ML (MD2-related lipid recognition) proteins are known to enhance innate immune responses in mammals. This study reports the analysis of the putative ML gene family in Arabidopsis thaliana and suggests a role for the ML3 gene in herbivory-associated responses in plants. Feeding by larvae of the Lepidopteran generalist herbivore Spodoptera littoralis and larvae of the specialist herbivore Plutella xylostella activated ML3 transcription in leaf tissues. ML3 loss-of-function Arabidopsis plants were compromised in the upregulation of herbivory-induced genes and displayed a semi-dwarf phenotype. Herbivory bioassays showed that larvae of S. littoralis fed on ml3 mutant plants gained more weight compared to larvae fed on wild-type plants while larvae of P. xylostella did not show any significant difference. Virus-induced gene silencing of ML3 expression in plants compromised in jasmonic acid (JA) and salicylic acid (SA) signalling revealed a complex role of ML3 in JA/defence signalling affecting both JA- and SA-dependent responses. The data suggest that ML3 is involved in herbivory-mediated responses in Arabidopsis and that it has a potential role in herbivory-associated molecular pattern recognition.

Objectives The aim of this data paper is to describe a collection of 33 genomic, transcriptomic and epigenomic sequencing datasets of the B-cell acute lymphoblastic leukemia (ALL) cell line REH. REH is one of the most frequently used cell lines for functional studies of pediatric ALL, and these data provide a multi-faceted characterization of its molecular features. The datasets described herein, generated with short- and long-read sequencing technologies, can both provide insights into the complex aberrant karyotype of REH, and be used as reference datasets for sequencing data quality assessment or for methods development. Data Description This paper describes 33 datasets corresponding to 450 GB of raw sequencing data generated from the REH cell line. These datasets include five different approaches for whole genome sequencing (WGS) on four sequencing platforms, two RNA sequencing (RNA-seq) techniques on two different sequencing platforms, DNA methylation sequencing, and single-cell ATAC-sequencing.