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

AnimalQTLdb: a livestock QTL database tool set for positional QTL information mining and beyond

The Animal Quantitative Trait Loci (QTL) database (AnimalQTLdb) is designed to house all publicly available QTL data on livestock animal species from which researchers can easily locate and compare QTL within species. The database tools are also added to link the QTL data to other types of genomic information, such as radiation hybrid (RH) maps, finger printed contig (FPC) physical maps, linkage maps and comparative maps to the human genome, etc. Currently, this database contains data on 1287 pig, 630 cattle and 657 chicken QTL, which are dynamically linked to respective RH, FPC and human comparative maps. We plan to apply the tool to other animal species, and add more structural genome information for alignment, in an attempt to aid comparative structural genome studies ()

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 \u3e14 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

Chickspress: a resource for chicken gene expression

High-throughput sequencing and proteomics technologies are markedly increasing the amount of RNA and peptide data that are available to researchers, which are typically made publicly available via data repositories such as the NCBI Sequence Read Archive and proteome archives, respectively. These data sets contain valuable information about when and where gene products are expressed, but this information is not readily obtainable from archived data sets. Here we report Chickspress (http://geneatlas.arl.arizona.edu), the first publicly available gene expression resource for chicken tissues. Since there is no single source of chicken gene models, Chickspress incorporates both NCBI and Ensembl gene models and links these gene sets with experimental gene expression data and QTL information. By linking gene models from both NCBI and Ensembl gene prediction pipelines, researchers can, for the first time, easily compare gene models from each of these prediction workflows to available experimental data for these products. We use Chickspress data to show the differences between these gene annotation pipelines. Chickspress also provides rapid search, visualization and download capacity for chicken gene sets based upon tissue type, developmental stage and experiment type. This first Chickspress release contains 161 gene expression data sets, including expression of mRNAs, miRNAs, proteins and peptides. We provide several examples demonstrating how researchers may use this resource.National Institutes of Health [R24 GM079326]; US Department of Agriculture National Institute of Food and Agriculture [2011-67015-30332]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Genome-wide association study for femur-related traits in broilers.

Abstract: Due to the intense selection for heavier and faster growing broilers, metabolic disorders such as skeletal problems became a worldwide concern. Advances in genome-wide association study (GWAS) methodologies increased the possibility of elucidating the genetic architecture controlling bone integrity traits. Therefore, the aim of this study was to perform a GWAS to identify potential genetic markers and candidate genes associated with femur traits in a paternal broiler line developed by Embrapa. To this, three femur bone-related traits were evaluated in 1,433 chickens: dry matter (FDM), ash content (FAC) and breaking strength (FBS). Chickens were genotyped using the 600K Affymetrix® Axiom® HD panel. A total of 16 regions associated to FAC, being a significant SNP in the GGA19 (rs317696422) and 15 suggestive SNPs in the GGA1, GGA2, GGA3, GGA5, GGA8, GGA13, GGA19 and GGA24. For FDM, only one SNP (GGA1) was significantly associated and was located in the DSCAM gene. For the FBS, two suggestive regions (GGA12 and GGA15) were found and no QTLs were described for this trait in these regions. According to the results, new candidate genes and miRNAs related to ossification, such as TPVR2, gga-mir-146a and PCP4 were associated to important femur traits in the broiler line under study. Resumo:Devido à intensa seleção de frangos de corte mais pesados ​​e de crescimento mais rápido, distúrbios metabólicos, como problemas esqueléticos, tornaram-se uma preocupação mundial. Avanços em metodologias de estudo de associação genômica ampla (GWAS) aumentaram a possibilidade de elucidar a arquitetura genética controlando características de integridade óssea. Portanto, o objetivo deste estudo foi realizar um GWAS para identificar potenciais marcadores genéticos e genes candidatos associados às características do fêmur em uma linhagem de frangos de corte paterna desenvolvida pela Embrapa. Para isso, três características relacionadas ao osso do fêmur foram avaliadas em 1.433 aves: matéria seca (FDM), teor de cinzas (FAC) e resistência à ruptura (FBS). As galinhas foram genotipadas usando o painel 600y Affymetrix® Axiom® HD. Um total de 16 regiões associadas ao FAC, sendo um significativo SNP no GGA19 (rs317696422) e 15 SNPs sugestivos no GGA1, GGA2, GGA3, GGA5, GGA8, GGA13, GGA19 e GGA24. Para FDM, apenas um SNP (GGA1) foi significativamente associado e foi localizado no gene DSCAM. Para o FBS, duas regiões sugestivas (GGA12 e GGA15) foram encontradas e não foram descritos QTLs para essa característica nessas regiões. De acordo com os resultados, novos genes candidatos e miRNAs relacionados à ossificação, como TPVR2, gga-mir-146a e PCP4, foram associados a importantes características do fêmur na linha de frangos em estudo

Farm animal genomics and informatics: an update

Farm animal genomics is of interest to a wide audience of researchers because of the utility derived from understanding how genomics and proteomics function in various organisms. Applications such as xenotransplantation, increased livestock productivity, bioengineering new materials, products and even fabrics are several reasons for thriving farm animal genome activity. Currently mined in rapidly growing data warehouses, completed genomes of chicken, fish and cows are available but are largely stored in decentralized data repositories. In this paper, we provide an informatics primer on farm animal bioinformatics and genome project resources which drive attention to the most recent advances in the field. We hope to provide individuals in biotechnology and in the farming industry with information on resources and updates concerning farm animal genome projects

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

Genomic Characterization of Local Croatian Sheep Breeds-Effective Population Size, Inbreeding & Signatures of Selection

The Istrian (IS) and the Pag sheep (PS) are local Croatian breeds which provide significant income for the regional economy and have a cultural and traditional importance for the inhabitants. The aim of this study was to estimate some important population specific genetic parameters in IS (N = 1293) and PS (N = 2637) based on genome wide SNPs. Estimates of linkage disequilibrium effective population size (Ne) evidenced more genetic variability in PS (Ne = 838) compared to IS (Ne = 197), regardless of historical time (both recent and ancient genetic variability). The discrepancy in the recent genetic variability between these breeds was additionally confirmed by the estimates of genomic inbreeding (FROH), which was estimated to be notably higher in IS (FROH>2 = 0.062) than in PS (FROH>2 = 0.029). The average FROH2–4, FROH4–8, FROH8–16, and FROH>16 were 0.26, 1.65, 2.14, and 3.72 for IS and 0.22, 0.61, 0.75, and 1.58 for PS, thus evidencing a high contribution of recent inbreeding in the overall inbreeding. One ROH island with > 30% of SNP incidence in ROHs was detected in IS (OAR6; 34,253,440–38,238,124 bp) while there was no ROH islands detected in PS. Seven genes (CCSER1, HERC3, LCORL, NAP1L5, PKD2, PYURF, and SPP1) involved in growth, feed intake, milk production, immune responses, and resistance were associated with the found autozygosity. The results of this study represent the first comprehensive insight into genomic variability of these two Croatian local sheep breeds and will serve as a baseline for setting up the most promising strategy of genomic Optimum Contribution Selection

Research Progress in Genetic Control of Reproductive Performance in Chicken by High-Throughput Sequencing Technology

In chicken, egg production performance is a key trait to the production performance of chickens. Currently, low egg production performance is the major bottleneck, which restraints the development of indigenous chicken industry and blocks the cultivation of new chicken breeds. It has always been the focus of animal genetic breeding in detecting and studying the formation mechanism of complex traits. Due to the egg production is a complex trait determined by multiple genes, and regulated by heredity, environment, and the interaction between them, the mechanism regulating egg-laying performance is yet unknown due to its complexity. With the recent progresses of omics techniques, related researches on it have achieved considerable progress, making it possible to elucidate the molecular mechanism of egg-laying trait now. This article will provide an overall review about the recent research progress in genetic regulation of egg-laying performance in poultry through high-throughput sequencing technology