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Whole-genome resequencing, alignment, and annotation analyses were undertaken for ten sires representing Gyr, Girolando, and Holstein cattle breeds to detect and make publicly available genome-wide single nucleotide variations (SNVs) and insertions/deletions (InDels). A total of approximately 3.5 billion reads from an Illumina HiSeq 2000 sequencer generated for each animal 10.7 to 16.4-fold genome coverage. Sequencing reads were mapped to the UMD 3.1 bovine genome assembly using the Burrows-Wheeler Aligner tool (v. 0.7.10-r789) with default parameters. Picard tools (v. 1.54) were used to eliminate PCR duplicates, and the variant calling was conducted with FreeBayes. The resulting variant lists obtained for each animal were filtered by vcffilter in order to remove variants with quality scores lower than 30 or coverage lower than 7. A total of 23,743,970 SNVs and 3,171,711 InDels were detected in the samples, of which approximately 2,224,013 SNVs and 798,8910 [Editor: Please check number.] InDels were novel. The high number of genetic variants identified for each animal within the same breed shows the importance of resequencing to identify novel variants for monitoring genetic diversity in the cattle breeds and for developing strategies to prevent some eventual loss of genetic variability. The submission of these genetic variants to the dbSNP database significantly increased the number of known variants, particularly for the indicine genome. The concordance rate between genotypes obtained using the Bovine HD BeadChip array and the same variants identified by sequencing was about 99.05%. The annotation of variants identified numerous nonsynonymous SNVs and frameshift InDels, which could affect phenotypic variation. Functional enrichment analysis was performed by the David (v. 6.8) tool and revealed that variants in the olfactory transduction pathway were overrepresented in all three cattle breeds, while the ECM-receptor interaction pathway was overrepresented only in the Girolando breed, the ABC transporters pathway was overrepresented only in the Holstein breed, and the metabolic pathways were overrepresented only in the Gyr breed. Therefore, the genetic variants discovered in this study provide a rich resource to help identify potential genomic markers and their associated molecular mechanisms that impact economically important traits for Gyr, Girolando, and Holstein breeding programs. [ABSTRACT FROM AUTHOR]

The aim of this study was to detect, by whole-genome resequencing, SNVs (single nucleotide variants) and indels (insertion/deletions) and annotate them into functional categories in order to identify functionally relevant variants in three important cattle breeds in Brazil: Gyr and Girolando (dairy production) and Guzerat (dual-purpose). A total of approximately 2.7 billion reads from an Illumina HiSeq 2000 sequencer generated for each animal 10.9- to 16.4-fold genome coverage. Sequencing reads were mapped to the UMD 3.1 bovine genome assembly using the Burrows-Wheeler Aligner tool (v.0.7.10-r789). Picard tools (v.1.54) were used to eliminate PCR duplicates, and the variant calling was conducted with FreeBayes. The resulting variant lists were filtered by vcffilter in order to remove SNVs and indels with quality scores lower than 30 or coverage lower than 7. A total of 25,020,024 SNVs (16,743,392 from Guzerat, 15,941,804 from Gyr, and 13,286,669 from Girolando) and 3,249,148 indels (1,975,563 from Guzerat, 1,833,387 from Gyr, and 1,413,047 from Girolando) were detected in the DNA samples. A total of 13,253, 13,817, and 12,480 genes showed genetic variation in Guzerat, Gyr, and Girolando, respectively, of which 64.84% of genes with SNVs and 31.29% of genes with indels were shared among all breeds. The functional enrichment analysis by the DAVID (v.6.8) tool revealed 24, 27, and 28 enriched KEGG pathways (FDR < 10%) in Guzerat, Gyr, and Girolando, respectively, of which 14 pathways were common to all breeds, three pathways were significantly overrepresented only in Guzerat (arachidonic acid metabolism, Fc gamma R-mediated phagocytosis, and aldosterone-regulated sodium reabsorption), six pathways only in Gyr (alanine, aspartate and glutamate metabolism, inflammatory mediator regulation of TRP channels, thyroid hormone synthesis, pancreatic secretion, central carbon metabolism in cancer, and choline metabolism in cancer), and eight pathways only in Girolando (amino sugar and nucleotide sugar metabolism, inositol phosphate metabolism, vascular smooth muscle contraction, tight junction, regulation of actin cytoskeleton, amoebiasis, small cell lung cancer, and dilated cardiomyopathy). Although the genetic variants identified were distributed throughout the genomes, a large number of novel variants were clustered in specific genes. A total of 61 genes were identified with novel variants common in all breeds, while 349, 404, and 206 genes were identified as enriched with novel variants exclusively in the Guzerat, Gyr, and Girolando breeds, respectively. These genes are related to many biological processes, providing valuable information about genomic variants that may be responsible for variation in economically important traits among these breeds. [ABSTRACT FROM AUTHOR]

An effective strategy for managing protein databases is to provide mechanisms to transform raw data into consistent, accurate and reliable information. Such mechanisms will greatly reduce operational inefficiencies and improve one's ability to better handle scientific objectives and interpret the research results. To achieve this challenging goal for the STING project, we introduce Sting&#95;RDB, a relational database of structural parameters for protein analysis with support for data warehousing and data mining. In this article, we highlight the main features of Sting&#95;RDB and show how a user can explore it for efficient and biologically relevant queries. Considering its importance for molecular biologists, effort has been made to advance Sting&#95;RDB toward data quality assessment. To the best of our knowledge, Sting&#95;RDB is one of the most comprehensive data repositories for protein analysis, now also capable of providing its users with a data quality indicator. This paper differs from our previous study in many aspects. First, we introduce Sting&#95;RDB, a relational database with mechanisms for efficient and relevant queries using SQL. Sting&#95;rdb evolved from the earlier, text (flat file)-based database, in which data consistency and integrity was not guaranteed. Second, we provide support for data warehousing and mining. Third, the data quality indicator was introduced. Finally and probably most importantly, complex queries that could not be posed on a text-based database, are now easily implemented. Further details are accessible at the Sting&#95;RDB demo web page: http://www.cbi.cnptia.embrapa.br/StingRDB.

Star STING is the latest version of the STING suite of programs and corresponding database. We report on five important aspects of this package that have acquired some new characteristics, designed to add key advantages to the whole suite: 1) availability for most popular platforms and browsers, 2) introduction of the STING&#95;DB quality assessment, 3) improvement in algorithms for calculation of three STING parameters, 4) introduction of five new STING modules, and 5) expansion of the existing modules. Star STING is freely accessible at: http://sms.cbi.cnptia.embrapa.br/SMS/, http://trantor.bioc.columbia.edu/SMS, http://www.es.embnet.org/SMS/, http://gibk26.bse.kyutech.ac.jp/SMS/ and http://www.ar.embnet.org/SMS.