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Background: Structural variations play a significant role in genetic diseases and evolutionary mechanisms. Extensive research has been conducted over the past decade to detect simple structural variations, leading to the development of well-established detection methods. However, recent studies have highlighted the potentially greater impact of complex structural variations on individuals compared to simple structural variations. Despite this, the field still lacks precise detection methods specifically designed for complex structural variations. Therefore, the development of a highly efficient and accurate detection method is of utmost importance., Result: In response to this need, we propose a novel method called FindCSV, which leverages deep learning techniques and consensus sequences to enhance the detection of SVs using long-read sequencing data. Compared to current methods, FindCSV performs better in detecting complex and simple structural variations., Conclusions: FindCSV is a new method to detect complex and simple structural variations with reasonable accuracy in real and simulated data. The source code for the program is available at https://github.com/nwpuzhengyan/FindCSV ., (© 2024. The Author(s).)

In this study, the phenomenon of the stability-activity trade-off, which is increasingly recognized in enzyme engineering, was explored. Typically, enhanced stability in enzymes correlates with diminished activity. Utilizing Rosa roxburghii copper-zinc superoxide dismutase ( RrCuZnSOD ) as a model, single-site mutations were introduced based on a semirational design derived from consensus sequences. The initial set of mutants was selected based on activity, followed by combinatorial mutation. This approach yielded two double-site mutants, D25/A115T (18,688 ± 206 U/mg) and A115T/S135P (18,095 ± 1556 U/mg), exhibiting superior enzymatic properties due to additive and synergistic effects. These mutants demonstrated increased half-lives ( T 1/2 ) at 80 °C by 1.2- and 1.6-fold, respectively, and their melting temperatures ( T m ) rose by 3.4 and 2.5 °C, respectively, without any loss in activity relative to the wild type. Via an integration of structural analysis and molecular dynamics simulations, we elucidated the underlying mechanism facilitating the concurrent enhancement of both thermostability and enzymatic activity.

Background: Despite the many cheap and fast ways to generate genomic data, good and exact genome assembly is still a problem, with especially the repeats being vastly underrepresented and often misassembled. As short reads in low coverage are already sufficient to represent the repeat landscape of any given genome, many read cluster algorithms were brought forward that provide repeat identification and classification. But how can trustworthy, reliable and representative repeat consensuses be derived from unassembled genomes?, Results: Here, we combine methods from repeat identification and genome assembly to derive these robust consensuses. We test several use cases, such as (1) consensus building from clustered short reads of non-model genomes, (2) from genome-wide amplification setups, and (3) specific repeat-centred questions, such as the linked vs. unlinked arrangement of ribosomal genes. In all our use cases, the derived consensuses are robust and representative. To evaluate overall performance, we compare our high-fidelity repeat consensuses to RepeatExplorer2-derived contigs and check, if they represent real transposable elements as found in long reads. Our results demonstrate that it is possible to generate useful, reliable and trustworthy consensuses from short reads by a combination from read cluster and genome assembly methods in an automatable way., Conclusion: We anticipate that our workflow opens the way towards more efficient and less manual repeat characterization and annotation, benefitting all genome studies, but especially those of non-model organisms., (© 2024. The Author(s).)

Cherry tomatoes (Lycopersicon esculentum var. cerasiforme) is the main tomato variety planted in Hainan Province, China and is prized for its nutritional value and sweet taste (Zheng et al. 2020). During October 2020 to February 2021, a leaf spot disease was observed on cherry tomatoes (cultivar Qianxi) in Chengmai, Hainan Province. The disease incidence was approximately 40% in each of three fields in Yongfa (19°76'-21°08'N, 110°21'-110°51'E). Leaves were initially chlorotic before developing black, irregular-shaped lesions on the leaf margins or tips. After several days, lesions expanded along the mid-vein to encompass the entire leaf. Then, the affected leaves turned gray-brown, leading to defoliation. Severely affected leaves became dry and necrotic. Leaf tissues of 10 diseased plants samples collected from the fields were surface sterilized in 70% ethanol for 30 s, 0.1% HgCl2 for 30 s, rinsed thrice with sterile distilled water for 30 s, placed on a modified potato dextrose agar (PDA) with 30 mg/liter of kanamycin sulfate, and incubated at 28°C in the dark for 3 to 5 days. Three fungal isolates were obtained from the diseased leaves by single-sporing. The mycelia on PDA were white and later became gray or dark gray after 3 to 4 days. Conidia were rostrate, straight to slightly curved, ellipsoidal to narrowly obclavate, dark brown, protuberant with a darker and thicker wall at the basal end. Conidia were 4 to 12 distoseptate and measured 63.92 ± 5.77 × 13.47 ± 1.22 µm (n= 50) Conidiophores were single, cylindrical, dark brown, geniculate, with swollen conidiogenous cells containing a acircular conidial scar. Morphological characteristics of the isolates were similar to those of Exserohilum rostratum (Cardona et al. 2008). A representative isolate (FQY-7) was used for pathogenicity and genomic studies. Genomic DNA was extracted from the mycelium of a representative isolate (FQY-7). The internal transcribed spacer (ITS) region, actin (act), translation elongation factor 1-alpha (tef1-α), glyceraldehydes 3-phos-phate dehydrogenase (gapdh) and β-tubulin (tub2) genes were amplified with primers ITS1/ITS4 (White et al. 1990), Act1/Act4 (Voigt and Wöstemeyer 2000), EF1-728F/EF1-986R (Carbone and Kohn 1999), Gpd-1/Gpd-2 (Berbee et al. 1999) and T1 (O'Donnell and Cigelnik 1997) + Bt2b (Glass and Donaldson 1995). The consensus sequences (GenBank Accession No. MW036279 for ITS, MW133266 for act, MW133268 for tef1-α, MW133267 for gapdh, and MW133269 for tub2) were aligned using BLAST in GenBank obtaining 100%, 100%, 99%, 100%, and 99% identity to E. rostratum strain CBS706 (LT837842, LT837674, LT896663, LT882546, LT899350). Maximum likelihood analysis based on the combined five gene sequences was conducted under 1,000 bootstrap replicates. The Phylogenetic tree showed that FQY-7 and E. rostratum were located in one clade supported with 99% bootstrap values. Pathogenicity test was performed by depositing 10-µl droplets of a conidial suspension (1 × 106 per ml) into 5 noninoculated leaves (using a sterile needle) of 10 healthy 5-month-old cherry tomato (cv. Qianxi) plants. An equal number of artificially control leaves were received only sterile water to serve as a negative control. The test was conducted three times. Plants were kept at 28°C with 80% humidity and observed for symptoms every day. Two weeks after inoculation, all the inoculated plants showed symptoms of black spots similar to those observed in the field. No symptoms were observed on the controls. FQY-7 was successfully re-isolated from the inoculated leaves and confirmed by morphological characterization and molecular assays as described herein. To the best of our knowledge, this is the first report of leaf spot of cherry tomatoes caused by E. rostratum in China. Confirming the existence of this pathogen in this area will be useful to adopt effective field management measures to control this disease on cherry tomatoes. References: Berbee, M. L., et al. 1999. Mycologia 91:964. Cardona, R. et al. 2008. Bioagro 20:141. Carbone, I. and Kohn, L. M. 1999. Mycologia 91:553. Glass, N. L., and Donaldson, G. C. 1995. Appl. Environl. Microb. 61:1323. White, T. J., et al. 1990. Page 315 in: PCR Protocols: A Guide to Methods and Applications. Academic Press, San Diego, CA. O'Donnell K., and Cigelnik, E. 1997. Mol. Phylogenet. Evol. 7:103. Voigt, K., and Wöstemeyer, J. 2000. Microbiol. Res. J. 155:179. Zheng J., et al. 2020. Guangdong Agr. Sci. 47:212. The author(s) declare no conflict of interest.

The advent of advanced NGS technologies have led to the generation of enormous amount of sequence data which further aid in the discovery of the various type of markers such as SSRs, SNPs, InDels, etc. Among all these markers, microsatellite SSR markers can be mined from the ddRADseq data as certain properties of SSR markers make them ideal markers for study. These assist researchers and breeders in diversity analysis and producing new varieties with desired traits. To extract the markers, first, the ddRADseq data is assembled into consensus sequences using STACKS program which are further assembled for mining microsatellites using QDD along with MISA tool., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Transposable elements (TEs) exert an increasingly diverse spectrum of influences on eukaryotic genome structure, function, and evolution. A deluge of genomic, transcriptomic, and proteomic data provides the foundation for turning essentially any non-model eukaryotic species into an emerging model to study any and all aspects of organismal biology, ultimately shaping future directions for biomedical, environmental, and biodiversity research. However, identification and annotation of the mobile genome component still lags behind the standards accepted for host gene annotation. To achieve the objective of providing every genome project with a comprehensive description of its mobilome component in addition to the standard genic and transcriptomic datasets, each step of TE identification, classification, and annotation should be focused on improving TE boundary designation, reducing identification error rates, and providing accurate information on the type and integrity of TE insertions. Here, we offer practical advice for generating TE models in de novo assemblies for non-model organisms, provide step-by-step instructions to guide inexperienced TE annotators through some of the commonly utilized TE analysis pipelines, and entertain suggestions for tool improvement which could be implemented by interested developers., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

HIV consensus sequences are used in various bioinformatic, evolutionary, and vaccine related research. Since the previous HIV-1 subtype and CRF consensus sequences were constructed in 2002, the number of publicly available HIV-1 sequences have grown exponentially, especially from non-EU and US countries. Here, we reconstruct 90 new HIV-1 subtype and CRF consensus sequences from 3,470 high-quality, representative, full genome sequences in the LANL HIV database. While subtypes and CRFs are unevenly spread across the world, in total 89 countries were represented. For consensus sequences that were based on at least 20 genomes, we found that on average 2.3% (range 0.8-10%) of the consensus genome site states changed from 2002 to 2021, of which about half were nucleotide state differences and the rest insertions and deletions. Interestingly, the 2021 consensus sequences were shorter than in 2002, and compared to 4,674 HIV-1 worldwide genome sequences, the 2021 consensuses were somewhat closer to the worldwide genome sequences, i.e., showing on average fewer nucleotide state differences. Some subtypes/CRFs have had limited geographical spread, and thus sampling of subtypes/CRFs is uneven, at least in part, due to the epidemiological dynamics. Thus, taken as a whole, the 2021 consensus sequences likely are good representations of the typical subtype/CRF genome nucleotide states. The new consensus sequences are available at the LANL HIV database., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Linchangco, Foley and Leitner.)

In extremely cold environments, living organisms like plants, animals, fishes, and microbes can die due to the intracellular ice formation in their bodies. To sustain life in such cold environments, some cold-blooded species produced Antifreeze proteins (AFPs), also called ice-binding proteins. AFPs are not only limited to the medical field but also have diverse significance in the area of biotechnology, agriculture, and the food industry. Different AFPs exhibit high heterogeneity in their structures and sequences. Keeping the significance of AFPs, several machine-learning-based models have been developed by scientists for the prediction of AFPs. However, due to the complex and diverse nature of AFPs, the prediction performance of the existing methods is limited. Therefore, it is highly indispensable for researchers to develop a reliable computational model that can accurately predict AFPs. In this connection, this study presents a novel predictor for AFPs, named AFP-CMBPred. The sequences of AFPs are formulated via four different feature representation methods, such as Amphiphilic pseudo amino acid composition (Amp-PseAAC), Dipeptide Deviation from Expected Mean (DDE), Multi-Blocks Position Specific Scoring Matrix (MB-PSSM), and Consensus Sequence-based on Multi-Blocks Position Specific Scoring Matrix (CS-MB-PSSM) to collect local and global descriptors. In the next step, the extracted feature vectors are evaluated via Support Vector Machine (SVM) and Random Forest (RF) based classification learners. The prediction performance of both classifiers is further assessed using three validation methods i.e., jackknife test, 10-fold cross-validation test, and independent test. After examining the prediction rates of all validation tests, it was found that our proposed model achieved the higher prediction accuracies of ∼2.65%, ∼2.84%, and ∼3.37% using jackknife, K-fold, and independent test, respectively. The experimental outcomes validate that our proposed "AFP-CMBPred" predictor secured the highest prediction results than the existing models for the identification of AFPs. It is further anticipated that our proposed AFP-CMBPred model will be considered a valuable tool in the research academia and drug development., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Protein phosphorylation is the most frequent post-translational modification by which the properties of eukaryotic proteins can be reversibly modified. In humans, over 500 protein kinases generate a huge phosphoproteome including more than 200,000 individual phosphosites, a figure which is still continuously increasing. The in vivo selectivity of protein kinases is the outcome of a multifaceted and finely tuned process where numerous factors play an integrated role. To gain information about the actual contribution to this process of local features that reflect the interaction of the protein targets with the catalytic site of the kinases, the prevalence of the commonest motifs determining the consensus sequence of Ser/Thr-specific kinases has been examined in the whole human phosphoproteome and in the phosphoproteomes generated by a panel of the 47 most pleiotropic protein kinases. Our analysis shows that: (1) most phosphosites do conform to at least one of the motifs considered, with a substantial proportion conforming to two or more of them; (2) some motifs, with special reference to the one recognized by protein kinase CK2 (pS/pT-x-x-E/D) are very promiscuous, being abundantly represented also at the phosphosites of all the other protein kinases considered; (3) by contrast, other phosphorylated motifs, notably pS/pT-P, pS/pT-Q and pS-x-E, are more discriminatory and selective, being nearly absent in the phosphosites that are not attributable to certain categories of kinases. The information provided will prove helpful to make reliable inferences based on the manual inspection of individual phosphosites.

The goal of protein design is to create proteins that are stable, soluble, and active. Here we focus on one approach to protein design in which sequence information is used to create a "consensus" sequence. Such consensus sequences comprise the most common residue at each position in a multiple sequence alignment (MSA). After describing some general ideas that relate MSA and consensus sequences and presenting a statistical thermodynamic framework that relates consensus and non-consensus sequences to stability, we detail the process of designing a consensus sequence and survey reports of consensus design and characterization from the literature. Many of these consensus proteins retain native biological activities including ligand binding and enzyme activity. Remarkably, in most cases the consensus protein shows significantly higher stability than extant versions of the protein, as measured by thermal or chemical denaturation, consistent with the statistical thermodynamic model. To understand this stability increase, we compare various features of consensus sequences with the extant MSA sequences from which they were derived. Consensus sequences show enrichment in charged residues (most notably glutamate and lysine) and depletion of uncharged polar residues (glutamine, serine, and asparagine). Surprisingly, a survey of stability changes resulting from point substitutions show little correlation with residue frequencies at the corresponding positions within the MSA, suggesting that the high stability of consensus proteins may result from interactions among residue pairs or higher-order clusters. Whatever the source, the large number of reported successes demonstrates that consensus design is a viable route to generating active and in many cases highly stabilized proteins., (© 2020 Elsevier Inc. All rights reserved.)

A nuclear export signal (NES) is a protein localization signal, which is involved in binding of cargo proteins to nuclear export receptor, thus contributes to regulate localization of cellular proteins. Consensus sequences of NES have been used to detect NES from protein sequences, but suffer from poor predictive power. Some recent peering works were proposed to use biochemical properties of experimental verified NES to refine NES candidates. Those methods can achieve high prediction rates, but their execution time will become unacceptable for large-scale NES searching if too much properties are involved. In this work, we developed a novel computational approach, named NES-REBS, to search NES from protein sequences, where biochemical properties of experimental verified NES, including secondary structure and surface accessibility, are utilized to refine NES candidates obtained by matching popular consensus sequences. We test our method by searching 262 experimental verified NES from 221 NES-containing protein sequences. It is obtained that NES-REBS runs in 2-3[Formula: see text]mins and performs well by achieving precision rate 47.2% and sensitivity 54.6%.

The splice-site sequences of U2-type introns are highly degenerate, so many different sequences can function as U2-type splice sites. Using our new profiles based on hydrophobicity properties we pointed out specific properties for regions surrounding splice sites. We built a set T of flanking regions of genes with 1-3 introns from 21st and 22nd chromosomes extracted from GenBank to define positions having conserved properties, namely hydrophobicity, that are potentially essential for recognition by spliceosome. GT-AG introns exist in U2 and U12-types. Therefore, intron type cannot be simply determined by the dinucleotide termini. We attempted to distinguish U2 and U12-types introns with help of hydrophobicity profiles on sets of spice sites for U2 or U12-type introns extracted from SpliceRack database. The positions given by our method, which may be important for recognition by spliceosome, were compared to the nucleotide consensus provided by a classical method, Pictogram. We showed that there is a similarity of hydrophobicity profiles inside intron types. On one hand, GT-AG and GC-AG introns belonging to U2-type have resembling hydrophobicity profiles as well as AT-AC and GT-AG introns belonging to U12-type. On the other hand, hydrophobicity profiles of U2 and U12-types GT-AG introns are completely different. We suggest that hydrophobicity profiles facilitate definition of intron type, distinguishing U2 and U12 intron types and can be used to build programs to search splice site and to evaluate their strength. Therefore, our study proves that hydrophobicity profiles are informative method providing insights into mechanisms of splice sites recognition.