Variation in allelic frequencies at loci associated with kernel weight and their effects on kernel weight-related traits in winter wheat

Development and marker-trait relationships of functional markers for glutamine synthetase GS1 and GS2 homoeogenes in bread wheat

GS1 and GS2 genes encode, respectively, the main cytosolic and the plastidic isoforms of glutamine synthetase (GS). In the present study, the wheat GS1 and GS2 homoeogenes located in the A, B and D genome chromosomes have been sequenced in a group of 15 bread wheat varieties including landraces, old commercial varieties and modern cultivars. Phenotypic characterization by multi-environment field trials detected significant effects of specific GS homoeogenes on three of the seven agronomic and grain quality traits analyzed. Based on the gene sequence polymorphisms found, biallelic molecular markers that could facilitate marker-assisted breeding were developed for genes GS1A, GS2A and GS2D. The remaining genes encoding main wheat GS were excluded because of being monomorphic (GS1D) or too polymorphic (GS1B and GS2B) in the sequencing panel varieties. A collection of 187 Spanish bread wheat landraces was genotyped for these gene-based molecular markers. Data analyses conducted with phenotypic records reported for this germplasm collection in López-Fernández et al. (Plants-Basel 10: 620, 2021) have revealed the beneficial influence of some individual alleles on thousand-kernel weight (TKW), kernels per spike (KS) and grain protein content. Furthermore, genetic interactions between GS1A, a cytosolic GS isoform coding gene, and GS2A or GS2D, plastidic GS enzyme coding genes, were found to affect TKW and KS. The finding that some alleles at one locus may mask the effect of positive alleles at hypostatic GS loci should be kept in mind if gene pyramiding strategies are attempted for the improvement of N-use efficiency-related traits.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01354-0.

Genome-wide association study reveals structural chromosome variations with phenotypic effects in wheat (Triticum aestivum L.)

Structural chromosome variations (SCVs) are large-scale genomic variations that can be detected by fluorescence in situ hybridization (FISH). SCVs have played important roles in the genome evolution of wheat (Triticum aestivum L.), but little is known about their genetic effects. In this study, a total of 543 wheat accessions from the Chinese wheat mini-core collection and the Shanxi Province wheat collection were used for chromosome analysis using oligonucleotide probe multiplex FISH. A total of 139 SCVs including translocations, pericentric inversions, presence/absence variations (PAVs), and copy number variations (CNVs) in heterochromatin were identified at 230 loci. The distribution frequency of SCVs varied between ecological regions and between landraces and modern cultivars. Structural analysis using SCVs as markers clearly divided the landraces and modern cultivars into different groups. There are very clear instances illustrating alien introgression and wide application of foreign germplasms improved the chromosome diversity of Chinese modern wheat cultivars. A genome-wide association study (GWAS) identified 29 SCVs associated with 12 phenotypic traits, and five (RT4AS•4AL-1DS/1DL•1DS-4AL, Mg2A-3, Mr3B-10, Mr7B-13, and Mr4A-7) of them were further validated using a doubled haploid population and advanced sib-lines, implying the potential value of these SCVs. Importantly, the number of favored SCVs that were associated with agronomic trait improvement was significantly higher in modern cultivars compared to landraces, indicating positive selection in wheat breeding. This study demonstrates the significant effects of SCVs during wheat breeding and provides an efficient method of mining favored SCVs in wheat and other crops.

Identification of effective alleles and haplotypes conferring pre-harvest sprouting resistance in winter wheat cultivars

BACKGROUND

Pre-harvest sprouting (PHS) is a serious limiting factor for wheat (Triticum aestivum L.) grain yield and end-use quality. Identification of reliable molecular markers and PHS-resistant germplasms is vital to improve PHS resistance by molecular marker-assisted selection (MAS), but the effects of allelic variation and haplotypes in genes conferring PHS resistance in winter wheat cultivars are less understood.

RESULTS

Resistance to PHS was tested in 326 commercial winter wheat cultivars for three consecutive growing seasons from 2018-2020. The effects of alleles and haplotypes of 10 genes associated with PHS resistance were determined for all cultivars and were validated by introgressing the PHS-resistance allele and haplotype into a susceptible wheat cultivar. High level of phenotypic variation in PHS resistance was observed in this set of cultivars and 8 of them were highly resistant to PHS with stable germination index (GI) of less than 25% in each individual year. Allelic effects of nine genes and TaMFT haplotype analysis demonstrated that the haplotype Hap1 with low-GI alleles at five positions had the best PHS resistance. This haplotype has the priority to use in improving PHS resistance because of its high effectiveness and rare present in the current commercial cultivars. Among 14 main allelic combinations (ACs) identified, the AC1 carrying the haplotype Hap1 and the TaSdr-B1a allele had better PHS resistance than the other classes. The introgression of Hap1 and TaSdr-B1a is able to significantly improve the PHS resistance in the susceptible cultivar Lunxuan 13.

CONCLUSIONS

The effectiveness of alleles conferring PHS resistance in winter wheat cultivars was determined and the useful alleles and haplotypes were identified, providing valuable information for parental selection and MAS aiming at improving PHS-resistance in winter wheat. The identification of the PHS-resistant cultivars without known resistance alleles offers an opportunity to explore new PHS-resistant genes.

Genes Impacting Grain Weight and Number in Wheat (Triticum aestivum L. ssp. aestivum)

The primary goal of common wheat (T. aestivum) breeding is increasing yield without negatively impacting the agronomic traits or product quality. Genetic approaches to improve the yield increasingly target genes that impact the grain weight and number. An energetic trade-off exists between the grain weight and grain number, the result of which is that most genes that increase the grain weight also decrease the grain number. QTL associated with grain weight and number have been identified throughout the hexaploid wheat genome, leading to the discovery of numerous genes that impact these traits. Genes that have been shown to impact these traits will be discussed in this review, including TaGNI, TaGW2, TaCKX6, TaGS5, TaDA1, WAPO1, and TaRht1. As more genes impacting the grain weight and number are characterized, the opportunity is increasingly available to improve common wheat agronomic yield by stacking the beneficial alleles. This review provides a synopsis of the genes that impact grain weight and number, and the most beneficial alleles of those genes with respect to increasing the yield in dryland and irrigated conditions. It also provides insight into some of the genetic mechanisms underpinning the trade-off between grain weight and number and their relationship to the source-to-sink pathway. These mechanisms include the plant size, the water soluble carbohydrate levels in plant tissue, the size and number of pericarp cells, the cytokinin and expansin levels in developing reproductive tissue, floral architecture and floral fertility.

Association of the Recessive Allele vrn-D1 With Winter Frost Tolerance in Bread Wheat

Winter frost has been considered the primary limiting factor in wheat production. Shimai 12 is an elite wheat cultivar grown in central and southern Hebei province of China, but sensitive to winter frost. In this study, the winter frost tolerant cultivar Lunxuan 103 was bred by introducing the recessive allele vrn-D1 from winter wheat Shijiazhuang 8 (frost tolerance) into Shimai 12 using marker-assisted selection (MAS). Different from Shimai 12, Lunxuan 103 exhibited a winter growth habit with strong winter frost tolerance. In the Shimai 12 × Shijiazhuang 8 population, the winter progenies (vrn-D1vrn-D1) had significantly lower winter-killed seedling/tiller rates than spring progenies (Vrn-D1aVrn-D1a), and the consistent result was observed in an association population. Winter frost damage caused a significant decrease in grain yield and spike number/m2 in Shimai 12, but not in Lunxuan 103 and Shijiazhuang 8. The time-course expression analysis showed that the transcript accumulation levels of the cold-responsive genes were higher in Lunxuan 103 and Shijiazhuang 8 than in Shimai 12. Lunxuan 103 possessed the same alleles as its parents in the loci for plant height, vernalization, and photoperiod, except for the vernalization gene Vrn-D1. An analysis of genomic composition showed that the two parents contributed similar proportions of genetic compositions to Lunxuan 103. This study provides an example of the improvement of winter frost tolerance by introducing the recessive vernalization gene in bread wheat.

Genetic dissection of grain architecture-related traits in a winter wheat population

BACKGROUND

The future productivity of wheat (T. aestivum L.) as the most grown crop worldwide is of utmost importance for global food security. Thousand kernel weight (TKW) in wheat is closely associated with grain architecture-related traits, e.g. kernel length (KL), kernel width (KW), kernel area (KA), kernel diameter ratio (KDR), and factor form density (FFD). Discovering the genetic architecture of natural variation in these traits, identifying QTL and candidate genes are the main aims of this study. Therefore, grain architecture-related traits in 261 worldwide winter accessions over three field-year experiments were evaluated.

RESULTS

Genome-wide association analysis using 90K SNP array in FarmCPU model revealed several interesting genomic regions including 17 significant SNPs passing false discovery rate threshold and strongly associated with the studied traits. Four of associated SNPs were physically located inside candidate genes within LD interval e.g. BobWhite_c5872_589 (602,710,399 bp) found to be inside TraesCS6A01G383800 (602,699,767-602,711,726 bp). Further analysis reveals the four novel candidate genes potentially involved in more than one grain architecture-related traits with a pleiotropic effects e.g. TraesCS6A01G383800 gene on 6A encoding oxidoreductase activity was associated with TKW and KA. The allelic variation at the associated SNPs showed significant differences betweeen the accessions carying the wild and mutated alleles e.g. accessions carying C allele of BobWhite_c5872_589, TraesCS6A01G383800 had significantly higher TKW than the accessions carying T allele. Interestingly, these genes were highly expressed in the grain-tissues, demonstrating their pivotal role in controlling the grain architecture.

CONCLUSIONS

These results are valuable for identifying regions associated with kernel weight and dimensions and potentially help breeders in improving kernel weight and architecture-related traits in order to increase wheat yield potential and end-use quality.

GridFree: a python package of imageanalysis for interactive grain counting and measuring

Grain characteristics, including kernel length, kernel width, and thousand kernel weight, are critical component traits for grain yield. Manual measurements and counting are expensive, forming the bottleneck for dissecting these traits' genetic architectures toward ultimate yield improvement. High-throughput phenotyping methods have been developed by analyzing images of kernels. However, segmenting kernels from the image background and noise artifacts or from other kernels positioned in close proximity remain as challenges. In this study, we developed a software package, named GridFree, to overcome these challenges. GridFree uses an unsupervised machine learning approach, K-Means, to segment kernels from the background by using principal component analysis on both raw image channels and their color indices. GridFree incorporates users' experiences as a dynamic criterion to set thresholds for a divide-and-combine strategy that effectively segments adjacent kernels. When adjacent multiple kernels are incorrectly segmented as a single object, they form an outlier on the distribution plot of kernel area, length, and width. GridFree uses the dynamic threshold settings for splitting and merging. In addition to counting, GridFree measures kernel length, width, and area with the option of scaling with a reference object. Evaluations against existing software programs demonstrated that GridFree had the smallest error on counting seeds for multiple crop species. GridFree was implemented in Python with a friendly graphical user interface to allow users to easily visualize the outcomes and make decisions, which ultimately eliminates time-consuming and repetitive manual labor. GridFree is freely available at the GridFree website (https://zzlab.net/GridFree).

Predominant wheat-alien chromosome translocations in newly developed wheat of China

Founder wheat lines have played key role in Chinese wheat improvement. Wheat-Dasypyrum villosum translocation T6VS·6AL has been widely used in wheat breeding in recent years due to its high level of powdery mildew resistance and other beneficial genes. Reference oligo-nucleotide multiplex probe (ONMP)-FISH karyotypes of six T6VS·6AL donor lines were developed and used for characterizing 32 derivative cultivars and lines. T6VS·6AL was present in 27 cultivar/lines with 20 from southern China. Next, ONMP-FISH was used to study chromosome constitution of randomly collected wheat cultivars and advanced breeding lines from southern and northern regions of China: 123 lines from the regional test plots of southern China and 110 from northern China. In southern China, T6VS·6AL (35.8%) was the most predominant variation, while T1RS·1BL (27.3%) was the most predominant in northern China. The pericentric inversion perInv 6B derived from its founder wheat Funo and Abbondaza was the second most predominant chromosome variant in both regions. Other chromosome variants were present in very low frequencies. Additionally, 167 polymorphic chromosome types were identified. Based on these variations, 271 cultivars and lines were clustered into three groups, including southern, northern, and mixed groups that contained wheat from both regions. Different dominant chromosome variations were seen, indicating chromosome differentiation in the three groups of wheat. The clearly identified wheat lines with T6VS·6AL in different backgrounds and oligonucleotide probe set will facilitate their utilization in wheat breeding and in identifying other beneficial traits that may be linked to this translocation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01206-3.

Cloning of wheat keto-acyl thiolase 2B reveals a role of jasmonic acid in grain weight determination

Grain weight (GW) is one of the component traits of wheat yield. Existing reports have shown that multiple phytohormones are involved in the regulation of GW in different crops. However, the potential role of jasmonic acid (JA) remains unclear. Here, we report that triticale grain weight 1 (tgw1) mutant, with marked reductions in both GW and JA content, is caused by a premature stop mutation in keto-acyl thiolase 2B (KAT-2B) involved in β-oxidation during JA synthesis. KAT-2B overexpression increases GW in wild type and boosts yield. Additionally, KAT-2B compliments the grain defect in tgw1 and rescues the lethal phenotype of the Arabidopsis kat2 mutant in a sucrose-free medium. Despite the suppression of JA synthesis in tgw1 mutant, ABA synthesis is upregulated, which is accompanied by enhanced expression of SAG3 and reduction of chlorophyll content in leaves. Together, these results demonstrate a role of the JA synthetic gene KAT-2B in controlling GW and its potential application value for wheat improvement.

It has been reported that several phytohormones are involved in the regulation of grain weight, but the role of jasmonic acids (JA) remains elusive. Here, via bulked segregant analysis (BSA)-based cloning, the authors show keto-acyl thiolase 2B involved in β-oxidation during JA synthesis is a positive regulator of wheat grain weight.

Identification of a novel ERF gene, TaERF8, associated with plant height and yield in wheat

BACKGROUND

Ethylene Responsive Factor (ERF) is involved in various processes of plant development and stress responses. In wheat, several ERFs have been identified and their roles in mediating biotic or abiotic stresses have been elucidated. However, their effects on wheat plant architecture and yield-related traits remain poorly studied.

RESULTS

In this study, TaERF8, a new member of the ERF family, was isolated in wheat (Triticum aestivum L.). Three homoeologous TaERF8 genes, TaERF8-2A, TaERF8-2B and TaERF8-2D (named according to sub-genomic origin), were cloned from the common wheat cultivar Chinese Spring. The three homoeologs showed highly similar protein sequences, with identical AP2 domain. Whereas homoeologs sequence polymorphism analysis allowed the establishment of ten, two and three haplotypes, respectively. Expression analysis revealed that TaERF8s were constitutively expressed through entire wheat developmental stages. Analysis of related agronomic traits of TaERF8-2B overexpressing transgenic lines showed that TaERF8-2B plays a role in regulating plant architecture and yield-related traits. Association analysis between TaERF8-2B haplotypes (Hap-2B-1 and Hap-2B-2) and agronomic traits showed that TaERF8-2B was associated with plant height, heading date and 1000 kernel weight (TKW). The TaERF8-2B haplotypes distribution analysis revealed that Hap-2B-2 frequency increased in domesticated emmer wheat and modern varieties, being predominant in five major China wheat producing zones.

CONCLUSION

These results indicated that TaERF8s are differentially involved in the regulation of wheat growth and development. Haplotype Hap-2B-2 was favored during domestication and in Chinese wheat breeding. Unveiling that the here described molecular marker TaERF8-2B-InDel could be used for marker-assisted selection, plant architecture and TKW improvement in wheat breeding.

Genetic architecture underpinning yield component traits in wheat

Genetic atlas, reliable QTL and candidate genes of yield component traits in wheat were figured out, laying concrete foundations for map-based gene cloning and dissection of regulatory mechanisms underlying yield. Mining genetic loci for yield is challenging due to the polygenic nature, large influence of environment and complex relationship among yield component traits (YCT). Many genetic loci related to wheat yield have been identified, but its genetic architecture and key genetic loci for selection are largely unknown. Wheat yield potential can be determined by three YCT, thousand kernel weight, kernel number per spike and spike number. Here, we summarized the genetic loci underpinning YCT from QTL mapping, association analysis and homology-based gene cloning. The major loci determining yield-associated agronomic traits, such as flowering time and plant height, were also included in comparative analyses with those for YCT. We integrated yield-related genetic loci onto chromosomes based on their physical locations. To identify the major stable loci for YCT, 58 QTL-rich clusters (QRC) were defined based on their distribution on chromosomes. Candidate genes in each QRC were predicted according to gene annotation of the wheat reference genome and previous information on validation of those genes in other species. Finally, a technological route was proposed to take full advantage of the resultant resources for gene cloning, molecular marker-assisted breeding and dissection of molecular regulatory mechanisms underlying wheat yield.