Background Flax (Linum usitatissimum L.) is grown for fiber and seed in many countries. Flax cultivars differ in the oil composition and, depending on the ratio of fatty acids, are used in pharmaceutical, food, or paint industries. It is known that genes of SAD (stearoyl-ACP desaturase) and FAD (fatty acid desaturase) families play a key role in the synthesis of fatty acids, and some alleles of these genes are associated with a certain composition of flax oil. However, data on genetic polymorphism of these genes are still insufficient. Results On the basis of the collection of the Institute for Flax (Torzhok, Russia), we formed a representative set of 84 cultivars and lines reflecting the diversity of fatty acid composition of flax oil. An approach for the determination of full-length sequences of SAD1, SAD2, FAD2A, FAD2B, FAD3A, and FAD3B genes using the Illumina platform was developed and deep sequencing of the 6 genes in 84 flax samples was performed on MiSeq. The obtained high coverage (about 400x on average) enabled accurate assessment of polymorphisms in SAD1, SAD2, FAD2A, FAD2B, FAD3A, and FAD3B genes and evaluation of cultivar/line heterogeneity. The highest level of genetic diversity was observed for FAD3A and FAD3B genes – 91 and 62 polymorphisms respectively. Correlation analysis revealed associations between particular variants in SAD and FAD genes and predominantly those fatty acids whose conversion they catalyze: SAD – stearic and oleic acids, FAD2 – oleic and linoleic acids, FAD3 – linoleic and linolenic acids. All except one low-linolenic flax cultivars/lines contained both the substitution of tryptophan to stop codon in the FAD3A gene and histidine to tyrosine substitution in the FAD3B gene, while samples with only one of these polymorphisms had medium content of linolenic acid and cultivars/lines without them were high-linolenic. Conclusions Genetic polymorphism of SAD and FAD genes was evaluated in the collection of flax cultivars and lines with diverse oil composition, and associations between particular polymorphisms and the ratio of fatty acids were revealed. The achieved results are the basis for the development of marker-assisted selection and DNA-based certification of flax cultivars.

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Accurate and reliable identification of chemical compounds is the ultimate goal of mass spectrometry analyses. Currently, identification of compounds is usually based on the measurement of the accurate mass and fragmentation spectrum, chromatographic elution time, and collisional cross section. Unfortunately, despite the growth of databases of experimentally measured MS/MS spectra (such as MzCloud and Metlin) and developing software for predicting MS/MS fragments in silico from SMILES patterns (such as MetFrag, CFM-ID, and Ms-Finder), the problem of identification is still unsolved. The major issue is that the elution time and fragmentation spectra depend considerably on the equipment used and are not the same for different LC-MS systems. It means that any additional descriptors depending only on the structure of the chemical compound will be of big help for LC-MS/MS-based omics. Our approach is based on the characterization of compounds by the number of labile hydrogen and oxygen atoms in the molecule, which can be measured using hydrogen/deuterium and 16O/18O-exchange approaches. The number of labile atoms (those from −OH, −NH, O, and −COOH groups) can be predicted from SMILES patterns and serves as an additional structural descriptor when performing a database search. In addition, distribution of isotope labels among MS/MS fragments can be roughly predicted by software such as MetFrag or CFM-ID. Here, we present an approach utilizing the selection of structural candidates from a database on the basis of the number of functional groups and analysis of isotope labels distribution among fragments. It was found that our approach allows reduction of the search space by a factor of 10 and considerably increases the reliability of the compound identification.

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Dissociation induced by the accumulation of internal energy via collisions of ions with neutral molecules is one of the most important fragmentation techniques in mass spectrometry (MS), and the identification of small singly charged molecules is based mainly on the consideration of the fragmentation spectrum. Many research studies have been dedicated to the creation of databases of experimentally measured tandem mass spectrometry (MS/MS) spectra (such as MzCloud, Metlin, etc.) and developing software for predicting MS/MS fragments in silico from the molecular structure (such as MetFrag, CFM-ID, CSI:FingerID, etc.). However, the fragmentation mechanisms and pathways are still not fully understood. One of the limiting obstacles is that protomers (positive ions protonated at different sites) produce different fragmentation spectra, and these spectra overlap in the case of the presence of different protomers. Here, we are proposing to use a combination of two powerful approaches: computing fragmentation trees that carry information of all consecutive fragmentations and consideration of the MS/MS data of isotopically labeled compounds. We have created PyFragMS—a web tool consisting of a database of annotated MS/MS spectra of isotopically labeled molecules (after H/D and/or 16 O/ 18 O exchange) and a collection of instruments for computing fragmentation trees for an arbitrary molecule. Using PyFragMS, we investigated how the site of protonation influences the fragmentation pathway for small molecules. Also, PyFragMS offers capabilities for performing database search when MS/MS data of the isotopically labeled compounds are taken into account.