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Background: This study aims to compare the performance of the recently developed Chinese (city) tariff of the EQ-5D-3L against the UK, US, Japanese and Korean tariffs in a general rural population in China.Methods: From November 2015 to September 2016, 12,085 permanent residents aged 45-69 from 257 villages randomly selected from Hua County, Henan Province, China, were interviewed using EQ-5D-3L, and a one-on-one questionnaire investigation was used to collect data on factors associated with HRQOL. The health utility scores were calculated using the UK, US, Japanese, Korean and Chinese (city) tariffs. The agreement, known-groups validity and sensitivity of these five tariffs were evaluated. Transition scores for pairs of observed EQ-5D-3L health states were calculated and compared.Results: The Korean tariff yielded the highest mean health utility score (0.963), followed by the Chinese (city) (0.948), US (0.943), UK (0.930) and Japanese (0.921) tariffs, but the differences in the scores of any two tariffs did not exceed the MCID. The Chinese (city) tariff showed higher ICC values (ICCs> 0.89, 95% CI:0.755-0.964) and narrower limits of agreement (0.099-0.167) than the Korean tariff [(ICCs> 0.71, 95% CI:0.451-0.955); (0.146-0.253)]. The Chinese (city) tariff had a higher relative efficiency and effect size statistics in 10 out of 11 variables as compared to the UK, US and Japanese tariffs. The Chinese (city) tariff (0.215) was associated with moderate mean absolute transition scores compared with the UK (0.342), US (0.230), Japanese (0.149) and Korean (0.189) tariffs for 1485 observed pairs of the EQ-5D-3L health states.Conclusions: Health utility scores derived from the five tariffs differed. The Chinese (city) tariff was the most suitable of these tariffs and was without obvious weakness. We recommend adopting the Chinese (city) tariff when applying EQ-5D-3L to assess quality of life among the elderly in China's agricultural region with socio-economic status similar to Hua County. Results of this study had provided a crucial basis for health surveys, health promotion projects, health intervention trials, and health economic evaluation taking HRQOL as a target in rural areas of China. [ABSTRACT FROM AUTHOR]

Stripe rust, caused by Puccinia striiformis f. sp. tritici ( Pst), is a serious yield-limiting factor for wheat production worldwide. The objective of this study was to identify and map a stripe rust resistance gene in wheat line Shaannong 104 using SSR markers. F1, F2 and F3 populations from Shaannong 104/Mingxian 169 were inoculated with Chinese Pst race CYR32 in a greenhouse. Shaannong 104 carried a single dominant gene, YrSN104. Six potential polymorphic SSR markers identified in bulk segregant analysis were used to genotype F2 and F3 families. YrSN104 was closely linked with all six SSR markers on chromosome 1BS with genetic distances of 2.0 cM ( Xgwm18, Xgwm273, Xbarc187), 2.6 cM ( Xgwm11, Xbarc137) and 5.9 cM ( Xbarc240). Pedigree analysis, pathogenicity tests using 26 Pst races, haplotyping of associated markers on isogenic lines carrying known stripe rust resistance genes, and associations with markers suggested that YrSN104 was a new resistance gene or an allele at the Yr24/Yr26 locus on chromosome 1BS. Deployment of YrSN104 singly or in combination to elite genotypes could play an effective role to lessen yield losses caused by stripe rust. [ABSTRACT FROM AUTHOR]

Cultivated barley ( Hordeum vulgare L.) is considered as a non-host or inappropriate host species for wheat stripe rust caused by Puccinia striiformis f. sp. tritici. Most barley cultivars show a broad-spectrum resistance to wheat stripe rust. To determine the genes for resistance to wheat stripe rust in barley, a cross was made between a resistant barley line Y12 and a susceptible line Y16. The two parents, F1 and 147 BC1 plants were tested at seedling stage with Chinese prevalent race CYR32 of Puccinia striiformis f. sp. tritici by artificial inoculation in greenhouse. The results indicated that Y12 possessed one dominant resistance gene to wheat stripe rust, designated YrpstY1 provisionally. A total of 388 simple sequence repeat (SSR) markers were used to map the resistance gene in Y12 using bulked segregant analysis. A linkage map, including nine SSR loci on chromosome 7H and YrpstY1, was constructed using the BC1 population, indicating that the resistance gene YrpstY1 is located on chromosome 7H. It is potential to transfer the resistance gene into common wheat for stripe rust resistance. [ABSTRACT FROM AUTHOR]

Cloning and phylogenetic analysis of Psy1 genes in common wheat and its relatives would help to understand the genetic diversity and evolution of Psy1 gene in common wheat and its related species. In the present study, common wheat (AABBDD) and eight relative species, including T. urartu (AuAu), T. boeoticum (AmAm), T. monococcum (AmAm), Ae. speltoides (SS), Ae. tauschii (DD), T. dicoccoides (AABB), T. dicoccum (AABB) and T. spelta (AABBDD), were sampled for the isolation of novel alleles at Psy1?A1, Psy1?B1/Psy1?S1 and Psy1?D1 loci corresponding to common wheat Psy1 genes, and 27 new alleles were identified at these loci, designated Psy1?A1f through Psy1?A1k, Psy1?A1m and Psy1?A1n, Psy1?B1h through Psy1?B1m, Psy1?S1a through Psy1?S1c, Psy1?D1a through Psy1?D1j, respectively. The genes contained six exons and five introns, and the sequences of exons were more conserved compared with those of introns. The Psy1?A1 genes encoded a polypeptide of 428 aminoacid residues, with one residue longer than those encoded by Psy1?D1 genes. The Psy1?B1/Psy1?S1 genes encoded four types of polypeptides, with 421 ( Psy1?B1h through Psy1?B1j, Psy1?B1l), 427 ( Psy1?B1k, Psy1?S1a and Psy1?S1c), 428 ( Psy1?B1m), and 429 ( Psy1?S1b) aminoacid residues, respectively. Neighbor joining tree was generated based on the gene sequences of the 27 novel alleles and those of the 13 alleles reported previously in common wheat and its relatives. The phylogenetic tree consisted of two subtrees. The subtree I comprised 11 of 14 alleles at Psy1?A1 locus, nine of 16 alleles at Psy1?B1/Psy1?S1 locus, and ten novel alleles at Psy1?D1 locus, while the subtree II included the other three alleles at Psy1?A1 locus, the remaining four Psy1?B1 alleles and three Psy1?S1 alleles. The alleles from different clusters showed high sequence divergences, indicated by various SNPs and InDels (insertion/deletion). The phylogenetic relationships of these allelic variants at the three loci in common wheat and its relatives also supported the hypothesis that common wheat was originated by recurrent hexaploidization events. In addition, 193 Chinese wheat cultivars with different yellow pigment contents were genotyped with two novel STS markers YP7D?1 and YP7D?2. The results indicated that 191 cultivars contained the allele Psy1?D1a, and two had Psy1?D1g. [ABSTRACT FROM AUTHOR]

The objectives of this study were to clarify the relationship between LMW-GS Glu-D3 gene of Ae. tauschii registered in GenBank and the six Glu-D3 genes including 12 allelic variants of common wheat characterized in our previous studies, and identify novel Glu-D3 genes and haplotypes from Ae. tauschii using gene specific PCR amplification. By searching the NCBI database, 13 LMW-GS genes/pseudogenes of Ae. tauschii were retrieved and classified into five gene families based on their nucleotide similarity with the six Glu-D3 genes of common wheat. Of them, four Ae. tauschii genes, AY585350, AY585354, AY585355 and AY585356 matched GluD3-4, GluD3-5, GluD3-1 and GluD3-2 of common wheat, respectively, and one pseudogene AY585351 matched to GluD3-6, but none of them matched to GluD3-3. In order to identify the Glu-D3 genes from Ae. tauschii corresponding to GluD3-3 and GluD3-6 of common wheat, gene specific primers were developed to amplify 8-18 Ae. tauschii entries. As a result, two novel Glu-D3 genes, designated as GluDt3-3 and GluDt3-6, were identified. GluDt3-3 showed seven allelic variants or haplotypes at the DNA level in eight Ae. tauschii entries, designated as GluDt3-31, GluDt3-32, GluDt3-33, GluDt3-34, GluDt3-35, GluDt3-36 and GluDt3-37, respectively. Two to eight SNPs were found among the seven haplotypes and 1-4 amino acid substitutions among the deduced peptides. Multiple sequence alignments showed that the DNA similarity was 99.6-99.9% among the seven GluDt3-3 haplotypes, and 99.4-99.7% between these haplotypes and those of common wheat GluD3-3 gene. GluDt3-6 presented seven haplotypes in 18 Ae. tauschii entries, designated as GluDt3-61, GluDt3-62, GluDt3-63, GluDt3-64, GluDt3-65, GluDt3-66 and GluDt3-67, respectively. GluDt3-61 from Ae. tauschii entry Ae38 was the only one haplotype with complete coding sequence, and the other six were all pseudogenes. Compared with GluD3-6 gene of common wheat, GluDt3-61 exhibited a 3-bp insertion, a 42-bp deletion and 11 base substitutions, leading to a glutamine insertion in position 52, 14 amino acid deletion in position 84-97 and 10 amino acid mutations in its deduced peptide; GluDt3-62 and GluDt3-63 showed a 6-bp insertion, a 24-bp deletion and 15-21 base substitutions in coding region, of which a nonsense mutation from C to T at position 622 resulted in pseudogenes; GluDt3-64 had five base substitution, including a nonsense mutation at the position 742. GluDt3-65, GluDt3-66 and GluDt3-67 all had a base deletion at position 247, as well as 7-8 base substitutions, which resulted in frameshift mutations in the three haplotypes. The results indicated that Ae. tauschii also contains six Glu-D3 genes and their allelic variants are even richer than those in common wheat. [ABSTRACT FROM AUTHOR]

Background: Black point is a serious threat to wheat production and can be managed by host resistance. Marker-assisted selection (MAS) has the potential to accelerate genetic improvement of black point resistance in wheat breeding. We performed a genome-wide association study (GWAS) using the high-density wheat 90 K and 660 K single nucleotide polymorphism (SNP) assays to better understand the genetic basis of black point resistance and identify associated molecular markers., Results: Black point reactions were evaluated in 166 elite wheat cultivars in five environments. Twenty-five unique loci were identified on chromosomes 2A, 2B, 3A, 3B (2), 3D, 4B (2), 5A (3), 5B (3), 6A, 6B, 6D, 7A (5), 7B and 7D (2), respectively, explaining phenotypic variation ranging from 7.9 to 18.0%. The highest number of loci was detected in the A genome (11), followed by the B (10) and D (4) genomes. Among these, 13 were identified in two or more environments. Seven loci coincided with known genes or quantitative trait locus (QTL), whereas the other 18 were potentially novel loci. Linear regression showed a clear dependence of black point scores on the number of favorable alleles, suggesting that QTL pyramiding will be an effective approach to increase resistance. In silico analysis of sequences of resistance-associated SNPs identified 6 genes possibly involved in oxidase, signal transduction and stress resistance as candidate genes involved in black point reaction., Conclusion: SNP markers significantly associated with black point resistance and accessions with a larger number of resistance alleles can be used to further enhance black point resistance in breeding. This study provides new insights into the genetic architecture of black point reaction.

Background: Phytoene synthase 1 (PSY1) is the most important regulatory enzyme in carotenoid biosynthesis, whereas its function is hardly known in common wheat. The aims of the present study were to investigate Psy1 function and genetic regulation using reverse genetics approaches., Results: Transcript levels of Psy1 in RNAi transgenic lines were decreased by 54-76 % and yellow pigment content (YPC) was reduced by 26-35 % compared with controls, confirming the impact of Psy1 on carotenoid accumulation. A series of candidate genes involved in secondary metabolic pathways and core metabolic processes responded to Psy1 down-regulation. The aspartate rich domain (DXXXD) was important for PSY1 function, and conserved nucleotides adjacent to the domain influenced YPC by regulating gene expression, enzyme activity or alternative splicing. Compensatory responses analysis indicated that three Psy1 homoeologs may be coordinately regulated under normal conditions, but separately regulated under stress. The period 14 days post anthesis (DPA) was found to be a key regulation node during grain development., Conclusion: The findings define key aspects of flour color regulation in wheat and facilitate the genetic improvement of wheat quality targeting color/nutritional specifications required for specific end products.

Background: Grain size and shape greatly influence grain weight which ultimately enhances grain yield in wheat. Digital imaging (DI) based phenomic characterization can capture the three dimensional variation in grain size and shape than has hitherto been possible. In this study, we report the results from using digital imaging of grain size and shape to understand the relationship among different components of this trait, their contribution to enhance grain weight, and to identify genomic regions (QTLs) controlling grain morphology using genome wide association mapping with high density diversity array technology (DArT) and allele-specific markers., Results: Significant positive correlations were observed between grain weight and grain size measurements such as grain length (r = 0.43), width, thickness (r = 0.64) and factor from density (FFD) (r = 0.69). A total of 231 synthetic hexaploid wheats (SHWs) were grouped into five different sub-clusters by Bayesian structure analysis using unlinked DArT markers. Linkage disequilibrium (LD) decay was observed among DArT loci > 10 cM distance and approximately 28% marker pairs were in significant LD. In total, 197 loci over 60 chromosomal regions and 79 loci over 31 chromosomal regions were associated with grain morphology by genome wide analysis using general linear model (GLM) and mixed linear model (MLM) approaches, respectively. They were mainly distributed on homoeologous group 2, 3, 6 and 7 chromosomes. Twenty eight marker-trait associations (MTAs) on the D genome chromosomes 2D, 3D and 6D may carry novel alleles with potential to enhance grain weight due to the use of untapped wild accessions of Aegilops tauschii. Statistical simulations showed that favorable alleles for thousand kernel weight (TKW), grain length, width and thickness have additive genetic effects. Allelic variations for known genes controlling grain size and weight, viz. TaCwi-2A, TaSus-2B, TaCKX6-3D and TaGw2-6A, were also associated with TKW, grain width and thickness. In silico functional analysis predicted a range of biological functions for 32 DArT loci and receptor like kinase, known to affect plant development, appeared to be common protein family encoded by several loci responsible for grain size and shape., Conclusion: Conclusively, we demonstrated the application and integration of multiple approaches including high throughput phenotyping using DI, genome wide association studies (GWAS) and in silico functional analysis of candidate loci to analyze target traits, and identify candidate genomic regions underlying these traits. These approaches provided great opportunity to understand the breeding value of SHWs for improving grain weight and enhanced our deep understanding on molecular genetics of grain weight in wheat.

Background: Low-molecular-weight glutenin subunits (LMW-GS) strongly influence the bread-making quality of bread wheat. These proteins are encoded by a multi-gene family located at the Glu-A3, Glu-B3 and Glu-D3 loci on the short arms of homoeologous group 1 chromosomes, and show high allelic variation. To characterize the genetic and protein compositions of LMW-GS alleles, we investigated 16 Aroona near-isogenic lines (NILs) using SDS-PAGE, 2D-PAGE and the LMW-GS gene marker system. Moreover, the composition of glutenin macro-polymers, dough properties and pan bread quality parameters were determined for functional analysis of LMW-GS alleles in the NILs., Results: Using the LMW-GS gene marker system, 14-20 LMW-GS genes were identified in individual NILs. At the Glu-A3 locus, two m-type and 2-4 i-type genes were identified and their allelic variants showed high polymorphisms in length and nucleotide sequences. The Glu-A3d allele possessed three active genes, the highest number among Glu-A3 alleles. At the Glu-B3 locus, 2-3 m-type and 1-3 s-type genes were identified from individual NILs. Based on the different compositions of s-type genes, Glu-B3 alleles were divided into two groups, one containing Glu-B3a, B3b, B3f and B3g, and the other comprising Glu-B3c, B3d, B3h and B3i. Eight conserved genes were identified among Glu-D3 alleles, except for Glu-D3f. The protein products of the unique active genes in each NIL were detected using protein electrophoresis. Among Glu-3 alleles, the Glu-A3e genotype without i-type LMW-GS performed worst in almost all quality properties. Glu-B3b, B3g and B3i showed better quality parameters than the other Glu-B3 alleles, whereas the Glu-B3c allele containing s-type genes with low expression levels had an inferior effect on bread-making quality. Due to the conserved genes at Glu-D3 locus, Glu-D3 alleles showed no significant differences in effects on all quality parameters., Conclusions: This work provided new insights into the composition and function of 18 LMW-GS alleles in bread wheat. The variation of i-type genes mainly contributed to the high diversity of Glu-A3 alleles, and the differences among Glu-B3 alleles were mainly derived from the high polymorphism of s-type genes. Among LMW-GS alleles, Glu-A3e and Glu-B3c represented inferior alleles for bread-making quality, whereas Glu-A3d, Glu-B3b, Glu-B3g and Glu-B3i were correlated with superior bread-making quality. Glu-D3 alleles played minor roles in determining quality variation in bread wheat. Thus, LMW-GS alleles not only affect dough extensibility but greatly contribute to the dough resistance, glutenin macro-polymers and bread quality.

Background: Low-molecular-weight glutenin subunits (LMW-GS) play a crucial role in determining end-use quality of common wheat by influencing the viscoelastic properties of dough. Four different methods - sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), two-dimensional gel electrophoresis (2-DE, IEF x SDS-PAGE), matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and polymerase chain reaction (PCR), were used to characterize the LMW-GS composition in 103 cultivars from 12 countries., Results: At the Glu-A3 locus, all seven alleles could be reliably identified by 2-DE and PCR. However, the alleles Glu-A3e and Glu-A3d could not be routinely distinguished from Glu-A3f and Glu-A3g, respectively, based on SDS-PAGE, and the allele Glu-A3a could not be differentiated from Glu-A3c by MALDI-TOF-MS. At the Glu-B3 locus, alleles Glu-B3a, Glu-B3b, Glu-B3c, Glu-B3g, Glu-B3h and Glu-B3j could be clearly identified by all four methods, whereas Glu-B3ab, Glu-B3ac, Glu-B3ad could only be identified by the 2-DE method. At the Glu-D3 locus, allelic identification was problematic for the electrophoresis based methods and PCR. MALDI-TOF-MS has the potential to reliably identify the Glu-D3 alleles., Conclusions: PCR is the simplest, most accurate, lowest cost, and therefore recommended method for identification of Glu-A3 and Glu-B3 alleles in breeding programs. A combination of methods was required to identify certain alleles, and would be especially useful when characterizing new alleles. A standard set of 30 cultivars for use in future studies was chosen to represent all LMW-GS allelic variants in the collection. Among them, Chinese Spring, Opata 85, Seri 82 and Pavon 76 were recommended as a core set for use in SDS-PAGE gels. Glu-D3c and Glu-D3e are the same allele. Two new alleles, namely, Glu-D3m in cultivar Darius, and Glu-D3n in Fengmai 27, were identified by 2-DE. Utilization of the suggested standard cultivar set, seed of which is available from the CIMMYT and INRA Clermont-Ferrand germplasm collections, should also promote information sharing in the identification of individual LMW-GS and thus provide useful information for quality improvement in common wheat.