Publications - Publications

Gut microbiota derived metabolites contribute to intestinal barrier maturation at the suckling-to-weaning transition

Mussard, É. M., Beaumont, . M., Paës, C., et al. — Wed, 01 Apr 2020 20:51:55 +0200

In suckling mammals, the onset of solid food ingestion is coincident with the maturation of the gut barrier. This ontogenic process is driven by the colonization of the intestine by the microbiota. However, the mechanisms underlying the microbial regulation of the intestinal development in early life are not fully understood. Here, we studied the co-maturation of the microbiota (composition and metabolic activity) and of the gut barrier at the suckling-to-weaning transition by using a combination of experiments in vivo (suckling rabbit model), ex vivo (Ussing chambers) and in vitro (epithelial cell lines and organoids). The microbiota composition, its metabolic activity, para-cellular epithelial permeability and the gene expression of key components of the gut barrier shifted sharply at the onset of solid food ingestion in vivo, despite milk was still predominant in the diet at that time. We found that cecal content sterile supernatant (i.e. containing a mixture of metabolites) obtained after the onset of solid food ingestion accelerated the formation of the epithelial barrier in Caco-2 cells in vitro and our results suggested that these effects were driven by the bacterial metabolite butyrate. Moreover, the treatment of organoids with cecal content sterile supernatant partially replicated in vitro the effects of solid food ingestion on the epithelial barrier in vivo. Altogether, our results show that the metabolites produced by the microbiota at the onset of solid food ingestion contribute to the maturation of the gut barrier at the suckling-to-weaning transition. Targeting the gut microbiota metabolic activity during this key developmental window might therefore be a promising strategy to promote intestinal homeostasis.

Developmental Stage, Solid Food Introduction, and Suckling Cessation Differentially Influence the Comaturation of the Gut Microbiota and Intestinal Epithelium in Rabbits

Beaumont, . M., Mussard, É. M., Barilly, C., et al. — Tue, 01 Mar 2022 20:51:55 +0100

Background: In mammals, the establishment around weaning of a symbiotic relationship between the gut microbiota
and its host determines long-term health.
Objectives: The aim of this study was to identify the factors driving the comaturation of the gut microbiota and intestinal
epithelium at the suckling-to-weaning transition. We hypothesized that the developmental stage, solid food ingestion,
and suckling cessation contribute to this process.
Methods: From birth to day 18, Hyplus rabbits were exclusively suckling. From day 18 to day 25, rabbits were 1)
exclusively suckling; 2) suckling and ingesting solid food; or 3) exclusively ingesting solid food. The microbiota (16S
amplicon sequencing), metabolome (nuclear magnetic resonance), and epithelial gene expression (high-throughput
qPCR) were analyzed in the cecum at days 18 and 25.
Results: The microbiota structure and metabolic activity were modified with age when rabbits remained exclusively
suckling. The epithelial gene expression of nutrient transporters, proliferation markers, and innate immune factors were
also regulated with age (e.g., 1.5-fold decrease of TLR5). Solid food ingestion by suckling rabbits had a major effect on
the gut microbiota by increasing its α diversity, remodeling its structure (e.g., 6.3-fold increase of Ruminococcaceae),
and metabolic activity (e.g., 4.6-fold increase of butyrate). Solid food introduction also regulated the gene expression of
nutrient transporters, differentiation markers, and innate immune factors in the epithelium (e.g., 3-fold increase of nitric
oxide synthase). Suckling cessation had no effect on the microbiota, while it regulated the expression of genes involved
in epithelial differentiation and immunoglobulin transport (e.g., 2.5-increase of the polymeric immunoglobulin receptor).
Conclusions: In rabbits, the maturation of the microbiota at the suckling-to-weaning transition is driven by the
introduction of solid food and, to a lesser extent, by the developmental stage. In contrast, the maturation of the
intestinal epithelium at the suckling-to-weaning transition is under the influence of the developmental stage, solid food
introduction, and suckling cessation. J Nutr 2022;152:723–736.

Forlænget laktation

Krogh, M. A., Thorup, V. M. — Tue, 27 Feb 2024 20:51:55 +0100

Ensiling sugar beets

Hvas, E. M. V., Larsen, M., Andersen, L., Bedenk, U., Weisbjerg, M. R. — Sun, 01 Dec 2024 20:51:55 +0100

Co-ensiling beets with other feeds allows for year-round feeding of beets and reduces the risk of dry matter (DM) loss as effluent from the silage. This study aimed to evaluate the effect of co-ensiling high DM beets with maize and grass/clover silage, grass seed straw, fresh beet pulp, and high DM concentrates (dried beet pulp, wheat distillers’ grain solubles; DDGS, wheat bran, rapeseed meal, sunflower meal, soybean hulls, and maize gluten feed) on gaseous weight loss (GWL), loss of effluents, and silage quality. Beets from harvest year 2021 were used to produce two sets of silages in laboratory silos, resulting in a total of 2 pure beet silages and 12 mixed beets silages. GWL was measured by weighing the laboratory silos until 181 days of ensiling. Fermentation was terminated by freezing after 30, 92, and 181 days of ensiling where loss of effluent was also measured. Total GWL was highest in the two pure beet silages (mean ± SEM; 282 ± 5.47 and 250 ± 7.94 g/kg DM, respectively), and differed among the mixed silages depending on mixer feed. Effluent was only observed in the pure beet silage in Set 1. Silage DM content at 181 days of ensiling was lowest for the two pure beet silages (180 ± 10.9 and 165 ± 5.95 g/kg). For all silages, pH was below 4.25 by 30 days of ensiling. Ethanol concentrations at 181 days of ensiling were highest in the two pure beet silages (345 ± 11.5 and 287 ± 11.8 g/kg DM). L-lactate content of pure beet silages was 38.4 ± 1.85 and 31.1 ± 1.21 g/kg DM at 181 days of ensiling. In Set 1, L-lactate content was lower in beets ensiled with maize silage, grass seed straw, dried beet pulp, or DDGS compared to pure beet silage. In Set 2, L-lactate content was higher in beets ensiled with maize gluten feed compared to pure beet silage. Silage concentration of NH₃ varied depending on mixer feed. The NH₃ content at 181 days of ensiling was 0.817 ± 0.626 and 2.05 ± 0.601 g/kg DM for pure beet silages and was highest in beets ensiled with grass/clover silage in both silage sets (16.4 ± 0.63 and 17.6 ± 0.60 g/kg DM). Co-ensiling beets with forages, high DM concentrates, and protein-rich feeds included in this study lowered fermentation weight loss, eliminated the loss of effluent, and resulted in silages of good fermentation quality.

Human physiological responses to different types of human-dog interactions

Fri, 01 Nov 2024 20:51:55 +0100

Previous studies of human-dog interventions vary in terms of type of interaction, which is rarely quantified, leading to contradictory findings and limited comparability. To uncover the influence of different types of interactions, the present study investigated if it was possible to detect differences in immediate physiological measurements of healthy humans during different standardised types of interaction with a dog. Thirty-three healthy participants (women = 25, men = 8, >18 years) were exposed to four different test situations with standardised types of interaction intensity with a dog in random order: no dog present (CONTROL), looking at a dog (VISUAL), petting a dog (TACTILE) or performing tricks with a dog (ACTIVE). Each test situation lasted 10 min with a 30-min break between each. Heart rate (HR), heart rate variability (HRV) and skin conductance (tonic level (SCL) and peak counts (SCR)) were continuously recorded. Blood pressure (BP) and salivary cortisol (s-cortisol) were measured before and after each test situation. Linear Mixed Models were applied. HR, HRV, BP, SCL and SCR increased with increased interaction with the dog (for all: p < 0.001). HRV increased with decreased HR (p = 0.002), increased SCL (p = 0.027), and SCR (p < 0.001) depending on the type of interaction. Generally, s-cortisol increased with increased HR (p = 0.042), SCL increased with increased SCR (p < 0.001), and SCR increased with increased HRV (p = 0.013), depending on type of interaction. The physiological measurements HR, HRV, BP, SCL and SCR are influenced by different types of dog interaction, and thus it is important to quantify and report the type of interaction in human-dog interaction studies. (ClinicalTrials.gov ID:NCT04696419).

Chapter 13: Precision Livestock Farming

Larsen, M. L. V., Pedersen, L. J., Norton, T. — Thu, 01 Aug 2024 20:51:55 +0200

On-farm animal welfare assessment in slaughter pigs across different production systems in four European countries

Larsen, M. L. V., Pedersen, L. J., Rousing, T. — Sun, 01 Sep 2024 20:51:55 +0200

At forstå dyrs ubehag

Lærke, H. N. — Tue, 10 Sep 2024 20:51:55 +0200

Application of on-farm computer vision for development, improvement and validation of motion sensor ear tags to monitor welfare and health for sows

Bahnsen, I., Pedersen, J.R., Schrøder-Petersen, D.L., et al. — Fri, 13 Sep 2024 20:51:55 +0200

Validity and reliability of the animal-based measures of welfare protocols in finisher pigs

Coutant, M. P., Rousing, T., Pedersen, L. J., Larsen, M. L. V. — Fri, 13 Sep 2024 20:51:55 +0200

Prediction of nutritional content of black soldier fly (BSF) larvae using multispectral imaging

Gebreyesus, G., Jensen, K., Luca, A. — Mon, 01 Jan 2024 20:51:55 +0100

The economic viability of BSF production for livestock and pet nutrition heavily relies on the nutritional composition of its larvae, notably protein and fat content, influenced by diet, harvest age, and genetics. Maintaining consistent product quality necessitates continuous monitoring across larvae developmental stages. Selective breeding also offers potential for enhancing BSF larvae’s nutritional profile, requiring phenotypic data from potential live candidates. Conventional chemometric methods, while accurate, are costly, time-consuming, and destructive, hindering their suitability for live larvae phenotyping. Hence, there’s a pressing need for rapid, non-destructive, and cost-effective techniques to evaluate the nutritional content at different stages of the BSF larvae. Recently, spectral imaging has emerged as a powerful tool for food quality assessment, capturing both spectral and spatial data simultaneously. This study explores the potential of multispectral imaging in predicting individual BSF larvae’s nutritional content. With 71 larvae sampled and imaged, prediction models, employing 19 wave bands as features via PLS, exhibited promising predictive performance for lipid mass and lipid percent. With reasonable correlation between measured and predicted parameters for a test set of 21 larvae, the study demonstrates the promise of multispectral imaging in predicting individual larvae’s nutritional content, offering avenues for future research in nutritional content prediction from live samples.

GEDI: an R package for integration of transcriptomic data from multiple high-throughput platforms

Stokholm, M.N., Rabaglino, M. B., Kadarmideen, H. — Sat, 13 Nov 2021 20:51:55 +0100

Investigation of gut microbiome association with inflammatory bowel disease and depression: a machine learning approach

Morell Miranda, P., Bertolini, F., Kadarmideen, H. — Fri, 19 Apr 2019 20:51:55 +0200

Systems genomics using next-generation sequencing methods

Mazzoni, G., Kogelman, L. J. A., Suravajhala, P., Kadarmideen, H. — Wed, 01 Jul 2015 20:51:55 +0200

Molecular characterization of two common Chadian cattle breeds

Flury, C., Ngandolo, B.N.R., Muller, B., Zinsstag, J., Kadarmideen, H. — Thu, 01 Jan 2009 20:51:56 +0100

Multi-Variate Genetic Evaluations of Body Condition and Milk Production in Dairy Cows

Kadarmideen, H. — Sat, 01 Jan 2005 20:51:56 +0100

Generalized marker regression and interval QTL mapping methods for binary traits in half-sib family designs

Kadarmideen, H., Dekkers, J.C.M — Sat, 12 Jan 2002 20:51:56 +0100

Genetic and economic relationships between somatic cell count and clinical mastitis and their use in selection for mastitis resistance in dairy cattle

Kadarmideen, H., Pryce, J.E. — Wed, 01 Aug 2001 20:51:56 +0200

Controlled and polygynous mating in the black soldier fly: advancing breeding programs through quantitative genetic designs

Jensen, K., Thormose, S. F., Noer, N. K. ., et al. — Mon, 01 Jan 2024 20:51:56 +0100

GeneDMRs

Wang, X., Hao, D., Kadarmideen, H. N. — Mon, 01 Mar 2021 20:51:56 +0100

DNA methylation in gene or gene body could influence gene transcription. Moreover, methylation in gene regions along with CpG island regions could modulate the transcription to undetectable gene expression levels. Therefore, it is necessary to investigate the methylation levels within the gene, gene body, CpG island regions, and their overlapped regions and then identify the gene-based differentially methylated regions (GeneDMRs). In this study, R package GeneDMRs aims to facilitate computing gene-based methylation rate using next-generation sequencing-based methylome data. The user-friendly GeneDMRs package is presented to analyze the methylation levels in each gene/promoter/exon/intron/CpG island/CpG island shore or each overlapped region (e.g., gene-CpG island/promoter-CpG island/exon-CpG island/intron-CpG island/gene-CpG island shore/promoter-CpG island shore/exon-CpG island shore/intron-CpG island shore). GeneDMRs can also interpret complex interplays between methylation levels and gene expression differences or similarities across physiological conditions or disease states. We used the public reduced representation bisulfite sequencing data of mouse (GSE62392) for evaluating software and revealing novel biologically significant results to supplement the previous research. In addition, the whole-genome bisulfite sequencing data of cattle (GSE106538) given the much larger size was used for further evaluation.

Building gene co-expression networks using transcriptomics data for systems biology investigations

Kadarmideen, H. N., Watson-Haigh, N. S. — Sun, 01 Jan 2012 20:51:56 +0100

Gene co-expression networks (GCN), built using high-throughput gene expression data are fundamental aspects of systems biology. The main aims of this study were to compare two popular approaches to building and analysing GCN. We use real ovine microarray transcriptomics datasets representing four different treatments with Metyrapone, an inhibitor of cortisol biosynthesis. We conducted several microarray quality control checks before applying GCN methods to filtered datasets. Then we compared the outputs of two methods using connectivity as a criterion, as it measures how well a node (gene) is connected within a network. The two GCN construction methods used were, Weighted Gene Co-expression Network Analysis (WGCNA) and Partial Correlation and Information Theory (PCIT) methods. Nodes were ranked based on their connectivity measures in each of the four different networks created by WGCNA and PCIT and node ranks in two methods were compared to identify those nodes which are highly differentially ranked (HDR). A total of 1,017 HDR nodes were identified across one or more of four networks. We investigated HDR nodes by gene enrichment analyses in relation to their biological relevance to phenotypes. We observed that, in contrast to WGCNA method, PCIT algorithm removes many of the edges of the most highly interconnected nodes. Removal of edges of most highly connected nodes or hub genes will have consequences for downstream analyses and biological interpretations. In general, for large GCN construction (with > 20000 genes) access to large computer clusters, particularly those with larger amounts of shared memory is recommended.

Genetic parameters for different measures of feed efficiency and related traits in boars of three pig breeds

Do, D. N., Strathe, A. B., Jensen, J., Mark, T., Kadarmideen, H. N. — Sun, 01 Sep 2013 20:51:56 +0200

Residual feed intake (RFI) is commonly used as a measure of feed efficiency at a given level of production. A total of 16,872 pigs with their pedigree traced back as far as possible was used to estimate genetic parameters for RFI, growth performance, food conversion ratio (FCR), body conformation, and feeding behavior traits in 3 Danish breeds [Duroc (DD), Landrace (LL), and Yorkshire (YY)]. Two measures of RFI were considered: residual feed intake 1 (RFI1) was calculated based on regression of daily feed intake (DFI) from 30 to 100 kg on initial test weight and ADG from 30 to 100 kg (ADG2). Residual feed intake 2 (RFI2) was as RFI1, except it was also regressed with respect to backfat (BF). The estimated heritabilities for RFI1 and RFI2 were 0.34 and 0.38 in DD, 0.34 and 0.36 in LL, and 0.39 and 0.40 in YY, respectively. The heritabilities ranged from 0.32 (DD) to 0.54 (LL) for ADG2, from 0.54 (DD) to 0.67 (LL) for BF, and from 0.13 (DD) to 0.19 (YY) for body conformation. Feeding behavior traits including DFI, number of visits to feeder per day (NVD), total time spent eating per day (TPD), feed intake rate (FR), feed intake per visit (FPV), and time spent eating per visit (TPV) were moderately to highly heritable. Residual feed intake 2 was genetically independent of ADG2 and BF in all breeds, except it had low genetic correlation to ADG2 in YY (0.2). Residual feed intake 1 was also genetically independent of ADG2 in DD and LL. Both RFI traits had strong genetic correlations with DFI (0.85 to 0.96) and FCR (0.76 to 0.99). They had low or no genetic correlations with feeding behavior traits. Unfavorable genetic correlations were found between ADG2 and both BF and DFI. Among feeding behavior traits, DFI had low genetic correlations to other traits in all breeds. High and negative genetic correlations were also found between TPD with FR (-0.79 in YY to -0.88 in DD), NVD, and TPD (-0.91 in DD to -0.94 in YY) and between NVD and FPV (-0.83 in DD to -0.91 in YY) in all breeds. The genetic trend for feed efficiency was favorable in all breeds regardless of the definition of feed efficiency used. In summary, RFI1 and RFI2 were heritable and selection for reduced RFI2 can be performed without adversely affecting ADG and BF and could replace FCR in the selection index for the Danish pig breeds. Selection could also be based on RFI1 for breeds with fewer concerns about a negative effect of BF or for breeds that do not have BF records.

Proximity loggers

Watson-Haigh, N. S., O'Neill, C. J., Kadarmideen, H. N. — Sun, 01 Jan 2012 20:51:56 +0100

Proximity loggers are a novel biotelemetry device used for quantifying animal-animal interactions in a non-invasive way. Such data has been used for studying a range of interactions from disease spread among badgers and cattle to quantifying cow-calf interactions. Such quantitative behavioral traits could be used for the purpose of selective breeding in domesticated animals. With the use of real data, from the study of oestrus behavior in cattle populations raised in an extensive grazing system, we have identified poor reciprocal agreement (RA) as a source of variation. To date, RA has not been adequately considered or addressed and can have serious implications for further analyses aimed at correctly quantifying and interpreting social behavior. We provide a database schema for storing the millions of contact records produced by proximity loggers and programming functions, for use in the statistical programming language R, for performing raw data quality control, data import, database queries and classification of RA between proximity logger pairs. Poor RA leads to a lack of confidence in the data recorded by a pair of loggers. At best, substantial noise is added to the data set and at worst can lead to over or under estimation of contacts between pairs of animals. Over successive deployments, the identification and removal of loggers consistently involved in poor RA pairs can improve the level of agreement and confidence in the recorded data. This is a necessity for the accurate estimation of genetic parameters based on proximity logger data.

Genetical systems biology in livestock

Kadarmideen, H. N. — Tue, 01 Jan 2008 20:51:56 +0100

Genetical systems biology or systems genetics treats the genome as the central reference point for all omics variations and is an emerging new branch of systems biology. Quantitative genetic principles were developed for high-throughput genomic, transcriptomic and metabolomic data observed in large populations. New statistical genetic models were developed for expression quantitative trait loci (eQTL), namely, marker regression eQTL mapping and marker-expression co-factor mapping. Evaluations of power to detect eQTL showed that sample size requirements are higher for detecting trans-acting genes than cis-acting genes. Power is higher for eQTL with high heritability than for eQTL with low heritability. These results will be valuable for systems genetic investigations. Gonadotrophin releasing hormone (GnRH) and its receptor gene (GnRH-R) are crucial for mammalian reproduction. Whole genome scan of eQTLs for GnRH-R gene expression in mouse showed three possible trans-eQTL regions on chr 13 and 19, harbouring regulatory genes. Applications of genetical genomics in systems biology were identified as: (1) detection and validation of causal gene for complex traits; (2) development of genetic interaction networks; (3) prediction of transcription factor binding sites and (4) in data-driven systems biology. These applications were illustrated using data on eQTL, protein network and signalling pathways for GnRH. Gpr54 (G protein-coupled receptor kinase 54), Prl (prolactin), Ins1 (insulin) and Fos (viral oncogenes) were found to be major regulators of GnRH and GnRH-R; thus validating their important role in reproduction, mammary gland development and sexual (im)maturity. These results will be useful for further study of mammalian reproductive biology.

Preface

Kadarmideen, H. N. — Fri, 01 Jan 2016 20:51:56 +0100

Population and systems genetics analyses of cortisol in pigs divergently selected for stress (Physiological Genomics 2007, 29 (57-65) DOI: 10.1152/physiolgenomics.00144.2006)

Kadarmideen, H. N., Janss, L. L.G. — Fri, 01 May 2009 20:51:56 +0200

Validation of genome-wide intervertebral disk calcification associations in Dachshund and further investigation of the chromosome 12 susceptibility locus

Mogensen, M. S., Scheibye-Alsing, K., Karlskov-Mortensen, P., et al. — Sun, 01 Jan 2012 20:51:56 +0100

Herniation of the intervertebral disk is a common cause of neurological dysfunction in the dog, particularly in the Dachshund. Using the Illumina CanineHD BeadChip, we have previously identified a major locus on canine chromosome 12 nucleotide positions 36,750,205-38,524,449 that strongly associates with intervertebral disk calcification in Danish wire-haired Dachshunds. In this study, targeted resequencing identified two synonymous variants in MB21 D1 and one in the 5′-untranslated region of KCNQ5 that associates with intervertebral disk calcification in an independent sample of wire-haired Dachshunds. Haploview identified seven linkage disequilibrium blocks across the disease-associated region. The effect of haplotype windows on disk calcification shows that all haplotype windows are significantly associated with disk calcification. However, our predictions imply that the causal variant(s) are most likely to be found between nucleotide 36,750,205-37,494,845 as this region explains the highest proportion of variance in the dataset. Finally, we develop a risk prediction model for wire-haired Dachshunds. We validated the association of the chromosome 12 locus with disk calcification in an independent sample of wire-haired Dachshunds and identify potential risk variants. Additionally, we estimated haplotype effects and set up a model for prediction of disk calcifications in wire-haired Dachshunds based on genotype data. This genetic prediction model may prove useful in selection of breeding animals in future breeding programs.

An F2 pig resource population as a model for genetic studies of obesity and obesity-related diseases in humans

Kogelman, L. J.A., Kadarmideen, H. N., Mark, T., et al. — Tue, 01 Jan 2013 20:51:56 +0100

Obesity is a rising worldwide public health problem. Difficulties to precisely measure various obesity traits and the genetic heterogeneity in human have been major impediments to completely disentangle genetic factors causing obesity. The pig is a relevant model for studying human obesity and obesity-related (OOR) traits. Using founder breeds divergent with respect to obesity traits we have created an F2 pig resource population (454 pigs), which has been intensively phenotyped for 36 OOR traits. The main rationale for our study is to characterize the genetic architecture of OOR traits in the F2 pig design, by estimating heritabilities, genetic, and phenotypic correlations using mixed-and multi-trait BLUP animal models. Our analyses revealed high coefficients of variation (15-42%) and moderate to high heritabilities (0.22-0.81) in fatness traits, showing large phenotypic and genetic variation in the F2 population, respectively. This fulfills the purpose of creating a resource population divergent for OOR traits. Strong genetic correlations were found between weight and lean mass at dual-energy x-ray absorptiometry scanning (0.56-0.97). Weight and conformation also showed strong genetic correlations with slaughter traits (e.g., rg between abdominal circumference and leaf fat at slaughtering: 0.66). Genetic correlations between fat-related traits and the glucose level vary between 0.35 and 0.74 and show a strong correlation between adipose tissue and impaired glucose metabolism. Our power calculations showed a minimum of 80% power for QTL detection for all phenotypes. We revealed genetic correlations at population level, for the first time, for several difficult to measure and novel OOR traits and diseases. The results underpin the potential of the established F2 pig resource population for further genomic, systems genetics, and functional investigations to unravel the genetic background of OOR traits.

An integrative systems genetics approach reveals potential causal genes and pathways related to obesity

Kogelman, L. J.A., Zhernakova, D. V., Westra, H. J., et al. — Tue, 20 Oct 2015 20:51:56 +0200

Background: Obesity is a multi-factorial health problem in which genetic factors play an important role. Limited results have been obtained in single-gene studies using either genomic or transcriptomic data. RNA sequencing technology has shown its potential in gaining accurate knowledge about the transcriptome, and may reveal novel genes affecting complex diseases. Integration of genomic and transcriptomic variation (expression quantitative trait loci [eQTL] mapping) has identified causal variants that affect complex diseases. We integrated transcriptomic data from adipose tissue and genomic data from a porcine model to investigate the mechanisms involved in obesity using a systems genetics approach. Methods: Using a selective gene expression profiling approach, we selected 36 animals based on a previously created genomic Obesity Index for RNA sequencing of subcutaneous adipose tissue. Differential expression analysis was performed using the Obesity Index as a continuous variable in a linear model. eQTL mapping was then performed to integrate 60K porcine SNP chip data with the RNA sequencing data. Results were restricted based on genome-wide significant single nucleotide polymorphisms, detected differentially expressed genes, and previously detected co-expressed gene modules. Further data integration was performed by detecting co-expression patterns among eQTLs and integration with protein data. Results: Differential expression analysis of RNA sequencing data revealed 458 differentially expressed genes. The eQTL mapping resulted in 987 cis-eQTLs and 73 trans-eQTLs (false discovery rate < 0.05), of which the cis-eQTLs were associated with metabolic pathways. We reduced the eQTL search space by focusing on differentially expressed and co-expressed genes and disease-associated single nucleotide polymorphisms to detect obesity-related genes and pathways. Building a co-expression network using eQTLs resulted in the detection of a module strongly associated with lipid pathways. Furthermore, we detected several obesity candidate genes, for example, ENPP1, CTSL, and ABHD12B. Conclusions: To our knowledge, this is the first study to perform an integrated genomics and transcriptomics (eQTL) study using, and modeling, genomic and subcutaneous adipose tissue RNA sequencing data on obesity in a porcine model. We detected several pathways and potential causal genes for obesity. Further validation and investigation may reveal their exact function and association with obesity.

Liver transcriptomic networks reveal main biological processes associated with feed efficiency in beef cattle

Alexandre, P. A., Kogelman, L. J.A., Santana, M. H.A., et al. — Fri, 18 Dec 2015 20:51:56 +0100

Background: The selection of beef cattle for feed efficiency (FE) traits is very important not only for productive and economic efficiency but also for reduced environmental impact of livestock. Considering that FE is multifactorial and expensive to measure, the aim of this study was to identify biological functions and regulatory genes associated with this phenotype. Results: Eight genes were differentially expressed between high and low feed efficient animals (HFE and LFE, respectively). Co-expression analyses identified 34 gene modules of which 4 were strongly associated with FE traits. They were mainly enriched for inflammatory response or inflammation-related terms. We also identified 463 differentially co-expressed genes which were functionally enriched for immune response and lipid metabolism. A total of 8 key regulators of gene expression profiles affecting FE were found. The LFE animals had higher feed intake and increased subcutaneous and visceral fat deposition. In addition, LFE animals showed higher levels of serum cholesterol and liver injury biomarker GGT. Histopathology of the liver showed higher percentage of periportal inflammation with mononuclear infiltrate. Conclusion: Liver transcriptomic network analysis coupled with other results demonstrated that LFE animals present altered lipid metabolism and increased hepatic periportal lesions associated with an inflammatory response composed mainly by mononuclear cells. We are now focusing to identify the causes of increased liver lesions in LFE animals.

Genome-wide association study reveals genetic architecture of eating behavior in pigs and its implications for humans obesity by comparative mapping.

Tue, 01 Jan 2013 20:51:56 +0100

This study was aimed at identifying genomic regions controlling feeding behavior in Danish Duroc boars and its potential implications for eating behavior in humans. Data regarding individual daily feed intake (DFI), total daily time spent in feeder (TPD), number of daily visits to feeder (NVD), average duration of each visit (TPV), mean feed intake per visit (FPV) and mean feed intake rate (FR) were available for 1130 boars. All boars were genotyped using the Illumina Porcine SNP60 BeadChip. The association analyses were performed using the GenABEL package in the R program. Sixteen SNPs were found to have moderate genome-wide significance (p<5E-05) and 76 SNPs had suggestive (p<5E-04) association with feeding behavior traits. MSI2 gene on chromosome (SSC) 14 was very strongly associated with NVD. Thirty-six SNPs were located in genome regions where QTLs have previously been reported for behavior and/or feed intake traits in pigs. The regions: 64-65 Mb on SSC 1, 124-130 Mb on SSC 8, 63-68 Mb on SSC 11, 32-39 Mb and 59-60 Mb on SSC 12 harbored several signifcant SNPs. Synapse genes (GABRR2, PPP1R9B, SYT1, GABRR1, CADPS2, DLGAP2 and GOPC), dephosphorylation genes (PPM1E, DAPP1, PTPN18, PTPRZ1, PTPN4, MTMR4 and RNGTT) and positive regulation of peptide secretion genes (GHRH, NNAT and TCF7L2) were highly significantly associated with feeding behavior traits. This is the first GWAS to identify genetic variants and biological mechanisms for eating behavior in pigs and these results are important for genetic improvement of pig feed efficiency. We have also conducted pig-human comparative gene mapping to reveal key genomic regions and/or genes on the human genome that may influence eating behavior in human beings and consequently affect the development of obesity and metabolic syndrome. This is the first translational genomics study of its kind to report potential candidate genes for eating behavior in humans.

PCIT

Watson-Haigh, N. S., Kadarmideen, H. N., Reverter, A. — Wed, 09 Dec 2009 20:51:56 +0100

We make the PCIT algorithm, used for detecting meaningful gene-gene associations in co-expression networks, available as an R package. Automatic detection of a suitable parallel environment is used such that scripts are portable between parallel and non-parallel environments with no modification of the script. Availability and implementation: Source code and binaries freely available (under GPL-3) for download via CRAN at http://cran.rproject. org/package=PCIT, implemented in R and supported on Linux and MS Windows. Contact: nathan.watson-haigh@csiro.au

Copy number variations and genome-wide associations reveal putative genes and metabolic pathways involved with the feed conversion ratio in beef cattle

de Almeida Santana, M. H., Junior, G. A. O., Cesar, A. S. M., et al. — Tue, 01 Nov 2016 20:51:56 +0100

The use of genome-wide association results combined with other genomic approaches may uncover genes and metabolic pathways related to complex traits. In this study, the phenotypic and genotypic data of 1475 Nellore (Bos indicus) cattle and 941,033 single nucleotide polymorphisms (SNPs) were used for genome-wide association study (GWAS) and copy number variations (CNVs) analysis in order to identify candidate genes and putative pathways involved with the feed conversion ratio (FCR). The GWAS was based on the Bayes B approach analyzing genomic windows with multiple regression models to estimate the proportion of genetic variance explained by each window. The CNVs were detected with PennCNV software using the log R ratio and B allele frequency data. CNV regions (CNVRs) were identified with CNVRuler and a linear regression was used to associate CNVRs and the FCR. Functional annotation of associated genomic regions was performed with the Database for Annotation, Visualization and Integrated Discovery (DAVID) and the metabolic pathways were obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG). We showed five genomic windows distributed over chromosomes 4, 6, 7, 8, and 24 that explain 12 % of the total genetic variance for FCR, and detected 12 CNVRs (chromosomes 1, 5, 7, 10, and 12) significantly associated [false discovery rate (FDR) < 0.05] with the FCR. Significant genomic regions (GWAS and CNV) harbor candidate genes involved in pathways related to energetic, lipid, and protein metabolism. The metabolic pathways found in this study are related to processes directly connected to feed efficiency in beef cattle. It was observed that, even though different genomic regions and genes were found between the two approaches (GWAS and CNV), the metabolic processes covered were related to each other. Therefore, a combination of the approaches complement each other and lead to a better understanding of the FCR.

Late gestation under- and overnutrition have differential impacts when combined with a post-natal obesogenic diet on glucose-lactate-insulin adaptations during metabolic challenges in adolescent sheep

Khanal, P., Axel, A. M.D., Kongsted, A. H., et al. — Sun, 01 Feb 2015 20:51:56 +0100

Aim: To determine whether late gestation under- and overnutrition programme metabolic plasticity in a similar way, and whether metabolic responses to an obesogenic diet in early post-natal life depend on the foetal nutrition history. Methods: In a 3 × 2 factorial design, twin-pregnant ewes were for the last 6 weeks of gestation (term = 147 days) assigned to HIGH (N = 13; 150 and 110% of energy and protein requirements, respectively), NORM (N = 9; 100% of requirements) or LOW (N = 14; 50% of requirements) diets. The twin offspring were raised on high-carbohydrate-high-fat (HCHF; N = 35) or conventional (CONV; N = 35) diets from 3 days to 6 months of age (around puberty). Then intravenous glucose (GTT; overnight fasted), insulin (ITT; fed) and propionate (gluconeogenetic precursor; PTT; both fed and fasted) tolerance tests were conducted to evaluate (hepatic) metabolic plasticity. Results: Prenatal malnutrition differentially impacted adaptations of particularly plasma lactate followed by glucose, cholesterol and insulin. This was most clearly expressed during PTT in fasted lambs and much less during ITT and GTT. In fasted lambs, propionate induced more dramatic increases in lactate than glucose, and HIGH lambs became more hyperglycaemic, hyperlactataemic and secreted less insulin compared to the hypercholesterolaemic LOW lambs. Propionate-induced insulin secretion was virtually abolished in fasted HCHF lambs, but upregulated in fasted compared to fed CONV lambs. HCHF lambs had the greatest glucose-induced insulin secretory responses. Conclusion: Prenatal malnutrition differentially programmed glucose-lactate metabolic pathways and cholesterol homeostasis. Prenatal overnutrition predisposed for hyperglycaemia and hyperlactataemia, whereas undernutrition predisposed for hypercholesterolaemia upon exposure to an obesogenic diet. Prenatal overnutrition (not undernutrition) interfered with pancreatic insulin secretion by non-glucose-dependent mechanisms.

Application of multi-omics data integration and machine learning approaches to identify epigenetic and transcriptomic differences between in vitro and in vivo produced bovine embryos

Rabaglino, M. B., O’Doherty, A., Secher, J. B. M., et al. — Sat, 01 May 2021 20:51:56 +0200

Pregnancy rates for in vitro produced (IVP) embryos are usually lower than for embryos produced in vivo after ovarian superovulation (MOET). This is potentially due to alterations in their trophectoderm (TE), the outermost layer in physical contact with the maternal endometrium. The main objective was to apply a multi-omics data integration approach to identify both temporally differentially expressed and differentially methylated genes (DEG and DMG), between IVP and MOET embryos, that could impact TE function. To start, four and five published transcriptomic and epigenomic datasets, respectively, were processed for data integration. Second, DEG from day 7 to days 13 and 16 and DMG from day 7 to day 17 were determined in the TE from IVP vs. MOET embryos. Third, genes that were both DE and DM were subjected to hierarchical clustering and functional enrichment analysis. Finally, findings were validated through a machine learning approach with two additional datasets from day 15 embryos. There were 1535 DEG and 6360 DMG, with 490 overlapped genes, whose expression profiles at days 13 and 16 resulted in three main clusters. Cluster 1 (188) and Cluster 2 (191) genes were down-regulated at day 13 or day 16, respectively, while Cluster 3 genes (111) were up-regulated at both days, in IVP embryos compared to MOET embryos. The top enriched terms were the KEGG pathway "focal adhesion" in Cluster 1 (FDR = 0.003), and the cellular component: "extracellular exosome" in Cluster 2 (FDR<0.0001), also enriched in Cluster 1 (FDR = 0.04). According to the machine learning approach, genes in Cluster 1 showed a similar expression pattern between IVP and less developed (short) MOET conceptuses; and between MOET and DKK1-treated (advanced) IVP conceptuses. In conclusion, these results suggest that early conceptuses derived from IVP embryos exhibit epigenomic and transcriptomic changes that later affect its elongation and focal adhesion, impairing post-transfer survival.

Expression studies of six human obesity-related genes in seven tissues from divergent pig breeds

Cirera, S., Jensen, M. S., Elbrønd, V. S., et al. — Sat, 01 Feb 2014 20:51:56 +0100

Obesity has reached epidemic proportions globally and has become the cause of several major health risks worldwide. Presently, more than 100 loci have been related to obesity and metabolic traits in humans by genome-wide association studies. The complex genetic architecture behind obesity has triggered a need for the development of better animal models than rodents. The pig has emerged as a very promising biomedical model to study human obesity traits. In this study, we have characterized the expression patterns of six obesity-related genes, leptin (LEP), leptin receptor (LEPR), melanocortin 4 receptor (MC4R), fat mass and obesity associated (FTO), neuronal growth regulator 1 (NEGR)1 and adiponectin (ADIPOQ), in seven obesity-relevant tissues (liver; muscle; pancreas; hypothalamus; and retroperitoneal, subcutaneous and mesenteric adipose tissues) in two pig breeds (production pigs and Göttingen minipigs) that deviate phenotypically and genetically from each other with respect to obesity traits. We observe significant differential expression for LEP, LEPR and ADIPOQ in muscle and in all three adipose tissues. Interestingly, in pancreas, LEP expression is only detected in the fat minipigs. FTO shows significant differential expression in all tissues analyzed, and NEGR1 shows significant differential expression in muscle, pancreas, hypothalamus and subcutaneous adipose tissue. The MC4R transcript can be detected only in hypothalamus. In general, the expression profiles of the investigated genes are in accordance with those observed in human studies. Our study shows that both the differences between the investigated breeds and the phenotypic state with respect to obesity/leanness play a large role for differential expression of the obesity-related genes.

Systems biology in animal production and health, vol. 2

Kadarmideen, H. N. — Fri, 01 Jan 2016 20:51:56 +0100

This two-volume work provides an overview on various state of the art experimental and statistical methods, modeling approaches and software tools that are available to generate, integrate and analyze multi-omics datasets in order to detect biomarkers, genetic markers and potential causal genes for improved animal production and health. The book will contain online resources where additional data and programs can be accessed. Some chapters also come with computer programming codes and example datasets to provide readers hands-on (computer) exercises. This second volume deals with integrated modeling and analyses of multi-omics datasets from theoretical and computational approaches and presents their applications in animal production and health as well as veterinary medicine to improve diagnosis, prevention and treatment of animal diseases. This book is suitable for both students and teachers in animal sciences and veterinary medicine as well as to researchers in this discipline.

Genetic variations (eQTLs) in muscle transcriptome and mitochondrial genes, and trans-eQTL molecular pathways in feed efficiency from Danish breeding pigs

Carmelo, V. A.O., Kadarmideen, H. N. — Tue, 01 Sep 2020 20:51:56 +0200

Feed efficiency (FE) is a key trait in pig production, as improvement in FE has positive economic and environmental impact. FE is a complex phenotype and testing animals for FE is costly. Therefore, there has been a desire to find functionally relevant single nucleotide polymorphisms (SNPs) as biomarkers, to improve our biological understanding of FE as well as accuracy of genomic prediction for FE. We have performed a cis- and trans- eQTL (expression quantitative trait loci) analysis, in a population of Danbred Durocs (N = 11) and Danbred Landrace (N = 27) using both a linear and ANOVA model based on muscle tissue RNA-seq. We analyzed a total of 1425x19179 or 2.7x10⁷ Gene-SNP combinations in eQTL detection models for FE. The 1425 genes were from RNA-Seq based differential gene expression analyses using 25880 genes related to FE and additionally combined with mitochondrial genes. The 19179 SNPs were from applying stringent quality control and linkage disequilibrium filtering on genotype data using a GGP Porcine HD 70k SNP array. We applied 1000 fold bootstrapping and enrichment analysis to further validate and analyze our detected eQTLs. We identified 13 eQTLs with FDR < 0.1, affecting several genes found in previous studies of commercial pig breeds. Examples include MYO19, CPT1B, ACSL1, IER5L, CPT1A, SUCLA2, CSRNP1, PARK7 and MFF. The bootstrapping results showed statistically significant enrichment (p-value<2.2x10^-16) of eQTLs with p-value < 0.01 in both cis and trans-eQTLs. Enrichment analysis of top trans-eQTLs revealed high enrichment for gene categories and gene ontologies associated with genomic context and expression regulation. This included transcription factors (p-value = 1.0x10^-13), DNA-binding (GO:0003677, p-value = 8.9x10^-14), DNA-binding transcription factor activity (GO:0003700,) nucleus gene (GO:0005634, p-value<2.2x10^-16), negative regulation of expression (GO:0010629, p-value<2.2x10^-16). These results would be useful for future genome assisted breeding of pigs to improve FE, and in the improved understanding of the functional mechanism of trans eQTLs.

FunctSNP

Goodswen, S. J., Gondro, C., Watson-Haigh, N. S., Kadarmideen, H. N. — Wed, 09 Jun 2010 20:51:56 +0200

Background: Whole genome association studies using highly dense single nucleotide polymorphisms (SNPs) are a set of methods to identify DNA markers associated with variation in a particular complex trait of interest. One of the main outcomes from these studies is a subset of statistically significant SNPs. Finding the potential biological functions of such SNPs can be an important step towards further use in human and agricultural populations (e.g., for identifying genes related to susceptibility to complex diseases or genes playing key roles in development or performance). The current challenge is that the information holding the clues to SNP functions is distributed across many different databases. Efficient bioinformatics tools are therefore needed to seamlessly integrate up-to-date functional information on SNPs. Many web services have arisen to meet the challenge but most work only within the framework of human medical research. Although we acknowledge the importance of human research, we identify there is a need for SNP annotation tools for other organisms.Description: We introduce an R package called FunctSNP, which is the user interface to custom built species-specific databases. The local relational databases contain SNP data together with functional annotations extracted from online resources. FunctSNP provides a unified bioinformatics resource to link SNPs with functional knowledge (e.g., genes, pathways, ontologies). We also introduce dbAutoMaker, a suite of Perl scripts, which can be scheduled to run periodically to automatically create/update the customised SNP databases. We illustrate the use of FunctSNP with a livestock example, but the approach and software tools presented here can be applied also to human and other organisms.Conclusions: Finding the potential functional significance of SNPs is important when further using the outcomes from whole genome association studies. FunctSNP is unique in that it is the only R package that links SNPs to functional annotation. FunctSNP interfaces to local SNP customised databases which can be built for any species contained in the National Center for Biotechnology Information dbSNP database.

Genetic architecture of gene expression in ovine skeletal muscle

Kogelman, L. J.A., Byrne, K., Vuocolo, T., et al. — Thu, 15 Dec 2011 20:51:56 +0100

Background: In livestock populations the genetic contribution to muscling is intensively monitored in the progeny of industry sires and used as a tool in selective breeding programs. The genes and pathways conferring this genetic merit are largely undefined. Genetic variation within a population has potential, amongst other mechanisms, to alter gene expression via cis- or trans-acting mechanisms in a manner that impacts the functional activities of specific pathways that contribute to muscling traits. By integrating sire-based genetic merit information for a muscling trait with progeny-based gene expression data we directly tested the hypothesis that there is genetic structure in the gene expression program in ovine skeletal muscle.Results: The genetic performance of six sires for a well defined muscling trait, longissimus lumborum muscle depth, was measured using extensive progeny testing and expressed as an Estimated Breeding Value by comparison with contemporary sires. Microarray gene expression data were obtained for longissimus lumborum samples taken from forty progeny of the six sires (4-8 progeny/sire). Initial unsupervised hierarchical clustering analysis revealed strong genetic architecture to the gene expression data, which also discriminated the sire-based Estimated Breeding Value for the trait. An integrated systems biology approach was then used to identify the major functional pathways contributing to the genetics of enhanced muscling by using both Estimated Breeding Value weighted gene co-expression network analysis and a differential gene co-expression network analysis. The modules of genes revealed by these analyses were enriched for a number of functional terms summarised as muscle sarcomere organisation and development, protein catabolism (proteosome), RNA processing, mitochondrial function and transcriptional regulation.Conclusions: This study has revealed strong genetic structure in the gene expression program within ovine longissimus lumborum muscle. The balance between muscle protein synthesis, at the levels of both transcription and translation control, and protein catabolism mediated by regulated proteolysis is likely to be the primary determinant of the genetic merit for the muscling trait in this sheep population. There is also evidence that high genetic merit for muscling is associated with a fibre type shift toward fast glycolytic fibres. This study provides insight into mechanisms, presumably subject to strong artificial selection, that underpin enhanced muscling in sheep populations.

Identification of co-expression gene networks, regulatory genes and pathways for obesity based on adipose tissue RNA Sequencing in a porcine model

Tue, 30 Sep 2014 20:51:56 +0200

Background: Obesity is a complex metabolic condition in strong association with various diseases, like type 2 diabetes, resulting in major public health and economic implications. Obesity is the result of environmental and genetic factors and their interactions, including genome-wide genetic interactions. Identification of co-expressed and regulatory genes in RNA extracted from relevant tissues representing lean and obese individuals provides an entry point for the identification of genes and pathways of importance to the development of obesity. The pig, an omnivorous animal, is an excellent model for human obesity, offering the possibility to study in-depth organ-level transcriptomic regulations of obesity, unfeasible in humans. Our aim was to reveal adipose tissue co-expression networks, pathways and transcriptional regulations of obesity using RNA Sequencing based systems biology approaches in a porcine model.

Methods. We selected 36 animals for RNA Sequencing from a previously created F2 pig population representing three extreme groups based on their predicted genetic risks for obesity. We applied Weighted Gene Co-expression Network Analysis (WGCNA) to detect clusters of highly co-expressed genes (modules). Additionally, regulator genes were detected using Lemon-Tree algorithms.

Results: WGCNA revealed five modules which were strongly correlated with at least one obesity-related phenotype (correlations ranging from -0.54 to 0.72, P < 0.001). Functional annotation identified pathways enlightening the association between obesity and other diseases, like osteoporosis (osteoclast differentiation, P = 1.4E^-7), and immune-related complications (e.g. Natural killer cell mediated cytotoxity, P = 3.8E^-5; B cell receptor signaling pathway, P = 7.2E^-5). Lemon-Tree identified three potential regulator genes, using confident scores, for the WGCNA module which was associated with osteoclast differentiation: CCR1, MSR1 and SI1 (probability scores respectively 95.30, 62.28, and 34.58). Moreover, detection of differentially connected genes identified various genes previously identified to be associated with obesity in humans and rodents, e.g. CSF1R and MARC2.

Conclusions: To our knowledge, this is the first study to apply systems biology approaches using porcine adipose tissue RNA-Sequencing data in a genetically characterized porcine model for obesity. We revealed complex networks, pathways, candidate and regulatory genes related to obesity, confirming the complexity of obesity and its association with immune-related disorders and osteoporosis.

Comparative analyses of QTLs influencing obesity and metabolic phenotypes in pigs and humans

Pant, S. D., Karlskov-Mortensen, P., Jacobsen, M. J., et al. — Tue, 08 Sep 2015 20:51:56 +0200

The pig is a well-known animal model used to investigate genetic and mechanistic aspects of human disease biology. They are particularly useful in the context of obesity and metabolic diseases because other widely used models (e.g. mice) do not completely recapitulate key pathophysiological features associated with these diseases in humans. Therefore, we established a F2 pig resource population (n = 564) designed to elucidate the genetics underlying obesity and metabolic phenotypes. Segregation of obesity traits was ensured by using breeds highly divergent with respect to obesity traits in the parental generation. Several obesity and metabolic phenotypes were recorded (n = 35) from birth to slaughter (242 ± 48 days), including body composition determined at about two months of age (63 ± 10 days) via dual-energy x-ray absorptiometry (DXA) scanning. All pigs were genotyped using Illumina Porcine 60k SNP Beadchip and a combined linkage disequilibrium-linkage analysis was used to identify genome-wide significant associations for collected phenotypes. We identified 229 QTLs which associated with adiposity- and metabolic phenotypes at genomewide significant levels. Subsequently comparative analyses were performed to identify the extent of overlap between previously identified QTLs in both humans and pigs. The combined analysis of a large number of obesity phenotypes has provided insight in the genetic architecture of the molecular mechanisms underlying these traits indicating that QTLs underlying similar phenotypes are clustered in the genome. Our analyses have further confirmed that genetic heterogeneity is an inherent characteristic of obesity traits most likely caused by segregation or fixation of different variants of the individual components belonging to cellular pathways in different populations. Several important genes previously associated to obesity in human studies, along with novel genes were identified. Altogether, this study provides novel insight that may further the current understanding of the molecular mechanisms underlying human obesity.

Combined genetic, genomic and transcriptomic methods in the analysis of animal traits

Kadarmideen, H. N., Reverter, A. — Sun, 01 Jul 2007 20:51:56 +0200

This paper reviews advances and current status in genetic, genomic and transcriptomic investigations of quantitative traits in livestock species and proposes possible strategies for integrating the vast amounts of information (outputs/datasets) arising from all three investigations into a systems genetics approach. This systems genetics approach is characterized by investigations of the genetic basis of -omic variations and gene regulatory/co-regulatory networks. This review is structured as follows. Genetics/genomics, transcriptomics, combined transcriptomics-genomics and, finally, systems genetics/biology. In the genetics or genomics part, we discuss current status and advances in quantitative trait loci (QTLs) mapping to fine-map multiple causative/candidate genes. We discuss the potential of single nucleotide polymorphism (SNP) genotyping arrays (e.g. Affymetrix GeneChip® arrays) to identify SNP-trait associations and fine-map QTLs to less than 0.1 cM. We provide references and resources for SNP analytical methods and tools. In the transcriptomics part, we formulate common biological questions relevant to livestock microarray gene expression profiling (MGEP) experiments to detect differentially expressed (DE) genes. In the combined transcriptomics-genomics (known as genetical genomics), we discuss detection and mapping of expression QTL (eQTL) that harbour regulatory genes for normal trait QTLs or candidate genes detected under 'genetics' and 'genomics' approaches. Illustrations from our own recent genetical genomic investigations in mouse and pigs are provided. One of the current challenges in genetical genomics is to have a coherent approach to design an experiment with due considerations for sample size and controlling false discovery rates (FDRs), while maintaining statistical power to detect eQTLs. Here we provide some concepts for the design of genetical genomics experiments with factors affecting FDR and power. This is followed by a systems biology/genetics section where we focus on combining research outputs from four different sources, namely: genetics or genomics (e.g. SNP, QTL and eQTLs), transcriptomics (e.g. DE genes, gene networks, and heritability of gene transcripts) and phenomics (e.g. phenotypes and pedigree). As a proof of principle, we provide results from systems biology/genetics approach anchored to a gene network for myogenin (MYOG), a muscle-specific transcription factor essential for the development of skeletal muscle. Using bovine expression datasets and in silico approaches, we built a gene network for MYOG that represents 35 significant connections between genes in this network. In conclusion, this paper provides strategies and tools to integrate data from genetics and -omics experiments in animals and highlighted the value of such 'systems genetics' strategy in understanding the genetics of complex traits.

Genetic parameters of infectious bovine keratoconjunctivitis and its relationship with weight and parasite infestations in Australian tropical Bos taurus cattle

Ali, A. A., Oneill, C. J., Thomson, P. C., Kadarmideen, H. N. — Sun, 01 Jan 2012 20:51:56 +0100

Background: Infectious bovine keratoconjunctivitis (IBK) or pinkeye is an economically important ocular disease that significantly impacts animal performance. Genetic parameters for IBK infection and its genetic and phenotypic correlations with cattle tick counts, number of helminth (unspecified species) eggs per gram of faeces and growth traits in Australian tropically adapted Bos taurus cattle were estimated. Methods. Animals were clinically examined for the presence of IBK infection before and after weaning when the calves were 3 to 6months and 15 to 18months old, respectively and were also recorded for tick counts, helminth eggs counts as an indicator of intestinal parasites and live weights at several ages including 18months. Results: Negative genetic correlations were estimated between IBK incidence and weight traits for animals in pre-weaning and post-weaning datasets. Genetic correlations among weight measurements were positive, with moderate to high values. Genetic correlations of IBK incidence with tick counts were positive for the pre-weaning and negative for the post-weaning datasets but negative with helminth eggs counts for the pre-weaning dataset and slightly positive for the post-weaning dataset. Genetic correlations between tick and helminth eggs counts were moderate and positive for both datasets. Phenotypic correlations of IBK incidence with helminth eggs per gram of faeces were moderate and positive for both datasets, but were close to zero for both datasets with tick counts. Conclusions: Our results suggest that genetic selection against IBK incidence in tropical cattle is feasible and that calves genetically prone to acquire IBK infection could also be genetically prone to have a slower growth. The positive genetic correlations among weight traits and between tick and helminth eggs counts suggest that they are controlled by common genes (with pleiotropic effects). Genetic correlations between IBK incidence and tick and helminth egg counts were moderate and opposite between pre-weaning and post-weaning datasets, suggesting that the environmental and (or) maternal effects differ between these two growth phases. This preliminary study provides estimated genetic parameters for IBK incidence, which could be used to design selection and breeding programs for tropical adaptation in beef cattle.

Evolutionary process of Bos taurus cattle in favourable versus unfavourable environments and its implications for genetic selection

O'Neill, C. J., Swain, D. L., Kadarmideen, H. N. — Wed, 01 Sep 2010 20:51:56 +0200

The evolutionary processes that have enabled Bos taurus cattle to establish around the globe are at the core to the future success of livestock production. Our study focuses on the history of cattle domestication including the last 60years of B.taurus breeding programmes in both favourable and unfavourable environments and its consequences on evolution and fitness of cattle. We discuss the emergence of 'production diseases' in temperate production systems and consider the evolutionary genetics of tropical adaptation in cattle and conclude that the Senepol, N'Dama, Adaptaur and Criollo breeds, among others with similar evolutionary trajectories, would possess genes capable of improving the productivity of cattle in challenging environments. Using our own experimental evidence from northern Australia, we review the evolution of the Adaptaur cattle breed which has become resistant to cattle tick. We emphasize that the knowledge of interactions between genotype, environment and management in the livestock systems will be required to generate genotypes for efficient livestock production that are both economically and environmentally sustainable. Livestock producers in the 21st century will have less reliance on infrastructure and veterinary products to alleviate environmental stress and more on the animal's ability to achieve fitness in a given production environment.

Weighted Interaction SNP Hub (WISH) network method for building genetic networks for complex diseases and traits using whole genome genotype data

Kogelman, L. J.A., Kadarmideen, H. N. — Wed, 01 Jan 2014 20:51:56 +0100

BACKGROUND: High-throughput genotype (HTG) data has been used primarily in genome-wide association (GWA) studies; however, GWA results explain only a limited part of the complete genetic variation of traits. In systems genetics, network approaches have been shown to be able to identify pathways and their underlying causal genes to unravel the biological and genetic background of complex diseases and traits, e.g., the Weighted Gene Co-expression Network Analysis (WGCNA) method based on microarray gene expression data. The main objective of this study was to develop a scale-free weighted genetic interaction network method using whole genome HTG data in order to detect biologically relevant pathways and potential genetic biomarkers for complex diseases and traits.

RESULTS: We developed the Weighted Interaction SNP Hub (WISH) network method that uses HTG data to detect genome-wide interactions between single nucleotide polymorphism (SNPs) and its relationship with complex traits. Data dimensionality reduction was achieved by selecting SNPs based on its: 1) degree of genome-wide significance and 2) degree of genetic variation in a population. Network construction was based on pairwise Pearson's correlation between SNP genotypes or the epistatic interaction effect between SNP pairs. To identify modules the Topological Overlap Measure (TOM) was calculated, reflecting the degree of overlap in shared neighbours between SNP pairs. Modules, clusters of highly interconnected SNPs, were defined using a tree-cutting algorithm on the SNP dendrogram created from the dissimilarity TOM (1-TOM). Modules were selected for functional annotation based on their association with the trait of interest, defined by the Genome-wide Module Association Test (GMAT). We successfully tested the established WISH network method using simulated and real SNP interaction data and GWA study results for carcass weight in a pig resource population; this resulted in detecting modules and key functional and biological pathways related to carcass weight.

CONCLUSIONS: We developed the WISH network method which is a novel 'systems genetics' approach to study genetic networks underlying complex trait variation. The WISH network method reduces data dimensionality and statistical complexity in associating genotypes with phenotypes in GWA studies and enables researchers to identify biologically relevant pathways and potential genetic biomarkers for any complex trait of interest.

In vitro procedures deregulate the embryonic disc and extraembryonic membranes transcriptome of day 15 elongated bovine embryos

Sun, 08 Sep 2024 20:51:56 +0200

Feed characteristics and potential effects on ruminal bacteria of ensiled sugar kelp and winged kelp for Holstein dairy cows

Sun, 01 Sep 2024 20:51:56 +0200

Seaweed silage has potential as an alternative feed ingredient for dairy cows. This study aims to investigate seaweed's and seaweed silageś nutrient digestibility as well as their impact on the ruminal bacterial composition. The cultivated S. latissima and A. esculenta were preserved by freezing at − 40 °C or ensiling (16 °C, 3 months) with four different treatments: no additives, 4 g formic acid/kg wet seaweed, lactic acid bacteria (LAB) inoculant, and LAB inoculant in prewilted biomass (ca. 300 g DM/kg wet biomass). The nutrient digestibility was estimated using standard feed evaluation methods. The bacterial composition in ruminal fluid after 48 h in vitro anaerobic incubation with seaweeds and common feedstuffs was analysed using 16S ribosomal RNA (rRNA) amplicon sequencing (V3-V4) and quantitative PCR (qPCR). The results suggest that S. latissima was more digestible than A. esculenta and that the preservation treatments had only a small effect on the nutrient digestibility and ruminal bacteria compositions. The rumen DM degradability of S. latissima was comparable to common perennial and corn forage; however, the total tract CP digestibility of S. latissima (460 g/kg CP) was lower than common forages (620 – 820 g/kg CP) and was not improved by ensiling. There was a lack of insoluble but rumen−degradable CP in A. esculenta, making it unsuitable as a nutrient ingredient for dairy cows. The ruminal bacterial composition changed depending on the seaweed species used as substrate: The dominant bacterial taxa when incubated with S. latissima belonged to the genus Prevotella (relative abundance: 79 – 93%), known for its ability to degrade polysaccharides in various ecosystems. Moreover, the fibrolytic bacteria including Fibrobacter succinogenes and Ruminococcus flavefaciens were > 2.5 Log2FoldChange higher when incubating with S. latissima than with A. esculenta. These bacterial taxa may play an important role in the in vitro organic matter digestibility, noted as 2 times higher in S. latissima compared to A. esculenta. The qPCR results indicated potential methane mitigation properties of the studied seaweed species, with significantly lower gene copies of Archaea 16S rRNA and methyl coenzyme-M reductase subunit A genes when the ruminal fluid was incubated with the seaweed substrates. Our study suggested that ensiled S. latissima biomass can be included in the diet of dairy cows as an alternative forage-like ingredient with the potential of methane mitigation.

Tiltag som kan forbedre pattegriseoverlevelsen

Pedersen, L. J., Kongsted, H., Su, G., Christensen, O. F. — Mon, 09 Sep 2024 20:51:56 +0200

Afdækning af eksisterende viden vedrørende variation i sæsonbestemt sodødelighed og genetisk variation i sodødelighed

Kongsted, H., Krogh, M. A., Poulsen, B. G., Christensen, O. F. — Mon, 09 Sep 2024 20:51:56 +0200