investigators: ZuchtData EDV-Dienstleistungen GmbH, Joanna Szyda, Magdalena Frąszczak, Tomasz Suchocki, Magda Mielczarek
The project is related to the analysis of hoof and leg quality data scored on cows. The major aim is to estimate additive, dominance and epistatic effects for those traits. Genomic information is provided by the SNP microarray.
investigators: Joanna Szyda, Tomasz Suchocki, Monika Bugno-Poniewierska
Investigators: Kotlarz K., Mielczarek M., Suchocki T., Dou J., Wang Y., Szyda J.
Heat stress is an increasingly serious problem in livestock production, not only due to the rise of global warming but also because of constantly increasing metabolic load, especially for high-productive animals. In this study, we used the Norwegian rat (Rattus norvegicus) as a model organism for a genome-wide scan of the transcriptional expression alterations induced by heat stress.
In the experiment, 5 rats were used in the control and the heat-stressed groups to investigate the transcriptomic regulation profiles. The RNA was isolated from the liver and adrenal gland from the control and heat-stressed group.
By applying different models, we considered four sources of variation in transcript expression, comprising transcripts (1), genes (2), Gene Ontology terms (3), and Reactome pathways (4) and focussed on accounting for the similarity within each source, which was expressed as a covariance matrix. Models based on transcripts or genes levels explained a larger proportion of log2 fold change than models fitting the functional components of Gene Ontology terms or Reactome pathways.
Since global temperature is expected to rise by 2°C in 2050, heat stress may become the most serious environmental factor. Individuals cope with heat stress by:
In animal production, heat stress is among the best characterized environmental stressors and it can lead to economic losses and increased health burdens.
investigators: N.C. Chung, J. Szyda, M. Frąszczak
Since domestication, population bottleneck, breed formation, and selective breeding have radically shaped the genealogy and population structure of Bos taurus. In turn, characterization of population structure among globally diverse bull genomes enables detailed assessment of genetic resources and origins, as well as informs genome-wide association studies, genomic selection, and breeding programs. By analyzing 432 unrelated bull genomes from 13 breeds and 16 countries, we demonstrate genetic diversity and structural complexity among the global bull population. Importantly, we relaxed a strong and potentially invalid assumption of discrete or admixed population, by adapting latent variable probabilistic models for individual-specific allele frequencies which directly capture a wide range of complex structure from genome-wide genotypes. We identified highly complex and continuous population structure that contribute to pervasive genetic differentiation in bull genomes. As measured by magnitude of differentiation, selection pressure on SNPs within genes is substantially greater than that on intergenic regions. Additionally, broad regions of chromosome 6 harboring largest genetic differentiation suggest recent positive natural selection underlying population structure. We carried out gene set analysis using SNP annotations to identify highly enriched functional categories such as energy-related processes and multiple development stages (sexual, respiratory, and embryonic). Our comprehensive analysis of bull population structure may support genetic management strategies that capture structural complexity and promote sustainable genetic breath.
investigators: Joanna Szyda, Magdalena Frąszczak, Magda Mielczarek, Tomasz Suchocki
The major aims of this study is to use the whole genome DNA sequence of 32 individuals to identify mononucleotide polymorphisms as well as the Copy Number Variations (CNVs) which are present in the genome of domestic cattle. These polymorphisms will be then used to find genes or genomic regions responsible for the risk of clinical mastitis.
Whole genome DNA sequences are available for 32 cows representing the Polish Holstein-Friesian breed selected out of the data base of 991 cows comprising individuals with clinical mastitis cases diagnosed by a veterinarian and their healthy herdmates. The average sequencing coverage calculated across the 32 individuals is high and amounts to 14.03 varying between 5 and 17. The experimental design comprises 16 paternal halfsib pairs comprising halfsisters matched by the number of parities, production level, and birth year, but differing in terms of their mastitis resistance expressed by the frequency of clinical mastitis diagnosed throughout their production life. In particular in each pair one of the halfsibs represents an animal without clinical mastitis occurrence throughout the whole production period (control group) and the other represents an animal with multiple clinical mastists cases (case group). The alignment to the reference genome will be carried out based on a paired-end
alignment, using the BWA-MEM software. Mononucleotide variant detection will be performed using the GATK and Samtools packages, further on the CNVnator program will be used for CNV detection, which uses local differences in read depth to identify copy number variation sites. Allele frequencies will be estimated using the Jackknife resampling algorithm. Moreover, the r square statistics, which quantifies the amount of linkage disequilibrium between pairs of SNPs will be calculated using the PLINK package. SNP haplotypes will be reconstructed with GATK and Beagle software packages. The Odds Ratio and the Likelihood Ratio Tests will be used to assess differences in SNP allele frequency between case and control groups. Afterwards, the nominal P values will be corrected for multiple testing based using the estimated number of effective, independent tests. In addition, the False Discovery Rate will be calculated. For testing haplotype effects a logistic regression model will be
compared with linear and quadratic discriminant models as well as with a random forest algorithm. Finally, a Variant Effect Predictor software together with custom written programs will be used for the functional annotation of the significant variants and regions.
Genetically, the significance of our project is related to the fact that, in contrast to commercial SNP panels, individual sequence data allow for the identification of rare genetic variants, which thanks to recent results from human genetic studies play a predominant role in the determination of genetic variation. To our knowledge no study involving rare variants has been conducted in dairy cattle. Also some novel statistical approaches need to be introduced: a novel method of multiple testing correction and a Jackknife resampling procedure, which has not been so far used in the context of whole genome DNA sequence analysis. Moreover, the understanding of genetic determination of clinical mastitis is of high importance for dairy cattle breeding, since udder infections in high performing cows are very common. They cause not only problems with animal welfare, but also considerable economical loss for the breeder.
investigators: Research Institute of Animal Breeding Balice, Joanna Szyda, Tomasz Suchocki, Magda Mielczarek
Routine evaluation of GEBV (Genomically Enhanced Breeding Value) in Poland includes bulls belonging to the Polish Holstein-Friesian breed (majority Black-and-White, nothing much Red-and-White). The genomic information is incorporated in a form of thousands of SNPs (Single Nucleotide Polymorphism) genotypes originating from a microarray technology. The evaluation is performed for prodution (milk, protein and fat yield), fertility (e.g. non return rates for heifers and for cows), udder health (Somatic Cell Score, SCS) and conformation (e.g. body depth, chest width, dairy character ) traits.
Magda Mielczarek, Joanna Szyda
An overview of the research material
The effect of TNF-? and LTFgenes on morbidity rate
The effect of TNF-? and LTFgenes on duration of mastitis
The effect of TNF-? and LTFgenes on extent of mastitis
Application of NGS technology to better understand the genetic background of clinical mastitis in dairy cattle
investigators: B. Czech, J. Szyda
The aim of this project is to analyze different cattle samples analyzed by high throughput technologies and integrate them to investigate the genetic background of heat stress in cattle. The project comprises the analysis of genome, transcriptome, microbiome, and metabolome data obtained with NGS and mass spectrometry technologies.
Conferences
B. Czech, K. Wang, S. Chen, Y. Wang, J. Szyda. Faecal microbiota and their association with heat stress in Bos taurus
B. Czech, K. Wang, S. Chen, Y. Wang, J. Szyda. Challenges of 16S rRNA gene analysis in Chinese Holstein cows under heat stress condition
J. Szyda, B. Czech, K. Wang, S. Chen, Y. Wang. The application of mixed linear models for the analysis of microbiome influence on heat stress in Chinese Holstein cows.
B. Czech, J. Szyda, K. Wang, S. Chen, Y. Wang. The effect of pipelines and databases on the analysis of the fecal microbiota of dairy cattle.
investigators: J.Szyda, T. Suchocki, M. Frąszczak
