Continuous Mapping Identifies Loci Associated With Weevil Resistance [Cosmopolites sordidus (Germar)] in a Triploid Banana Population

The first step toward marker-assisted selection is linking the phenotypes to molecular markers through quantitative trait loci (QTL) analysis. While the process is straightforward in self-pollinating diploid (2x) species, QTL analysis in polyploids requires unconventional methods. In this study, we have identified markers associated with weevil Cosmopolites sordidus (Germar) resistance in bananas using 138 triploid (2n = 3x) hybrids derived from a cross between a tetraploid "Monyet" (2n = 4x) and a 2x "Kokopo" (2n = 2x) banana genotypes. The population was genotyped by Diversity Arrays Technology Sequencing (DArTSeq), resulting in 18,009 polymorphic single nucleotide polymorphisms (SNPs) between the two parents. Marker-trait association was carried out by continuous mapping where the adjusted trait means for the corm peripheral damage (PD) and total cross-section damage (TXD), both on the logit scale, were regressed on the marker allele frequencies. Forty-four SNPs that were associated with corm PD were identified on the chromosomes 5, 6, and 8, with 41 of them located on chromosome 6 and segregated in "Kokopo." Eleven SNPs associated with corm total TXD were identified on chromosome 6 and segregated in "Monyet." The additive effect of replacing one reference allele with the alternative allele was determined at each marker position. The PD QTL was confirmed using conventional QTL linkage analysis in the simplex markers segregating in "Kokopo" (AAAA × RA). We also identified 43 putative genes in the vicinity of the markers significantly associated with the two traits. The identified loci associated with resistance to weevil damage will be used in the efforts of developing molecular tools for marker-assisted breeding in bananas.

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.

Crossbreeding East African Highland Bananas: Lessons Learnt Relevant to the Botany of the Crop After 21 Years of Genetic Enhancement

East African highland bananas (EAHB) were regarded as sterile. Their screening for female fertility with "Calcutta 4" as male parent revealed that 37 EAHB were fertile. This was the foundation for the establishment of the EAHB crossbreeding programs by the International Institute of Tropical Agriculture (IITA) and the National Agricultural Research Organization (NARO) in Uganda in the mid-1990s. The aim of this study was to assess the progress and efficiency of the EAHB breeding program at IITA, Sendusu in Uganda. Data on pollinations, seeds generated and germinated, plus hybrids selected between 1995 and 2015 were analyzed. Pollination success and seed germination percentages for different cross combinations were calculated. The month of pollination did not result in significantly different (P = 0.501) pollination success. Musa acuminata subsp. malaccensis accession 250 had the highest pollination success (66.8%), followed by the cultivar "Rose" (66.6%) among the diploid males. Twenty-five EAHB out of 41 studied for female fertility produced up to 305 seeds per pollinated bunch, and were therefore deemed fertile. The percentage of seed germination varied among crosses: 26% for 2x × 4x, 23% for 2x × 2x, 11% for 3x × 2x, and 7% for 4x × 2x. Twenty-seven NARITA hybrids (mostly secondary triploids ensuing from the 4x × 2x) were selected for further evaluation in the East African region. One so far -"NARITA 7"- was officially released to farmers in Uganda. Although pollination of EAHB can be conducted throughout the year, the seed set and germination is low. Thus, further research on pollination conditions and optimization of embryo culture protocols should be done to boost seed set and embryo germination, respectively. More research in floral biology and seed germination as well as other breeding strategies are required to increase the efficiency of the EAHB breeding program.

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.

Suitability of existing Musa morphological descriptors to characterize East African highland 'matooke' bananas

Morphological traits are commonly used for characterizing plant genetic resources. Germplasm characterization should be based on distinctly identifiable, stable and heritable traits that are expressed consistently and are easy to distinguish by the human eye. Characterization and documentation of a representative sample of East African highland bananas (Lujugira-Mutika subgroup) was carried out following an internationally accepted standard protocol for bananas. Eleven cultivars were characterized using an existing set of minimum descriptors (31 qualitative and quantitative traits) with the aim of determining stable descriptors and the ability of these descriptors to distinguish among East African highland banana cultivars. There was variation in stability of these descriptors within cultivars and across the 11 cultivars. Only 10 (32%) out of 31 descriptors studied were stable in the 11 cultivars. However, they had similar scores and therefore are not suitable to distinguish between cultivars within this group. Nonetheless, these 10 descriptors may be useful for distinguishing the East African highland bananas as a group from other groups of bananas. A few descriptors were unique to the cultivar 'Tereza' and may be used to distinguish this cultivar from other 'matooke' cultivars. None of the quantitative descriptors were stable.

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.