Runs of homozygosity are long, uninterrupted stretches of homozygous genotypes that enable reliable estimation of levels of inbreeding (i.e., autozygosity) based on high-throughput, chip-based single ...nucleotide polymorphism (SNP) genotypes. While the theoretical definition of runs of homozygosity is straightforward, their empirical identification depends on the type of SNP chip used to obtain the data and on a number of factors, including the number of heterozygous calls allowed to account for genotyping errors. We analyzed how SNP chip density and genotyping errors affect estimates of autozygosity based on runs of homozygosity in three cattle populations, using genotype data from an SNP chip with 777,972 SNPs and a 50 k chip.
Data from the 50 k chip led to overestimation of the number of runs of homozygosity that are shorter than 4 Mb, since the analysis could not identify heterozygous SNPs that were present on the denser chip. Conversely, data from the denser chip led to underestimation of the number of runs of homozygosity that were longer than 8 Mb, unless the presence of a small number of heterozygous SNP genotypes was allowed within a run of homozygosity.
We have shown that SNP chip density and genotyping errors introduce patterns of bias in the estimation of autozygosity based on runs of homozygosity. SNP chips with 50,000 to 60,000 markers are frequently available for livestock species and their information leads to a conservative prediction of autozygosity from runs of homozygosity longer than 4 Mb. Not allowing heterozygous SNP genotypes to be present in a homozygosity run, as has been advocated for human populations, is not adequate for livestock populations because they have much higher levels of autozygosity and therefore longer runs of homozygosity. When allowing a small number of heterozygous calls, current software does not differentiate between situations where these calls are adjacent and therefore indicative of an actual break of the run versus those where they are scattered across the length of the homozygous segment. Simple graphical tests that are used in this paper are a current, yet tedious solution.
Quantifying human, plant and livestock inbreeding has been an important goal of evolutionary biologists and agricultural scientists for nearly a century, and methods to do so continue to evolve. This ...review examines current approaches for estimating inbreeding at individual and population levels based on genetic information. Central to this approach is the detection of runs of homozygosity (ROH), long stretches of homozygous genome that most likely arise when the individual is the offspring of related individuals. When related individuals mate, the offspring carry long sections of the genome that are homozygous and identical by descent (IBD). Long ROH are most likely derived from a recent ancestor; shorter ones, from a more distant ancestor. Calculating how much an individual׳s genome occurs as ROH of particular lengths (e.g. >1Mb, >2Mb, and >4Mb) provides information about levels of inbreeding relative to reference populations specific numbers of generations ago. Although identifying and quantifying ROH can be complicated by genotyping errors and undetected heterozygosity within apparently continuous ROH, inbreeding estimates based on ROH clearly indicate that inbreeding levels in bovine and porcine populations are much higher than those in human populations. Frequencies of ROH vary widely within and across chromosomes, with chromosomes exhibiting ROH hotspots or “islands” as well as coldspots or “deserts”. The reasons for this variation are unclear and are attracting growing interest. Next-generation sequencing may improve our understanding of ROH and their usefulness as a tool in inbreeding research. We argue for combining ROH analysis and other genomic estimators unrelated to haplotype length in order to better define the inbreeding reference population.
•The runs of homozygosity (ROH) concept is well suited for estimating inbreeding.•Length and distribution of ROH can help revealing a population׳s demographic history.•ROH frequencies vary widely within and across chromosomes.•Bovine and porcine populations exhibit higher ROH inbreeding than human populations.
Inbreeding depression is known to affect quantitative traits such as male fertility and sperm quality, but the genetic basis for these associations is poorly understood. Most studies have been ...limited to examining how pedigree- or marker-derived genome-wide autozygosity is associated with quantitative phenotypes. In this study, we analyzed possible associations of genetic features of inbreeding depression with percentage of live spermatozoa and total number of spermatozoa in 19,720 ejaculates obtained from 554 Austrian Fleckvieh bulls during routine artificial insemination programs. Genome-wide inbreeding depression was estimated and genomic regions contributing to inbreeding depression were mapped. Inbreeding depression did affect total number of spermatozoa, and such depression was predicted by pedigree-based inbreeding levels and genome-wide inbreeding levels based on runs of homozygosity (ROH). Genome-wide inbreeding depression did not seem to affect percentage of live spermatozoa. A model incorporating genetic effects of the bull, environmental factors, and additive genetic and ROH status effects of individual single-nucleotide polymorphisms revealed genomic regions significantly associated with ROH status for total number of spermatozoa (4 regions) or percentage of live spermatozoa (5 regions). All but one region contains genes related to spermatogenesis and sperm morphology. These genomic regions contain genes affecting sperm morphogenesis and efficacy. The results highlight that next-generation sequencing may help explain some of the genetic factors contributing to inbreeding depression of sperm quality traits in Fleckvieh bulls.
ABSTRACT Inbreeding depression, reduction in performance of quantitative traits, including reproduction and survival, caused by inbreeding, is a well-known phenomenon observed in almost all ...experimental, domesticated, and natural populations. In spite of its importance to the fate of a small population and numerous research performed in the last century, the genetic basis of inbreeding depression is still unclear. Recent fast development of molecular techniques has enabled estimation of a genomic inbreeding coefficient (FROH), which reflects realized autozygosity and can be further partitioned to chromosomes and chromosomal segments. In this review, we first describe classical approach used in the estimation of inbreeding in livestock populations, followed by early concepts of replacing pedigree inbreeding coefficient by individual heterozygosity. Then, we explain runs of homozygosity as key approach in estimating realized autozygosity. Furthermore, we present two different concepts of analysing regions that substantially contribute to the inbreeding depression. Thus, we describe how to identify or map mutations that result in the reduction of performance and, in terms of quantitative genetics, how to analyse the architecture of inbreeding depression. At the end, we discuss future perspectives in eliminating deleterious mutations from livestock populations.
Genome-wide prediction has become the method of choice in animal and plant breeding. Prediction of breeding values and phenotypes are routinely performed using large genomic data sets with number of ...markers on the order of several thousands to millions. The number of evaluated individuals is usually smaller which results in problems where model sparsity is of major concern. The LASSO technique has proven to be very well-suited for sparse problems often providing excellent prediction accuracy. Several computationally efficient LASSO algorithms have been developed, but optimization of hyper-parameters can be demanding.
We have developed a novel automatic adaptive LASSO (AUTALASSO) based on the alternating direction method of multipliers (ADMM) optimization algorithm. The two major hyper-parameters of ADMM are the learning rate and the regularization factor. The learning rate is automatically tuned with line search and the regularization factor optimized using Golden section search. Results show that AUTALASSO provides superior prediction accuracy when evaluated on simulated and real bull data compared to the adaptive LASSO, LASSO and ridge regression implemented in the popular glmnet software.
The AUTALASSO provides a very flexible and computationally efficient approach to GWP, especially when it is important to obtain high prediction accuracy and genetic gain. The AUTALASSO also has the capability to perform GWAS of both additive and dominance effects with smaller prediction error than the ordinary LASSO.
Livestock conservation practice is changing rapidly in light of policy developments, climate change and diversifying market demands. The last decade has seen a step change in technology and ...analytical approaches available to define, manage and conserve Farm Animal Genomic Resources (FAnGR). However, these rapid changes pose challenges for FAnGR conservation in terms of technological continuity, analytical capacity and integrative methodologies needed to fully exploit new, multidimensional data. The final conference of the ESF Genomic Resources program aimed to address these interdisciplinary problems in an attempt to contribute to the agenda for research and policy development directions during the coming decade. By 2020, according to the Convention on Biodiversity's Aichi Target 13, signatories should ensure that "…the genetic diversity of …farmed and domesticated animals and of wild relatives …is maintained, and strategies have been developed and implemented for minimizing genetic erosion and safeguarding their genetic diversity." However, the real extent of genetic erosion is very difficult to measure using current data. Therefore, this challenging target demands better coverage, understanding and utilization of genomic and environmental data, the development of optimized ways to integrate these data with social and other sciences and policy analysis to enable more flexible, evidence-based models to underpin FAnGR conservation. At the conference, we attempted to identify the most important problems for effective livestock genomic resource conservation during the next decade. Twenty priority questions were identified that could be broadly categorized into challenges related to methodology, analytical approaches, data management and conservation. It should be acknowledged here that while the focus of our meeting was predominantly around genetics, genomics and animal science, many of the practical challenges facing conservation of genomic resources are societal in origin and are predicated on the value (e.g., socio-economic and cultural) of these resources to farmers, rural communities and society as a whole. The overall conclusion is that despite the fact that the livestock sector has been relatively well-organized in the application of genetic methodologies to date, there is still a large gap between the current state-of-the-art in the use of tools to characterize genomic resources and its application to many non-commercial and local breeds, hampering the consistent utilization of genetic and genomic data as indicators of genetic erosion and diversity. The livestock genomic sector therefore needs to make a concerted effort in the coming decade to enable to the democratization of the powerful tools that are now at its disposal, and to ensure that they are applied in the context of breed conservation as well as development.
Environmental contaminants like arsenic (As), cadmium (Cd), mercury (Hg) or lead (Pb) may disrupt hypothalamic–pituitary–adrenal (HPA) and hypothalamic-pituitary-gonadal (HPG) axes due to their ...endocrine toxicity potential. Resulting long-term physiological stress or adverse effects on wildlife reproduction and ontogeny may cause detrimental effects at the individual and population levels. However, data on environmental metal(loid)sʼ impact on reproductive and stress hormones in wildlife, especially large terrestrial carnivores, are scarce. Hair cortisol, progesterone and testosterone concentrations were quantified and modelled with hair As, Cd, total Hg, Pb, biological, environmental and sampling factors to test for potential effects in free-ranging brown bears (Ursus arctos) from Croatia (N = 46) and Poland (N = 27). Testosterone in males (N = 48) and females (N = 25) showed positive associations with Hg and an interaction between Cd and Pb, but a negative association with interaction between age and Pb. Higher testosterone was found in hair during its growth phase compared to quiescent phase. Body condition index was negatively associated with hair cortisol and positively associated with hair progesterone. Year and conditions of sampling were important for cortisol variation, while maturity stage for progesterone variation (lower concentrations in cubs and yearlings compared to subadult and adult bears). These findings suggest that environmental levels of Cd, Hg and Pb might influence the HPG axis in brown bears. Hair was shown to be a reliable non-invasive sample for investigating hormonal fluctuations in wildlife while addressing individual and sampling specificities.
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•First effect study on hormonal association with metal (loid)s in European brown bear.•Hair testosterone was associated with potentially toxic metal (loid) levels.•Year and conditions of sampling important for cortisol variation in hair.•Maturity stage important for progesterone variation (lowest in cubs & yearlings).
The majority of the nearly 400 existing local pig breeds are adapted to specific environments and human needs. The demand for large production quantities and the industrialized pig production have ...caused a rapid decline of many local pig breeds in recent decades. Black Slavonian pig and Turopolje pig, the latter highly threatened, are the two Croatian local indigenous breeds typically grown in extensive or semi-intensive systems. In order to guide a long-term breeding program to prevent the disappearance of these breeds, we analyzed their genetic diversity, inbreeding level and relationship with other local breeds across the world, as well as modern breeds and several wild populations, using high throughput genomic data obtained using the Illumina Infinium PorcineSNP60 v2 BeadChip. Multidimensional scaling analysis positioned Black Slavonian pigs close to the UK/North American breeds, while the Turopolje pig clustered within the Mediterranean breeds. Turopolje pig showed a very high inbreeding level (F
= 0.400 and F
= 0.332) that considerably exceeded the level of full-sib mating, while Black Slavonian pig showed much lower inbreeding (F
= 0.098 and F
= 0.074), indicating a planned mating strategy. In Croatian local breeds we identified several genome regions showing adaptive selection signals that were not present in commercial breeds. The results obtained in this study reflect the current genetic status and breeding management of the two Croatian indigenous local breeds. Given the small populations of both breeds, a controlled management activity has been implemented in Black Slavonian pigs since their commercial value has been recognized. In contrast, the extremely high inbreeding level observed in Turopolje pig argues for an urgent conservation plan with a long-term, diversity-oriented breeding program.
Runs of homozygosity (ROH) islands are stretches of homozygous sequence in the genome of a large proportion of individuals in a population. Algorithms for the detection of ROH depend on the ...similarity of haplotypes. Coverage gaps and copy number variants (CNV) may result in incorrect identification of such similarity, leading to the detection of ROH islands where none exists. Misidentified hemizygous regions will also appear as homozygous based on sequence variation alone. Our aim was to identify ROH islands influenced by marker coverage gaps or CNV, using Illumina BovineHD BeadChip (777 K) single nucleotide polymorphism (SNP) data for Austrian Brown Swiss, Tyrol Grey and Pinzgauer cattle.
ROH were detected using clustering, and ROH islands were determined from population inbreeding levels for each marker. CNV were detected using a multivariate copy number analysis method and a hidden Markov model. SNP coverage gaps were defined as genomic regions with intermarker distances on average longer than 9.24 kb. ROH islands that overlapped CNV regions (CNVR) or SNP coverage gaps were considered as potential artefacts. Permutation tests were used to determine if overlaps between CNVR with copy losses and ROH islands were due to chance. Diversity of the haplotypes in the ROH islands was assessed by haplotype analyses.
In Brown Swiss, Tyrol Grey and Pinzgauer, we identified 13, 22, and 24 ROH islands covering 26.6, 389.0 and 35.8 Mb, respectively, and we detected 30, 50 and 71 CNVR derived from CNV by using both algorithms, respectively. Overlaps between ROH islands, CNVR or coverage gaps occurred for 7, 14 and 16 ROH islands, respectively. About 37, 44 and 52% of the ROH islands coverage in Brown Swiss, Tyrol Grey and Pinzgauer, respectively, were affected by copy loss. Intersections between ROH islands and CNVR were small, but significantly larger compared to ROH islands at random locations across the genome, implying an association between ROH islands and CNVR. Haplotype diversity for reliable ROH islands was lower than for ROH islands that intersected with copy loss CNVR.
Our findings show that a significant proportion of the ROH islands in the bovine genome are artefacts due to CNV or SNP coverage gaps.
Runs of homozygosity (ROH) and genome wide association study (GWAS) were used to identify genomic regions of entropion in Austrian Fleckvieh cattle. Entropion is an eye disorder where the eye lids ...turn inward, causing inflammations, cornea damage or even blindness if left untreated. A total of 196 bulls genotyped by BovineSNP50 BeadChip were analysed, nine of which had the disorder confirmed by a veterinarian, ten were unconfirmed and 177 were healthy control animals. Runs of homozygosity analysis highlighted regions on seven chromosomes where the proportion of animals in ROH significantly (p<0.001) differed between cases and controls. None of the 19 genes identified in these regions showed any connection to entropion or eye development. The GWAS study using only cases and controls had a mild peak directly on top of the ITGA9 gene. This gene was previously identified in mice affecting cornea and eye lid development, therefore we consider it being a candidate to influence entropion also in cattle.
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