Frequency and Spectrum of Mutations Induced by Gamma Rays Revealed by Phenotype Screening and Whole-Genome Re-Sequencing in Arabidopsis thaliana

Genetic variations are an important source of germplasm diversity, as it provides an allele resource that contributes to the development of new traits for plant breeding. Gamma rays have been widely used as a physical agent for mutation creation in plants, and their mutagenic effect has attracted extensive attention. However, few studies are available on the comprehensive mutation profile at both the large-scale phenotype mutation screening and whole-genome mutation scanning. In this study, biological effects on M1 generation, large-scale phenotype screening in M2 generation, as well as whole-genome re-sequencing of seven M3 phenotype-visible lines were carried out to comprehensively evaluate the mutagenic effects of gamma rays on Arabidopsis thaliana. A total of 417 plants with visible mutated phenotypes were isolated from 20,502 M2 plants, and the phenotypic mutation frequency of gamma rays was 2.03% in Arabidopsis thaliana. On average, there were 21.57 single-base substitutions (SBSs) and 11.57 small insertions and deletions (InDels) in each line. Single-base InDels accounts for 66.7% of the small InDels. The genomic mutation frequency was 2.78 × 10−10/bp/Gy. The ratio of transition/transversion was 1.60, and 64.28% of the C > T events exhibited the pyrimidine dinucleotide sequence; 69.14% of the small InDels were located in the sequence with 1 to 4 bp terminal microhomology that was used for DNA end rejoining, while SBSs were less dependent on terminal microhomology. Nine genes, on average, were predicted to suffer from functional alteration in each re-sequenced line. This indicated that a suitable mutation gene density was an advantage of gamma rays when trying to improve elite materials for one certain or a few traits. These results will aid the full understanding of the mutagenic effects and mechanisms of gamma rays and provide a basis for suitable mutagen selection and parameter design, which can further facilitate the development of more controlled mutagenesis methods for plant mutation breeding.

A bifunctional chemical signature enabling RNA 4-thiouridine enrichment sequencing with single-base resolution

Both sequence enrichment and base resolution is essential for accurate sequencing analysis of low-abundance RNA. Yet it is hindered by the lack of molecular tools. Here we report a bifunctional...

Polyamine–Oligonucleotide Conjugates: 2′-OMe-Triazole-Linked 1,4,7,10-Tetraazacyclododecane and Intercalating Dyes and Their Effect on the Thermal Stability of DNA Duplexes

Oligonucleotides with the sequences 5′-GTG AUPA TGC, 5′-GCA TAUP CAC and 5′-GUPG ATA UPGC, where UP is 2′-O-propargyl uridine, were subjected to post-synthetic Cu(I)-catalyzed azide–alkyne cycloaddition to attach 1,4,7,10-tetraazacyclododecane (cyclen) and two well-known DNA intercalating dyes: thioxanthone and 1,8-naphthalimide. We propose a convenient cyclen protection–deprotection strategy that allows efficient separation of the resulting polyamine–oligonucleotide conjugates from the starting materials by RP-HPLC to obtain high-purity products. In this paper, we present hitherto unknown macrocyclic polyamine–oligonucleotide conjugates and their hybridization properties reflected in the thermal stability of thirty-two DNA duplexes containing combinations of labeled strands, their unmodified complementary strands, and strands with single base pair mismatches. Circular dichroism measurements showed that the B-conformation is retained for all dsDNAs consisting of unmodified and modified oligonucleotides. An additive and destabilizing effect of cyclen moieties attached to dsDNAs was observed. Tm measurements indicate that placing the hydrophobic dye opposite to the cyclen moiety can reduce its destabilizing effect and increase the thermal stability of the duplex. Interestingly, the cyclen-modified U showed significant selectivity for TT mismatch, which resulted in stabilization of the duplex. We conclude the paper with a brief review and discussion in which we compare our results with several examples of oligonucleotides labeled with polyamines at internal strand positions known in the literature.

A New Method for Correcting Deviation of Volatiles Content and Chamber Pressure for Single Base Propellant

In this study, special treatment was applied to two production batches of single-base propellant to correct three of the most important properties in the final product. These properties are internal and external volatile content (IV%, EV% respectively) and chamber pressure, the special treatments depend on mixing two batches with different percentages of mixing starting with sieving and ended with blending to guarantee the homogeneity of the final batch. The batches under study (A and B), batch A with (IV% 0.53%) which must be not less than 0.6%, so it deviated from standard requirement and Bach B with (IV =0.88%), the treatment applied for these batches to generate (C and D) batches. Batch C was a mixture composed of (25% of batch A and 0.75% of batch B). batch D was a mixture composed of (50%batchA and 50% of batch B). Six samples were subjected to sieving and blending according to calculations to correct internal and external volatile content and chamber pressure. For all samples lab, ballistics test, and executive calculations were done. After the test observed that no significant difference between the test and the results of calculations for all samples with different mixing ratios either volatiles content or chamber pressure so according to the result achieved the procedure (Method) was dependable for correcting the deviation of volatiles content and chamber pressure. The selectivity of the optimum mixing ratio can be controlled by using the equation used in this study. The importance of this study in reducing material losses due to the non-conformity of the final product with the specification.

Clinical feature-related single-base substitution sequence signatures identified with an unsupervised machine learning approach

Background Mutation processes leave different signatures in genes. For single-base substitutions, previous studies have suggested that mutation signatures are not only reflected in mutation bases but also in neighboring bases. However, because of the lack of a method to identify features of long sequences next to mutation bases, the understanding of how flanking sequences influence mutation signatures is limited. Methods We constructed a long short-term memory-self organizing map (LSTM-SOM) unsupervised neural network. By extracting mutated sequence features via LSTM and clustering similar features with the SOM, single-base substitutions in The Cancer Genome Atlas database were clustered according to both their mutation site and flanking sequences. The relationship between mutation sequence signatures and clinical features was then analyzed. Finally, we clustered patients into different classes according to the composition of the mutation sequence signatures by the K-means method and then studied the differences in clinical features and survival between classes. Results Ten classes of mutant sequence signatures (mutation blots, MBs) were obtained from 2,141,527 single-base substitutions via LSTM-SOM machine learning approach. Different features in mutation bases and flanking sequences were revealed among MBs. MBs reflect both the site and pathological features of cancers. MBs were related to clinical features, including age, sex, and cancer stage. The class of an MB in a given gene was associated with survival. Finally, patients were clustered into 7 classes according to the MB composition. Significant differences in survival and clinical features were observed among different patient classes. Conclusions We provided a method for analyzing the characteristics of mutant sequences. Result of this study showed that flanking sequences, together with mutation bases, shape the signatures of SBSs. MBs were shown related to clinical features and survival of cancer patients. Composition of MBs is a feasible predictive factor of clinical prognosis. Further study of the mechanism of MBs related to cancer characteristics is suggested.