Development of the Wheat Practical Haplotype Graph database as a resource for genotyping data storage and genotype imputation.

To improve the efficiency of high-density genotype data storage and imputation in bread wheat (Triticum aestivum L.), we applied the Practical Haplotype Graph (PHG) tool. The Wheat PHG database was built using whole-exome capture sequencing data from a diverse set of 65 wheat accessions. Population haplotypes were inferred for the reference genome intervals defined by the boundaries of the high-quality gene models. Missing genotypes in the inference panels, composed of wheat cultivars or recombinant inbred lines genotyped by exome capture, genotyping-by-sequencing (GBS), or whole-genome skim-seq sequencing approaches, were imputed using the Wheat PHG database. Though imputation accuracy varied depending on the method of sequencing and coverage depth, we found 92% imputation accuracy with 0.01× sequence coverage, which was slightly lower than the accuracy obtained using the 0.5× sequence coverage (96.6%). Compared to Beagle, on average, PHG imputation was ∼3.5% (P-value < 2 × 10-14) more accurate, and showed 27% higher accuracy at imputing a rare haplotype introgressed from a wild relative into wheat. We found reduced accuracy of imputation with independent 2× GBS data (88.6%), which increases to 89.2% with the inclusion of parental haplotypes in the database. The accuracy reduction with GBS is likely associated with the small overlap between GBS markers and the exome capture dataset, which was used for constructing PHG. The highest imputation accuracy was obtained with exome capture for the wheat D genome, which also showed the highest levels of linkage disequilibrium and proportion of identity-by-descent regions among accessions in the PHG database. We demonstrate that genetic mapping based on genotypes imputed using PHG identifies SNPs with a broader range of effect sizes that together explain a higher proportion of genetic variance for heading date and meiotic crossover rate compared to previous studies.

The Haplotype-Based Analysis of Aegilops tauschii Introgression Into Hard Red Winter Wheat and Its Impact on Productivity Traits.

The introgression from wild relatives have a great potential to broaden the availability of beneficial allelic diversity for crop improvement in breeding programs. Here, we assessed the impact of the introgression from 21 diverse accessions of Aegilops tauschii, the diploid ancestor of the wheat D genome, into 6 hard red winter wheat cultivars on yield and yield component traits. We used 5.2 million imputed D genome SNPs identified by the whole-genome sequencing of parental lines and the sequence-based genotyping of introgression population, including 351 BC1F3:5 lines. Phenotyping data collected from the irrigated and non-irrigated field trials revealed that up to 23% of the introgression lines (ILs) produce more grain than the parents and check cultivars. Based on 16 yield stability statistics, the yield of 12 ILs (3.4%) was stable across treatments, years, and locations; 5 of these lines were also high yielding lines, producing 9.8% more grain than the average yield of check cultivars. The most significant SNP- and haplotype-trait associations were identified on chromosome arms 2DS and 6DL for the spikelet number per spike (SNS), on chromosome arms 2DS, 3DS, 5DS, and 7DS for grain length (GL) and on chromosome arms 1DL, 2DS, 6DL, and 7DS for grain width (GW). The introgression of haplotypes from A. tauschii parents was associated with an increase in SNS, which was positively correlated with a heading date (HD), whereas the haplotypes from hexaploid wheat parents were associated with an increase in GW. We show that the haplotypes on 2DS associated with an increase in the spikelet number and HD are linked with multiple introgressed alleles of Ppd-D1 identified by the whole-genome sequencing of A. tauschii parents. Meanwhile, some introgressed haplotypes exhibited significant pleiotropic effects with the direction of effects on the yield component traits being largely consistent with the previously reported trade-offs, there were haplotype combinations associated with the positive trends in yield. The characterized repertoire of the introgressed haplotypes derived from A. tauschii accessions with the combined positive effects on yield and yield component traits in elite germplasm provides a valuable source of alleles for improving the productivity of winter wheat by optimizing the contribution of component traits to yield.

Significant progressive heterobeltiosis in banana crossbreeding.

BACKGROUND: Heterobeltiosis is the phenomenon when the hybrid's performance is superior to its best performing parent. Banana (Musa spp. AAA) breeding is a tedious, time-consuming process, taking up to two decades to develop a consumer acceptable hybrid. Exploiting heterobeltiosis in banana breeding will help to select breeding material with high complementarity, thus increasing banana breeding efficiency. The aim of this study was therefore to determine and document the level of heterobeltiosis of bunch weight and plant stature in the East African highland bananas, in order to identify potential parents that can be used to produce offspring with desired bunch weight and stature after a few crosses. RESULTS: This research found significant progressive heterobeltiosis in cross-bred 'Matooke' (highland cooking) banana hybrids, also known as NARITAs, when grown together across years with their parents and grandparents in Uganda. Most (all except 4) NARITAs exhibited positive heterobeltiosis for bunch weight, whereas slightly more than half of them had negative heterobeltiosis for stature. The secondary triploid NARITA 17 had the highest heterobeltiosis for bunch weight: 249% versus its 'Matooke' grandparent and 136% against its primary tetraploid parent. Broad sense heritability (across three cropping cycles) for yield potential and bunch weight were high (0.84 and 0.76 respectively), while that of plant stature was very low (0.0035). There was a positive significant correlation (P < 0.05) between grandparent heterobeltiosis for bunch weight and genetic distance between parents (r = 0.39, P = 0.036), bunch weight (r = 0.7, P < 0.001), plant stature (r = 0.38, P = 0.033) and yield potential (r = 0.59, P < 0.001). Grandparent heterobeltiosis for plant stature was significantly, but negatively, correlated to the genetic distance between parents (r = - 0.6, P < 0.001). CONCLUSIONS: Such significant heterobeltiosis exhibited for bunch weight is to our knowledge the largest among main food crops. Since bananas are vegetatively propagated, the effect of heterobeltiosis is easily fixed in the hybrids and will not be lost over time after the release and further commercialization of these hybrids.

Genomic Patterns of Introgression in Interspecific Populations Created by Crossing Wheat with Its Wild Relative.

Introgression from wild relatives is a valuable source of novel allelic diversity for breeding. We investigated the genomic patterns of introgression from Aegilops tauschii, the diploid ancestor of the wheat D genome, into winter wheat (Triticum aestivum) cultivars. The population of 351 BC1F3:5 lines was selected based on phenology from crosses between six hexaploid wheat lines and 21 wheat-Ae. tauschii octoploids. SNP markers developed for this population and a diverse panel of 116 Ae. tauschii accessions by complexity-reduced genome sequencing were used to detect introgression based on the identity-by-descent analysis. Overall, introgression frequency positively correlated with recombination rate, with a high incidence of introgression at the ends of chromosomes and low in the pericentromeric regions, and was negatively related to sequence divergence between the parental genomes. Reduced introgression in the pericentromeric low-recombining regions spans nearly 2/3 of each chromosome arm, suggestive of the polygenic nature of introgression barriers that could be associated with multilocus negative epistasis between the alleles of wild and cultivated wheat. On the contrary, negative selection against the wild allele of Tg, controlling free-threshing trait and located in the high-recombining chromosomal region, led to reduced introgression only within ∼10 Mbp region around Tg These results are consistent with the effect of selection on linked variation described by the Hill-Robertson effect, and offer insights into the introgression population development for crop improvement to maximize retention of introgressed diversity across entire genome.

Association genetics of bunch weight and its component traits in East African highland banana (Musa spp. AAA group).

KEY MESSAGE: The major quantitative trait loci associated with bunch weight and its component traits in the East African highland banana-breeding population are located on chromosome 3. Bunch weight increase is one of the major objectives of banana improvement programs, but little is known about the loci controlling bunch weight and its component traits. Here we report for the first time some genomic loci associated with bunch weight and its component traits in banana as revealed through a genome-wide association study. A banana-breeding population of 307 genotypes varying in ploidy was phenotyped in three locations under different environmental conditions, and data were collected on bunch weight, number of hands and fruits; fruit length and circumference; and diameter of both fruit and pulp for three crop cycles. The population was genotyped with genotyping by sequencing and 27,178 single nucleotide polymorphisms (SNPs) were generated. The association between SNPs and the best linear unbiased predictors of traits was performed with TASSEL v5 using a mixed linear model accounting for population structure and kinship. Using Bonferroni correction, false discovery rate, and long-range linkage disequilibrium (LD), 25 genomic loci were identified with significant SNPs and most were localized on chromosome 3. Most SNPs were located in genes encoding uncharacterized and hypothetical proteins, but some mapped to transcription factors and genes involved in cell cycle regulation. Inter-chromosomal LD of SNPs was present in the population, but none of the SNPs were significantly associated with the traits. The clustering of significant SNPs on chromosome 3 supported our hypothesis that fruit filling in this population was under control of a few quantitative trait loci with major effects.

Genotype Imputation in Winter Wheat Using First-Generation Haplotype Map SNPs Improves Genome-Wide Association Mapping and Genomic Prediction of Traits.

Genome-wide single nucleotide polymorphism (SNP) variation allows for the capture of haplotype structure in populations and prediction of unobserved genotypes based on inferred regions of identity-by-descent (IBD). Here we have used a first-generation wheat haplotype map created by targeted re-sequencing of low-copy genomic regions in the reference panel of 62 lines to impute marker genotypes in a diverse panel of winter wheat cultivars from the U.S. Great Plains. The IBD segments between the reference population and winter wheat cultivars were identified based on SNP genotyped using the 90K iSelect wheat array and genotyping by sequencing (GBS). A genome-wide association study and genomic prediction of resistance to stripe rust in winter wheat cultivars showed that an increase in marker density achieved by imputation improved both the power and precision of trait mapping and prediction. The majority of the most significant marker-trait associations belonged to imputed genotypes. With the vast amount of SNP variation data accumulated for wheat in recent years, the presented imputation framework will greatly improve prediction accuracy in breeding populations and increase resolution of trait mapping hence, facilitate cross-referencing of genotype datasets available across different wheat populations.

Molecular and Cytogenetic Study of East African Highland Banana.

East African highland bananas (EAHBs) are staple food crop in Uganda, Tanzania, Burundi, and other countries in the African Great Lakes region. Even though several morphologically different types exist, all EAHBs are triploid and display minimal genetic variation. To provide more insights into the genetic variation within EAHBs, genotyping using simple sequence repeat (SSR) markers, molecular analysis of ITS1-5.8S-ITS2 region of ribosomal DNA locus, and the analysis of chromosomal distribution of ribosomal DNA sequences were done. A total of 38 triploid EAHB accessions available in the Musa germplasm collection (International Transit Centre, Leuven, Belgium) were characterized. Six diploid accessions of Musa acuminata ssp. zebrina, ssp. banksii, and ssp. malaccensis representing putative parents of EAHBs were included in the study. Flow cytometric estimation of 2C nuclear DNA content revealed small differences (max ~6.5%) in genome size among the EAHB clones. While no differences in the number of 45S and 5S rDNA loci were found, genotyping using 19 SSR markers resulted in grouping the EAHB accessions into four clusters. The DNA sequence analysis of the internal transcribed spacer region indicated a relation of EAHB clones with M. acuminata and, surprisingly, also with M. schizocarpa. The results suggest that EAHB cultivars originated from a single hybrid clone with M. acuminata ssp. zebrina and ssp. banksii being its most probable parents. However, M. schizocarpa seems to have contributed to the formation of this group of banana.

Genomic Prediction in a Multiploid Crop: Genotype by Environment Interaction and Allele Dosage Effects on Predictive Ability in Banana.

Improving the efficiency of selection in conventional crossbreeding is a major priority in banana ( spp.) breeding. Routine application of classical marker assisted selection (MAS) is lagging in banana due to limitations in MAS tools. Genomic selection (GS) based on genomic prediction models can address some limitations of classical MAS, but the use of GS in banana has not been reported to date. The aim of this study was to evaluate the predictive ability of six genomic prediction models for 15 traits in a multi-ploidy training population. The population consisted of 307 banana genotypes phenotyped under low and high input field management conditions for two crop cycles. The single nucleotide polymorphism (SNP) markers used to fit the models were obtained from genotyping by sequencing (GBS) data. Models that account for additive genetic effects provided better predictions with 12 out of 15 traits. The performance of BayesB model was superior to other models particularly on fruit filling and fruit bunch traits. Models that included averaged environment data were more robust in trait prediction even with a reduced number of markers. Accounting for allele dosage in SNP markers (AD-SNP) reduced predictive ability relative to traditional bi-allelic SNP (BA-SNP), but the prediction trend remained the same across traits. The high predictive values (0.47- 0.75) of fruit filling and fruit bunch traits show the potential of genomic prediction to increase selection efficiency in banana breeding.

Trait variation and genetic diversity in a banana genomic selection training population.

Banana (Musa spp.) is an important crop in the African Great Lakes region in terms of income and food security, with the highest per capita consumption worldwide. Pests, diseases and climate change hamper sustainable production of bananas. New breeding tools with increased crossbreeding efficiency are being investigated to breed for resistant, high yielding hybrids of East African Highland banana (EAHB). These include genomic selection (GS), which will benefit breeding through increased genetic gain per unit time. Understanding trait variation and the correlation among economically important traits is an essential first step in the development and selection of suitable GS models for banana. In this study, we tested the hypothesis that trait variations in bananas are not affected by cross combination, cycle, field management and their interaction with genotype. A training population created using EAHB breeding material and its progeny was phenotyped in two contrasting conditions. A high level of correlation among vegetative and yield related traits was observed. Therefore, genomic selection models could be developed for traits that are easily measured. It is likely that the predictive ability of traits that are difficult to phenotype will be similar to less difficult traits they are highly correlated with. Genotype response to cycle and field management practices varied greatly with respect to traits. Yield related traits accounted for 31-35% of principal component variation under low and high input field management conditions. Resistance to Black Sigatoka was stable across cycles but varied under different field management depending on the genotype. The best cross combination was 1201K-1xSH3217 based on selection response (R) of hybrids. Genotyping using simple sequence repeat (SSR) markers revealed that the training population was genetically diverse, reflecting a complex pedigree background, which was mostly influenced by the male parents.

The triploid East African Highland Banana (EAHB) genepool is genetically uniform arising from a single ancestral clone that underwent population expansion by vegetative propagation.

KEY MESSAGE: All East African Highland Banana varieties are genetically uniform having arisen from a single clone introduced to Africa. East African Highland bananas (EAHBs) are a subgroup of triploid (AAA genome) bananas of importance to food security in the Great Lakes region of Africa. Little is known about their genetic variation, population structure and evolutionary history. Ninety phenotypically diverse EAHB cultivars were genotyped at 100 SSR microsatellite markers to investigate population genetic diversity, the correlation of genetic variability with morphological classes, and evolutionary origins since introduction to Africa. Population-level statistics were compared to those for plantain (AAB) and dessert (AAA) cultivars representing other M. acuminata subgroups. EAHBs displayed minimal genetic variation and are largely genetically uniform, irrespective of whether they were derived from the distinct Ugandan or Kenyan germplasm collections. No association was observed between EAHB genetic diversity and currently employed morphological taxonomic systems for EAHB germplasm. Population size dynamics indicated that triploid EAHBs arose as a single hybridization event, which generated a genetic bottleneck during foundation of the EAHB genepool. As EAHB triploids are sterile, subsequent asexual vegetative propagation of EAHBs allowed a recent rapid expansion in population size. This provided a basis for emergence of genetically near-isogenic somatic mutants selected across farmers and environments in East Africa over the past 2000 years since EAHBs were first introduced to the African continent.