Formation of the Codon Degeneracy during Interdependent Development between Metabolism and Replication

Nirenberg’s genetic code chart shows a profound correspondence between codons and amino acids. The aim of this article is to try to explain the primordial formation of the codon degeneracy. It remains a puzzle how informative molecules arose from the supposed prebiotic random sequences. If introducing an initial driving force based on the relative stabilities of triplex base pairs, the prebiotic sequence evolution became innately nonrandom. Thus, the primordial assignment of the 64 codons to the 20 amino acids has been explained in detail according to base substitutions during the coevolution of tRNAs with aaRSs; meanwhile, the classification of aaRSs has also been explained.

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.

C-to-G Base Editing Enhances Oleic Acid Production by Generating Novel Alleles of FATTY ACID DESATURASE 2 in Plants

The demand for vegetable oil, which is mainly used for dietary purposes and cooking, is steadily increasing worldwide. It is often desirable to reduce unsaturation levels of fatty acids in order to increase storage stability and reduce trans-fat generation during cooking. Functional disruption of FATTY ACID DESATURASE 2 (FAD2) prevents the conversion of monounsaturated oleic acid to polyunsaturated linoleic acid, thereby enhancing the production of the desirable oleic acid. However, FAD2 null alleles, due to growth defects under stress conditions, are impractical for agronomical purposes. Here, we aimed to attenuate FAD2 activity in planta while avoiding adverse growth effects by introducing amino-acid substitutions using CRISPR base editors. In Arabidopsis, we applied the adenine base editor (ABE) and cytosine base editor (CBE) to induce semi-random base substitutions within several selected FAD2 coding regions. Isolation of base-edited fad2 alleles with higher oleic acid revealed that the CBE application induced C-to-T and/or C-to-G base substitutions within the targeted sequences, resulting in an alteration of the FAD2 enzyme activities; for example, fad2-144 with multiple C-to-G base substitutions showed less growth defects but with a significant increase in oleic acids by 3-fold higher than wild type. Our “proof-of-concept” approach suggests that equivalent alleles may be generated in vegetable oil crops via precision genome editing for practical cultivation. Our targeted semi-random strategy may serve as a new complementary platform for planta engineering of useful agronomic traits.

Comprehensive analysis of clustered mutations in cancer reveals recurrent APOBEC3 mutagenesis of ecDNA

Clustered somatic mutations are common in cancer genomes with prior analyses revealing several types of clustered single-base substitutions, including doublet- and multi-base substitutions, diffuse hypermutation termed omikli, and longer strand-coordinated events termed kataegis. Here, we provide a comprehensive characterization of clustered substitutions and clustered small insertions and deletions (indels) across 2,583 whole-genome sequenced cancers from 30 cancer types. While only 3.7% of substitutions and 0.9% of indels were found to be clustered, they contributed 8.4% and 6.9% of substitution and indel drivers, respectively. Multiple distinct mutational processes gave rise to clustered indels including signatures enriched in tobacco smokers and homologous-recombination deficient cancers. Doublet-base substitutions were caused by at least 12 mutational processes, while the majority of multi-base substitutions were generated by either tobacco smoking or exposure to ultraviolet light. Omikli events, previously attributed to the activity of APOBEC3 deaminases, accounted for a large proportion of clustered substitutions. However, only 16.2% of omikli matched APOBEC3 patterns with experimental validation confirming additional mutational processes giving rise to omikli. Kataegis was generated by multiple mutational processes with 76.1% of all kataegic events exhibiting AID/APOBEC3-associated mutational patterns. Co-occurrence of APOBEC3 kataegis and extrachromosomal-DNA (ecDNA) was observed in 31% of samples with ecDNA. Multiple distinct APOBEC3 kataegic events were observed on most mutated ecDNA. ecDNA containing known cancer genes exhibited both positive selection and kataegic hypermutation. Our results reveal the diversity of clustered mutational processes in human cancer and the role of APOBEC3 in recurrently mutating and fueling the evolution of ecDNA.

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, gender, 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.

Genotype-by-Sequencing Analysis of Mutations and Recombination in Pepper Progeny of Gamma-Irradiated Gametophytes

The irradiation of dry seeds is the most widely-used irradiation method for improving seed-propagated crops; however, the irradiation of other tissues also has useful effects. The irradiation of plant reproductive organs, rather than seeds, for mutation breeding has advantages, such as producing non-chimeric progeny. However, the mutation frequency and spectrum produced using this method have not been analyzed on a genome-wide level. We performed a genotype-by-sequencing analysis to determine the frequencies of single-base substitutions and small (1–2 bp) insertions and deletions in hot pepper (Capsicum annuum L.) plants derived from crosses using gamma-irradiated female or male gametophytes. The progeny of irradiated gametophytes showed similar or higher DNA mutation frequencies, which were dependent on the irradiation dose and irradiated tissue, and less biased single base substitutions than progeny of irradiated seeds. These characteristics were expected to be beneficial for development of mutation population with a high frequency of small DNA mutations and performing reverse-genetics-based mutation screening. We also examined the possible use of this irradiation method in manipulating the meiotic recombination frequency; however, no statistically significant increase was detected. Our results provide useful information for further research and breeding using irradiated gametophytes.

Evolution of the genetic code; Evidence from serine codon use disparity inEscherichia coli

Among the 20 amino acids, three of them—leucine (Leu), arginine (Arg), and serine (Ser)—are encoded by six different codons. In comparison, all of the other 17 amino acids are encoded by either 4, 3, 2, or 1 codon. Peculiarly, Ser is separated into two disparate Ser codon boxes, differing by at least two-base substitutions, in contrast to Leu and Arg, of which codons are mutually exchangeable by a single-base substitution. We propose that these two different Ser codons independently emerged during evolution. In this hypothesis, at the time of the origin of life there were only seven primordial amino acids: Valine (coded by GUX [X = U, C, A or G]), alanine (coded by GCX), aspartic acid (coded by GAY [Y = U or C]), glutamic acid (coded by GAZ [Z = A or G]), glycine (coded by GGX), Ser (coded by AGY), and Arg (coded by CGX and AGZ). All of these were derived from GGX for glycine by single-base substitutions. Later in evolution, another class of Ser codons, UCX, were derived from alanine codons, GCX, distinctly different from the other primordial Ser codon, AGY. From the analysis of theEscherichia coligenome, we find extensive disparities in the usage of these two Ser codons, as some genes use only AGY for Ser in their genes. In contrast, others use only UCX, pointing to distinct differences in their origins, consistent with our hypothesis.

Generating realistic null hypothesis of cancer mutational landscapes using SigProfilerSimulator

Background Performing a statistical test requires a null hypothesis. In cancer genomics, a key challenge is the fast generation of accurate somatic mutational landscapes that can be used as a realistic null hypothesis for making biological discoveries. Results Here we present SigProfilerSimulator, a powerful tool that is capable of simulating the mutational landscapes of thousands of cancer genomes at different resolutions within seconds. Applying SigProfilerSimulator to 2144 whole-genome sequenced cancers reveals: (i) that most doublet base substitutions are not due to two adjacent single base substitutions but likely occur as single genomic events; (ii) that an extended sequencing context of ± 2 bp is required to more completely capture the patterns of substitution mutational signatures in human cancer; (iii) information on false-positive discovery rate of commonly used bioinformatics tools for detecting driver genes. Conclusions SigProfilerSimulator’s breadth of features allows one to construct a tailored null hypothesis and use it for evaluating the accuracy of other bioinformatics tools or for downstream statistical analysis for biological discoveries. SigProfilerSimulator is freely available at https://github.com/AlexandrovLab/SigProfilerSimulator with an extensive documentation at https://osf.io/usxjz/wiki/home/.