Briefings in Functional Genomics最新文献_第4页

A lossless reference-free sequence compression algorithm leveraging grammatical, statistical, and substitution rules. 利用语法、统计和替换规则的无损无引用序列压缩算法。

IF 2.5 3区生物学

Briefings in Functional Genomics Pub Date : 2025-01-15 DOI: 10.1093/bfgp/elae050

Subhankar Roy, Dilip Kumar Maity, Anirban Mukhopadhyay

{"title":"A lossless reference-free sequence compression algorithm leveraging grammatical, statistical, and substitution rules.","authors":"Subhankar Roy, Dilip Kumar Maity, Anirban Mukhopadhyay","doi":"10.1093/bfgp/elae050","DOIUrl":"10.1093/bfgp/elae050","url":null,"abstract":"Deoxyribonucleic acid (DNA) or ribonucleic acid (RNA) sequence compressors for novel species frequently face challenges when processing wide-scale raw, FASTA, or multi-FASTA structured data. For years, molecular sequence databases have favored the widely used general-purpose Gzip and Zstd compressors. The absence of sequence-specific characteristics in these encoders results in subpar performance, and their use depends on time-consuming parameter adjustments. To address these limitations, in this article, we propose a reference-free, lossless sequence compressor called GraSS (Grammatical, Statistical, and Substitution Rule-Based). GraSS compresses sequences more effectively by taking advantage of certain characteristics seen in DNA and RNA sequences. It supports various formats, including raw, FASTA, and multi-FASTA, commonly found in GenBank DNA and RNA files. We evaluate GraSS's performance using ten benchmark DNA sequences with reduced number of repeats, two highly repetitive RNA sequences, and fifteen raw DNA sequences. Test results indicate that the weighted average compression ratios (WACR) for DNA and RNA sequences are 4.5 and 19.6, respectively. Additionally, the entire DNA sequence corpus has a total compression time (TCT) of 246.8 seconds (s). These results demonstrate that the proposed compression method performs better than several advanced algorithms specifically designed to handle various levels of sequence redundancy. The decompression times, memory usage, and CPU usage are also very competitive. Contact: anirban@klyuniv.ac.in.","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11735755/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142959201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identification of pathogenic cell types and shared genetic loci and genes for Alzheimer's disease and inflammatory bowel disease. 阿尔茨海默病和炎症性肠病的致病细胞类型和共享基因位点和基因的鉴定。

IF 2.5 3区生物学

Briefings in Functional Genomics Pub Date : 2025-01-15 DOI: 10.1093/bfgp/elaf013

Jingjing Zhang, Yuqing Yan, Liqin Han, Rui Qiao, Xiaohui Niu, Peiluan Li

{"title":"Identification of pathogenic cell types and shared genetic loci and genes for Alzheimer's disease and inflammatory bowel disease.","authors":"Jingjing Zhang, Yuqing Yan, Liqin Han, Rui Qiao, Xiaohui Niu, Peiluan Li","doi":"10.1093/bfgp/elaf013","DOIUrl":"10.1093/bfgp/elaf013","url":null,"abstract":"Background: Comorbidities and genetic correlations between gastrointestinal tract diseases and psychiatric disorders have been widely reported, but the underlying intrinsic link between Alzheimer's disease (AD) and inflammatory bowel disease (IBD) is not adequately understood.Methods: To identify pathogenic cell types of AD and IBD and explore their shared genetic architecture, we developed Pathogenic Cell types and shared Genetic Loci (PCGL) framework, which studied AD and IBD and its two subtypes of ulcerative colitis (UC) and Crohn's disease (CD).Results: We found that monocytes and CD8 T cells were the enriched pathogenic cell types of AD and IBDs, respectively. By PCGL framework, there was a significant global genetic correlation between AD and each of IBD, UC, and CD. Especially, local genetic correlations between AD and IBD showed strong signals in chr6. Bidirectional two-sample MR Analyses also validated these. Cross-trait meta-analysis identified two key genetic loci rs660895 (on chr6) and rs917117 (on chr7), which have not been previously reported. Two loci are located on the genes HLA-DRB1 and JAZF1, respectively. MAGMA genome-wide gene-based analysis identified six overlapping genes including HLA-DRB1. Subsequently, for one thing, SMR analyses further validated six shared genes in specific tissues and monocytes. For another, pathway enrichment analysis revealed shared genes were enriched in several natural killer cell mediated cytotoxicity and chemokine signaling pathways.Conclusions: PCGL not only revealed the significant genetic correlations underlying AD and IBDs but also identified enriched pathogenic cell types and new shared loci and genes. We highlighted the mediation of HLA-DRB1 effects in the comorbidity mechanisms.","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":"24 ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12415860/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145014481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unmeasured human transcription factor ChIP-seq data shape functional genomics and demand strategic prioritization. 未测量的人类转录因子ChIP-seq数据塑造功能基因组学和需求战略优先级。

IF 2.5 3区生物学

Briefings in Functional Genomics Pub Date : 2025-01-15 DOI: 10.1093/bfgp/elaf016

Saeko Tahara, Haruka Ozaki

{"title":"Unmeasured human transcription factor ChIP-seq data shape functional genomics and demand strategic prioritization.","authors":"Saeko Tahara, Haruka Ozaki","doi":"10.1093/bfgp/elaf016","DOIUrl":"10.1093/bfgp/elaf016","url":null,"abstract":"Transcription factor (TF) chromatin immunoprecipitation followed by sequencing (ChIP-seq) is essential for identifying genome-wide TF-binding sites (TFBSs), and the collected datasets offer a variety of opportunities for downstream analyses such as inference of gene regulatory network and prediction for effects of single-nucleotide polymorphisms (SNPs) on TFBSs. Although TF ChIP-seq data continue to accumulate in public databases, comprehensive coverage of biologically relevant TF-sample pairs (i.e. combination of targeted TF and cell type) remains elusive. This is due to the need for TF-specific antibodies and large cell numbers, limiting feasible TF-cell type combinations. Moreover, ChIP-seq is measurable when the TF is expressed in the target cell type. Thus, defining the full space of biologically relevant TF-sample pairs-including both measured and unmeasured-is essential to assess and improve dataset comprehensiveness. Here, we investigated publicly available human TF ChIP-seq datasets and introduced the concept of unmeasured TF-sample pairs, defined as biologically relevant TF-sample combinations for which ChIP-seq experiments have not yet been performed. Notably, many expressed TFs in specific cell types remain unmeasured by ChIP-seq, affecting the coverage of regulatory regions revealed by TF ChIP-seq and genome-wide association study-SNP analyses. Furthermore, we propose practical strategies to efficiently supplement currently unmeasured data and discuss how these approaches can significantly enhance data-driven research. The database of unmeasured human TF-sample pairs is publicly accessible at https://moccs-db.shinyapps.io/Unmeasured_shiny_v1/, facilitating the systematic expansion of TF ChIP-seq datasets and thereby enhancing our comprehension of gene regulatory mechanisms.","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":"24 ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12479113/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145193796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A comprehensive review of approaches for spatial domain recognition of spatial transcriptomes. 空间转录组的空间域识别方法综述。

IF 2.5 3区生物学

Briefings in Functional Genomics Pub Date : 2024-12-06 DOI: 10.1093/bfgp/elae040

Ziyi Wang, Aoyun Geng, Hao Duan, Feifei Cui, Quan Zou, Zilong Zhang

引用次数: 0

AMLdb: a comprehensive multi-omics platform to identify biomarkers and drug targets for acute myeloid leukemia. AMLdb：鉴定急性髓性白血病生物标志物和药物靶点的综合性多组学平台。

IF 2.5 3区生物学

Briefings in Functional Genomics Pub Date : 2024-12-06 DOI: 10.1093/bfgp/elae024

Keerthana Vinod Kumar, Ambuj Kumar, Kavita Kundal, Avik Sengupta, Kunjulakshmi R, Subashani Singh, Bhanu Teja Korra, Simran Sharma, Vandana Suresh, Mayilaadumveettil Nishana, Rahul Kumar

{"title":"AMLdb: a comprehensive multi-omics platform to identify biomarkers and drug targets for acute myeloid leukemia.","authors":"Keerthana Vinod Kumar, Ambuj Kumar, Kavita Kundal, Avik Sengupta, Kunjulakshmi R, Subashani Singh, Bhanu Teja Korra, Simran Sharma, Vandana Suresh, Mayilaadumveettil Nishana, Rahul Kumar","doi":"10.1093/bfgp/elae024","DOIUrl":"10.1093/bfgp/elae024","url":null,"abstract":"Acute myeloid leukemia (AML) is one of the leading leukemic malignancies in adults. The heterogeneity of the disease makes the diagnosis and treatment extremely difficult. With the advent of next-generation sequencing (NGS) technologies, exploration at the molecular level for the identification of biomarkers and drug targets has been the focus for the researchers to come up with novel therapies for better prognosis and survival outcomes of AML patients. However, the huge amount of data from NGS platforms requires a comprehensive AML platform to streamline literature mining efforts and save time. To facilitate this, we developed AMLdb, an interactive multi-omics platform that allows users to query, visualize, retrieve, and analyse AML related multi-omics data. AMLdb contains 86 datasets for gene expression profiles, 15 datasets for methylation profiles, CRISPR-Cas9 knockout screens of 26 AML cell lines, sensitivity of 26 AML cell lines to 288 drugs, mutations in 41 unique genes in 23 AML cell lines, and information on 41 experimentally validated biomarkers. In this study, we have reported five genes, i.e. CBFB, ENO1, IMPDH2, SEPHS2, and MYH9 identified via our analysis using AMLdb. ENO1 is uniquely identified gene which requires further investigation as a novel potential target while other reported genes have been previously confirmed as targets through experimental studies. Top of form we believe that these findings utilizing AMLdb can make it an invaluable resource to accelerate the development of effective therapies for AML and assisting the research community in advancing their understanding of AML pathogenesis. AMLdb is freely available at https://project.iith.ac.in/cgntlab/amldb.","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":" ","pages":"798-805"},"PeriodicalIF":2.5,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141307484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing novel isoform discovery: leveraging nanopore long-read sequencing and machine learning approaches. 加强新型同工酶的发现：利用纳米孔长读数测序和机器学习方法。

IF 2.5 3区生物学

Briefings in Functional Genomics Pub Date : 2024-12-06 DOI: 10.1093/bfgp/elae031

Kristina Santucci, Yuning Cheng, Si-Mei Xu, Michael Janitz

{"title":"Enhancing novel isoform discovery: leveraging nanopore long-read sequencing and machine learning approaches.","authors":"Kristina Santucci, Yuning Cheng, Si-Mei Xu, Michael Janitz","doi":"10.1093/bfgp/elae031","DOIUrl":"10.1093/bfgp/elae031","url":null,"abstract":"Long-read sequencing technologies can capture entire RNA transcripts in a single sequencing read, reducing the ambiguity in constructing and quantifying transcript models in comparison to more common and earlier methods, such as short-read sequencing. Recent improvements in the accuracy of long-read sequencing technologies have expanded the scope for novel splice isoform detection and have also enabled a far more accurate reconstruction of complex splicing patterns and transcriptomes. Additionally, the incorporation and advancements of machine learning and deep learning algorithms in bioinformatic software have significantly improved the reliability of long-read sequencing transcriptomic studies. However, there is a lack of consensus on what bioinformatic tools and pipelines produce the most precise and consistent results. Thus, this review aims to discuss and compare the performance of available methods for novel isoform discovery with long-read sequencing technologies, with 25 tools being presented. Furthermore, this review intends to demonstrate the need for developing standard analytical pipelines, tools, and transcript model conventions for novel isoform discovery and transcriptomic studies.","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":" ","pages":"683-694"},"PeriodicalIF":2.5,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142001414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advances in integrating single-cell sequencing data to unravel the mechanism of ferroptosis in cancer. 整合单细胞测序数据以揭示癌症中铁凋亡机制的进展。

IF 2.5 3区生物学

Briefings in Functional Genomics Pub Date : 2024-12-06 DOI: 10.1093/bfgp/elae025

Zhaolan Du, Yi Shi, Jianjun Tan

{"title":"Advances in integrating single-cell sequencing data to unravel the mechanism of ferroptosis in cancer.","authors":"Zhaolan Du, Yi Shi, Jianjun Tan","doi":"10.1093/bfgp/elae025","DOIUrl":"10.1093/bfgp/elae025","url":null,"abstract":"Ferroptosis, a commonly observed type of programmed cell death caused by abnormal metabolic and biochemical mechanisms, is frequently triggered by cellular stress. The occurrence of ferroptosis is predominantly linked to pathophysiological conditions due to the substantial impact of various metabolic pathways, including fatty acid metabolism and iron regulation, on cellular reactions to lipid peroxidation and ferroptosis. This mode of cell death serves as a fundamental factor in the development of numerous diseases, thereby presenting a range of therapeutic targets. Single-cell sequencing technology provides insights into the cellular and molecular characteristics of individual cells, as opposed to bulk sequencing, which provides data in a more generalized manner. Single-cell sequencing has found extensive application in the field of cancer research. This paper reviews the progress made in ferroptosis-associated cancer research using single-cell sequencing, including ferroptosis-associated pathways, immune checkpoints, biomarkers, and the identification of cell clusters associated with ferroptosis in tumors. In general, the utilization of single-cell sequencing technology has the potential to contribute significantly to the investigation of the mechanistic regulatory pathways linked to ferroptosis. Moreover, it can shed light on the intricate connection between ferroptosis and cancer. This technology holds great promise in advancing tumor-wide diagnosis, targeted therapy, and prognosis prediction.","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":" ","pages":"713-725"},"PeriodicalIF":2.5,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141319002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SAMP: Identifying antimicrobial peptides by an ensemble learning model based on proportionalized split amino acid composition. SAMP：基于按比例分割氨基酸组成的集合学习模型识别抗菌肽。

IF 2.5 3区生物学

Briefings in Functional Genomics Pub Date : 2024-12-06 DOI: 10.1093/bfgp/elae046

Junxi Feng, Mengtao Sun, Cong Liu, Weiwei Zhang, Changmou Xu, Jieqiong Wang, Guangshun Wang, Shibiao Wan

{"title":"SAMP: Identifying antimicrobial peptides by an ensemble learning model based on proportionalized split amino acid composition.","authors":"Junxi Feng, Mengtao Sun, Cong Liu, Weiwei Zhang, Changmou Xu, Jieqiong Wang, Guangshun Wang, Shibiao Wan","doi":"10.1093/bfgp/elae046","DOIUrl":"10.1093/bfgp/elae046","url":null,"abstract":"It is projected that 10 million deaths could be attributed to drug-resistant bacteria infections in 2050. To address this concern, identifying new-generation antibiotics is an effective way. Antimicrobial peptides (AMPs), a class of innate immune effectors, have received significant attention for their capacity to eliminate drug-resistant pathogens, including viruses, bacteria, and fungi. Recent years have witnessed widespread applications of computational methods especially machine learning (ML) and deep learning (DL) for discovering AMPs. However, existing methods only use features including compositional, physiochemical, and structural properties of peptides, which cannot fully capture sequence information from AMPs. Here, we present SAMP, an ensemble random projection (RP) based computational model that leverages a new type of feature called proportionalized split amino acid composition (PSAAC) in addition to conventional sequence-based features for AMP prediction. With this new feature set, SAMP captures the residue patterns like sorting signals at both the N-terminal and the C-terminal, while also retaining the sequence order information from the middle peptide fragments. Benchmarking tests on different balanced and imbalanced datasets demonstrate that SAMP consistently outperforms existing state-of-the-art methods, such as iAMPpred and AMPScanner V2, in terms of accuracy, Matthews correlation coefficient (MCC), G-measure, and F1-score. In addition, by leveraging an ensemble RP architecture, SAMP is scalable to processing large-scale AMP identification with further performance improvement, compared to those models without RP. To facilitate the use of SAMP, we have developed a Python package that is freely available at https://github.com/wan-mlab/SAMP.","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":" ","pages":"879-890"},"PeriodicalIF":2.5,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11631067/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142689781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Long-read RNA sequencing can probe organelle genome pervasive transcription. 长读 RNA 测序可探测细胞器基因组的普遍转录。

IF 2.5 3区生物学

Briefings in Functional Genomics Pub Date : 2024-12-06 DOI: 10.1093/bfgp/elae026

Matheus Sanita Lima, Douglas Silva Domingues, Alexandre Rossi Paschoal, David Roy Smith

{"title":"Long-read RNA sequencing can probe organelle genome pervasive transcription.","authors":"Matheus Sanita Lima, Douglas Silva Domingues, Alexandre Rossi Paschoal, David Roy Smith","doi":"10.1093/bfgp/elae026","DOIUrl":"10.1093/bfgp/elae026","url":null,"abstract":"40 years ago, organelle genomes were assumed to be streamlined and, perhaps, unexciting remnants of their prokaryotic past. However, the field of organelle genomics has exposed an unparallel diversity in genome architecture (i.e. genome size, structure, and content). The transcription of these eccentric genomes can be just as elaborate - organelle genomes are pervasively transcribed into a plethora of RNA types. However, while organelle protein-coding genes are known to produce polycistronic transcripts that undergo heavy posttranscriptional processing, the nature of organelle noncoding transcriptomes is still poorly resolved. Here, we review how wet-lab experiments and second-generation sequencing data (i.e. short reads) have been useful to determine certain types of organelle RNAs, particularly noncoding RNAs. We then explain how third-generation (long-read) RNA-Seq data represent the new frontier in organelle transcriptomics. We show that public repositories (e.g. NCBI SRA) already contain enough data for inter-phyla comparative studies and argue that organelle biologists can benefit from such data. We discuss the prospects of using publicly available sequencing data for organelle-focused studies and examine the challenges of such an approach. We highlight that the lack of a comprehensive database dedicated to organelle genomics/transcriptomics is a major impediment to the development of a field with implications in basic and applied science.","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":" ","pages":"695-701"},"PeriodicalIF":2.5,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141332590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prioritization of candidate genes for major QTLs governing yield traits employing integrated multi-omics approach in rice (Oryza sativa L.). 利用综合多组学方法对水稻（Oryza sativa L.）产量性状主要 QTL 候选基因进行优先排序。

IF 2.5 3区生物学

Briefings in Functional Genomics Pub Date : 2024-12-06 DOI: 10.1093/bfgp/elae035

Issa Keerthi, Vishnu Shukla, Sudhamani Kalluru, Lal Ahamed Mohammad, P Lavanya Kumari, Eswarayya Ramireddy, Lakshminarayana R Vemireddy

{"title":"Prioritization of candidate genes for major QTLs governing yield traits employing integrated multi-omics approach in rice (Oryza sativa L.).","authors":"Issa Keerthi, Vishnu Shukla, Sudhamani Kalluru, Lal Ahamed Mohammad, P Lavanya Kumari, Eswarayya Ramireddy, Lakshminarayana R Vemireddy","doi":"10.1093/bfgp/elae035","DOIUrl":"10.1093/bfgp/elae035","url":null,"abstract":"Rapidly identifying candidate genes underlying major QTLs is crucial for improving rice (Oryza sativa L.). In this study, we developed a workflow to rapidly prioritize candidate genes underpinning 99 major QTLs governing yield component traits. This workflow integrates multiomics databases, including sequence variation, gene expression, gene ontology, co-expression analysis, and protein-protein interaction. We predicted 206 candidate genes for 99 reported QTLs governing ten economically important yield-contributing traits using this approach. Among these, transcription factors belonging to families of MADS-box, WRKY, helix-loop-helix, TCP, MYB, GRAS, auxin response factor, and nuclear transcription factor Y subunit were promising. Validation of key prioritized candidate genes in contrasting rice genotypes for sequence variation and differential expression identified Leucine-Rich Repeat family protein (LOC_Os03g28270) and cytochrome P450 (LOC_Os02g57290) as candidate genes for the major QTLs GL1 and pl2.1, which govern grain length and panicle length, respectively. In conclusion, this study demonstrates that our workflow can significantly narrow down a large number of annotated genes in a QTL to a very small number of the most probable candidates, achieving approximately a 21-fold reduction. These candidate genes have potential implications for enhancing rice yield.","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":" ","pages":"843-857"},"PeriodicalIF":2.5,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142127426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0