Progress 07/01/20 to 09/30/22
Outputs
Target Audience:The target audiences for the work during this period include both public and private breeding companies and growers in California. The target groups were briefed on the objectives and possible results of the project for about 15 minutes of talk and open discussion on field visits during the 2022 Small Grains Breeding Programs Field Day held at UC Davison May 17, 2022. Changes/Problems:The lack of spike phenotype, the project had unexpected challenges to meet objective 2 (high-resolution mapping) and downstream analysis. This will require another generation of recombinant analysis to proceed further, provided favorable environmental /physiologicalconditions are met. What opportunities for training and professional development has the project provided?This project has been executed during the most difficult time during the covid-19 pandemic lockdown. Hence there were no in-person training and conferences (including NIFA's annual meetings). Nevertheless, I have attended an online PAG (Plant and Animal genome conferences, 2022), an online training workshop on "Tools for Polyploids Workshop", hands-on online training on "Introduction to the Command Line for Bioinformatics" organized by Bioinformatics Core at the genome center of UC Davis, as well as self-training courses on different R packages for Statistical data analysis. How have the results been disseminated to communities of interest?The objectives and results from this project were presented and discussed with the growers and industry at UC Davis open field day held in May 2022. Soon the results will also be published in scientific journals for the scientific comminutes. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
Objective 1: QTL mapping for spike branching suppressor genes Status: Completed One hundred eighty-eight F2 mapping populations were phenotyped in the greenhouse in 2021. To capture and quantify all phenotypic variations in the mapping population, spikelets from each lateral mini branch from each node of the spike and total spikelets number per spike (SNS) were counted and used for QTL mapping. All 188 F2s were genotyped using the wheat 90K Infinium iSelect SNP array. About 1630 single nucleotide polymorphic (SNP) markers were used to generate the genetic linkage map. Summary: The F2 lines showed significant variation for the spike branching. From the 188 F2 lines, 77 F2s didn't show any spike branching but secondary spikelets. About 48 lines showed spike branching exactly resembling 'Miracle Wheat' (parent 1). The rest 49 F2 lines showed different degrees of branching i.e. from one to three branches per spike. QTL mapping identified 5 significant and novel QTL on Chromosome 5A (143.3cM), 3B (123.91cM), 4A (80.11cM), and 7A (58.11cM) for spikelets number from the lateral mini spike arising from the 2nd, 5th, 6th, and 8th node of the spike, respectively, explaining in total about 48% of the phenotypic variance. Mapping of SNS (sum of the spikelets from the lateral min spikes plus those spikelets from the unbranched section of the spike) resulted in one strong QTL on chromosome 6B (165.4cM) explaining about 21% of the phenotypic variance. The 6B QTL showed an epistatic interaction with heading date QTL on Chromosome 5A and 7B and were eliminated from further analysis. Objective 2:High-resolution mapping using heterogeneous inbred families(HIF) Status: Partially completed (Challenged) After identifying the 6B QTL (165.4cM) for SNS, I moved to objective 2 to perform high-resolution mapping using heterogeneous inbred families (HIF) segregating for the QTL. I selected 8 F2 families that were homozygous for the 5A and 7B alleles for late heading time and heterozygous for the 6B QTL. To complement the high-resolution mapping, I have also produced backcrossed mapping population from F1 seeds obtained from the same cross that produced the F2 mapping population. F1 plants were randomly backcrossed to DG-bht-NILs to produce BC1F1 seeds. The BC1F1 plants were also randomly backcrossed to DG-bht-NILs to produce BC2F1 seeds. BC2F2 plants were genotyped using the flanking markers of the 6B QTL. Lines from BC2F2 carrying QTL were identified. Furthermore, exome capture has been performed on the parents i.e. TRI 19165 and DG-bht-NILs. A total of 996 plants from 8 F2/F3 heterozygous families alongside 456 progenies from 19 selected lines with recombination events within the 20 cM confidence interval of the 6B QTL were phenotyped and genotyped to Mendelize the 6B QTL. A total of 1452 plants were grown and phenotyped in the greenhouse Summary: Spike branching in wheat is sometimes unstable and environmentally the most sensitive phenotype. It also shows varying degree of penetrance and expressivity. Although the F2 mapping population segregated sufficiently to map SNS QTL on chromosome 6, the 8 selected critical recombinants identified under objective 2 failed to show spike phenotype i.e. spikes didn't show branching in a genetically meaningful (Mendelian) pattern. Out of 996 lines, only 30 lines showed spike branching with different degrees of expressivity i.e., one to three branches per spike. The lack of spike branching was also manifested in 'Miracle Wheat' itself which was planted alongside the critical recombinants. Instead of showing spike branching, the mini spike branches were reduced to a few secondary spikelets suggesting the extent of phenotypic plasticity (ability to alter physiology/morphology in response to changes in environmental conditions) of spike branching in wheat. This has posed a significant challenge to successfully accomplish objective 2 of the project. Hence, it is important to suggest that along with backcrossed BC2F2 populations, re-phenotyping another batch of critical recombinants for the 6B QTL could possibly help to narrow down the region and produce a high-resolution map provided that favorable physiological/environmental conditions are met. Objective 3: The development of bht-A1 and bht-B1 NILs and evaluation of the effect of increased spikelet number on grain yield. Status: Completed To check the effect of increased spikelet number on grain yield, bht-A1 and bht-B1 NILs were developed using marker-assisted selection (MAS). Two durum wheat varieties: Desert Gold (DG) and UC1771 were selected for NILs development. The NILs from DG and UC1771 were designated as DG-bht-NILs and UC1771- bht NILs, respectively. Along with the controls (i.e. those without bht-A1 and bht-B1 alleles), DG-bht-NILs and UC1771- bht NILs were field evaluated in Davis (northern California) and Imperial Valley (southern California) in the 2022 growing season in a Randomized Complete Block Design with five replications in each location. Ten random spikes were collected from each plot from each location to analyze spikelet number per spike (SNS), grain number per spike (GNS), grain number per spikelet (GPS), and thousand kernel weight (TKW). Summary: Phenotypic analysis of SNS from both NILs suggested that DG-bht-NILs express more SNS ranging from 87% to 114% compared to the control (spikes without bht-A1, bht-B1) while SNS in UC1771- bht NILs ranged 23 to 32 % as compared to the control (spikes without bht-A1, bht-B1). This data suggests that bht-A1 and bht-B1are beneficial alleles for increasing spikelet number in wheat. Interestingly, the increased SNS was associated with increased GNS both in DG- bht NILs and UC1771- bht NILs. Due to the increased SNS, DG- bht NILs has 23.5 % to 28.8 % more GNS as compared to the control (without bht-A1, bht-B1) which suggest a positive correlation between SNS and GNS. Although SNS and GNS were increased in the NILs, GPS in both NILs was low. Reduction in GPS in DG-bht-NILs can reach about 31% (in Imperial Valley) to 42.4% (in Davis) as compared to the controls. In UC7171-bht-NILs, there was a 21.4 % (Imperial Valley) to 34.4% (Davis) reduction in GPS compared to the control. This clearly indicated the negative (trade-off) effect of increasing SNS on spikelet fertility (GPS). Probably because of the reduction in GPS, none of the NILs have shown a yield advantage over the controls. Yield (kg/ha) reduction in DG- bht NILs ranged from 3.25% to 18.75%. Taken together, this result suggests that GPS is the most critical factor than the SNS for increasing grain yield. Thousand kernel weight (TKW) is also another primary grain yield component in wheat. However, the negative relationship between grain number and TKW remained to be the main challenge in wheat breeding. Because of the increased SNS and GNS, the reduction in TKW was stronger (20.54% to 26.78%) in DG-bht-NILs. Grains from 'Miracle Wheat' are usally small and round in shape. Interestingly, the grains from bht-NILs also showed similar characteristics, suggesting the clear pleiotropic effect of bht-A1and bht-B1 on grain morphometric traits in wheat. Changes in knowledge 'Miracle Wheat' has been known to the wheat community for several years. But it is the least utilized genetic resource either due to its instability, low penetrance, and expressivity and or low GPS because of the increased SNS. Increasing grain yield by increasing SNS is more challenging due to the associated trade-off effects on GPS and TKW. This study clearly indicated that increasing SNS has strong negative effect on grain yield and the TKW. As wheat yields are pushed closer to biological harvest limits and the fact that GPS is more important than the SNS, future work needs to focus on increasing GPS than increasing the SNS as increasing SNS is now genetically straight forward using alleles such as the bht-A1and bht-B1.
Publications
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Progress 07/01/20 to 06/30/21
Outputs
Target Audience:
Nothing Reported
Changes/Problems:Modifications has been made on our approach for objective1. We initially proposed to develop a Double Haploid (DH) mapping population for the QTL mapping. Due to the significant delays to develop the DH population during the pandemic (i.e., about 11 months), we decided to use an F2 mapping population. This change had no negative impact in the project since we were able to generate the map and identify the critical QTL without problem. It can be argued that the change was even favorable since it allowed us to check a much larger population of 188 lines instead of the initially planned 120 DH, which were limited by the cost of DH production. What opportunities for training and professional development has the project provided?
Nothing Reported
How have the results been disseminated to communities of interest?
Nothing Reported
What do you plan to do during the next reporting period to accomplish the goals?Now that Objective one is completed, I will focus on objectives 2 and 3. Under objective 2(high-resolution mapping), I will perform progeny tests for the 19 critical recombinantsin the 6B candidate gene region that are homozygous for the 5A and 7B QTL to define more precisely the candidate region. At the same time, I will advance the HIF population and screen its progeny for additional recombinants. In parallel, I will also develop additional markers in the region by using exome capture data from the parents for the mapping population. The exome capture data will provide a comprehensive list of the polymorphisms in the genes present in the candidate gene region and will help us not only to develop molecular markers for the progeny tests but also to identify polymorphic genes within the candidate gene region. If we identify any promising candidate gene, I will validate the gene either using the sequenced mutant database or CRISPRCas9. Under objective 3(yield trial), I will complete the analysis of the yield and yield component data from the 2021 harvest and I will prepare additional experiments in two locations in CA using the UC1171 and Desert Gold near isogeneic lines with and without the bh-A1 and bh-B1 alleles. The experiments will be organized as randomized complete block designswith 6replications.In parallel I will continue the generation of a Desert Gold line including the 6BL QTL together with the bh-A1 and bh-B1 alleles. Once this line is completed and seed is increased, we will compare its performance relative to the original Desert Gold and the Desert Gold isogenic line including only the bh-A1 and bh-B1 alleles.
Impacts
What was accomplished under these goals?
Objective 1. To accomplish the goal outlined in this objective, we initially proposed to develop a Double Haploid (DH) mapping population for the QTL mapping. We later discovered that the generation of a DH population was delayed 11 months. So, we decided to use an F2 mapping population instead of DH to save time. Accordingly, we developed an F2 mapping population including 188 plants for QTL mapping. The F2 mapping population was phenotyped in the greenhouse in 2021. All 188 F2s were genotyped using the wheat 90K Infinium iSelect SNP array and a genetic map including 1630 loci was generated. QTL mapping has been completed, and I identified 6chromosomal locations with significant LOD scores for the different spike branching phenotypes. Some of these QTL, particularly those affecting spikelet number per spike (SNS) were pleiotropic effects of heading or height genes segregating in the population and were eliminated. Based on these results and experiments in a different segregating population we decided to focus our efforts on the significant QTL on chromosomes 6B for the high-resolution mapping outlined in objective 2. Objective 2. To perform the high-resolution mapping of the QTL on chromosome 6B we first studied its epistatic interactions with other QTL affecting SNS on chromosomes 5A and 7B, that affect both SNS and heading time. A factorial ANOVA indicated significant interaction for SNS between the 6B QTL and these two additional QTL. Analysis of these data showed that the effects of the 6B QTL were enhanced in the presence of the alleles for late flowering in the 5A and 7B QTL. Therefore, I selected 8 F2 families that were homozygous for the 5A and 7B allele for late heading time and heterozygous for the 6B QTL. I started advancing these lines to generate heterogeneous inbreed families (HIF) for the later steps of the high-density map of the 6B QTL. I also identified 52 recombination events within the 20 cM confidence region of the 6B QTL and focused on 19 of them that were homozygous for both the 5A and 7B QTL to minimize genetic background variation. I have initiated the characterization of progeny tests of these informative recombination events to reduce the candidate gene region and to Mendelize the SNS QTL. In the 90K map we have 8 loci mapped within the critical candidate region and I will develop molecular markers for them to facilitate the genotyping of the plants in the progeny tests. Objective 3. To deploy the branching QTL in our breeding program we are trying to combine the 6B QTL with the previously identified bh-A1 and bh-B1 alleles for increase branching in the high quality and highly productive variety Desert Gold developed by the UCD Wheat Breeding Program. I had already performed three generations of random backcrossing of F1 plants to Desert Gold, and I will screen the progenies for the presence of the 6B QTLs. These lines will be crossed with the Desert Gold near isogeneic line with the bh-A1 and bh-B1 alleles to generate a line including the three genes. Meanwhile, I have initiated field testing of near isogeneic line including with and without the bh-A1 and bh-B1 alleles in the genetic backgrounds of Desert Gold and UC 1771. The lines were evaluated in in the field facilities at UC Davis in a randomized complete block design with at least 3 replications. The trial was harvested in June 2021, and seed cleaning and data analysis is under way. Seeds from this trial will be used for next season field trial in two locations in California with more replications.
Publications
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