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Additional file 2: Table S1. Summary of the 306 worldwide wheat accessions. Table S2. Comparison of the eight plant architecture traits between two environments. Table S3. Detailed information of all significantly associated SNPs for the investigated traits> 5). Table S4. The 330 identified loci associated with investigated traits in this study. Table S5. Overlap between the known genes/QTLs and 330 identified loci in this study. Table S6. XP-CLR scores for the known genes. Table S7. The haplotypes of four major loci for the length of the four internodes in 831 Chinese wheat accessions. Table S8. The phenotypic data for the varieties from the seven continents/regions. Table S9. The phenotypic data of the haplotypes of the four major loci for the length of the four internodes. Table S10. The distribution of haplotypes of the four internodes in 306 worldwide accessions. Table S11. The genotypic data of all the varieties in the first pedigree. Table S12. The genotypic data of all the varieties in the second pedigree. Table S13. The interaction between environments and haplotypes for the length of the four internodes. Table S14. The interaction between environments and haplotypes for the length of the four internodes. Table S15. The 432 wheat varieties used for the analysis of the evolutionary relationship of the haplotypes. Table S16. The haplotype combinations for the length of the four internodes in 306 worldwide wheat accessions. Table S17. The haplotype combinations for the length of the four internodes in 306 worldwide wheat accessions. Table S18. The distribution of haplotype combinations for the length of the four internodes in 831 Chinese wheat accessions. Table S19. The phenotypic data of the four major haplotypes of TraesCS1A02G064800 in 306 worldwide wheat accessions. Table S20. The allele distribution of the SNP used in the RILs in the 306 worldwide wheat accessions. Table S21. The phenotypic data of RILs.

Additional file 3. Review history.

Additional file 2: Table S1. Summary of the 306 worldwide wheat accessions. Table S2. Comparison of the eight plant architecture traits between two environments. Table S3. Detailed information of all significantly associated SNPs for the investigated traits> 5). Table S4. The 330 identified loci associated with investigated traits in this study. Table S5. Overlap between the known genes/QTLs and 330 identified loci in this study. Table S6. XP-CLR scores for the known genes. Table S7. The haplotypes of four major loci for the length of the four internodes in 831 Chinese wheat accessions. Table S8. The phenotypic data for the varieties from the seven continents/regions. Table S9. The phenotypic data of the haplotypes of the four major loci for the length of the four internodes. Table S10. The distribution of haplotypes of the four internodes in 306 worldwide accessions. Table S11. The genotypic data of all the varieties in the first pedigree. Table S12. The genotypic data of all the varieties in the second pedigree. Table S13. The interaction between environments and haplotypes for the length of the four internodes. Table S14. The interaction between environments and haplotypes for the length of the four internodes. Table S15. The 432 wheat varieties used for the analysis of the evolutionary relationship of the haplotypes. Table S16. The haplotype combinations for the length of the four internodes in 306 worldwide wheat accessions. Table S17. The haplotype combinations for the length of the four internodes in 306 worldwide wheat accessions. Table S18. The distribution of haplotype combinations for the length of the four internodes in 831 Chinese wheat accessions. Table S19. The phenotypic data of the four major haplotypes of TraesCS1A02G064800 in 306 worldwide wheat accessions. Table S20. The allele distribution of the SNP used in the RILs in the 306 worldwide wheat accessions. Table S21. The phenotypic data of RILs.

Additional file 3. Review history.

Objective To construct a prediction model for more precise evaluation of prognosis which will allow personalized treatment recommendations for adjuvant therapy in patients following resection of esophageal squamous cell carcinoma (ESCC). Background Marked heterogeneity of patient prognosis and limited evidence regarding survival benefit of various adjuvant therapy regimens pose challenges in the clinical treatment of ESCC. Methods Based on comprehensive clinical data obtained from 4,129 consecutive patients with resected ESCC in a high-risk region in China, we identified predictors for overall survival (OS) through a two-phase selection based on Cox proportional hazard regression and minimization of Akaike information criterion. The model was internally validated using bootstrapping and externally validated in 1,815 patients from a non-high-risk region in China. Results The final model incorporates nine variables: age, sex, primary site, T stage, N stage, number of lymph nodes harvested, tumor size, adjuvant treatment, and hemoglobin level. A significant interaction was also observed between N stage and adjuvant treatment. N1+ stage patients were likely to benefit from addition of adjuvant therapy as opposed to surgery alone, but adjuvant therapy did not improve OS for N0 stage patients. The C-index of the model was 0.729 in the training cohort, 0.723 after bootstrapping, and 0.695 in the external validation cohort. This model outperformed the seventh edition American Joint Committee on Cancer staging system in prognostic prediction and risk stratification. Conclusion The prediction model constructed in this study may facilitate precise prediction of survival and inform decision-making about adjuvant therapy according to N stage.

Plant nitrogen assimilation and use efficiency in the seedling's root system are beneficial for adult plants in field condition for yield enhancement. Identification of the genetic basis between root traits and N uptake plays a crucial role in wheat breeding. In the present study, 198 doubled haploid lines from the cross of Yangmai 16/Zhongmai 895 were used to identify quantitative trait loci (QTLs) underpinning four seedling biomass traits and five root system architecture (RSA) related traits. The plants were grown under hydroponic conditions with control, low and high N treatments (Ca(NO3)2·4H2O at 0, 0.05 and 2.0 mmol L−1, respectively). Significant variations among the treatments and genotypes, and positive correlations between seedling biomass and RSA traits (r=0.20 to 0.98) were observed. Inclusive composite interval mapping based on a high-density map from the Wheat 660K single nucleotide polymorphisms (SNP) array identified 51 QTLs from the three N treatments. Twelve new QTLs detected on chromosomes 1AL (1) in the control, 1DS (2) in high N treatment, 4BL (5) in low and high N treatments, and 7DS (3) and 7DL (1) in low N treatments, are first reported in influencing the root and biomass related traits for N uptake. The most stable QTLs (RRS.caas-4DS) on chromosome 4DS, which were related to ratio of root to shoot dry weight trait, was in close proximity of the Rht-D1 gene, and it showed high phenotypic effects, explaining 13.1% of the phenotypic variance. Twenty-eight QTLs were clustered in 12 genetic regions. SNP markers tightly linked to two important QTLs clusters C10 and C11 on chromosomes 6BL and 7BL were converted to kompetitive allele-specific PCR (KASP) assays that underpin important traits in root development, including root dry weight, root surface area and shoot dry weight. These QTLs, clusters and KASP assays can greatly improve the efficiency of selection for root traits in wheat breeding programmes.

To evaluate the long-term and short-term outcomes of minimally invasive esophagectomy (MIE) compared with open esophagectomy (OE) in localized esophageal squamous cell carcinoma (ESCC) patients in real-world settings.MIE is an alternative to OE, despite the limited evidence regarding its effect on long-term survival.We recruited 5822 consecutive patients with resectable ESCC in two typical high-volume centers in southern and northern China, 1453 of whom underwent MIE. Propensity score-based overlap weighted regression adjusted for multifaceted confounding factors was used to compare outcomes in the MIE and OE groups.Five-year overall survival (OS) was 62.7% in the MIE group and 57.7% in the OE group. The overlap weighted Cox regression showed slightly better OS in the MIE group (HR 0.93, 95% CI: 0.82-1.06). Although duration of surgery was longer and treatment cost higher in the MIE group than in the OE group, the number of lymph nodes harvested was larger, the proportion of intraoperative blood transfusions lower, and postoperative complications less in the MIE group. 30-day (RR 0.77, 0.38-1.55) and 90-day (RR 0.79, 0.46-1.35) mortality were lower in the MIE group versus the OE group, although not statistically significant. These findings were consistent across different analytic approaches and subgroups, notably in the subset of ESCC patients with large tumors.MIE can be performed safely with OS comparable to OE for patients with localized ESCC, indicating MIE may be recommended as the primary surgical approach for resectable ESCC in health facilities with requisite technical capacity.

Fusarium head blight (FHB) resistance of Yangmai wheat cultivars has been paid much attention, but the underlying genetic mechanism is unclear. In recent years, Yangmai 16 is a predominant wheat cultivar durably resistant to FHB in production. A population of 174 double haploid lines (DH) produced by crossing Yangmai 16 (YM16) with the susceptible cultivar Zhongmai 895 (ZM895) was evaluated for FHB response using point inoculation from 2017 to 2019. The DH population was genotyped with wheat 660K SNP array and a high-density genetic map was constructed. Six resistance QTLs were detected, and among them, five were from the resistant parent Yangmai 16 and one from Zhongmai 895. QFhb.yaas-4DS and QFhb.yaas-6AS were detected at least in two years, explaining 8.8% to 15.0% of the phenotypic variances, respectively. QFhb.yaas-2DL and QFhb.yaas-3BL were detected only in one year, accounting for 10.5% and 14.7% of the phenotypic variances. QFhb.yaas-5BL and QFhb.yaas-4BS were detected in one year, too, accounting for 6.4% and 8.3% of the phenotypic variances, respectively. Pyramiding of multiple resistant loci with large effects (>10%) is an effective approach to increase FHB resistance. The QTLs identified from Yangmai 16 in the present study will provide a starting point for genetic studies of other Yangmai cultivars, and the QTLs closely linked to markers will be useful for marker-assisted selection in wheat FHB improvement.

Stem lignin content (SLC) in common wheat (Triticum aestivum L.) contributes to lodging resistance. Caffeic acid 3-O-methyltransferase (COMT) is a key enzyme involved in lignin biosynthesis. Characterization of TaCOMT genes and development of gene-specific markers could enable marker-assisted selection in wheat breeding. In the present study, the full-length genomic DNA (gDNA) sequences of TaCOMT genes located on chromosomes 3A, 3B, and 3D were cloned by homologous cloning. Two allelic variants, TaCOMT-3Ba and TaCOMT-3Bb, were identified and differed by a 222-bp insertion/deletion (InDel) in the 3′-untranslated region (3′-UTR). A co-dominant gene-specific marker based on this InDel was developed and designated as TaCOMT-3BM. A total of 157 wheat cultivars and advanced lines grown in four environments were used to validate the associations between allelic patterns and SLC. The SLC of cultivars with TaCOMT-3Ba was significantly (P

Additional file 1: Supplement Table 1. Definitions and coding forms of risk factors of dyslipidemia investigated in ESECC trial from rural Hua County, China. Supplement Table 2. Selected demographic and behavioral characteristics in three analytical approaches. Supplementary Figure 1. Estimates of association of undernutrition and risk of low HDL-C in pooled analysis and subgroup analysis*. Supplementary Figure 2. Association of undernutrition and dyslipidemia stratified by BMI groups in three analytic approaches*. Supplementary Figure 3. Association of undernutrition and high status of dyslipidemia stratified by gender in three analytic approaches*.

Stripe rust is a serious foliar disease posing a grave threat to wheat production worldwide. The most economical and environmentally friendly way to control this disease is to breed and deploy resistant cultivars. Zhongmai 175 is an elite winter wheat cultivar conferring resistance to a broad spectrum of Puccinia striiformis f. sp. tritici ( Pst ) races. To identify the resistance gene in the cultivar, genetic analysis was conducted using the parents, F 1 , F 2 and F 2:3 populations derived from the cross of Lunxuan 987/Zhongmai 175. Segregations in the F 2 and F 2:3 populations indicated a single dominant gene conferring resistance to stripe rust in Zhongmai 175, temporarily designated YrZM175. Bulked segregant analysis (BSA) with wheat iSelect 90K SNP array determined a preliminary location of YrZM175. Subsequently, YrZM175 was mapped on chromosome 2AS using simple sequence repeats (SSR), expressed sequence tags (EST) and newly-developed kompetitive allele specific PCR (KASP) markers, being flanked by Xgwm636 and Xwmc382 at genetic distances of 4.9 and 8.1 cM, respectively. Comparison of reaction patterns of YrZM175 on 23 Pst races or isolates and pedigree analysis with other genes on chromosome 2AS suggested that it is likely to be a new gene for resistance to stripe rust. The resistance gene and linked molecular markers will be useful in wheat breeding targeting for the improvement of stripe rust resistance.

China and CIMMYT have collaborated on wheat improvement for over 40 years and significant progress has been achieved in five aspects in China. A standardized protocol for testing Chinese noodle quality has been established with three selection criteria, i.e., gluten quality, starch viscosity and flour color are identified as being responsible for noodle quality. Genomic approaches have been used to develop and validate gene-specific markers, leading to the establishment of a KASP platform, and seven cultivars have been released through application of molecular marker technology. Methodology for breeding adult-plant resistance to yellow rust, leaf rust and powdery mildew, based on the pleiotropic effect of minor genes has been established, resulting in release of six cultivars. More than 330 cultivars derived from CIMMYT germplasm have been released and are now grown over 9% of the Chinese wheat production area. Additionally, physiological approaches have been used to characterize yield potential and develop high-efficiency phenotyping platforms. CIMMYT has also provided valuable training for Chinese scientists. Development of climate-resilient cultivars with application of new technology will be the priority for future collaboration.

The Italian wheat cv. Strampelli displays high resistance to powdery mildew caused by Blumeria graminis f. sp. tritici. The objective of this study was to map quantitative trait loci (QTLs) for resistance to powdery mildew in a population of 249 F2:3 lines from Strampelli/Huixianhong. Adult plant powdery mildew tests were conducted over 2 yr in Beijing and 1 yr in Anyang and simple sequence repeat (SSR) markers were used for genotyping. QTLs Qpm.caas-3BS, Qpm.caas-5BL.1, and Qpm.caas-7DS were consistent across environments whereas, Qpm.caas-2BS.1 found in two environments, explained 0.4–1.6, 5.5–6.9, 27.1–34.5, and 1.0–3.5% of the phenotypic variation respectively. Qpm.caas-7DS corresponded to the genomic location of Pm38/Lr34/Yr18. Qpm.caas-4BL was identified in Anyang 2010 and Beijing 2011, accounting for 1.9–3.5% of phenotypic variation. Qpm.caas-2BS.1 and Qpm.caas-5BL.1 contributed by Strampelli and Qpm.caas-3BS by Huixianhong, seem to be new QTL for powdery mildew resistance. Qpm.caas-4BL, Qpm.caas-5BL.3, and Qpm.caas-7DS contributed by Strampelli appeared to be in the same genomic regions as those mapped previously for stripe rust resistance in the same population, indicating that these loci conferred resistance to both stripe rust and powdery mildew. Strampelli could be a valuable genetic resource for improving durable resistance to both powdery mildew and stripe rust in wheat.

ζ(zeta)-carotene desaturase (ZDS) is a key enzyme for carotenoid biosynthesis, demonstrating high association with the yellow pigment (YP) content in wheat grain. Cloning ZDS gene and developing functional markers are important for marker-assisted selection in wheat breeding. In the present study, the full-length DNA sequence of a ZDS gene on wheat chromosome 2A, designated TaZds-A1 , was cloned, with 14 exons and 13 introns, and it has an open reading frame (ORF) of 1 707 bp, encoding 568 amino acid residues. A co-dominant functional marker, YP2A-1, was designed based on the polymorphisms of two alleles at the locus, TaZds-A1a and TaZds-A1b , yielding 183- and 179-bp fragments in TaZds-A1a and TaZds-A1b genotypes, respectively. A new QTL for YP content was detected on chromosome 2A, co-segregating with the functional marker YP2A-1 and TaZds-A1 ; it explained 11.3% of the phenotypic variance for YP content in a doubled haploid (DH) population from Zhongyou 9507/CA9632. Among 217 Chinese wheat cultivars and advanced lines, the average grain YP content of 126 cultivars with TaZds-A1b allele was 7.8% higher than that of 91 cultivars with TaZds-A1a allele.

Information on advances in wheat (Triticum aestivum L.) productivity is essential for genetic improvement on yield potential. Four yield potential trials with totally 59 leading cultivars from Sichuan, Yunnan, Gansu, and Xinjiang, China were conducted using a randomized complete block design with 3 replications under controlled environments in 2 successive cropping seasons from 2007 to 2009. The experimental sites were located in Chengdu in Sichuan, Lijiang in Yunnan, Wuwei in Gansu, and Changji in Xinjiang. Molecular markers were used to detect the presence of dwarfing genes and 1B/1R translocation. The results indicated that the annual genetic gains in yield were 0.73% in Sichuan, 0.34% in Yunnan, 0.58% in Gansu, and 1.43% in Xinjiang. There was no obvious trend of yield component improvement for yield increase in Sichuan; while reduced spikes per square meter and increased kernels per spike were the main factor for yield increase in Yunnan; increased kernels per spike were the main factor for yield increase in Gansu; and increased kernel weight of main spike and harvest index were the main factor for yield increase in Xinjiang, together with the contribution from reduced plant height and earlier maturity. It also indicated that the dwarfing genes Rht-B1b and Rht-D1b were all from International Maize and Wheat Improvement Center (CIMMYT) lines, and the significant progresses of genetic gain in yield in the 4 provinces were mainly due to the direct and indirect use of CIMMYT germplasm. Stripe rust resistance was the main contribution of CIMMYT germplasm in Sichuan and Yunnan; while CIMMYT germplasm contributed to high yield potential with high kernel number per spike, short plant height, and wide adaptability in Xinjiang and Gansu.

Bread-making quality based on dough properties is routinely measured with various equipments to predict quality of wheat cultivar.It is critical to clarify the association between the newly available Mixolab parameters and dough characteristics determined by Farinograph,Extensograph,and bread-making quality.Forty-one breeding lines were used to measure parameters of Mixolab,Farinograph,Extensograph and bread-making quality,and to determine the associations between parameters of Mixolab and Farinograph and Extensograph and the reliability of predicting bread-making quality using these parameters.These results indicated that parameters of Farinograph and Extensograph could be predicted by Mixolab C1(development time),stability,C2(protein weakening during heating) and time C4(time to come setback of starch pasting),accounting for 74-90% of the variation.Mixolab C2 could be used in prediction of loaf volume,bread appearance,structure,and total score,accounting for 52%,73%,70%,and 68% of variation,respectively.For bread texture and elasiticity,the Mixolab stability,C2,parameters of starch pasting properties,such as time C3,C4,C5,and T°C5,were more important parameters.The effects of protein property and starch quality on bread baking quality were explained well with Mixolab parameters,thus,Mixolab was particularly applicable to determine wheat quality property.Because of the different contributions to the evaluations of bread volume,texture,and structure,Mixolab,Farinograph,and Extensograph are suggested to be used according to experimental purposes.

Two sets of common wheat ( Triticum aestivum L.) lines were used in this study, including 23 spring wheat genotypes in Trial I and 21 winter wheat genotypes in Trial II. The size distribution of glutenin polymers was significantly affected by allelic variation and expression quantity of Glu-1 loci based on flour protein content, especially on total expression quantity of high-molecular-weight glutenin subunits (HMW-GS). In Trail I, when the expression of HMW-GS was in a low level, significantly ( P Glu-B1 and Glu-D1 loci on content of SDS-unextractable polymeric protein (UPP) and percent SDS-unextractable polymeric protein in total polymeric protein (%UPP). The contribution of individual glutenin subunit ranked as 7 OE +8* > 7+9 > 17+18 > 7+8 at Glu-B1 and 5+10 > 2+12 at Glu-D1 . The %UPP in genotype with subunit combination of 5+10 was higher than that with subunit combination of 2+12. The quantity of HMW-GS was positively correlated with UPP ( r = 0.79–0.93, P Glu-D1 ( P 2+12 or 4+12 at Glu-D1 . The size distribution of polymers was not significantly different among subunit combinations. The quantity of HMW-GS was positively correlated with UPP ( r = 0.42–0.86, P

The plant hormone abscisic acid (ABA) regulates many important physiological and developmental processes in plants. The objective of this study was to clone the ABA 8′-hydroxylase gene in common wheat. In the present study, we used the cDNA sequence of barley HvCYP707A1 gene (GenBank accession no. AB239299) as a probe for BLAST search against the common wheat (Triticum aestivum L.) EST database in GenBank. All wheat ESTs sharing high similarity with the reference gene were subjected to contig assembly. Primers were designed based on the constructed contigs to clone the wheat CYP707A1 gene, designated as TaCYP707A1. The genomic DNA sequence of TaCYP707A1 gene comprised five exons and four introns, with a size of 2 225 bp. The corresponding cDNA sequence of TaCYP707A1 was 1 737 bp, containing an open reading frame (ORF) of 1 431 bp, a 42-bp 5′-untranslated region (UTR) and a 264-bp 3′UTR, with 94.9% of identical sequences to HvCYP707A1 gene (AB239299). The neighbor joining tree indicated that the deduced amino acid sequences of TaCYP707A1 gene was highly similar to those of barley and rice. The TaCYP707A1 gene was located on chromosome 6BL using a set of Chinese Spring nullisomic-tetrasomic lines and ditelosomic line 6BS. These results will be of high importance in understanding of molecular mechanism of ABA catabolism.

Improvement of end-use quality in bread wheat depends on a thorough understanding of current wheat quality and the influences of genotype (G), environment (E), and genotype by environment interaction (G x E) on quality traits. Thirty-nine spring-sown spring wheat (SSSW) cultivars and advanced lines from China were grown in four agro-ecological zones comprising seven locations during the 1998 and 1999 cropping seasons. Data on 12 major bread-making quality traits were used to investigate the effect of G, E, and G x E on these traits. Wide range variability for protein quantity and quality, starch quality parameters and milling quality in Chinese SSSW was observed. Genotype and environment were found to significantly influence all quality parameters as major effects. Kernel hardness, flour yield, Zeleny sedimentation value and mixograph properties were mainly influenced by the genetic variance components, while thousand kernel weight, test weight, and falling number were mostly influenced by the environmental variance components. Genotype, environment, and their interaction had important effects on test weight, mixing development time and RVA parameters. Cultivars originating from Zone VI (northeast) generally expressed high kernel hardness, good starch quality, but poor milling and medium to weak mixograph performance; those from Zone VII (north) medium to good gluten and starch quality, but low milling quality; those from Zone VIII (central northwest) medium milling and starch quality, and medium to strong mixograph performance; those from Zone IX (western/southwestern Qinghai-Tibetan Plateau) medium milling quality, but poor gluten strength and starch parameters; and those from Zone X (northwest) high milling quality, strong mixograph properties, but low protein content. Samples from Harbin are characterized by good gluten and starch quality, but medium to poor milling quality; those from Hongxinglong by strong mixograph properties, medium to high milling quality, but medium to poor starch quality and medium to low protein content; those from Hohhot by good gluten but poor milling quality; those from Linhe by weak gluten quality, medium to poor milling quality; those from Lanzhou by poor bread-making and starch quality; those from Yongning by acceptable bread-making and starch quality and good milling quality; and those from Urumqi by good milling quality, medium gluten quality and good starch pasting parameters. Our findings suggest that Chinese SSSW quality could be greatly enhanced through genetic improvement for targeted well-characterized production environments.

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a serious wheat fungal disease, causing significant annual yield losses worldwide. The Chinese wheat cultivar Chuanyu 16 has shown good adult-plant resistance (APR) to stripe rust in Sichuan province, a hotspot for stripe rust epidemics. Chuanyu 16 was crossed with Chuanyu 12 and Chuanmai 32. Two populations, each with 140 recombinant inbred lines (RILs), were developed by single-seed descent, and used for quantitative trait locus (QTL) mapping. Field trials were conducted in Chengdu and Yaan from 2005 to 2008, providing stripe rust reaction data for six environments. Seven hundred and thirty one simple sequence repeat (SSR) markers were screened for association with stripe rust reaction, initially through bulked segregant analysis (BSA). Three QTLs for stripe rust resistance derived from Chuanyu 16 were detected in the first cross. They were detected by inclusive composite interval mapping (ICIM) and designated QYr.caas-1BL.1, QYr.caas-1BL.2 and QYr.caas-2AS. They explained 6.0 - 12.8%, 4.5 - 5.8% and 14.9 - 43.0%, respectively, of the phenotypic variance across environments. One digenic epistatic QTL between QYr.caas-1BL.2 and QYr.caas-2AS explained 4.3 - 10.4% of the phenotypic variance. QYr.caas-2AS was also detected in Chuanmai 32/Chuanyu 16, explaining 27.9 - 57.2% of the phenotypic variance across six environments. This QTL showed a major effect against stripe rust in Chuanyu 16, and was located in a similar position to Yr17. Specific markers indicated the presence of a segment from chromosome 2N of Triticum ventricosum that carries Yr17. Despite the lack of evidence for Yr17 in Chuanyu 16 based on pedigree, and inconsistencies in stripe rust response relative to a near-isogenic reference stock with the gene, we concluded that QYr.caas-2AS is Yr17. QYr.caas-1BL.1 and QYr.caas-1BL.2 showed minor effects for APR against stripe rust. QYr.caas-1BL.1 is probably a new gene for APR to stripe rust.

The endosperm storage proteins of 205 Chinese bread wheat cultivars and advanced lines were fractionated by SDS-PAGE to determine their high molecular weight (HMW) glutenin subunit composition. Seventeen alleles were identified: three at Glu-A1, eight at Glu-B1, and six at Glu-D1. The most common alleles were Null, 1, 7+8, 7+9, and 2+12. The results indicate that wheats from different regions differ in their frequencies of HMW glutenin subunits, however, none of the subunits could be related to specific environments. The glutenin quality scores of Chinese wheats ranged from 3 to 10, with an average of 6.7. Increasing quality scores have implications in improving steam-bread making quality for Chinese consumers. On the basis of HMW glutenin subunit composition, Chinese wheats are close to European wheats, especially Italian wheats because several Italian introductions are widely distributed in the pedigrees of Chinese wheat.

Three groups of characters selected using three methods were used to calculate genetic distance among two groups of winter wheat lines using Euclidean distance based on principal components. These wheat lines were then clustered by the unweighted pair-group arithmetic average method. The relationship between genetic distance and standardized potence was seemingly influenced by genetic materials. In order to obtain promising crosses, it is advisable to select parents from intercluster rather than intracluster materials. The results suggested that the repeatability method was better than the conventional and weighting methods for selecting characters for distance analysis.