Engineered endolysin of Klebsiella pneumoniae phage is a potent and broad-spectrum bactericidal agent against "ESKAPEE" pathogens.

The rise of antimicrobial resistance in ESKAPEE pathogens poses significant clinical challenges, especially in polymicrobial infections. Bacteriophage-derived endolysins offer promise in combating this crisis, but face practical hurdles. Our study focuses on engineering endolysins from a Klebsiella pneumoniae phage, fusing them with ApoE23 and COG133 peptides. We assessed the resulting chimeric proteins' bactericidal activity against ESKAPEE pathogens in vitro. ApoE23-Kp84B (CHU-1) reduced over 3 log units of CFU for A. baumannii, E. faecalis, K. pneumoniae within 1 h, while COG133-Kp84B (CHU-2) showed significant efficacy against S. aureus. COG133-L1-Kp84B, with a GS linker insertion in CHU-2, exhibited outstanding bactericidal activity against E. cloacae and P. aeruginosa. Scanning electron microscopy revealed alterations in bacterial morphology after treatment with engineered endolysins. Notably, CHU-1 demonstrated promising anti-biofilm and anti-persister cell activity against A. baumannii and E. faecalis but had limited efficacy in a bacteremia mouse model of their coinfection. Our findings advance the field of endolysin engineering, facilitating the customization of these proteins to target specific bacterial pathogens. This approach holds promise for the development of personalized therapies tailored to combat ESKAPEE infections effectively.

Enhanced bovine genome annotation through integration of transcriptomics and epi-transcriptomics datasets facilitates genomic biology.

BACKGROUND: The accurate identification of the functional elements in the bovine genome is a fundamental requirement for high-quality analysis of data informing both genome biology and genomic selection. Functional annotation of the bovine genome was performed to identify a more complete catalog of transcript isoforms across bovine tissues. RESULTS: A total of 160,820 unique transcripts (50% protein coding) representing 34,882 unique genes (60% protein coding) were identified across tissues. Among them, 118,563 transcripts (73% of the total) were structurally validated by independent datasets (PacBio isoform sequencing data, Oxford Nanopore Technologies sequencing data, de novo assembled transcripts from RNA sequencing data) and comparison with Ensembl and NCBI gene sets. In addition, all transcripts were supported by extensive data from different technologies such as whole transcriptome termini site sequencing, RNA Annotation and Mapping of Promoters for the Analysis of Gene Expression, chromatin immunoprecipitation sequencing, and assay for transposase-accessible chromatin using sequencing. A large proportion of identified transcripts (69%) were unannotated, of which 86% were produced by annotated genes and 14% by unannotated genes. A median of two 5' untranslated regions were expressed per gene. Around 50% of protein-coding genes in each tissue were bifunctional and transcribed both coding and noncoding isoforms. Furthermore, we identified 3,744 genes that functioned as noncoding genes in fetal tissues but as protein-coding genes in adult tissues. Our new bovine genome annotation extended more than 11,000 annotated gene borders compared to Ensembl or NCBI annotations. The resulting bovine transcriptome was integrated with publicly available quantitative trait loci data to study tissue-tissue interconnection involved in different traits and construct the first bovine trait similarity network. CONCLUSIONS: These validated results show significant improvement over current bovine genome annotations.

Chinese expert consensus on imaging diagnosis of drug-resistant pulmonary tuberculosis.

Tuberculosis (TB) remains one of the major infectious diseases in the world with a high incidence rate. Drug-resistant tuberculosis (DR-TB) is a key and difficult challenge in the prevention and treatment of TB. Early, rapid, and accurate diagnosis of DR-TB is essential for selecting appropriate and personalized treatment and is an important means of reducing disease transmission and mortality. In recent years, imaging diagnosis of DR-TB has developed rapidly, but there is a lack of consistent understanding. To this end, the Infectious Disease Imaging Group, Infectious Disease Branch, Chinese Research Hospital Association; Infectious Diseases Group of Chinese Medical Association of Radiology; Digital Health Committee of China Association for the Promotion of Science and Technology Industrialization, and other organizations, formed a group of TB experts across China. The conglomerate then considered the Chinese and international diagnosis and treatment status of DR-TB, China's clinical practice, and evidence-based medicine on the methodological requirements of guidelines and standards. After repeated discussion, the expert consensus of imaging diagnosis of DR-PB was proposed. This consensus includes clinical diagnosis and classification of DR-TB, selection of etiology and imaging examination [mainly X-ray and computed tomography (CT)], imaging manifestations, diagnosis, and differential diagnosis. This expert consensus is expected to improve the understanding of the imaging changes of DR-TB, as a starting point for timely detection of suspected DR-TB patients, and can effectively improve the efficiency of clinical diagnosis and achieve the purpose of early diagnosis and treatment of DR-TB.

A combinatorial approach implementing new database structures to facilitate practical data curation management of QTL, association, correlation and heritability data on trait variants.

A precise description of traits is essential in genetics and genomics studies to facilitate comparative genetics and meta-analyses. It is an ongoing challenge in research and production environments to unambiguously and consistently compare traits of interest from data collected under various conditions. Despite previous efforts to standardize trait nomenclature, it remains a challenge to fully and accurately capture trait nomenclature granularity in a way that ensures long-term data sustainability in terms of the data curation processes, data management logistics and the ability to make meaningful comparisons across studies. In the Animal Quantitative Trait Loci Database and the Animal Trait Correlation Database, we have recently introduced a new method to extend livestock trait ontologies by using trait modifiers and qualifiers to define traits that differ slightly in how they are measured, examined or combined with other traits or factors. Here, we describe the implementation of a system in which the extended trait data, with modifiers, are managed at the experiment level as 'trait variants'. This has helped us to streamline the management and curation of such trait information in our database environment. Database URL  https://www.animalgenome.org/PGNET/.

Analysis of clinical characteristics of 66 pediatric patients with B.1.617.2 (Delta) variant of COVID-19.

BACKGROUND: The aim of this study was to analyze the clinical characteristics of 66 pediatric patients with B.1.617.2 (Delta) variant of coronavirus disease 2019 (COVID-19). METHODS: Sixty-six pediatric patients with B.1.617.2 (Delta) variant of COVID-19 admitted to the hospital from July to August 2021 were classified into mild (n = 41) and moderate groups (n = 25). Clinical characteristics, laboratory data and dynamic trends in different time periods were analyzed retrospectively. RESULTS: There were no statistically significant differences in age, gender ratios and clinical symptoms between the mild group and the moderate group. All the patients in the moderate group had clusters of onsets, and the incubation period was shorter than that of the mild group. Within 24 hours of admission, the levels of erythrocyte sedimentation rate, cardiac troponin I, D-dimer in the moderate group were higher than that in the mild group (P < 0.05). The titers of immunoglobulin (Ig) G and IgM antibodies gradually increased after disease onset. Thirty-five (53.03%) children were tested positive for antibodies in 4-12 days. IgG increased gradually, while IgM decreased obviously in about 15 days after disease onset. The cycle threshold values of open reading frame 1ab and nucleocapsid protein gene in the severe acute respiratory syndrome coronavirus 2 genomes increased gradually on the 3rd, 6th, 9th, and 12th days after disease onset, compared with those in day 0. CONCLUSIONS: The symptoms of children with B.1.617.2 (Delta) variant of COVID-19 were mild. The description and analysis of the clinical characteristics and laboratory data can help medical staff to evaluate the condition of children with COVID-19 and to accumulate more clinical experience.

Chest CT features of children infected by B.1.617.2 (Delta) variant of COVID-19.

BACKGROUND: This study aimed to explore the imaging characteristics, diversity and changing trend in CT scans of pediatric patients infected with Delta-variant strain by studying imaging features of children infected with Delta and comparing the results to those of children with original COVID-19. METHODS: A retrospective, comparative analysis of initial chest CT manifestations between 63 pediatric patients infected with Delta variant in 2021 and 23 pediatric patients with COVID-19 in 2020 was conducted. Corresponding imaging features were analyzed. In addition, the changing trend in imaging features of COVID-19 Delta-variant cases were explored by evaluating the initial and follow-up CT scans. RESULTS: Among 63 children with Delta-variant COVID-19 in 2021, 34 (53.9%) showed positive chest CT presentation; and their CT score (1.10 ± 1.41) was significantly lower than that in 2020 (2.56 ± 3.5) (P = 0.0073). Lesion distribution: lung lesions of Delta cases appear mainly in the lower lungs on both sides. Most children had single lobe involvement (18 cases, 52.9%), 14 (41.2%) in the right lung alone, and 14 (41.2%) in both lungs. A majority of Delta cases displayed initially ground glass (23 cases, 67.6%) and nodular shadows (13 cases, 38.2%) in the first CT scan, with few extrapulmonary manifestations. The 34 children with abnormal chest CT for the first time have a total of 92 chest CT examinations. These children showed a statistically significant difference between the 0-3 day group and the 4-7 day group (P = 0.0392) and a significant difference between the 4-7 day group and the more than 8 days group (P = 0.0003). CONCLUSIONS: The early manifestations of COVID-19 in children with abnormal imaging are mostly small subpleural nodular ground glass opacity. The changes on the Delta-variant COVID-19 chest CT were milder than the original strain. The lesions reached a peak on CT in 4-7 days and quickly improved and absorbed after a week. Dynamic CT re-examination can achieve a good prognosis.

Bringing the Animal QTLdb and CorrDB into the future: meeting new challenges and providing updated services.

The Animal QTLdb (https://www.animalgenome.org/QTLdb) and CorrDB (https://www.animalgenome.org/CorrDB) are unique resources for livestock animal genetics and genomics research which have been used extensively by the international livestock genome research community. This is largely due to the active development of the databases over the years to keep up with the rapid advancement of genome sciences. The ongoing development has ensured that these databases provide researchers not only with continually updated data but also with new web tools to disseminate the data. Through our continued efforts, the databases have evolved from the original Pig QTLdb for cross-experiment QTL data comparisons to an Animal QTLdb hosting 220 401 QTL, SNP association and eQTL data linking phenotype to genotype for 2210 traits. In addition, there are 23 552 correlations for 866 traits and 4273 heritability data on 1069 traits in CorrDB. All these data were curated from 3157 publications that cover seven livestock species. Along with the continued data curation, new species, additional genome builds, and new functions and features have been built into the databases as well. Standardized procedures to support data mapping on multiple species/genome builds and the ability to browse data based on linked ontology terms are highlights of the recent developments.

Building a livestock genetic and genomic information knowledgebase through integrative developments of Animal QTLdb and CorrDB.

Successful development of biological databases requires accommodation of the burgeoning amounts of data from high-throughput genomics pipelines. As the volume of curated data in Animal QTLdb (https://www.animalgenome.org/QTLdb) increases exponentially, the resulting challenges must be met with rapid infrastructure development to effectively accommodate abundant data curation and make metadata analysis more powerful. The development of Animal QTLdb and CorrDB for the past 15 years has provided valuable tools for researchers to utilize a wealth of phenotype/genotype data to study the genetic architecture of livestock traits. We have focused our efforts on data curation, improved data quality maintenance, new tool developments, and database co-developments, in order to provide convenient platforms for users to query and analyze data. The database currently has 158 499 QTL/associations, 10 482 correlations and 1977 heritability data as a result of an average 32% data increase per year. In addition, we have made >14 functional improvements or new tool implementations since our last report. Our ultimate goals of database development are to provide infrastructure for data collection, curation, and annotation, and more importantly, to support innovated data structure for new types of data mining, data reanalysis, and networked genetic analysis that lead to the generation of new knowledge.

Helicase lymphoid-specifics and selenoprotein P1 are potential candidate genes in the progression and prognosis of lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (AD) remains one of the most common cancers. Early diagnosis of AD improves therapeutic strategy and lengthens survival time. The objective of this study is to identify hub genes influencing the process of lung AD. METHODS: The microarray profiles of GSE43458 were extracted from the Gene Expression Omnibus (GEO) database to screen potential targets during lung AD. Differentially expressed genes (DEGs) between AD patients and normal controls were detected. Then gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis were performed. Moreover, the major modules of protein-protein interaction (PPI) network of those DEGs were performed using the MCODE plug of the Cytoscape. The hub genes were validated in the Oncomine and GEPIA datasets. Additionally, the prognostic values of hub genes were evaluated in Kaplan Meier plotter and GEPIA databases. RESULTS: Totally, 859 DEGs were identified, including 278 up-regulated and 581 down-regulated genes. Functional annotation suggested those DEGs were related to cell adhesion, migration and motility. Besides, helicase lymphoid-specifics (HELLs) and selenoprotein P1 (SEPP1) were regarded as hub genes in AD. Then, the upregulation of HELLs and downregulation of SEPP1 were validated in the Oncomine and GEPIA databases, respectively. Moreover, Kaplan-Meier and GEPIA databases also suggested both HELLs and SEPP1 could affect the prognosis of lung AD patients. CONCLUSIONS: Our study demonstrated HELLs and SEPP1 were hub genes contributing to the progress of lung AD. They could be potential target genes for the diagnosis and therapy of lung AD.

AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture.

The future of agricultural research depends on data. The sheer volume of agricultural biological data being produced today makes excellent data management essential. Governmental agencies, publishers and science funders require data management plans for publicly funded research. Furthermore, the value of data increases exponentially when they are properly stored, described, integrated and shared, so that they can be easily utilized in future analyses. AgBioData (https://www.agbiodata.org) is a consortium of people working at agricultural biological databases, data archives and knowledgbases who strive to identify common issues in database development, curation and management, with the goal of creating database products that are more Findable, Accessible, Interoperable and Reusable. We strive to promote authentic, detailed, accurate and explicit communication between all parties involved in scientific data. As a step toward this goal, we present the current state of biocuration, ontologies, metadata and persistence, database platforms, programmatic (machine) access to data, communication and sustainability with regard to data curation. Each section describes challenges and opportunities for these topics, along with recommendations and best practices.

Large-scale gene co-expression network as a source of functional annotation for cattle genes.

BACKGROUND: Genome sequencing and subsequent gene annotation of genomes has led to the elucidation of many genes, but in vertebrates the actual number of protein coding genes are very consistent across species (~20,000). Seven years after sequencing the cattle genome, there are still genes that have limited annotation and the function of many genes are still not understood, or partly understood at best. Based on the assumption that genes with similar patterns of expression across a vast array of tissues and experimental conditions are likely to encode proteins with related functions or participate within a given pathway, we constructed a genome-wide Cattle Gene Co-expression Network (CGCN) using 72 microarray datasets that contained a total of 1470 Affymetrix Genechip Bovine Genome Arrays that were retrieved from either NCBI GEO or EBI ArrayExpress. RESULTS: The total of 16,607 probe sets, which represented 11,397 genes, with unique Entrez ID were consolidated into 32 co-expression modules that contained between 29 and 2569 probe sets. All of the identified modules showed strong functional enrichment for gene ontology (GO) terms and Reactome pathways. For example, modules with important biological functions such as response to virus, response to bacteria, energy metabolism, cell signaling and cell cycle have been identified. Moreover, gene co-expression networks using "guilt-by-association" principle have been used to predict the potential function of 132 genes with no functional annotation. Four unknown Hub genes were identified in modules highly enriched for GO terms related to leukocyte activation (LOC509513), RNA processing (LOC100848208), nucleic acid metabolic process (LOC100850151) and organic-acid metabolic process (MGC137211). Such highly connected genes should be investigated more closely as they likely to have key regulatory roles. CONCLUSIONS: We have demonstrated that the CGCN and its corresponding regulons provides rich information for experimental biologists to design experiments, interpret experimental results, and develop novel hypothesis on gene function in this poorly annotated genome. The network is publicly accessible at http://www.animalgenome.org/cgi-bin/host/reecylab/d .

Developmental progress and current status of the Animal QTLdb.

The Animal QTL Database (QTLdb; http://www.animalgenome.org/QTLdb) has undergone dramatic growth in recent years in terms of new data curated, data downloads and new functions and tools. We have focused our development efforts to cope with challenges arising from rapid growth of newly published data and end users' data demands, and to optimize data retrieval and analysis to facilitate users' research. Evidenced by the 27 releases in the past 11 years, the growth of the QTLdb has been phenomenal. Here we report our recent progress which is highlighted by addition of one new species, four new data types, four new user tools, a new API tool set, numerous new functions and capabilities added to the curator tool set, expansion of our data alliance partners and more than 20 other improvements. In this paper we present a summary of our progress to date and an outlook regarding future directions.

The Vertebrate Trait Ontology: a controlled vocabulary for the annotation of trait data across species.

BACKGROUND: The use of ontologies to standardize biological data and facilitate comparisons among datasets has steadily grown as the complexity and amount of available data have increased. Despite the numerous ontologies available, one area currently lacking a robust ontology is the description of vertebrate traits. A trait is defined as any measurable or observable characteristic pertaining to an organism or any of its substructures. While there are several ontologies to describe entities and processes in phenotypes, diseases, and clinical measurements, one has not been developed for vertebrate traits; the Vertebrate Trait Ontology (VT) was created to fill this void. DESCRIPTION: Significant inconsistencies in trait nomenclature exist in the literature, and additional difficulties arise when trait data are compared across species. The VT is a unified trait vocabulary created to aid in the transfer of data within and between species and to facilitate investigation of the genetic basis of traits. Trait information provides a valuable link between the measurements that are used to assess the trait, the phenotypes related to the traits, and the diseases associated with one or more phenotypes. Because multiple clinical and morphological measurements are often used to assess a single trait, and a single measurement can be used to assess multiple physiological processes, providing investigators with standardized annotations for trait data will allow them to investigate connections among these data types. CONCLUSIONS: The annotation of genomic data with ontology terms provides unique opportunities for data mining and analysis. Links between data in disparate databases can be identified and explored, a strategy that is particularly useful for cross-species comparisons or in situations involving inconsistent terminology. The VT provides a common basis for the description of traits in multiple vertebrate species. It is being used in the Rat Genome Database and Animal QTL Database for annotation of QTL data for rat, cattle, chicken, swine, sheep, and rainbow trout, and in the Mouse Phenome Database to annotate strain characterization data. In these databases, data are also cross-referenced to applicable terms from other ontologies, providing additional avenues for data mining and analysis. The ontology is available at http://bioportal.bioontology.org/ontologies/50138.

Animal QTLdb: an improved database tool for livestock animal QTL/association data dissemination in the post-genome era.

The Animal QTL database (QTLdb; http://www.animalgenome.org/QTLdb) is designed to house all publicly available QTL and single-nucleotide polymorphism/gene association data on livestock animal species. An earlier version was published in the Nucleic Acids Research Database issue in 2007. Since then, we have continued our efforts to develop new and improved database tools to allow more data types, parameters and functions. Our efforts have transformed the Animal QTLdb into a tool that actively serves the research community as a quality data repository and more importantly, a provider of easily accessible tools and functions to disseminate QTL and gene association information. The QTLdb has been heavily used by the livestock genomics community since its first public release in 2004. To date, there are 5920 cattle, 3442 chicken, 7451 pigs, 753 sheep and 88 rainbow trout data points in the database, and at least 290 publications that cite use of the database. The rapid advancement in genomic studies of cattle, chicken, pigs, sheep and other livestock animals has presented us with challenges, as well as opportunities for the QTLdb to meet the evolving needs of the research community. Here, we report our progress over the recent years and highlight new functions and services available to the general public.

[Effect of microRNA on proliferation caused by mutant HBx in human hepatocytes].

To study the effect of micro (mi)RNA on cellular proliferation induced by hepatitis B x protein, HBx, in human liver cells and to investigate the underlying molecular mechanism of this cancer-related effect. The human L02 hepatocyte cell line was stably transfected with HBx (L02/HBx) or an HBx mutant (L02/HBx-d382) that induces higher levels of cellular proliferation. The differential miRNA expression profiles were determined by microarray analysis and confirmed by real-time PCR. Two miRNAs, miR-338-3p and miR-551b, that were found to be significantly down-regulated in the L02/HBx-d382 cells were selected for further study and transfected individually into cells using the lipofectamine procedure. The cell survival rate was analyzed by MTT assay, and cell cycles were assessed by flow cytometry. Expressions of cyclinD1, cyclinG1, and E2F1 were assessed by real-time PCR and Western blotting. Compared with the microarray miRNA profile of L02/pcDNA3.0 cells, six miRNAs were up-regulated and five miRNAs were down-regulated in the L02/HBx-d382 cells, while four miRNAs were up-regulated and 12 were down-regulated in the L02/HBx cells. The microarray results were consistent with real-time PCR results. Transfection of miR-338-3p and miR-551b significantly inhibited the cell survival rates (P less than 0.001) and induced G0/G1 phase cycle arrest. According to MTT results: for L02/HBx-d382 cells, compared with lipofectamine or non-transfected (NC) controls, the t value of miR-338-3p was 10.402, 9.133 and the t value of miR-551b was 8.763, 7.403; for L02/HBx cells, compared with lipofectamine or NC controls, the t value of miR-338-3p was 9.105, 8.074 and the t value of miR-551b was 7.673, 7.52. According to flow cytometry results: for L02/HBx-d382 cells, compared with lipofectamine or NC controls, the t value of miR-338-3p was 12.173, 11.107 and the t value of miR-551b was 15.364, 13.377; for L02/HBx cells, compared with lipofectamine or NC controls, the t value of miR-338-3p was 15.416, 13.378, and the t value of miR-551b was 13.276, 13.109. The protein levels of cyclinD1, cyclinG1, and E2F1 were significantly reduced by both miR-338-3p and miR-551b ( P less than 0.001). For L02/HBx-d382 cells, compared with lipofectamine or NC controls: E2F1 had t = 11.132, 10.031 and 12.017, 10.973, respectively; cyclinD1 had t = 15.654, 15.013 and 15.447, 14.733, respectively; cyclinG1 had t = 8.017, 7.661 and 7.402, 7.417, respectively. For L02/HBx cells, compared with lipofectamine or NC controls: E2F1 had t = 14.244, 13.331 and 15.022, 14.468, respectively; cyclinD1 had t = 8.695, 8.137 and 7.877, 7.503, respectively; cyclinG1 had t = 7.73, 7.471 and 7.596, 7.41, respectively. In contrast, the mRNA levels for E2F1, cyclinD1, and cylcinG1 showed no significant differences between the miRNA transfected cells and controls. Wild-type HBx and the high proliferation-inducing mutant HBx can influence the miRNA expression profile of L02 cells. HBx down-regulates miR-338-3p and miR-551b in L02 cells, and the high proliferation-inducing mutant has a more robust effect. The mechanism of miR-338-3p- or miR-551b-mediated cell growth inhibition appears to be related to the direct modulation of cyclinD1, cyclinG1, and E2F1.

Prediction of altered 3'- UTR miRNA-binding sites from RNA-Seq data: the swine leukocyte antigen complex (SLA) as a model region.

THE SLA (swine leukocyte antigen, MHC: SLA) genes are the most important determinants of immune, infectious disease and vaccine response in pigs; several genetic associations with immunity and swine production traits have been reported. However, most of the current knowledge on SLA is limited to gene coding regions. MicroRNAs (miRNAs) are small molecules that post-transcriptionally regulate the expression of a large number of protein-coding genes in metazoans, and are suggested to play important roles in fine-tuning immune mechanisms and disease responses. Polymorphisms in either miRNAs or their gene targets may have a significant impact on gene expression by abolishing, weakening or creating miRNA target sites, possibly leading to phenotypic variation. We explored the impact of variants in the 3'-UTR miRNA target sites of genes within the whole SLA region. The combined predictions by TargetScan, PACMIT and TargetSpy, based on different biological parameters, empowered the identification of miRNA target sites and the discovery of polymorphic miRNA target sites (poly-miRTSs). Predictions for three SLA genes characterized by a different range of sequence variation provided proof of principle for the analysis of poly-miRTSs from a total of 144 M RNA-Seq reads collected from different porcine tissues. Twenty-four novel SNPs were predicted to affect miRNA-binding sites in 19 genes of the SLA region. Seven of these genes (SLA-1, SLA-6, SLA-DQA, SLA-DQB1, SLA-DOA, SLA-DOB and TAP1) are linked to antigen processing and presentation functions, which is reminiscent of associations with disease traits reported for altered miRNA binding to MHC genes in humans. An inverse correlation in expression levels was demonstrated between miRNAs and co-expressed SLA targets by exploiting a published dataset (RNA-Seq and small RNA-Seq) of three porcine tissues. Our results support the resource value of RNA-Seq collections to identify SNPs that may lead to altered miRNA regulation patterns.

Design database for quantitative trait loci (QTL) data warehouse, data mining, and meta-analysis.

A database can be used to warehouse quantitative trait loci (QTL) data from multiple sources for comparison, genomic data mining, and meta-analysis. A robust database design involves sound data structure logistics, meaningful data transformations, normalization, and proper user interface designs. This chapter starts with a brief review of relational database basics and concentrates on issues associated with curation of QTL data into a relational database, with emphasis on the principles of data normalization and structure optimization. In addition, some simple examples of QTL data mining and meta-analysis are included. These examples are provided to help readers better understand the potential and importance of sound database design.

Meta-analysis of QTL mapping experiments.

Meta-analysis is an important tool for integrating information from multiple quantitative trait loci (QTLs) studies. Pooling of results from several studies allows greater statistical power for QTL detection and more precise estimation of their genetic effects. Hence, a meta-analysis can yield conclusions that are stronger than those of individual studies and can give greater insight into the genetic architecture of complex traits. In this chapter, we present basic theories and methods for meta-analysis of QTL mapping experiments. The meta-analytic procedures are described in a general context. The statistical methods cover both parametric and nonparametric statistical models. Finally, we illustrate the features of these statistical methods using simulated and real datasets.