SNAP: predict effect of non-synonymous polymorphisms on function

The Gastrodia menghaiensis (Orchidaceae) genome provides new insights of orchid mycorrhizal interactions

BACKGROUND

To illustrate the molecular mechanism of mycoheterotrophic interactions between orchids and fungi, we assembled chromosome-level reference genome of Gastrodia menghaiensis (Orchidaceae) and analyzed the genomes of two species of Gastrodia.

RESULTS

Our analyses indicated that the genomes of Gastrodia are globally diminished in comparison to autotrophic orchids, even compared to Cuscuta (a plant parasite). Genes involved in arbuscular mycorrhizae colonization were found in genomes of Gastrodia, and many of the genes involved biological interaction between Gatrodia and symbiotic microbionts are more numerous than in photosynthetic orchids. The highly expressed genes for fatty acid and ammonium root transporters suggest that fungi receive material from orchids, although most raw materials flow from the fungi. Many nuclear genes (e.g. biosynthesis of aromatic amino acid L-tryptophan) supporting plastid functions are expanded compared to photosynthetic orchids, an indication of the importance of plastids even in totally mycoheterotrophic species.

CONCLUSION

Gastrodia menghaiensis has the smallest proteome thus far among angiosperms. Many of the genes involved biological interaction between Gatrodia and symbiotic microbionts are more numerous than in photosynthetic orchids.

Whole-genome resequencing reveals genomic footprints of Italian sweet and hot pepper heirlooms giving insight into genes underlying key agronomic and qualitative traits

BACKGROUND

Pepper is a major crop species of the Solanaceae family, largely appreciated for its high nutritional and healthy contribution to human diets. In the Mediterranean basin, the favorable pedoclimatic conditions enhanced the selection of several diversified landraces cultivated pepper (Capsicum annuum), for whom Italy can be considered a main pole of diversification. Hence, a survey of traditional C. annuum genetic resources is essential for deep understanding of such diversity and for applications in genomics assisted breeding. Here, we report whole-genome resequencing analyses of two sweet and two pungent genotypes highly diffused in South Italy and representative of the variability for shape, colour and nutritional properties.

RESULTS

The four genomes were reconstructed at a chromosomal scale using a reference-guided approach, based on a dataset of 2.6 billion paired-end reads, corresponding to 20× genome coverage and a mapping rate above 99% for a final genomes size of approximately 3 Gb. After five iterations of variant calling, a total of 29,258,818 single nucleotide polymorphisms (SNPs) and 1,879,112 InDels, were identified. Substantial differences were observed among the four genomes based on geographical origin, with chromosomes 9 and 11 showing more polymorphisms in the accessions with higher fruit weight and absence of pungency. Among the identified variants, a small private indel (T - > TA) shared between sweet and big fruits accessions induces a frameshift with the generation of a new stop codon in a gene annotated as extensin, whereas two private SNPs within hot types were identified in 1-aminocyclopropane-1-carboxylate oxidase (ACO), a key gene involved in fruit ripening. The estimation of repetitive elements highlights a preponderant presence of Long Terminal Repeats (LTRs), the majority of which belonged to Gypsy superfamily. By comparing the four genomes with publicly available references including 'CM334' and Zunla-1 highlight the presence of 49,475 shared gene families.

CONCLUSIONS

The new genomic sequences aim to enrich the whole genome information of pepper local varieties, providing a valuable tool for precision gene mapping, marker discovery, comparative studies. Such knowledge widens the frontiers to understand the selection history of Italian pepper landraces toward the recognition of specificity local agri-food products marks.

Unraveling structural and conformational dynamics of DGAT1 missense nsSNPs in dairy cattle

Cattle are domestic animals that have been nourishing humans for thousands of years. Milk from cattle represents a key source of high-quality protein, fat, and other nutrients. The nutritional value of milk and dairy products is closely associated with the fat content, providing up to 30% of the total fat consumed in the human diet. The fat content in cattle milk represents a major concern for the scientific community due to its association with human health. The relationship between milk fat content and diacylglycerol o-acyltransferase 1 gene (DGAT1) is well described in literature. Several studies demonstrated the difference in fat contents and other milk production traits in a wide range of cattle breeds, to be associated with missense non-synonymous single nucleotide polymorphisms (nsSNPs) of the DGAT1 gene. As a result, an nsSNPs analysis is crucial for unraveling the DGAT1 structural and conformational dynamics linked to milk fat content. DGAT1-nsSNPs are yet to be studied in terms of their structural and functional impact. Therefore, state-of-the-art computational and structural genomic methods were used to analyze five selected variants (W128R, W214R, C215G, P245R, and W459G), along with the wild type DGAT1. Significant structural and conformational changes in the variants were observed. We illustrate how single amino acid substitutions affect DGAT1 function, how this contributes to our understanding of the molecular basis of variations in DGAT1, and ultimately its impact in improving fat quality in milk.

Genome-Wide Survey and Development of the First Microsatellite Markers Database (AnCorDB) in Anemone coronaria L

Anemone coronaria L. (2n = 2x = 16) is a perennial, allogamous, highly heterozygous plant marketed as a cut flower or in gardens. Due to its large genome size, limited efforts have been made in order to develop species-specific molecular markers. We obtained the first draft genome of the species by Illumina sequencing an androgenetic haploid plant of the commercial line “MISTRAL^® Magenta”. The genome assembly was obtained by applying the MEGAHIT pipeline and consisted of 2 × 10⁶ scaffolds. The SciRoKo SSR (Simple Sequence Repeats)-search module identified 401.822 perfect and 188.987 imperfect microsatellites motifs. Following, we developed a user-friendly “Anemone coronaria Microsatellite DataBase” (AnCorDB), which incorporates the Primer3 script, making it possible to design couples of primers for downstream application of the identified SSR markers. Eight genotypes belonging to eight cultivars were used to validate 62 SSRs and a subset of markers was applied for fingerprinting each cultivar, as well as to assess their intra-cultivar variability. The newly developed microsatellite markers will find application in Breeding Rights disputes, developing genetic maps, marker assisted breeding (MAS) strategies, as well as phylogenetic studies.

Autosomal Recessive Cerebellar Atrophy and Spastic Ataxia in Patients With Pathogenic Biallelic Variants in GEMIN5

The hereditary ataxias are a heterogenous group of disorders with an increasing number of causative genes being described. Due to the clinical and genetic heterogeneity seen in these conditions, the majority of such individuals endure a diagnostic odyssey or remain undiagnosed. Defining the molecular etiology can bring insights into the responsible molecular pathways and eventually the identification of therapeutic targets. Here, we describe the identification of biallelic variants in the GEMIN5 gene among seven unrelated families with nine affected individuals presenting with spastic ataxia and cerebellar atrophy. GEMIN5, an RNA-binding protein, has been shown to regulate transcription and translation machinery. GEMIN5 is a component of small nuclear ribonucleoprotein (snRNP) complexes and helps in the assembly of the spliceosome complexes. We found that biallelic GEMIN5 variants cause structural abnormalities in the encoded protein and reduce expression of snRNP complex proteins in patient cells compared with unaffected controls. Finally, knocking out endogenous Gemin5 in mice caused early embryonic lethality, suggesting that Gemin5 expression is crucial for normal development. Our work further expands on the phenotypic spectrum associated with GEMIN5-related disease and implicates the role of GEMIN5 among patients with spastic ataxia, cerebellar atrophy, and motor predominant developmental delay.

Whole genome sequence analysis showing unique SARS-CoV-2 lineages of B.1.524 and AU.2 in Malaysia

SARS-CoV-2 has spread throughout the world since its discovery in China, and Malaysia is no exception. WGS has been a crucial approach in studying the evolution and genetic diversity of SARS-CoV-2 in the ongoing pandemic. Despite considerable number of SARS-CoV-2 genome sequences have been submitted to GISAID and NCBI databases, there is still scarcity of data from Malaysia. This study aims to report new Malaysian lineages of the virus, responsible for the sustained spikes in COVID-19 cases during the third wave of the pandemic. Patients with nasopharyngeal and/or oropharyngeal swabs confirmed COVID-19 positive by real-time RT-PCR with CT value < 25 were chosen for WGS. The selected SARS-CoV-2 isolates were then sequenced, characterized and analyzed along with 986 sequences of the dominant lineages of D614G variants currently circulating throughout Malaysia. The prevalence of clade GH and G formed strong ground for the presence of two Malaysian lineages of AU.2 and B.1.524 that has caused sustained spikes of cases in the country. Statistical analysis on the association of gender and age group with Malaysian lineages revealed a significant association (p <0.05). Phylogenetic analysis revealed dispersion of 41 lineages, of these, 22 lineages are still active. Mutational analysis showed presence of unique G1223C missense mutation in transmembrane domain of the spike protein. For better understanding of the SARS-CoV-2 evolution in Malaysia especially with reference to the reported lineages, large scale studies based on WGS are warranted.

Identification of destabilizing SNPs in SARS-CoV2-ACE2 protein and spike glycoprotein: implications for virus entry mechanisms

COVID-19 an outbreak of a novel corona virus originating from Wuhan, China in December 2019 has now spread across the entire world and has been declared a pandemic by WHO. Angiotensin converting enzyme 2 (ACE2) is a receptor protein that interacts with the spike glycoprotein of the host to facilitate the entry of coronavirus (SARS-CoV-2) hence causing the disease (COVID-19). Our experimental design is based on bioinformatics approach that combines sequence, structure and consensus based tools to label a protein coding single nucleotide polymorphism (SNP) as damaging/deleterious or neutral. The interaction of wildtype ACE2-spike glycoprotein and their variants were analyzed using docking studies. The mutations W461R, G405E and F588S in ACE2 receptor protein and population specific mutations P391S, C12S and G1223A in the spike glycoprotein were predicted as highly destabilizing to the structure of the bound complex. So far, no extensive in silico study has been reported that identifies the effect of SNPs on Spike glycoprotein-ACE2 interaction exploring both sequence and structural features. To this end, this study conducted an in-depth analysis that facilitates in identifying the mutations that blocks the interaction of two proteins that can result in stopping the virus from entering the host cell.Communicated by Ramaswamy H. Sarma.

The Chromosome-Level Genome of Miracle Fruit (Synsepalum dulcificum) Provides New Insights Into the Evolution and Function of Miraculin

Miracle fruit (Synsepalum dulcificum) is a rare valuable tropical plant famous for a miraculous sweetening glycoprotein, miraculin, which can modify sour flavors to sweet flavors tasted by humans. Here, we present a chromosome-level high-quality genome of S. dulcificum with an assembly genome size of ∼550 Mb, contig N50 of ∼14.14 Mb, and 37,911 annotated protein-coding genes. Phylogenetic analysis revealed that S. dulcificum was most closely related to Camellia sinensis and Diospyros oleifera, and that S. dulcificum diverged from the Diospyros genus ∼75.8 million years ago (MYA), and that C. sinensis diverged from Synsepalum ∼63.5 MYA. Ks assessment and collinearity analysis with S. dulcificum and other species suggested that a whole-genome duplication (WGD) event occurred in S. dulcificum and that there was good collinearity between S. dulcificum and Vitis vinifera. On the other hand, transcriptome and metabolism analysis with six tissues containing three developmental stages of fleshes and seeds of miracle fruit revealed that Gene Ontology (GO) terms and metabolic pathways of "cellular response to chitin," "plant-pathogen interaction," and "plant hormone signal transduction" were significantly enriched during fruit development. Interestingly, the expression of miraculin (Chr10G0299340) progressively increased from vegetative organs to reproductive organs and reached an incredible level in mature fruit flesh, with an fragments per kilobase of transcript per million (FPKM) value of ∼113,515, which was the most highly expressed gene among all detected genes. Combining the unique signal peptide and the presence of the histidine-30 residue together composed the main potential factors impacting miraculin's unique properties in S. dulcificum. Furthermore, integrated analysis of weighted gene coexpression network analysis (WGCNA), enrichment and metabolite correlation suggested that miraculin plays potential roles in regulating plant growth, seed germination and maturation, resisting pathogen infection, and environmental pressure. In summary, valuable genomic, transcriptomic, and metabolic resources provided in this study will promote the utilization of S. dulcificum and in-depth research on species in the Sapotaceae family.

Computational Saturation Mutagenesis of SARS-CoV-1 Spike Glycoprotein: Stability, Binding Affinity, and Comparison With SARS-CoV-2

Severe Acute respiratory syndrome coronavirus (SARS-CoV-1) attaches to the host cell surface to initiate the interaction between the receptor-binding domain (RBD) of its spike glycoprotein (S) and the human Angiotensin-converting enzyme (hACE2) receptor. SARS-CoV-1 mutates frequently because of its RNA genome, which challenges the antiviral development. Here, we per-formed computational saturation mutagenesis of the S protein of SARS-CoV-1 to identify the residues crucial for its functions. We used the structure-based energy calculations to analyze the effects of the missense mutations on the SARS-CoV-1 S stability and the binding affinity with hACE2. The sequence and structure alignment showed similarities between the S proteins of SARS-CoV-1 and SARS-CoV-2. Interestingly, we found that target mutations of S protein amino acids generate similar effects on their stabilities between SARS-CoV-1 and SARS-CoV-2. For example, G839W of SARS-CoV-1 corresponds to G857W of SARS-CoV-2, which decrease the stability of their S glycoproteins. The viral mutation analysis of the two different SARS-CoV-1 isolates showed that mutations, T487S and L472P, weakened the S-hACE2 binding of the 2003–2004 SARS-CoV-1 isolate. In addition, the mutations of L472P and F360S destabilized the 2003–2004 viral isolate. We further predicted that many mutations on N-linked glycosylation sites would increase the stability of the S glycoprotein. Our results can be of therapeutic importance in the design of antivirals or vaccines against SARS-CoV-1 and SARS-CoV-2.

Prediction of disease-associated nsSNPs by integrating multi-scale ResNet models with deep feature fusion

More than 6000 human diseases have been recorded to be caused by non-synonymous single nucleotide polymorphisms (nsSNPs). Rapid and accurate prediction of pathogenic nsSNPs can improve our understanding of the principle and design of new drugs, which remains an unresolved challenge. In the present work, a new computational approach, termed MSRes-MutP, is proposed based on ResNet blocks with multi-scale kernel size to predict disease-associated nsSNPs. By feeding the serial concatenation of the extracted four types of features, the performance of MSRes-MutP does not obviously improve. To address this, a second model FFMSRes-MutP is developed, which utilizes deep feature fusion strategy and multi-scale 2D-ResNet and 1D-ResNet blocks to extract relevant two-dimensional features and physicochemical properties. FFMSRes-MutP with the concatenated features achieves a better performance than that with individual features. The performance of FFMSRes-MutP is benchmarked on five different datasets. It achieves the Matthew's correlation coefficient (MCC) of 0.593 and 0.618 on the PredictSNP and MMP datasets, which are 0.101 and 0.210 higher than that of the existing best method PredictSNP1. When tested on the HumDiv and HumVar datasets, it achieves MCC of 0.9605 and 0.9507, and area under curve (AUC) of 0.9796 and 0.9748, which are 0.1747 and 0.2669, 0.0853 and 0.1335, respectively, higher than the existing best methods PolyPhen-2 and FATHMM (weighted). In addition, on blind test using a third-party dataset, FFMSRes-MutP performs as the second-best predictor (with MCC and AUC of 0.5215 and 0.7633, respectively), when compared with the other four predictors. Extensive benchmarking experiments demonstrate that FFMSRes-MutP achieves effective feature fusion and can be explored as a useful approach for predicting disease-associated nsSNPs. The webserver is freely available at http://csbio.njust.edu.cn/bioinf/ffmsresmutp/ for academic use.

MutTMPredictor: Robust and accurate cascade XGBoost classifier for prediction of mutations in transmembrane proteins

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Prediction of mutations in transmembrane proteins is of significance for diseases diagnosis.

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Building on the evolutionary information, proposed the Gaussian WAPSSM algorithm.

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Based on WAPSSM and sequence and structure-based features, proposed the cascade XGBoost algorithm.

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Webserver is freely at (http://csbio.njust.edu.cn/bioinf/ffmsresmutp/).

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Implement MutTMPredictor to predict mutations in transmembrane proteins.

Transmembrane proteins have critical biological functions and play a role in a multitude of cellular processes including cell signaling, transport of molecules and ions across membranes. Approximately 60% of transmembrane proteins are considered as drug targets. Missense mutations in such proteins can lead to many diverse diseases and disorders, such as neurodegenerative diseases and cystic fibrosis. However, there are limited studies on mutations in transmembrane proteins. In this work, we first design a new feature encoding method, termed weight attenuation position-specific scoring matrix (WAPSSM), which builds upon the protein evolutionary information. Then, we propose a new mutation prediction algorithm (cascade XGBoost) by leveraging the idea learned from consensus predictors and gcForest. Multi-level experiments illustrate the effectiveness of WAPSSM and cascade XGBoost algorithms. Finally, based on WAPSSM and other three types of features, in combination with the cascade XGBoost algorithm, we develop a new transmembrane protein mutation predictor, named MutTMPredictor. We benchmark the performance of MutTMPredictor against several existing predictors on seven datasets. On the 546 mutations dataset, MutTMPredictor achieves the accuracy (ACC) of 0.9661 and the Matthew’s Correlation Coefficient (MCC) of 0.8950. While on the 67,584 dataset, MutTMPredictor achieves an MCC of 0.7523 and area under curve (AUC) of 0.8746, which are 0.1625 and 0.0801 respectively higher than those of the existing best predictor (fathmm). Besides, MutTMPredictor also outperforms two specific predictors on the Pred-MutHTP datasets. The results suggest that MutTMPredictor can be used as an effective method for predicting and prioritizing missense mutations in transmembrane proteins. The MutTMPredictor webserver and datasets are freely accessible at http://csbio.njust.edu.cn/bioinf/muttmpredictor/ for academic use.

In silico study of missense variants of FANCA, FANCC and FANCG genes reveals high risk deleterious alleles predisposing to Fanconi anemia pathogenesis

Among the 22 Fanconi anemia (FA) reported genes, 90% of mutational spectra were found in three genes, namely FANCA (64%), FANCC (12%) and FANCG (8%). Therefore, this study aimed to identify the high-risk deleterious variants in three selected genes (FANCA, FANCC, and FANCG) through various computational approaches. The missense variant datasets retrieved from the UCSC genome browser were analyzed for their pathogenicity, stability, and phylogenetic conservancy. A total of 23 alterations, of which 16 in FANCA, 6 in FANCC and one variant in FANCG, were found to be highly deleterious. The native and mutant structures were generated, which demonstrated a profound impact on the respective proteins. Besides, their pathway analysis predicted many other pathways in addition to the Fanconi anemia pathway, homologous recombination, and mismatch repair pathways. Hence, this is the first comprehensive study that can be useful for understanding the genetic signatures in the development of FA.

Evolutionary history and pan-genome dynamics of strawberry (Fragaria spp.)

Strawberry (Fragaria spp.) has emerged as a model system for various fundamental and applied research in recent years. In total, the genomes of five different species have been sequenced over the past 10 y. Here, we report chromosome-scale reference genomes for five strawberry species, including three newly sequenced species' genomes, and genome resequencing data for 128 additional accessions to estimate the genetic diversity, structure, and demographic history of key Fragaria species. Our analyses obtained fully resolved and strongly supported phylogenies and divergence times for most diploid strawberry species. These analyses also uncovered a new diploid species (Fragaria emeiensis Jia J. Lei). Finally, we constructed a pan-genome for Fragaria and examined the evolutionary dynamics of gene families. Notably, we identified multiple independent single base mutations of the MYB10 gene associated with white pigmented fruit shared by different strawberry species. These reference genomes and datasets, combined with our phylogenetic estimates, should serve as a powerful comparative genomic platform and resource for future studies in strawberry.

Computational algorithmic and molecular dynamics study of functional and structural impacts of non-synonymous single nucleotide polymorphisms in human DHFR gene

Human dihydrofolate reductase (DHFR) is a conserved enzyme that is central to folate metabolism and is widely targeted in pathogenic diseases as well as cancers. Although studies have reported the fact that genetic mutations in DHFR leads to a rare autosomal recessive inborn error of folate metabolism and drug resistance, there is a lack of an extensive study on how the deleterious non-synonymous SNPs (nsSNPs) disrupt its phenotypic effects. In this study, we aim at discovering the structural and functional consequences of nsSNPs in DHFR by employing a combined computational approach consisting of ten recently developed in silico tools for identification of damaging nsSNPs and molecular dynamics (MD) simulation for getting deeper insights into the magnitudes of damaging effects. Our study revealed the presence of 12 most deleterious nsSNPs affecting the native phenotypic effects, with three (R71T, G118D, Y122D) identified in the co-factor and ligand binding active sites. MD simulations also suggested that these three SNPs particularly Y122D, alter the overall structural flexibility and dynamics of the native DHFR protein which can provide more understandings into the crucial roles of these mutants in influencing the loss of DHFR function.

Three chromosome-level duck genome assemblies provide insights into genomic variation during domestication

Domestic ducks are raised for meat, eggs and feather down, and almost all varieties are descended from the Mallard (Anas platyrhynchos). Here, we report chromosome-level high-quality genome assemblies for meat and laying duck breeds, and the Mallard. Our new genomic databases contain annotations for thousands of new protein-coding genes and recover a major percentage of the presumed "missing genes" in birds. We obtain the entire genomic sequences for the C-type lectin (CTL) family members that regulate eggshell biomineralization. Our population and comparative genomics analyses provide more than 36 million sequence variants between duck populations. Furthermore, a mutant cell line allows confirmation of the predicted anti-adipogenic function of NR2F2 in the duck, and uncovered mutations specific to Pekin duck that potentially affect adipose deposition. Our study provides insights into avian evolution and the genetics of oviparity, and will be a rich resource for the future genetic improvement of commercial traits in the duck.

Pathogenic genetic variants from highly connected cancer susceptibility genes confer the loss of structural stability

Genetic polymorphisms in DNA damage repair and tumor suppressor genes have been associated with increasing the risk of several types of cancer. Analyses of putative functional single nucleotide polymorphisms (SNP) in such genes can greatly improve human health by guiding choice of therapeutics. In this study, we selected nine genes responsible for various cancer types for gene enrichment analysis and found that BRCA1, ATM, and TP53 were more enriched in connectivity. Therefore, we used different computational algorithms to classify the nonsynonymous SNPs which are deleterious to the structure and/or function of these three proteins. The present study showed that the major pathogenic variants (V1687G and V1736G of BRCA1, I2865T and V2906A of ATM, V216G and L194H of TP53) might have a greater impact on the destabilization of the proteins. To stabilize the high-risk SNPs, we performed mutation site-specific molecular docking analysis and validated using molecular dynamics (MD) simulation and molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) studies. Additionally, SNPs of untranslated regions of these genes affecting miRNA binding were characterized. Hence, this study will assist in developing precision medicines for cancer types related to these polymorphisms.

A comprehensive in Silico analysis of the functional and structural impact of single nucleotide polymorphisms (SNPs) in the human IL-33 gene

Interleukin 33 (IL-33) is the latest member of the IL-1 cytokine family, which plays both pro - and anti-inflammatory functions. Numerous Single-nucleotide polymorphisms (SNPs) in the IL-33 gene have been recognized to be associated with a vast variety of inflammatory disorders. SNPs associated studies have become a crucial approach in uncovering the genetic background of human diseases. However, distinguishing the functional SNPs in a disease-related gene from a pool of both functional and neutral SNPs is a major challenge and needs multiple experiments of hundreds or thousands of SNPs in candidate genes. This study aimed to identify the possible deleterious SNPs in the IL-33 gene using bioinformatics predictive tools. The nonsynonymous SNPs (nsSNPs) were analyzed by SIFT, PolyPhen, PROVEAN, SNP&GO, MutPred, SNAP, PhD SNP, and I-Mutant tools. The Non-coding SNPs (ncSNPs) were also analyzed by SNPinfo and RegulomeDB tools. In conclusion, our in-silico analysis predicted 5 nsSNPs and 22 ncSNPs as potential candidates in the IL-33 gene for future genetic association studies.

Computational studies of anaplastic lymphoma kinase mutations reveal common mechanisms of oncogenic activation

High-risk tumors are genomically heterogeneous, harboring gene amplifications and mutations. The activation status of mutated proteins in cancer can profoundly impact disease progression, patient response, and drug sensitivity. Yet, outside of a few hotspot mutations, functional studies of clinically observed mutations are not commonly pursued. We report a combined experimental profiling and computational analysis of the effects of clinically observed and “test” mutations in the kinase domain of anaplastic lymphoma kinase (ALK), a known oncogenic driver in pediatric neuroblastoma. We find that the activation status of the mutated protein is a good indicator of the transforming ability in NIH 3T3 cells. We also report biophysical as well as data-driven models with predictive power to profile these mutant kinases in silico.

Kinases play important roles in diverse cellular processes, including signaling, differentiation, proliferation, and metabolism. They are frequently mutated in cancer and are the targets of a large number of specific inhibitors. Surveys of cancer genome atlases reveal that kinase domains, which consist of 300 amino acids, can harbor numerous (150 to 200) single-point mutations across different patients in the same disease. This preponderance of mutations—some activating, some silent—in a known target protein make clinical decisions for enrolling patients in drug trials challenging since the relevance of the target and its drug sensitivity often depend on the mutational status in a given patient. We show through computational studies using molecular dynamics (MD) as well as enhanced sampling simulations that the experimentally determined activation status of a mutated kinase can be predicted effectively by identifying a hydrogen bonding fingerprint in the activation loop and the αC-helix regions, despite the fact that mutations in cancer patients occur throughout the kinase domain. In our study, we find that the predictive power of MD is superior to a purely data-driven machine learning model involving biochemical features that we implemented, even though MD utilized far fewer features (in fact, just one) in an unsupervised setting. Moreover, the MD results provide key insights into convergent mechanisms of activation, primarily involving differential stabilization of a hydrogen bond network that engages residues of the activation loop and αC-helix in the active-like conformation (in >70% of the mutations studied, regardless of the location of the mutation).

Bioinformatics analysis of GNAQ, GNA11, BAP1, SF3B1,SRSF2, EIF1AX, PLCB4, and CYSLTR2 genes and their role in the pathogenesis of Uveal Melanoma

Uveal melanoma (UM) is the most common primary intraocular malignancy in adults, and its metastases are known to be fatal. It is critical to identify molecular markers to be used in potential prognostic evaluation for early diagnosis, treatment, and metastasis or to investigate all aspects of known genetic anomalies. Therefore, this study aimed to analyze the eight genes (GNAQ, GNA11, BAP1, SF3B1, SRSF2, EIF1AX, PLCB4, and CYSLTR2) that are associated with the most common genetic anomalies in UM from a molecular perspective. The genome sequences and expression profiles of 108 UM patients were obtained via bioinformatics tools that provide data from TCGA. The overall mutational load and the mutation patterns for eight genes, in particular, were thoroughly determined. Moreover, PolyPhen2 and SNAP² tools were used to estimate the oncogenic/pathogenic properties of identified mutations for UM. In addition to the mutation profile, the effects of the presence of a mutation on gene expression and survival were determined. Finally, STRING network analysis was performed to better understand the functional relationships of mutated proteins in cellular processes. There were 27 missense mutations, 16 frameshift mutations, six nonsense mutations, and three splice region mutations among the 52 mutations found in eight genes, and 26 of them had pathogenic properties. BAP1 m-RNA expression was significantly lower in tumors with the mutant genotype (p = .001). The impact of gene expression, which has poor prognostic importance, on survival is statistically significant for high-expressed BAP1 (p = .0015) and low-expressed CYSLTR2 (p = .0021). To assess the current state of this potentially devastating disease, a molecular perspective has been evaluated. Defining this molecular perspective can be useful in developing targeted drug therapies and personalized medicine.

The Algerian Chapter of SARS-CoV-2 Pandemic: An Evolutionary, Genetic, and Epidemiological Prospect

To explore the SARS-CoV-2 pandemic in Algeria, a dataset comprising ninety-five genomes originating from SARS-CoV-2 sampled from Algeria and other countries worldwide, from 24 December 2019, through 4 March 2021, was thoroughly examined. While performing a multi-component analysis regarding the Algerian outbreak, the toolkit of phylogenetic, phylogeographic, haplotype, and genomic analysis were effectively implemented. We estimated the Time to the Most Recent Common Ancestor (TMRCA) in reference to the Algerian pandemic and highlighted the multiple introductions of the disease and the missing data depicted in the transmission loop. In addition, we emphasized the significant role played by local and international travels in disease dissemination. Most importantly, we unveiled mutational patterns, the effect of unique mutations on corresponding proteins, and the relatedness regarding the Algerian sequences to other sequences worldwide. Our results revealed individual amino-acid replacements such as the deleterious replacement A23T in the orf3a gene in Algeria_EPI_ISL_418241. Additionally, a connection between Algeria_EPI_ISL_420037 and sequences originating from the USA was observed through a USA characteristic amino-acid replacement T1004I in the nsp3 gene, found in the aforementioned Algerian sequence. Similarly, successful tracing could be established, such as Algeria/G37318-8849/2020|EPI_ISL_766863, which was imported from Saudi Arabia during the pilgrimage. Lastly, we assessed the Algerian mitigation measures regarding disease containment using statistical analyses.

Identification of a novel calcium activated potassium channel from Leishmania donovani and in silico predictions of its antigenic features

Visceral Leishmaniasis is a major neglected tropical disease with increasing incidences of drug resistance. This has led to the search for a suitable drug target for chemotherapeutic intervention. Potassium channels are a family of membrane proteins which play a vital role in homeostasis and any perturbation in them alters cell survival which makes them an attractive target. To characterize a calcium-activated potassium channel from Leishmania donovani (LdK_Ca), a putative ion-channel like protein which showed sequence similarity with other Trypanosoma cruzi putative potassium channels was selected. It was cloned and expressed with a histidine tag. MALDI confirmed that it is a potassium channel. Homology model of LdK_Ca was generated by I-TASSER. It is a transmembrane protein localized in the plasma membrane as predicted by DeepLoc tool. In silico analyses of the protein showed that it is a small conductance calcium activated potassium channel. Point mutation in conserved signature domain 'TXGYGD' affects the protein function as predicted by heat map analysis. The LdK_Ca model predicted amino acids S207, T208 and M236 as ligand-binding sites. The sequence HSLRGRSARVIQLAWRLRKARKVGPHAPSLKQKVYTLVLSWLLT was the highest scoring B-cell epitope. The highest scoring T-cell epitope was RLYSVIVYL. This study may provide new insights into antigenicity features of leishmanial calcium-activated potassium channels.

Computational and Mass Spectrometry-Based Approach Identify Deleterious Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) in JMJD6

The jumonji domain-containing protein 6 (JMJD6) gene catalyzes the arginine demethylation and lysine hydroxylation of histone and a growing list of its known substrate molecules, including p53 and U2AF65, suggesting a possible role in mRNA splicing and transcription in cancer progression. Mass spectrometry-based technology offers the opportunity to detect SNP variants accurately and effectively. In our study, we conducted a combined computational and filtration workflow to predict the nonsynonymous single nucleotide polymorphisms (nsSNPs) present in JMJD6, followed by a liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis and validation. The computational approaches SIFT, PolyPhen-2, SNAP, I-Mutant 2.0, PhD-SNP, PANTHER, and SNPS&GO were integrated to screen out the predicted damaging/deleterious nsSNPs. Through the three-dimensional structure of JMJD6, H187R (rs1159480887) was selected as a candidate for validation. The validation experiments showed that the mutation of this nsSNP in JMJD6 obviously affected mRNA splicing or the transcription of downstream genes through the reduced lysyl-hydroxylase activity of its substrates, U2AF65 and p53, further indicating the accuracy of this prediction method. This research provides an effective computational workflow for researchers with an opportunity to select prominent deleterious nsSNPs and, thus, remains promising for examining the dysfunction of proteins.

Structural and functional analysis of disease-associated mutations in GOT1 gene: An in silico study

Disease-associated single nucleotide polymorphisms (SNPs) alter the natural functioning and the structure of proteins. Glutamic-oxaloacetic transaminase 1 (GOT1) is a gene associated with multiple cancers and neurodegenerative diseases which codes for aspartate aminotransferase. The present study involved a comprehensive in-silico analysis of the disease-associated SNPs of human GOT1. Four highly deleterious nsSNPs (L36R, Y159C, W162C and L345P) were identified through SNP screening using several sequence-based and structure-based tools. Conservation analysis and oncogenic analysis showed that most of the nsSNPs are at highly conserved residues, oncogenic in nature and cancer drivers. Molecular dynamics simulations (MDS) analysis was performed to understand the dynamic behaviour of native and mutant proteins. PTM analysis revealed that the nsSNP Y159C is at a PTM site and will mostly affect phosphorylation at that site. Based on the overall analyses carried out in this study, L36R is the most deleterious mutation amongst the aforementioned deleterious mutations of GOT1.

Improved genome assembly and pan-genome provide key insights into eggplant domestication and breeding

Eggplant (Solanum melongena L.) is an important horticultural crop and one of the most widely grown vegetables from the Solanaceae family. It was domesticated from a wild, prickly progenitor carrying small, round, non-anthocyanic fruits. We obtained a novel, highly contiguous genome assembly of the eggplant '67/3' reference line, by Hi-C retrofitting of a previously released short read- and optical mapping-based assembly. The sizes of the 12 chromosomes and the fraction of anchored genes in the improved assembly were comparable to those of a chromosome-level assembly. We resequenced 23 accessions of S. melongena representative of the worldwide phenotypic, geographic, and genetic diversity of the species, and one each from the closely related species Solanum insanum and Solanum incanum. The eggplant pan-genome contained approximately 51.5 additional megabases and 816 additional genes compared with the reference genome, while the pan-plastome showed little genetic variation. We identified 53 selective sweeps related to fruit color, prickliness, and fruit shape in the nuclear genome, highlighting selection leading to the emergence of present-day S. melongena cultivars from its wild ancestors. Candidate genes underlying the selective sweeps included a MYBL1 repressor and CHALCONE ISOMERASE (for fruit color), homologs of Arabidopsis GLABRA1 and GLABROUS INFLORESCENCE STEMS2 (for prickliness), and orthologs of tomato FW2.2, OVATE, LOCULE NUMBER/WUSCHEL, SUPPRESSOR OF OVATE, and CELL SIZE REGULATOR (for fruit size/shape), further suggesting that selection for the latter trait relied on a common set of orthologous genes in tomato and eggplant.

Novel rare variants in FGFR1 and clinical characteristics analysis in a series of congenital hypogonadotropic hypogonadism patients

OBJECTIVE

We aimed to analyse FGFR1 rare variants in a series of Chinese congenital hypogonadotropic hypogonadism (CHH) patients. In addition, we intended to understand the clinical characteristics and the response to treatment of CHH patients with FGFR1 rare variants.

PATIENTS AND METHODS

A total of 357 CHH patients were recruited at Peking Union Medical College Hospital. We used Sanger sequencing to analyse FGFR1 gene. In silico analysis was carried out to study the pathogenicity of novel missense variants. The clinical, endocrinological and therapeutic effects from patients carrying FGFR1 rare variants were analysed retrospectively.

RESULTS

Thimissense mutations.rty patients in this series were found to harbour 29 FGFR1 rare variants, with 8 recurrent and 21 novel variants. After comprehensive analysis, 18 out of 21 novel variants were classified as likely pathogenic (LP) ones. These variants are widely spread throughout the FGFR1 gene and almost all FGFR1 functional domains, which exhibited no hot spot. Cryptorchidism, cleft palate and dental abnormality incidence in this CHH series that possessed FGFR1 LP variants were approximately 38.5%, 7.6% and 3.8%, respectively. Among patients who accepted the fertility-promoting treatment, 8 out of 10 patients succeeded in spermatogenesis.

CONCLUSIONS

Eighteen novel LP variants were found to expand the spectrum of FGFR1 rare variants. In CHH patients possessing FGFR1 variants, we found that the rate of spermatogenesis was high following fertility-promoting therapy and the existence of cryptorchidism may represent the underlying factors which affect spermatogenesis.

Mitochondrial disease patients with novel ND4 12058A > C and ND1 m.3911A > G variations: implications for a role in the phenotype following a bioinformatic investigation

Mitochondrial diseases include a wide group of clinically heterogeneous disorders caused by a dysfunction of the mitochondrial respiratory chain and can be related to mutations in nuclear or mitochondrial DNA genes. In the present report, we performed a whole mitochondrial genome screening in two patients with clinical features of mitochondrial diseases. Mutational analysis revealed the presence of two undescribed heteroplasmic mitochondrial variations, the m.3911A > G (E202G) variant in the MT-ND1 gene found in two patients (P1 and P2) and the m.12058A > C (E433D) pathogenic variant in the MT-ND4 gene present only in patient P2 who had a more severe phenotype. These two substitutions were predicted to be damaging by several bioinformatics tools and lead to amino acid changes in two conserved residues localized in two important functional domains of the mitochondrial subunits of complex I. Furthermore, the 3D modeling suggested that the two amino acid changes could therefore alter the structure of the two subunits and may decrease the stability and the function of complex I. The two described pathogenic variants found in patient P2 could act synergically and alter the complex I function by affecting the proton pumping processes and the energy production and then could explain the severe phenotype compared to patient P1 presenting only the E202G substitution in ND1.

Introgressing the Aegilops tauschii genome into wheat as a basis for cereal improvement

Increasing crop production is necessary to feed the world's expanding population, and crop breeders often utilize genetic variations to improve crop yield and quality. However, the narrow diversity of the wheat D genome seriously restricts its selective breeding. A practical solution is to exploit the genomic variations of Aegilops tauschii via introgression. Here, we established a rapid introgression platform for transferring the overall genetic variations of A. tauschii to elite wheats, thereby enriching the wheat germplasm pool. To accelerate the process, we assembled four new reference genomes, resequenced 278 accessions of A. tauschii and constructed the variation landscape of this wheat progenitor species. Genome comparisons highlighted diverse functional genes or novel haplotypes with potential applications in wheat improvement. We constructed the core germplasm of A. tauschii, including 85 accessions covering more than 99% of the species' overall genetic variations. This was crossed with elite wheat cultivars to generate an A. tauschii-wheat synthetic octoploid wheat (A-WSOW) pool. Laboratory and field analysis with two examples of the introgression lines confirmed its great potential for wheat breeding. Our high-quality reference genomes, genomic variation landscape of A. tauschii and the A-WSOW pool provide valuable resources to facilitate gene discovery and breeding in wheat.

The chromosome-level Stevia genome provides insights into steviol glycoside biosynthesis

Stevia (Stevia rebaudiana Bertoni) is well known for its very sweet steviol glycosides (SGs) consisting of a common tetracyclic diterpenoid steviol backbone and a variable glycone. Steviol glycosides are 150-300 times sweeter than sucrose and are used as natural zero-calorie sweeteners. However, the most promising compounds are biosynthesized in small amounts. Based on Illumina, PacBio, and Hi-C sequencing, we constructed a chromosome-level assembly of Stevia covering 1416 Mb with a contig N50 value of 616.85 kb and a scaffold N50 value of 106.55 Mb. More than four-fifths of the Stevia genome consisted of repetitive elements. We annotated 44,143 high-confidence protein-coding genes in the high-quality genome. Genome evolution analysis suggested that Stevia and sunflower diverged ~29.4 million years ago (Mya), shortly after the whole-genome duplication (WGD) event (WGD-2, ~32.1 Mya) that occurred in their common ancestor. Comparative genomic analysis revealed that the expanded genes in Stevia were mainly enriched for biosynthesis of specialized metabolites, especially biosynthesis of terpenoid backbones, and for further oxidation and glycosylation of these compounds. We further identified all candidate genes involved in SG biosynthesis. Collectively, our current findings on the Stevia reference genome will be very helpful for dissecting the evolutionary history of Stevia and for discovering novel genes contributing to SG biosynthesis and other important agronomic traits in future breeding programs.

Analysis and Interpretation of the Impact of Missense Variants in Cancer

Large scale genome sequencing allowed the identification of a massive number of genetic variations, whose impact on human health is still unknown. In this review we analyze, by an in silico-based strategy, the impact of missense variants on cancer-related genes, whose effect on protein stability and function was experimentally determined. We collected a set of 164 variants from 11 proteins to analyze the impact of missense mutations at structural and functional levels, and to assess the performance of state-of-the-art methods (FoldX and Meta-SNP) for predicting protein stability change and pathogenicity. The result of our analysis shows that a combination of experimental data on protein stability and in silico pathogenicity predictions allowed the identification of a subset of variants with a high probability of having a deleterious phenotypic effect, as confirmed by the significant enrichment of the subset in variants annotated in the COSMIC database as putative cancer-driving variants. Our analysis suggests that the integration of experimental and computational approaches may contribute to evaluate the risk for complex disorders and develop more effective treatment strategies.

Global Dynamics Renders Protein Sites with High Functional Response

Deep mutational scanning enables examination of the effects of many mutations at each amino acid position in a query protein, readily disclosing positions that are particularly sensitive. Mutations in these positions alter protein function the most. Here, on the premise that dynamics underlie function, we explore to what extent the measured sensitivity to mutations could be linked to-perhaps be explained by-the structural dynamics of the protein. We employ a minimalist perturbation-response approach based on the Gaussian Network Model (GNM) on a data set of seven proteins with deep mutational scanning data. The analysis shows that the mutation-sensitive positions are often of capacity to modulate the global dynamics and to intermediate allosteric interactions in the structure. With that, upon strain perturbation, these positions decrease residue fluctuations the most, affecting function via entropy changes. This is particularly relevant for positions that are distant from binding sites or other functional regions of the protein and are sensitive to mutations, nevertheless. Our results indicate that mutations in these positions allosterically manipulate protein function.

Rare genetic variants: making the connection with breast cancer susceptibility

The practice of clinical genetics in the context of breast cancer predisposition has reached another critical point in its evolution. For the past two decades, genetic testing offered to women attending clinics has been limited to BRCA1 and BRCA2 unless other syndromic indicators have been evident (e.g. PTEN and TP53 for Cowden and Li-Fraumeni syndrome, respectively). Women (and their families) who are concerned about their personal and/or family history of breast and ovarian cancer have enthusiastically engaged with clinical genetics services, anticipating a genetic cause for their cancer predisposition will be identified and to receive clinical guidance for their risk management and treatment options. Genetic testing laboratories have demonstrated similar enthusiasm for transitioning from single gene to gene panel testing that now provide opportunities for the large number of women found not to carry mutations in BRCA1 and BRCA2, enabling them to undergo additional genetic testing. However, these panel tests have limited clinical utility until more is understood about the cancer risks (if any) associated with the genetic variation observed in the genes included on these panels. New data is urgently needed to improve the interpretation of the genetic variation data that is already reported from these panels and to inform the selection of genes included in gene panel tests in the future. To address this issue, large internationally coordinated research studies are required to provide the evidence-base from which clinical genetics for breast cancer susceptibility can be practiced in the era of gene panel testing and oncogenetic practice.

Two significant steps associated with this process include i) validating the genes on these panels (and those likely to be added in the future) as bona fide1 breast cancer predisposition genes and ii) interpreting the variation, on a variant-by-variant basis in terms of their likely “pathogenicity”—a process commonly referred to as “variant classification” that will enable this new genetic information to be used at an individual level in clinical genetics services. Neither of these fundamental steps have been achieved for the majority of genes included on the panels.

We are thus at a critical point for translational research in breast cancer clinical genetics—how can rare genetic variants be interpreted such that they can be used in clinical genetics services and oncogenetic practice to identify and to inform the management of families that carry these variants?

Whole-genome assembly of Corylus avellana cv'Tonda Gentile delle Langhe' using linked-reads (10X Genomics)

The European hazelnut (Corylus avellana L.; 2n = 2x = 22) is a worldwide economically important tree nut that is cross-pollinated due to sporophytic incompatibility. Therefore, any individual plant is highly heterozygous. Cultivars are clonally propagated using mound layering, rooted suckers, and micropropagation. In recent years, the interest in this crop has increased, due to a growing demand related to the recognized health benefits of nut consumption. C. avellana cv “Tonda Gentile delle Langhe” (“TGdL”) is well-known for its high kernel quality, and the premium price paid for this cultivar is an economic benefit for producers in northern Italy. Assembly of a high-quality genome is a difficult task in many plant species because of the high level of heterozygosity. We assembled a chromosome-level genome sequence of “TGdL” with a two-step approach. First, 10X Genomics Chromium Technology was used to create a high-quality sequence, which was then assembled into scaffolds with cv “Tombul” genome as the reference. Eleven pseudomolecules were obtained, corresponding to 11 chromosomes. A total of 11,046 scaffolds remained unplaced, representing 11% of the genome (46,504,161 bp). Gene prediction, performed with Maker-P software, identified 27,791 genes (AED ≤0.4 and 92% of BUSCO completeness), whose function was analyzed with BlastP and InterProScan software. To characterize “TGdL” specific genetic mechanisms, Orthofinder was used to detect orthologs between hazelnut and closely related species. The “TGdL” genome sequence is expected to be a powerful tool to understand hazelnut genetics and allow detection of markers/genes for important traits to be used in targeted breeding programs.

Loss of function mutations in GEMIN5 cause a neurodevelopmental disorder

GEMIN5, an RNA-binding protein is essential for assembly of the survival motor neuron (SMN) protein complex and facilitates the formation of small nuclear ribonucleoproteins (snRNPs), the building blocks of spliceosomes. Here, we have identified 30 affected individuals from 22 unrelated families presenting with developmental delay, hypotonia, and cerebellar ataxia harboring biallelic variants in the GEMIN5 gene. Mutations in GEMIN5 perturb the subcellular distribution, stability, and expression of GEMIN5 protein and its interacting partners in patient iPSC-derived neurons, suggesting a potential loss-of-function mechanism. GEMIN5 mutations result in disruption of snRNP complex assembly formation in patient iPSC neurons. Furthermore, knock down of rigor mortis, the fly homolog of human GEMIN5, leads to developmental defects, motor dysfunction, and a reduced lifespan. Interestingly, we observed that GEMIN5 variants disrupt a distinct set of transcripts and pathways as compared to SMA patient neurons, suggesting different molecular pathomechanisms. These findings collectively provide evidence that pathogenic variants in GEMIN5 perturb physiological functions and result in a neurodevelopmental delay and ataxia syndrome.

Relationship between P2XR4 Gene Variants and the Risk of Schizophrenia in South-East of Iran: A Preliminary Case-Control Study and in Silico Analysis

Background:

Schizophrenia (SZN) is a heterogeneous disorder. Recently, the role of purinergic receptor’s signaling in mental disorders has implicated. There is no evidence regarding the association of P2XR4 single nucleotide polymorphisms (SNPs) and the risk of behavioral disorders. Therefore, this preliminary study, we determined the association of rs1169727A/G and rs25644A/G variants located in P2XR4 gene with the risk of SZN.

Methods:

This case-control study was performed on 150 SZN patient referring to Baharan Hospital, Zahedan (Eastern of Iran) in 2018. Genotyping was done by tetra-amplification refractory mutation system polymerase chain reaction (Tetra ARMS-PCR). Different databases were used to determine the effects of the SNPs on the secondary structure of P2XR4 pre-mRNA and protein as well as binding of transcriptional regulators.

Results:

The G allele of rs1169727 significantly increased the risk of SZN (OR=1.41, 95%CI=1.02–1.93, P=0.039), but there was no significant association was found between the other SNP and SZN. Moreover, GG model of rs1169727 (OR=2.46, 95%CI= 1.32–4.62, P=0.004) and rs25644 (OR=3.45, 95%CI= 1.12–5.10, P=0.013) increased the risk of SZN. The substitution of A and G alleles of rs1169727 significantly altered the secondary structure of pre-mRNA (P=0.1). In silico analysis revealed that rs25644A/G could act as an intronic cryptic donor site. Screening for flanking sequence of rs1169727A/G and rs25644A/G predicted a novel enhancer and silencer for both SNPs.

Conclusion:

rs1169727A/G and rs25644A/G are linked to SZN susceptibility in a sample of the Iranian population. In-silico analysis indicated that rs25644 have substantial roles in determining the pre-mRNA and protein structure of P2XR4 gene.

In silico explanation for the causalities of deleterious RNF213 SNPs in Moyamoya disease and insulin resistance

Moyamoya disease (MMD), a cerebrovascular disorder caused by the RNF213 gene, is a cerebrovascular, neurological disorder leading to ischemic strokes. Our previous work suggested that RNF213 might be involved in the pro-inflammatory TNFα-mediated insulin-resistance pathway in adipocytes. Insulin resistance can lead to cerebrovascular diseases and ischemic strokes. Though p. R4810 K has been reported as the founder mutation for Asian population with this disease, there are several mutations continuously reported in clinical diagnosis. We are interested to know whether these mutations can modulate insulin resistance. Also, we are intended to understand the causalities of RNF213 and its associated mutations in MMD. For this, we have adopted a computational approach to characterize RNF213 and its naturally occurring SNPs. Clinically reported SNPs and the predicted SNPs were analyzed for their pathogenicity and effect on the biological function of the protein. To increase accuracy, this was performed through three different analysis software (PROVEAN, SIFT, and SNAP2). The mutations that were found to be deleterious in all the three platforms were further analyzed for their effect on the thermal stability of the protein through I-mutant and iStable. It was found that R4810 K and other mutations decreased the thermodynamic stability of the protein. Loss of function of RNF213 was suggested in some reports. Contrary to this, some studies reported a gain of function state due to the R4810K mutation. To understand this we have measured the ligand-binding ability of this mutated protein through COFACTOR and COACH. An increase in ligand binding is always related to the functional stability of a protein. We have observed that the R4810K mutation might increase the iron-binding efficiency of the amino acid residues. This increase in binding was further validated by analyzing the binding efficiencies by docking. Since RNF213 was previously reported as a target for Protein Tyrosine Phosphatase 1B (PTP1B), we have also analyzed whether PTP1B-binding positions are susceptible to mutations. We have re-analyzed our earlier report on the differential expression pattern of RNF213 in cancer and obese samples. We have provided a detailed analysis of the most deleterious SNPs related to RNF213. Also, we provide a prediction for the loss of function and gain of function attributes of RNF213 and its predicted causalities in MMD and insulin resistance.

Computational modeling and bioinformatic analyses of functional mutations in drug target genes in Mycobacterium tuberculosis

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MycoTRAP-DB, a database of mutations and their impact on normal functionality of protein in M.tb genes.

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Several secondary mutations were identified with significant impact on protein structure and function.

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Comprehensive information gives insight for screening of suspected hotspots in advance to combat drug resistant TB.

Tuberculosis (TB) continues to be the leading cause of deaths due to its persistent drug resistance and the consequent ineffectiveness of anti-TB treatment. Recent years witnessed huge amount of sequencing data, revealing mutations responsible for drug resistance. However, the lack of an up-to-date repository remains a barrier towards utilization of these data and identifying major mutations-associated with resistance. Amongst all mutations, non-synonymous mutations alter the amino acid sequence of a protein and have a much greater effect on pathogenicity. Hence, this type of gene mutation is of prime interest of the present study. The purpose of this study is to develop an updated database comprising almost all reported substitutions within the Mycobacterium tuberculosis (M.tb) drug target genes rpoB, inhA, katG, pncA, gyrA and gyrB. Various bioinformatics prediction tools were used to assess the structural and biophysical impacts of the resistance causing non-synonymous single nucleotide polymorphisms (nsSNPs) at the molecular level. This was followed by evaluating the impact of these mutations on binding affinity of the drugs to target proteins. We have developed a comprehensive online resource named MycoTRAP-DB (Mycobacterium tuberculosis Resistance Associated Polymorphisms Database) that connects mutations in genes with their structural, functional and pathogenic implications on protein. This database is accessible at http://139.59.12.92. This integrated platform would enable comprehensive analysis and prioritization of SNPs for the development of improved diagnostics and antimycobacterial medications. Moreover, our study puts forward secondary mutations that can be important for prognostic assessments of drug-resistance mechanism and actionable anti-TB drugs.

Structure analysis of deleterious nsSNPs in human PALB2 protein for functional inference

Partner and Localizer of BRCA2 or PALB2 is a typical tumor suppressor protein, that responds to DNA double stranded breaks through homologous recombination repair. Heterozygous mutations in PALB2 are known to contribute to the susceptibility of breast and ovarian cancer. However, there is no comprehensive study characterizing the structural and functional impacts of SNPs located in the PALB2 gene. Therefore, it is of interest to document a comprehensive analysis of coding and non-coding SNPs located at the PALB2 loci using in silico tools. The data for 1455 non-synonymous SNPs (nsSNPs) located in the PALB2 loci were retrieved from the dbSNP database. Comprehensive characterization of the SNPs using a combination of in silico tools such as SIFT, PROVEAN, PolyPhen, PANTHER, PhD-SNP, Pmut, MutPred 2.0 and SNAP-2, identified 28 functionally important SNPs. Among these, 16 nsSNPs were further selected for structural analysis using conservation profile and protein stability. The most deleterious nsSNPs were documented within the WD40 domain of PALB2. A general outline of the structural consequences of each variant was developed using the HOPE project data. These 16 mutant structures were further modelled using SWISS Model and three most damaging mutant models (rs78179744, rs180177123 and rs45525135) were identified. The non-coding SNPs in the 3' UTR region of the PALB2 gene were analyzed for altered miRNA target sites. The comprehensive characterization of the coding and non-coding SNPs in the PALB2 locus has provided a list of damaging SNPs with potential disease association. Further validation through genetic association study will reveal their clinical significance.

Low Diversity of Human Variation Despite Mostly Mild Functional Impact of De Novo Variants

Non-synonymous Single Nucleotide Variants (nsSNVs), resulting in single amino acid variants (SAVs), are important drivers of evolutionary adaptation across the tree of life. Humans carry on average over 10,000 SAVs per individual genome, many of which likely have little to no impact on the function of the protein they affect. Experimental evidence for protein function changes as a result of SAVs remain sparse – a situation that can be somewhat alleviated by predicting their impact using computational methods. Here, we used SNAP to examine both observed and in silico generated human variation in a set of 1,265 proteins that are consistently found across a number of diverse species. The number of SAVs that are predicted to have any functional effect on these proteins is smaller than expected, suggesting sequence/function optimization over evolutionary timescales. Additionally, we find that only a few of the yet-unobserved SAVs could drastically change the function of these proteins, while nearly a quarter would have only a mild functional effect. We observed that variants common in the human population localized to less conserved protein positions and carried mild to moderate functional effects more frequently than rare variants. As expected, rare variants carried severe effects more frequently than common variants. In line with current assumptions, we demonstrated that the change of the human reference sequence amino acid to the reference of another species (a cross-species variant) is unlikely to significantly impact protein function. However, we also observed that many cross-species variants may be weakly non-neutral for the purposes of quick adaptation to environmental changes, but may not be identified as such by current state-of-the-art methodology.

PDX1-MODY: A rare missense mutation as a cause of monogenic diabetes

Maturity-Onset Diabetes of the Young type 4 is a rare form of diabetes mellitus, caused by mutations in the PDX1 gene. However, only a few mutations in this gene have been associated as a cause of monogenic diabetes up to date. It makes difficult to create a clinical manifestation profile of this disease and, consequently, to improve the therapeutic management for these patients. Here we report a normal weight woman, diagnosed with diabetes mellitus at 27 years old, during her first pregnancy. At the time of the recruitment, she was 40 years old and had a body mass index of 23.9 kg/m², glycated hemoglobin level of 9.6%, and fasting plasma glucose (FPG) of 254 mg/dL. She presented no diabetic complications and she was being treated with insulin. She reported a family history of diabetes mellitus characteristic of an autosomal dominant mode of inheritance. Molecular analysis of the PDX1 gene revealed the missense variant c.532G > A (p.(Glu178Lys)) segregating from the patient to her son, reported as diabetic. It was absent in her healthy daughter. The c.532G > A seems to be a rare variant, absent in human variants databases, and among 86 normoglycemic controls. Eight in silico algorithms classified this variant as probably pathogenic. Additionally, analysis of the evolutionary conservation showed the glutamic acid in the position 178 of PDX-1 protein as conserved among several species. Our findings reinforce the importance of screening rare MODY genes among families with suspicion of monogenic diabetes to help better understand the clinical manifestations of this disease.

Chromosome-level assembly of the mangrove plant Aegiceras corniculatum genome generated through Illumina, PacBio and Hi-C sequencing technologies

Aegiceras corniculatum is a major mangrove plant species adapted to waterlogging and saline conditions, grows in the coastal intertidal zone of tropical and subtropical regions. Here, we present a chromosome-level genome assembly of A. corniculatum by incorporating PacBio long-read sequencing and Hi-C technology. The results showed that the PacBio draft genome size is 906.63 Mb. Hi-C scaffolding anchored 885.06 Mb contigs (97.62% of draft assembly) onto 24 pseudochromosomes. The contig N50 and scaffold N50 were 7.1 Mb and 37.74 Mb, respectively. Out of 40,727 protein-coding genes predicted in the study, 89% have functional annotations in public databases. We also showed that of the 603.93 Mb repetitive sequences predicted in the assembled genome, long terminal repeat retrotransposons constitute 41.52%. The genome evolution analysis showed that the A. corniculatum genome experienced two whole-genome duplication events and shared the ancient γ whole-genome triplication event. A comparative genomic analysis revealed an incidence of expansion in 1,488 gene families associated with essential metabolism and biosynthetic pathways, including photosynthesis, oxidative phosphorylation, phenylalanine, glyoxylate, dicarboxylate metabolism, and DNA replication, which probably constitute adaptation traits that allow the A. corniculatum to survive in the intertidal zone. Also, the systematic characterization of genes associated with flavonoid biosynthesis pathway and the AcNHX gene family conducted in this study will provide insight into the adaptation mechanism of A. corniculatum to intertidal environments. The high-quality genome reported here can provide historical insights into genomic transformations that support the survival of A. corniculatum under harsh intertidal habitats.

Insights into triterpene synthesis and unsaturated fatty-acid accumulation provided by chromosomal-level genome analysis of Akebia trifoliata subsp. australis

Akebia trifoliata subsp. australis is a well-known medicinal and potential woody oil plant in China. The limited genetic information available for A. trifoliata subsp. australis has hindered its exploitation. Here, a high-quality chromosome-level genome sequence of A. trifoliata subsp. australis is reported. The de novo genome assembly of 682.14 Mb was generated with a scaffold N50 of 43.11 Mb. The genome includes 25,598 protein-coding genes, and 71.18% (485.55 Mb) of the assembled sequences were identified as repetitive sequences. An ongoing massive burst of long terminal repeat (LTR) insertions, which occurred ~1.0 million years ago, has contributed a large proportion of LTRs in the genome of A. trifoliata subsp. australis. Phylogenetic analysis shows that A. trifoliata subsp. australis is closely related to Aquilegia coerulea and forms a clade with Papaver somniferum and Nelumbo nucifera, which supports the well-established hypothesis of a close relationship between basal eudicot species. The expansion of UDP-glucoronosyl and UDP-glucosyl transferase gene families and β-amyrin synthase-like genes and the exclusive contraction of terpene synthase gene families may be responsible for the abundant oleanane-type triterpenoids in A. trifoliata subsp. australis. Furthermore, the acyl-ACP desaturase gene family, including 12 stearoyl-acyl-carrier protein desaturase (SAD) genes, has expanded exclusively. A combined transcriptome and fatty-acid analysis of seeds at five developmental stages revealed that homologs of SADs, acyl-lipid desaturase omega fatty acid desaturases (FADs), and oleosins were highly expressed, consistent with the rapid increase in the content of fatty acids, especially unsaturated fatty acids. The genomic sequences of A. trifoliata subsp. australis will be a valuable resource for comparative genomic analyses and molecular breeding.

Draft genome assembly of the biofuel grass crop Miscanthus sacchariflorus

Miscanthus sacchariflorus (Maxim.) Hack. is a highly productive C4 perennial rhizomatous biofuel grass crop. M. sacchariflorus is among the most widely distributed species in the genus, particularly at cold northern latitudes, and is one of the progenitor species of the commercial M. × giganteus genotypes. We generated a 2.54 Gb whole-genome assembly of the diploid M. sacchariflorus cv. "Robustus 297" genotype, which represented ~59% of the expected total genome size. We later anchored this assembly using the chromosomes from the M. sinensis genome to generate a second assembly with improved contiguity. We annotated 86,767 and 69,049 protein-coding genes in the unanchored and anchored assemblies, respectively. We estimated our assemblies included ~85% of the M. sacchariflorus genes based on homology and core markers. The utility of the new reference for genomic studies was evidenced by a 99% alignment rate of the RNA-seq reads from the same genotype.  The raw data, unanchored and anchored assemblies, and respective gene annotations are publicly available.

Oncogenic potential of ATAD2 in stomach cancer and insights into the protein-protein interactions at its AAA + ATPase domain and bromodomain

ATAD2 has recently been shown to promote stomach cancer. However, nothing is known about the functional network of ATAD2 in stomach carcinogenesis. This study illustrates the oncogenic potential of ATAD2 and the participation of its ATPase and bromodomain in stomach malignancy. Expression of ATAD2 in stomach cancer is analyzed by in silico and in vitro techniques including western blot and immunofluorescence microscopy of stomach cancer cells (SCCs) and tissues. The oncogenic potential of ATAD2 is examined thoroughly using genetic alterations, driver gene prediction, survival analysis, identification of interacting partners, and analysis of canonical pathways. To understand the protein-protein interactions (PPI) at residue level, molecular docking and molecular dynamics simulations (1200 ns) are performed. Enhanced expression of ATAD2 is observed in H. pylori-infected SCCs, patient biopsy tissues, and all stages and grades of stomach cancer. High expression of ATAD2 is found to be negatively correlated with the survival of stomach cancer patients. ATAD2 is a cancer driver gene with 37 mutational sites and a predictable factor for stomach cancer prognosis with high accuracy. The top canonical pathways of ATAD2 indicate its participation in stomach malignancy. The ATAD2-PPI in stomach cancer identify top-ranked partners; ESR1, SUMO2, SPTN2, and MYC show preference for the bromodomain whereas NCOA3 and HDA11 have preference for the ATPase domain of ATAD2. The oncogenic characterization of ATAD2 provides strong evidence to consider ATAD2 as a stomach cancer biomarker. These studies offer an insight for the first time into the ATAD2-PPI interface presenting a novel target for cancer therapeutics. Communicated by Ramaswamy H. Sarma.

The Impact of Mutations in Wolframin on Psychiatric Disorders

Wolfram Syndrome is a rare autosomal recessive disease characterized by early-onset diabetes mellitus, neurodegeneration, and psychological disorders. Mutations in the gene WFS1, coding for the protein wolframin, cause Wolfram Syndrome and are associated with bipolar disorder and schizophrenia. This report aims to connect WFS1 mutations to their impact on protein expression and structure, which ultimately translates to altered cell function and behavioral alterations of an individual. Methods: Published data were used to compile WFS1 mutations associated with psychiatric symptoms, both in homozygous patients and heterozygous carriers of WFS1 mutations. These mutations were evaluated in silico using SNAP2, PolyPhen-2, and PROVEAN to predict the effects of sequence variants. Statistical analysis was performed to assess the correlation between the locations of the mutations and the damage prediction scores. Results: Several mutations, clustering in the center and C-terminus of the WFS1 polypeptide, such as A559T and R558C, are found in individuals with psychiatric diseases and appear particularly impactful on protein structure. Our analysis showed that mutations in all regions of wolframin were present in patients with schizophrenia whereas only cytoplasmic and ER luminal mutations were reported in patients with manic episodes and bipolar disorders. According to Poly-Phen-2 predictions, 82.4% of the ER lumen mutations and 85.7% of the membrane mutations are damaging. Conclusion: We propose mood disorders in Wolfram Syndrome and heterozygous carriers of WFS1 mutations are the consequence of specific mutations in WFS1 that alter the structure of wolframin, resulting in intracellular calcium dysregulations and impaired cell signaling, Understanding the effect of WFS1 mutations on bipolar disorder and schizoprenia is integral to designing clinically targeted treatments for both diseases, which need more specialized treatments.

High-Quality Genome of the Medicinal Plant Strobilanthes cusia Provides Insights Into the Biosynthesis of Indole Alkaloids

Strobilanthes cusia (Nees) Kuntze is an important plant used to process the traditional Chinese herbal medicines "Qingdai" and "Nanbanlangen". The key active ingredients are indole alkaloids (IAs) that exert antibacterial, antiviral, and antitumor pharmacological activities and serve as natural dyes. We assembled the S. cusia genome at the chromosome level through combined PacBio circular consensus sequencing (CCS) and Hi-C sequencing data. Hi-C data revealed a draft genome size of 913.74 Mb, with 904.18 Mb contigs anchored into 16 pseudo-chromosomes. Contig N50 and scaffold N50 were 35.59 and 68.44 Mb, respectively. Of the 32,974 predicted protein-coding genes, 96.52% were functionally annotated in public databases. We predicted 675.66 Mb repetitive sequences, 47.08% of sequences were long terminal repeat (LTR) retrotransposons. Moreover, 983 Strobilanthes-specific genes (SSGs) were identified for the first time, accounting for ~2.98% of all protein-coding genes. Further, 245 putative centromeric and 29 putative telomeric fragments were identified. The transcriptome analysis identified 2,975 differentially expressed genes (DEGs) enriched in phenylpropanoid, flavonoid, and triterpenoid biosynthesis. This systematic characterization of key enzyme-coding genes associated with the IA pathway and basic helix-loop-helix (bHLH) transcription factor family formed a network from the shikimate pathway to the indole alkaloid synthesis pathway in S. cusia. The high-quality S. cusia genome presented herein is an essential resource for the traditional Chinese medicine genomics studies and understanding the genetic underpinning of IA biosynthesis.

TargetMM: Accurate Missense Mutation Prediction by Utilizing Local and Global Sequence Information with Classifier Ensemble

Aim and Objective:

Missense mutation (MM) may lead to various human diseases by disabling proteins. Accurate prediction of MM is important and challenging for both protein function annotation and drug design. Although several computational methods yielded acceptable success rates, there is still room for further enhancing the prediction performance of MM.

Materials and Methods:

In the present study, we designed a new feature extracting method, which considers the impact degree of residues in the microenvironment range to the mutation site. Stringent cross-validation and independent test on benchmark datasets were performed to evaluate the efficacy of the proposed feature extracting method. Furthermore, three heterogeneous prediction models were trained and then ensembled for the final prediction. By combining the feature representation method and classifier ensemble technique, we reported a novel MM predictor called TargetMM for identifying the pathogenic mutations from the neutral ones.

Results:

Comparison outcomes based on statistical evaluation demonstrate that TargetMM outperforms the prior advanced methods on the independent test data. The source codes and benchmark datasets of TargetMM are freely available at https://github.com/sera616/TargetMM.git for academic use.