Pedigree Validation Using Genetic Markers in an Intensively-Managed Taonga Species, the Critically Endangered Kakī (\u3cem\u3eHimantopus novaezelandiae\u3c/em\u3e)

Many species recovery programmes use pedigrees to understand the genetic ancestry of individuals to inform conservation management. However, incorrect parentage assignment may limit the accuracy of these pedigrees and subsequent management decisions. This is especially relevant for pedigrees that include wild individuals, where misassignment may not only be attributed to human error, but also promiscuity (i.e. extra-pair parentage) or egg-dumping (i.e. brood parasitism). Here, we evaluate pedigree accuracy in the socially monogamous and critically endangered kakī (black stilt, Himantopus novaezelandiae) using microsatellite allele-exclusion analyses for 56 wild family groups across three breeding seasons (2014–2016, n= 340). We identified 16 offspring where parentage was incorrectly assigned, representing 5.9% of all offspring. Of the 16 misassigned offspring, three can be attributed to non-kakī brood parasitism, one can be assigned to human error, but others cannot be readily distinguished between non-monogamous mating behaviours and human error. In the short term, we advise the continued use of microsatellites to identify misassigned offspring in the kakī pedigree, and to verify non-kakī brood parasitism. We also recommend the Department of Conservation’s Kakī Recovery Programme further evaluate the implications of pedigree error to the management of this critically endangered taonga species

Routes for breaching and protecting genetic privacy

We are entering the era of ubiquitous genetic information for research, clinical care, and personal curiosity. Sharing these datasets is vital for rapid progress in understanding the genetic basis of human diseases. However, one growing concern is the ability to protect the genetic privacy of the data originators. Here, we technically map threats to genetic privacy and discuss potential mitigation strategies for privacy-preserving dissemination of genetic data.Comment: Draft for comment

Methods and Algorithms for Inference Problems in Population Genetics

Inference of population history is a central problem of population genetics. The advent of large genetic data brings us not only opportunities on developing more accurate methods for inference problems, but also computational challenges. Thus, we aim at developing accurate method and fast algorithm for problems in population genetics. Inference of admixture proportions is a classical statistical problem. We particularly focus on the problem of ancestry inference for ancestors. Standard methods implicitly assume that both parents of an individual have the same admixture fraction. However, this is rarely the case in real data. We develop a Hidden Markov Model (HMM) framework for estimating the admixture proportions of the immediate ancestors of an individual, i.e. a type of appropriation of an individual\u27s admixture proportions into further subsets of ancestral proportions in the ancestors. Based on a genealogical model for admixture tracts, we develop an efficient algorithm for computing the sampling probability of the genome from a single individual, as a function of the admixture proportions of the ancestors of this individual. We show that the distribution and lengths of admixture tracts in a genome contain information about the admixture proportions of the ancestors of an individual. This allows us to perform probabilistic inference of admixture proportions of ancestors only using the genome of an extant individual. To better understand population, we further study the species delimitation problem. It is a problem of determining the boundary between population and species. We propose a classification-based method to assign a set of populations to a number of species. Our new method uses summary statistics generated from genetic data to classify pairwise populations as either \u27same species\u27 or \u27different species\u27. We show that machine learning can be used for species delimitation and scaled for large genomic data. It can also outperform Bayesian approaches, especially when gene flow involves in the evolutionary process

Genome-Wide Association Study in Bipolar Patients Stratified by Co-Morbidity

Bipolar disorder is a severe psychiatric disorder with high heritability. Co-morbid conditions are common and might define latent subgroups of patients that are more homogeneous with respect to genetic risk factors.In the Caucasian GAIN bipolar disorder sample of 1000 cases and 1034 controls, we tested the association of single nucleotide polymorphisms with patient subgroups defined by co-morbidity.). All three associations were found under the recessive genetic model. Bipolar disorder with low probability of co-morbid conditions did not show significant associations.Conceptualizing bipolar disorder as a heterogeneous disorder with regard to co-morbid conditions might facilitate the identification of genetic risk alleles. Rare variants might contribute to the susceptibility to bipolar disorder

Development of genetic tools for managing populations of the Southern white rhinoceros (Ceratotherium simum simum)

The southern white rhinoceros (SWR) is one of five extant species of rhinoceros. The species experienced historical bottleneck due to unrestricted hunting and was on the brink of extinction during the end of nineteenth century, with only one population remaining in South Africa. This population was intensively protected and as it subsequently increased, it became the source of SWR for all of Southern Africa. With advances in immobilisation and translocation techniques, a surplus SWRs were relocated to the former range states of the species. Therefore, most or all modern populations of SWRs originated from the single founder population. As in other former range states, Botswana re-established SWR populations, but poaching remained an imminent threat to the national herd and the species was almost wiped out for a second time. In response to this threat, the Department of Wildlife and National Parks of Botswana (DWNP) began to capture free ranging animals and relocate them into enclosed reserves where they could be protected intensively by anti-poaching teams. Subsequently the population size of the national herd has been increasing due to successful breeding together with the continued introduction of SWRs from South Africa. Although this conservation strategy has been successful, it has generated many fragmented populations, which required regular exchanges of animals to prevent inbreeding. However, selection of animals for translocation has been made based on observational data about the relationships among animals and genetic information has rarely been used. The efficient identification of candidates for translocation, requires an accurate and complete pedigree to determine the individuals with high risk of producing inbred progeny. In this thesis, three populations of SWRs in Botswana (Botswana1, Botswana2, and Botswana3) were used as models to develop genetic tools that would facilitate metapopulation management. The purpose of Chapter 2 was to integrate previously characterised microsatellites (MS) genotypes with an incomplete, field-observed pedigree to make inferences about mean kinship and basic demographic data that could be used to inform translocation programmes for SWR. Level of heterozygosity and genetic diversity of the population were not as low as initially expected based on the severe bottleneck, but the population showed a very low mean number of alleles per locus. Using several different strategies for exclusion of unlikely parents, parental pairs of 29 out of 45 offspring could be assigned confidently. The combined pedigree was constructed from the assignable parent-offspring relationships and subsequently used to estimate kinship coefficients. Based on population mean kinship (MK), eight bulls with high individual MK could be identified as the best candidates for translocation. The pedigree was further used to estimate population demographic parameters; importantly, the reproductive dominance of the bulls was not as skewed as expected after the original dominant bull was removed, suggesting that closed populations can maintain multiple, simultaneously breeding males. Because the currently available markers (i.e. microsatellites) did not provide sufficient analytical power to construct a complete pedigree, a sequencing method that would allow marker discovery and genotyping in non-model species was required. A commonly used complexity reduction approach (double digestion restriction-associated DNA sequencing; ddRADseq) for identifying genome-wide single nucleotide polymorphisms (SNPs) was initially attempted. However, signs of DNA degradation were evident for nearly one third of the samples, which made the ddRADseq approach impractical. Thus, in Chapter 3, I tested the efficiency of an approach (RADcapture) that uses hybrid sequence capture to enrich the genome for SNPs identified by ddRADseq conducted on a set of high-quality DNA extractions. A total of 32 samples was chosen based on their molecular weight judged from 1% agarose gel electrophoresis; these were divided into two groups corresponding to their qualities. RADcapture identified 6,481 SNPs and performed equally well in both groups of samples, and there was no relationship between the quality of samples and the performance of the protocol. This suggested that hybrid capture could be useful for resolving SNPs in both high- and low-quality samples. In Chapter 4, RADcapture was applied to a collection of samples from the three managed populations to assess the utility of applying this approach to population management across metapopulation. Using RADcapture, 302 SNPs could be genotyped consistently across all individuals. For the Botswana1, these markers were used for parentage analysis, for comparison with the combined pedigree in Chapter 2, and for construction a consensus pedigree. Seven offspring for which MS were not effective could be assigned using SNPs, indicating better resolution by SNPs. The consensus pedigree could be constructed and was subsequently used to estimate pedigree-based kinship coefficients that suggested six and eight individuals as the best candidates for translocation and for breeding, respectively. Four of the six candidates for translocation were male; of which one were in agreement with the suggestions made in Chapter 2, the other two were the SNP-assigned fathers that involved four cases that SNPs provided better resolution. This suggested the potential effects of pedigree completeness on the candidates identified. RADcapture data were also used to estimate marker-based kinship coefficients for all three populations. For the Botswana1 population, marker-based kinships identified different individuals from the candidates suggested by the pedigree-based MK. The disagreements suggested that the latter optimised genetic contributions of animals, whereas the marker-based MK might instead promote the individuals that carried rare alleles. No candidates could be identified for Botswana2 or Botswana3 because there were no individuals with individual MK above and below the thresholds. Based on between-population MKs estimated from RADcapture data of the three populations, exchanges of animals between any pair of them would reduce population MK of the recipients. The principal component analysis revealed no genetic clusters observed across individuals from the three populations. Chapter 4 demonstrated the potential applications of RADcapture for parentage assignment and for identification of the candidates for translocation and breeding; however, completeness of the pedigree and the methods used to estimate kinships could affect the population management regarding the candidates identified. In summary, the key outcomes of this thesis were 1) resolving the pedigree of a SWR population that has been an important source of animals for the national reintroduction programme in Botswana; 2) development of a sequencing method that allows the retrieval of genetic markers from DNA of various qualities; 3) demonstration of quantifiable methods (i.e. management based on kinship coefficients) that showed the potential to facilitate population management to prevent inbreeding in fragmented populations of SWRs; and 4) initiation of a genomic database obtained from RADcapture (i.e. RADcapture sequences) that could be used as the raw materials for various purposes of future applications (e.g. development of SNP array, wildlife forensics). These tools for genetic-based population management can now be applied to minimise inbreeding which is currently of particular concern for fragmented SWR populations. Most importantly, this thesis demonstrated approaches that are not applicable to only SWR, but can equally be applied in conservation programmes of other endangered species, i.e. sequencing methods for non-model species, methods for identification of candidates for translocation and breeding. The key outcomes present in this thesis should improve efficiency of the conservation of the species as well as other endangered species