Diversity and genetic architecture of agro-morphological traits in a core collection of European traditional tomato

European traditional tomato varieties have been selected by farmers given their consistent performance and adaptation to local growing conditions. Here we developed a multipurpose core collection, comprising 226 accessions representative of the genotypic, phenotypic, and geographical diversity present in European traditional tomatoes, to investigate the basis of their phenotypic variation, gene×environment interactions, and stability for 33 agro-morphological traits. Comparison of the traditional varieties with a modern reference panel revealed that some traditional varieties displayed excellent agronomic performance and high trait stability, as good as or better than that of their modern counterparts. We conducted genome-wide association and genome-wide environment interaction studies and detected 141 quantitative trait loci (QTLs). Out of those, 47 QTLs were associated with the phenotype mean (meanQTLs), 41 with stability (stbQTLs), and 53 QTL-by-environment interactions (QTIs). Most QTLs displayed additive gene actions, with the exception of stbQTLs, which were mostly recessive and overdominant QTLs. Both common and specific loci controlled the phenotype mean and stability variation in traditional tomato; however, a larger proportion of specific QTLs was observed, indicating that the stability gene regulatory model is the predominant one. Developmental genes tended to map close to meanQTLs, while genes involved in stress response, hormone metabolism, and signalling were found within regions affecting stability. A total of 137 marker–trait associations for phenotypic means and stability were novel, and therefore our study enhances the understanding of the genetic basis of valuable agronomic traits and opens up a new avenue for an exploitation of the allelic diversity available within European traditional tomato germplasmThis work was supported by European Commission H2020 research and innovation program through TRADITOM grant agreement no. 634561, G2P-SOL, grant agreement no. 677379, and HARNESSTOM grant agreement no. 101000716. Networking activities were funded by COST Actions “EUROCAROTEN CA15136 and ‘RoxyCOST’ CA18210 ‘RoxyCOSTPostprint (published version

Molecular Characterization of Jatropha curcas Resources and Identification of Population-Specific Markers

Jatropha curcas L. is cited as one of the best candidates for future oil and biodiesel production. It is widespread in many tropical and subtropical countries but has not yet received much genetic improvement. The objective of this study was to collect Jatropha germplasm and characterize it with molecular markers. A total of 64 genotypes, collected from seven geographic locations on two continents, were analyzed with 32 simple sequence repeat and two candidate gene-specific primers (ISPJ-1 gene and Curcin-P2 gene promoter). In general, markers were found to be highly conserved, and many (40%) were monomorphic in the studied populations. Polymorphic primers, which amplified population-specific fragments, were identified. The polymorphic information content of the polymorphic markers ranged from 0.03 to 0.47. Genetic similarity analysis identified two distinct groups at 0.73 DICE similarity coefficient. Group I included germplasm collected from the islands of Cuba and Cape Verde, and group II consisted of Brazil, Mozambique, and Senegal populations. Island genotypes were found to be very distinct compared to their mainland counterparts. Sequencing of monomorphic fragments identified single nucleotide polymorphism (SNP) between these two groups. High-resolution melting analysis of the SNP in the Jcps9 locus further confirmed the two gene pools. Sequencing of polymorphic fragments of the Jc03 locus identified a deletion in a (GT)4 repeat motif in the genotypes in group II. Several population-specific microsatellites and SNP markers have been recognized. The distinct Jatropha genotypes and the population-specific molecular markers identified in this study will be valuable resources in breeding programs

Association mapping and genomic selection for sorghum adaptation to tropical soils of Brazil in a sorghum multiparental random mating population.

Tropical soils where low phosphorus (P) and aluminum (Al) toxicity limit sorghum [Sorghum bicolor (L.) Moench] production are widespread in the developing world. We report on BRP13R, a multiparental random mating population (MPRMP), which is commonly used in sorghum recurrent selection targeting tropical soil adaptation. Recombination dissipated much of BRP13R?s likely original population structure and average linkage disequilibrium (LD) persisted up to 2.5 Mb, establishing BRP13R as a middle ground between biparental populations and sorghum association panels. Genome-wide association mapping (GWAS) identifed conserved QTL from previous studies, such as for root morphology and grain yield under low-P, and indicated the importance of dominance in the genetic architecture of grain yield. By overlapping consensus QTL regions, we mapped two candidate P efciency genes to a ~5 Mb region on chromosomes 6 (ALMT) and 9 (PHO2). Remarkably, we fnd that only 200 progeny genotyped with~45,000 markers in BRP13R can lead to GWAS-based positional cloning of naturally rare, subpopulation-specifc alleles, such as for SbMATE-conditioned Al tolerance. Genomic selection was found to be useful in such MP-RMP, particularly if markers in LD with major genes are ftted as fxed efects into GBLUP models accommodating dominance. Shifts in allele frequencies in progeny contrasting for grain yield indicated that intermediate to minor-efect genes on P efciency, such as SbPSTOL1 genes, can be employed in pre-breeding via allele mining in the base population. Therefore, MP-RMPs such as BRP13R emerge as multipurpose resources for efcient gene discovery and deployment for breeding sorghum cultivars adapted to tropical soils

GENOMIC VARIATION IN LIVESTOCK USING DENSE SNP CHIP DATA

Part I describes two possible approaches to investigate Mexican chicken genetic variation, using selective sweeps and Copy Number Variants (CNV). CNVs are genomic polymorphisms that influence phenotypic expression and are an important source of genetic variation in populations. The aim of the first study here presented was to characterize the genetic variability of the Mexican chicken\u2019s population and to disclose any underlying population structure. A total of 213 chickens were sampled in different rural production units located in 25 states of M\ue9xico. Genotypes were obtained using the Affymetrix Axiom\uae 600K Chicken Genotyping Array. The Identity by Descent (IBD) and the Principal Components Analysis (PCA) were performed by SVS software on pruned SNPs. Analyses done with ADMIXTURE identified three ancestors and determined, for each individual, the proportion of the genetic contribution from each of the three ancestors. The results of the Neighbor-Joining (NJ) analysis were consistent with those obtained by the PCA. All methods used in this study did not allow a classification of Mexican chicken in distinct genetic groups. A total of 3,059 Run of homozygosity (ROH) were identified and, being mainly short in length (< 4 Mb), these regions are indicative of a low inbreeding level in the population. Finally, findings from the ROH analysis indicated the presence of natural selective pressure in the population of Mexican chicken. In the second study we used CNVs to investigate genetic variability in the Mexican Creole chicken and to relate this variation to the available gene annotation. The Hidden Markov Model of the PennCNV software detected a total of 1,924 CNVs in the chicken genome of 256 individuals. Input data were LOGR Ratio and B allele frequency obtained with the Axiom\uae Genome-Wide Chicken Genotyping Array (Affymetrix). The mapped CNVs comprised 1,538 gains and 386 losses resulting, at population level, in 1,216 CNV regions (CNVRs), of which 959 gains, 226 losses and 31 complexes (i.e. containing both losses and gains). The CNVRs covered a total of 47 Mb of the whole genome sequence length, corresponding to 5.12 % of the chicken galGal4 autosome assembly. This study allowed a deep insight into the structural variation in the genome of unselected Mexican chicken population, which up to now has not been genetically characterized. The genomic study disclosed that the population, even if presenting extreme morphological variation, couldn\u2019t be organized in differentiated genetic subpopulations. Finally, this study provided a chicken CNV map based on the 600K SNP chip array, jointly with a genome-wide gene copy number estimates in a native, unselected for more than 500 years, chicken population. Genetic variation can be caused by adaptive evolutionary changes and by artificial selection. The genetic makeup of populations is the result of a long-term process of selection and adaptation to specific environments and ecosystems. The two studies here presented indicate that the Mexican chicken clearly appear to be a unique Creole chicken population that was not subjected to a specific directional selection. Results provide a genetic knowledge that can be used as a basis for the genetic management of a unique genetic resource. Industry is likely envisaging to use the female native populations mating them with selected males to increase the productivity and the economic revenue of family farming agriculture, which is a large reality of United States of M\ue9xico. \u2022 Part II describes a CNV scan and a population analysis of turkey populations coming from different countries. The domesticated turkey was brought to Europe in late 1500 by Spanish conquerors from Central America, likely from Mexico. The evolution of the Mexican turkey population occurred as such independently for more than 500 years from the European ones and the commercial hybrids. This study investigates the genomic diversity of several turkey populations using CNVs as source of variation. A total of 116 individuals from 6 Italian breeds (Colle Euganei, Bronzato Comune Italiano, Parma e Piacenza, Brianzolo, Nero d\u2019Italia and Ermellinato di Rovigo), 7 Narragansett, 38 commercial hybrids and 31 Mexican turkeys, were processed with the Affymetrix 600K SNP turkey array. The CNV calling was performed with the HMM of PennCNV software. CNV were summarized into CNV regions (CNVRs) at population level using BEDTools. Variability among populations has been addressed by hierarchical clustering (pvclust R package) and by principal component analysis (PCA). A total of 2,987 CNV were identified covering 4.65% of the autosomes of the Turkey_5.0/melGal5 assembly. The CNVRs including at least 2 individuals were 362, 189 gains, 116 losses and 57 complexes. Among these regions the 51% contain genes. This study is the first CNV mapping of turkey population using 600K SNP chip. CNVs clustered the individuals according to population and their geographical origin. CNVs are also known to be indicators of adaptation, as some researches are suggesting investigating different species. The outcomes of this are likely reflecting the human action on domestication of domesticated turkey after its introduction into Europe and the directional selection occurring in the last 40 years to produce a fast-growing heavy bird. \u2022 Part III describes the CNV mapping in the Valdostana Red Pied (VRP) cattle breed, an autochthonous Italian dual-purpose cattle population reared in the Alps, and the comparison with the CNV maps detected in previous studies in the Italian Brown Swiss (IBS) and in the Mexican Holstein (HOL). Many studies have focused on identifying CNVs within and between human and livestock populations alike, but only few have explored population-genetic properties in cattle based on CNVs derived from a high-density SNP array. In this study in cattle we report a high-resolution CNV scan, using the Illumina 777k BovineHD Beadchip, for VRP, a population that did not undergo strong selection for production traits. After stringent quality control and filtering, CNVs were called across 108 bulls using the PennCNV software. A total of 6,784 CNVs were identified, summarized to 1,723 CNV regions (CNVRs) on 29 autosomes covering a total of ~59 Mb of the UMD3.1 assembly. Among the mapped CNVRs, there were 812 losses, 832 gains and 79 complexes. A total of 171 CNVRs were common to VRP, IBS and HOL. Between VRP and IBS, 474 regions overlapped, while only 313 were in common between VRP and HOL, indicating a more similar genetic structure among populations with common origins, i.e. the Alps. The clustering and admixture analyses showed a clear separation of the three breeds into three distinct clusters. In order to describe the distribution of CNVs within and among breeds we used the pair VST statistic. We considered only the CNVRs shared by more than 5 individuals within breed. We identified unique and highly differentiated CNVs (n=33), some of which could be due to specific breed selection and adaptation. Genes and QTL within these regions were also characterized adding evidence to the relationship between CNV and adaptation

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

Large-scale whole-genome resequencing unravels the domestication history of Cannabis sativa.

Cannabis sativa has long been an important source of fiber extracted from hemp and both medicinal and recreational drugs based on cannabinoid compounds. Here, we investigated its poorly known domestication history using whole-genome resequencing of 110 accessions from worldwide origins. We show that C. sativa was first domesticated in early Neolithic times in East Asia and that all current hemp and drug cultivars diverged from an ancestral gene pool currently represented by feral plants and landraces in China. We identified candidate genes associated with traits differentiating hemp and drug cultivars, including branching pattern and cellulose/lignin biosynthesis. We also found evidence for loss of function of genes involved in the synthesis of the two major biochemically competing cannabinoids during selection for increased fiber production or psychoactive properties. Our results provide a unique global view of the domestication of C. sativa and offer valuable genomic resources for ongoing functional and molecular breeding research

Genetisk diversitet, seleksjonssignaturer og ernæringmessig sammensetning av enset (Ensete ventricosum) fra Etiopia

Most of the agrobiodiversity exists in the form of landraces and wild relatives in traditional smallholderbased farming systems. This diversity mainly exists among neglected and underutilized species, so called orphan crops. Moreover, climate change has a huge negative impact on agriculture resulting in uncertainty as regard agricultural productivity, particularly in food-insecure countries. Within this frame, this thesis focuses on enset (Ensete ventricosum), an important crop in Ethiopia which is a good example of a neglected and underutilized orphan crop. Three types of enset are present in Ethiopia, i.e., cultivated enset which is a large, perennial, and single-stemmed type propagated by induced suckers, the Entada landrace propagated by natural suckers, and wild enset propagated by seed. Enset is not well characterized at the genomic level and information on the variation in nutritional composition in diverse Ethiopian ensets is scarce. A number of cultivated and Entada enset genotypes, and some wild ensets were collected from farmers, natural habitats, and research fields in the southern regions Sidama, Gurage, and South Omo in Ethiopia. The aim was to study the genetic diversity, population structure, selection signatures, nutritional compositions, and content of bioactive compounds among and within all different form of enset.Det meste av agrobiodiversiteten eksisterer i form av landraser og ville slektninger i tradisjonelle småbruksbaserte dyrkingssystemer. Dette mangfoldet eksisterer hovedsakelig blant forsømte og underutnyttede arter, såkalte ‘orphan crops’. Klimaendringene har dessuten en enorm negativ innvirkning på landbruket, noe som resulterer i usikkerhet når det gjelder jordbruksproduktivitet, spesielt i land med usikker matforsyning. Innenfor denne rammen fokuserer denne oppgaven på enset (Ensete ventricosum), en viktig matplante i Etiopia og et godt eksempel på en forsømt og underutnyttet ‘orphan crop’. Enset er ikke godt karakterisert på genomisk nivå, og informasjon om variasjon i ernæringsmessig sammensetning i forskjellige type enset fra Etiopia er mangelfull. En rekke dyrkede sorter/genotyper, samt genotyper av Entada og noen ville genotyper, ble samlet inn fra bønder, naturlige habitater og forskningsfelt i de sørlige regionene Sidama, Gurage og South Omo i Etiopia. Målet var å studere genetisk diversitet, populasjonsstruktur, seleksjonssignaturer, ernæringsmessige sammensetning og innhold av bioaktive stoffer blant og innen de ulike typer enset

Characterisation of sweet sorghum germplasm based on agro-morphological traits, molecular markers and juice related traits.

Master of Science in Plant Breeding. University of KwaZulu-Natal, Pietermaritzburg, 2018.There is rising interest for alternative energy sources because of the decline in fossil fuel production and concern over environmental pollution. Currently most biofuel is based on maize and sugar cane as raw materials. However, the use of feedstocks has triggered concerns related to food security, while sugar cane has a high-water consumption and high production requirements amongst other drawbacks. A crop which meets several requirements for biofuel (such as high biomass yield and growth rate, perennial growth, low input requirements, adaptation to the marginal areas, and tolerance to multiple stresses) is sweet sorghum. This study, therefore, aimed at characterising sweet sorghum germplasm using agro-morphological traits and molecular markers (single nucleotide polymorphisms (SNP) during the 2016-2017 summer season at two sites (Ukulinga farm and Potchefstroom). Fourteen quantitative traits were evaluated in an alpha lattice (10 x 5) design with three replications. Analysis of variance for the quantitative traits revealed high levels of genetic variability. This implies that morphological traits differed greatly with a significant G x E interaction across the two sites. Most of the accessions yielded high at Ukulinga than Potchefstroom on juice yield and %brix with a mean yield of 9 605 l/ha and 16.3%, respectively. Most of the accessions studied were early to medium maturing, as evidenced by the mean number of days to 50% flowering (74 days). Analysis of principle components showed that the first four principle components (PC) accounted for 79.12% of the total variation and that some quantitative traits were significantly positively correlated. The estimates for phenotypic coefficient of variation (PCV) were higher than those of genetic coefficient of variation (GCV) for all the traits, indicating the influence of the environment on these traits. However, GCV values for days to 50% flowering, plant height, stalk diameter and stalk yield were very close to PCV. This indicated minimal influence of the environment on the phenotypic expression of these traits. The highest broad sense heritability (H2) of 99.2% was recorded for plant height. Juice volume had the highest expected genetic advance, expressed as a percentage of mean (GAM) of 131.2%. Days to 50% flowering were significantly and positively correlated to plant height, stalk diameter, number of leaves, stalk yield, brix, juice volume and bagasse weight, but negatively significantly correlated to panicle length, panicle width, panicle weight and 1000 grain weight. Plant height was significantly positively correlated to stalk diameter, number of leaves per plant, stalk yield, juice volume and fresh bagasse weight. Bagasse weight, brix, stalk diameter, plant height and number of leaves had a highly positive and direct contribution on juice yield. Several traits had a highly positively and indirect contribution on juice yield via these traits which had a direct contribution. This revealed primary and secondary traits with practical relevance to sweet sorghum improvement programme, because they showed direct and indirect effects on juice yield (volume), which ultimately translates to sugar yield for ethanol production. Kompetitive Allele Specific Polymorphism (KASP) genotyping using 137 SNP markers revealed a considerable level of genetic diversity among the sweet sorghum accessions. Three populations were generated from the analysis. The expected heterozygosity (He) values ranged from 0.236 to 0.291 with a mean of 0.266. The mean of effective alleles across populations was of 1.438. The percentage of polymorphic loci ranged from 80.29% to 91.24% with a mean of 86.86%. Dissimilarity indices ranged from 0.000 to 0.583 with a mean of 0.296. The highest dissimilarity index was observed between SA 2193 and SA 2014, which implied a considerable amount of genetic diversity. Accessions were clustered into three main groups based on dissimilarity indices. The study identified SA 4490, SA 2400, SA 4495, SA 2193 and SA 4479 as superior accessions in juice yield. These accessions should be used as parents in sweet sorghum improvement programme

NESTED ASSOCIATION MAPPING TO IDENTIFY SEED COMPOSITION QTL IN DIVERSE SOYBEAN LINES

Soybeans are economically the most important legume grown worldwide. It provides quality protein and oil to food and feed markets in addition to being used for industrial products. The value of soybean could be enhanced by increasing protein, oil, and sucrose contents, while lowering anti-nutritional compounds such as oligosaccharides. Understanding the genetic and environmental factors controlling soybean seed composition is an essential prerequisite for such an endeavor. Three separate studies were initiated to understand the underlying genetics governing soybean seed compositional traits

The Development of Genetic Resources to Futureproof Shellfish Aquaculture against Climate Change

The global population is expected to reach 9.7 billion people by 2050. Therefore, sustainable intensification of the food system to support the increasing population under a changing climate is vital. Aquaculture is the fastest expanding food sector globally, but projections suggest this industry will be severely impacted by anthropogenically induced climate change in the coming decades. Genomic selection has been highlighted by the Food and Agriculture Organisation (FAO) as an avenue to ensure the aquaculture industry will thrive under future climatic conditions, fast-tracking breeding of specialised lines. Following this line of reasoning, the work in this thesis aimed to contribute to the advances in genomic breeding of marine molluscs, a highly sustainable source of animal protein. In the first chapter, I reviewed the existing literature on shellfish aquaculture, exploring how the current production systems and aquaculture practices may impact the genetic diversity of the produced stock and, consequently, the success of any proposed genomic breeding in these taxa, alongside identifying the main gaps in our current knowledge in this field. Subsequently, each experimental chapter of this thesis then addressed a separate gap in our current understanding. In chapter II, I developed a multi-species 60 K SNP-array applicable for genotyping four mussel species relevant for aquaculture: M. edulis, M. galloprovincialis, M. chilensis and M. trossulus. Following low-coverage whole genome sequencing of 138 mussels, ~60K SNPs were implemented in the platform, from which 23,252 are applicable for genotyping M. edulis individuals, 22,165 for M. chilensis, 20,504 SNPs M. galloprovincialis and 20,149 for M. trossulus. This tool therefore represents a major advance in the current technological capability available in this species complex, and will allow researchers to explore the genetic diversity of mussels using a dense number of markers (on the scale of thousands), whilst producing comparable data among studies. It is also applicable for breeding purposes and may facilitate future implementation of genomic selection in these taxa. Subsequently, in chapter III, I applied this SNP-array to explore the genomic structure of blue mussels in South West England; an important area for mussel aquaculture and a region that has been key for our understanding of hybrid zone dynamics, between the species M. galloprovincialis and M. edulis, historically. Results from this chapter agree with the previous description of the hybrid zone, with M. galloprovincialis genotypes dominating the north coast of Cornwall whilst M. edulis is the prevailing species in the southern coast of SW England. Furthermore, the transition zone between the two species was located at Lizard Point. These results validate the utility of the SNP-array for determining speciation across a wide region, and update our knowledge in genotype distribution in this key hybrid zone. In the thesis’ fourth chapter, I explored how selection towards environmental resilience impacts the phenotypes and/or genotypes of blue mussels. For this, I compared the genetic diversity and performance of juvenile mussels exposed to a thermal stress event to those of individuals which did not faced it. Results from this chapter suggest that thermal resilience may impact the performance of mussels, as stressed individuals presented a lower dry tissue weight (g) than naïve ones. In addition, a shift towards M. edulis genotypes occurred in the selected cohort. With climate change expected to increase the average sea surface temperature of the ocean, results presented in this thesis shows that such changes may impact the genetic background of mussel spat in the Baltic Sea and possibly. Such results may also impact aquaculture production of this species. In the final chapter, I discuss how the research questions explored in this thesis advance our knowledge in marine bivalve genomics and how they may change the field by supporting the development and application of genomic approaches for breeding these taxa.Natural Environment Research Council (NERC