The Consequences of Mitochondrial T10432C Mutation in Cika Cattle: A "Potential" Model for Leber's Hereditary Optic Neuropathy.

While mitogenome mutations leading to pathological manifestations are rare, more than 200 such mutations have been described in humans. In contrast, pathogenic mitogenome mutations are rare in domestic animals and have not been described at all in cattle. In the small local Slovenian cattle breed Cika, we identified (next-generation sequencing) two cows with the T10432C mitogenome mutation in the ND4L gene, which corresponds to the human T10663C mutation known to cause Leber's hereditary optic neuropathy (LHON). Pedigree analysis revealed that the cows in which the mutation was identified belong to two different maternal lineages with 217 individual cows born between 1997 and 2020. The identified mutation and its maternal inheritance were confirmed by Sanger sequencing across multiple generations, whereas no single analysis revealed evidence of heteroplasmy. A closer clinical examination of one cow with the T10432C mutation revealed exophthalmos, whereas histopathological examination revealed retinal ablations, subretinal oedema, and haemorrhage. The results of these analyses confirm the presence of mitochondrial mutation T10432C with homoplasmic maternal inheritance as well as clinical and histopathological signs similar to LHON in humans. Live animals with the mutation could be used as a suitable animal model that can improve our understanding of the pathogenesis of LHON and other mitochondriopathies.

MaGelLAn 1.0: a software to facilitate quantitative and population genetic analysis of maternal inheritance by combination of molecular and pedigree information.

BACKGROUND: Identification of genes or even nucleotides that are responsible for quantitative and adaptive trait variation is a difficult task due to the complex interdependence between a large number of genetic and environmental factors. The polymorphism of the mitogenome is one of the factors that can contribute to quantitative trait variation. However, the effects of the mitogenome have not been comprehensively studied, since large numbers of mitogenome sequences and recorded phenotypes are required to reach the adequate power of analysis. Current research in our group focuses on acquiring the necessary mitochondria sequence information and analysing its influence on the phenotype of a quantitative trait. To facilitate these tasks we have produced software for processing pedigrees that is optimised for maternal lineage analysis. RESULTS: We present MaGelLAn 1.0 (maternal genealogy lineage analyser), a suite of four Python scripts (modules) that is designed to facilitate the analysis of the impact of mitogenome polymorphism on quantitative trait variation by combining molecular and pedigree information. MaGelLAn 1.0 is primarily used to: (1) optimise the sampling strategy for molecular analyses; (2) identify and correct pedigree inconsistencies; and (3) identify maternal lineages and assign the corresponding mitogenome sequences to all individuals in the pedigree, this information being used as input to any of the standard software for quantitative genetic (association) analysis. In addition, MaGelLAn 1.0 allows computing the mitogenome (maternal) effective population sizes and probability of mitogenome (maternal) identity that are useful for conservation management of small populations. CONCLUSIONS: MaGelLAn is the first tool for pedigree analysis that focuses on quantitative genetic analyses of mitogenome data. It is conceived with the purpose to significantly reduce the effort in handling and preparing large pedigrees for processing the information linked to maternal lines. The software source code, along with the manual and the example files can be downloaded at http://lissp.irb.hr/software/magellan-1-0/ and https://github.com/sristov/magellan .

Identification of Selection Signals on the X-Chromosome in East Adriatic Sheep: A New Complementary Approach.

Sheep are one of the most important livestock species in Croatia, found mainly in the Mediterranean coastal and mountainous regions along the East Adriatic coast, well adapted to the environment and mostly kept extensively. Our main objective was therefore to map the positive selection of the X-chromosome (18,983 SNPs that passed quality control), since nothing is known about the adaptation genes on this chromosome for any of the breeds from the Balkan cluster. Analyses were performed on a sample of eight native Croatian breeds (101 females and 100 males) representing the East Adriatic metapopulation and on 10 mouflons (five females and males), all sampled in Croatia. Three classical within-population approaches (extreme Runs of Homozygosity islands, integrated Haplotype Score, and number of Segregating Sites by Length) were applied along with our new approach called Haplotype Richness Drop (HRiD), which uses only the information contained in male haplotypes. We have also shown that phylogenetic analyses, such as the Median-joining network, can provide additional information when performed with the selection signals identified by HRiD. Our new approach identifies positive selection signals by searching for genomic regions that exhibit a sudden decline in haplotype richness. In total, we identified 14 positive selection signals, 11 using the classical approach and three using the HRiD approach, all together containing 34 annotated genes. The most reliable selection signal was mapped by all four approaches in the same region, overlapping between 13.17 and 13.60 Mb, and assigned to the CA5B, ZRSR2, AP1S2, and GRPR genes. High repeatability (86%) of results was observed, as 12 identified selection signals were also confirmed in other studies with sheep. HRiD offers an interesting possibility to be used complementary to other approaches or when only males are genotyped, which is often the case in genomic breeding value estimations. These results highlight the importance of the X-chromosome in the adaptive architecture of domestic ruminants, while our novel HRiD approach opens new possibilities for research.

Large-scale mitogenome sequencing reveals consecutive expansions of domestic taurine cattle and supports sporadic aurochs introgression.

The contribution of domestic cattle in human societies is enormous, making cattle, along with other essential benefits, the economically most important domestic animal in the world today. To expand existing knowledge on cattle domestication and mitogenome diversity, we performed a comprehensive complete mitogenome analysis of the species (802 sequences, 114 breeds). A large sample was collected in South-east Europe, an important agricultural gateway to Europe during Neolithization and a region rich in cattle biodiversity. We found 1725 polymorphic sites (810 singletons, 853 parsimony-informative sites and 57 indels), 701 unique haplotypes, a haplotype diversity of 0.9995 and a nucleotide diversity of 0.0015. In addition to the dominant T3 and several rare haplogroups (Q, T5, T4, T2 and T1), we have identified maternal line in Austrian Murbodner cattle that possess surviving aurochs' mitochondria haplotype P1 that diverged prior to the Neolithization process. This is convincing evidence for rare female-mediated adaptive introgression of wild aurochs into domesticated cattle in Europe. We revalidated the existing haplogroup classification and provided Bayesian phylogenetic inference with a more precise estimated divergence time than previously available. Occasionally, classification based on partial mitogenomes was not reliable; for example, some individuals with haplogroups P and T5 were not recognized based on D-loop information. Bayesian skyline plot estimates (median) show that the earliest population growth began before domestication in cattle with haplogroup T2, followed by Q (~10.0-9.5 kyBP), whereas cattle with T3 (~7.5 kyBP) and T1 (~3.0-2.5 kyBP) expanded later. Overall, our results support the existence of interactions between aurochs and cattle during domestication and dispersal of cattle in the past, contribute to the conservation of maternal cattle diversity and enable functional analyses of the surviving aurochs P1 mitogenome.

Hierarchical Modelling of Haplotype Effects on a Phylogeny.

We introduce a hierarchical model to estimate haplotype effects based on phylogenetic relationships between haplotypes and their association with observed phenotypes. In a population there are many, but not all possible, distinct haplotypes and few observations per haplotype. Further, haplotype frequencies tend to vary substantially. Such data structure challenge estimation of haplotype effects. However, haplotypes often differ only due to few mutations, and leveraging similarities can improve the estimation of effects. We build on extensive literature and develop an autoregressive model of order one that models haplotype effects by leveraging phylogenetic relationships described with a directed acyclic graph. The phylogenetic relationships can be either in a form of a tree or a network, and we refer to the model as the haplotype network model. The model can be included as a component in a phenotype model to estimate associations between haplotypes and phenotypes. Our key contribution is that we obtain a sparse model, and by using hierarchical autoregression, the flow of information between similar haplotypes is estimated from the data. A simulation study shows that the hierarchical model can improve estimates of haplotype effects compared to an independent haplotype model, especially with few observations for a specific haplotype. We also compared it to a mutation model and observed comparable performance, though the haplotype model has the potential to capture background specific effects. We demonstrate the model with a study of mitochondrial haplotype effects on milk yield in cattle. We provide R code to fit the model with the INLA package.