Approaches for investigating genome variability in cattle

Aim of the present thesis is to study the genetic variability of cattle breeds farmed in Italy. These were selected in order to represent different origin, selection history and production aptitudes. The variation at genome level was investigated by using three approaches that allow for disentangling different aspects of the genetic difference between animal populations. One approach checked the difference between two breeds by using a modification of the Fst metric methodology, developed in order to make the signal pattern more readable through a local regression smoothing and to identify outlier signals based on statistical evidence. This study was focused a identifying genomic regions that harbor genes involved in the differences between dairy and beef cattle. Then a multi-breed investigation was performed based on the comparison between allele frequencies under the hypothesis of the binomial distributions. The research was mainly aimed at looking for genes shared between breeds grouped according to production aptitudes. Finally a third study was carried out to analyse the structural differences in the genome by investigating the variation of the distribution of ROH between breeds. Relationships between runs of homozygosity features and inbreeding coefficients have been investigated within and between breeds

detectRUNS: Detect runs of homozygosity and runs of heterozygosity in diploid genomes

detectRUNS is a R package for the detection of runs of homozygosity (ROH/ROHom) and of heterozygosity (ROHet, a.k.a. “heterozygosity-rich regions”) in diploid genomes. ROH/ROHom were first studied in humans (e.g. McQuillan et al. 2008) and rapidly found applications not only in human genetics abut also in animal genetics (e.g. Ferencakovic et al., 2011, in Bos taurus). More recently, the idea of looking also at “runs of heterozygosity” (ROHet or, more appropriately, “heterozygosity-rich regions”) has been proposed (Wiliams et al. 2016)

Characterization of FeOOH nanoparticles and amorphous silica matrix in an FeOOH-Sio 2 nanocomposite

A nanocomposite with an FeOOH/SiO2ratio equal to 17.7 wt% and the pertinent matrix, obtained by etching away the nanoparticles through reaction with hydrochloric acid, were investigated by XRD, TGA-DTA, heliostereopicnometry, BET, and TEM techniques. The study shows the presence in the nanocomposite of ferrihydrite nanoparticles phase with average dimensions around 4 nm. The FeOOH nanoparticles structure was analyzed by synchrotron X-ray diffraction data using the distribution difference curve method. The porous structure of the matrix resulting by etching away the nanoparticles differs significantly from that of a pureSiO2sample obtained by hydrolysis of TEOS under the same operative conditions followed in the nanocomposite preparation

Investigating inbreeding in the turkey (Meleagris gallopavo) genome

The detrimental effects of increased homozygosity due to inbreeding have prompted the development of methods to reduce inbreeding. The detection of runs of homozygosity (ROH), or contiguous stretches of homozygous marker genotypes, can be used to describe and quantify the level of inbreeding in an individual. The estimation of inbreeding coefficients can be calculated based on pedigree information, ROH, or the genomic relationship matrix. The aim of this study was to detect and describe ROH in the turkey genome and compare estimates of pedigree-based inbreeding coefficients (FPED) with genomic-based inbreeding coefficients estimated from ROH (FROH) and the genomic relationship matrix (FGRM). A total of 2,616,890 pedigree records were available. Of these records, 6,371 genotyped animals from three purebred turkey (Meleagris gallopavo) lines between 2013 and 2019 were available, and these were obtained using a dense single nucleotide polymorphism array (56,452 SNPs). The overall mean length of detected ROH was 2.87 ± 0.29 Mb with a mean number of 84.87 ± 8.79 ROH per animal. Short ROH with lengths of 1 to 2 Mb long were the most abundant throughout the genome. Mean ROH coverage differed greatly between chromosomes and lines. Considering inbreeding coefficient means across all lines, genomic derived inbreeding coefficients (FROH = 0.27; FGRM = 0.32) were higher than coefficients estimated from pedigree records (FPED = 0.14). Correlations between FROH and FPED, FROH and FGRM, and FPED and FGRM ranged between 0.19 to 0.31, 0.68 to 0.73, and 0.17 to 0.30, respectively. Additionally, correlations between FROH from different lengths and FPED substantially increased with ROH length from -0.06 to 0.33. Results of the current research, including the distribution of ROH throughout the genome and ROH-derived inbreeding estimates, can provide a more comprehensive description of inbreeding in the turkey genome. This knowledge can be used to evaluate genetic diversity, a requirement for genetic improvement, and develop methods to minimize inbreeding in turkey breeding programs

Identification of unique ROH regions with unfavorable effects on production and fertility traits in Canadian Holsteins

Background: The advent of genomic information and the reduction in the cost of genotyping have led to the use of genomic information to estimate genomic inbreeding as an alternative to pedigree inbreeding. Using genomic measures, effects of genomic inbreeding on production and fertility traits have been observed. However, there have been limited studies on the specific genomic regions causing the observed negative association with the trait of interest. Our aim was to identify unique run of homozygosity (ROH) genotypes present within a given genomic window that display negative associations with production and fertility traits and to quantify the effects of these identified ROH genotypes. Methods: In total, 50,575 genotypes based on a 50K single nucleotide polymorphism (SNP) array and 259,871 pedigree records were available. Of these 50,575 genotypes, 46,430 cows with phenotypic records for production and fertility traits and having a first calving date between 2008 and 2018 were available. Unique ROH genotypes identified using a sliding-window approach were fitted into an animal mixed model as fixed effects to determine their effect on production and fertility traits. Results: In total, 133 and 34 unique ROH genotypes with unfavorable effects were identified for production and fertility traits, respectively, at a 1% genome-wise false discovery rate. Most of these ROH regions were located on bovine chromosomes 8, 13, 14 and 19 for both production and fertility traits. For production traits, the average of all the unfavorably identified unique ROH genotypes effects were estimated to decrease milk yield by 247.30 kg, fat yield by 11.46 kg and protein yield by 8.11 kg. Similarly, for fertility traits, an average 4.81-day extension in first service to conception, a 0.16 increase in number of services, and a - 0.07 incidence in 56-day non-return rate were observed. Furthermore, a ROH region located on bovine chromosome 19 was identified that, when homozygous, had a negative effect on production traits. Signatures of selection proximate to this region have implicated GH1 as a potential candidate gene, which encodes the growth hormone that binds the growth hormone receptor. This observed negative effect could be a consequence of unfavorable alleles in linkage disequilibrium with favorable alleles. Conclusions: ROH genotypes with unfavorable effects on production and fertility traits were identified within and across multiple traits on most chromosomes. These identified ROH genotypes could be included in mate selection programs to minimize their frequency in future generations

Genome-wide patterns of homozygosity provide clues about the population history and adaptation of goats

Abstract Background Patterns of homozygosity can be influenced by several factors, such as demography, recombination, and selection. Using the goat SNP50 BeadChip, we genotyped 3171 goats belonging to 117 populations with a worldwide distribution. Our objectives were to characterize the number and length of runs of homozygosity (ROH) and to detect ROH hotspots in order to gain new insights into the consequences of neutral and selection processes on the genome-wide homozygosity patterns of goats. Results The proportion of the goat genome covered by ROH is, in general, less than 15% with an inverse relationship between ROH length and frequency i.e. short ROH ( 0.20) F ROH values. For populations from Asia, the average number of ROH is smaller and their coverage is lower in goats from the Near East than in goats from Central Asia, which is consistent with the role of the Fertile Crescent as the primary centre of goat domestication. We also observed that local breeds with small population sizes tend to have a larger fraction of the genome covered by ROH compared to breeds with tens or hundreds of thousands of individuals. Five regions on three goat chromosomes i.e. 11, 12 and 18, contain ROH hotspots that overlap with signatures of selection. Conclusions Patterns of homozygosity (average number of ROH of 77 and genome coverage of 248 Mb; F ROH < 0.15) are similar in goats from different geographic areas. The increased homozygosity in local breeds is the consequence of their small population size and geographic isolation as well as of founder effects and recent inbreeding. The existence of three ROH hotspots that co-localize with signatures of selection demonstrates that selection has also played an important role in increasing the homozygosity of specific regions in the goat genome. Finally, most of the goat breeds analysed in this work display low levels of homozygosity, which is favourable for their genetic management and viability