Prune homolog 2 with BCH domain (PRUNE2) gene expression is associated with feed efficiency-related traits in Nelore steers.

Animal feeding is a critical factor in increasing producer profitability. Improving feed efficiency can help reduce feeding costs and reduce the environmental impact of beef production. Candidate genes previously identified for this trait in differential gene expression studies (e.g., case-control studies) have not examined continuous gene-phenotype variation, which is a limitation. The aim of this study was to investigate the association between the expression of five candidate genes in the liver, measured by quantitative real-time PCR and feed-related traits. We adopted a linear mixed model to associate liver gene expression from 52 Nelore steers with the following production traits: average daily gain (ADG), body weight (BW), dry matter intake (DMI), feed conversion ratio (FCR), feed efficiency (FE), Kleiber index (KI), metabolic body weight (MBW), residual feed intake (RFI), and relative growth ratio (RGR). The total expression of the prune homolog 2 (PRUNE2) gene was significantly associated with DMI, FCR, FE, and RFI (P < 0.05). Furthermore, we have identified a new transcript of PRUNE2 (TCONS_00027692, GenBank MZ041267) that was inversely correlated with FCR and FE (P < 0.05), in contrast to the originally identified PRUNE2 transcript. The cytochrome P450 subfamily 2B (CYP2B6), early growth response protein 1 (EGR1), collagen type I alpha 1 chain (COL1A1), and connective tissue growth factor (CTGF) genes were not associated with any feed efficiency-related traits (P > 0.05). The findings reported herein suggest that PRUNE2 expression levels affects feed efficiency-related traits variation in Nelore steers.

Plant Co-expression Annotation Resource: a web server for identifying targets for genetically modified crop breeding pipelines.

The development of genetically modified crops (GM) includes the discovery of candidate genes through bioinformatics analysis using genomics data, gene expression, and others. Proteins of unknown function (PUFs) are interesting targets for GM crops breeding pipelines for the novelty associated with such targets and also to avoid copyright protection. One method of inferring the putative function of PUFs is by relating them to factors of interest such as abiotic stresses using orthology and co-expression networks, in a guilt-by-association manner. In this regard, we have downloaded, analyzed, and processed genomics data of 53 angiosperms, totaling 1,862,010 genes and 2,332,974 RNA. Diamond and InterproScan were used to discover 72,266 PUFs for all organisms. RNA-seq datasets related to abiotic stresses were downloaded from NCBI/GEO. The RNA-seq data was used as input to the LSTrAP software to construct co-expression networks. LSTrAP also created clusters of transcripts with correlated expression, whose members are more probably related to the molecular mechanisms associated with abiotic stresses in the plants. Orthologous groups were created (OrhtoMCL) using all 2,332,974 proteins in order to associate PUFs to abiotic stress-related clusters of co-expression and therefore infer their function in a guilt-by-association manner. A freely available web resource named "Plant Co-expression Annotation Resource" ( https://www.machado.cnptia.embrapa.br/plantannot ), Plantannot, was created to provide indexed queries to search for PUF putatively associated with abiotic stresses. The web interface also allows browsing, querying, and retrieving of public genomics data from 53 plants. We hope Plantannot to be useful for researchers trying to obtain novel GM crops resistant to climate change hazards.

Identification of putative regulatory regions and transcription factors associated with intramuscular fat content traits.

BACKGROUND: Integration of high throughput DNA genotyping and RNA-sequencing data allows for the identification of genomic regions that control gene expression, known as expression quantitative trait loci (eQTL), on a whole genome scale. Intramuscular fat (IMF) content and carcass composition play important roles in metabolic and physiological processes in mammals because they influence insulin sensitivity and consequently prevalence of metabolic diseases such as obesity and type 2 diabetes. However, limited information is available on the genetic variants and mechanisms associated with IMF deposition in mammals. Thus, our hypothesis was that eQTL analyses could identify putative regulatory regions and transcription factors (TFs) associated with intramuscular fat (IMF) content traits. RESULTS: We performed an integrative eQTL study in skeletal muscle to identify putative regulatory regions and factors associated with intramuscular fat content traits. Data obtained from skeletal muscle samples of 192 animals was used for association analysis between 461,466 SNPs and the transcription level of 11,808 genes. This yielded 1268 cis- and 10,334 trans-eQTLs, among which we identified nine hotspot regions that each affected the expression of > 119 genes. These putative regulatory regions overlapped with previously identified QTLs for IMF content. Three of the hotspots respectively harbored the transcription factors USF1, EGR4 and RUNX1T1, which are known to play important roles in lipid metabolism. From co-expression network analysis, we further identified modules significantly correlated with IMF content and associated with relevant processes such as fatty acid metabolism, carbohydrate metabolism and lipid metabolism. CONCLUSION: This study provides novel insights into the link between genotype and IMF content as evident from the expression level. It thereby identifies genomic regions of particular importance and associated regulatory factors. These new findings provide new knowledge about the biological processes associated with genetic variants and mechanisms associated with IMF deposition in mammals.

Whole genome sequencing of Guzerá cattle reveals genetic variants in candidate genes for production, disease resistance, and heat tolerance.

In bovines, artificial selection has produced a large number of breeds which differ in production, environmental adaptation, and health characteristics. To investigate the genetic basis of these phenotypical differences, several bovine breeds have been sequenced. Millions of new SNVs were described at every new breed sequenced, suggesting that every breed should be sequenced. Guzerat or Guzerá is an indicine breed resistant to drought and parasites that has been the base for some important breeds such as Brahman. Here, we describe the sequence of the Guzerá genome and the in silico functional analyses of intragenic breed-specific variations. Mate-paired libraries were generated using the ABI SOLiD system. Sequences were mapped to the Bos taurus reference genome (UMD 3.1) and 87% of the reference genome was covered at a 26X. Among the variants identified, 2,676,067 SNVs and 463,158 INDELs were homozygous, not found in any database searched, and may represent true differences between Guzerá and B. taurus. Functional analyses investigated with the NGS-SNP package focused on 1069 new, non-synonymous SNVs, splice-site variants (including acceptor and donor sites, and the conserved regions at both intron borders, referred to here as splice regions) and coding INDELs (NS/SS/I). These NS/SS/I map to 935 genes belonging to cell communication, environmental adaptation, signal transduction, sensory, and immune systems pathways. These pathways have been involved in phenotypes related to health, adaptation to the environment and behavior, and particularly, disease resistance and heat tolerance. Indeed, 105 of these genes are known QTLs for milk, meat and carcass, production, reproduction, and health traits. Therefore, in addition to describing new genetic variants, our approach provided groundwork for unraveling key candidate genes and mutations.

POTION: an end-to-end pipeline for positive Darwinian selection detection in genome-scale data through phylogenetic comparison of protein-coding genes.

BACKGROUND: Detection of genes evolving under positive Darwinian evolution in genome-scale data is nowadays a prevailing strategy in comparative genomics studies to identify genes potentially involved in adaptation processes. Despite the large number of studies aiming to detect and contextualize such gene sets, there is virtually no software available to perform this task in a general, automatic, large-scale and reliable manner. This certainly occurs due to the computational challenges involved in this task, such as the appropriate modeling of data under analysis, the computation time to perform several of the required steps when dealing with genome-scale data and the highly error-prone nature of the sequence and alignment data structures needed for genome-wide positive selection detection. RESULTS: We present POTION, an open source, modular and end-to-end software for genome-scale detection of positive Darwinian selection in groups of homologous coding sequences. Our software represents a key step towards genome-scale, automated detection of positive selection, from predicted coding sequences and their homology relationships to high-quality groups of positively selected genes. POTION reduces false positives through several sophisticated sequence and group filters based on numeric, phylogenetic, quality and conservation criteria to remove spurious data and through multiple hypothesis corrections, and considerably reduces computation time thanks to a parallelized design. Our software achieved a high classification performance when used to evaluate a curated dataset of Trypanosoma brucei paralogs previously surveyed for positive selection. When used to analyze predicted groups of homologous genes of 19 strains of Mycobacterium tuberculosis as a case study we demonstrated the filters implemented in POTION to remove sources of errors that commonly inflate errors in positive selection detection. A thorough literature review found no other software similar to POTION in terms of customization, scale and automation. CONCLUSION: To the best of our knowledge, POTION is the first tool to allow users to construct and check hypotheses regarding the occurrence of site-based evidence of positive selection in non-curated, genome-scale data within a feasible time frame and with no human intervention after initial configuration. POTION is available at http://www.lmb.cnptia.embrapa.br/share/POTION/.

SchistoDB: an updated genome resource for the three key schistosomes of humans.

The new release of SchistoDB (http://SchistoDB.net) provides a rich resource of genomic data for key blood flukes (genus Schistosoma) which cause disease in hundreds of millions of people worldwide. SchistoDB integrates whole-genome sequence and annotation of three species of the genus and provides enhanced bioinformatics analyses and data-mining tools. A simple, yet comprehensive web interface provided through the Strategies Web Development Kit is available for the mining and visualization of the data. Genomic scale data can be queried based on BLAST searches, annotation keywords and gene ID searches, gene ontology terms, sequence motifs, protein characteristics and phylogenetic relationships. Search strategies can be saved within a user's profile for future retrieval and may also be shared with other researchers using a unique web address.

Repressive epigenetic mechanisms, such as the H3K27me3 histone modification, were predicted to affect muscle gene expression and its mineral content in Nelore cattle.

Epigenetic repression has been linked to the regulation of different cell states. In this study, we focus on the influence of this repression, mainly by H3K27me3, over gene expression in muscle cells, which may affect mineral content, a phenotype that is relevant to muscle function and beef quality. Based on the inverse relationship between H3K27me3 and gene expression (i.e., epigenetic repression) and on contrasting sample groups, we computationally predicted regulatory genes that affect muscle mineral content. To this end, we applied the TRIAGE predictive method followed by a rank product analysis. This methodology can predict regulatory genes that might be affected by repressive epigenetic regulation related to mineral concentration. Annotation of orthologous genes, between human and bovine, enabled our investigation of gene expression in the Longissimus thoracis muscle of Bos indicus cattle. The animals under study had a contrasting mineral content in their muscle cells. We identified candidate regulatory genes influenced by repressive epigenetic mechanisms, linking histone modification to mineral content in beef samples. The discovered candidate genes take part in multiple biological pathways, i.e., impulse transmission, cell signalling, immunological, and developmental pathways. Some of these genes were previously associated with mineral content or regulatory mechanisms. Our findings indicate that epigenetic repression can partially explain the gene expression profiles observed in muscle samples with contrasting mineral content through the candidate regulators here identified.

The Schistosoma mansoni phylome: using evolutionary genomics to gain insight into a parasite's biology.

BACKGROUND: Schistosoma mansoni is one of the causative agents of schistosomiasis, a neglected tropical disease that affects about 237 million people worldwide. Despite recent efforts, we still lack a general understanding of the relevant host-parasite interactions, and the possible treatments are limited by the emergence of resistant strains and the absence of a vaccine. The S. mansoni genome was completely sequenced and still under continuous annotation. Nevertheless, more than 45% of the encoded proteins remain without experimental characterization or even functional prediction. To improve our knowledge regarding the biology of this parasite, we conducted a proteome-wide evolutionary analysis to provide a broad view of the S. mansoni's proteome evolution and to improve its functional annotation. RESULTS: Using a phylogenomic approach, we reconstructed the S. mansoni phylome, which comprises the evolutionary histories of all parasite proteins and their homologs across 12 other organisms. The analysis of a total of 7,964 phylogenies allowed a deeper understanding of genomic complexity and evolutionary adaptations to a parasitic lifestyle. In particular, the identification of lineage-specific gene duplications pointed to the diversification of several protein families that are relevant for host-parasite interaction, including proteases, tetraspanins, fucosyltransferases, venom allergen-like proteins, and tegumental-allergen-like proteins. In addition to the evolutionary knowledge, the phylome data enabled us to automatically re-annotate 3,451 proteins through a phylogenetic-based approach rather than solely sequence similarity searches. To allow further exploitation of this valuable data, all information has been made available at PhylomeDB (http://www.phylomedb.org). CONCLUSIONS: In this study, we used an evolutionary approach to assess S. mansoni parasite biology, improve genome/proteome functional annotation, and provide insights into host-parasite interactions. Taking advantage of a proteome-wide perspective rather than focusing on individual proteins, we identified that this parasite has experienced specific gene duplication events, particularly affecting genes that are potentially related to the parasitic lifestyle. These innovations may be related to the mechanisms that protect S. mansoni against host immune responses being important adaptations for the parasite survival in a potentially hostile environment. Continuing this work, a comparative analysis involving genomic, transcriptomic, and proteomic data from other helminth parasites, other parasites, and vectors will supply more information regarding parasite's biology as well as host-parasite interactions.

DNA methylation may affect beef tenderness through signal transduction in Bos indicus.

BACKGROUND: Beef tenderness is a complex trait of economic importance for the beef industry. Understanding the epigenetic mechanisms underlying this trait may help improve the accuracy of breeding programs. However, little is known about epigenetic effects on Bos taurus muscle and their implications in tenderness, and no studies have been conducted in Bos indicus. RESULTS: Comparing methylation profile of Bos indicus skeletal muscle with contrasting beef tenderness at 14 days after slaughter, we identified differentially methylated cytosines and regions associated with this trait. Interestingly, muscle that became tender beef had higher levels of hypermethylation compared to the tough group. Enrichment analysis of predicted target genes suggested that differences in methylation between tender and tough beef may affect signal transduction pathways, among which G protein signaling was a key pathway. In addition, different methylation levels were found associated with expression levels of GNAS, PDE4B, EPCAM and EBF3 genes. The differentially methylated elements correlated with EBF3 and GNAS genes overlapped CpG islands and regulatory elements. GNAS, a complex imprinted gene, has a key role on G protein signaling pathways. Moreover, both G protein signaling pathway and the EBF3 gene regulate muscle homeostasis, relaxation, and muscle cell-specificity. CONCLUSIONS: We present differentially methylated loci that may be of interest to decipher the epigenetic mechanisms affecting tenderness. Supported by the previous knowledge about regulatory elements and gene function, the methylation data suggests EBF3 and GNAS as potential candidate genes and G protein signaling as potential candidate pathway associated with beef tenderness via methylation.

Allele-specific expression reveals functional SNPs affecting muscle-related genes in bovine.

Single nucleotide polymorphisms showing allele-specific expression (ASE SNPs) are useful for cis-regulatory variants discovery. Despite this potential, there are expensive costs involved in genome-level ASE analysis for large sample sizes. If different data resolutions are available, genotype imputation can be used to mitigate this limitation. Aiming to increase the power to detect regulatory variants, we used a large dataset (>4 million) of imputed SNP genotypes and RNA-Seq data from 190 Nelore steers. Differences between major and minor allele expressions in muscle were tested with a Binomial Test. We identified 38,177 ASE SNPs (FDR ≤ 0.05) within 7304 linkage disequilibrium blocks. After that, we searched for aseQTLs (i.e., neighboring SNPs potentially regulating the ASE SNPs' allelic expression) by comparing the ASE of heterozygous to homozygous sample groups under a Wilcoxon Rank Sum test. We identified 21,543 aseQTLs potentially regulating 430 ASE SNPs (FDR ≤ 0.05). A total of 3333 cis-eQTLs (being 2098 ASE SNPs and 1075 aseQTLs) were associated with the expression of 758 transcripts (FDR ≤ 0.05), demonstrating the cis-regulatory effect of these ASE SNPs and aseQTLs. Data integration showed reproducibility with previous studies in bovine ASE and genomic imprinting. Furthermore, we identified 36,756 novel ASE regions due to the imputation approach. Comparisons with epigenetics data from Functional Annotation of Animal Genomes (FAANG) suggest a regulatory potential of the ASE-related SNPs. The affected genes were enriched in metabolic pathways essential for muscle homeostasis. These findings reinforce the potential of using ASE for discovering cis-regulatory SNPs that may affect muscle-related traits.

Differential Allele-Specific Expression Revealed Functional Variants and Candidate Genes Related to Meat Quality Traits in B. indicus Muscle.

Traditional transcriptomics approaches have been used to identify candidate genes affecting economically important livestock traits. Regulatory variants affecting these traits, however, remain under covered. Genomic regions showing allele-specific expression (ASE) are under the effect of cis-regulatory variants, being useful for improving the accuracy of genomic selection models. Taking advantage of the better of these two methods, we investigated single nucleotide polymorphisms (SNPs) in regions showing differential ASE (DASE SNPs) between contrasting groups for beef quality traits. For these analyses, we used RNA sequencing data, imputed genotypes and genomic estimated breeding values of muscle-related traits from 190 Nelore (Bos indicus) steers. We selected 40 contrasting unrelated samples for the analysis (N = 20 animals per contrasting group) and used a beta-binomial model to identify ASE SNPs in only one group (i.e., DASE SNPs). We found 1479 DASE SNPs (FDR ≤ 0.05) associated with 55 beef-quality traits. Most DASE genes were involved with tenderness and muscle homeostasis, presenting a co-expression module enriched for the protein ubiquitination process. The results overlapped with epigenetics and phenotype-associated data, suggesting that DASE SNPs are potentially linked to cis-regulatory variants affecting simultaneously the transcription and phenotype through chromatin state modulation.

Eukaryotic protein kinases (ePKs) of the helminth parasite Schistosoma mansoni.

BACKGROUND: Schistosomiasis remains an important parasitic disease and a major economic problem in many countries. The Schistosoma mansoni genome and predicted proteome sequences were recently published providing the opportunity to identify new drug candidates. Eukaryotic protein kinases (ePKs) play a central role in mediating signal transduction through complex networks and are considered druggable targets from the medical and chemical viewpoints. Our work aimed at analyzing the S. mansoni predicted proteome in order to identify and classify all ePKs of this parasite through combined computational approaches. Functional annotation was performed mainly to yield insights into the parasite signaling processes relevant to its complex lifestyle and to select some ePKs as potential drug targets. RESULTS: We have identified 252 ePKs, which corresponds to 1.9% of the S. mansoni predicted proteome, through sequence similarity searches using HMMs (Hidden Markov Models). Amino acid sequences corresponding to the conserved catalytic domain of ePKs were aligned by MAFFT and further used in distance-based phylogenetic analysis as implemented in PHYLIP. Our analysis also included the ePK homologs from six other eukaryotes. The results show that S. mansoni has proteins in all ePK groups. Most of them are clearly clustered with known ePKs in other eukaryotes according to the phylogenetic analysis. None of the ePKs are exclusively found in S. mansoni or belong to an expanded family in this parasite. Only 16 S. mansoni ePKs were experimentally studied, 12 proteins are predicted to be catalytically inactive and approximately 2% of the parasite ePKs remain unclassified. Some proteins were mentioned as good target for drug development since they have a predicted essential function for the parasite. CONCLUSIONS: Our approach has improved the functional annotation of 40% of S. mansoni ePKs through combined similarity and phylogenetic-based approaches. As we continue this work, we will highlight the biochemical and physiological adaptations of S. mansoni in response to diverse environments during the parasite development, vector interaction, and host infection.

Identification of Schistosoma mansoni microRNAs.

BACKGROUND: MicroRNAs (miRNAs) constitute a class of single-stranded RNAs which play a crucial role in regulating development and controlling gene expression by targeting mRNAs and triggering either translation repression or messenger RNA (mRNA) degradation. miRNAs are widespread in eukaryotes and to date over 14,000 miRNAs have been identified by computational and experimental approaches. Several miRNAs are highly conserved across species. In Schistosoma, the full set of miRNAs and their expression patterns during development remain poorly understood. Here we report on the development and implementation of a homology-based detection strategy to search for miRNA genes in Schistosoma mansoni. In addition, we report results on the experimental detection of miRNAs by means of cDNA cloning and sequencing of size-fractionated RNA samples. RESULTS: Homology search using the high-throughput pipeline was performed with all known miRNAs in miRBase. A total of 6,211 mature miRNAs were used as reference sequences and 110 unique S. mansoni sequences were returned by BLASTn analysis. The existing mature miRNAs that produced these hits are reported, as well as the locations of the homologous sequences in the S. mansoni genome. All BLAST hits aligned with at least 95% of the miRNA sequence, resulting in alignment lengths of 19-24 nt. Following several filtering steps, 15 potential miRNA candidates were identified using this approach. By sequencing small RNA cDNA libraries from adult worm pairs, we identified 211 novel miRNA candidates in the S. mansoni genome. Northern blot analysis was used to detect the expression of the 30 most frequent sequenced miRNAs and to compare the expression level of these miRNAs between the lung stage schistosomula and adult worm stages. Expression of 11 novel miRNAs was confirmed by northern blot analysis and some presented a stage-regulated expression pattern. Three miRNAs previously identified from S. japonicum were also present in S. mansoni. CONCLUSION: Evidence for the presence of miRNAs in S. mansoni is presented. The number of miRNAs detected by homology-based computational methods in S. mansoni is limited due to the lack of close relatives in the miRNA repository. In spite of this, the computational approach described here can likely be applied to the identification of pre-miRNA hairpins in other organisms. Construction and analysis of a small RNA library led to the experimental identification of 14 novel miRNAs from S. mansoni through a combination of molecular cloning, DNA sequencing and expression studies. Our results significantly expand the set of known miRNAs in multicellular parasites and provide a basis for understanding the structural and functional evolution of miRNAs in these metazoan parasites.

SchistoDB: a Schistosoma mansoni genome resource.

SchistoDB (http://schistoDB.net/) is a genomic database for the parasitic organism Schistosoma mansoni, one of the major causative agents of schistosomiasis worldwide. It currently incorporates sequences and annotation for S. mansoni in a single user-friendly database. Several genomic scale analyses are available as well as ESTs, oligonucleotides, metabolic pathways and drugs. In this article, we describe the data sets and its analyses, how to query the database and tools available in the website.

Evolutionary histories of expanded peptidase families in Schistosoma mansoni.

Schistosoma mansoni is one of the three main causative agents of human schistosomiasis, a major health problem with a vast socio-economic impact. Recent advances in the proteomic analysis of schistosomes have revealed that peptidases are the main virulence factors involved in the pathogenesis of this disease. In this context, evolutionary studies can be applied to identify peptidase families that have been expanded in genomes over time in response to different selection pressures. Using a phylogenomic approach, we searched for expanded endopeptidase families in the S. mansoni predicted proteome with the aim of contributing to the knowledge of such enzymes as potential therapeutic targets. We found three endopeptidase families that comprise leishmanolysins (metallopeptidase M8 family), cercarial elastases (serine peptidase S1 family) and cathepsin D proteins (aspartic peptidase A1 family). Our results suggest that the Schistosoma members of these families originated from successive gene duplication events in the parasite lineage after its diversification from other metazoans. Overall, critical residues are conserved among the duplicated genes/proteins. Furthermore, each protein family displays a distinct evolutionary history. Altogether, this work provides an evolutionary view of three S. mansoni peptidase families, which allows for a deeper understanding of the genomic complexity and lineage-specific adaptations potentially related to the parasitic lifestyle.

Muscle allele-specific expression QTLs may affect meat quality traits in Bos indicus.

Single nucleotide polymorphisms (SNPs) located in transcript sequences showing allele-specific expression (ASE SNPs) were previously identified in the Longissimus thoracis muscle of a Nelore (Bos indicus) population consisting of 190 steers. Given that the allele-specific expression pattern may result from cis-regulatory SNPs, called allele-specific expression quantitative trait loci (aseQTLs), in this study, we searched for aseQTLs in a window of 1 Mb upstream and downstream from each ASE SNP. After this initial analysis, aiming to investigate variants with a potential regulatory role, we further screened our aseQTL data for sequence similarity with transcription factor binding sites and microRNA (miRNA) binding sites. These aseQTLs were overlapped with methylation data from reduced representation bisulfite sequencing (RRBS) obtained from 12 animals of the same population. We identified 1134 aseQTLs associated with 126 different ASE SNPs. For 215 aseQTLs, one allele potentially affected the affinity of a muscle-expressed transcription factor to its binding site. 162 aseQTLs were predicted to affect 149 miRNA binding sites, from which 114 miRNAs were expressed in muscle. Also, 16 aseQTLs were methylated in our population. Integration of aseQTL with GWAS data revealed enrichment for traits such as meat tenderness, ribeye area, and intramuscular fat . To our knowledge, this is the first report of aseQTLs identification in bovine muscle. Our findings indicate that various cis-regulatory and epigenetic mechanisms can affect multiple variants to modulate the allelic expression. Some of the potential regulatory variants described here were associated with the expression pattern of genes related to interesting phenotypes for livestock. Thus, these variants might be useful for the comprehension of the genetic control of these phenotypes.

The contributions of the Genome Project to the study of schistosomiasis.

In this paper we review the impact that the availability of the Schistosoma mansoni genome sequence and annotation has had on schistosomiasis research. Easy access to the genomic information is important and several types of data are currently being integrated, such as proteomics, microarray and polymorphic loci. Access to the genome annotation and powerful means of extracting information are major resources to the research community.

Machado: Open source genomics data integration framework.

BACKGROUND: Genome projects and multiomics experiments generate huge volumes of data that must be stored, mined, and transformed into useful knowledge. All this information is supposed to be accessible and, if possible, browsable afterwards. Computational biologists have been dealing with this scenario for more than a decade and have been implementing software and databases to meet this challenge. The GMOD's (Generic Model Organism Database) biological relational database schema, known as Chado, is one of the few successful open source initiatives; it is widely adopted and many software packages are able to connect to it. FINDINGS: We have been developing an open source software package named Machado, a genomics data integration framework implemented in Python, to enable research groups to both store and visualize genomics data. The framework relies on the Chado database schema and, therefore, should be very intuitive for current developers to adopt it or have it running on top of already existing databases. It has several data-loading tools for genomics and transcriptomics data and also for annotation results from tools such as BLAST, InterproScan, OrthoMCL, and LSTrAP. There is an API to connect to JBrowse, and a web visualization tool is implemented using Django Views and Templates. The Haystack library integrated with the ElasticSearch engine was used to implement a Google-like search, i.e., single auto-complete search box that provides fast results and filters. CONCLUSION: Machado aims to be a modern object-relational framework that uses the latest Python libraries to produce an effective open source resource for genomics research.

Allele-specific expression is widespread in Bos indicus muscle and affects meat quality candidate genes.

Differences between the expression of the two alleles of a gene are known as allele-specific expression (ASE), a common event in the transcriptome of mammals. Despite ASE being a source of phenotypic variation, its occurrence and effects on genetic prediction of economically relevant traits are still unexplored in bovines. Furthermore, as ASE events are likely driven by cis-regulatory mutations, scanning them throughout the bovine genome represents a significant step to elucidate the mechanisms underlying gene expression regulation. To address this question in a Bos indicus population, we built the ASE profile of the skeletal muscle tissue of 190 Nelore steers, using RNA sequencing data and SNPs genotypes from the Illumina BovineHD BeadChip (770 K bp). After quality control, 820 SNPs showed at least one sample with ASE. These SNPs were widespread among all autosomal chromosomes, being 32.01% found in 3'UTR and 31.41% in coding regions. We observed a considerable variation of ASE profile among individuals, which highlighted the need for biological replicates in ASE studies. Functional analysis revealed that ASE genes play critical biological functions in the development and maintenance of muscle tissue. Additionally, some of these genes were previously reported as associated with beef production and quality traits in livestock, thus indicating a possible source of bias on genomic predictions for these traits.

Genetic regulators of mineral amount in Nelore cattle muscle predicted by a new co-expression and regulatory impact factor approach.

Mineral contents in bovine muscle can affect meat quality, growth, health, and reproductive traits. To better understand the genetic basis of this phenotype in Nelore (Bos indicus) cattle, we analysed genome-wide mRNA and miRNA expression data from 114 muscle samples. The analysis implemented a new application for two complementary algorithms: the partial correlation and information theory (PCIT) and the regulatory impact factor (RIF), in which we included the estimated genomic breeding values (GEBVs) for the phenotypes additionally to the expression levels, originally proposed for these methods. We used PCIT to determine putative regulatory relationships based on significant associations between gene expression and GEBVs for each mineral amount. Then, RIF was adopted to determine the regulatory impact of genes and miRNAs expression over the GEBVs for the mineral amounts. We also investigated over-represented pathways, as well as pieces of evidences from previous studies carried in the same population and in the literature, to determine regulatory genes for the mineral amounts. For example, NOX1 expression level was positively correlated to Zinc and has been described as Zinc-regulated in humans. Based on our approach, we were able to identify genes, miRNAs and pathways not yet described as underlying mineral amount. The results support the hypothesis that extracellular matrix interactions are the core regulator of mineral amount in muscle cells. Putative regulators described here add information to this hypothesis, expanding the knowledge on molecular relationships between gene expression and minerals.