Drought is one of the main abiotic stresses that seriously influences cotton production. Many indicators can be used to evaluate cotton drought tolerance, but the key indicators remain to be determined. The objective of this study was to identify effective cotton drought tolerance indicators from 19 indices, including morphology, photosynthesis, physiology, and yield-related indices, and to evaluate the yield potential of 104 cotton varieties under both normal and drought-stress field conditions. Combined with principal component analysis (PCA) and a regression analysis method, the results showed that the top five PCs among the 19, with eigenvalues > 1, contributed 65.52, 63.59, and 65.90% of the total variability during 2016 to 2018, respectively, which included plant height (PH), effective fruit branch number (EFBN), single boll weight (SBW), transpiration rate (Tr) and chlorophyll (Chl). Therefore, the indicator dimension decreased from 19 to 5. A comparison of the 19 indicators with the 5 identified indicators through PCA and a combined regression analysis found that the results of the final cluster of drought tolerance on 104 cotton varieties were basically consistent. The results indicated that these five traits could be used in combination to screen cotton varieties or lines for drought tolerance in cotton breeding programs, and Zhong R2016 and Xin lu zao 45 exhibited high drought tolerance and can be selected as superior parents for good yield performance under drought stress.

A high-density consensus map is a powerful tool for gene mapping, cloning and molecular marker-assisted selection (MAS) 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 (RIL) 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.

Disease resistance is one of the most complicated yet important plant traits. The potential functions of long noncoding RNAs (lncRNAs) in response to pathogenic fungi remain unclear. In this study, we sequenced the transcriptomes of four different sea-island cotton (Gossypium barbadense) recombinant inbred lines (RILs) with susceptible, highly susceptible, highly resistant, or super highly resistant phenotypes and compared their responses to Fusarium oxysporum f. sp. vasinfectum (Fov) infection with those of their susceptible and resistant parents. Infection-induced protein coding genes were highly enriched in similar disease resistance-related pathways regardless of fungal susceptibility. In contrast, we found that the expression of a large number of Fov infection-induced lncRNAs was positively correlated with plant susceptibility. Bioinformatics analysis of potential target mRNAs of lncRNAs with both trans-acting and cis-acting mechanisms showed that mRNAs co-expressed or co-located with Fov-regulated lncRNAs were highly enriched in disease resistance-related pathways, including glutathione metabolism, glycolysis, plant hormone signal transduction, anthocyanin biosynthesis, and butanoate metabolism. Together these results suggest that lncRNAs could play a significant role in the response to pathogenic fungal infection and the establishment of disease resistance. The transcriptional regulation of these infection-susceptible lncRNAs could be coordinated with infection-susceptible mRNAs and integrated into a regulatory network to modulate plant-pathogen interactions and disease resistance. Fov-susceptible lncRNAs represent a novel class of molecular markers for breeding of Fov-resistant cotton cultivars.

Background: Domain of unknown function 668 (DUF668) may play a crucial role in the plant growth and developmental response to adverse stress. However, our knowledge of the function of the DUF668 gene family is limited. Results: Our study was conducted based on the DUF668 gene family identified from cotton genome sequencing. Phylogenetic analysis showed that the DUF668 family genes can be classified into four subgroups in cotton. We identified 32 DUF668 genes, which are distributed on 17 chromosomes and most of them located in the nucleus of Gossypium hirsutum. Gene structure and motif analyses revealed that the members of the DUF668 gene family can be clustered in G. hirsutum into two broad groups, which are relatively evolutionarily conserved. Transcriptome data analysis showed that the GhDUF668 genes are differentially expressed in different tissues under various stresses (cold, heat, drought, salt, and Verticillium dahliae), and expression is generally increased in roots and stems. Promoter and expression analyses indicated that Gh_DUF668–05, Gh_DUF668–08, Gh_DUF668–11, Gh_DUF668–23 and Gh_DUF668–28 in G. hirsutum might have evolved resistance to adverse stress. Additionally, qRT-PCR revealed that these 5 genes in four cotton lines, KK1543 (drought resistant), Xinluzao 26 (drought sensitive), Zhongzhimian 2 (disease resistant) and Simian 3 (susceptible), under drought and Verticillium wilt stress were all significantly induced. Roots had the highest expression of these 5 genes before and after the treatment. Among them, the expression levels of Gh_DUF668–08 and Gh_DUF668–23 increased sharply at 6 h and reached a maximum at 12 h under biotic and abiotic stress, which showed that they might be involved in the process of adverse stress resistance in cotton. Conclusion: The significant changes in GhDUF668 expression in the roots after adverse stress indicate that GhDUF668 is likely to increase plant resistance to stress. This study provides an important theoretical basis for further research on the function of the DUF668 gene family and the molecular mechanism of adverse stress resistance in cotton.

In plant cells, vacuolar H⁺-ATPases (V-ATPases) are responsible for deacidification of the cytosol and energisation of the secondary transport processes across the tonoplast. A number of V-ATPase subunit genes have been demonstrated to be involved in the regulation of the plant response to water deficit. However, there are no reports on the role of V-ATPase subunit A (VHA-A) in dehydration tolerance of cotton. In this study, cotton GhVHA-A gene was functionally characterized, especially with regard to its role in dehydration stress tolerance. Expression analysis showed that GhVHA-A was differentially expressed in various cotton organs and was induced by dehydration, low temperature, high salinity, and abscisic acid treatment in leaves. We also report that GhVHA-A improve dehydration tolerance in transgenic tobacco and cotton. Virus-induced gene silencing of GhVHA-A decreased the tolerance of cotton plantlets to dehydration stress. Silencing GhVHA-A decreased chlorophyll content and antioxidant enzyme activities and increased malondialdehyde (MDA) content in cotton under dehydration stress. However, transgenic tobacco expressing GhVHA-A exhibited enhanced dehydration resistance, resulting in reduced leaf water loss, higher average root length, and lower MDA levels under dehydration stress. Meanwhile, overexpression of GhVHA-A in tobacco conferred water deficit tolerance by enhancing osmotic adjustment (proline) and the activities of the antioxidant enzymes superoxide dismutase and peroxidase, thereby enhancing reactive oxygen species detoxification. These results suggest that GhVHA-A plays an important role in conferring resistance to dehydration stress. Our results have identified GhVHA-A as a candidate gene for improving dehydration tolerance in plants.