An improved melon reference genome with single-molecule sequencing uncovers a recent burst of transposable elements with potential impact on genes

The published melon (Cucumis melo L.) reference genome assembly (v3.6.1) has still 41.6 Mb (Megabases) of sequences unassigned to pseudo-chromosomes and about 57 Mb of gaps. Although different approaches have been undertaken to improve the melon genome assembly in recent years, the high percentage of repeats (~40%) and limitations due to read length have made it difficult to resolve gaps and scaffold's misassignments to pseudomolecules, especially in the heterochromatic regions. Taking advantage of the PacBio single- molecule real-time (SMRT) sequencing technology, an improvement of the melon genome was achieved. About 90% of the gaps were filled and the unassigned sequences were drastically reduced. A lift-over of the latest annotation v4.0 allowed to re-collocate protein-coding genes belonging to the unassigned sequences to the pseudomolecules. A direct proof of the improvement reached in the new melon assembly was highlighted looking at the improved annotation of the transposable element fraction. By screening the new assembly, we discovered many young (inserted less than 2Mya), polymorphic LTR-retrotransposons that were not captured in the previous reference genome. These elements sit mostly in the pericentromeric regions, but some of them are inserted in the upstream region of genes suggesting that they can have regulatory potential. This improved reference genome will provide an invaluable tool for identifying new gene or transposon variants associated with important phenotypes.info:eu-repo/semantics/publishedVersio

Transposable element polymorphisms improve prediction of complex agronomic traits in rice

Acord transformatiu CRUE-CSICKey message: Transposon insertion polymorphisms can improve prediction of complex agronomic traits in rice compared to using SNPs only, especially when accessions to be predicted are less related to the training set. Abstract: Transposon insertion polymorphisms (TIPs) are significant sources of genetic variation. Previous work has shown that TIPs can improve detection of causative loci on agronomic traits in rice. Here, we quantify the fraction of variance explained by single nucleotide polymorphisms (SNPs) compared to TIPs, and we explore whether TIPs can improve prediction of traits when compared to using only SNPs. We used eleven traits of agronomic relevance from by five different rice population groups (Aus, Indica, Aromatic, Japonica, and Admixed), 738 accessions in total. We assess prediction by applying data split validation in two scenarios. In the within-population scenario, we predicted performance of improved Indica varieties using the rest of Indica accessions. In the across population scenario, we predicted all Aromatic and Admixed accessions using the rest of populations. In each scenario, Bayes C and a Bayesian reproducible kernel Hilbert space regression were compared. We find that TIPs can explain an important fraction of total genetic variance and that they also improve genomic prediction. In the across population prediction scenario, TIPs outperformed SNPs in nine out of the eleven traits analyzed. In some traits like leaf senescence or grain width, using TIPs increased predictive correlation by 30-50%. Our results evidence, for the first time, that TIPs genotyping can improve prediction on complex agronomic traits in rice, especially when accessions to be predicted are less related to training accessions

Amplification dynamics of miniature inverted-repeat transposable elements and their impact on rice trait variability

Ministerio de Ciencia y Innovación (PID2019-106374RB-I00) - DOI 10.13039/501100011033Transposable elements (TEs) are a rich source of genetic variability. Among TEs, miniature inverted-repeat TEs (MITEs) are of particular interest as they are present in high copy numbers in plant genomes and are closely associated with genes. MITEs are deletion derivatives of class II transposons, and can be mobilized by the transposases encoded by the latter through a typical cut-and-paste mechanism. However, MITEs are typically present at much higher copy numbers than class II transposons. We present here an analysis of 103 109 transposon insertion polymorphisms (TIPs) in 738 Oryza sativa genomes representing the main rice population groups. We show that an important fraction of MITE insertions has been fixed in rice concomitantly with its domestication. However, another fraction of MITE insertions is present at low frequencies. We performed MITE TIP-genome-wide association studies (TIP-GWAS) to study the impact of these elements on agronomically important traits and found that these elements uncover more trait associations than single nucleotide polymorphisms (SNPs) on important phenotypes such as grain width. Finally, using SNP-GWAS and TIP-GWAS we provide evidence of the replicative amplification of MITEs

T-lex3 : An accurate tool to genotype and estimate population frequencies of transposable elements using the latest short-read whole genome sequencing data

Motivation: Transposable elements (TEs) constitute a significant proportion of the majority of genomes sequenced to date. TEs are responsible for a considerable fraction of the genetic variation within and among species. Accurate genotyping of TEs in genomes is therefore crucial for a complete identification of the genetic differences among individuals, populations and species. Results: In this work, we present a new version of T-lex, a computational pipeline that accurately genotypes and estimates the population frequencies of reference TE insertions using short-read high-throughput sequencing data. In this new version, we have re-designed the T-lex algorithm to integrate the BWA-MEM short-read aligner, which is one of the most accurate short-read mappers and can be launched on longer short-reads (e.g. reads >150 bp). We have added new filtering steps to increase the accuracy of the genotyping, and new parameters that allow the user to control both the minimum and maximum number of reads, and the minimum number of strains to genotype a TE insertion. We also showed for the first time that T-lex3 provides accurate TE calls in a plant genome. Availability and implementation: To test the accuracy of T-lex3, we called 1630 individual TE insertions in Drosophila melanogaster, 1600 individual TE insertions in humans, and 3067 individual TE insertions in the rice genome. We showed that this new version of T-lex is a broadly applicable and accurate tool for genotyping and estimating TE frequencies in organisms with different genome sizes and different TE contents. T-lex3 is available at Github: https://github.com/GonzalezLab/T-lex3

Genomics and transcriptomics characterization of genes expressed during postharvest at 4°C by the edible basidiomycete Pleurotus ostreatus

Pleurotus ostreatus is an industrially cultivated basidiomycete with nutritional and environmental applications. Its genome, which was sequenced by the Joint Genome Institute, has become a model for lignin degradation and for fungal genomics and transcriptomics studies. The complete P. ostreatus genome contains 35 Mbp organized in 11 chromosomes, and two different haploid genomes have been individually sequenced. In this work, genomics and transcriptomics approaches were employed in the study of P. ostreatus under different physiological conditions. Specifically, we analyzed a collection ofexpressed sequence tags (EST) obtained from cut fruit bodies that had been stored at 4°C for 7 days (postharvest conditions). Studies of the 253 expressed clones that had been automatically and manually annotated provided a detailed picture of the life characteristics of the self-sustained fruit bodies. The results suggested a complex metabolism in which autophagy, RNA metabolism, and protein and carbohydrate turnover are increased. Genes involved in environment sensing and morphogenesis were expressed under these conditions. The data improve our understanding of the decay process in postharvest mushrooms and highlight the use of high-throughput techniques to construct models of living organisms subjected to different environmental conditions