sparse, zero-inflated data, Bray--Curtis-based RoDPAA recovered shared structure that was stable to prevalence filtering, whereas log-ratio-based alternatives were not. Its leading microbiome--metabolome factors, learned without disease labels, were the only ones associated with IBD.

bioinformatics↗

bioRxiv2026

Deducing splicing events from transcript sets with splicelogic

Long-read RNA sequencing captures a greater proportion of full-length transcripts, enabling more accurate isoform identification, discovery of novel isoforms, and more precise differential transcript usage analysis. However, comparing transcripts, whether between conditions or between sets such as novel and annotated isoforms, yields complex isoform changes that are hard to manipulate, summarize, and visualize. This is compounded by vertical integration of some tools, where downstream analysis depends on the specific output of a particular upstream tool. To address this gap, we have developed splicelogic, an R/Bioconductor package that makes transcript-set comparisons biologically interpretable by turning them into discrete splicing events, such as exon skipping, alternative splice sites, intron retention, and alternative transcription start and end sites. We designed splicelogic to integrate easily with existing RNA-seq workflows and tools. The splicelogic functions are modular, readable, and extensible, making it easy for users to adapt core logic to their own custom scientific questions or novel splicing definitions. By obtaining interpretable splicing events from transcript changes, splicelogic enables downstream analyses, including annotation of RNA-binding protein recognition sites, alongside summary statistics and visualization. The splicelogic package is publicly available and distributed through Bioconductor.

bioinformatics↗