Theoretical and Applied Genetics最新文献

Key message: QKl/Tgw/Gns.yaas-2D associates with KL, TGW, and GNS, and QKl/Tgw.yaas-5A associates with KL and TGW. Significantly pleiotropic and additive effects of these two QTL were validated. The YM5 allele both at QKl/Tgw/Gns.yaas-2D and QKl/Tgw.yaas-5A was proved to be the best allelic combination for improving yield potential. Kernel length (KL), kernel width (KW), thousand grain weight (TGW), and grain number per spike (GNS) play important roles in the yield improvement of wheat. In this study, one recombinant inbred line (RIL) derived from a cross between Yangmai 5 (YM5) and Yanzhan 1 (YZ1) was used to identify quantitative trait loci (QTL) associated with KL, KW, TGW, and GNS across three years. Two pleiotropic QTL namely QKl/Tgw/Gns.yaas-2D and QKl/Tgw.yaas-5A were located in two genomic regions on chromosomes 2D and 5A, respectively. Breeder-friendly Kompetitive Allele-Specific PCR (KASP) markers for QKl/Tgw/Gns.yaas-2D and QKl/Tgw.yaas-5A were developed and validated in a set of 246 wheat cultivars/lines. Analysis of allelic combinations indicated that the YM5 allele both at QKl/Tgw/Gns.yaas-2D and QKl/Tgw.yaas-5A is probably the best one to promote TGW, GNS, and grain weight per spike. Based on the analysis of gene annotation, sequence variations, expression patterns, and GO enrichment, twenty-five and twenty-four candidate genes of QKl/Tgw/Gns.yaas-2D and QKl/Tgw.yaas-5A, respectively, were identified. These results provide the basis of fine-mapping the target QTL and marker-assisted selection in wheat yield-breeding programs.

Key message: Robust QTLs conferring resistance to bacterial leaf streak in wheat were mapped on chromosomes 3B and 5A from the variety Boost and on chromosome 7D from the synthetic wheat line W-7984. Bacterial leaf streak (BLS), caused by Xanthomonas translucens pv. undulosa poses a significant threat to global wheat production. High levels of BLS resistance are rare in hexaploid wheat. Here, we screened 101 diverse wheat genotypes under greenhouse conditions to identify new sources of BLS resistance. Five lines showed good levels of resistance including the wheat variety Boost and the synthetic hexaploid wheat line W-7984. Recombinant inbred populations derived from the cross of Boost × ND830 (BoostND population) and W-7984 × Opata 85 (ITMI population) were subsequently evaluated in greenhouse and field experiments to investigate the genetic basis of resistance. QTLs on chromosomes 3B, 5A, and 5B were identified in the BoostND population. The 3B and 5A QTLs were significant in all environments, but the 3B QTL was the strongest under greenhouse conditions explaining 38% of the phenotypic variation, and the 5A QTL was the most significant in the field explaining up to 29% of the variation. In the ITMI population, a QTL on chromosome 7D explained as much as 46% of the phenotypic variation in the greenhouse and 18% in the field. BLS severity in both populations was negatively correlated with days to heading, and some QTLs for these traits overlapped, which explained the tendency of later maturing lines to have relatively higher levels of BLS resistance. Markers associated with the QTLs were converted to KASP markers, which will aid in the deployment of the QTLs into elite lines for the development of BLS-resistant wheat varieties.

Key message: A major QTL responsible for self-incompatibility was stably identified in two F₂ populations. Through fine mapping and qRT-PCR analysis, ARK3 emerged as the most promising candidate gene, playing a pivotal role in regulating self-incompatibility in Brassica oleracea. Self-incompatibility (SI) is a common phenomenon in Brassica oleracea species, which can maintain genetic diversity but will also limit seed production. Although the S locus has been extensively studied in Arabidopsis and some Brassicaceae crops, map-based cloning of self-incompatibility genes has not been conducted in Brassica oleracea, such as cauliflower and broccoli. In the present study, we identified a major co-localized QTL on chromosome C6 that control SI in two F₂ populations derived from intervarietal crosses: broccoli × cauliflower (CL_F₂) and cauliflower × Chinese kale (CJ_F₂). Subsequently, this QTL was narrowed down to 168.5 Kb through fine mapping using 3,429 F_2:3 progenies and 12 available KASP markers. Within this 168.5 Kb region, BolC6t39084H, a homologue of Arabidopsis ARK3, could be a candidate gene that plays a key role in regulating SI in B. oleracea species. This finding can pave the way for an in-depth understanding of the molecular mechanisms underlying SI, and will contribute to the seed production of B. oleracea vegetables.

Key message: Two novel and one known genomic regions associated with R-gene resistance to Phytophthora sojae were identified by genome-wide association analysis and linkage analysis in soybean. Phytophthora root and stem rot (PRR) caused by Phytophthora sojae is a severe disease that causes substantial economic losses in soybean [Glycine max (L.) Merr.]. The primary approach for successful disease management of PRR is using R-gene-mediated resistance. Based on the phenotypic evaluation of 376 cultivated soybean accessions for the R-gene type resistance to P. sojae (isolate 2457), a genome-wide association analysis identified two regions on chromosomes 3 and 8. The most significant genomic region (20.7-21.3 Mbp) on chromosome 8 was a novel resistance locus where no Rps gene was previously reported. Instead, multiple copies of the UDP-glycosyltransferase superfamily protein-coding gene, associated with disease resistance, were annotated in this new locus. Another genomic region on chromosome 3 was a well-known Rps cluster. Using the Daepung × Ilpumgeomjeong RIL population, a linkage analysis confirmed these two resistance loci and identified a resistance locus on chromosome 2. A unique feature of the resistance in Ilpumgeomjeong was discovered when phenotypic distribution was projected upon eight groups of RILs carrying different combinations of resistance alleles for the three loci. Interestingly, the seven groups carrying at least one resistance allele statistically differed from the other with none, regardless of the number of resistance alleles. This suggests that the respective three different resistance genes can confer resistance to P. sojae isolate 2457. Deployment of the three regions via marker-assisted selection will facilitate effectively improving resistance to particular P. sojae isolates in soybean breeding programs.

Key message: The QTLs and candidate genes governing the multifoliolate phenotype were identified by combining linkage mapping with BSR-seq, revealing a possible interplay between genetics and the environment in soybean leaf development. Soybean, as a legume, is typified by trifoliolate leaves. Although multifoliolate leaves (compound leaves with more than three leaflets each) have been reported in soybean, including sporadic appearances in the first compound leaves in a recombinant inbred line (RIL) population from a cross between cultivated soybean C08 and wild soybean W05 from this study, the genetic basis of this phenomenon is still unclear. Here, we integrated quantitative trait locus (QTL) mapping with bulked segregant RNA sequencing (BSR-seq) to identify the genetic loci associated with the multifoliolate phenotype in soybean. Using linkage mapping, ten QTLs related to the multifoliolate trait were identified. Among these, a significant and major QTL, qMF-2-1 on chromosome 2 and consistently detected across biological replicates, explained more than 10% of the phenotypic variation. Together with BSR-seq analyses, which analyzed the RILs with the highest multifoliolate frequencies and those with the lowest frequencies as two distinct bulks, two candidate genes were identified: Glyma.06G204300 encoding the transcription factor TCP5, and Glyma.06G204400 encoding LONGIFOLIA 2 (LNG2). Transcriptome analyses revealed that stress-responsive genes were significantly differentially expressed between high-multifoliolate occurrence lines and low occurrence ones, indicating environmental factors probably influence the appearance of multifoliolate leaves in soybean through stress-responsive genes. Hence, this study offers new insights into the genetic mechanism behind the multifoliolate phenotype in soybean.

Key message: A major stable QTL, QGPC.caas-7AL, for grain protein content of wheat, was narrowed down to a 1.82-Mb inter on chromosome 7AL, and four candidate genes were predicated. Wheat grain protein content (GPC) is important for end-use quality. Identification of genetic loci for GPC is helpful to create new varieties with good processing quality and nutrients. Zhongmai 578 (ZM578) and Jimai 22 (JM22) are two elite wheat varieties with different contents of GPC. In the present study, 262 recombinant inbred lines (RILs) derived from a cross between ZM578 and JM22 were used to map the GPC with high-density wheat Illumina iSelect 50 K single-nucleotide polymorphism (SNP) array. Seven quantitative trait loci (QTLs) were identified for GPC on chromosomes 3AS, 3AL, 3BS, 4AL, 5BS, 5DL and 7AL by inclusive composite interval mapping, designated as QGPC.caas-3AS, QGPC.caas-3AL, QGPC.caas-3BS, QGPC.caas-4AL, QGPC.caas-5BS, QGPC.caas-5DL and QGPC.caas-7AL, respectively. Among these, alleles for increasing GPC at QGPC.caas-3AS, QGPC.caas-3BS, QGPC.caas-4AL and QGPC.caas-7AL loci were contributed by ZM578, whereas those at the other three loci were from JM22. The stable QTL QGPC.caas-7AL was fine mapped to a 1.82-Mb physical interval using secondary populations from six heterozygous recombinant plants obtained by selfing a residual RIL. Four genes were predicted as candidates of QGPC.caas-7AL based on sequence polymorphism and expression patterns. The near-isogenic lines (NILs) with the favorable allele at the QGPC.caas-7AL locus increased Farinograph stability time, Extensograph extension area, extensibility and maximum resistance by 19.6%, 6.3%, 6.0% and 20.3%, respectively. Kompetitive allele-specific PCR (KASP) marker for QGPC.caas-7AL was developed and validated in a diverse panel of 166 Chinese wheat cultivars. These results provide further insight into the genetic basis of GPC, and the fine-mapped QGPC.caas-7AL will be an attractive target for map-based cloning and marker-assisted selection in wheat breeding programs.

Key message: Genetic gain in Nordic spring barley varieties was estimated to 1.07% per year. Additionally, genomic predictive ability for yield was 0.61 in a population of breeding lines. Barley is one of the most important crops in Europe and meeting the growing demand for food and feed requires continuous increase in yield. Genomic prediction (GP) has the potential to be a cost-efficient tool in breeding for complex traits; however, the rate of yield improvement in current barley varieties is unknown. This study therefore investigated historical and current genetic gains in spring barley and how accounting for row-type population stratification in a breeding population influences GP results. The genetic gain in yield was estimated using historical data from field trials from 2014 to 2022, with 22-60 market varieties grown yearly. The genetic gain was estimated to 1.07% per year for all varieties, serving as a reference point for future breeding progress. To analyse the potential of using GP in spring barley a population of 375 breeding lines of two-row and six-row barley were tested in multi-environment trials in 2019-2022. The genetic diversity of the row-types was examined and used as a factor in the predictions, and the potential to predict untested locations using yield data from other locations was explored. This resulted in an overall predictive ability of 0.61 for yield (kg/ha), with 0.57 and 0.19 for the separate two-row and the six-row breeding lines, respectively. Together this displays the potential of implementing GP in breeding programs and the genetic gain in spring barley market varieties developed through GP will help in quantifying the benefit of GP over conventional breeding in the future.

Key message: Climate change can limit yields of naturally resilient crops, like sorghum, challenging global food security. Agriculture under an erratic climate requires tapping into a reservoir of flexible adaptive loci that can lead to lasting yield stability under multiple abiotic stress conditions. Domesticated in the hot and dry regions of Africa, sorghum is considered a harsh crop, which is adapted to important stress factors closely related to climate change. To investigate the genetic basis of drought stress adaptation in sorghum, we used a multi-environment multi-locus genome-wide association study (MEML-GWAS) in a subset of a diverse sorghum association panel (SAP) phenotyped for performance both under well-watered and water stress conditions. We selected environments in Brazil that foreshadow agriculture where both drought and temperature stresses coincide as in many tropical agricultural frontiers. Drought reduced average grain yield (Gy) by up to 50% and also affected flowering time (Ft) and plant height (Ph). We found 15 markers associated with Gy on all sorghum chromosomes except for chromosomes 7 and 9, in addition to loci associated with phenology traits. Loci associated with Gy strongly interacted with the environment in a complex way, while loci associated with phenology traits were less affected by G × E. Studying environmental covariables potentially underpinning G × E, increases in relative humidity and evapotranspiration favored and disfavored grain yield, respectively. High temperatures influenced G × E and reduced sorghum yields, with a ~ 100 kg ha^-1 average decrease in grain yield for each unit increase in maximum temperature between 29 and 38 °C. Extreme G × E for sorghum stress resilience poses an additional challenge to breed crops for moving, erratic weather conditions.

Key message: Specific combinations of LFY and WAPO1 natural alleles maximize spikelet number per spike in wheat. Spikelet number per spike (SNS) is an important yield component in wheat that determines the maximum number of grains that can be formed in a wheat spike. In wheat, loss-of-function mutations in LEAFY (LFY) or its interacting protein WHEAT ORTHOLOG OF APO1 (WAPO1) significantly reduce SNS by reducing the rate of formation of spikelet meristems. In previous studies, we identified a natural amino acid change in WAPO1 (C47F) that significantly increases SNS in hexaploid wheat. In this study, we searched for natural variants in LFY that were associated with differences in SNS and detected significant effects in the LFY-B region in a nested association mapping population. We generated a large mapping population and confirmed that the LFY-B polymorphism R80S is linked with the differences in SNS, suggesting that LFY-B is the likely causal gene. A haplotype analysis revealed two amino acid changes P34L and R80S, which were both enriched during wheat domestication and breeding suggesting positive selection. We also explored the interactions between the LFY and WAPO1 natural variants for SNS using biparental populations and identified significant interaction, in which the positive effect of the 80S and 34L alleles from LFY-B was only detected in the WAPO-A1 47F background but not in the 47C background. Based on these results, we propose that the allele combination WAPO-A1-47F/LFY-B 34L 80S can be used in wheat breeding programs to maximize SNS and increase grain yield potential in wheat.