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Dissecting the genetic basis underlying drought tolerance at different development stages in soybean.

INTRODUCTION: Soybean is an indispensable crop supplying protein and oil for humans and animals, and playing an essential role in global food security. Drought represses soybean seed germination, reducing biomass accumulation and even inhibiting yield. METHODS: In order to dissect the genetic components underlying soybean drought tolerance during different development stage, a natural population containing 140 accessions was employed to evaluate seven drought tolerance-related traits under water-welled and drought stress conditions. Subsequently, genome-wide association study (GWAS) was conducted based on 150K single nucleotide polymorphism (SNP) markers of "Zhongdouxin-1". And the drought tolerance coefficient of seven different traits were analyzed with seven GWAS models. RESULTS: A total of 1807 significant SNPs were detected across 20 chromosome, including 569 SNPs for germination stage, and 1242 SNPs for seedling stage. Of 569 SNPs identified in germination stage, 354 SNPs on chromosomes 2, 7, 13, 14, and 17 accounting for 62.21%. Among 1242 SNPs found in seedling stage, 869 SNPs on chromosomes 11, 14, 15, 17 and 18 accounting for 69.97%. Moreover, among 1807 significant SNPs, 163 SNPs exhibited pleiotropic effects, of which 23 were located in exon, 21 in intron, 12 in 5'UTR or 3'UTR and 11 in upstream or downstream. Furthermore, 249 stable SNPs were detected by more than four GWAS models. According to these stable SNPs, RNA expression levels and gene annotations, four causal genes (Glyma.02G080200, Glyma.11G056200, Glyma.12G188900, and Glyma.18G110200) conferring soybean drought tolerance were detected, which participated in ethylene stimulus response, water deprivation response, and proteolysis. DISCUSSION: Collectively, 249 stable SNPs, 163 pleiotropic SNPs and four candidate genes identified in present study provided promising molecular resources and reliable foundation for drought resistance improvement and marker-assisted selective breeding in soybean.

GWAS

Bayesian reconstruction and differential testing of excised introns.

MOTIVATION: Characterizing the differential excision of introns is critical for understanding the functional complexity of a cell or tissue, from normal developmental processes to disease pathogenesis. Most transcript reconstruction methods infer full-length transcripts from high-throughput sequencing data. However, this is a challenging task due to incomplete annotations and the heterogeneous expression of transcripts across cell-types, tissues, and experimental conditions. Several recent methods circumvent these difficulties by considering local splicing events, but these methods lose transcript-level splicing information and may conflate similar, but distinct transcripts. RESULTS: In this work, we formalize a new transcript reconstruction problem that interpolates between the full-length and local splicing perspectives by considering sequences of exon-exon junctions (SEEJs) that co-occur in transcripts. We then present a hierarchical Bayesian admixture model and posterior inference algorithms for computing SEEJs (BSEEJ), and a generalized linear model for characterizing differential SEEJ usage based on model parameter estimates. We show that BSEEJ achieves high F1 score for reconstruction tasks and improved accuracy and sensitivity in differential splicing when compared with six transcript and local splicing methods on simulated data. Lastly, we evaluate BSEEJ on experimental data based on transcript reconstruction, novelty of transcripts produced, model sensitivity to hyperparameters, and a functional analysis of differentially expressed SEEJs. AVAILABILITY AND IMPLEMENTATION: BSEEJ is freely available at https://github.com/bayesomicslab/BSEEJ.

Bayes Theorem

Improved splice site detection in Genie.

We present an improved splice site predictor for the genefinding program Genie. Genie is based on a generalized Hidden Markov Model (GHMM) that describes the grammar of a legal parse of a multi-exon gene in a DNA sequence. In Genie, probabilities are estimated for gene features by using dynamic programming to combine information from multiple content and signal sensors, including sensors that integrate matches to homologous sequences from a database. One of the hardest problems in genefinding is to determine the complete gene structure correctly. The splice site sensors are the key signal sensors that address this problem. We replaced the existing splice site sensors in Genie with two novel neural networks based on dinucleotide frequencies. Using these novel sensors, Genie shows significant improvements in the sensitivity and specificity of gene structure identification. Experimental results in tests using a standard set of annotated genes showed that Genie identified 86% of coding nucleotides correctly with a specificity of 85%, versus 80% and 84% in the older system. In further splice site experiments, we also looked at correlations between splice site scores and intron and exon lengths, as well as at the effect of distance to the nearest splice site on false positive rates.

Animals

Prediction of locally optimal splice sites in plant pre-mRNA with applications to gene identification in Arabidopsis thaliana genomic DNA.

Prediction of splice site selection and efficiency from sequence inspection is of fundamental interest (testing the current knowledge of requisite sequence features) and practical importance (genome annotation, design of mutant or transgenic organisms). In plants, the dominant variables affecting splice site selection and efficiency include the degree of matching to the extended splice site consensus and the local gradient of U- and G+C-composition (introns being U-rich and exons G+C-rich). We present a novel method for splice site prediction, which was particularly trained for maize and Arabidopsis thaliana. The method extends our previous algorithm based on logitlinear models by considering three variables simultaneously: intrinsic splice site strength, local optimality and fit with respect to the overall splice pattern prediction. We show that the method considerably improves prediction specificity without compromising the high degree of sensitivity required in gene prediction algorithms. Applications to gene identification are illustrated for Arabidopsis and suggest that successful methods must combine scoring for splice sites, coding potential and similarity with potential homologs in non-trivial ways. A WWW version of the SplicePredictor program is available at http:/gnomic.stanford.edu/volker/SplicePredi ctor.html/

Algorithms

Tackling non-canonical splicing in arrhythmogenic cardiomyopathy to reduce the uncertain significance variants burden.

BACKGROUND: Splice-altering variants (SAVs), particularly those outside canonical splice sites, are an underappreciated contributor to inherited cardiovascular diseases. In arrhythmogenic cardiomyopathy (ACM), these variants frequently remain classified as of uncertain significance (VUS) due to limited predictive power and lack of transcript-level evidence, constraining genetic yield and clinical management. Our study aimed to determine the functional impact of SAVs in ACM genes and refine their classification using ACMG/AMP and ClinGen SVI criteria. METHODS: SAVs identified in 200 ACM probands underwent SpliceAI prediction, GTEx cardiac exon-usage annotation, and functional assessment using pSPL3-based minigene assays. Aberrant transcripts were quantified using Percent Splicing Alteration (PSA). Segregation data and ACMG/AMP criteria refined by ClinGen SVI were applied to integrate functional and clinical evidence for classification. RESULTS: Aberrant splicing was confirmed in 9/20 variants (45%), including synonymous, missense, and non-canonical intronic changes. SpliceAI scores correlated strongly with PSA values (R²=0.86). Case-control burden testing revealed significant enrichment of splice-altering variants in DSP, DSG2, DSC2 and FLNC. Integrating predictive algorithms with experimental validation and segregation analysis markedly enhances reclassification of 16/20 variants (80%). CONCLUSION: Splicing defects beyond canonical sites significantly shape ACM genetic landscape. Integrating predictive models with experimental validation clarifies uncertain variants bridging the gap between genomic uncertainty and clinical decision-making.

Humans

Mitochondrial genomic characteristics and phylogenetic analysis of Cunninghamella elegans (Mucorales: Cunninghamellaceae).

Cunninghamella, a filamentous fungal genus with important biomedical and biochemical value, lacks any fully annotated mitochondrial genome to date. Herein, we presented the first complete mitogenome of Cunninghamella elegans, a circular 41,552 bp molecule (GC 27.86%) encoding 14 conserved protein-coding genes, 2 rRNA genes, 24 tRNA genes, and 6 non-conserved ORFs. Structural comparison with related species (Absidia glauca and Gongronella sp. w5) revealed dynamic evolution in intron and repeat elements. Phylogenetics places C. elegans within Cunninghamellaceae, with Gongronella as its closest relative. This reference mitogenome will underpin future evolutionary and taxonomic investigations of this industrially and medically significant lineage.

Cunninghamella elegans

Dynamite: a flexible code generating language for dynamic programming methods used in sequence comparison.

We have developed a code generating language, called Dynamite, specialised for the production and subsequent manipulation of complex dynamic programming methods for biological sequence comparison. From a relatively simple text definition file Dynamite will produce a variety of implementations of a dynamic programming method, including database searches and linear space alignments. The speed of the generated code is comparable to hand written code, and the additional flexibility has proved invaluable in designing and testing new algorithms. An innovation is a flexible labelling system, which can be used to annotate the original sequences with biological information. We illustrate the Dynamite syntax and flexibility by showing definitions for dynamic programming routines (i) to align two protein sequences under the assumption that they are both poly-topic transmembrane proteins, with the simultaneous assignment of transmembrane helices and (ii) to align protein information to genomic DNA, allowing for introns and sequencing error.

Algorithms

The complete and annotated mitochondrial genome of Hemileia vastatrix Race I, causal agent of coffee leaf rust.

Hemileia vastatrix is the fungal pathogen responsible for coffee leaf rust (CLR), the most economically important disease of Coffea arabica worldwide. Recently, the nuclear genome of this fungus was completely deciphered. However, the mitochondrial genome of H. vastatrix has remained undercharacterized. Here, we present the complete, circularized mitochondrial genome of H. vastatrix Race I (isolate HvRI), assembled using a hybrid approach combining PacBio HiFi long reads and BGIseq short reads. The genome is 173,525 bp in length with a GC content of 33.1% and encodes 41 functional genes, including 15 protein-coding genes, 2 rRNAs, and 24 tRNAs. The assembly reveals significant structural complexity, driven by intron expansion in the cox1 and cob genes. Notably, the atp8 gene contains a group II intron, rare for this locus, whose internal open reading frame displays evidence of pseudogenization via internal stop codons.. We also characterized a putative replication initiation zone (~1.2 kb) defined by a poly-G homopolymer and conserved regulatory motifs. The mitogenome of the HvRI isolate does not contain cob mutations that lead to amino acid substitutions G143A and F129L associated with the quinone outside inhibitor (QoI) fungicide resistance. This high-quality mitogenome is an important resource for comparative mitogenomics, population diversity studies, and the molecular surveillance of QoI fungicide resistance.

Genome, Mitochondrial

Construction of an approximately 700-kb transcript map around the familial Mediterranean fever locus on human chromosome 16p13.3.

We used a combination of cDNA selection, exon amplification, and computational prediction from genomic sequence to isolate transcribed sequences from genomic DNA surrounding the familial Mediterranean fever (FMF) locus. Eighty-seven kb of genomic DNA around D16S3370, a marker showing a high degree of linkage disequilibrium with FMF, was sequenced to completion, and the sequence annotated. A transcript map reflecting the minimal number of genes encoded within the approximately 700 kb of genomic DNA surrounding the FMF locus was assembled. This map consists of 27 genes with discreet messages detectable on Northerns, in addition to three olfactory-receptor genes, a cluster of 18 tRNA genes, and two putative transcriptional units that have typical intron-exon splice junctions yet do not detect messages on Northerns. Four of the transcripts are identical to genes described previously, seven have been independently identified by the French FMF Consortium, and the others are novel. Six related zinc-finger genes, a cluster of tRNAs, and three olfactory receptors account for the majority of transcribed sequences isolated from a 315-kb FMF central region (between D16S468/D16S3070 and cosmid 377A12). Interspersed among them are several genes that may be important in inflammation. This transcript map not only has permitted the identification of the FMF gene (MEFV), but also has provided us an opportunity to probe the structural and functional features of this region of chromosome 16.

Amino Acid Sequence

Analysis of EST-driven gene annotation in human genomic sequence.

We have performed a systematic analysis of gene identification in genomic sequence by similarity search against expressed sequence tags (ESTs) to assess the suitability of this method for automated annotation of the human genome. A BLAST-based strategy was constructed to examine the potential of this approach, and was applied to test sets containing all human genomic sequences longer than 5 kb in public databases, plus 300 kb of exhaustively characterized benchmark sequence. At high stringency, 70%-90% of all annotated genes are detected by near-identity to EST sequence; >95% of ESTs aligning with well-annotated sequences overlap a gene. These ESTs provide immediate access to the corresponding cDNA clones for follow-up laboratory verification and subsequent biologic analysis. At lower stringency, up to 97% of annotated genes were identified by similarity to ESTs. The apparent false-positive rate rose to 55% of ESTs among all sequences and 20% among benchmark sequences at the lowest stringency, indicating that many genes in public database entries are unannotated. Approximately half of the alignments span multiple exons, and thus aid in the construction of gene predictions and elucidation of alternative splicing. In addition, ESTs from multiple cDNA libraries frequently cluster over genes, providing a starting point for crude expression profiles. Clone IDs may be used to form EST pairs, and particularly to extend models by associating alignments of lower stringency with high-quality alignments. These results demonstrate that EST similarity search is a practical general-purpose annotation technique that complements pattern recognition methods as a tool for gene characterization.

Base Sequence

Mitochondrial genome characteristics and phylogenetic analysis of Ramaria longispora.

This study, for the first time, assembled and annotated the complete mitochondrial genome of R. longispora using high-throughput sequencing technology. The genome is a circular molecule with a total length of 157,712 bp and a GC content of 31.55%. It encodes 71 genes, including 15 core protein-coding genes (PCGs), 25 transfer RNA (tRNA) genes, 2 ribosomal RNA (rRNA) genes, 5 free-stranding open reading frames (ORFs), and 24 intronic ORFs. Among these, most free-stranding ORFs have unknown functions but include a DNA polymerase gene, while the intronic ORFs primarily encode LAGLIDADG and GIY-YIG endonucleases. The mitochondrial genome contains 39 introns. Phylogenetic analyses based on 15 core PCGs using Bayesian inference (BI) and maximum likelihood (ML) methods revealed that this R. longispora is most closely related to Ramaria flavescens and Ramaria ichnusensis. This study provides foundational data for mitochondrial genome research in the Ramaria genus and offers important references for taxonomic and evolutionary studies of this group.

Mitochondrial genome

Dual Aberrant Splicing Caused by an Apparently Missense CHD7 Variant, c.5273A>G (p.Asp1758Gly), in CHARGE Syndrome.

CHARGE syndrome is a rare congenital disorder primarily attributed to heterozygous pathogenic variants of the CHD7 gene. Most pathogenic CHD7 variants are loss-of-function (LoF) variants, whereas the interpretation of missense variants remains challenging in the absence of functional evidence for their pathogenicity. We report a female infant presenting with clinical features characteristic of CHARGE syndrome. Targeted sequencing identified a heterozygous CHD7 variant (NM_017780.4:c.5273A>G), initially annotated as a missense substitution p.Asp1758Gly. This variant has been previously reported and registered with conflicting pathogenicity classifications; however, its transcript-level consequences remain unclear. Long-PCR-based RNA sequencing of total RNA from peripheral blood mononuclear cells revealed two aberrant splicing patterns associated with the variant: a predominant transcript carrying a 28-bp deletion due to cryptic donor splice-site activation, and a minor transcript with partial intron 24 retention. Both transcripts were predicted to result in premature termination codons. These findings demonstrate that c.5273A>G functions as a LoF variant through dual aberrant splicing rather than a simple missense substitution. This case underscores the importance of RNA-level splicing analysis for the accurate interpretation and classification of CHD7 missense variants.

CHD7

Improving spliced alignment by modeling splice sites with deep learning.

MOTIVATION: Spliced alignment refers to the alignment of messenger RNA (mRNA) or protein sequences to eukaryotic genomes. It plays a critical role in gene annotation and the study of gene functions. Accurate spliced alignment demands sophisticated modeling of splice sites, but current aligners use simple models, which may affect their accuracy given dissimilar sequences. RESULTS: We implemented minisplice to learn splice signals with a one-dimensional convolutional neural network (1D-CNN) and trained a model with 7,026 parameters for vertebrate and insect genomes. It captures conserved splice signals across phyla and reveals GC-rich introns specific to mammals and birds. We used this model to estimate the empirical splicing probability for every GT and AG in genomes, and modified minimap2 and miniprot to leverage pre-computed splicing probability during alignment. Evaluation on human long-read RNA-seq data and cross-species protein datasets showed our method greatly improves the junction accuracy especially for noisy long RNA-seq reads and proteins of distant homology. AVAILABILITY AND IMPLEMENTATION: https://github.com/lh3/minisplice.

Journal Article

EbEST: an automated tool using expressed sequence tags to delineate gene structure.

Large numbers of expressed sequence tags (ESTs) continue to fill public and private databases with partial cDNA sequences. However, using this huge amount of ESTs to facilitate gene finding in genomic sequence imposes a challenge, especially to wet-lab scientists who often have limited computing resources. In an effort to consolidate the information hidden in the vast number of ESTs into a readable and manageable format, we have developed EbEST-a program that automates the process of using ESTs to help delineate gene structure in long stretches of genomic sequence. The EbEST program consists of three functional modules-the first module separates homologous ESTs into clusters and identifies the most informative ESTs within each cluster; the second module uses the informative ESTs to perform gapped alignment and to predict the exon-intron boundary; and the third module generates text file and graphic outputs that illustrate the orientation, exonic structure, and untranslated regions (UTRs) of putative genes in the genomic sequence being analyzed. Evaluation of EbEST with 176 human genes from the ALLSEQ set indicated that it performed in-line with several existing gene finding programs, but was more tolerant to sequencing errors. Furthermore, when EbEST was challenged with query sequences that harbor more than one gene, it suffered only a slight drop in performance, whereas the performance of the other programs evaluated decreased more. EbEST may be used as a stand-alone tool to annotate human genomic sequences with EST-derived gene elements, or can be used in conjunction with computational gene-recognition programs to increase the accuracy of gene prediction. [EbBEST is available at http://EbEST.ifrc.mcw.edu]

Base Sequence

Development and validation of a high-density 'Amahysnp' genotyping array in grain amaranth (Amaranthus hypochondriacus).

BACKGROUND: Grain amaranth has recently gained global attention as a promising crop alternative to traditional cereals due to its nutritional value and adaptability to various growing conditions. Although gene banks conserve extensive collections of amaranth germplasm, the genomic and phenotypic characterization of these resources is limited, which hinders their full utilization in breeding programs. A major challenge is the lack of high-throughput genotyping assays essential for comprehensive genomic characterization and trait mapping. High-density SNP arrays have become standard tools for genome-wide analysis across multiple loci, enabling molecular breeding across a range of crop species. RESULTS: In this study, we developed a 64 K high-throughput SNP genotyping array named "AmahySNP", using Affymetrix® Axiom® technology. The array contains 64,069 high-density SNPs distributed across both genic (55.17%) and non-genic (44.83%) regions of the Amaranthus hypochondriacus genome. The genic region includes 8,879 genes, which consist of 4,830 single-copy genes and 4,049 multi-copy genes distributed across 16 scaffolds. These genes cover various functional regions, including exons (10.5%), introns (40.1%), 5'UTRs (1.6%), and 3'UTRs (2.9%), respectively. The AmahySNP array was effectively utilized for population structure analysis, genetic diversity studies, core development, and genome wide association studies (GWAS) in amaranth germplasm. A representative core set of 112 accessions was identified, which includes two released varieties (Annapurna and Suvarna) and 100 diverse accessions from 12 different regions, representing 12% of the total 917 accessions evaluated. Phylogenetic analysis revealed three major genetic clusters, independent of their geographical origins. GWAS conducted using 22,763 polymorphic SNPs from 540 genotypes identified 13 novel loci associated days to flowering (DTF) trait, seven of which were located within annotated genes. CONCLUSIONS: The AmahySNP 64 K SNP chip a valuable genomic tool for amaranth research and breeding with a strong potential to accelerate its genetic improvement. It enables high-throughput genotyping for a wide range of applications, including GWAS and other genomic studies, and will significantly advance the exploration of natural genetic variations. Ultimately, this resource will empower amaranth breeders to develop improved amaranth cultivars with enhanced crop yield, resilience, and nutritional quality, contributing to global food security and sustainable agriculture.

Amaranthus

Gene finding in the chicken genome.

BACKGROUND: Despite the continuous production of genome sequence for a number of organisms, reliable, comprehensive, and cost effective gene prediction remains problematic. This is particularly true for genomes for which there is not a large collection of known gene sequences, such as the recently published chicken genome. We used the chicken sequence to test comparative and homology-based gene-finding methods followed by experimental validation as an effective genome annotation method. RESULTS: We performed experimental evaluation by RT-PCR of three different computational gene finders, Ensembl, SGP2 and TWINSCAN, applied to the chicken genome. A Venn diagram was computed and each component of it was evaluated. The results showed that de novo comparative methods can identify up to about 700 chicken genes with no previous evidence of expression, and can correctly extend about 40% of homology-based predictions at the 5' end. CONCLUSIONS: De novo comparative gene prediction followed by experimental verification is effective at enhancing the annotation of the newly sequenced genomes provided by standard homology-based methods.

Animals

Highly specific localization of promoter regions in large genomic sequences by PromoterInspector: a novel context analysis approach.

We present a new algorithm called PromoterInspector to locate eukaryotic polymase II promoter regions in large genomic sequences with a high degree of specificity. PromoterInspector focuses on the genetic context of promoters, rather than their exact location. Application of PromoterInspector can serve as a crucial pre-processing step for other methods to locate exactly, or to analyze promoters. PromoterInspector does not depend on heuristics, because it is purely based on libraries of IUPAC words extracted from training sequences by an unsupervised learning approach. We compared PromoterInspector to in silico promoter prediction tools using the sequences from the review by J.W. Fickett. PromoterInspector compared favourably on Fickett's evaluation scheme. A true positive to false positive ratio of 2.3 was obtained, surpassing the best ratio of 0.6, reported for TSSG. The application of our method to several large genomic sequences of over 1.3 million base-pairs in total resulted in even more specific predictions. The coverage of annotated promoters was comparable to other in silico promoter prediction methods, while the true positive predictions increased by up to 100% of total matches. PromoterInspector scans 100 kb in less than one minute on a workstation, and thus is especially applicable for large genome analysis. The method is available at http://genomatix.gsf. de/cgi-bin/promoterinspector/promoterinspector.pl.

3' Untranslated Regions

Genetic analysis of four cases of Poirier Bienvenu neurodevelopmental syndrome associated with CSNK2B variant.

BACKGROUND: CSNK2B deficiency underlies the pathogenesis of Poirier-Bienvenu neurodevelopmental syndrome (POBINDS). In this study, we present four cases of pediatric seizures caused by de novo variants in CSNK2B, with the aim to reinforce the clinical and variant data pertaining to early genetic factors associated with epilepsy. METHODS: Trio whole exome sequencing were used to detect variants in the proband and her family members, and bioinformatics annotation was performed for the variant. Sanger sequencing and CSNK2B cDNA sequencing were employed to ascertain the carrier status of additional family members and evaluate the potential impact of variants on splicing. RESULTS: All four cases presented with epilepsy as the initial manifestation, accompanied by global developmental delay, particularly in language and motor developmental delay. Cases 1, 3 and 4 exhibited full-scale tonic-clonic seizures, while case 2 displayed myoclonic and typical absence seizures. Furthermore, case 2 demonstrated delayed growth and development compared to age-matched peers. No abnormality was detected in the head magnetic resonance imaging (MRI). Genetic analysis revealed novel heterozygous variants in the CSNK2B gene in all four cases, including c.175 + 1G > A, c.73-2A > G, c.291 + 1G > A and c.481delA. In case 2, reverse transcription analysis of CSNK2B mRNA revealed the retention of the 3' end sequence of Intron 2 and deletion of the 5' end sequence of Exon 3. In treatment, four case received a combination of one to three types of antiseizure medication and rehabilitation training individually. Case 1 continued to experience seizures to varying degrees, while cases 2-4 demonstrated effective seizure control. Overall motor and intellectual development improved in all four cases, however, there was slow recovery in language function. CONCLUSION: This study elucidates the molecular etiology of epilepsy in four cases with POBINDS and expands the mutational spectrum of pathogenic variants in the CSNK2B, highlighting their impact on splicing. The highly genetic heterogeneous phenotype of POBINDS relies on the detection of pathogenic variants in CSNK2B. Conventional antiseizure medication effectively control seizures, while rehabilitation treatment can significantly improve intelligence and motor function to varying degrees; however, language recovery tends to be relatively slow.

Humans