A framework for detecting noncoding rare variant associations of large-scale whole-genome sequencing studies

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare variants' (RVs) associations with complex human traits. Variant set analysis is a powerful approach to study RV association, and a key component of it is constructing RV sets for analysis. However, existing methods have limited ability to define analysis units in the noncoding genome. Furthermore, there is a lack of robust pipelines for comprehensive and scalable noncoding RV association analysis. Here we propose a computationally-efficient noncoding RV association-detection framework that uses STAAR (variant-set test for association using annotation information) to group noncoding variants in gene-centric analysis based on functional categories. We also propose SCANG (scan the genome)-STAAR, which uses dynamic window sizes and incorporates multiple functional annotations, in a non-gene-centric analysis. We furthermore develop STAARpipeline to perform flexible noncoding RV association analysis, including gene-centric analysis as well as fixed-window-based and dynamic-window-based non-gene-centric analysis. We apply STAARpipeline to identify noncoding RV sets associated with four quantitative lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several noncoding RV associations in an additional 9,123 TOPMed samples.

MeiosisOnline: A Manually Curated Database for Tracking and Predicting Genes Associated With Meiosis

Meiosis, an essential step in gametogenesis, is the key event in sexually reproducing organisms. Thousands of genes have been reported to be involved in meiosis. Therefore, a specialist database is much needed for scientists to know about the function of these genes quickly and to search for genes with potential roles in meiosis. Here, we developed “MeiosisOnline,” a publicly accessible, comprehensive database of known functional genes and potential candidates in meiosis (https://mcg.ustc.edu.cn/bsc/meiosis/index.html). A total of 2,052 meiotic genes were manually curated from literature resource and were classified into different categories. Annotation information was provided for both meiotic genes and predicted candidates, including basic information, function, protein–protein interaction (PPI), and expression data. On the other hand, 165 mouse genes were predicted as potential candidates in meiosis using the “Greed AUC Stepwise” algorithm. Thus, MeiosisOnline provides the most updated and detailed information of experimental verified and predicted genes in meiosis. Furthermore, the searching tools and friendly interface of MeiosisOnline will greatly help researchers in studying meiosis in an easy and efficient way.

Physiological and transcriptome analysis elucidates the metabolic mechanism of versatile Porphyridium purpureum under nitrogen deprivation for exopolysaccharides accumulation

Porphyridium purpureum is a mesophilic, unicellular red alga rich in phycoerythrin, sulfate polysaccharides, and polyunsaturated fatty acids. Nitrogen deficiency inhibited the growth of P. purpureum and resulted in yellowing of the cells and thickening of the extracellular viscousness sheath. Under nitrogen stress, the contents of total lipids and exopolysaccharides in P. purpureum were increased by 65.2% and 188.0%, respectively. We demonstrate that the immediate response of P. purpureum to nitrogen deficiency is mediated by carbon flow to polysaccharide synthesis, while the synthesis of lipids is enhanced as a permanent energy storage substance at the later stage. Based on transcriptome annotation information, we elucidate the synthesis pathway of polysaccharides from P. purpureum from the perspective of glycosyl-donor interconversion, and demonstrate that the n-6 pathway is the main synthesis pathway of polyunsaturated fatty acids. This study not only provides a production strategy for polysaccharides and fatty acids by single-celled marine red algae P. purpureum, but also provides targets for further genetic modification.

Transcriptome analysis reveals genes potentially related to high fiber strength in a Gossypium hirsutum line IL9 with Gossypium mustelinum introgression

Cotton (Gossypium L.) is the most important fiber crop worldwide. Here, transcriptome analysis was conducted on developing fibers of a G. mustelinum introgression line, IL9, and its recurrent parent, PD94042, at 17 and 21 days post-anthesis (dpa). Differentially expressed genes (DEGs) of PD94042 and IL9 were identified. Gene Ontology (GO) enrichment analysis showed that the annotated DEGs were rich in two main biological processes and two main molecular functions. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis likewise showed that the annotated DEGs were mainly enriched in metabolic pathways and biosynthesis of secondary metabolites. In total, 52 DEGs were selected as candidate genes based on comparison of the DEGs and GO function annotation information. Quantitative real-time PCR (RT-qPCR) analysis results for 12 randomly selected DEGs were consistent with transcriptome analysis. SNP identification based on G. mustelinum chromatin segment introgression showed that 394 SNPs were identified in 268 DEGs, and two genes with known functions were identified within fiber strength quantitative trait loci (QTL) regions or near the confidence intervals. We identified 52 key genes potentially related to high fiber strength in a G. mustelinum introgression line and provided significant insights into the study of cotton fiber quality improvement.

New Genotype of Yersinia pestis Found in Live Rodents in Yunnan Province, China

Yunnan Province, China is thought to be the original source of biovar Orientalis of Yersinia pestis, the causative agent of the third plague pandemic that has spread globally since the end of the 19th century. Although encompassing a large area of natural plague foci, Y. pestis strains have rarely been found in live rodents during surveillance in Yunnan, and most isolates are from rodent corpses and their fleas. In 2017, 10 Y. pestis strains were isolated from seven live rodents and three fleas in Heqing County of Yunnan. These strains were supposed to have low virulence to local rodents Eothenomys miletus and Apodemus chevrieri because the rodents were healthy and no dead animals were found in surrounding areas, as had occurred in previous epizootic disease. We performed microscopic and biochemical examinations of the isolates, and compared their whole-genome sequences and transcriptome with those of 10 high virulence Y. pestis strains that were isolated from nine rodents and one parasitic flea in adjacent city (Lijiang). We analyzed the phenotypic, genomic, and transcriptomic characteristics of live rodent isolates. The isolates formed a previously undefined monophyletic branch of Y. pestis that was named 1.IN5. Six SNPs, two indels, and one copy number variation were detected between live rodent isolates and the high virulence neighbors. No obvious functional consequence of these variations was found according to the known annotation information. Among genes which expression differential in the live rodent isolates compared to their high virulent neighbors, we found five iron transfer related ones that were significant up-regulated (| log2 (FC) | > 1, p.adjust < 0.05), indicating these genes may be related to the low-virulence phenotype. The novel genotype of Y. pestis reported here provides further insights into the evolution and spread of plague as well as clues that may help to decipher the virulence mechanism of this notorious pathogen.

Skeletal Muscle Transcriptome Analysis of Hanzhong Ma Duck at Different Growth Stages Using RNA-Seq

As one of the most important poultry worldwide, ducks (Anas platyrhynchos) are raised mainly for meat and egg products, and muscle development in ducks is important for meat production. Therefore, an investigation of gene expression in duck skeletal muscle would significantly contribute to our understanding of muscle development. In this study, twenty-four cDNA libraries were constructed from breast and leg muscles of Hanzhong Ma ducks at day 17, 21, 27 of the embryo and postnatal at 6-month-old. High-throughput sequencing and bioinformatics were used to determine the abundances and characteristics of transcripts. A total of 632,172,628 (average 52,681,052) and 637,213,938 (average 53,101,162) reads were obtained from the sequencing data of breast and leg muscles, respectively. Over 71.63% and 77.36% of the reads could be mapped to the Anas platyrhynchos genome. In the skeletal muscle of Hanzhong duck, intron variant (INTRON), synonymous variant (SYNONYMOUS_CODING), and prime 3′ UTR variant (UTR_3_PRIME) were the main single nucleotide polymorphisms (SNP) annotation information, and “INTRON”, “UTR_3_PRIME”, and downstream-gene variant (DOWNSTREAM) were the main insertion-deletion (InDel) annotation information. The predicted number of alternative splicing (AS) in all samples were mainly alternative 5′ first exon (transcription start site)-the first exon splicing (TSS) and alternative 3′ last exon (transcription terminal site)-the last exon splicing (TTS). Besides, there were 292 to 2801 annotated differentially expressed genes (DEGs) in breast muscle and 304 to 1950 annotated DEGs in leg muscle from different databases. It is worth noting that 75 DEGs in breast muscle and 49 DEGs in leg muscle were co-expressed at all developmental points of comparison, respectively. The RNA-Seq data were confirmed to be reliable by qPCR. The identified DEGs, such as CREBL2, RHEB, GDF6, SHISA2, MYLK2, ACTN3, RYR3, and STMN1, were specially highlighted, indicating their strong associations with muscle development in the Hanzhong Ma duck. KEGG pathway analysis suggested that regulation of actin cytoskeleton, oxidative phosphorylation, and focal adhesion were involved in the development of skeletal muscle. The findings from this study can contribute to future investigations of the growth and development mechanism in duck skeletal muscle.

Improvement, identification, and target prediction for miRNAs in the porcine genome by using massive, public high-throughput sequencing data

Despite the broad variety of available microRNA (miRNA) research tools and methods, their application to the identification, annotation, and target prediction of miRNAs in nonmodel organisms is still limited. In this study, we collected nearly all public sRNA-seq data to improve the annotation for known miRNAs and identify novel miRNAs that have not been annotated in pigs (Sus scrofa). We newly annotated 210 mature sequences in known miRNAs and found that 43 of the known miRNA precursors were problematic due to redundant/missing annotations or incorrect sequences. We also predicted 811 novel miRNAs with high confidence, which was twice the current number of known miRNAs for pigs in miRBase. In addition, we proposed a correlation-based strategy to predict target genes for miRNAs by using a large amount of sRNA-seq and RNA-seq data. We found that the correlation-based strategy provided additional evidence of expression compared with traditional target prediction methods. The correlation-based strategy also identified the regulatory pairs that were controlled by nonbinding sites with a particular pattern, which provided abundant complementarity for studying the mechanism of miRNAs that regulate gene expression. In summary, our study improved the annotation of known miRNAs, identified a large number of novel miRNAs, and predicted target genes for all pig miRNAs by using massive public data. This large data-based strategy is also applicable for other nonmodel organisms with incomplete annotation information.

Comparative proteomic analysis of the sweetpotato provides insights into response mechanisms to Fusarium oxysporum f. sp. batatas

The Fusarium wilt disease caused by Fusarium oxysporum f. sp. batatas (Fob) is one of the devastating diseases of sweetpotato. However, the molecular mechanisms of sweetpotato response to Fob is poorly understood. In the present study, comparative quantitative proteomic analysis was conducted to investigate the defense mechanisms involved. Two sweetpotato cultivars with differential Fob infection responses were inoculated with Fob spore suspensions and quantitatively analyzed by Tandem Mass Tags (TMT). 2267 proteins were identified and 1897 of them were quantified. There were 817 proteins with quantitative ratios of 1.2-fold change between Fob-inoculated and mock-treated samples. Further, nine differentially expressed proteins were validated by Parallel Reaction Monitoring (PRM). According to Gene Ontology (GO) annotation information, the proteins functioned in molecular metabolism, cellular component formation, and biological processes. Interestingly, the results showed that sweetpotato resistant response to Fob infection included many proteins associated with signaling transduction, plant resistance, chitinase and subtilisin-like protease. The functions and possible roles of those proteins were discussed. The results provides first insight into molecular mechanisms involved in sweetpotato defense responses to Fob.

Gramene 2021: harnessing the power of comparative genomics and pathways for plant research

Gramene (http://www.gramene.org), a knowledgebase founded on comparative functional analyses of genomic and pathway data for model plants and major crops, supports agricultural researchers worldwide. The resource is committed to open access and reproducible science based on the FAIR data principles. Since the last NAR update, we made nine releases; doubled the genome portal's content; expanded curated genes, pathways and expression sets; and implemented the Domain Informational Vocabulary Extraction (DIVE) algorithm for extracting gene function information from publications. The current release, #63 (October 2020), hosts 93 reference genomes—over 3.9 million genes in 122 947 families with orthologous and paralogous classifications. Plant Reactome portrays pathway networks using a combination of manual biocuration in rice (320 reference pathways) and orthology-based projections to 106 species. The Reactome platform facilitates comparison between reference and projected pathways, gene expression analyses and overlays of gene–gene interactions. Gramene integrates ontology-based protein structure–function annotation; information on genetic, epigenetic, expression, and phenotypic diversity; and gene functional annotations extracted from plant-focused journals using DIVE. We train plant researchers in biocuration of genes and pathways; host curated maize gene structures as tracks in the maize genome browser; and integrate curated rice genes and pathways in the Plant Reactome.

Recommendation Based on Java Code Analysis and Search

How to improve the efficiency and quality of software development is an ongoing concern in the field of software engineering. As a useful auxiliary function, code recommendation is embedded in almost all integrated development environments. There has been increasing interest and research in the area of code recommendation in recent years due to its convenience for project development. Existing research has made a lot of contributions to this field, but there are still many issues that need further study. One of the key points is the low success rate of recommendation. Focusing on this problem, this paper proposes a method to recommend Java source code after parsing massive amounts of source code information. We propose a new source code analysis algorithm for the scraped source code data. A source file is parsed into classes, methods, and attributes as recommendation objects. At the same time, the annotation information is bound to the annotated objects. Finally, the parsed information is indexed at the project, class, and method levels for code recommendations in a hierarchical recommendation manner. A code recommendation system is implemented by combining this with full-text retrieval technology for class library, class, and method level recommendation. The experimental results show that the method proposed in this paper has better performance in recommendation accuracy than existing code recommendation engines.