BACKGROUND: Structural variants (SVs) play an important role in genetic research and precision medicine. As existing SV detection methods usually contain a substantial number of false positive calls, approaches to filter the detection results are needed.
RESULTS: We developed a novel deep learning-based SV filtering tool, CSV-Filter, for both short and long reads. CSV-Filter uses a novel multi-level grayscale image encoding method based on CIGAR strings of the alignment results and employs image augmentation techniques to improve SV feature extraction. CSV-Filter also utilizes self-supervised learning networks for transfer as classification models, and employs mixed-precision operations to accelerate training. The experiments showed that the integration of CSV-Filter with popular SV detection tools could considerably reduce false positive SVs for short and long reads, while maintaining true positive SVs almost unchanged. Compared with DeepSVFilter, a SV filtering tool for short reads, CSV-Filter could recognize more false positive calls and support long reads as an additional feature.
METHODS: https://github.com/xzyschumacher/CSV-Filter.

Hybrid Pennisetum, a top biomass energy source, faces usage limitations because of its scarce lactic acid bacteria and high fiber content. This study assessed the influence of rumen fluid pretreatment on hybrid Pennisetum\'s silage, with focus on silage duration and rumen fluid effects on quality and fiber decomposition. Advanced third-generation sequencing was used to track microbial diversity changes and revealed that rumen fluid considerably enhanced dry matter, crude protein, and water-soluble carbohydrates, thus improving fermentation quality to satisfactory pH levels (3.40-3.67). Ideal results, including the highest fiber breakdown and enzymatic efficiency (47.23 %), were obtained with 5 % rumen fluid in 60 days. The addition of rumen fluid changed the dominant species, including Paucilactobacillus vaccinostercus (0.00 % vs. 18.21 %) and Lactiplantibacillus plantarum (21.03 % vs. 47.02 %), and no Enterobacter was detected in the high-concentration treatments. Moreover, strong correlations were found between specific lactic acid bacteria and fermentation indicators, revealing the potential of achieving efficient and economically beneficial hybrid Pennisetum production.

BACKGROUND: Structural variation (SV) detection methods using third-generation sequencing data are widely employed, yet accurately detecting SVs remains challenging. Different methods often yield inconsistent results for certain SV types, complicating tool selection and revealing biases in detection.
RESULTS: This study comprehensively evaluates 53 SV detection pipelines using simulated and real data from PacBio (CLR: Continuous Long Read, CCS: Circular Consensus Sequencing) and Nanopore (ONT) platforms. We assess their performance in detecting various sizes and types of SVs, breakpoint biases, and genotyping accuracy with various sequencing depths. Notably, pipelines such as Minimap2-cuteSV2, NGMLR-SVIM, PBMM2-pbsv, Winnowmap-Sniffles2, and Winnowmap-SVision exhibit comparatively higher recall and precision. Our findings also show that combining multiple pipelines with the same aligner, like pbmm2 or winnowmap, can significantly enhance performance. The individual pipelines\' detailed ranking and performance metrics can be viewed in a dynamic table: http://pmglab.top/SVPipelinesRanking .
CONCLUSIONS: This study comprehensively characterizes the strengths and weaknesses of numerous pipelines, providing valuable insights that can improve SV detection in third-generation sequencing data and inform SV annotation and function prediction.

α-thalassemia major (α-TM) often causes Hb Bart\'s (c4) hydrops fetalis and severe obstetric complications in the mother. Step-wise screening for couples at risk of having offspring(s) affected by α-TM is the efficient prevention method but some rare genotypes of thalassemia cannot be detected. A 32-year-old male with low HbA2 (2.4%) and mild anemia was performed real-time PCR-based multicolor melting curve analysis (MMCA) because his wife was -SEA deletion carrier. The result of multiplex ligation-dependent probe amplification (MLPA) suggested the existence of -SEA deletion in the proband. A novel deletion of the α-globin gene cluster was found using self-designed MLPA probes combined with longer PCR, which was further accurately described to be 16.8Kb (hg38, Chr16:1,65,236-1,82,113) deletion by the third-generation sequencing. A fragment ranging from 1,53,226 to 1,54,538(GRch38/hg38) was identified which suggested the existence of the homologous recombination event. The third-generation sequencing is accurate and efficient in obtaining accurate information for complex structural variations.

While poly (3-hydroxybutyrate) (PHB) holds promise as a bioplastic, its commercial utilization has been hampered by the high cost of raw materials. However, glycerol emerges as a viable feedstock for PHB production, offering a sustainable production approach and substantial cost reduction potential. Glycerol stands out as a promising feedstock for PHB production, offering a pathway toward sustainable manufacturing and considerable cost savings. The identification and characterization of strains capable of converting glycerol into PHB represent a pivotal strategy in advancing PHB production research. In this study, we isolated a strain, Ralstonia sp. RRA (RRA). The strain exhibits remarkable proficiency in synthesizing PHB from glycerol. With glycerol as the carbon source, RRA achieved a specific growth rate of 0.19 h-1, attaining a PHB content of approximately 50% within 30 h. Through third-generation genome and transcriptome sequencing, we elucidated the genome composition and identified a total of eight genes (glpR, glpD, glpS, glpT, glpP, glpQ, glpV, and glpK) involved in the glycerol metabolism pathway. Leveraging these findings, the strain RRA demonstrates significant promise in producing PHB from low-cost renewable carbon sources.

Honeybees are an indispensable pollinator in nature with pivotal ecological, economic, and scientific value. However, a full-length transcriptome for Apis mellifera, assembled with the advanced third-generation nanopore sequencing technology, has yet to be reported. Here, nanopore sequencing of the midgut tissues of uninoculated and Nosema ceranae-inoculated A. mellifera workers was conducted, and the full-length transcriptome was then constructed and annotated based on high-quality long reads. Next followed improvement of sequences and annotations of the current reference genome of A. mellifera. A total of 5,942,745 and 6,664,923 raw reads were produced from midguts of workers at 7 days post-inoculation (dpi) with N. ceranae and 10 dpi, while 7,100,161 and 6,506,665 raw reads were generated from the midguts of corresponding uninoculated workers. After strict quality control, 6,928,170, 6,353,066, 5,745,048, and 6,416,987 clean reads were obtained, with a length distribution ranging from 1 kb to 10 kb. Additionally, 16,824, 17,708, 15,744, and 18,246 full-length transcripts were respectively detected, including 28,019 nonredundant ones. Among these, 43,666, 30,945, 41,771, 26,442, and 24,532 full-length transcripts could be annotated to the Nr, KOG, eggNOG, GO, and KEGG databases, respectively. Additionally, 501 novel genes (20,326 novel transcripts) were identified for the first time, among which 401 (20,255), 193 (13,365), 414 (19,186), 228 (12,093), and 202 (11,703) were respectively annotated to each of the aforementioned five databases. The expression and sequences of three randomly selected novel transcripts were confirmed by RT-PCR and Sanger sequencing. The 5\' UTR of 2082 genes, the 3\' UTR of 2029 genes, and both the 5\' and 3\' UTRs of 730 genes were extended. Moreover, 17,345 SSRs, 14,789 complete ORFs, 1224 long non-coding RNAs (lncRNAs), and 650 transcription factors (TFs) from 37 families were detected. Findings from this work not only refine the annotation of the A. mellifera reference genome, but also provide a valuable resource and basis for relevant molecular and -omics studies.

OBJECTIVE: To explore the diagnostic value of third-generation nanopore sequencing technology in patients with diabetes mellitus suspected of pulmonary tuberculosis.
METHODS: Samples, including sputum and bronchoalveolar lavage fluid(BALF), were collected from patients with diabetes mellitus suspected of pulmonary tuberculosis who were admitted from October 2021 to August 2023. Nanopore sequencing, acid-fast bacilli (AFB) smear, mycobacterial solid culture, Xpert MTB/RIF, and DNA detection were performed, and their diagnostic efficacy was compared.
RESULTS: Third-generation nanopore sequencing technology exhibited high accuracy in diagnosing pulmonary tuberculosis in patients with diabetes mellitus. Compared to traditional methods, nanopore sequencing showed significantly improved sensitivity (76.80 %), negative predictive value (30.40 %), coincidence (77.92 %), and diagnostic accuracy (AUC = 0.822). Combined detection with Xpert achieved the highest diagnostic performance, with increased sensitivity (81.20 %), positive predictive value (98.20 %), negative predictive value (35.00 %), coincidence (81.82 %), and AUC (0.843). Although acid-fast staining had limitations, its combination with nanopore sequencing improved screening effectiveness.
CONCLUSIONS: Compared to established diagnostic modalities such as acid-fast staining, mycobacterial solid culture, Xpert MTB/RIF, and DNA detection, third-generation nanopore sequencing technology demonstrates a significant improvement in sensitivity for detecting suspected pulmonary tuberculosis in diabetic patients. Notably, the combined application of nanopore sequencing with Xpert testing offers a further enhancement in diagnostic accuracy.

Deletion is a crucial type of genomic structural variation and is associated with numerous genetic diseases. The advent of third-generation sequencing technology has facilitated the analysis of complex genomic structures and the elucidation of the mechanisms underlying phenotypic changes and disease onset due to genomic variants. Importantly, it has introduced innovative perspectives for deletion variants calling. Here we propose a method named Dual Attention Structural Variation (DASV) to analyze deletion structural variations in sequencing data. DASV converts gene alignment information into images and integrates them with genomic sequencing data through a dual attention mechanism. Subsequently, it employs a multi-scale network to precisely identify deletion regions. Compared with four widely used genome structural variation calling tools: cuteSV, SVIM, Sniffles and PBSV, the results demonstrate that DASV consistently achieves a balance between precision and recall, enhancing the F1 score across various datasets. The source code is available at https://github.com/deconvolution-w/DASV.

Thalassemia is one of the most common and damaging monogenic diseases in the world. It is caused by pathogenic variants of α- and/or β-globin genes, which disrupt the balance of these two protein chains and leads to α-thalassemia or β-thalassemia, respectively. Patients with α-thalassemia or β-thalassemia could exhibit a severe phenotype, with no simple and effective treatment. A three-tiered strategy of carrier screening, prenatal diagnosis and newborn screening has been established in China for the prevention and control of thalassemia, of which the first two parts have been studied thoroughly. The implementation of neonatal thalassemia screening is lagging, and the effectiveness of various screening programs has not yet been demonstrated. In this study, hemoglobin capillary electrophoresis (CE), hotspot testing method, and third-generation sequencing (TGS) were used in the variant detection of 2000 newborn samples, to assess the efficacy of these methods in neonatal thalassemia screening. Compared with CE (249, 12.45 %) and hotspot analysis (424, 21.2 %), CATSA detected the largest number of thalassemia variants (535, 26.75 %), which included 24 hotspot variants, increased copy number of α-globin gene, rare pathogenic variants, and three unreported potentially disease-causing variants. More importantly, CATSA directly determined the cis-trans relationship of variants in three newborns, which greatly shortens the clinical diagnosis time of thalassemia. CATSA showed a great advantage over other genetic tests and could become the most powerful technical support for the three-tiered prevention and control strategy of thalassemia.

UNASSIGNED: Conventional thalassemia screening takes a stepwise approach and has limitations in comprehensively identifying all spectrums of mutations. This study aimed to investigate the performance of third-generation sequencing (TGS) compared to conventional molecular testing.
UNASSIGNED: TGS was applied to validate all known variants detected by conventional testing and to detect missing variants in undiagnosed cases. The study was conducted at Maharaj Nakorn Chiang Mai Hospital between December 2021 and April 2022.
UNASSIGNED: In total, 19 cases were included in this study, among which 52.6% (10/19) had known thalassemia variants, while 47.7% (9/19) cases were undiagnosed by conventional methods. All 16 variants previously detected were validated by TGS, and TGS additionally detected 43.8% (7/16) thalassemia variants for 36.8% (7/19) cases.
UNASSIGNED: TGS could provide additional genetic diagnoses compared with conventional methods. Further cost-effectiveness studies with a larger sample size are needed to explore the role of TGS in clinical practices.