Background

The increasing use of DNA microarrays for genetical genomics studies generates a need for platforms with complete coverage of the genome. We have compared the effective gene coverage in the mouse genome of different commercial and noncommercial oligonucleotide microarray platforms by performing an in-house gene annotation of probes. We only used information about probes that is available from vendors and followed a process that any researcher may take to find the gene targeted by a given probe. In order to make consistent comparisons between platforms, probes in each microarray were annotated with an Entrez Gene id and the chromosomal position for each gene was obtained from the UCSC Genome Browser Database. Gene coverage was estimated as the percentage of Entrez Genes with a unique position in the UCSC Genome database that is tested by a given microarray platform.

Results

A MySQL relational database was created to store the mapping information for 25,416 mouse genes and for the probes in five microarray platforms (gene coverage level in parenthesis): Affymetrix430 2.0 (75.6%), ABI Genome Survey (81.24%), Agilent (79.33%), Codelink (78.09%), Sentrix (90.47%); and four array-ready oligosets: Sigma (47.95%), Operon v.3 (69.89%), Operon v.4 (84.03%), and MEEBO (84.03%). The differences in coverage between platforms were highly conserved across chromosomes. Differences in the number of redundant and unspecific probes were also found among arrays. The database can be queried to compare specific genomic regions using a web interface. The software used to create, update and query the database is freely available as a toolbox named ArrayGene.

Conclusion

The software developed here allows researchers to create updated custom databases by using public or proprietary information on genes for any organisms. ArrayGene allows easy comparisons of gene coverage between microarray platforms for any region of the genome. The comparison presented here reveals that the commercial microarray Sentrix, which is based on the MEEBO public oligoset, showed the best mouse genome coverage currently available. We also suggest the creation of guidelines to standardize the minimum set of information that vendors should provide to allow researchers to accurately evaluate the advantages and disadvantages of using a given platform.

The attainment of a specific mature body size is one of the most fundamental differences among species of mammals. Moreover, body size seems to be the central factor underlying differences in traits such as growth rate, energy metabolism and body composition. An important proportion of this variability is of genetic origin. The goal of the genetic analysis of animal growth is to understand its "genetic architecture", that is the number and position of loci affecting the trait, the magnitude of their effects, allele frequencies and types of gene action. In this review, the different strategies developed to identify and characterize genes involved in the regulation of growth in the mouse are described, with emphasis on the methods developed to map loci contributing to the regulation of quantitative traits (QTLs).

The continuous uploading of polygenic additive mutational variability has been reported in several studies in laboratory species with an inbred genetic background. These studies have focused on the direct contribution of new mutations without considering the possibility of epistatic effects derived from the interaction of new mutations with pre-existing polymorphisms. In this work we focused on this main topic and analysed the statistical and biological relevance of the epistatic variance for 9 week body weight in two populations of inbred mice. We developed a new linear mixed model parameterization where founder-related additive genetic variability, additive mutational variability and the interaction terms between both sources of variation were accounted for under a Bayesian design and without requiring the inversion of a matrix of epistatic genetic covariances. The analyses focused on a six-generations data set from C57BL/6J mice (n = 3736) and a five-generations data set from C57BL/6J(hg/hg) mice (n = 2843). The deviance information criterion (DIC) clearly favoured the model accounting for epistatic variability with reductions larger than 50 DIC units in both populations. Modal estimates for founder related, mutational and epistatic heritabilities were 0·068, 0·011 and 0·095 in C57BL/6J and 0·060, 0·010 and 0·113 in C57BL/6J(hg/hg), ruling out any doubt about the biological relevance of epistasis originating from new mutations in mice. These results contribute new insights on the relevance of epistasis in the genetic architecture of mammals and serve as an important component of an additional source of genetic heterogeneity for inbred strains of laboratory mice.

Abstract Background Cow milk is a complex bioactive fluid consumed by humans beyond infancy. Even though the chemical and physical properties of cow milk are well characterized, very limited research has been done on characterizing the milk transcriptome. This study performs a comprehensive expression profiling of genes expressed in milk somatic cells of transition (day 15), peak (day 90) and late (day 250) lactation Holstein cows by RNA sequencing. Milk samples were collected from Holstein cows at 15, 90 and 250 days of lactation, and RNA was extracted from the pelleted milk cells. Gene expression analysis was conducted by Illumina RNA sequencing. Sequence reads were assembled and analyzed in CLC Genomics Workbench. Gene Ontology (GO) and pathway analysis were performed using the Blast2GO program and GeneGo application of MetaCore program. Results A total of 16,892 genes were expressed in transition lactation, 19,094 genes were expressed in peak lactation and 18,070 genes were expressed in late lactation. Regardless of the lactation stage approximately 9,000 genes showed ubiquitous expression. Genes encoding caseins, whey proteins and enzymes in lactose synthesis pathway showed higher expression in early lactation. The majority of genes in the fat metabolism pathway had high expression in transition and peak lactation milk. Most of the genes encoding for endogenous proteases and enzymes in ubiquitin-proteasome pathway showed higher expression along the course of lactation. Conclusions This is the first study to describe the comprehensive bovine milk transcriptome in Holstein cows. The results revealed that 69% of NCBI Btau 4.0 annotated genes are expressed in bovine milk somatic cells. Most of the genes were ubiquitously expressed in all three stages of lactation. However, a fraction of the milk transcriptome has genes devoted to specific functions unique to the lactation stage. This indicates the ability of milk somatic cells to adapt to different molecular functions according to the biological need of the animal. This study provides a valuable insight into the biology of lactation in the cow, as well as many avenues for future research on the bovine lactome.

Parameters of bone geometry such as width, length, and cross-sectional area are major determinants of bone strength. Although these traits are highly heritable, few genes influencing bone geometry have been identified. Here, we dissect a major quantitative trait locus (QTL) influencing femur size. This QTL was originally identified in an F2 cross between the C57BL/6J-hg/hg (HG) and CAST/EiJ strains and was referred to as femur length in high growth mice 2 (Feml2). Feml2 was located on chromosome (Chr.) 9 at ∼20 cM. Here, we show that the HG.CAST-(D9Mit249-D9Mit133)/Ucd congenic strain captures Feml2 In an F2 congenic cross, we fine-mapped the location of Feml2 to an ∼6 Mbp region extending from 57.3 to 63.3 Mbp on Chr. 9. We have identified candidates by mining the complete genome sequence of CAST/EiJ and through allele-specific expression (ASE) analysis of growth plates in C57BL/6J × CAST/EiJ F1 hybrids. Interestingly, we also find that the refined location of Feml2 overlaps a cluster of six independent genome-wide associations for human height. This work provides the foundation for the identification of novel genes affecting bone geometry.

We investigated the possibility of single-step genome editing in small ruminants by CRISPR-Cas9 zygote electroporation. We targeted SOCS2 and PDX1 in sheep embryos and OTX2 in goat embryos, utilizing a dual sgRNA approach. Gene editing efficiency was compared between microinjection and three different electroporation settings performed at four different times of embryo development. Electroporation of sheep zygotes 6 h after fertilization with settings that included short high-voltage (poring) and long low-voltage (transfer) pulses was efficient at producing SOCS2 knock-out blastocysts. The mutation rate after CRISPR/Cas9 electroporation was 95.6% ± 8%, including 95.4% ± 9% biallelic mutations; which compared favorably to 82.3% ± 8% and 25% ± 10%, respectively, when using microinjection. We also successfully disrupted the PDX1 gene in sheep and the OTX2 gene in goat embryos. The biallelic mutation rate was 81 ± 5% for PDX1 and 85% ± 6% for OTX2. In conclusion, using single-step CRISPR-Cas9 zygote electroporation, we successfully introduced biallelic deletions in the genome of small ruminant embryos.

Background

High growth (hg) modifier and background independent quantitative trait loci (QTL) affecting growth, adiposity and carcass composition were previously identified on mouse chromosomes (MMU) 1, 2, 5, 8, 9, 11 and 17. To confirm and further characterize each QTL, two panels of speed congenic strains were developed by introgressing CAST/EiJ (CAST) QTL alleles onto either mutant C57Bl/6J-hg/hg (HG) or wild type C57Bl/6J (B6) genetic backgrounds.

Results

The first speed congenic panel was developed by introgressing four overlapping donor regions spanning MMU2 in its entirety onto both HG and B6 backgrounds, for a total of eight strains. Phenotypic characterization of the MMU2 panel confirmed the segregation of multiple growth and obesity QTL and strongly suggested that a subset of these loci modify the effects of the hg deletion. The second panel consisted of individual donor regions on an HG background for each QTL on MMU1, 5, 8, 9, 11 and 17. Of the six developed strains, five were successfully characterized and displayed significant differences in growth and/or obesity as compared to controls. All five displayed phenotypes similar to those originally attributed to each QTL, however, novel phenotypes were unmasked in several of the strains including sex-specific effects.

Conclusion

The speed congenic strains developed herein constitute an invaluable genomic resource and provide the foundation to identify the specific nature of genetic variation influencing growth and obesity.

The aquaculture industry continues to promote the diversification of ingredients used in aquafeed in order to achieve a more sustainable aquaculture production system. The evaluation of large numbers of diets in aquaculture species is costly and requires time-consuming trials in some species. In contrast, zebrafish (Danio rerio) can solve these drawbacks as an experimental model, and represents an ideal organism to carry out preliminary evaluation of diets. In addition, zebrafish has a sequenced genome allowing the efficient utilization of new technologies, such as RNA-sequencing and genotyping platforms to study the molecular mechanisms that underlie the organism's response to nutrients. Also, biotechnological tools like transgenic lines with fluorescently labeled neutrophils that allow the evaluation of the immune response in vivo, are readily available in this species. Thus, zebrafish provides an attractive platform for testing many ingredients to select those with the highest potential of success in aquaculture. In this perspective article aspects related to diet evaluation in which zebrafish can make important contributions to nutritional genomics and nutritional immunity are discussed.

Background

The characterization of the human intestinal microflora and their interactions with the host have been identified as key components in the study of intestinal disorders such as inflammatory bowel diseases. High-throughput sequencing has enabled culture-independent studies to deeply analyze bacteria in the gut. It is possible with this technology to systematically analyze links between microbes and the genetic constitution of the host, such as DNA polymorphisms and methylation, and gene expression.

Methods and findings

In this study the V2 region of the bacterial 16S ribosomal RNA (rRNA) gene using 454 pyrosequencing from seven anatomic regions of human colon and two types of stool specimens were analyzed. The study examined the number of reads needed to ascertain differences between samples, the effect of DNA extraction procedures and PCR reproducibility, and differences between biopsies and stools in order to design a large scale systematic analysis of gut microbes. It was shown (1) that sequence coverage lower than 1,000 reads influenced quantitative and qualitative differences between samples measured by UniFrac distances. Distances between samples became stable after 1,000 reads. (2) Difference of extracted bacteria was observed between the two DNA extraction methods. In particular, Firmicutes Bacilli were not extracted well by one method. (3) Quantitative and qualitative difference in bacteria from ileum to rectum colon were not observed, but there was a significant positive trend between distances within colon and quantitative differences. Between sample type, biopsies or stools, quantitative and qualitative differences were observed.

Conclusions

Results of human colonic bacteria analyzed using high-throughput sequencing were highly dependent on the experimental design, especially the number of sequence reads, DNA extraction method, and sample type.

High-throughput sequencing of RNA (RNA-Seq) was developed primarily to analyze global gene expression in different tissues. However, it also is an efficient way to discover coding SNPs. The objective of this study was to perform a SNP discovery analysis in the milk transcriptome using RNA-Seq. Seven milk samples from Holstein cows were analyzed by sequencing cDNAs using the Illumina Genome Analyzer system. We detected 19,175 genes expressed in milk samples corresponding to approximately 70% of the total number of genes analyzed. The SNP detection analysis revealed 100,734 SNPs in Holstein samples, and a large number of those corresponded to differences between the Holstein breed and the Hereford bovine genome assembly Btau4.0. The number of polymorphic SNPs within Holstein cows was 33,045. The accuracy of RNA-Seq SNP discovery was tested by comparing SNPs detected in a set of 42 candidate genes expressed in milk that had been resequenced earlier using Sanger sequencing technology. Seventy of 86 SNPs were detected using both RNA-Seq and Sanger sequencing technologies. The KASPar Genotyping System was used to validate unique SNPs found by RNA-Seq but not observed by Sanger technology. Our results confirm that analyzing the transcriptome using RNA-Seq technology is an efficient and cost-effective method to identify SNPs in transcribed regions. This study creates guidelines to maximize the accuracy of SNP discovery and prevention of false-positive SNP detection, and provides more than 33,000 SNPs located in coding regions of genes expressed during lactation that can be used to develop genotyping platforms to perform marker-trait association studies in Holstein cattle.