Drought significantly limits worldwide crop yields, with autophagy acting as an essential regulatory component in plant adaptation to stress. In Tartary buckwheat, while there has been evidence of autophagosome accumulation and increased levels of FtATG8a due to drought, the molecular pathways governing FtATG8a have not yet been clarified. Our research shows that overexpressing FtATG8a markedly improves drought tolerance in genetically modified plants by synchronizing the activation of autophagy, boosting antioxidant defenses (such as SOD, POD, and CAT), and promoting proline biosynthesis. Through yeast two-hybrid screening, we identified FtE2FB as a nuclear-localized partner that interacts with FtATG8a, with their interaction facilitated by a conserved ATG8-interacting motif (EKFEDI) found in FtE2FB, which was validated using various complementary assays. Importantly, FtE2FB expression demonstrated dual induction patterns in response to drought stress and the overexpression of FtATG8a, indicating a feedback regulatory mechanism. Functional experiments showed that the solitary overexpression of FtE2FB boosts drought resistance via the modulation of the antioxidant system and increased proline levels in Arabidopsis. Additionally, the combined expression of FtATG8a and FtE2FB led to a more substantial rise in both antioxidant enzyme activity and proline content when compared to the overexpression of either FtE2FB or FtATG8a on its own under 20 % PEG6000 treatment. This study clarifies an autophagy-related regulatory network that underpins drought adaptation in Tartary buckwheat, offering valuable mechanistic insights into the coordination of stress responses and highlighting potential molecular targets for enhancing crop improvement strategies.

Zinc is an essential microelement of enzymes and proteins in wheat grains and humans. A deficiency in zinc content can lead to decreased wheat yield and low zinc content in grains, which in turn leads to insufficient dietary zinc intake. One recombinant inbred line (RIL) population derived from crosses Avocet/Huites (AH population) was used to map QTL for grain zinc content (GZnC) using diversity array technology (DArT). Nine QTLs were identified on chromosomes 2D, 3B, 4A, 4D, 5A, 5B, 6A, 7A, and 7D. Among them, QGZn.haust-AH-2D was detected in multiple environments, accounting for 5.61% to 11.27% of the phenotypic variation with a physical interval of 13.62 Mb to 17.82 Mb. Meanwhile, a genome-wide association study (GWAS) (CH population) comprising 243 cultivars or advanced lines revealed some genetic loci associated with zinc content in the wheat 660K single-nucleotide polymorphism (SNP) array. This was also identified within the physical interval of 13.61 Mb to 15.12 Mb of chromosome 2D, which accounted for 8.99% to 11.58% of the phenotypic variation in five models. A high-throughput competitive allele specific PCR (KASP) marker was developed, which verified the wheat natural population (NA population). QGZn.haust-AH-2D was fine mapped into a narrow region named TaZn-2DS between KAZn-2D-3 and 1111273 at a physical distance of 2.70 Mb, and the genetic effect of TaZn-2DS was 11.43%. This study shows that TaZn-2DS is associated with zinc content, and develops KAZn-2D-3 markers for the genetic improvement of nutritional quality in wheat.

BACKGROUNDThe English grain aphid, Sitobion avenae (Fabricius), is a devastating pest impacts yield and quality in wheat (Triticum aestivum L.). Breeding resistant wheat varieties and detecting resistance genes are important strategies to control aphid. RESULTSIn this study, we evaluated the number of aphids per spike, the rate of thousand kernel weight decrease and aphid index based on three classic resistance mechanisms (antibiosis, tolerance and antixenosis), and detected SNPs/QTLs for resistance to S. avenae in a natural population of 163 varieties with 20 689 high-quality single-nucleotide polymorphism (SNP) markers and recombinant inbred line (RIL) population of 164 lines with 3627 diversity arrays technology (DArT) markers. Results showed that 83 loci significantly associated with S. avenae antibiosis and 182 loci significantly associated with S. avenae tolerance were detected by genome-wide association study (GWAS), explaining 6.47-15.82% and 8.36-35.61% of the phenotypic variances, respectively. The wsnp_Ku_c4568_8243646 detected in two periods was localized at 34.52 Mb on chromosome 3AS. Then, we confirmed a stable QSa.haust-3A.2 explained 11.19-20.10% of the phenotypic variances in two periods with S. avenae antixenosis in the physical interval of 37.49-37.50 Mb on chromosome 3A in the RIL population. Therefore, a narrow region in the physical interval of 34.52-37.50 Mb on chromosome 3AS was named as qSa-3A, which was a new locus between wsnp_Ku_c4568_8243646 and QSa.haust-3A.2 associated with S. avenae resistance. CONCLUSIONWe found qSa-3A was a new locus associated with S. avenae resistance. The results could be applied in gene cloning and genetic improvement of S. avenae resistance in wheat. & COPY; 2023 Society of Chemical Industry.

Genetic dissection of yield component traits including kernel characteristics is essential for the continuous improvement in wheat yield. In the present study, one recombinant inbred line (RIL) F-6 population derived from a cross between Avocet and Chilero was used to evaluate the phenotypes of kernel traits of thousand-kernel weight (TKW), kernel length (KL), and kernel width (KW) in four environments at three experimental stations during the 2018-2020 wheat growing seasons. The high-density genetic linkage map was constructed with the diversity arrays technology (DArT) markers and the inclusive composite interval mapping (ICIM) method to identify the quantitative trait loci (QTLs) for TKW, KL, and KW. A total of 48 QTLs for three traits were identified in the RIL population on the 21 chromosomes besides 2A, 4D, and 5B, accounting for 3.00%-33.85% of the phenotypic variances. Based on the physical positions of each QTL, nine stable QTL clusters were identified in the RILs, and among these QTL clusters, TaTKW-1A was tightly linked to the DArT marker interval 3950546-1213099, explaining 10.31%-33.85% of the phenotypic variances. A total of 347 high-confidence genes were identified in a 34.74-Mb physical interval. TraesCS1A02G045300 and TraesCS1A02G058400 were among the putative candidate genes associated with kernel traits, and they were expressed during grain development. Moreover, we also developed high-throughput kompetitive allele-specific PCR (KASP) markers of TaTKW-1A, validated in a natural population of 114 wheat varieties. The study provides a basis for cloning the functional genes underlying the QTL for kernel traits and a practical and accurate marker for molecular breeding.

于河南孟津对我国不同育成年代的268个小麦品种(系)进行田间成株期麦长管蚜抗性鉴定.结果表明,供试材料中抗性品种(系)仅37.31％,其中,免疫(北京841、内乡184)、高抗、中抗、低抗品种(系)分别占供试品种总数的0.75％、1.49％、7.46％、27.61％.2010年之后育成品种(系)感性品种占比达79.72％.研究表明,供试268个小麦品种(系)中小麦麦长管蚜免疫、高抗、中抗品种(系)较少,且2010年之后育成品种(系)抗性品种匮乏.

Wheat (Triticum aestivum L.) is one of the main food crops in the world and a primary source of zinc (Zn) and iron (Fe) in the human body. The genetic mechanisms underlying related traits have been clarified, thereby providing a molecular theoretical foundation for the development of germplasm resources. In this study, a total of 23,536 high-quality DArT markers was used to map quantitative trait loci (QTL) of grain Zn (GZn) and grain Fe (GFe) concentrations in recombinant inbred lines crossed by Avocet/Chilero. A total of 17 QTLs was located on chromosomes 1BL, 2BL, 3BL, 4AL, 4BS, 5AL, 5DL, 6AS, 6BS, 6DS, and 7AS accounting for 0.38–16.62% of the phenotypic variance. QGZn.haust-4AL, QGZn.haust-7AS.1, and QGFe.haust-6BS were detected on chromosomes 4AL, 6BS, and 7AS, accounting for 10.63–16.62% of the phenotypic variance. Four stable QTLs, QGZn.haust-4AL, QGFe.haust-1BL, QGFe.haust-4AL, and QGFe.haust-5DL, were located on chromosomes 1BL, 4AL, and 5DL. Three pleiotropic effects loci for GZn and GFe concentrations were located on chromosomes 1BL, 4AL, and 5DL. Two high-throughput Kompetitive Allele Specific PCR markers were developed by closely linking single-nucleotide polymorphisms on chromosomes 4AL and 5DL, which were validated by a germplasm panel. Therefore, it is the most important that quantitative trait loci and KASP marker for grain zinc and iron concentrations were developed for utilizing in marker-assisted breeding and biofortification of wheat grain in breeding programs.

Seed vigor is an important parameter of seed quality, and identification of seed vigor related genes can provide an important basis for highly efficient molecular breeding in wheat. In the present study, a doubled haploid (DH) population with 174 lines derived from a cross between Yangmai16 and Zhongmai 895 was used to evaluate 10 seed vigor related traits in Luoyang during the 2018-2019 cropping season and in Mengjin and Luoning Counties during 2019-2020 cropping season for three environments. Quantitative trait locus (QTL) mapping of 10 seed vigor related traits in the DH population resulted in the discovery/identification of 28 QTLs on chromosomes 2B, 3D, 4B, 4D, 5A, 5B, 6A, 6B, 6D, 7A and 7D, explaining 3.6-23.7% of the phenotypic variances. Among them, one QTL cluster for shoot length, root length and vigor index was mapped between AX-89421921 and Rht-D1_SNP on chromosome 4D in the physical intervals of 18.78-19.29 Mb (0.51 Mb), explaining 9.2-20.5% of the phenotypic variances. Another QTL for these traits was identified at the physical position 185.74 Mb on chromosome 5B, which was flanked by AX-111465230 and AX-109519938 and accounted for 8.0-13.3% of the phenotypic variances. Two QTLs for shoot length, shoot fresh weight and shoot dry weight were identified in the marker intervals of AX-109384026-AX-111120402 and AX-111651800-AX-94443918 on chromosomes 6A and 6B, explaining 8.2-11.7% and 3.6-10.3% of the phenotypic variance, respectively; both alleles for increasing phenotypic values were derived from Yangmai 16. We also developed the KASP markers for the QTL cluster QVI.haust-4D.1/QSL.haust-4D/QRL.haust-4D , and validated in an international panel of 135 wheat accessions. The germplasm, genes and KASP markers were developed for breeders to improve wheat varieties with seed vigor related traits.

为了解中国不同麦区小麦种质资源籽粒脂肪氧化酶(lipoxygenase,LOX)活性相关基因TaLox-Bl的差异和分布,利用小麦4B染色体上的功能标记LOX16和LOX18对7个麦区的436份种质资源进行分子检测.结果表明:在供试材料中共检测到3种TaLox-B1基因等位变异类型,分别为TaLox-B1a(与高LOX活性相关)、TaLox-B1b(与低LOX活性相关)和杂合型,其频率分别为19.0％、70.4％和10.6％.小麦LOX活性基因不同变异类型在各生态区的分布存在明显差异:基因型TaLox-B1a在黄淮冬麦区、北部冬麦区和长江中下游冬麦区分布较多,其比例分别为21.1％、19.8％和17.6％;基因型TaLox-B1b在西南冬麦区和长江中下游冬麦区分布较多,比例分别为87.9％、72.5％;杂合型仅存在于北部冬麦区、黄淮冬麦区与长江中下游冬麦区,比例分别为14.2％、12.4％和9.8％.利用标记LOX16和LOX18对53个自选高代品系进行分子检测,发现自选品系仅有TaLox-B1b与杂合型两种基因型,其中基因型TaLox-B1ab有32个,比例为60.4％.采用分子标记辅助选择,有利于快速鉴定小麦籽粒LOX活性,加速LOX的遗传改良和新品种选育.

为了丰富高产稳产小麦新品种资源,促进河南小麦生产,2011年,河南科技大学利用系统育种法在洛阳种植的淮麦18群体中选育出科大111,并于2021年通过河南省主要农作物品种审定委员会审定.该品种属于半冬性小麦,冬季抗寒性较强,株型松散适度,茎秆弹性好,抗倒性好,对条锈病抗性表现稳定.2017—2018年和2018—2019年度参加河南省区域试验平均产量为6498.0～8518.5 kg/hm2,比对照品种周麦18增产2.9％～5.1％,增产试验点比例为63.6％～81.8％.2019—2020年度生产试验平均产量为8128.5 kg/hm2,比对照增产4.0％,增产试验点比例为100％.介绍了科大111的选育过程、主要生物学特性、抗性鉴定与品质检测结果以及主要栽培措施.

Abstract Background Lesion-mimic and premature aging (lmpa) mutant lmpa1 was identified from the ethyl methane sulfonate (EMS) mutant library in the bread wheat variety Keda 527 (KD527) background. To reveal the genetic basis of lmpa1 mutant, phenotypic observations and analyses of chlorophyll content and photosynthesis were carried out in lmpa1, KD527 and their F1 and F2 derivatives. Further, bulked segregation analysis (BSA) in combination with a 660 K SNP array were conducted on the F2 segregation population of lmpa1/Chinese spring (CS) to locate the lmpa1 gene. Results Most agronomic traits of lmpa1 were similar to those of KD527 before lesion-like spots appeared. Genetic analysis indicated that the F1 plants from the crossing of lmpa1 and KD527 exhibited the lmpa phenotype and the F2 progenies showed a segregation of normal (wild type, WT) and lmpa, with the ratios of lmpa: WT = 124:36(χ2 = 1.008 < =3.841), indicating that lmpa is a dominant mutation. The combination of BSA and the SNP array analysis of CS, lmpa1 and lmpa1/CS F2 WT pool (50 plants) and lmpa pool (50 plants) showed that polymorphic SNPs were enriched on chromosome 5A, within a region of 30–40 Mb, indicating that the wheat premature aging gene Lmpa1 was probably located on the short arm of chromosome 5A. Conclusions EMS-mutagenized mutant lmpa1 deriving from elite wheat line KD527 conferred lmpa. Lmpa phenotype of lmpa1 mutant is controlled by a single dominant allele designated as Lmpa1, which affected wheat growth and development and reduced the thousand grain weight (tgw) of single plant in wheat. The gene Lmpa1 was tentatively located within the region of 30–40 Mb near to the short arm of chromosome 5A.

Flag leaf traits influence wheat yield by affecting photosynthetic capacity and plant architecture. In this study, flag leaf traits over 4 years in Chinese common wheat were investigated for genome-wide association study (GWAS) analysis using the wheat 90 K SNP array. A total of 618 significant SNPs were identified in 9 environments and 36 of them are significant in at least three environments and BLUP (best linear unbiased prediction). Linkage mapping indicated that 23 QTL regulating flag leaf traits were detected in a bi-parental population with 5.8 to 28.7% phenotypic variation explained, respectively. Further analysis of multi-environmentally significant SNP revealed a candidate geneTaFLL-5B1(TraesCS5B02G390300) related to flag leaf length (FLL). Sequencing results indicated that a 40-bp InDel (insertion/deletion) was identified inTaFLL-5B1gene of different wheat cultivars. Association analysis showed that cultivars withTaFLL-5B1a(with a 40-bp InDel) showed significantly longer FLL than those withTaFLL-5B1b(without a 40-bp InDel). EMS-mutagenized tetraploid wheat line Kronos2282 with premature stop codon ofTaFLL-5B1gene showed significantly shorter FLL than wild type. It suggests thatTaFLL-5B1possibly plays a key role in modulating wheat flag leaf traits. This research increases our understanding of the genetic basis of flag leaf traits and provides genetic loci potentially useful in breeding programs focused on improving wheat architecture and yield.

Using Wheat 90 K SNP assay, kernel-related traits of Chinese bread wheat were used to perform association mapping in 14 environments by GWAS. Results indicated that 996 and 953 of 4417 and 3172 significant SNPs for kernel length and thousand-kernel weight were located on the chromosome 7B. Haplotype analysis of these SNPs on 7B generated the block containing the predicted TaGW8-B1 gene. TaGW8-B1 gene was further cloned by sequencing in bread wheat and a 276-bp InDel was found in the first intron. TaGW8-B1 without and with the 276-bp InDel were designated as TaGW8-B1a and TaGW8-B1b , respectively. Analysis of agronomic traits indicated that cultivars with TaGW8-B1a possessed significantly wider kernel width, significantly more kernel number per spike, longer kernel length, higher thousand-kernel weight and more spikelet number per spike than cultivars with TaGW8-B1b . Furthermore, cultivars with TaGW8-B1a possessed significantly higher yield than cultivars with TaGW8-B1b . Therefore, TaGW8-B1a was considered as a potentially superior allele. Meanwhile, TaGW8-B1a possessed a significantly higher expression level than TaGW8-B1b in mature seeds by qRT-PCR. It possibly suggested that the high expression of TaGW8-B1 was positively associated with kernel size in bread wheat. Distribution of TaGW8-B1 allele indicated that TaGW8-B1a has been positively selected in Chinese wheat.

Heading date is one of the most important traits in wheat breeding as it affects adaptation and yield potential. A genome-wide association study (GWAS) using the 90 K iSelect SNP genotyping assay indicated that a total of 306 loci were significantly associated with heading and flowering dates in 13 environments in Chinese common wheat from the Yellow and Huai wheat region. Of these, 105 loci were significantly correlated with both heading and flowering dates and were found in clusters on chromosomes 2, 5, 6, and 7. Based on differences in distribution of the vernalization and photoperiod genes among chromosomes, arms, or block regions, 13 novel, environmentally stable genetic loci were associated with heading and flowering dates, including RAC875_c41145_189 on 1DS, RAC875_c50422_299 on 2BL, and RAC875_c48703_148 on 2DS, that accounted for more than 20% phenotypic variance explained (PVE) of the heading/flowering date in at least four environments. GWAS and t test of a combination of SNPs and vernalization and photoperiod alleles indicated that the Vrn-B1, Vrn-D1, and Ppd-D1 genes significantly affect heading and flowering dates in Chinese common wheat. Based on the association of heading and flowering dates with the vernalization and photoperiod alleles at seven loci and three significant SNPs, optimal linear regression equations were established, which show that of the seven loci, the Ppd-D1 gene plays the most important role in modulating heading and flowering dates in Chinese wheat, followed by Vrn-B1 and Vrn-D1. Additionally, three novel genetic loci (RAC875_c41145_189, Excalibur_c60164_137, and RAC875_c50422_299) also show important effect on heading and flowering dates. Therefore, Ppd-D1, Vrn-B1, Vrn-D1, and the novel genetic loci should be further investigated in terms of improving heading and flowering dates in Chinese wheat. Further quantitative analysis of an F10 recombinant inbred lines population identified a major QTL that controls heading and flowering dates within the Ppd-D1 locus with PVEs of 28.4% and 34.0%, respectively; this QTL was also significantly associated with spike length, peduncle length, fertile spikelets number, cold resistance, and tiller number.

SummaryBread wheat is a leading cereal crop worldwide. Limited amount of superior allele loci restricted the progress of molecular improvement in wheat breeding. Here, we revealed new allelic variation distribution for 13 yield‐related traits in series of genome‐wide association studies (GWAS) using the wheat 90K genotyping assay, characterized in 163 bread wheat cultivars. Agronomic traits were investigated in 14 environments at three locations over 3 years. After filtering SNP data sets, GWAS using 20 689 high‐quality SNPs associated 1769 significant loci that explained, on average, ~20% of the phenotypic variation, both detected already reported loci and new promising genomic regions. Of these, repetitive and pleiotropic SNPs on chromosomes 6AS, 6AL, 6BS, 5BL and 7AS were significantly linked to thousand kernel weight, for example BS00021705_51 on 6BS and wsnp_Ex_c32624_41252144 on 6AS, with phenotypic variation explained (PVE) of ~24%, consistently identified in 12 and 13 of the 14 environments, respectively. Kernel length‐related SNPs were mainly identified on chromosomes 7BS, 6AS, 5AL and 5BL. Plant height‐related SNPs on chromosomes 4DS, 6DL, 2DS and 1BL were, respectively, identified in more than 11 environments, with averaged PVE of ~55%. Four SNPs were confirmed to be important genetic loci in two RIL populations. Based on repetivity and PVE, a total of 41 SNP loci possibly played the key role in modulating yield‐related traits of the cultivars surveyed. Distribution of superior alleles at the 41 SNP loci indicated that superior alleles were getting popular with time and modern cultivars had integrated many superior alleles, especially for peduncle length‐ and plant height‐related superior alleles. However, there were still 19 SNP loci showing less than percentages of 50% in modern cultivars, suggesting they should be paid more attention to improve yield‐related traits of cultivars in the Yellow and Huai wheat region. This study could provide useful information for dissection of yield‐related traits and valuable genetic loci for marker‐assisted selection in Chinese wheat breeding programme.

Identification of distribution of dwarf genes and their influence on agronomic traits in bread wheat could contribute to reasonable use of dwarf genes and could provid evaluable information for wheat breeding program.Different molecular markers at six Rht loci (Rht1,Rht2,Rht4,Rht8,Rht9 andRht12) were used to detect distribution of dwarf genes in 246 common wheat from the Yellow and Huai wheat region.A total of ten agronomic traits,including plant height,spike length,peduncle length,spikelet number per spike,flag leaf length,flag leaf width,kernel number per spike,kernel length,kernel width and thousand-kernel weight were investigated for three years and their relationship with the Rht loci were analyzed.The results showed that six dwarf genes showed an extensive distribution in the Yellow and Huai wheat region,especially for the Rht1 and Rht2 genes.Association analysis of the six dwarf genes with the ten agronomic traits in bread wheat showed that atRht1locus cultivars with Rht1-B1aand Rht1-B1balleles did not show significant difference for plant height.At Rht2locus,cultivars with Rht2-D1b had significantly lower plant height,peduncle length but higher thousand-kernel weight in the three years,suggesting that Rht2-D1bis the superior allele.Excluding the effect ofRht1 and Rht2genes,due to their strong influence on agronomic traits,the four loci of Rht4,Rht8,Rht9andRht12had also important effects on different agronomic traits in wheat cultivars from the Yellow and Huai valley.Among the four loci,Rht4played an important role in plant height and thousand-kernel weight and thus Rht4-B1bis the relatively superior allele;Rht8had important effects on spike length,peduncle length and thousand-kernel weight and thus Rht8-D1bis the relatively superior allele;Rht9had important effects on plant height and thousand-kernel weight and thus Rht9-A1ais the relatively superior allele;Rht12had important effects on spike length and thousand-kernel weight and thusRht12-A1ais the superior allele.Further analysis showed that Rht2showed the most important effect on plant height among the six loci,which was followed byRht4.Four (Rht1,Rht2,Rht8andRht12) of the six loci showed significant effect on thousand-kernel weight,of whichRht2 also showed the most significant effect.Analysis of the distribution of the six superior alleles in cultivars from different periods indicated percentage of the superior alleles generally increased from early historical cultivars,recent historical cultivars to modern cultivars in the Yellow and Huai valley,and especially 82.9％ of modern cultivars had Rht2-D1b.

In previous work, we cloned TaGS5 gene and found the association of TaGS5-A1 alleles with agronomic traits. In this study, the promoter sequence of the TaGS5-A1 gene was isolated from bread wheat. Sequencing results revealed that a G insertion was found in position -1925 bp of the TaGS5-A1 gene (Reference to ATG), which occurred in the Sp1 domain of the promoter sequence. Combined with previous single nucleotide polymorphism (SNP) in the TaGS5-A1 exon sequence, four genotypes were formed at the TaGS5-A1 locus and were designated as TaGS5-A1a-a, TaGS5-A1a-b, TaGS5-A1b-a, and TaGS5-A1b-b, respectively. Analysis of the association of TaGS5-A1 alleles with agronomic traits indicated that cultivars with the TaGS5-A1a-b allele possessed significantly higher thousand-kernel weight (TKW) and lower plant height than cultivars with the TaGS5-A1a-a allele, and cultivars with the TaGS5-A1b-b allele showed higher TKW than cultivars with the TaGS5-A1b-a allele. The differences of these traits between the TaGS5-A1a-a and TaGS5-A1a-b alleles were larger than those of the TaGS5-A1b-a and TaGS5-A1b-b alleles, suggesting that the -1925G insertion plays the more important role in TaGS5-A1a genotypes than in TaGS5-A1b genotypes. qRT-PCR indicated that TaGS5-A1b-b possessed the significantly highest expression level among four TaGS5-A1 haplotypes in mature seeds and further showed a significantly higher expression level than TaGS5-A1b-a at five different developmental stages of the seeds, suggesting that high expression of TaGS5-A1 was positively associated with high TKW in bread wheat. This study could provide a relatively superior genotype in view of TKW in wheat breeding programs and could also provide important information for dissection of the regulatory mechanism of the yield-related traits.