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Endophytes, which are widely found in host plants and have no harmful effects, are a vital biological resource. Plant endophytes promote plant growth and enhance plants' resistance to diseases, pests, and environmental stresses. In addition, they enhance the synthesis of important secondary metabolites in plants and improve the potential applicability of plants in agriculture, medicine, food, and horticulture. In this review, we summarize the recent progress in understanding the interaction between endophytes and plants and summarize the construction of synthetic microbial communities (SynComs) and metaomics analysis of the interaction between endophytes and plants. The application and development prospects of endophytes in agriculture, medicine, and other industries are also discussed to provide a reference for further study of the interaction between endophytes and plants and further development and utilization of endophytes. [ABSTRACT FROM AUTHOR]

To screen the genes regulating the biosynthesis of phenolic acid derivatives from the genome of Bletilla striata , we designed a suspension culture system to sample the cells for the following experiments. The contents of four phenolic acid derivatives were determined by high-performance liquid chromatography, and several full-length transcriptome sequencings of RNA samples at 10 time points were performed for bioinformatics analysis. The correlation analysis was used to identify and verify the key DEGs involved in the biosynthesis of the four phenolic acid derivatives. The results showed that the contents of p-hydroxybenzylalcohol (HBA), Dactylorhin A, Militarine, and Coelonin peaked at 33 days postinoculation (Dpi), 18 Dpi, 39 Dpi, and 39 Dpi of the culture system, respectively. Based on transcriptome data, 80 DEGs involved in the biosynthesis of phenolic acid derivatives were obtained. The KEGG pathway enrichment analysis classified them mostly into five metabolic pathways: phenylpropane biosynthesis, starch and sucrose metabolic, cyanoamino acid metabolism, gluconeogenesis and glycolysis, and phenylalanine metabolism. qPCR analysis revealed that the relative gene expression levels were consistent with the overall trend of transcriptome sequencing results. Among them, 14, 18, 23, and 41 unigenes were found to be involved in the synthesis of HBA, Dactylorhin A, Coelonin, and Militarine, respectively. These unigenes laid a solid foundation for elucidating the biosynthesis mechanism of phenolic acid derivatives in suspension cells of B. striata. [ABSTRACT FROM AUTHOR]

Wheat is one of the most important cereal crops worldwide. A consensus map combines genetic information from multiple populations, providing an effective alternative to improve the genome coverage and marker density. In this study, we constructed a consensus map from three populations of recombinant inbred lines (RILs) of wheat using a 90K single nucleotide polymorphism (SNP) array. Phenotypic data on plant height (PH), spike length (SL), and thousand-kernel weight (TKW) was collected in six, four, and four environments in the three populations, and then used for quantitative trait locus (QTL) mapping. The mapping results obtained using the constructed consensus map were compared with previous results obtained using individual maps and previous studies on other populations. A simulation experiment was also conducted to assess the performance of QTL mapping with the consensus map. The constructed consensus map from the three populations spanned 4558.55 cM in length, with 25,667 SNPs, having high collinearity with physical map and individual maps. Based on the consensus map, 21, 27, and 19 stable QTLs were identified for PH, SL, and TKW, much more than those detected with individual maps. Four PH QTLs and six SL QTLs were likely to be novel. A putative gene called TraesCS4D02G076400 encoding gibberellin-regulated protein was identified to be the candidate gene for one major PH QTL located on 4DS, which may enrich genetic resources in wheat semi-dwarfing breeding. The simulation results indicated that the length of the confidence interval and standard errors of the QTLs detected using the consensus map were much smaller than those detected using individual maps. The consensus map constructed in this study provides the underlying genetic information for systematic mapping, comparison, and clustering of QTL, and gene discovery in wheat genetic study. The QTLs detected in this study had stable effects across environments and can be used to improve the wide adaptation of wheat cultivars through marker-assisted breeding. [ABSTRACT FROM AUTHOR]

Background: Bletilla striata has been widely used in the pharmacology industry. To effectively produce the secondary metabolites through suspension cultured cells of B. striata , it is important to exploring the full-length transcriptome data and the genes related to cell growth and chemical producing of all culture stages. We applied a combination of Real-Time Sequencing of Single Molecule (SMRT) and second-generation sequencing (SGS) to generate the complete and full-length transcriptome of B. striata suspension cultured cells. Methods: The B. striata transcriptome was formed in de novo way by using PacBio isoform sequencing (Iso-Seq) on a pooled RNA sample derived from 23 samples of 10 culture stages, to explore the potential for capturing full-length transcript isoforms. All unigenes were obtained after splicing, assembling, and clustering, and corrected by the SGS results. The obtained unigenes were compared with the databases, and the functions were annotated and classified. Results and conclusions: A total of 100,276 high-quality full-length transcripts were obtained, with an average length of 2530 bp and an N50 of 3302 bp. About 52% of total sequences were annotated against the Gene Ontology, 53,316 unigenes were hit by KOG annotations and divided into 26 functional categories, 80,020 unigenes were mapped by KEGG annotations and clustered into 363 pathways. Furthermore, 15,133 long-chain non-coding RNAs (lncRNAs) were detected. And 68,996 coding sequences were identified based on SSR analysis, among which 31 pairs of primers selected at random were amplified and obtained stable bands. In conclusion, our results provide new full-length transcriptome data and genetic resources for identifying growth and metabolism-related genes, which provide a solid foundation for further research on its growth regulation mechanisms and genetic engineering breeding mechanisms of B. striata. [ABSTRACT FROM AUTHOR]

The primary cause of time‐dependent discoloration in wheat (Triticum aestivum L.)‐based products is polyphenol oxidase (PPO) activity. A comprehensive genetic characterization of PPO activity in wheat could expedite the development of wheat varieties with low PPO activity. To dissect the genetic architecture of PPO activity in wheat flour, a panel of 166 diverse bread wheat cultivars was phenotyped in four different environments and genotyped by high‐density wheat 90K and 660K arrays. A genome‐wide association study (GWAS) was performed by a mixed linear model that incorporated population structure and relative kinship. Four hundred and sixty‐five stable marker–trait associations representative of 43 quantitative trait loci (QTL) for PPO activity identified in at least two environments were located on all wheat chromosomes except 5A, with each explaining 6.6–32.4% of the phenotypic variance. Based on IWGSC RefSeq v1.0, we found that QPPO2A.3, QPPO2B.1, QPPO2B.2, and QPPO2D.2 were consistent with the previously reported QTL, and 12 QTL located on homoeologous group 1 chromosomes (6 QTL), chromosomes 4B, 4D, and 7A (2 QTL), and chromosome 7B (2 QTL) are likely to be new PPO loci. Based on physical positions of QTL and previous studies, Ppo‐A1, Ppo‐A2, Ppo‐B2, Ppo‐D2, Pinb‐D1, and genes encoding a Cu ion‐binding protein and a Cu‐transporting ATPase RAN1‐like protein were considered as candidates for QPPO2A.3, QPPO2B.1, QPPO2D.2, QPPO5D.1, QPPO4A.2, and QPPO7D.2, respectively. This study provided insights into the molecular basis of wheat PPO activity, and associated markers can be used for selection of low PPO breeding lines as a means of improving the marketing quality of wheat products. [ABSTRACT FROM AUTHOR]

Water soluble carbohydrates (WSC) in stems play an important role in buffering grain yield in wheat against biotic and abiotic stresses; however, knowledge of genes controlling WSC is very limited. We conducted a genome-wide association study (GWAS) using a high-density 90K SNP array to better understand the genetic basis underlying WSC, and to explore marker-based breeding approaches. WSC was evaluated in an association panel comprising 166 Chinese bread wheat cultivars planted in four environments. Fifty two marker-trait associations (MTAs) distributed across 23 loci were identified for phenotypic best linear unbiased estimates (BLUEs), and 11 MTAs were identified in two or more environments. Liner regression showed a clear dependence of WSC BLUE scores on numbers of favorable (increasing WSC content) and unfavorable alleles (decreasing WSC), indicating that genotypes with higher numbers of favorable or lower numbers of unfavorable alleles had higher WSC content. In silico analysis of flanking sequences of trait-associated SNPs revealed eight candidate genes related to WSC content grouped into two categories based on the type of encoding proteins, namely, defense response proteins and proteins triggered by environmental stresses. The identified SNPs and candidate genes related to WSC provide opportunities for breeding higher WSC wheat cultivars. [ABSTRACT FROM AUTHOR]

Stripe rust is one of the most devastating diseases of wheat (Triticum aestivum) worldwide. Adult-plant resistance (APR) is an efficient approach to provide long-term protection of wheat from the disease. The Chinese winter wheat cultivar Zhong 892 has a moderate level of APR to stripe rust in the field. To determine the inheritance of the APR resistance in this cultivar, 273 F6 recombinant inbred lines (RILs) were developed from a cross between Linmai 2 and Zhong 892. The RILs were evaluated for maximum disease severity (MDS) in two sites during the 2011–2012, 2012–2013 and 2013–2014 cropping seasons, providing data for five environments. Illumina 90k SNP (single nucleotide polymorphism) chips were used to genotype the RILs and their parents. Composite interval mapping (CIM) detected eight QTL, namely QYr.caas-2AL, QYr.caas-2BL.3, QYr.caas-3AS, QYr.caas-3BS, QYr.caas-5DL, QYr.caas-6AL, QYr.caas-7AL and QYr.caas-7DS.1, respectively. All except QYr.caas-2BL.3 resistance alleles were contributed by Zhong 892. QYr.caas-3AS and QYr.caas-3BS conferred stable resistance to stripe rust in all environments, explaining 6.2–17.4% and 5.0–11.5% of the phenotypic variances, respectively. The genome scan of SNP sequences tightly linked to QTL for APR against annotated proteins in wheat and related cereals genomes identified two candidate genes (autophagy-related gene and disease resistance gene RGA1), significantly associated with stripe rust resistance. These QTL and their closely linked SNP markers, in combination with kompetitive allele specific PCR (KASP) technology, are potentially useful for improving stripe rust resistances in wheat breeding. [ABSTRACT FROM AUTHOR]

Endophytes is a kind of microorganism resource with great potential medicinal value. The interactions between endophytes and host not only promote the growth and development of each other but also drive the biosynthesis of many new medicinal active substances. In this review, we summarized recent reports related to the interactions between endophytes and hosts, mainly regarding the research progress of endophytes affecting the growth and development of host plants, physiological stress and the synthesis of new compounds. Then, we also discussed the positive effects of multiomics analysis on the interactions between endophytes and their hosts, as well as the application and development prospects of metabolites synthesized by symbiotic interactions. This review may provide a reference for the further development and utilization of endophytes and the study of their interactions with their hosts., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Li, Wen, Qin, He, Xu and Li.)

Flour color-related traits, including brightness (L * ), redness (a * ), yellowness (b * ) and yellow pigment content (YPC), are very important for end-use quality of wheat. Uncovering the genetic architecture of these traits is necessary for improving wheat quality by marker-assisted selection (MAS). In the present study, a genome-wide association study (GWAS) was performed on a collection of 166 bread wheat cultivars to better understand the genetic architecture of flour color-related traits using the wheat 90 and 660 K SNP arrays, and 10 allele-specific markers for known genes influencing these traits. Fifteen, 28, 25, and 32 marker-trait associations (MTAs) for L * , a * , b * , and YPC, respectively, were detected, explaining 6.5-20.9% phenotypic variation. Seventy-eight loci were consistent across all four environments. Compared with previous studies, Psy-A1, Psy-B1, Pinb-D1 , and the 1B•1R translocation controlling flour color-related traits were confirmed, and four loci were novel. Two and 11 loci explained much more phenotypic variation of a * and YPC than phytoene synthase 1 gene ( Psy1 ), respectively. Sixteen candidate genes were predicted based on biochemical information and bioinformatics analyses, mainly related to carotenoid biosynthesis and degradation, terpenoid backbone biosynthesis and glycolysis/gluconeogenesis. The results largely enrich our knowledge of the genetic basis of flour color-related traits in bread wheat and provide valuable markers for wheat quality improvement. The study also indicated that GWAS was a powerful strategy for dissecting flour color-related traits and identifying candidate genes based on diverse genotypes and high-throughput SNP arrays.

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.

A high-density consensus map is a powerful tool for gene mapping, cloning and molecular marker-assisted selection in wheat breeding. The objective of this study was to construct a high-density, single nucleotide polymorphism (SNP)-based consensus map of common wheat ( Triticum aestivum L.) by integrating genetic maps from four recombinant inbred line populations. The populations were each genotyped using the wheat 90K Infinium iSelect SNP assay. A total of 29,692 SNP markers were mapped on 21 linkage groups corresponding to 21 hexaploid wheat chromosomes, covering 2,906.86 cM, with an overall marker density of 10.21 markers/cM. Compared with the previous maps based on the wheat 90K SNP chip detected 22,736 (76.6%) of the SNPs with consistent chromosomal locations, whereas 1,974 (6.7%) showed different chromosomal locations, and 4,982 (16.8%) were newly mapped. Alignment of the present consensus map and the wheat expressed sequence tags (ESTs) Chromosome Bin Map enabled assignment of 1,221 SNP markers to specific chromosome bins and 819 ESTs were integrated into the consensus map. The marker orders of the consensus map were validated based on physical positions on the wheat genome with Spearman rank correlation coefficients ranging from 0.69 (4D) to 0.97 (1A, 4B, 5B, and 6A), and were also confirmed by comparison with genetic position on the previously 40K SNP consensus map with Spearman rank correlation coefficients ranging from 0.84 (6D) to 0.99 (6A). Chromosomal rearrangements reported previously were confirmed in the present consensus map and new putative rearrangements were identified. In addition, an integrated consensus map was developed through the combination of five published maps with ours, containing 52,607 molecular markers. The consensus map described here provided a high-density SNP marker map and a reliable order of SNPs, representing a step forward in mapping and validation of chromosomal locations of SNPs on the wheat 90K array. Moreover, it can be used as a reference for quantitative trait loci (QTL) mapping to facilitate exploitation of genes and QTL in wheat breeding.

Height is an important trait related to plant architecture and yield potential in bread wheat ( Triticum aestivum L.). We previously identified a major quantitative trait locus QPH.caas-6A flanked by simple sequence repeat markers Xbarc103 and Xwmc256 that reduced height by 8.0-10.4%. Here QPH.caas-6A , designated as Rht24 , was confirmed using recombinant inbred lines (RILs) derived from a Jingdong 8/Aikang 58 cross. The target sequences of Xbarc103 and Xwmc256 were used as queries to BLAST against International Wheat Genome Sequence Consortium database and hit a super scaffold of approximately 208 Mb. Based on gene annotation of the scaffold, three gene-specific markers were developed to genotype the RILs, and Rht24 was narrowed to a 1.85 cM interval between TaAP2 and TaFAR . In addition, three single nucleotide polymorphism (SNP) markers linked to Rht24 were identified from SNP chip-based screening in combination with bulked segregant analysis. The allelic efficacy of Rht24 was validated in 242 elite wheat varieties using TaAP2 and TaFAR markers. These showed a significant association between genotypes and plant height. Rht24 reduced plant height by an average of 6.0-7.9 cm across environments and were significantly associated with an increased TGW of 2.0-3.4 g. The findings indicate that Rht24 is a common dwarfing gene in wheat breeding, and TaAP2 and TaFAR can be used for marker-assisted selection.

Dough rheological and starch pasting properties play an important role in determining processing quality in bread wheat (Triticum aestivum L.). In the present study, a recombinant inbred line (RIL) population derived from a Gaocheng 8901/Zhoumai 16 cross grown in three environments was used to identify quantitative trait loci (QTLs) for dough rheological and starch pasting properties evaluated by Mixograph, Rapid Visco-Analyzer (RVA), and Mixolab parameters using the wheat 90 and 660 K single nucleotide polymorphism (SNP) chip assays. A high-density linkage map constructed with 46,961 polymorphic SNP markers from the wheat 90 and 660 K SNP assays spanned a total length of 4121 cM, with an average chromosome length of 196.2 cM and marker density of 0.09 cM/marker; 6596 new SNP markers were anchored to the bread wheat linkage map, with 1046 and 5550 markers from the 90 and 660 K SNP assays, respectively. Composite interval mapping identified 119 additive QTLs on 20 chromosomes except 4D; among them, 15 accounted for more than 10% of the phenotypic variation across two or three environments. Twelve QTLs for Mixograph parameters, 17 for RVA parameters and 55 for Mixolab parameters were new. Eleven QTL clusters were identified. The closely linked SNP markers can be used in marker-assisted wheat breeding in combination with the Kompetitive Allele Specific PCR (KASP) technique for improvement of processing quality in bread wheat.

Identification of genes for yield components, plant height (PH), and yield-related physiological traits and tightly linked molecular markers is of great importance in marker-assisted selection (MAS) in wheat breeding. In the present study, 246 F8 RILs derived from the cross of Zhou 8425B/Chinese Spring were genotyped using the high-density Illumina iSelect 90K single nucleotide polymorphism (SNP) assay. Field trials were conducted at Zhengzhou and Zhoukou of Henan Province, during the 2012-2013 and 2013-2014 cropping season under irrigated conditions, providing data for four environments. Analysis of variance (ANOVA) of agronomic and physiological traits revealed significant differences (P < 0.01) among RILs, environments, and RILs × environments interactions. Broad-sense heritabilities of all traits including thousand kernel weight (TKW), PH, spike length (SL), kernel number per spike (KNS), spike number/m(2) (SN), normalized difference in vegetation index at anthesis (NDVI-A) and at 10 days post-anthesis (NDVI-10), SPAD value of chlorophyll content at anthesis (Chl-A) and at 10 days post-anthesis (Chl-10) ranged between 0.65 and 0.94. A linkage map spanning 3609.4 cM was constructed using 5636 polymorphic SNP markers, with an average chromosome length of 171.9 cM and marker density of 0.64 cM/marker. A total of 866 SNP markers were newly mapped to the hexaploid wheat linkage map. Eighty-six QTL for yield components, PH, and yield-related physiological traits were detected on 18 chromosomes except 1D, 5D, and 6D, explaining 2.3-33.2% of the phenotypic variance. Ten stable QTL were identified across four environments, viz. QTKW.caas-6A.1, QTKW.caas-7AL, QKNS.caas-4AL, QSN.caas-1AL.1, QPH.caas-4BS.2, QPH.caas-4DS.1, QSL.caas-4AS, QSL.caas-4AL.1, QChl-A.caas-5AL, and QChl-10.caas-5BL. Meanwhile, 10 QTL-rich regions were found on chromosome 1BS, 2AL (2), 3AL, 4AL (2), 4BS, 4DS, 5BL, and 7AL exhibiting pleiotropic effects. These QTL or QTL clusters are tightly linked to SNP markers, with genetic distances to the closest SNPs ranging from 0 to 1.5 cM, and could serve as target regions for fine mapping, candidate gene discovery, and MAS in wheat breeding.