Miniature inverted-repeat transposable elements (MITEs) are short, non-autonomous class II transposable elements present in a high number of conserved copies in eukaryote genomes. An accurate identification of these elements can help to shed light on the mechanisms controlling genome evolution and gene regulation. The structure and distribution of these elements are well-defined and therefore computational approaches can be used to identify MITEs sequences. Here we describe MITE Tracker, a novel, open source software program that finds and classifies MITEs using an efficient alignment strategy to retrieve nearby inverted-repeat sequences from large genomes. This program groups them into high sequence homology families using a fast clustering algorithm and finally filters only those elements that were likely transposed from different genomic locations because of their low scoring flanking sequence alignment. Many programs have been proposed to find MITEs hidden in genomes. However, none of them are able to process large-scale genomes such as that of bread wheat. Furthermore, in many cases the existing methods perform high false-positive rates (or miss rates). The rice genome was used as reference to compare MITE Tracker against known tools. Our method turned out to be the most reliable in our tests. Indeed, it revealed more known elements, presented the lowest false-positive number and was the only program able to run with the bread wheat genome as input. In wheat, MITE Tracker discovered 6013 MITE families and allowed the first structural exploration of MITEs in the complete bread wheat genome.

Background: Increasing wheat (Triticum aestivum L.) production is required to feed a growing human population. In order to accomplish this task a deeper understanding of the genetic structure of cultivated wheats and the detection of genomic regions significantly associated with the regulation of important agronomic traits are necessary steps. To better understand the genetic basis and relationships of adaptation and yield related traits, we used a collection of 102 Argentinean hexaploid wheat cultivars genotyped with the 35k SNPs array, grown from two to six years in three different locations. Based on SNPs data and gene-related molecular markers, we performed a haplotype block characterization of the germplasm and a genome-wide association study (GWAS). Results: The genetic structure of the collection revealed four subpopulations, reflecting the origin of the germplasm used by the main breeding programs in Argentina. The haplotype block characterization showed 1268 blocks of different sizes spread along the genome, including highly conserved regions like the 1BS chromosome arm where the 1BL/1RS wheat/rye translocation is located. Based on GWAS we identified ninety-seven chromosome regions associated with heading date, plant height, thousand grain weight, grain number per spike and fruiting efficiency at harvest (FEh). In particular FEh stands out as a promising trait to raise yield potential in Argentinean wheats; we detected fifteen haplotypes/markers associated with increased FEh values, eleven of which showed significant effects in all three evaluated locations. In the case of adaptation, the Ppd-D1 gene is consolidated as the main determinant of the life cycle of Argentinean wheat cultivars. Conclusion: This work reveals the genetic structure of the Argentinean hexaploid wheat germplasm using a wide set of molecular markers anchored to the Ref Seq v1.0. Additionally GWAS detects chromosomal regions (haplotypes) associated with important yield and adaptation components that will allow improvement of these traits through marker-assisted selection.

Background: Plant miRNAs are a class of small non-coding RNAs that can repress gene expression at the post-transcriptional level by targeting RNA degradation or promoting translational repression. There is increasing evidence that some miRNAs can derive from a group of non-autonomous class II transposable elements called Miniature Inverted-repeat Transposable Elements (MITEs).Results: We used public small RNA and degradome libraries fromTriticum aestivumto screen for microRNAs production and predict their cleavage target sites. In parallel, we also created a comprehensive wheat MITE database by identifying novel elements and compiling known ones. When comparing both data sets, we found high homology between MITEs and 14% of all the miRNAs production sites detected. Furthermore, we show that MITE-derived miRNAs have preference for targeting degradation sites with MITE insertions in the 3’ UTR regions of the transcripts.Conclusions: Our results revealed that MITE-derived miRNAs can underlay the origin of some miRNAs and potentially shape a regulatory gene network. Since MITEs are found in millions of insertions in the wheat genome and are closely linked to genic regions, this kind of regulatory network could have a significant impact on the post-transcriptional control of gene expression.

Cannabis sativa L. is a globally cultivated plant with significant industrial, nutritional, and medicinal value. Its genome, comprising nine autosomes and sex chromosomes (X and Y), has been extensively studied, particularly in the context of precise breeding for specific enduses. Recent advances have facilitated genome-wide analyses through platforms like the NCBI Comparative Genome Viewer (CGV) and CannabisGDB, among others, enabling comparative studies across multiple Cannabis genotypes. Despite the abundance of genomic data, a particular group of transposable elements, known as miniature inverted-repeat transposable elements (MITEs), remains underexplored in Cannabis. These elements are non-autonomous class II DNA transposons characterized by high copy numbers and insertion preference in non-coding regions, potentially affecting gene expression. In the present study, we report the sequence annotation of MITEs in wild-type and domesticated Cannabis genomes obtained using the MITE Tracker software. We also develop a simple and innovative protocol to identify genome-specific MITE families, offering valuable tools for future research on marker development focused on important genetic variation for breeding in Cannabis sativa.