Visualising errors in animal pedigree genotype data

Genetic analysis of a breeding animal population involves determining the inheritance pattern of genotypes for multiple genetic markers across the individuals in the population pedigree structure. However, experimental pedigree genotype data invariably contains errors in both the pedigree structure and in the associated individual genotypes, which introduce inconsistencies into the dataset, rendering them useless for further analysis. The resolution of these errors requires consideration of the genotype inheritance patterns in the context of the pedigree structure. Existing visualisations of pedigree structures are typically more suited to human pedigrees and are less suitable for large complex animal pedigrees which may exhibit cross generational inbreeding. Similarly, current table-based viewers of genotype marker information can highlight where errors become apparent but lack the functionality and interactive visual feedback to enable users to locate the underlying source of errors within the pedigree. In this paper, we detail a design study steered by biologists who work with pedigree data, and describe successive iterations through approaches and prototypes for viewing genotyping errors in the context of a displayed pedigree. We describe how each approach performs with real pedigree genotype data and why eventually we deemed them unsuitable. Finally, a novel prototype visualisation for pedigrees, which we term the ‘sandwich view’, is detailed and we demonstrate how the approach effectively communicates errors in the pedigree context, supporting the biologist in the error identification task

Development and validation of a RAD-Seq target-capture based genotyping assay for routine application in advanced black tiger shrimp (Penaeus monodon) breeding programs

Background: The development of genome-wide genotyping resources has provided terrestrial livestock and crop industries with the unique ability to accurately assess genomic relationships between individuals, uncover the genetic architecture of commercial traits, as well as identify superior individuals for selection based on their specific genetic profile. Utilising recent advancements in de-novo genome-wide genotyping technologies, it is now possible to provide aquaculture industries with these same important genotyping resources, even in the absence of existing genome assemblies. Here, we present the development of a genome-wide SNP assay for the Black Tiger shrimp (Penaeus monodon) through utilisation of a reduced-representation whole-genome genotyping approach (DArTseq). Results: Based on a single reduced-representation library, 31,262 polymorphic SNPs were identified across 650 individuals obtained from Australian wild stocks and commercial aquaculture populations. After filtering to remove SNPs with low read depth, low MAF, low call rate, deviation from HWE, and non-Mendelian inheritance, 7542 high-quality SNPs were retained. From these, 4236 high-quality genome-wide loci were selected for baits-probe development and 4194 SNPs were included within a finalized target-capture genotype-by-sequence assay (DArTcap). This assay was designed for routine and cost effective commercial application in large scale breeding programs, and demonstrates higher confidence in genotype calls through increased call rate (from 80.2 ± 14.7 to 93.0% ± 3.5%), increased read depth (from 20.4 ± 15.6 to 80.0 ± 88.7), as well as a 3-fold reduction in cost over traditional genotype-by-sequencing approaches. Conclusion: Importantly, this assay equips the P. monodon industry with the ability to simultaneously assign parentage of communally reared animals, undertake genomic relationship analysis, manage mate pairings between cryptic family lines, as well as undertake advance studies of genome and trait architecture. Critically this assay can be cost effectively applied as P. monodon breeding programs transition to undertaking genomic selection

Genetic admixture, inbreeding and heritability estimates in captive African cheetahs (Acinonyx jubatus) including linkage analysis for the King cheetah phenotype

This multifaceted study primarily aimed at understanding the genetic make-up of captive versus wild cheetah (Acinonyx jubatus) populations in South Africa, with a specific emphasis on a valuable gene pool of a recessive phenotype that is increasingly being maintained in captive population country-wide. The current literature on cheetah genetics has very little information on diversity levels of wild South African cheetahs, and no information on founder dynamics and genetic make-up of South African captive populations. Decisions on cheetah relocations are being made, implementing current conservation policy, from assumptions on origin and relatedness. This research compared population genetic parameters within the largest South African captive cheetah population to free-ranging Namibian and South African conspecifics. The study addressed concerns regarding excessive Namibian genetic introgression into the native captive population and established the extent of genetic variability and Namibian ancestry within the captive population. The study has attempted to address the rising concern among conservation officials with respect to illegal trade of wild-captured cheetahs, wild caught cheetahs that are sold as captive-bred after implanting a microchip. In addition to establishing routine parentage verification using genetic markers that are polymorphic in this species, this study established a technique powerful enough to estimate ancestry in cheetahs of unknown antecedents. The potential of spatial Bayesian clustering to differentiate the point of origin of unknown cheetahs was exploited and in addition, a database for future forensic efforts to address the problem of illegal trade was established. The captive population that was part of this dataset proved to be quite admixed, excepting for the King lineage which was distinct. The second aspect of this study investigated complex conditions such as development of gastritis, renal conditions and/or susceptibility to infections and its relation to pedigree and marker based inbreeding levels. Heritability values for important breeding traits were estimated from pedigree records of 532 cheetahs and are reported for the first time. Gastritis was weakly correlated to the expression of the King trait. Finally, a smaller cohort of the captive pedigree that segregates for a recessive colour variant called the King phenotype was tested for the assumption that the variation is a mutation of the tabby locus described in domestic cats. Genetic linkage analysis was done by testing microsatellite markers detected linked to Tabby for linkage to a conserved region in the cheetah that potentially codes for the King coat colour. Genetic linkage analysis was not detected between the King locus and the domestic cat microsatellite markers used for this study, with LOD scores remaining non-significant for all the markers.Thesis (PhD)--University of Pretoria, 2011.Production Animal Studiesunrestricte

Study on grain yield stability, molecular diversity and multi-trait relationships among elite soybean lines.

Master of Science in Plant Breeding. University of KwaZulu-Natal, Pietermaritzburg, 2018.The demand for soybean production has increased in recent years, due to its multipurpose use for human food, livestock feed and industrial purposes. The soybean crop is one of the important source of oil and protein of the world, and is used as a source of high quality edible oil and protein. For a quantitative trait, yield is known to be influenced by changes in the environment in which the crop is grown, suggesting the need to evaluate soybean lines in different growing regions to assess their adaptability and stability. In plant breeding, selection is one of the most important stages in the breeding cycle. Multi-location testing of soybean genotypes precedes selection while genetic characterisation of germplasm enhances selection due to the variation realised and it is the basis for genetic improvement. The objectives of the study were: 1) to determine yield stability and adaptability of elite soybean lines across six locations, 2) to study genotype by trait associations and multiple trait relationships among soybean elite lines across six locations and 3) to assess the level of genetic diversity among the soybean elite lines using single nucleotide polymorphisms (SNP) markers. The stability and adaptation study was carried out to investigate genotype by environment interaction (GEI) for grain yield of 26 elite soybean lines along with four checks grown in 6 environments spreading across three countries (Zambia, Malawi and Mozambique) in a 6 x 5 alpha lattice design. The additive main effect and multiplicative interaction model (AMMI) indicated that environments, genotypes and GEI significantly affected grain yield (P<0.001) and contributed 3.8%, 17% and 78%, respectively, to the total variation. Three AMMI interaction principal components (IPCA1, IPCA2 and IPCA3) were significant (P<0.01). Genotype plus GEI (GGE) biplots were created based on the first two principal components, PC1 and PC2, which accounted for 39.23% and 26.86% of genotype plus GEI variation, respectively. The GGE biplot analysis ranked the genotypes for yield and stability, and environments for representativeness and discriminativeness. The relationships between genotypes and environments were also demonstrated. Genotype TGX 2001-3FM was identified as the ideal genotype with high yield mean performance and high stability. Therefore, it could be recommended for cultivar release if the study can be repeated to verify these findings. Chitedze in Malawi was the most informative test environment hence it is ideal for selecting generally adapted genotypes. Genotypes TGX 2002-4FM and TGX 2001-15DM were low yielding but with high stability hence can be recommended for further improvements. For the second objective, a study was conducted using 30 genotypes to determine the correlation and path coefficient of secondary traits on yield. The genotype by trait biplot is a tool that graphically compares genotypes on the basis of multiple traits and graphically visualises trait relationships, and genotype-trait associations. Trait profiling of genotypes through genotype-trait association analysis helps in making decisions on which genotypes to use as parents for a breeding programme. Significant differences among genotypes were observed for all studied traits. Correlation coefficient analysis presented that grain yield had a significant and negative correlation with days to 50% flowering. However, grain yield had a significant and positive correlation with plant height. Path coefficient analysis indicated that plant height and early vigour had a positive direct effect on yield while days to 50% flowering and days to 50% podding had negative indirect effects on yield via days to maturity. The genotype by trait biplot graphically showed consistent trait relationships and identified TGX 2001-3FM, TGX 2001-26DM and TGX 2002-3DM as genotypes that can be used as parents in breeding programmes for yield improvement. Estimation of genetic diversity among 48 soybean lines from the International Institute for Tropical Agriculture (IITA) was conducted using 348 SNP markers. The average gene diversity and genetic distance ranged from 0.42 to 0.55 with an average of 0.47 and 0.61 to 0.87, respectively. The polymorphic information content ranged from 0.44 to 0.50 with a mean of 0.48. Genotypes TGX 2002-3DM and TGX 2002-3FM had the highest genetic distance between them indicating that they were highly diverse. The AMOVA indicated highly significant differences at F=0.001 with among individuals, among populations and within individuals contributing 45%, 28% and 26%, respectively. The 48 soybean lines were clustered in three main groups. The study indicated that genetic diversity exists among the IITA tested lines. The information obtained from the study, can be fully utilised in future soybean breeding programmes through crossing of diverse parents in order to incorporate new alleles to develop improved cultivars. In general, the study showed the existence of genotype by environment of soybean grain yield across the selected locations in southern Africa. Based on the SNP markers, the study confirmed the existence of wide genetic diversity among the soybean lines. The lines with superior performances can be used for future breeding programmes or recommended for cultivar release

Statistical identification of major genes in pigs

Litter size is an important characteristic in pig breeding. Apart from selection within available lines, also the development of a synthetic line with the Chinese Meishan breed could be an interesting approach to obtain a line with an increased level of litter size. To investigate genetic aspects of traits of interest in such a synthetic line, Dutch pig breeding companies have produced F 1 and F 2 Meishan x Western crossbreds. This thesis focusses on one important genetic aspect, the presence of major genes. In Chapters 2 to 4, statistical methodology to model a major gene inheritance is investigated and developed Chapters 5 and 6 consider analysis of data collected on the produced Meishan crossbreds for presence of major genes. To develop a synthetic line with Meishan, presence of major genes affecting litter size, growth and fatness is of interest. Additionally, the presence of major genes is investigated for meat quality traits.Statistical methodologyIn Chapter 2, the possibility to detect major genes by use of F 1 and F 2 is investigated. Here, special attention is paid to the situation where alleles at the major locus are fixed in the founder populations. Using 1000 F 2 observations, the power to detect major genes reaches more than 95% for additive and completely dominant effects (difference between homozygotes) of 4 and 2 residual standard deviations, respectively. When F, data is included, any increase in variance from F 1 to F 2 biases parameter estimates and leads to putative detection of a major gene. Also when in reality alleles at the major locus segregate in the founder populations, parameter estimates become biased, unless the average allele frequency in the founder populations is exactly 0.5. Use of data and use of a model in which alleles segregate in parents, e.g. F 3 data, is concluded to give better robustness and larger power. The latter is confirmed in a separate study, as referenced in Chapter 7, which shows that effects up to 4 times as small can be detected when alleles at the major locus segregate in the founder lines. Based on the findings in Chapter 2, Chapters 3 and 4 focus on the development of general models for a mixed inheritance. Use of such models is referred to as 'segregation analysis'.In Chapter 3, an advancement is made for use of analytical approaches to segregation analysis. It is noted that animal breeding pedigrees, as opposed to human pedigrees, generally contain many loops, such that exact computation of likelihoods isinfeasible. Loops in animal breeding pedigrees arise due to multiple matings, i.e. sires are generally mated to several dams, and due to inbreeding. Multiple matings generally already create many loops when considering 3-generation pedigrees. In Chapter 3, 'iterative peeling' is introduced, a method equivalent to the traditional recursive peeling method to compute exact likelihoods in non-looped pedigrees, but which also can be used to obtain approximate likelihoods in looped pedigrees. In simulations, hypothesis testing and parameter estimation are compared based on approximated likelihoods in looped pedigrees and exact likelihoods in non-looped pedigrees. This shows that no biases are introduced by the approximation in looped pedigrees. Iterative peeling is developed and investigated using a monogenic model, but could be extended to compute likelihoods for a mixed inheritance model. Such extension, however, was not made because an alternative non-analytical approach became available and was developed in Chapter 4. 0In Chapter 4, the application of Gibbs sampling is considered for inference in a mixed inheritance model. Gibbs sampling is a Markov chain Monte Carlo procedure which does not require analytical approximation. The approximation in such an approach is of a different nature: a marginal posterior distribution, or a feature thereof, is estimated based on a finite sample from the true posterior distribution. To generate such a sample, a Markov chain is constructed with an equilibrium distribution equal to the posterior distribution to be approximated. For application of Gibbs sampling to a mixed inheritance model, an implementation on scalar components, as used for human populations, appears not efficient because mixing of parameters in the Markov chain is slow. Therefore, an approach with blockwise sampling of genotypes is proposed for use in animal populations. The blockwise sampling, by which genotypes of a sire and its final progeny were sampled jointly, is effective to improve mixing. In Chapter 4 it is concluded that further measures to improve mixing could be looked for. In later Chapters such a further improvement is found in the additional use of a relaxation technique. In Chapter 4, inferences are made from a single Gibbs chain. In later Chapters, this approach is improved by use of multiple chains from which convergence of the Gibbs sampler is assessed by comparison of between- and within chain variances in an analysis- of-variance. The use of Bayesian estimators, which is feasible when using Gibbs sampling, is found preferable over the use of classical maximum likelihood estimators. In Chapter 7, it is discussed that the use of Bayeslian procedures fits in a general trend to better account for uncertainty in statistical estimation procedures.Analysis of dataIn Chapters 5 and 6, analysis of data obtained on the Meishan crossbreds is presented. In Chapter 5, presence of major genes affecting meat quality traits is investigated using data from F 2 individuals. Cooking loss, drip loss, two pH measurements, intramuscular fat, shearforce and back-fat thickness (by HGP measurement) are found to be likely influenced by a major gene. In all cases, a recessive allele is found, which originates from one of the founder lines, likely the Meishan breed. By studying associations between genotypes for major genes affecting the various traits, it is concluded that cooking loss, two pH measurements and possibly backfat thickness are influenced by one gene, and that a second gene influences intramuscular fat and possibly shearforce and drip loss. The statistical findings are supported by demonstrating marked differences in vanances of families of fathers inferred as carriers and families of fathers inferred as non-carriers.In Chapter 6, presence of major genes is investigated for two growth traits, backfat thickness (by" ultrasonic measurement) and litter size at first and second parity, using data from F 1 and F 2 crossbreds. Here, two analyses are performed for each trait. In a first analysis, joint analysis of F, and F 2 crossbred data is performed, in which different error variances are fitted for F 1 and F 2 observations. In this first analysis, significant contributions of major-gene variance are found for the two growth traits, for backfat, and for litter size at first parity. In a second analysis, analysis of F 2 data only is performed to check whether no biases are introduced in the joint analysis of F 1 and F 2 data. In the second analysis, no major genes are found for growth traits. Major genes affecting backfat and litter size at first parity are confirmed. Effects of the gene affecting backfat are similar to the effects of the gene affecting backfat identified in Chapter 5, and this likely is the same gene. The major genes affecting backfat and litter size are dominant genes, of which the recessive alleles can be considered unfavourable.. the recessive alleles of these genes cause an increase of backfat and a decrease of litter size.General results from the statistical analyses indicate that further molecular genetic research effort to map these genes will have a high probability of success. III Chapter 7 benefits are discussed from selection against the recessive alleles of the genes influencing backfat and litter size, as well as use of the gene affecting intramuscular fat to produce extra-tasty quality meat.ConclusionsIn this thesis, segregation analysis (SA) is made applicable for use in animal populations. SA will be a valuable addition to linkage analysis, where SA will be more typically applied to large amounts of data which are routinely collected. In the search for genes affecting quantitative traits, SA can directly identify functional genes, and can estimate genotypes of animals for such a functional gene. In combination with linkage analyses, this could supply important aids for molecular geneticists to locate functional genes. In this thesis, a number of major genes was identified to affect traits in the Meishan crosses. Further genetic analyses could generate more knowledge on the regulation of the quantitative traits involved and will aid in assessing the value of these genes for practical breeding. Chapter 8 additionally describes expected variance changes in a synthetic line, which could aid to optimise selection in such a line