A barley pan-transcriptome reveals layers of genotype-dependent transcriptional complexity.

A pan-transcriptome describes the transcriptional and post-transcriptional consequences of genome diversity from multiple individuals within a species. We developed a barley pan-transcriptome using 20 inbred genotypes representing domesticated barley diversity by generating and analyzing short- and long-read RNA-sequencing datasets from multiple tissues. To overcome single reference bias in transcript quantification, we constructed genotype-specific reference transcript datasets (RTDs) and integrated these into a linear pan-genome framework to create a pan-RTD, allowing transcript categorization as core, shell or cloud.

Identification of biomarker genes from multiple studies for abiotic stress in maize through machine learning.

Abiotic stresses are major limiting factors for maize growth. Therefore, exploration of the mechanisms underlying the response to abiotic stress in maize is of great interest. Toward this end, we performed integration of the feature selection method into the meta-analysis of microarray gene expression.

A Genomic BSAseq Approach for the Characterization of QTLs Underlying Resistance to in Eggplant.

Eggplant ( L.), similar to many other crops, suffers from soil-borne diseases, including f. sp.

Transcriptomic and biochemical investigations support the role of rootstock-scion interaction in grapevine berry quality.

Background: In viticulture, rootstock genotype plays a critical role to improve scion physiology, berry quality and to adapt grapevine (Vitis vinifera L.) to different environmental conditions. This study aimed at investigating the effect of two different rootstocks (1103 Paulsen - P - and Mgt 101-14 - M) in comparison with not grafted plants - NGC - on transcriptome (RNA-seq and small RNA-seq) and chemical composition of berry skin in Pinot noir, and exploring the influence of rootstock-scion interaction on grape quality.

Ab initio GO-based mining for non-tandem-duplicated functional clusters in three model plant diploid genomes.

A functional Non-Tandem Duplicated Cluster (FNTDC) is a group of non-tandem-duplicated genes that are located closer than expected by mere chance and have a role in the same biological function. The identification of secondary-compounds-related FNTDC has gained increased interest in recent years, but little ab-initio attempts aiming to the identification of FNTDCs covering all biological functions, including primary metabolism compounds, have been carried out. We report an extensive FNTDC dataset accompanied by a detailed assessment on parameters used for genome scanning and their impact on FNTDC detection.