Construction and characterization of a de novo draft genome of garden cress (Lepidium sativum L.).

Garden cress (Lepidium sativum L.) is a Brassicaceae crop recognized as a healthy vegetable and a medicinal plant. Lepidium is one of the largest genera in Brassicaceae, yet, the genus has not been a focus of extensive genomic research. In the present work, garden cress genome was sequenced using the long read high-fidelity sequencing technology. A de novo, draft genome assembly that spans 336.5 Mb was produced, corresponding to 88.6% of the estimated genome size and representing 90% of the evolutionarily expected orthologous gene content. Protein coding gene content was structurally predicted and functionally annotated, resulting in the identification of 25,668 putative genes. A total of 599 candidate disease resistance genes were identified by predicting resistance gene domains in gene structures, and 37 genes were detected as orthologs of heavy metal associated protein coding genes. In addition, 4289 genes were assigned as "transcription factor coding." Six different machine learning algorithms were trained and tested for their performance in classifying miRNA coding genomic sequences. Logistic regression proved the best performing trained algorithm, thus utilized for pre-miRNA coding loci identification in the assembly. Repetitive DNA analysis involved the characterization of transposable element and microsatellite contents. L. sativum chloroplast genome was also assembled and functionally annotated. Data produced in the present work is expected to constitute a foundation for genomic research in garden cress and contribute to genomics-assisted crop improvement and genome evolution studies in the Brassicaceae family.

The trnL (UAA)-trnF (GAA) intergenic spacer is a robust marker of green pea (Pisum sativum L.) adulteration in economically valuable pistachio nuts (Pistacia vera L.).

BACKGROUND: Pistachio (Pistacia vera L.) is an expensive culinary nut species; it is therefore susceptible to adulteration for economic profit. Green pea (Pisum sativum L.) kernels constitute the most common material used for adulterating chopped / ground pistachio nuts and pistachio paste. Food genomics enables the species composition of a food sample to be ascertained through DNA analysis. Accordingly, a barcode DNA genotyping approach was used to standardize a test method to identify green pea adulteration in pistachio nuts. RESULTS: The trnL (UAA)-trnF (GAA) intergenic spacer in the plastid genome was the target analyte in the present study. The barcode locus displayed a significant, discriminatory size difference between pistachio and pea, with amplicon sizes of 449 and 179 bp, respectively. Polymerase chain reaction-capillary electrophoresis (PCR-CE) analysis of the intergenic spacer resulted in the successful identification of species composition in the in-house admixtures, which contained 5% to 30% of green pea. CONCLUSION: The present work describes a fast and straightforward DNA test that identifies green pea adulteration in pistachio nuts without requiring a statistical data interpretation process. The plastid trnL (UAA)-trnF (GAA) intergenic spacer length widely varies among plant taxa, so the PCR-CE protocol that operates on the intergenic spacer holds the potential to reveal adulteration with a plethora of adulterants. The PCR-CE assay described in the present work can be adopted readily by food-quality laboratories in the public sector or the food industry as an easy and reliable method to analyze pistachio authenticity. © 2020 Society of Chemical Industry.

De novo assembly and characterization of the first draft genome of quince (Cydonia oblonga Mill.).

Quince (Cydonia oblonga Mill.) is the sole member of the genus Cydonia in the Rosacea family and closely related to the major pome fruits, apple (Malus domestica Borkh.) and pear (Pyrus communis L.). In the present work, whole genome shotgun paired-end sequencing was employed in order to assemble the first draft genome of quince. A genome assembly that spans 488.4 Mb of sequence corresponding to 71.2% of the estimated genome size (686 Mb) was produced in the study. Gene predictions via ab initio and homology-based sequence annotation strategies resulted in the identification of 25,428 and 30,684 unique putative protein coding genes, respectively. 97.4 and 95.6% of putative homologs of Arabidopsis and rice transcription factors were identified in the ab initio predicted genic sequences. Different machine learning algorithms were tested for classifying pre-miRNA (precursor microRNA) coding sequences, identifying Support Vector Machine (SVM) as the best performing classifier. SVM classification predicted 600 putative pre-miRNA coding loci. Repetitive DNA content of the assembly was also characterized. The first draft assembly of the quince genome produced in this work would constitute a foundation for functional genomic research in quince toward dissecting the genetic basis of important traits and performing genomics-assisted breeding.