Genome- wide structural and functional variant discovery of rice landraces using genotyping by sequencing

Utilizing Genomics to Characterize the Common Oat Gene Pool—The Story of More than a Century of Polish Breeding

This study was undertaken to investigate the diversity and population structure of 487 oat accessions, including breeding lines from the ongoing programs of the three largest Polish breeding companies, along with modern and historical Polish and foreign cultivars. The analysis was based on 7411 DArTseq-derived SNPs distributed among three sub-genomes (A, C, and D). The heterogeneity of the studied material was very low, as only cultivars and advanced breeding lines were examined. Principal component analysis (PCA), principal coordinate analysis (PCoA), and cluster and STRUCTURE analyses found congruent results, which show that most of the examined cultivars and materials from Polish breeding programs formed major gene pools, that only some accessions derived from Strzelce Plant Breeding, and that foreign cultivars were outside of the main group. During the 120 year oat breeding process, only 67 alleles from the old gene pool were lost and replaced by 67 new alleles. The obtained results indicate that no erosion of genetic diversity was observed within the Polish native oat gene pool. Moreover, current oat breeding programs have introduced 673 new alleles into the gene pool relative to historical cultivars. The analysis also showed that most of the changes in relation to historical cultivars occurred within the A sub-genome with emphasis on chromosome 6A. The targeted changes were the rarest in the C sub-genome. This study showed that Polish oat breeding based mainly on traditional breeding methods—although focused on improving traits typical to this crop, i.e., enhancing the grain yield and quality and improving adaptability—did not significantly narrow the oat gene pool and in fact produced cultivars that are not only competitive in the European market but are also reservoirs of new alleles that were not found in the analyzed foreign materials.

Genome-wide discovery of genetic variations between rice cultivars with contrasting drought stress response and their potential functional relevance

Drought stress is a serious threat to rice productivity. Investigating genetic variations between drought-tolerant (DT) and drought-sensitive (DS) rice cultivars may decipher the candidate genes/regulatory regions involved in drought stress tolerance/response. In this study, whole-genome resequencing data of four DS and five DT rice cultivars were analyzed. We identified a total of approximately 4.8 million single nucleotide polymorphisms (SNPs) and 0.54 million insertions/deletions (InDels). The genetic variations (162,638 SNPs and 17,217 InDels) differentiating DS and DT rice cultivars were found to be unevenly distributed throughout the rice genome; however, they were more frequent near the transcription start and stop sites than in the genic regions. The cis-regulatory motifs representing the binding sites of stress-related transcription factors (MYB, HB, bZIP, ERF, ARR, and AREB) harboring the SNPs/InDels in the promoter regions of a few differentially expressed genes (DEGs) were identified. Importantly, many of these DEGs were located within the drought-associated quantitative trait loci. Overall, this study provides a valuable large-scale genotyping resource and facilitates the discovery of candidate genes associated with drought stress tolerance in rice.

qPCR Genotyping of Polyploid Species

A simple and cost-effective method for genotyping polyploid plants using quantitative PCR (qPCR) is described in this chapter. There is no additional operation, only simultaneous amplification of alleles and reference sequences with constant copy number in the genome. The qPCR genotyping can detect the genotypes of important traits in polyploid plants without whole genome sequencing data.

High-resolution quantitative trait locus mapping for rice grain quality traits using genotyping by sequencing

Rice is a major food crop that sustains approximately half of the world population. Recent worldwide improvements in the standard of living have increased the demand for high-quality rice. Accurate identification of quantitative trait loci (QTLs) for rice grain quality traits will facilitate rice quality breeding and improvement. In the present study, we performed high-resolution QTL mapping for rice grain quality traits using a genotyping-by-sequencing approach. An F₂ population derived from a cross between an elite japonica variety, Koshihikari, and an indica variety, Nona Bokra, was used to construct a high-density genetic map. A total of 3,830 single nucleotide polymorphism markers were mapped to 12 linkage groups spanning a total length of 2,456.4 cM, with an average genetic distance of 0.82 cM. Seven grain quality traits-the percentage of whole grain, percentage of head rice, percentage of area of head rice, transparency, percentage of chalky rice, percentage of chalkiness area, and degree of chalkiness-of the F₂ population were investigated. In total, 15 QTLs with logarithm of the odds (LOD) scores >4 were identified, which mapped to chromosomes 6, 7, and 9. These loci include four QTLs for transparency, four for percentage of chalky rice, four for percentage of chalkiness area, and three for degree of chalkiness, accounting for 0.01%-61.64% of the total phenotypic variation. Of these QTLs, only one overlapped with previously reported QTLs, and the others were novel. By comparing the major QTL regions in the rice genome, several key candidate genes reported to play crucial roles in grain quality traits were identified. These findings will expedite the fine mapping of these QTLs and QTL pyramiding, which will facilitate the genetic improvement of rice grain quality.

Tracking Changes in the Spring Barley Gene Pool in Poland during 120 Years of Breeding

This study was undertaken to investigate the diversity and population structure of 83 spring barley (Hordeum vulgare L.) cultivars, which corresponded to 120 years of this crop's breeding in Poland. The analysis was based on 11,655 DArTseq-derived SNPs evenly distributed across seven barley chromosomes. Five groups were assigned in the studied cultivars according to the period of their breeding. A decrease in observed heterozygosity within the groups was noted along with the progress in breeding, with a simultaneous increase in the inbreeding coefficient value. As a result of breeding, some of the unique allelic variation present in old cultivars was lost, but crosses with foreign materials also provided new alleles to the barley gene pool. It is important to mention that the above changes affected different chromosomes to varying degrees. The internal variability of the cultivars ranged from 0.011 to 0.236. Internal uniformity was lowest among the oldest cultivars, although some highly homogeneous ones were found among them. This is probably an effect of genetic drift or selection during their multiplications and regenerations in the period from breeding to the time of analysis. The population genetic structure of the studied group of cultivars appears to be quite complex. It was shown that their genetic makeup consists of as many as eleven distinct gene pools. The analysis also showed traces of directed selection on chromosomes 3H and 5H. Detailed data analysis confirmed the presence of duplicates for 11 cultivars. The performed research will allow both improvement of the management of barley genetic resources in the gene bank and the reuse of this rich and forgotten variability in breeding programs and research.

Genetic diversity and population structure of rice (Oryza sativa L.) landraces from Kerala, India analyzed through genotyping-by-sequencing

Researchers stand at the vanguard of advancement and application of next-generation sequencing technology for developing dominant strategies for the sustainable management of genetically diverse crops. We attempt to fill the existing research lacuna in the molecular characterization of potent rice landraces in Kerala. Genotyping-by-sequencing (GBS) was performed on 96 Kerala rice accessions to identify single-nucleotide polymorphisms (SNPs), to examine the genetic diversity, population structure, and to delineate linkage disequilibrium (LD) pattern. GBS identified 5856 high-quality SNPs. The structure analysis indicated three subpopulations with the highest probability for population clustering with significant genetic differentiation, confirmed by principal component analysis. The genome-wide LD decay distance was 772 kb, at which the r² dropped to half its maximum value. The analysis of genetic properties of the identified SNP panel with an average polymorphism information content (PIC) value of 0.22 and a minor allele frequency (MAF) > 0.1 unveiled their efficacy in genome-wide association studies (GWAS). High F_ST (0.266) and low Nm (0.692) portray a strong genetic differentiation among the rice landraces, complementing the genetic structuring observed in the studied population. Slow LD decay in the rice landraces reflects their self-pollinating behavior and the indirect selection of desired traits by domestication. Moreover, the high LD entails only a minimum number of SNP markers for detecting marker-trait association. The diverse germplasm utilized in this study can be further utilized to disclose genetic variants associated with phenotypic traits and define signatures of selection via GWAS and selective sweep, respectively.

Association mapping of drought tolerance and agronomic traits in rice (Oryza sativa L.) landraces

BACKGROUND

Asian cultivars were predominantly represented in global rice panel selected for sequencing and to identify novel alleles for drought tolerance. Diverse genetic resources adapted to Indian subcontinent were not represented much in spite harboring useful alleles that could improve agronomic traits, stress resilience and productivity. These rice accessions are valuable genetic resource in developing rice varieties suited to different rice ecosystem that experiences varying drought stress level, and at different crop stages. A core collection of rice germplasm adapted to Southwestern Indian peninsular genotyped using SSR markers and characterized by contrasting water regimes to associate genomic regions for physiological, root traits and yield related traits. Genotyping-By-Sequencing of selected accessions within the diverse panel revealed haplotype variation in genic content within genomic regions mapped for physiological, morphological and root traits.

RESULTS

Diverse rice panel (99 accessions) were evaluated in field and measurements on plant physiological, root traits and yield related traits were made over five different seasons experiencing varying drought stress intensity at different crop stages. Traits like chlorophyll stability index, leaf rolling, days to 50% flowering, chlorophyll content, root volume and root biomass were identified as best predictors of grain yield under stress. Association mapping revealed genetic variation among accessions and revealed 14 genomic targets associated with different physiological, root and plant production traits. Certain accessions were found to have beneficial allele to improve traits, plant height, root length and spikelet fertility, that contribute to the grain yield under stress. Genomic characterization of eleven accessions revealed haplotype variation within key genomic targets on chromosomes 1, 4, 6 and 11 for potential use as molecular markers to combine drought avoidance and tolerance traits. Genes mined within the genomic QTL intervals identified were prioritized based on tissue specific expression level in publicly available rice transcriptome data.

CONCLUSION

The genetic and genomic resources identified will enable combining traits with agronomic value to optimize yield under stress and hasten trait introgression into elite cultivars. Alleles associated with plant height, specific leaf area, root length from PTB8 and spikelet fertility and grain weight from PTB26 can be harnessed in future rice breeding program.

Genotyping of polyploid plants using quantitative PCR: application in the breeding of white-fleshed triploid loquats (Eriobotrya japonica)

BACKGROUND

Ploidy manipulation is effective in seedless loquat breeding, in which flesh color is a key agronomic and economic trait. Few techniques are currently available for detecting the genotypes of polyploids in plants, but this ability is essential for most genetic research and molecular breeding.

RESULTS

We developed a system for genotyping by quantitative PCR (qPCR) that allowed flesh color genotyping in multiple tetraploid and triploid loquat varieties (lines). The analysis of 13 different ratios of DNA mixtures between two homozygous diploids (AA and aa) showed that the proportion of allele A has a high correlation (R² = 0.9992) with parameter b [b = a₁/(a₁ + a₂)], which is derived from the two normalized allele signals (a₁ and a₂) provided by qPCR. Cluster analysis and variance analysis from simulating triploid and tetraploid hybrids provided completely correct allelic configurations. Four genotypes (AAA, AAa, Aaa, aaa) were found in triploid loquats, and four (AAAA, AAAa, AAaa, Aaaa; absence of aaaa homozygotes) were found in tetraploid loquats. DNA markers analysis showed that the segregation of flesh color in all F₁ hybrids conformed to Mendel's law. When tetraploid B431 was the female parent, more white-fleshed triploids occurred among the progeny.

CONCLUSIONS

qPCR can detect the flesh color genotypes of loquat polyploids and provides an alternative method for analyzing polyploid genotype and breeding, dose effects and allele-specific expression.

SSR marker-based genetic diversity analysis and SNP haplotyping of genes associating abiotic and biotic stress tolerance, rice growth and development and yield across 93 rice landraces

BACKGROUND

As rice is the staple food for more than half of the world's population, enhancing grain yield irrespective of the variable climatic conditions is indispensable. Many traditionally cultivated rice landraces are well adapted to severe environmental conditions and have high genetic diversity that could play an important role in crop improvement.

METHODS AND RESULTS

The present study revealed a high level of genetic diversity among the unexploited rice landraces cultivated by the farmers of Kerala. Twelve polymorphic markers detected a total of seventy- seven alleles with an average of 6.416 alleles per locus. Polymorphic Information Content (PIC) value ranged from 0.459 to 0.809, and to differentiate the rice genotypes, RM 242 was found to be the most appropriate marker with a high value of 0.809. The current study indicated that the rice landraces are highly diverse with higher values of the adequate number of alleles, PIC, and Shannon information index. Utilizing these informative SSR markers for future molecular characterization and population genetic studies in rice landraces are advisable. Haplotypes are sets of genomic regions within a chromosome inherited together, and haplotype-based breeding is a promising strategy for designing next-generation rice varieties. Here, haplotype analysis explored 270 haplotype blocks and 775 haplotypes from all the chromosomes of landraces under study. The number of SNPs in each haplotype block ranged from two to 28. Haplotypes of genes related to biotic and abiotic stress tolerance, yield-enhancing, and growth and development in rice landraces were also elucidated in the current study.

CONCLUSIONS

The present investigation revealed the genetic diversity of rice landraces and the haplotype analysis will open the way for genome-wide association studies, QTL identification, and marker-assisted selection in the unexplored rice landraces collected from Kerala.