Mapping and functional characterisation of the Atlantic salmon genome and its regulation of pathogen response

Atlantic salmon is a species of both scientific and economic importance, and Atlantic salmon farming is a highly profitable industry worldwide. One of the biggest challenges being faced by farms, which affects production efficiency and results in severe economic loss, is disease. In livestock production, one of the approaches taken to limit the impact of disease outbreaks is to selectively breed for improved resistance within farmed populations. Although traditional family-based resistance breeding programs have shown improvements in resistance to a variety of bacterial, viral and parasitic diseases on Atlantic salmon farms, response to selection can be slow. One way of increasing selection efficiency is through the incorporation of genetic markers into breeding programs, for marker-assisted or genomic selection. However, genomic resources for cultured aquatic species are sparse, and the generation of new and denser resources for use in selective breeding programs would be advantageous. The main focus of this thesis is the development of genomic resources in Atlantic salmon and the application of those resources to gain a better understanding of the salmon genome, particularly in the genetic basis of host resistance to infectious diseases. The first aim of this thesis was to develop improved genomic resources for Atlantic salmon, and to characterise the Atlantic salmon genome via construction and analysis of a SNP linkage map derived from RAD-Sequencing (RAD-Seq). Approximately 6,500 SNPs were assigned to 29 linkage groups, and ~1,800 male-segregating, and ~1,400 female-segregating SNPs were ordered and positioned. Overall map lengths and recombination ratios were relatively consistent between the sexes and across the linkage groups (~1:1.5, male:female). However, a substantial difference in the degree of marker clustering was seen between males and females, which is reflective of the difference in the positions of chiasmata between the two sexes. Using this map, ~4,000 Atlantic salmon reference genome contigs were assigned to a linkage group, and 112 contigs were assigned to multiple linkage groups, highlighting regions of homeology (large sections of duplicated chromosomal regions) within the salmon genome. Alignment of SNP-flanking sequences to the stickleback and rainbow trout genomes identified putative gene-associated SNPs and cross-species chromosomal orthologies, and provided evidence in support of the salmonid-specific genome duplication. In addition, based on this and other publically available RAD-Seq datasets, the utility of RAD-Seq-derived data from different species and laboratories for population genetics analyses was tested. Short RAD-Seq contigs in Atlantic salmon and nine other teleost fish were used to identify cross-species orthologous genomic relationships. Several thousands of orthologous RAD loci were identified across the species, with the number of RAD loci decreasing with evolutionary distance, as expected. Previously published broad-level relationships between orthologous chromosomes were confirmed. The identified cross-species orthologous RAD loci were used to estimate evolutionary relationships between the ten teleost fish species. Previously published relationships were recovered, suggesting that RAD-Seq data derived from different laboratories is useful for this purpose. The second aim was to characterise the genetic architecture of resistance to two viral diseases affecting Atlantic salmon production on farms: pancreas disease (PD), and infectious pancreatic necrosis (IPN). Using data and samples collected from a large population of salmon fry challenged with PD, a high heritability for resistance was estimated (h2 ~0.5), and four QTL were identified, on chromosomes 3, 4, 7 and 23. The QTL explaining the highest within-family variation for resistance was located on chromosome 3. This QTL has been confirmed in a population of post-smolts by an independent research group, highlighting the potential for its incorporation into breeding programs to improve PD resistance. For IPN, the major resistance QTL had previously been mapped to linkage group 21. However, the mutation(s) underlying this QTL effect and the consequences of these mutation(s) on the affected genes and relevant biological resistance mechanisms are unknown. To generate a list of candidate genes within the vicinity of the IPN QTL, QTL-linked DNA sequences were aligned to four model fish genomes. This identified two QTL-orthologous regions in each of the species, and gene order within these regions was highly conserved across species. Analysis of gene expression patterns between IPN resistant and susceptible salmon in a viral challenge experiment revealed that the five most significantly differentially-expressed genes mapped to the QTL-orthologous region on linkage group II of stickleback. Pathway enrichment analysis across all differentially-expressed genes suggests that biological pathways influencing viral infection stress response/entry/replication, cellular energy production and apoptosis may be involved in resistance during the initial stages of IPN virus (IPNV) infection. These results have provided the basis for further study of the putative involvement of these candidate genes and pathways in genetic resistance to IPNV. In summary, the results and resources presented in this thesis extend our current understanding of the salmon genome and the genetic basis of resistance to two viral diseases, and provide resources with the potential to be used in Atlantic salmon selective breeding programs to tackle disease outbreaks

Трансформация производства радиоформатов в российском радиовещании в конце 2000-х годов

Additional file 4: Table S1. Standardised cumulative proportion of times that haplotypes of the top 50 focal individuals selected by AlphaSeqOpt, the key ancestors approach (PEDIG) or the two haplotype-based approaches of Bickhart et al. [15] and Gusev et al. [16] appear in the rest of the population. Table S2. Standardised cumulative proportion of times that haplotypes of the top 200 focal individuals selected by AlphaSeqOpt, the key ancestors approach (PEDIG) or the two haplotype-based approaches of Bickhart et al. [15] and Gusev et al. [16] appear in the rest of the population. Table S3. The cumulative sum of the pedigree-inferred expected marginal contributions of the top 50 and 200 focal individuals selected by the key ancestors approach (implemented in the PEDIG software) for pedigrees of 5, 10, 15, 30 and 50 generations

The potential of shifting recombination hotspots to increase genetic gain in livestock breeding

Abstract Background This study uses simulation to explore and quantify the potential effect of shifting recombination hotspots on genetic gain in livestock breeding programs. Methods We simulated three scenarios that differed in the locations of quantitative trait nucleotides (QTN) and recombination hotspots in the genome. In scenario 1, QTN were randomly distributed along the chromosomes and recombination was restricted to occur within specific genomic regions (i.e. recombination hotspots). In the other two scenarios, both QTN and recombination hotspots were located in specific regions, but differed in whether the QTN occurred outside of (scenario 2) or inside (scenario 3) recombination hotspots. We split each chromosome into 250, 500 or 1000 regions per chromosome of which 10% were recombination hotspots and/or contained QTN. The breeding program was run for 21 generations of selection, after which recombination hotspot regions were kept the same or were shifted to adjacent regions for a further 80 generations of selection. We evaluated the effect of shifting recombination hotspots on genetic gain, genetic variance and genic variance. Results Our results show that shifting recombination hotspots reduced the decline of genetic and genic variance by releasing standing allelic variation in the form of new allele combinations. This in turn resulted in larger increases in genetic gain. However, the benefit of shifting recombination hotspots for increased genetic gain was only observed when QTN were initially outside recombination hotspots. If QTN were initially inside recombination hotspots then shifting them decreased genetic gain. Discussion Shifting recombination hotspots to regions of the genome where recombination had not occurred for 21 generations of selection (i.e. recombination deserts) released more of the standing allelic variation available in each generation and thus increased genetic gain. However, whether and how much increase in genetic gain was achieved by shifting recombination hotspots depended on the distribution of QTN in the genome, the number of recombination hotspots and whether QTN were initially inside or outside recombination hotspots. Conclusions Our findings show future scope for targeted modification of recombination hotspots e.g. through changes in zinc-finger motifs of the PRDM9 protein to increase genetic gain in production species

Linkage maps of the Atlantic salmon (Salmo salar) genome derived from RAD sequencing

BACKGROUND: Genetic linkage maps are useful tools for mapping quantitative trait loci (QTL) influencing variation in traits of interest in a population. Genotyping-by-sequencing approaches such as Restriction-site Associated DNA sequencing (RAD-Seq) now enable the rapid discovery and genotyping of genome-wide SNP markers suitable for the development of dense SNP linkage maps, including in non-model organisms such as Atlantic salmon (Salmo salar). This paper describes the development and characterisation of a high density SNP linkage map based on SbfI RAD-Seq SNP markers from two Atlantic salmon reference families. RESULTS: Approximately 6,000 SNPs were assigned to 29 linkage groups, utilising markers from known genomic locations as anchors. Linkage maps were then constructed for the four mapping parents separately. Overall map lengths were comparable between male and female parents, but the distribution of the SNPs showed sex-specific patterns with a greater degree of clustering of sire-segregating SNPs to single chromosome regions. The maps were integrated with the Atlantic salmon draft reference genome contigs, allowing the unique assignment of ~4,000 contigs to a linkage group. 112 genome contigs mapped to two or more linkage groups, highlighting regions of putative homeology within the salmon genome. A comparative genomics analysis with the stickleback reference genome identified putative genes closely linked to approximately half of the ordered SNPs and demonstrated blocks of orthology between the Atlantic salmon and stickleback genomes. A subset of 47 RAD-Seq SNPs were successfully validated using a high-throughput genotyping assay, with a correspondence of 97% between the two assays. CONCLUSIONS: This Atlantic salmon RAD-Seq linkage map is a resource for salmonid genomics research as genotyping-by-sequencing becomes increasingly common. This is aided by the integration of the SbfI RAD-Seq SNPs with existing reference maps and the draft reference genome, as well as the identification of putative genes proximal to the SNPs. Differences in the distribution of recombination events between the sexes is evident, and regions of homeology have been identified which are reflective of the recent salmonid whole genome duplication

AlphaSim: Software for Breeding Program Simulation

This paper describes AlphaSim, a software package for simulating plant and animal breeding programs. AlphaSim enables the simulation of multiple aspects of breeding programs with a high degree of flexibility. AlphaSim simulates breeding programs in a series of steps: (i) simulate haplotype sequences and pedigree; (ii) drop haplotypes into the base generation of the pedigree and select single-nucleotide polymorphism (SNP) and quantitative trait nucleotide (QTN); (iii) assign QTN effects, calculate genetic values, and simulate phenotypes; (iv) drop haplotypes into the burn-in generations; and (v) perform selection and simulate new generations. The program is flexible in terms of historical population structure and diversity, recent pedigree structure, trait architecture, and selection strategy. It integrates biotechnologies such as doubled-haploids (DHs) and gene editing and allows the user to simulate multiple traits and multiple environments, specify recombination hot spots and cold spots, specify gene jungles and deserts, perform genomic predictions, and apply optimal contribution selection. AlphaSim also includes restart functionalities, which increase its flexibility by allowing the simulation process to be paused so that the parameters can be changed or to import an externally created pedigree, trial design, or results of an analysis of previously simulated data. By combining the options, a user can simulate simple or complex breeding programs with several generations, variable population structures and variable breeding decisions over time. In conclusion, AlphaSim is a flexible and computationally efficient software package to simulate biotechnology enhanced breeding programs with the aim of performing rapid, low-cost, and objective in silico comparison of breeding technologies

A method for the allocation of sequencing resources in genotyped livestock populations

International audienceAbstractBackgroundThis paper describes a method, called AlphaSeqOpt, for the allocation of sequencing resources in livestock populations with existing phased genomic data to maximise the ability to phase and impute sequenced haplotypes into the whole population.MethodsWe present two algorithms. The first selects focal individuals that collectively represent the maximum possible portion of the haplotype diversity in the population. The second allocates a fixed sequencing budget among the families of focal individuals to enable phasing of their haplotypes at the sequence level. We tested the performance of the two algorithms in simulated pedigrees. For each pedigree, we evaluated the proportion of population haplotypes that are carried by the focal individuals and compared our results to a variant of the widely-used key ancestors approach and to two haplotype-based approaches. We calculated the expected phasing accuracy of the haplotypes of a focal individual at the sequence level given the proportion of the fixed sequencing budget allocated to its family.ResultsAlphaSeqOpt maximises the ability to capture and phase the most frequent haplotypes in a population in three ways. First, it selects focal individuals that collectively represent a larger portion of the population haplotype diversity than existing methods. Second, it selects focal individuals from across the pedigree whose haplotypes can be easily phased using family-based phasing and imputation algorithms, thus maximises the ability to impute sequence into the rest of the population. Third, it allocates more of the fixed sequencing budget to focal individuals whose haplotypes are more frequent in the population than to focal individuals whose haplotypes are less frequent. Unlike existing methods, we additionally present an algorithm to allocate part of the sequencing budget to the families (i.e. immediate ancestors) of focal individuals to ensure that their haplotypes can be phased at the sequence level, which is essential for enabling and maximising subsequent sequence imputation.ConclusionsWe present a new method for the allocation of a fixed sequencing budget to focal individuals and their families such that the final sequenced haplotypes, when phased at the sequence level, represent the maximum possible portion of the haplotype diversity in the population that can be sequenced and phased at that budget

Potential of gene drives with genome editing to increase genetic gain in livestock breeding programs

Abstract Background This paper uses simulation to explore how gene drives can increase genetic gain in livestock breeding programs. Gene drives are naturally occurring phenomena that cause a mutation on one chromosome to copy itself onto its homologous chromosome. Methods We simulated nine different breeding and editing scenarios with a common overall structure. Each scenario began with 21 generations of selection, followed by 20 generations of selection based on true breeding values where the breeder used selection alone, selection in combination with genome editing, or selection with genome editing and gene drives. In the scenarios that used gene drives, we varied the probability of successfully incorporating the gene drive. For each scenario, we evaluated genetic gain, genetic variance ( \u3c3 A 2 ) , rate of change in inbreeding ( \u394 F ), number of distinct quantitative trait nucleotides (QTN) edited, rate of increase in favourable allele frequencies of edited QTN and the time to fix favourable alleles. Results Gene drives enhanced the benefits of genome editing in seven ways: (1) they amplified the increase in genetic gain brought about by genome editing; (2) they amplified the rate of increase in the frequency of favourable alleles and reduced the time it took to fix them; (3) they enabled more rapid targeting of QTN with lesser effect for genome editing; (4) they distributed fixed editing resources across a larger number of distinct QTN across generations; (5) they focussed editing on a smaller number of QTN within a given generation; (6) they reduced the level of inbreeding when editing a subset of the sires; and (7) they increased the efficiency of converting genetic variation into genetic gain. Conclusions Genome editing in livestock breeding results in short-, medium- and long-term increases in genetic gain. The increase in genetic gain occurs because editing increases the frequency of favourable alleles in the population. Gene drives accelerate the increase in allele frequency caused by editing, which results in even higher genetic gain over a shorter period of time with no impact on inbreeding