Genomic Signatures of Domestication Selection in the Australasian Snapper (Chrysophrys auratus)

Domestication of teleost fish is a recent development, and in most cases started less than 50 years ago. Shedding light on the genomic changes in key economic traits during the domestication process can provide crucial insights into the evolutionary processes involved and help inform selective breeding programmes. Here we report on the recent domestication of a native marine teleost species in New Zealand, the Australasian snapper (Chrysophrys auratus). Specifically, we use genome-wide data from a three-generation pedigree of this species to uncover genetic signatures of domestication selection for growth. Genotyping-By-Sequencing (GBS) was used to generate genome-wide SNP data from a three-generation pedigree to calculate generation-wide averages of FST between every generation pair. The level of differentiation between generations was further investigated using ADMIXTURE analysis and Principal Component Analysis (PCA). After that, genome scans using Bayescan, LFMM and XP-EHH were applied to identify SNP variants under putative selection following selection for growth. Finally, genes near candidate SNP variants were annotated to gain functional insights. Analysis showed that between generations FST values slightly increased as generational time increased. The extent of these changes was small, and both ADMIXTURE analysis and PCA were unable to form clear clusters. Genome scans revealed a number of SNP outliers, indicative of selection, of which a small number overlapped across analyses methods and populations. Genes of interest within proximity of putative selective SNPs were related to biological functions, and revealed an association with growth, immunity, neural development and behaviour, and tumour repression. Even though few genes overlapped between outlier SNP methods, gene functionalities showed greater overlap between methods. While the genetic changes observed were small in most cases, a number of outlier SNPs could be identified, of which some were found by more than one method. Multiple outlier SNPs appeared to be predominately linked to gene functionalities that modulate growth and survival. Ultimately, the results help to shed light on the genomic changes occurring during the early stages of domestication selection in teleost fish species such as snapper, and will provide useful candidates for the ongoing selective breeding in the future of this and related species.

Clustering patterns mirror the geographical distribution and genetic history of Lemnos and Lesvos sheep populations

Elucidating the genetic variation and structure of Lemnos and Lesvos sheep is critical for maintaining local genetic diversity, ecosystem integrity and resilience of local food production of the two North Aegean islands. In the present study, we explored genetic diversity and differentiation as well as population structure of the Lemnos and Lesvos sheep. Furthermore, we sought to identify a small panel of markers with the highest discriminatory power to assign animals across islands. A total number of n = 424 (n = 307, Lemnos and n = 117, Lesvos) ewes, sampled from n = 24 herds dispersed at different geographic regions on the two islands, were genotyped with the 50K SNP array. Mean observed heterozygosity was higher (but not statistically significantly different) in Lesvos than in Lemnos population (0.384 vs. 0.377) while inbreeding levels were higher in Lemnos than Lesvos herds (0.065 vs. 0.031). Results of principal components along with that of admixture analysis and estimated genetic distances revealed genetic clusters corresponding to Lesvos and Lemnos origin and the existence of infrastructure within islands that were associated with geographical isolation and genetic history of the studied populations. In particular, genetic analyses highlighted three geographically isolated herds in Lemnos that are located at mountainous areas of the island and are characterized as representatives of the local sheep by historic data and reports. Admixture analysis also showed a shared genetic background between Lemnos and Lesvos sheep attributable to past gene flow. Little overall genetic differentiation was detected between the two island sheep populations, while 150 discriminatory SNPs could accurately assign animals to their origin. Present results are comparable with those reported in the worldwide sheep breeds, suggesting geography related genetic patterns across and within islands and the existence of the local Lemnos sheep.

Keep Garfagnina alive. An integrated study on patterns of homozygosity, genomic inbreeding, admixture and breed traceability of the Italian Garfagnina goat breed

The objective of this study was to investigate the genetic diversity of the Garfagnina (GRF) goat, a breed that currently risks extinction. For this purpose, 48 goats were genotyped with the Illumina CaprineSNP50 BeadChip and analyzed together with 214 goats belonging to 9 other Italian breeds (~25 goats/breed), whose genotypes were available from the AdaptMap project [Argentata (ARG), Bionda dell’Adamello (BIO), Ciociara Grigia (CCG), Di Teramo (DIT), Garganica (GAR), Girgentana (GGT), Orobica (ORO), Valdostana (VAL) and Valpassiria (VSS)]. Comparative analyses were conducted on i) runs of homozygosity (ROH), ii) admixture ancestries and iii) the accuracy of breed traceability via discriminant analysis on principal components (DAPC) based on cross-validation. ROH analyses was used to assess the genetic diversity of GRF, while admixture and DAPC to evaluate its relationship to the other breeds. For GRF, common ROH (more than 45% in GRF samples) was detected on CHR 12 at, roughly 50.25–50.94Mbp (ARS1 assembly), which spans the CENPJ (centromere protein) and IL17D (interleukin 17D) genes. The same area of common ROH was also present in DIT, while a broader region (~49.25–51.94Mbp) was shared among the ARG, CCG, and GGT. Admixture analysis revealed a small region of common ancestry from GRF shared by BIO, VSS, ARG and CCG breeds. The DAPC model yielded 100% assignment success for GRF. Overall, our results support the identification of GRF as a distinct native Italian goat breed. This work can contribute to planning conservation programmes to save GRF from extinction and will improve the understanding of the socio-agro-economic factors related with the farming of GRF.

Admixture Analysis Using Genotyping-by-Sequencing Reveals Genetic Relatedness and Parental Lineage Distribution in Highbush Blueberry Genotypes and Cross Derivatives

Blueberries (Vaccinium section Cyanococcus) are perennial shrubs widely cultivated for their edible fruits. In this study, we performed admixture and genetic relatedness analysis of northern highbush (NHB, primarily V. corymbosum) and southern highbush (SHB, V. corymbosum introgressed with V. darrowii, V. virgatum, or V. tenellum) blueberry genotypes, and progenies of the BNJ16-5 cross (V. corymbosum × V. darrowii). Using genotyping-by-sequencing (GBS), we generated more than 334 million reads (75 bp). The GBS reads were aligned to the V. corymbosum cv. Draper v1.0 reference genome sequence, and ~2.8 million reads were successfully mapped. From the alignments, we identified 2,244,039 single-nucleotide polymorphisms, which were used for principal component, haplotype, and admixture analysis. Principal component analysis revealed three main groups: (1) NHB cultivars, (2) SHB cultivars, and (3) BNJ16-5 progenies. The overall fixation index (FST) and nucleotide diversity for NHB and SHB cultivars indicated wide genetic differentiation, and haplotype analysis revealed that SHB cultivars are more genetically diverse than NHB cultivars. The admixture analysis identified a mixture of various lineages of parental genomic introgression. This study demonstrated the effectiveness of GBS-derived single-nucleotide polymorphism markers in genetic and admixture analyses to reveal genetic relatedness and to examine parental lineages in blueberry, which may be useful for future breeding plans.

Admixture Analysis Using Genotyping-by-Sequencing Reveals Genetic Relatedness and Parental Lineage Distribution in Highbush Blueberry Genotypes and Cross Derivatives

Blueberries (Vaccinium section Cyanococcus) are perennial shrubs widely cultivated for their edible fruits. In this study, we used admixture and genetic relatedness analysis of northern highbush (NHB, V. corymbosum) and southern highbush (SHB, V. darrowii) blueberry genotypes and F2 progenies of the V. corymbosum × V. darrowii cross. Using genotyping-by-sequencing (GBS), we generated ~3.34 billion reads (75 bp). The GBS reads were aligned to the Vaccinium corymbosum cv. Draper v1.0 reference genome sequence, and ~2.8 million reads were successfully mapped. From the alignments, we identified 2,244,039 single nucleotide polymorphisms (SNPs), which were used for principal component, haplotype, and admixture analysis. PCA formed three main groups: 1) NHB cultivars, 2) SHB cultivars, and 3) BNJ16-5 progenies. The overall fixation index (FST) and nucleotide diversity for NHB and SHB, indicated wide genetic differentiation, and haplotype analysis revealed that SHB cultivars are more genetically diverse than NHB cultivars. The admixture analysis identified a mix of various lineages of parental genomic introgression. This study demonstrated the effectiveness of GBS-derived SNP markers in genetic and admixture analyses to reveal genetic relatedness and to examine parental lineages in blueberry, which may be useful for future breeding plans.

Genotyping-by-Sequencing to Unlock Genetic Diversity and Population Structure in White Yam (Dioscorea rotundata Poir.)

White yam (Dioscorearotundata Poir.) is one of the most important tuber crops in West Africa, where it is indigenous and represents the largest repository of biodiversity through several years of domestication, production, consumption, and trade. In this study, the genotyping-by-sequencing (GBS) approach was used to sequence 814 genotypes consisting of genebank landraces, breeding lines, and market varieties to understand the level of genetic diversity and pattern of the population structure among them. The genetic diversity among different genotypes was assessed using three complementary clustering methods, the model-based admixture, discriminant analysis of principal components (DAPC), and phylogenetic tree. ADMIXTURE analysis revealed an optimum number of four groups that matched with the number of clusters obtained through phylogenetic tree. Clustering results obtained from ADMIXTURE analysis were further validated using DAPC-based clustering. Analysis of molecular variance (AMOVA) revealed high genetic diversity (96%) within each genetic group. A network analysis was further carried out to depict the genetic relationships among the three genetic groups (breeding lines, genebank landraces, and market varieties) used in the study. This study showed that the use of advanced sequencing techniques such as GBS coupled with statistical analysis is a robust method for assessing genetic diversity and population structure in a complex crop such as white yam.

Admixture analysis of age at onset in older patients with schizophrenia spectrum disorders

ABSTRACTThe nature of schizophrenia spectrum disorders with an onset in middle or late adulthood remains controversial. The aim of our study was to determine in patients aged 60 and older if clinically relevant subtypes based on age at onset can be distinguished, using admixture analysis, a data-driven technique. We conducted a cross-sectional study in 94 patients aged 60 and older with a diagnosis of schizophrenia or schizoaffective disorder. Admixture analysis was used to determine if the distribution of age at onset in this cohort was consistent with one or more populations of origin and to determine cut-offs for age at onset groups, if more than one population could be identified. Results showed that admixture analysis based on age at onset demonstrated only one normally distributed population. Our results suggest that in older schizophrenia patients, early- and late-onset ages form a continuum.

Keep Garfagnina alive. An integrated study on patterns of homozygosity, genomic inbreeding, admixture and breed traceability of the Italian Garfagnina goat breed

The objective of this study was to investigate the genomic background of the Garfagnina (GRF) goat breed that faces the risk of extinction. In total, 48 goats genotyped with the Illumina CaprineSNP50 BeadChip were analyzed together with 214 goats belonging to 9 Italian breeds (~25 goats/breed) from the AdaptMap project [Argentata (ARG), Bionda dell’Adamello (BIO), Ciociara Grigia (CCG), Di Teramo (DIT), Garganica (GAR), Girgentana (GGT), Orobica (ORO), Valdostana (VAL) and Valpassiria (VSS)]. We estimated i) runs of homozygosity (ROH), ii) admixture ancestries and iii) traceability success via discriminant analysis on principal components (DAPC) based on cross-validation. For GRF, an excess of frequent ROH (more than 45% in the GRF samples analyzed) was detected on CHR 12 at, roughly 50.25-50.94Mbp (ARS1 assembly), spanned between the CENPJ (centromere protein) and IL17D (interleukin 17D) genes. The same area was also present in DIT, while the broader region (~49.25-51.94Mbp) was shared among the ARG, CCG, and GGT. Admixture analysis depicted the uniqueness of the GRF breed, with a small part of common ancestry shared with BIO, VSS, ARG and CCG breeds. The DAPC model resulted in a 100% assignment success. We hope this work will contribute to the efforts of preventing the GRF from extinction and to add value to all the socio-agro-economic factors related with the farming of the GRF breed.

ipADMIXTURE: R package for inferring sub-population clusters based on genetic admixture

AbstractipADMIXTURE is an R package to infer clusters and their phylogeny based on Q matrices of genetic admixture analysis. It is the first software of its kind to infer not just only clusters, but also the hierarchy of sub-populations w.r.t. the minimum number of ancestors that split any pair of clusters apart. Since inputs of the package, Q matrices, can be obtained from well-known software (ADMIXTURE, STRUCTURE, etc.) and the Q matrices are mandatory information that are used in genetic population structure study, our package has a potential to help scientists and researchers to find deeper explanation of admixture analysis in their studies. Our package comes with a user-friendly interface to make the software accessible for everyone.