Distinct Cellular Origins and Differentiation Process Account for Distinct Oncogenic and Clinical Behaviors of Leiomyosarcomas.

In leiomyosarcoma (LMS), a very aggressive disease, a relatively transcriptionally uniform subgroup of well-differentiated tumors has been described and is associated with poor survival. The question raised how differentiation and tumor progression, two apparently antagonist processes, coexist and allow tumor malignancy. We first identified the most transcriptionally homogeneous LMS subgroup in three independent cohorts, which we named 'hLMS'. The integration of multi-omics data and functional analysis suggests that hLMS originate from vascular smooth muscle cells and show that hLMS transcriptional program reflects both modulations of smooth muscle contraction activity controlled by MYOCD/SRF regulatory network and activation of the cell cycle activity controlled by E2F/RB1 pathway. We propose that the phenotypic plasticity of vascular smooth muscle cells coupled with MYOCD/SRF pathway amplification, essential for hLMS survival, concomitant with PTEN absence and RB1 alteration, could explain how hLMS balance this uncommon interplay between differentiation and aggressiveness.

Medium levels of transcription and replication related chromosomal instability are associated with poor clinical outcome.

Genomic instability (GI) influences treatment efficacy and resistance, and an accurate measure of it is lacking. Current measures of GI are based on counts of specific structural variation (SV) and mutational signatures. Here, we present a holistic approach to measuring GI based on the quantification of the steady-state equilibrium between DNA damage and repair as assessed by the residual breakpoints (BP) remaining after repair, irrespective of SV type. We use the notion of Hscore, a BP "hotspotness" magnitude scale, to measure the propensity of genomic structural or functional DNA elements to break more than expected by chance. We then derived new measures of transcription- and replication-associated GI that we call iTRAC (transcription-associated chromosomal instability index) and iRACIN (replication-associated chromosomal instability index). We show that iTRAC and iRACIN are predictive of metastatic relapse in Leiomyosarcoma (LMS) and that they may be combined to form a new classifier called MAGIC (mixed transcription- and replication-associated genomic instability classifier). MAGIC outperforms the gold standards FNCLCC and CINSARC in stratifying metastatic risk in LMS. Furthermore, iTRAC stratifies chemotherapeutic response in LMS. We finally show that this approach is applicable to other cancers.

ATRX Alteration Contributes to Tumor Growth and Immune Escape in Pleomorphic Sarcomas.

Whole genome and transcriptome sequencing of a cohort of 67 leiomyosarcomas has been revealed ATRX to be one of the most frequently mutated genes in leiomyosarcomas after TP53 and RB1. While its function is well described in the alternative lengthening of telomeres mechanism, we wondered whether its alteration could have complementary effects on sarcoma oncogenesis. ATRX alteration is associated with the down-expression of genes linked to differentiation in leiomyosarcomas, and to immunity in an additional cohort of 60 poorly differentiated pleomorphic sarcomas. In vitro and in vivo models showed that ATRX down-expression increases tumor growth rate and immune escape by decreasing the immunity load of active mast cells in sarcoma tumors. These data indicate that an alternative to unsuccessful targeting of the adaptive immune system in sarcoma could target the innate system. This might lead to a better outcome for sarcoma patients in terms of ATRX status.

Dissecting quantitative trait variation in the resequencing era: complementarity of bi-parental, multi-parental and association panels.

Quantitative trait loci (QTL) have been identified using traditional linkage mapping and positional cloning identified several QTLs. However linkage mapping is limited to the analysis of traits differing between two lines and the impact of the genetic background on QTL effect has been underlined. Genome-wide association studies (GWAs) were proposed to circumvent these limitations. In tomato, we have shown that GWAs is possible, using the admixed nature of cherry tomato genomes that reduces the impact of population structure. Nevertheless, GWAs success might be limited due to the low decay of linkage disequilibrium, which varies along the genome in this species. Multi-parent advanced generation intercross (MAGIC) populations offer an alternative to traditional linkage and GWAs by increasing the precision of QTL mapping. We have developed a MAGIC population by crossing eight tomato lines whose genomes were resequenced. We showed the potential of the MAGIC population when coupled with whole genome sequencing to detect candidate single nucleotide polymorphisms (SNPs) underlying the QTLs. QTLs for fruit quality traits were mapped and related to the variations detected at the genome sequence and expression levels. The advantages and limitations of the three types of population, in the context of the available genome sequence and resequencing facilities, are discussed.

Potential of a tomato MAGIC population to decipher the genetic control of quantitative traits and detect causal variants in the resequencing era.

Identification of the polymorphisms controlling quantitative traits remains a challenge for plant geneticists. Multiparent advanced generation intercross (MAGIC) populations offer an alternative to traditional linkage or association mapping populations by increasing the precision of quantitative trait loci (QTL) mapping. Here, we present the first tomato MAGIC population and highlight its potential for the valorization of intraspecific variation, QTL mapping and causal polymorphism identification. The population was developed by crossing eight founder lines, selected to include a wide range of genetic diversity, whose genomes have been previously resequenced. We selected 1536 SNPs among the 4 million available to enhance haplotype prediction and recombination detection in the population. The linkage map obtained showed an 87% increase in recombination frequencies compared to biparental populations. The prediction of the haplotype origin was possible for 89% of the MAGIC line genomes, allowing QTL detection at the haplotype level. We grew the population in two greenhouse trials and detected QTLs for fruit weight. We mapped three stable QTLs and six specific of a location. Finally, we showed the potential of the MAGIC population when coupled with whole genome sequencing of founder lines to detect candidate SNPs underlying the QTLs. For a previously cloned QTL on chromosome 3, we used the predicted allelic effect of each founder and their genome sequences to select putative causal polymorphisms in the supporting interval. The number of candidate polymorphisms was reduced from 12 284 (in 800 genes) to 96 (in 54 genes), including the actual causal polymorphism. This population represents a new permanent resource for the tomato genetics community.

Whole genome resequencing in tomato reveals variation associated with introgression and breeding events.

BACKGROUND: One of the goals of genomics is to identify the genetic loci responsible for variation in phenotypic traits. The completion of the tomato genome sequence and recent advances in DNA sequencing technology allow for in-depth characterization of genetic variation present in the tomato genome. Like many self-pollinated crops, cultivated tomato accessions show a low molecular but high phenotypic diversity. Here we describe the whole-genome resequencing of eight accessions (four cherry-type and four large fruited lines) chosen to represent a large range of intra-specific variability and the identification and annotation of novel polymorphisms. RESULTS: The eight genomes were sequenced using the GAII Illumina platform. Comparison of the sequences with the reference genome yielded more than 4 million single nucleotide polymorphisms (SNPs). This number varied from 80,000 to 1.5 million according to the accessions. Almost 128,000 InDels were detected. The distribution of SNPs and InDels across and within chromosomes was highly heterogeneous revealing introgressions from wild species and the mosaic structure of the genomes of the cherry tomato accessions. In-depth annotation of the polymorphisms identified more than 16,000 unique non-synonymous SNPs. In addition 1,686 putative copy-number variations (CNVs) were identified. CONCLUSIONS: This study represents the first whole genome resequencing experiment in cultivated tomato. Substantial genetic differences exist between the sequenced tomato accessions and the reference sequence. The heterogeneous distribution of the polymorphisms may be related to introgressions that occurred during domestication or breeding. The annotated SNPs, InDels and CNVs identified in this resequencing study will serve as useful genetic tools, and as candidate polymorphisms in the search for phenotype-altering DNA variations.

Phenotypic diversity and association mapping for fruit quality traits in cultivated tomato and related species.

Association mapping has been proposed as an efficient approach to assist in the identification of the molecular basis of agronomical traits in plants. For this purpose, we analyzed the phenotypic and genetic diversity of a large collection of tomato accessions including 44 heirloom and vintage cultivars (Solanum lycopersicum), 127 S. lycopersicum var. cerasiforme (cherry tomato) and 17 Solanum pimpinellifolium accessions. The accessions were genotyped using a SNPlex™ assay of 192 SNPs, among which 121 were informative for subsequent analysis. Linkage disequilibrium (LD) of pairwise loci and population structure were analyzed, and the association analysis between SNP genotypes and ten fruit quality traits was performed using a mixed linear model. High level of LD was found in the collection at the whole genome level. It was lower when considering only the 127 S. lycopersicum var. cerasiforme accessions. Genetic structure analysis showed that the population was structured into two main groups, corresponding to cultivated and wild types and many intermediates. The number of associations detected per trait varied, according to the way the structure was taken into account, with 0-41 associations detected per trait in the whole collection and a maximum of four associations in the S. lycopersicum var. cerasiforme accessions. A total of 40 associations (30 %) were co-localized with previously identified quantitative trait loci. This study thus showed the potential and limits of using association mapping in tomato populations.