Improved genome assembly of the whiteleg shrimp Penaeus (Litopenaeus) vannamei using long- and short-read sequences from public databases

The Pacific whiteleg shrimp Penaeus (Litopenaeus) vannamei is a highly relevant species for the world's aquaculture development, for which an incomplete genome is available in public databases. In this work, PacBio long-reads from 14 publicly available genomic libraries (131.2 Gb) were mined to improve the reference genome assembly. The libraries were assembled, polished using Illumina short-reads, and scaffolded with P. vannamei, Feneropenaeus chinensis, and Penaeus monodon genomes. The reference-guided assembly, organized into 44 pseudo-chromosomes and 15,682 scaffolds, showed an improvement from previous reference genomes with a genome size of 2.055 Gb, N50 of 40.14 Mb, L50 of 21, and the longest scaffold of 65.79 Mb. Most orthologous genes (92.6%) of the Arthropoda_odb10 database were detected as "complete", and BRAKER predicted 21,816 gene models; from these, we detected 1,814 single-copy orthologues conserved across the genomic references for Marsupenaeus japonicus, F. chinensis, and P. monodon. Transcriptomic-assembly data aligned in more than 99% to the new reference-guided assembly. The collinearity analysis of the assembled pseudo-chromosomes against the P. vannamei and P. monodon reference genomes showed high conservation in different sets of pseudo-chromosomes. In addition, more than 21,000 publicly available genetic marker sequences were mapped to single-site positions. This new assembly represents a step forward to previously reported P. vannamei assemblies. It will be helpful as a reference genome for future studies on the evolutionary history of the species, the genetic architecture of physiological and sex-determination traits, and the analysis of the changes in genetic diversity and composition of cultivated stocks.

A high-density linkage map construction in guava (Psidium guajava L.) using genotyping by sequencing and identification of QTLs for leaf, peel, and pulp color in an intervarietal mapping population

Psidium guajava L. is an important fruit crop in the tropical and subtropical regions of the world. The advanced breeding methods are not employed for important commercial traits like peel and pulp color, seed hardiness, fruit size, etc., due to the scarcity of genome-wide molecular markers and high-density linkage maps. In this study, we employed single-nucleotide polymorphism (SNP) markers and identified quantitative trait loci (QTL) regions that are associated with color traits of leaf, peel, and pulp in the guava intervarietal mapping population. The mapping population was developed from the contrasting genotypes of fruit and leaf color. Variations in color among the segregating hybrids were recorded both visually and using a Color reader. A high-density linkage map of guava was constructed using the SNP markers from genotyping by sequencing (GBS) of 150 hybrid individuals of the cross 'Arka Poorna' (green) x 'Purple Local' (purple). The integrated linkage map consisted of 1426 SNPs mapped on 11 linkage groups (LG), spanning a total distance of around 730 cM with an average of 129.6 markers per LG. Through QTL analysis for color traits, a minor QTL region was identified for visually scored leaf color and peel color on LG1, whereas a major QTL was detected for pulp color in LG4. The Hunter color values (L* and, a*) also had major QTLs with overlapping marker intervals for leaf and peel colors, establishing the association of SNP markers to the trait. The QTLs harbored genes and transcription factors involved in lycopene and anthocyanin pigment biosynthesis. This is the first report of a high-density linkage map based on SNP markers in guava and QTL mapping for color characters in leaf, fruit peel and pulp. The genotyping information generated in this study can aid in genetic engineering and marker-assisted breeding in guava.

Using NGS Technology and Association Mapping to Identify Candidate Genes Associated with Fusarium Stalk Rot Resistance

Stalk rot caused by Fusarium fungi is one of the most widespread and devastating diseases of maize, and the introduction of resistant genotypes is one of the most effective strategies for controlling the disease. Breeding genotypes with genetically determined resistance will also allow less use of crop protection products. The aim of the research was to identify molecular markers and associated candidate genes determining maize plant resistance to Fusarium stalk rot. The plant material for this study consisted of 122 maize hybrids. The experiment was conducted in two localities: Smolice and Kobierzyce. The Fusarium stalk rot values ranged from 1.65% (for genotype G01.10) to 31.18% (for genotype G03.07) in Kobierzyce and from 0.00% (for 58 genotypes) to 6.36% (G05.03) in Smolice. The analyzed genotypes were simultaneously subjected to next-generation sequencing using the Illumina platform. Illumina sequencing identified 60,436 SilicoDArT markers and 32,178 SNP markers (92,614 in total). For association mapping, 32,900 markers (26,234 SilicoDArT and 6666 SNP) meeting the criteria (MAF > 0.25 and the number of missing observations <10%) were used. The results of the observation of the degree of infection and sequencing were used for association mapping, which ultimately resulted in the selection of ten molecular markers important at both places. Among the identified markers, two SNP markers that are located inside candidate genes play an important role. Marker 4772836 is located inside the serine/threonine-protein kinase bsk3 gene, while marker 4765764 is located inside the histidine kinase 1 gene. Both genes can be associated with plant resistance to Fusarium stalk rot, and these genes can also be used in breeding programs to select resistant varieties.

Estimation of the contemporary effective population size from SNP data while accounting for mating structure

A new method is developed to estimate the contemporary effective population size (Ne ) from linkage disequilibrium (LD) between SNPs without information on their location, which is the usual scenario in non-model species. The general theory of linkage disequilibrium is extended to include the contribution of full-sibs to the measure of LD, leading naturally to the estimation of Ne in monogamous and polygamous mating systems, as well as in multiparous species, and with non-random distributions of full-sib family size due to selection or other causes. Prediction of confidence intervals for Ne estimates was solved using a small artificial neural network trained on a dataset of over 105 simulation results. The method, implemented in a user-friendly and fast software (currentNe), is able to estimate Ne even in problematic scenarios with large population sizes or small sample sizes and provides confidence intervals that are more consistent than resampling methods.

Identification and Analysis of Candidate Genes Associated with Yield Structure Traits and Maize Yield Using Next-Generation Sequencing Technology

The main challenge of agriculture in the 21st century is the continuous increase in food production. In addition to ensuring food security, the goal of modern agriculture is the continued development and production of plant-derived biomaterials. Conventional plant breeding methods do not allow breeders to achieve satisfactory results in obtaining new varieties in a short time. Currently, advanced molecular biology tools play a significant role worldwide, markedly contributing to biological progress. The aim of this study was to identify new markers linked to candidate genes determining grain yield. Next-generation sequencing, gene association, and physical mapping were used to identify markers. An additional goal was to also optimize diagnostic procedures to identify molecular markers on reference materials. As a result of the conducted research, 19 SNP markers significantly associated with yield structure traits in maize were identified. Five of these markers (28629, 28625, 28640, 28649, and 29294) are located within genes that can be considered candidate genes associated with yield traits. For two markers (28639 and 29294), different amplification products were obtained on the electrophorograms. For marker 28629, a specific product of 189 bp was observed for genotypes 1, 4, and 10. For marker 29294, a specific product of 189 bp was observed for genotypes 1 and 10. Both markers can be used for the preliminary selection of well-yielding genotypes.

Identification and Analysis of Candidate Genes Associated with Maize Fusarium Cob Resistance Using Next-Generation Sequencing Technology

The pressure to reduce mineral fertilization and the amount of pesticides used has become a factor limiting production growth, as has the elimination of many crop protection chemicals from the market. A key condition for this to be an effective form of protection is the use of varieties with higher levels of resistance. The most effective and fastest way to assist in the selection and control of pathogens is the conducting of genome-wide association studies. These are useful tools for identifying candidate genes, especially when combined with QTL mapping to map and validate loci for quantitative traits. The aim of this study was to identify new markers coupled to genes that determine maize plant resistance to fusarium head blight through the use of next-generation sequencing, association and physical mapping, and to optimize diagnostic procedures to identify selected molecular markers coupled to plant resistance to this fungal disease. As a result of field experiments and molecular analyses, molecular markers coupled to potential genes for resistance to maize ear fusariosis were selected. The newly selected markers were tested against reference genotypes. As a result of the analyses, it was found that two markers (11801 and 20607) out of the ten that were tested differentiated between susceptible and resistant genotypes. Marker number 11801 proved to be the most effective, with a specious product of 237 bp appearing for genotypes 1, 3, 5, 9 and 10. These genotypes were characterized by a field resistance of 4-6 on the 9° scale (1 being susceptible, 9 being resistant) and for all genotypes except 16 and 20, which were characterized by a field resistance of 9. In the next step, this marker will be tested on a wider population of extreme genotypes in order to use it for the preliminary selection of fusarium-resistant genotypes, and the phosphoenolpyruvate carboxylase kinase 1 gene coupled to it will be subjected to expression analysis.

Accurate prediction of quantitative traits with failed SNP calls in canola and maize

In modern plant breeding, genomic selection is becoming the gold standard to select superior genotypes in large breeding populations that are only partially phenotyped. Many breeding programs commonly rely on single-nucleotide polymorphism (SNP) markers to capture genome-wide data for selection candidates. For this purpose, SNP arrays with moderate to high marker density represent a robust and cost-effective tool to generate reproducible, easy-to-handle, high-throughput genotype data from large-scale breeding populations. However, SNP arrays are prone to technical errors that lead to failed allele calls. To overcome this problem, failed calls are often imputed, based on the assumption that failed SNP calls are purely technical. However, this ignores the biological causes for failed calls-for example: deletions-and there is increasing evidence that gene presence-absence and other kinds of genome structural variants can play a role in phenotypic expression. Because deletions are frequently not in linkage disequilibrium with their flanking SNPs, permutation of missing SNP calls can potentially obscure valuable marker-trait associations. In this study, we analyze published datasets for canola and maize using four parametric and two machine learning models and demonstrate that failed allele calls in genomic prediction are highly predictive for important agronomic traits. We present two statistical pipelines, based on population structure and linkage disequilibrium, that enable the filtering of failed SNP calls that are likely caused by biological reasons. For the population and trait examined, prediction accuracy based on these filtered failed allele calls was competitive to standard SNP-based prediction, underlying the potential value of missing data in genomic prediction approaches. The combination of SNPs with all failed allele calls or the filtered allele calls did not outperform predictions with only SNP-based prediction due to redundancy in genomic relationship estimates.

Genetic characterization of root architectural traits in barley (Hordeum vulgare L.) using SNP markers

Increasing attention is paid to providing new tools to breeders for targeted breeding for specific root traits that are beneficial in low-fertility, drying soils; however, such information is not available for barley (Hordeum vulgare L.). A panel of 191 barley accessions (originating from Australia, Europe, and Africa) was phenotyped for 26 root and shoot traits using the semi-hydroponic system and genotyped using 21 062 high-quality single nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing (GBS). The population structure analysis of the barley panel identified six distinct groups. We detected 1199 significant (P<0.001) marker-trait associations (MTAs) with r2 values up to 0.41. The strongest MTAs were found for root diameter in the top 20 cm and the longest root length. Based on the physical locations of these MTAs in the barley reference genome, we identified 37 putative QTLs for the root traits, and three QTLs for shoot traits, with nine QTLs located in the same physical regions. The genomic region 640-653 Mb on chromosome 7H was significant for five root length-related traits, where 440 annotated genes were located. The putative QTLs for various root traits identified in this study may be useful for genetic improvement regarding the adaptation of new barley cultivars to suboptimal environments and abiotic stresses.

A multiplexed plant-animal SNP array for selective breeding and species conservation applications

Reliable and high-throughput genotyping platforms are of immense importance for identifying and dissecting genomic regions controlling important phenotypes, supporting selection processes in breeding programs, and managing wild populations and germplasm collections. Amongst available genotyping tools, single nucleotide polymorphism arrays have been shown to be comparatively easy to use and generate highly accurate genotypic data. Single-species arrays are the most commonly used type so far; however, some multi-species arrays have been developed for closely related species that share single nucleotide polymorphism markers, exploiting inter-species cross-amplification. In this study, the suitability of a multiplexed plant-animal single nucleotide polymorphism array, including both closely and distantly related species, was explored. The performance of the single nucleotide polymorphism array across species for diverse applications, ranging from intra-species diversity assessments to parentage analysis, was assessed. Moreover, the value of genotyping pooled DNA of distantly related species on the single nucleotide polymorphism array as a technique to further reduce costs was evaluated. Single nucleotide polymorphism performance was generally high, and species-specific single nucleotide polymorphisms proved suitable for diverse applications. The multi-species single nucleotide polymorphism array approach reported here could be transferred to other species to achieve cost savings resulting from the increased throughput when several projects use the same array, and the pooling technique adds another highly promising advancement to additionally decrease genotyping costs by half.

Association Mapping of Candidate Genes Associated with Iron and Zinc Content in Rice (Oryza sativa L.) Grains

Micronutrient deficiencies, particularly of iron (Fe) and zinc (Zn), in the diet contribute to health issues and hidden hunger. Enhancing the Fe and Zn content in globally staple food crops like rice is necessary to address food malnutrition. A Genome-Wide Association Study (GWAS) was conducted using 85 diverse rice accessions from the Democratic Republic of Congo (DRC) to identify genomic regions associated with grain Fe and Zn content. The Fe content ranged from 0.95 to 8.68 mg/100 g on a dry weight basis (dwb) while Zn content ranged from 0.87 to 3.8 mg/100 g (dwb). Using MLM and FarmCPU models, we found 10 significant SNPs out of which one SNP on chromosome 11 was associated with the variation in Fe content and one SNP on chromosome 4 was associated with the Zn content, and both were commonly detected by the two models. Candidate genes belonging to transcription regulator activities, including the bZIP family genes and MYB family genes, as well as transporter activities involved in Fe and Zn homeostasis were identified in the vicinity of the SNP markers and selected. The identified SNP markers hold promise for marker-assisted selection in rice breeding programs aimed at enhancing Fe and Zn content in rice. This study provides valuable insights into the genetic factors controlling Fe and Zn uptake and their transport and accumulation in rice, offering opportunities for developing biofortified rice varieties to combat malnutrition among rice consumers.

Analysis of genetic diversity and genome-wide association study for drought tolerance related traits in Iranian bread wheat

BACKGROUND

Drought is most likely the most significant abiotic stress affecting wheat yield. The discovery of drought-tolerant genotypes is a promising strategy for dealing with the world's rapidly diminishing water resources and growing population. A genome-wide association study (GWAS) was conducted on 298 Iranian bread wheat landraces and cultivars to investigate the genetic basis of yield, yield components, and drought tolerance indices in two cropping seasons (2018-2019 and 2019-2020) under rainfed and well-watered environments.

RESULTS

A heatmap display of hierarchical clustering divided cultivars and landraces into four categories, with high-yielding and drought-tolerant genotypes clustering in the same group. The results of the principal component analysis (PCA) demonstrated that selecting genotypes based on the mean productivity (MP), geometric mean productivity (GMP), harmonic mean (HM), and stress tolerance index (STI) can help achieve high-yield genotypes in the environment. Genome B had the highest number of significant marker pairs in linkage disequilibrium (LD) for both landraces (427,017) and cultivars (370,359). Similar to cultivars, marker pairs on chromosome 4A represented the strongest LD (r2 = 0.32). However, the genomes D, A, and B have the highest LD, respectively. The single-locus mixed linear model (MLM) and multi-locus random-SNP-effect mixed linear model (mrMLM) identified 1711 and 1254 significant marker-trait association (MTAs) (-log10 P > 3) for all traits, respectively. A total of 874 common quantitative trait nucleotides (QTNs) were simultaneously discovered by both MLM and mrMLM methods. Gene ontology revealed that 11, 18, 6, and 11 MTAs were found in protein-coding regions (PCRs) for spike weight (SW), thousand kernel weight (TKW), grain number per spike (GN), and grain yield (GY), respectively.

CONCLUSION

The results identified rich regions of quantitative trait loci (QTL) on Ch. 4A and 5A suggest that these chromosomes are important for drought tolerance and could be used in wheat breeding programs. Furthermore, the findings indicated that landraces studied in Iranian bread wheat germplasm possess valuable alleles, that are responsive to water-limited conditions. This GWAS experiment is one of the few types of research conducted on drought tolerance that can be exploited in the genome-mediated development of novel varieties of wheat.

Haplotype blocks for genomic prediction: a comparative evaluation in multiple crop datasets

In modern plant breeding, genomic selection is becoming the gold standard for selection of superior genotypes. The basis for genomic prediction models is a set of phenotyped lines along with their genotypic profile. With high marker density and linkage disequilibrium (LD) between markers, genotype data in breeding populations tends to exhibit considerable redundancy. Therefore, interest is growing in the use of haplotype blocks to overcome redundancy by summarizing co-inherited features. Moreover, haplotype blocks can help to capture local epistasis caused by interacting loci. Here, we compared genomic prediction methods that either used single SNPs or haplotype blocks with regards to their prediction accuracy for important traits in crop datasets. We used four published datasets from canola, maize, wheat and soybean. Different approaches to construct haplotype blocks were compared, including blocks based on LD, physical distance, number of adjacent markers and the algorithms implemented in the software "Haploview" and "HaploBlocker". The tested prediction methods included Genomic Best Linear Unbiased Prediction (GBLUP), Extended GBLUP to account for additive by additive epistasis (EGBLUP), Bayesian LASSO and Reproducing Kernel Hilbert Space (RKHS) regression. We found improved prediction accuracy in some traits when using haplotype blocks compared to SNP-based predictions, however the magnitude of improvement was very trait- and model-specific. Especially in settings with low marker density, haplotype blocks can improve genomic prediction accuracy. In most cases, physically large haplotype blocks yielded a strong decrease in prediction accuracy. Especially when prediction accuracy varies greatly across different prediction models, prediction based on haplotype blocks can improve prediction accuracy of underperforming models. However, there is no "best" method to build haplotype blocks, since prediction accuracy varied considerably across methods and traits. Hence, criteria used to define haplotype blocks should not be viewed as fixed biological parameters, but rather as hyperparameters that need to be adjusted for every dataset.

A genome-wide comparison between selected and unselected Valle del Belice sheep reveals differences in population structure and footprints of recent selection

About three decades of breeding and selection in the Valle del Belìce sheep are expected to have left several genomic footprints related to milk production traits. In this study, we have assembled a dataset with 451 individuals of the Valle del Belìce sheep breed: 184 animals that underwent directional selection for milk production and 267 unselected animals, genotyped for 40,660 single-nucleotide polymorphisms (SNPs). Three different statistical approaches, both within (iHS and ROH) and between (Rsb) groups, were used to identify genomic regions potentially under selection. Population structure analyses separated all individuals according to their belonging to the two groups. A total of four genomic regions on two chromosomes were jointly identified by at least two statistical approaches. Several candidate genes for milk production were identified, corroborating the polygenic nature of this trait and which may provide clues to potential new selection targets. We also found candidate genes for growth and reproductive traits. Overall, the identified genes may explain the effect of selection to improve the performances related to milk production traits in the breed. Further studies using high-density array data, would be particularly relevant to refine and validate these results.

High-density DArTSeq SNP markers revealed wide genetic diversity and structured population in common bean (Phaseolus vulgaris L.) germplasm in Ethiopia

INTRODUCTION

Common bean is one of the widely consumed food security crop in Africa, Asia, and South America. Understanding genetic diversity and population structure is crucial for designing breeding strategies.

MATERIALS

Two hundred and eighty-nine germplasm were recently collected from different regions of Ethiopia and introduced from CIAT to estimate genetic diversity and population structure using 11,480 DArTSeq SNP markers.

RESULTS

The overall mean genetic diversity and polymorphic information content (PIC) were 0.38 and 0.30, respectively, suggested the presence of adequate genetic diversity among the genotypes. Among the geographical regions, landraces collected from Oromia showed the highest diversity (0.39) and PIC (0.30). The highest genetic distance was observed between genotypes collected from SNNPR and CIAT (0.49). In addition, genotypes from CIAT were genetically more related to improved varieties than the landraces which could be due to sharing of parents in the improvement process. The analysis of molecular variance revealed that the largest proportion of variation was due to within the population both in geographical region (63.67%) and breeding status (61.3%) based classification. Model-based structure analysis delineated the 289 common bean genotypes into six hypothetical ancestoral populations.

CONCLUSIONS

The genotypes were not clustered based on geographical regions and they were not the main drivers for the differentiation. This indicated that selection of the parental lines should be based on systematic assessment of the diversity rather than geographical distance. This article provides new insights into the genetic diversity and population structure of common bean for association studies, designing effective collection and conservation for efficient utilization for the improvement of the crop.

High resolution mapping of QTLs for fruit color and firmness in Amrapali/Sensation mango hybrids

Introduction

Mango (Mangifera indica L.), acclaimed as the 'king of fruits' in the tropical world, has historical, religious, and economic values. It is grown commercially in more than 100 countries, and fresh mango world trade accounts for ~3,200 million US dollars for the year 2020. Mango is widely cultivated in sub-tropical and tropical regions of the world, with India, China, and Thailand being the top three producers. Mango fruit is adored for its taste, color, flavor, and aroma. Fruit color and firmness are important fruit quality traits for consumer acceptance, but their genetics is poorly understood.

Methods

For mapping of fruit color and firmness, mango varieties Amrapali and Sensation, having contrasting fruit quality traits, were crossed for the development of a mapping population. Ninety-two bi-parental progenies obtained from this cross were used for the construction of a high-density linkage map and identification of QTLs. Genotyping was carried out using an 80K SNP chip array.

Results and discussion

Initially, we constructed two high-density linkage maps based on the segregation of female and male parents. A female map with 3,213 SNPs and male map with 1,781 SNPs were distributed on 20 linkages groups covering map lengths of 2,844.39 and 2,684.22cM, respectively. Finally, the integrated map was constructed comprised of 4,361 SNP markers distributed on 20 linkage groups, which consisted of the chromosome haploid number in Mangifera indica (n =20). The integrated genetic map covered the entire genome of Mangifera indica cv. Dashehari, with a total genetic distance of 2,982.75 cM and an average distance between markers of 0.68 cM. The length of LGs varied from 85.78 to 218.28 cM, with a mean size of 149.14 cM. Phenotyping for fruit color and firmness traits was done for two consecutive seasons. We identified important consistent QTLs for 12 out of 20 traits, with integrated genetic linkages having significant LOD scores in at least one season. Important consistent QTLs for fruit peel color are located at Chr 3 and 18, and firmness on Chr 11 and 20. The QTLs mapped in this study would be useful in the marker-assisted breeding of mango for improved efficiency.

Transcriptome, Ectopic Expression and Genetic Population Analysis Identify Candidate Genes for Fiber Quality Improvement in Cotton

Comparative transcriptome analysis of fiber tissues between Gossypium barbadense and Gossypium hirsutum could reveal the molecular mechanisms underlying high-quality fiber formation and identify candidate genes for fiber quality improvement. In this study, 759 genes were found to be strongly upregulated at the elongation stage in G. barbadense, which showed four distinct expression patterns (I-IV). Among them, the 346 genes of group IV stood out in terms of the potential to promote fiber elongation, in which we finally identified 42 elongation-related candidate genes by comparative transcriptome analysis between G. barbadense and G. hirsutum. Subsequently, we overexpressed GbAAR3 and GbTWS1, two of the 42 candidate genes, in Arabidopsis plants and validated their roles in promoting cell elongation. At the secondary cell wall (SCW) biosynthesis stage, 2275 genes were upregulated and exhibited five different expression profiles (I-V) in G. barbadense. We highlighted the critical roles of the 647 genes of group IV in SCW biosynthesis and further picked out 48 SCW biosynthesis-related candidate genes by comparative transcriptome analysis. SNP molecular markers were then successfully developed to distinguish the SCW biosynthesis-related candidate genes from their G. hirsutum orthologs, and the genotyping and phenotyping of a BC₃F₅ population proved their potential in improving fiber strength and micronaire. Our results contribute to the better understanding of the fiber quality differences between G. barbadense and G. hirsutum and provide novel alternative genes for fiber quality improvement.

Development of SNP markers linked to purple blotch resistance for marker-assisted selection in onion (Allium cepa L.) breeding

Purple blotch (PB), caused by Alternaria porri (Ellis) Cifferi, is one of the most destructive diseases of onion worldwide. Rapid development and deployment of resistant onion varieties is the most effective approach to control this disease. A single dominant gene, ApR1 was previously linked to PB resistance in onion cultivar 'Arka Kalyan'. In this study, an advanced RIL population derived from a cross between the resistant (Arka Kalyan) and susceptible (Agrifound Rose) cultivar of onion was used to fine map the resistant locus with SNP markers. Twenty plants from the RIL population, ten each with disease resistance and susceptibility trait, were subjected to restriction site-associated DNA sequencing (RAD-Seq) and generated 7388 single nucleotide polymorphisms (SNPs). Correlation analysis between marker genotypes and PB disease phenotype on the 20 plants identified 27 SNPs as candidate markers linked to ApR1 gene for PB resistance. Six candidate SNPs were converted to Kompetitive Allele-Specific PCR (KASP) markers designated as ApRsnip5, ApRsnip8, ApRsnip14, ApRsnip21, ApRsnip23 and ApRsnip25. Marker-trait association based on disease phenotyping and KASP genotyping data on 153 RILs confirmed that all six KASP markers were tightly associated with ApR1 gene within the genetic distance of 1.3 CentiMorgan (cM). ApRsnip14 co-segregated with the ApR1 locus. Further, the six KASP markers were tested on 27 onion lines with different genetic backgrounds. ApRsnip14, ApRsnip21, ApRsnip5 and ApRsnip23 not only showed the correct resistance allele in 3 resistance genotypes, but also clustered together in the remaining 24 susceptible lines. Alternatively, ApRsnip8 and ApRsnip25 exhibited false positives in two onion lines which do not have the R-gene. Overall, our results suggest that ApRsnip14 and ApRsnip23 with their close linkage to ApR1 locus and greater applicability on breeding germplasm are recommended in marker-assisted selection for PB resistance in onion breeding program.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03562-7.

Next-Generation Sequencing (NGS) Identified Species-Specific SSR and SNP Markers, Allow the Unequivocal Identification of Strawberry Tree (Arbutus unedo L.) Germplasm Accessions and Contribute to Assess Their Genetic Relationships

The strawberry tree (Arbutus unedo L.), an evergreen bush to small tree of the Ericaceae family, is a main component of the natural flora of the Mediterranean basin that also grows profusely through the Iberian Peninsula, southwestern France, and Ireland. The small edible red fruits are usually used to produce preserves, jams, and liquors, as the Portuguese "aguardente de medronho". The leaves and fruits have been used for a long time in traditional medicine, and their bioactive compounds are presently the subject of intense research. A strawberry tree germplasm collection was recently established by the company Corte Velada (Odiáxere, Portugal). A set of 50 germplasm accessions was selected for a breeding program. A next-generation sequencing project was performed, resulting in the establishment of the first strawberry tree genome assembly and further identification of 500 SSR and 500 SNP loci. Individual molecular fingerprints for the unequivocal identification of the selected 50 accessions were established based on 71 markers alleles amplified by 4 SSR and 9 SNP markers. The same species-specific markers alleles combined with 61 random amplified markers amplified by 5 RAPD and 5 ISSR primers were used to assess the genetic variability and genetic relationships among the selected accessions.

Genetic diversity assessment and genome-wide association study reveal candidate genes associated with component traits in sweet potato (Ipomoea batatas (L.) Lam)

The Korean sweet potatoes were bred by various cultivars introduced from Japanese, American, Porto Rico, China, and Burundi. This issue enriched their genetic diversity but also resulted in a mixture of cultivars. For genotyping, we collected and sequenced 66 sweet potato germplasms from different localities around Korea, including 36 modern cultivars, 5 local cultivars, and 25 foreign cultivars. This identified 447.6 million trimmed reads and 324.8 million mapping reads and provided 39,424 single nucleotide polymorphisms (SNPs) markers. Phylogenetic clustering and population structure analysis distinctly classified these germplasms into 5 genetic groups, group 1, group 2, group 3, group 4, and group 5, containing 20, 15, 10, 7, and 14 accessions, respectively. Sixty-three significant SNPs were selected by genome-wide association for sugar composition-related traits (fructose, glucose, and total sugars), total starch, amylose content, and total carotenoid of the storage root. A total of 37 candidate genes encompassing these significant SNPs were identified, among which, 7 genes were annotated to involve in sugar and starch metabolism, including galactose metabolism (itf04g30630), starch and sucrose metabolism (itf03g13270, itf15g09320), carbohydrate metabolism (itf14g10250), carbohydrate and amino acid metabolism (itf12g19270), and amino sugar and nucleotide sugar metabolism (itf03g21950, itf15g04880). This results indicated that sugar and starch are important characteristics to determine the genetic diversity of sweet potatoes. These findings not only illustrate the importance of component traits to genotyping sweet potatoes but also explain an important reason resulting in genetic diversity of sweet potato.

Genetic mapping of leaf rust (Puccinia triticina Eriks) resistance genes in six Canadian spring wheat cultivars

The Canada Western Red Spring wheat (Triticum aestivum L.) cultivars AAC Concord, AAC Prevail, CDC Hughes, Lillian, Glenlea, and elite line BW961 express a spectrum of resistance to leaf rust caused by Puccinia triticina Eriks. This study aimed to identify and map the leaf rust resistance of the cultivars using three doubled haploid populations, AAC Prevail/BW961 (PB), CDC Hughes/AAC Concord (HC), and Lillian/Glenlea (LG). The populations were evaluated for seedling resistance in the greenhouse and adult plant disease response in the field at Morden, MB for 3 years and genotyped with the 90K wheat Infinium iSelect SNP array. Genetic maps were constructed to perform QTL analysis on the seedling and field leaf rust data. A total of three field leaf rust resistance QTL segregated in the PB population, five in the HC, and six in the LG population. In the PB population, BW961 contributed two QTL on chromosomes 2DS and 7DS, and AAC Prevail contributed a QTL on 4AL consistent across trials. Of the five QTL in HC, AAC Concord contributed two QTL on 4AL and 7AL consistent across trials and a QTL on 3DL.1 that provided seedling resistance only. CDC Hughes contributed two QTL on 1DS and 3DL.2. Lillian contributed four QTL significant in at least two of the three trials on 2BS, 4AL, 5AL, and 7AL, and Glenlea two QTL on 4BL and 7BL. The 1DS QTL from CDC Hughes, the 2DS from BW961, the 4AL from the AAC Prevail, AAC Concord, and Lillian, and the 7AL from AAC Concord and Lillian conferred seedling leaf rust resistance. The QTL on 4AL corresponded with Lr30 and was the same across cultivars AAC Prevail, AAC Concord, and Lillian, whereas the 7AL corresponding with LrCen was coincident between AAC Concord and Lillian. The 7DS and 2DS QTL in BW961 corresponded with Lr34 and Lr2a, respectively, and the 1DS QTL in CDC Hughes with Lr21. The QTL identified on 5AL could represent a novel gene. The results of this study will widen our knowledge of leaf rust resistance genes in Canadian wheat and their utilization in resistance breeding.

Construction of SNP fingerprint and population genetic analysis of honeysuckle germplasm resources in China

INTRODUCTION

The flower buds of Lonicera japonica Thunb. are widely used in Chinese medicine for their anti-inflammatory properties, and they have played an important role in the fight against SARS COVID-19 and other major epidemics. However, due to the lack of scientific and accurate variety identification methods and national unified standards, scattered and non-standardized management in flower bud production has led to mixed varieties that have caused significant difficulties in the cataloging and preservation of germplasm resources and the identification, promotion, and application of new L. japonica varieties.

METHODS

In this study, we evaluated the population structure, genetic relationships, and genetic fingerprints of 39 germplasm resources of Lonicera in China using simplified genome sequencing technology.

RESULTS

A total of 13,143,268 single nucleotide polymorphisms (SNPs) were identified. Thirty-nine samples of Lonicera were divided into four subgroups, and the population structure and genetic relationships among existing Lonicera germplasm resources were determined using principal component analysis, population structure analysis, and phylogenetic tree analysis. Through several stringent selection criteria, 15 additional streamlined, high-quality DNA fingerprints were filtered out of the validated 50 SNP loci and verified as being able to effectively identify the 39 Lonicera varieties.

DISCUSSION

To our knowledge, this is the first comprehensive study measuring the diversity and population structure of a large collection of Lonicera varieties in China. These results have greatly broadened our understanding of the diversity, phylogeny, and population structure of Lonicera. The results may enhance the future analysis of genetic diversity, species identification, property rights disputes, and molecular breeding by providing a scientific basis and reference data for these efforts.

Genome-wide association studies of Striga resistance in extra-early maturing quality protein maize inbred lines

Identification of genes associated with Striga resistance is invaluable for accelerating genetic gains in breeding for Striga resistance in maize. We conducted a genome-wide association study to identify genomic regions associated with grain yield and other agronomic traits under artificial Striga field infestation. One hundred and forty-one extra-early quality protein maize inbred lines were phenotyped for key agronomic traits. The inbred lines were also genotyped using 49,185 DArTseq markers from which 8,143 were retained for population structure analysis and genome wide-association study. Cluster analysis and population structure revealed the presence of 3 well-defined genetic groups. Using the mixed linear model, 22 SNP markers were identified to be significantly associated with grain yield, Striga damage at 10 weeks after planting, number of emerged Striga plants at 8 and 10 weeks after planting and ear aspect. The identified SNP markers would be useful for breeders for marker-assisted selection to accelerate the genetic enhancement of maize for Striga resistance in sub-Saharan Africa after validation.

Genetic diversity and population structure assessment of Western Canadian barley cooperative trials

Studying the population structure and genetic diversity of historical datasets is a proposed use for association analysis. This is particularly important when the dataset contains traits that are time-consuming or costly to measure. A set of 96 elite barley genotypes, developed from eight breeding programs of the Western Canadian Cooperative Trials were used in the current study. Genetic diversity, allelic variation, and linkage disequilibrium (LD) were investigated using 5063 high-quality SNP markers via the Illumina 9K Barley Infinium iSelect SNP assay. The distribution of SNPs markers across the barley genome ranged from 449 markers on chromosome 1H to 1111 markers on chromosome 5H. The average polymorphism information content (PIC) per locus was 0.275 and ranged from 0.094 to 0.375. Bayesian clustering in STRUCTURE and principal coordinate analysis revealed that the populations are differentiated primarily due to the different breeding program origins and ear-row type into five subpopulations. Analysis of molecular variance based on PhiPT values suggested that high values of genetic diversity were observed within populations and accounted for 90% of the total variance. Subpopulation 5 exhibited the most diversity with the highest values of the diversity indices, which represent the breeding program gene pool of AFC, AAFRD, AU, and BARI. With increasing genetic distance, the LD values, expressed as r², declined to below the critical r^{2 =} 0.18 after 3.91 cM, and the same pattern was observed on each chromosome. Our results identified an important pattern of genetic diversity among the Canadian barley panel that was proposed to be representative of target breeding programs and may have important implications for association mapping in the future. This highlight, that efforts to identify novel variability underlying this diversity may present practical breeding opportunities to develop new barley genotypes.

Genetic Variation Among Tropical Maize Inbred Lines from NARS and CGIAR Breeding Programs

The use of molecular markers allows for precise estimates of genetic diversity, which is an important parameter that enables breeders to select parental lines and designing breeding systems. We assessed the level of genetic diversity and population structure in a panel of 151 tropical maize inbred lines using 10,940 SNP (single nucleotide polymorphism) markers generated through the DArTseq genotyping platform. The average gene diversity was 0.39 with expected heterozygosity ranging from 0.00 to 0.84, and a mean of 0.02. Analysis of molecular variance showed that 97% of allelic diversity was attributed to individual inbred lines within the populations while only 3% was distributed among the populations. Both neighbor-joining clustering and STRUCTURE analysis classified the inbred lines into four major groups. The crosses that involve inbred lines from most divergent subgroups are expected to generate maximum heterosis and produce wide variation. The results will be beneficial for breeders to better understand and exploit the genetic diversity available in the set of maize inbred lines we studied.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11105-022-01358-2.

Sweet Cherry Diversity and Relationships in Modern and Local Varieties Based on SNP Markers

The sweet cherry is an important fruit species that is widespread globally. In addition to the well-known traditional and modern varieties, a myriad of landraces is present in Europe, as well as in southern Italy. This study aims to evaluate the population structure, genetic relationships, and cases of duplicate samples in a collection of 143 accessions using GBS-derived SNP markers. The genetic material under investigation includes modern commercial varieties, ancient European and American varieties, landraces, and individuals retrieved from small orchards. Some of the known varieties were genetically analyzed here for the first time. In addition, several genotypes were collected from the Basilicata region (southern Italy), an area largely unexplored for sweet cherry genetic resources. The relationships among genotypes were assessed using four different methods: allele frequency and ancestry estimation, principal component analysis, Neighbor-Joining tree, and identity-by-state estimation. The analyses returned quite congruent results and highlighted the presence of four main genetic groups, namely: (i) American varieties, (ii) the 'Germersdorfer-Ferrovia' cluster, (iii) the 'Burlat' group, and (iv) the group of Italian landraces. The main drivers of clustering were ancestry, geographical distribution, and some important traits such as self-compatibility. The sweet cherries from Basilicata, herewith examined for the first time, were mostly distributed within the group of Italian landraces, being particularly linked to the autochthonous varieties of the Campania region. However, some genotypes were outside this group, thus suggesting the introduction of genetic material from other Italian regions or from European countries. The considerable amount of American and European modern varieties analyzed are genetically very closely related, suggesting a reduced genetic basis. In addition, we highlighted the discriminating ability of SNP markers to distinguish between an original variety and its mutant. Overall, our results may be useful in defining conservation strategies for sweet cherry germplasm and developing future breeding programs to enlarge the genetic basis of commercial varieties.

High-density linkage map construction in an autotetraploid blueberry population and detection of quantitative trait loci for anthocyanin content

Highbush blueberry (Vaccinium corymbosum, 2n = 4x = 48) is the most cultivated type of blueberry, both in New Zealand and overseas. Its perceived nutritional value is conferred by phytonutrients, particularly anthocyanins. Identifying the genetic mechanisms that control the biosynthesis of these metabolites would enable faster development of cultivars with improved fruit qualities. Here, we used recently released tools for genetic mapping in autotetraploids to build a high-density linkage map in highbush blueberry and to detect quantitative trait loci (QTLs) for fruit anthocyanin content. Genotyping was performed by target sequencing, with ∼18,000 single nucleotide polymorphism (SNP) markers being mapped into 12 phased linkage groups (LGs). Fruits were harvested when ripe for two seasons and analyzed with high-performance liquid chromatography-mass spectrometry (HPLC-MS): 25 different anthocyanin compounds were identified and quantified. Two major QTLs that were stable across years were discovered, one on LG2 and one on LG4, and the underlying candidate genes were identified. Interestingly, the presence of anthocyanins containing acylated sugars appeared to be under strong genetic control. Information gained in this study will enable the design of molecular markers for marker-assisted selection and will help build a better understanding of the genetic control of anthocyanin biosynthesis in this crop.

Mansonia spp. population genetics based on mitochondrion whole-genome sequencing alongside the Madeira River near Porto Velho, Rondonia, Brazil

In high abundance, females of the genus Mansonia (Blanchard) can be a nuisance to humans and animals because they are voraciously hematophagous and feed on the blood of a myriad of vertebrates. The spatial-temporal distribution pattern of Mansonia species is associated with the presence of their host plants, usually Eichhornia crassipes, E. azurea, Ceratopteris pteridoides, Limnobium laevigatum, Pistia stratiotes, and Salvinia sp. Despite their importance, there is a lack of investigation on the dispersion and population genetics of Mansonia species. Such studies are pivotal to evaluating the genetic structuring, which ultimately reflects populational expansion-retraction patterns and dispersal dynamics of the mosquito, particularly in areas with a history of recent introduction and establishment. The knowledge obtained could lead to better understanding of how anthropogenic changes to the environment can modulate the population structure of Mansonia species, which in turn impacts mosquito population density, disturbance to humans and domestic animals, and putative vector-borne disease transmission patterns. In this study, we present an Illumina NGS sequencing protocol to obtain whole-mitogenome sequences of Mansonia spp. to assess the microgeographic genetic diversity and dispersion of field-collected adults. The specimens were collected in rural environments in the vicinities of the Santo Antônio Energia (SAE) hydroelectric reservoir on the Madeira River.

DNA fingerprinting reveals varietal composition of Vietnamese cassava germplasm (Manihot esculenta Crantz) from farmers' field and genebank collections

A molecular analysis using informative SNP markers in 1570 clones of cassava from Vietnam reveals varietal composition from farmers' field and genebank collections Cassava is the most important smallholder cash crops in Southeast Asia and is especially used in industrial products. Yet, systematic genetic studies on molecular markers from Vietnamese germplasm have not been considered for breeding and conservation programs. We conducted a molecular analysis of 1570 clones of cassava germplasm from farms across six agro-ecological zones using informative SNP markers. We unraveled the genetic diversity and population structure and provided insights into the value of breeding and conservation programs. Duplicated genotypes comprised 98% of the total sample of the Central Highlands region. Ninety-six SNPs were amplified Central Highlands and South East provinces had the highest allelic richness, covering up to 83% of alleles. The average observed heterozygosity (Ho = 0.43) was slightly higher than expected (He = 0.40) across SNP markers, suggesting an excess of heterozygotes plants. Diversity indexes indicated that cassava populations from North West and Eastern Vietnam are genetically diverse (mean He = 0.40). Genetic parentage tests identified 85 unique genetic groups within the varieties KM94, KM419, BRA1305, KM101, KM140, PER262, KM60, KM57 and two unidentified varieties, which accounted for 82% of the frequency distribution. KM94 is the most dominant variety in Vietnamese farms surveyed (38%), reflecting its superior quality and productivity. Discriminant analysis of principal components (DAPC) revealed four main subgroups, which were partially corroborated by neighbor joining (NJ) analyses. After removing duplicates, 31 unique genotypes were distributed across five of the agro-ecological zones. These were well distributed in the subgroups revealed via DAPC and NJ analyses. The genetic groups identified herein could be used to select unique accessions that should ideally conform with ex situ germplasm collections and identify areas where on-farm conservation programs should be targeted. Newly identified genotypes may also contribute as genetic breeding resources that could be used to adapt cassava to future changes and farmers' needs.

Genomic regions associated with chocolate spot (Botrytis fabae Sard.) resistance in faba bean (Vicia faba L.)

Chocolate spot (CS), caused by Botrytis fabae Sard., is an important threat to global faba bean production. Growing resistant faba bean cultivars is, therefore, paramount to preventing yield loss. To date, there have been no reported quantitative trait loci (QTL) associated with CS resistance in faba bean. The objective of this study was to identify genomic regions associated with CS resistance using a recombinant inbred line (RIL) population derived from resistant accession ILB 938. A total of 165 RILs from the cross Mélodie/2 × ILB 938/2 were genotyped and evaluated for CS reactions under replicated controlled climate conditions. The RIL population showed significant variation in response to CS resistance. QTL analysis identified five loci contributing to CS resistance on faba bean chromosomes 1 and 6, accounting for 28.4% and 12.5%, respectively, of the total phenotypic variance. The results of this study not only provide insight into disease-resistance QTL, but also can be used as potential targets for marker-assisted breeding in faba bean genetic improvement for CS resistance.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01307-7.

Maize dispersal patterns associated with different types of endosperm and migration of indigenous groups in lowland South America

BACKGROUND AND AIMS

The lowlands of South America appear to be remarkably important in the evolutionary history of maize, due to new evidence that suggests that maize dispersed from Mexico and arrived in this region in a state of partial domestication. This study aimed to identify dispersal patterns of maize genetic diversity in this part of the continent.

METHODS

A total of 170 maize accessions were characterized with 4398 single nucleotide polymorphisms (SNPs) and analysed to determine if maize dispersal was associated with types of endosperm and indigenous language families.

KEY RESULTS

Four genetic groups were identified in the discriminant analysis of principal components and five groups in the cluster analysis (neighbour-joining method). The groups were structured according to the predominance of endosperm types (popcorn, floury, flint/semi-flint). Spatial principal component analysis of genetic variation suggests different dispersal patterns for each endosperm type and can be associated with hypotheses of expansions of different indigenous groups.

CONCLUSIONS

From a possible origin in Southwestern Amazonia, different maize dispersal routes emerged: (1) towards Northern Amazonia, which continued towards the Caatinga and south-eastern Atlantic Forest (Floury); (2) towards Southern Brazil, passing through the Cerrado and Southern Atlantic Forest reaching the Pampa region (Floury); and (3) along the Atlantic Coast, following Tupi movements originating from two separate expansions: one (Tupinamba) from north to south, and the other (Guarani) in the opposite direction, from south to north (flint, floury and popcorn).

RAD-seq as an effective strategy for heterogenous variety identification in plants-a case study in Italian Ryegrass (Lolium multiflorum)

The primary approach for variety distinction in Italian ryegrass is currently the DUS (distinctness, uniformity and stability) test based on phenotypic traits. Considering the diverse genetic background within the population and the complexity of the environment, however, it is challenging to accurately distinguish varieties based on DUS criteria alone. In this study, we proposed the application of high-throughput RAD-seq to distinguish 11 Italian ryegrass varieties with three bulks of 50 individuals per variety. Our findings revealed significant differences among the 11 tested varieties. The PCA, DAPC and STRUCTURE analysis indicated a heterogeneous genetic background for all of them, and the AMOVA analysis also showed large genetic variance among these varieties (Φ_ST = 0.373), which were clearly distinguished based on phylogenetic analysis. Further nucleotide diversity (Pi) analysis showed that the variety 'Changjiang No.2' had the best intra-variety consistency among 11 tested varieties. Our findings suggest that the RAD-seq could be an effectively alternative method for the variety distinction of Italian ryegrass, as well as a potential tool for open-pollinated varieties (OPVs) of other allogamous species.

tritici, the Wheat Stripe Rust Pathogen

Stripe rust caused by Puccinia striiformis f. sp. tritici (Pst) is a destructive disease that occurs throughout the major wheat-growing regions of the world. This pathogen is highly variable due to the capacity of virulent races to undergo rapid changes in order to circumvent resistance in wheat cultivars and genotypes and to adapt to different environments. Intensive efforts have been made to study the genetics of wheat resistance to this disease; however, no known avirulence genes have been molecularly identified in Pst so far. To identify molecular markers for avirulence genes, a Pst panel of 157 selected isolates representing 126 races with diverse virulence spectra was genotyped using 209 secreted protein gene-based single nucleotide polymorphism (SP-SNP) markers via association analysis. Nineteen SP-SNP markers were identified for significant associations with 12 avirulence genes: AvYr1, AvYr6, AvYr7, AvYr9, AvYr10, AvYr24, AvYr27, AvYr32, AvYr43, AvYr44, AvYrSP, and AvYr76. Some SP-SNPs were associated with two or more avirulence genes. These results further confirmed that association analysis in combination with SP-SNP markers is a powerful tool for identifying markers for avirulence genes. This study provides genomic resources for further studies on the cloning of avirulence genes, understanding the mechanisms of host–pathogen interactions, and developing functional markers for tagging specific virulence genes and race groups.

GWAS Reveal Novel Sex-Related Markers and Candidate Genes in Sea Urchin Mesocentrotus nudus

Mesocentrotus nudus is an economically important mariculture species. Identification of sex-related markers and candidate genes has potential implications for sex-control breeding of Mesocentrotus nudus. The aim of this study was to identify the molecular markers and genes associated with the sex of M. nudus. Initial GWAS analysis based on 80 individuals genotyped by using GBS identified 22 sex-related SNPs located on 9 GBS tags. Further targeted sequencing in another population of 124 individuals confirmed that 7 SNPs located on 7 GBS tags displayed complete associations with sex, suggesting a ZW/ZZ sex-determination system in M. nudus. Besides, genome and transcriptome annotations presented that the heat shock protein 75 kDa, mitochondrial (trap1), and protein furry homolog-like (fryl) may be important candidate genes involved in sex determination and differentiation in M. nudus. However, further studies are needed to elucidate the functions of these genes. Overall, the current results not only provide molecular markers that may contribute to the sex-control breeding for M. nudus, but also provide new insights to understand the regulatory mechanism of sea urchin sex.

Phenotypic Diversity and Association Mapping of Ascorbic Acid Content in Spinach

Ascorbic acid (AsA), or vitamin C, is an essential nutrient for humans. In plants, AsA functions as an antioxidant during normal metabolism or in response to stress. Spinach is a highly nutritious green leafy vegetable that is consumed fresh, cooked or as a part of other dishes. One current goal in spinach breeding programs is to enhance quality and nutritional content. However, little is known about the diversity of nutritional content present in spinach germplasm, especially for AsA content. In this study, a worldwide panel of 352 accessions was screened for AsA content showing that variability in spinach germplasm is high and could be utilized for cultivar improvement. In addition, a genome-wide association study for marker-trait association was performed using three models, and associated markers were searched in the genome for functional annotation analysis. The generalized linear model (GLM), the compressed mixed linear model (CMLM) based on population parameters previously determined (P3D) and the perMarker model together identified a total of 490 significant markers distributed across all six spinach chromosomes indicating the complex inheritance of the trait. The different association models identified unique and overlapping marker sets, where 27 markers were identified by all three models. Identified high AsA content accessions can be used as parental lines for trait introgression and to create segregating populations for further genetic analysis. Bioinformatic analysis indicated that identified markers can differentiate between high and low AsA content accessions and that, upon validation, these markers should be useful for breeding programs.

A Combination of Leaf Rust Resistance Genes, Including Lr34 and Lr46, Is the Key to the Durable Resistance of the Canadian Wheat Cultivar, Carberry

The hexaploid spring wheat cultivar, Carberry, was registered in Canada in 2009, and has since been grown over an extensive area on the Canadian Prairies. Carberry has maintained a very high level of leaf rust (Puccinia triticina Eriks.) resistance since its release. To understand the genetic basis of Carberry's leaf rust resistance, Carberry was crossed with the susceptible cultivar, Thatcher, and a doubled haploid (DH) population of 297 lines was generated. The DH population was evaluated for leaf rust in seven field environments at the adult plant stage. Seedling and adult plant resistance (APR) to multiple virulence phenotypes of P. triticina was evaluated on the parents and the progeny population in controlled greenhouse studies. The population was genotyped with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, and quantitative trait loci (QTL) analysis was performed. The analysis using field leaf rust response indicated that Carberry contributed nine QTL located on chromosomes 1B, 2B (2 loci), 2D, 4A, 4B, 5A, 5B, and 7D. The QTL located on 1B, 2B, 5B, and 7D chromosomes were observed in two or more environments, whereas the remainder were detected in single environments. The resistance on 1B, detected in five environments, was attributed to Lr46 and on 7D, detected in seven environments to Lr34. The first 2B QTL corresponded with the adult plant gene, Lr13, while the second QTL corresponded with Lr16. The seedling analysis showed that Carberry carries Lr2a, Lr16, and Lr23. Five epistatic effects were identified in the population, with synergistic interactions being observed for Lr34 with Lr46, Lr16, and Lr2a. The durable rust resistance of Carberry is attributed to Lr34 and Lr46 in combination with these other resistance genes, because the resistance has remained effective even though the P. triticina population has evolved virulent to Lr2a, Lr13, Lr16, and Lr23.

The genomic structure of isolation across breed, country and strain for important South African and Australian sheep populations

Background

South Africa and Australia shares multiple important sheep breeds. For some of these breeds, genomic breeding values are provided to breeders in Australia, but not yet in South Africa. Combining genomic resources could facilitate development for across country selection, but the influence of population structures could be important to the compatability of genomic data from varying origins. The genetic structure within and across breeds, countries and strains was evaluated in this study by population genomic parameters derived from SNP-marker data. Populations were first analysed by breed and country of origin and then by subpopulations of South African and Australian Merinos.

Results

Mean estimated relatedness according to the genomic relationship matrix varied by breed (-0.11 to 0.16) and bloodline (-0.08 to 0.06) groups and depended on co-ancestry as well as recent genetic links. Measures of divergence across bloodlines (F_ST: 0.04–0.12) were sometimes more distant than across some breeds (F_ST: 0.05–0.24), but the divergence of common breeds from their across-country equivalents was weak (F_ST: 0.01–0.04). According to mean relatedness, F_ST, PCA and Admixture, the Australian Ultrafine line was better connected to the SA Cradock Fine Wool flock than with other AUS bloodlines. Levels of linkage disequilibrium (LD) between adjacent markers was generally low, but also varied across breeds (r²: 0.14–0.22) as well as bloodlines (r²: 0.15–0.19). Patterns of LD decay was also unique to breeds, but bloodlines differed only at the absolute level. Estimates of effective population size (N_e) showed genetic diversity to be high for the majority of breeds (N_e: 128–418) but also for bloodlines (N_e: 137–369).

Conclusions

This study reinforced the genetic complexity and diversity of important sheep breeds, especially the Merino breed. The results also showed that implications of isolation can be highly variable and extended beyond breed structures. However, knowledge of useful links across these population substructures allows for a fine-tuned approach in the combination of genomic resources. Isolation across country rarely proved restricting compared to other structures considered. Consequently, research into the accuracy of across-country genomic prediction is recommended.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08020-3.

Genetic Diversity and Population Structure of the Rice False Smut Pathogen Ustilaginoidea virens in the Sichuan-Chongqing Region

Rice false smut caused by Ustilaginoidea virens is one of the most devastating fungal diseases of rice panicles worldwide. In this study, two novel molecular markers derived from single nucleotide polymorphism-rich genomic DNA fragments and a previously reported molecular marker were used for analyzing the genetic diversity and population structure of 167 U. virens isolates collected from nine areas in the Sichuan-Chongqing region, China. A total of 62 haplotypes were identified, and a few haplotypes with high frequency were found and distributed in two to three areas, suggesting gene flow among different geographical populations. All isolates were divided into six genetic groups. Groups I and VI were the largest, with 61 and 48 isolates, respectively. The pairwise F_ST values showed significant genetic differentiation among all compared geographical populations. Analysis of molecular variance showed that intergroup genetic variation accounted for 40.17% of the total genetic variation, while 59.83% of genetic variation came from intragroup genetic variation. The unweighted pair-group method with arithmetic means dendrogram and population structure revealed that the genetic composition of isolates collected from Santai, Nanchong, Yongchuan, and Wansheng dominated by the same genetic subgroup was different from those collected from other areas. In addition, genetic recombination was found in a few isolates. These findings will help to improve the strategies for rice false smut management and resistance breeding, such as evaluating breeding lines with different isolates or haplotypes at different elevations and landforms.

Managing High-Density Genotyping Data with Gigwa

Next generation sequencing technologies enabled high-density genotyping for large numbers of samples. Nowadays SNP calling pipelines produce up to millions of such markers, but which need to be filtered in various ways according to the type of analyses. One of the main challenges still lies in the management of an increasing volume of genotyping files that are difficult to handle for many applications. Here, we provide a practical guide for efficiently managing large genomic variation data using Gigwa, a user-friendly, scalable and versatile application that may be deployed either remotely on web servers or on a local machine.

Population Structure and Relatedness for Genome-Wide Association Studies

The estimation of the population structure and genetic relatedness between individuals within a collection of accessions is important in the formation of core collections for the conservation of genetic resources, uncovering the demographic history of the population under study, as well as for association studies. With the recent development of high-throughput genotyping technologies, several algorithms and methods have been developed and implemented in software to estimate the extent of genetic diversity between individuals. In this chapter, our objective is to describe methods to capture population structure and relatedness in a step-by-step fashion. To exemplify the process, two pruned datasets (14K and 243K SNP markers) were used to investigate population structure and relatedness among a soybean GWAS panel using different approaches and methods.

Genome-Wide Association Study of Root Mealiness and Other Texture-Associated Traits in Cassava

Cassava breeders have made significant progress in developing new genotypes with improved agronomic characteristics such as improved root yield and resistance against biotic and abiotic stresses. However, these new and improved cassava (Manihot esculenta Crantz) varieties in cultivation in Nigeria have undergone little or no improvement in their culinary qualities; hence, there is a paucity of genetic information regarding the texture of boiled cassava, particularly with respect to its mealiness, the principal sensory quality attribute of boiled cassava roots. The current study aimed at identifying genomic regions and polymorphisms associated with natural variation for root mealiness and other texture-related attributes of boiled cassava roots, which includes fibre, adhesiveness (ADH), taste, aroma, colour, and firmness. We performed a genome-wide association (GWAS) analysis using phenotypic data from a panel of 142 accessions obtained from the National Root Crops Research Institute (NRCRI), Umudike, Nigeria, and a set of 59,792 high-quality single nucleotide polymorphisms (SNPs) distributed across the cassava genome. Through genome-wide association mapping, we identified 80 SNPs that were significantly associated with root mealiness, fibre, adhesiveness, taste, aroma, colour and firmness on chromosomes 1, 4, 5, 6, 10, 13, 17 and 18. We also identified relevant candidate genes that are co-located with peak SNPs linked to these traits in M. esculenta. A survey of the cassava reference genome v6.1 positioned the SNPs on chromosome 13 in the vicinity of Manes.13G026900, a gene recognized as being responsible for cell adhesion and for the mealiness or crispness of vegetables and fruits, and also known to play an important role in cooked potato texture. This study provides the first insights into understanding the underlying genetic basis of boiled cassava root texture. After validation, the markers and candidate genes identified in this novel work could provide important genomic resources for use in marker-assisted selection (MAS) and genomic selection (GS) to accelerate genetic improvement of root mealiness and other culinary qualities in cassava breeding programmes in West Africa, especially in Nigeria, where the consumption of boiled and pounded cassava is low.

Identification of a Diverse Core Set Panel of Rice From the East Coast Region of India Using SNP Markers

In India, rice (Oryza sativa L.) is cultivated under a variety of climatic conditions. Due to the fragility of the coastal ecosystem, rice farming in these areas has lagged behind. Salinity coupled with floods has added to this trend. Hence, to prevent genetic erosion, conserving and characterizing the coastal rice, is the need of the hour. This work accessed the genetic variation and population structure among 2,242 rice accessions originating from India’s east coast comprising Andhra Pradesh, Orissa, and Tamil Nadu, using 36 SNP markers, and have generated a core set (247 accessions) as well as a mini-core set (30 accessions) of rice germplasm. All the 36 SNP loci were biallelic and 72 alleles found with average two alleles per locus. The genetic relatedness of the total collection was inferred using the un-rooted neighbor-joining tree, which grouped all the genotypes (2,242) into three major clusters. Two groups were obtained with a core set and three groups obtained with a mini core set. The mean PIC value of total collection was 0.24, and those of the core collection and mini core collection were 0.27 and 0.32, respectively. The mean heterozygosity and gene diversity of the overall collection were 0.07 and 0.29, respectively, and the core set and mini core set revealed 0.12 and 0.34, 0.20 and 0.40 values, respectively, representing 99% of distinctiveness in the core and mini core sets. Population structure analysis showed maximum population at K = 4 for total collection and core collection. Accessions were distributed according to their population structure confirmed by PCoA and AMOVA analysis. The identified small and diverse core set panel will be useful in allele mining for biotic and abiotic traits and managing the genetic diversity of the coastal rice collection. Validation of the 36-plex SNP assay was done by comparing the genetic diversity parameters across two different rice core collections, i.e., east coast and northeast rice collection. The same set of SNP markers was found very effective in deciphering diversity at different genetic parameters in both the collections; hence, these marker sets can be utilized for core development and diversity analysis studies.

Diversity, Dispersal and Mode of Reproduction of Amanita exitialis in Southern China

Amanita exitialis is a poisonous mushroom and has caused many deaths in southern China. In this study, we collected 118 fruiting bodies of A. exitialis from seven different sites in Guangdong Province in southern China and investigated their genetic relationships using 14 polymorphic molecular markers. These 14 markers grouped the 118 fruiting bodies into 20 multilocus genotypes. Among these 20 genotypes, eight were each found only once while the remaining 12 were each represented by two to 54 fruiting bodies. Interestingly, among the 12 shared genotypes, four were shared between/among local populations that were separated by as far as over 80 km, a result consistent with secondary homothallic reproduction and long-distance spore dispersal. Despite the observed gene flow, significant genetic differentiations were found among the local populations, primarily due to the over-representation of certain genotypes within individual local populations. STRUCTURE analyses revealed that the 118 fruiting bodies belonged to three genetic clusters, consistent with divergence within this species in this geographic region. Interestingly, we found an excess of heterozygous individuals at both the local and the total sample level, suggesting potential inbreeding depression and heterozygous advantage in these populations of A. exitialis. We discuss the implications of our results for understanding the life cycle, dispersal, and evolution of this poisonous mushroom.

Genomic Approaches for Improvement of Tropical Fruits: Fruit Quality, Shelf Life and Nutrient Content

The breeding of tropical fruit trees for improving fruit traits is complicated, due to the long juvenile phase, generation cycle, parthenocarpy, polyploidy, polyembryony, heterozygosity and biotic and abiotic factors, as well as a lack of good genomic resources. Many molecular techniques have recently evolved to assist and hasten conventional breeding efforts. Molecular markers linked to fruit development and fruit quality traits such as fruit shape, size, texture, aroma, peel and pulp colour were identified in tropical fruit crops, facilitating Marker-assisted breeding (MAB). An increase in the availability of genome sequences of tropical fruits further aided in the discovery of SNP variants/Indels, QTLs and genes that can ascertain the genetic determinants of fruit characters. Through multi-omics approaches such as genomics, transcriptomics, metabolomics and proteomics, the identification and quantification of transcripts, including non-coding RNAs, involved in sugar metabolism, fruit development and ripening, shelf life, and the biotic and abiotic stress that impacts fruit quality were made possible. Utilizing genomic assisted breeding methods such as genome wide association (GWAS), genomic selection (GS) and genetic modifications using CRISPR/Cas9 and transgenics has paved the way to studying gene function and developing cultivars with desirable fruit traits by overcoming long breeding cycles. Such comprehensive multi-omics approaches related to fruit characters in tropical fruits and their applications in breeding strategies and crop improvement are reviewed, discussed and presented here.

Genomic regions associated with resistance to Fusarium wilt in castor identified through linkage and association mapping approaches

Fusarium wilt, caused by Fusarium oxysporum f. sp. ricini, is the most destructive disease in castor. Host plant resistance is the best strategy for the management of wilt. Identification of molecular markers linked to wilt resistance will enhance the efficiency and effectiveness of breeding for wilt resistance. In the present study, genomic regions linked to wilt resistance were mapped using a bi-parental population of 185 F₆-RILs and a genetically diverse panel of 300 germplasm accessions. Quantitative trait loci (QTL) analysis performed using a linkage map consisting of 1090 SNP markers identified a major QTL on chromosome 7 with an LOD score of 18.7, which explained 44% of the phenotypic variance. The association mapping performed using genotypic data from 3465 SNP loci revealed 69 significant associations (p < 1 × 10^-4) for wilt resistance. The phenotypic variance explained by the individual SNPs ranged from 0.063 to 0.210. The QTL detected in the bi-parental mapping population was not identified in the association analysis. Thus, the results of this study indicate the possibility of vast gene diversity for Fusarium wilt resistance in castor.

Identification of quantitative trait nucleotides and candidate genes for tuber yield and mosaic virus tolerance in an elite population of white guinea yam (Dioscorea rotundata) using genome-wide association scan

BACKGROUND

Improvement of tuber yield and tolerance to viruses are priority objectives in white Guinea yam breeding programs. However, phenotypic selection for these traits is quite challenging due to phenotypic plasticity and cumbersome screening of phenotypic-induced variations. This study assessed quantitative trait nucleotides (QTNs) and the underlying candidate genes related to tuber yield per plant (TYP) and yam mosaic virus (YMV) tolerance in a panel of 406 white Guinea yam (Dioscorea rotundata) breeding lines using a genome-wide association study (GWAS).

RESULTS

Population structure analysis using 5,581 SNPs differentiated the 406 genotypes into seven distinct sub-groups based delta K. Marker-trait association (MTA) analysis using the multi-locus linear model (mrMLM) identified seventeen QTN regions significant for TYP and five for YMV with various effects. The seveteen QTNs were detected on nine chromosomes, while the five QTNs were identified on five chromosomes. We identified variants responsible for predicting higher yield and low virus severity scores in the breeding panel through the marker-effect prediction. Gene annotation for the significant SNP loci identified several essential putative genes associated with the growth and development of tuber yield and those that code for tolerance to mosaic virus.

CONCLUSION

Application of different multi-locus models of GWAS identified 22 QTNs. Our results provide valuable insight for marker validation and deployment for tuber yield and mosaic virus tolerance in white yam breeding. The information on SNP variants and genes from the present study would fast-track the application of genomics-informed selection decisions in breeding white Guinea yam for rapid introgression of the targeted traits through markers validation.

Development of SNP Markers for White Immature Fruit Skin Color in Cucumber (Cucumis sativus L.) Using QTL-seq and Marker Analyses

Despite various efforts in identifying the genes governing the white immature fruit skin color in cucumber, the genetic basis of the white immature fruit skin color is not well known. In the present study, genetic analysis showed that a recessive gene confers the white immature fruit skin-color phenotype over the light-green color of a Korean slicer cucumber. High-throughput QTL-seq combined with bulked segregation analysis of two pools with the extreme phenotypes (white and light-green fruit skin color) in an F₂ population identified two significant genomic regions harboring QTLs for white fruit skin color within the genomic region between 34.1 and 41.67 Mb on chromosome 3, and the genomic region between 12.2 and 12.7 Mb on chromosome 5. Further, nonsynonymous SNPs were identified with a significance of p < 0.05 within the QTL regions, resulting in eight homozygous variants within the QTL region on chromosome 3. SNP marker analysis uncovered the novel missense mutations in Chr3CG52930 and Chr3CG53640 genes and showed consistent results with the phenotype of light-green and white fruit skin-colored F₂ plants. These two genes were located 0.5 Mb apart on chromosome 3, which are considered strong candidate genes. Altogether, this study laid a solid foundation for understanding the genetic basis and marker-assisted breeding of immature fruit skin color in cucumber.

ssGBLUP Method Improves the Accuracy of Breeding Value Prediction in Huacaya Alpaca

Simple Summary

Alpaca breeding takes place in the most entrenched areas of the Andes, where the conditions to implement genetic improvement programs are very difficult. Likewise, taking phenotypic records is limited in its ability to predict genetic merit accurately. For this reason, genomic information is shown as an alternative that helps to predict the genetic values of fiber traits more precisely. This study showed how genomic information increased precision by 2.623% for the fiber diameter, 6.442% for the standard deviation of the fiber diameter, and 1.471% for the percentage of medullation compared to traditional methods for predicting genetic merit, suggesting that adding genomic data in prediction models could be beneficial for alpaca breeding programs in the future.

Abstract

Improving textile characteristics is the main objective of alpaca breeding. A recently developed SNP chip for alpacas could potentially be used to implement genomic selection and accelerate genetic progress. Therefore, this study aimed to compare the increase in prediction accuracy of three important fiber traits: fiber diameter (FD), standard deviation of fiber diameter (SD), and percentage of medullation (PM) in Huacaya alpacas. The data contains a total pedigree of 12,431 animals, 24,169 records for FD and SD, and 8386 records for PM and 60,624 SNP markers for each of the 431 genotyped animals of the Pacomarca Genetic Center. Prediction accuracy of breeding values was compared between a classical BLUP and a single-step Genomic BLUP (ssGBLUP). Deregressed phenotypes were predicted. The accuracies of the genetic and genomic values were calculated using the correlation between the predicted breeding values and the deregressed values of 100 randomly selected animals from the genotyped ones. Fifty replicates were carried out. Accuracies with ssGBLUP improved by 2.623%, 6.442%, and 1.471% on average for FD, SD, and PM, respectively, compared to the BLUP method. The increase in accuracy was relevant, suggesting that adding genomic data could benefit alpaca breeding programs.

Genomic prediction for fusiform rust disease incidence in a large cloned population of Pinus taeda

In this study, 723 Pinus taeda L. (loblolly pine) clonal varieties genotyped with 16920 SNP markers were used to evaluate genomic selection for fusiform rust disease caused by the fungus Cronartium quercuum f. sp. fusiforme. The 723 clonal varieties were from five full-sib families. They were a subset of a larger population (1831 clonal varieties), field-tested across 26 locations in the southeast US. Ridge regression, Bayes B, and Bayes Cπ models were implemented to study marker-trait associations and estimate predictive ability for selection. A cross-validation scenario based on a random sampling of 80% of the clonal varieties for the model building had higher (0.71-0.76) prediction accuracies of genomic estimated breeding values compared with family and within-family cross-validation scenarios. Random sampling within families for model training to predict genomic estimated breeding values of the remaining progenies within each family produced accuracies between 0.38 and 0.66. Using four families out of five for model training was not successful. The results showed the importance of genetic relatedness between the training and validation sets. Bayesian whole-genome regression models detected three QTL with large effects on the disease outcome, explaining 54% of the genetic variation in the trait. The significance of QTL was validated with GWAS while accounting for the population structure and polygenic effect. The odds of disease incidence for heterozygous AB genotypes were 10.7 and 12.1 times greater than the homozygous AA genotypes for SNP11965 and SNP6347 loci, respectively. Genomic selection for fusiform rust disease incidence could be effective in P. taeda breeding. Markers with large effects could be fit as fixed covariates to increase the prediction accuracies, provided that their effects are validated further.

Molecular epidemiology of Burkholderia mallei isolates from India (2015-2016): New SNP markers for strain tracing

Glanders, caused by a bacterium called B. mallei, is primarily an infectious horse and human disease. Although its incidence is rare in developed countries, it is nonetheless prevalent in several geographical areas of the world. There is a lack of cost-effective, rapid and specific molecular typing tools for epidemiological tracing of glanders cases. We previously reported an SNP-based typing method that categorizes global B. mallei strains into three lineages (L1 to L3), as well as additional branches, sub-branches and groups. However, further discrimination of the Indian and Pakistani isolates within the L2B2sB2 sub-branch was not possible due to the lack of sufficient epidemiological markers. In this study, 10 B. mallei strains isolated from four states in India during 2015-2016 were whole genome sequenced; SNP analysis further confirmed their position in the L2B2sB2 branch. To better track the strains, four new markers targeting Indian or Pakistani strains, and specifically targeting sub-groups within the Indian strains, were identified. The new SNP markers were tested and validated on the 10 Indian isolates included in this study as well as on 6 contemporary B. mallei Pakistani strains. These rapid and discriminating typing tools will contribute to the epidemiological monitoring of B. mallei infections, particularly in South Asia and the Middle East, endemic regions of the disease.

Genome-Wide SNP Markers for Genotypic and Phenotypic Differentiation of Melon (Cucumis melo L.) Varieties Using Genotyping-by-Sequencing

Melon (Cucumis melo L.) is an economically important horticultural crop with abundant morphological and genetic variability. Complex genetic variations exist even among melon varieties and remain unclear to date. Therefore, unraveling the genetic variability among the three different melon varieties, muskmelon (C. melo subsp. melo), makuwa (C. melo L. var. makuwa), and cantaloupes (C. melo subsp. melo var. cantalupensis), could provide a basis for evolutionary research. In this study, we attempted a systematic approach with genotyping-by-sequencing (GBS)-derived single nucleotide polymorphisms (SNPs) to reveal the genetic structure and diversity, haplotype differences, and marker-based varieties differentiation. A total of 6406 GBS-derived SNPs were selected for the diversity analysis, in which the muskmelon varieties showed higher heterozygote SNPs. Linkage disequilibrium (LD) decay varied significantly among the three melon varieties, in which more rapid LD decay was observed in muskmelon (r² = 0.25) varieties. The Bayesian phylogenetic tree provided the intraspecific relationships among the three melon varieties that formed, as expected, individual clusters exhibiting the greatest genetic distance based on the posterior probability. The haplotype analysis also supported the phylogeny result by generating three major networks for 48 haplotypes. Further investigation for varieties discrimination allowed us to detect a total of 52 SNP markers that discriminated muskmelon from makuwa varieties, of which two SNPs were converted into cleaved amplified polymorphic sequence markers for practical use. In addition to these markers, the genome-wide association study identified two SNPs located in the genes on chromosome 6, which were significantly associated with the phenotypic traits of melon seed. This study demonstrated that a systematic approach using GBS-derived SNPs could serve to efficiently classify and manage the melon varieties in the genebank.