Comparative transcriptome and coexpression network analysis reveals key pathways and hub candidate genes associated with sunflower (Helianthus annuus L.) drought tolerance.

BACKGROUND: Drought severely limits sunflower production especially at the seedling stage. To investigate the response mechanism of sunflowers to drought stress, we utilized two genotypes of sunflower materials with different drought resistances as test materials. The physiological responses were investigated under well-watered (0 h) and drought-stressed conditions (24 h, 48 h, and 72 h). RESULTS: ANOVA revealed the greatest differences in physiological indices between 72 h of drought stress and 0 h of drought stress. Transcriptome analysis was performed after 72 h of drought stress. At 0 h, there were 7482 and 5627 differentially expressed genes (DEGs) in the leaves of K55 and K58, respectively, and 2150 and 2527 DEGs in the roots of K55 and K58, respectively. A total of 870 transcription factors (TFs) were identified among theDEGs, among which the high-abundance TF families included AP2/ERF, MYB, bHLH,and WRKY. Five modules were screened using weighted gene coexpressionnetwork analysis (WGCNA), three and two of which were positively and negatively, respectively, related to physiological traits. KEGG analysis revealedthat under drought stress, "photosynthesis", "carotenoid biosynthesis", "starch and sucrose metabolism", "ribosome", "carotenoid biosynthesis", "starch and sucrose metabolism", "protein phosphorylation" and "phytohormone signaling" are six important metabolic pathways involved in the response of sunflower to drought stress. Cytoscape software was used to visualize the three key modules, and the hub genes were screened. Finally, a total of 99 important candidate genes that may be associated with the drought response in sunflower plants were obtained, and the homology of these genes was compared with that in Arabidopsis thaliana. CONCLUSIONS: Taken together, our findings could lead to a better understanding of drought tolerance in sunflowers and facilitate the selection of drought-tolerant sunflower varieties.

Analyzing the Diversity of MYB Family Response Strategies to Drought Stress in Different Flax Varieties Based on Transcriptome Data.

The MYB transcription factor family has numerous members, and is involved in biological activities, such as ABA signaling, which plays an important role in a plant's resistance to abiotic stresses such as drought. However, the diversity of MYB members that respond to drought stress and their regulatory mechanisms in different flax varieties were unclear. In this study, we obtained 855.69 Gb of clean data from 120 flax root samples from 20 flax (Linum usitatissimum L.) varieties, assembled 92,861 transcripts, and identified 434 MYB family members in each variety. The expression profiles of the MYB transcription factor family from 20 flax varieties under drought stress were analyzed. The results indicated that there are four strategies by which the MYB family responds to drought stress in these 20 flax varieties, each of which has its own specific processes, such as development, reproduction, and localization processes. The four strategies also include common biological processes, such as stimulus responses, metabolic processes, and biological regulation. The WGCNA method was subsequently employed to identify key members of the MYB family involved in response strategies to drought stress. The results demonstrated that a 1R-MYB subfamily gene co-expression network is significantly related to the gibberellin response and cytokinin-activated signaling pathway processes in the 'Strategy 4' for MYB family response to drought, identifying core genes such as Lus.scaffold70.240. Our results showed a diversity of MYB family responses to drought stress within flax varieties, and these results contribute to deciphering the mechanisms of the MYB family regulation of drought resistance. This will promote the more accurate breeding development of flax to adapt to agricultural production under drought conditions.

Diversity and functional prediction of fungal communities in different segments of mongolian horse gastrointestinal tracts.

BACKGROUND: Anaerobic fungi are effective fibre-degrading microorganisms in the digestive tract of horses. However, our understanding of their diversity and community structure is limited, especially in different parts of the gastrointestinal tract. RESULTS: For the first time, high-throughput sequencing technology was used to analyse and predict fungal microbial diversity in different parts of the gastrointestinal tract of Mongolian horses. The results revealed that the richness and diversity of fungi in the hindgut of Mongolian horses were much higher than those in the foregut. The foregut was dominated by Basidiomycota and Ascomycota, whereas the hindgut was dominated by Neocallimastigomycota and Basidiomycota. At the genus level, the relative abundance of many pathogenic fungi (Cryptococcus, Cladosporium, Alternaria, and Sarocladium) in the foregut was significantly higher than that in the posterior gut, indicating that Mongolian horses have strong disease resistance. The prediction of fungal function also showed significant differences in the fungal flora between the foregut and the hindgut. The fungi in Mongolian horses' foreguts were mainly pathologically nutritive and contained many animal and plant pathogens, particularly in the small intestine (jejunum and ileum). This indicates that the foregut may be the most important immune site in the digestive system of Mongolian horses, which explains the high disease resistance of Mongolian horses. The number of unassigned functional groups in the posterior gut was significantly higher than that in the anterior gut, indicating that the functions of fungal groups in the posterior gut have not been fully explored, and further studies are required in the future. CONCLUSIONS: Analysis of high-throughput sequencing results revealed that the fungal composition varied greatly among different gastrointestinal tract segments in Mongolian horses, whose hindgut contains many anaerobic fungi involved in plant cellulose degradation. This provides important basic data for studying fungal diversity in the digestive system of healthy horses, which can be used for the health assessment of horses and provides clues for further research on the disease resistance and digestive capacity of horses, as well as a reference for the early diagnosis of intestinal diseases and innovative treatment methods.

High-Quality Genome Assembly and Genome-Wide Association Study of Male Sterility Provide Resources for Flax Improvement.

Flax is an economic crop with a long history. It is grown worldwide and is mainly used for edible oil, industry, and textiles. Here, we reported a high-quality genome assembly for "Neiya No. 9", a popular variety widely grown in China. Combining PacBio long reads, Hi-C sequencing, and a genetic map reported previously, a genome assembly of 473.55 Mb was constructed, which covers ~94.7% of the flax genome. These sequences were anchored onto 15 chromosomes. The N50 lengths of the contig and scaffold were 0.91 Mb and 31.72 Mb, respectively. A total of 32,786 protein-coding genes were annotated, and 95.9% of complete BUSCOs were found. Through morphological and cytological observation, the male sterility of flax was considered dominant nuclear sterility. Through GWAS analysis, the gene LUSG00017705 (cysteine synthase gene) was found to be closest to the most significant SNP, and the expression level of this gene was significantly lower in male sterile plants than in fertile plants. Among the significant SNPs identified in the GWAS analysis, only two were located in the coding region, and these two SNPs caused changes in the protein encoded by LUSG00017565 (cysteine protease gene). It was speculated that these two genes may be related to male sterility in flax. This is the first time the molecular mechanism of male sterility in flax has been reported. The high-quality genome assembly and the male sterility genes revealed, provided a solid foundation for flax breeding.

Analysis of QTL mapping for germination and seedling response to drought stress in sunflower (Helianthus annuus L.).

Sunflower is an important oilseed crop across the world. It is considered as a moderately drought tolerant plant, however, its yield is still negatively affected by drought stress. Improving drought tolerance is of the outmost important for breeding. Although several studies have documented the relationship between the sunflower phenotype and genotype under drought stress, but relatively few studies have simultaneously investigated the molecular mechanisms of drought tolerance in the sunflower at different growth stages. In this study, we conducted quantitative trait locus (QTL) analysis for different sunflower traits during the germination and seedling stages. Eighteen phenotypic traits were evaluated under well-watered and drought stress conditions. We determined that the germination rate, germination potential, germination index, and root-to-shoot ratio can be used as effective indexes for drought tolerance selection and breeding. A total of 33 QTLs were identified on eight chromosomes (PVE: 0.016%-10.712% with LOD: 2.017-7.439). Within the confidence interval of the QTL, we identified 60 putative drought-related genes. Four genes located on chromosome 13 may function in both germination and seedling stages for drought response. Genes LOC110898128, LOC110898092, LOC110898071, and LOC110898072 were annotated as aquaporin SIP1-2-like, cytochrome P450 94C1, GABA transporter 1-like, and GABA transporter 1-like isoform X2, respectively. These genes will be used for further functional validation. This study provides insight into the molecular mechanisms of the sunflower's in response to drought stress. At the same time, it lays a foundation for sunflower drought tolerance breeding and genetic improvement.

Chromosome-scale Genome Assembly of the Yellow Nutsedge (Cyperus esculentus).

The yellow nutsedge (Cyperus esculentus L. 1753) is an unconventional oil plant with oil-rich tubers, and a potential alternative for traditional oil crops. Here, we reported the first high-quality and chromosome-level genome assembly of the yellow nutsedge generated by combining PacBio HiFi long reads, Novaseq short reads, and Hi-C data. The final genome size is 225.6 Mb with an N50 of 4.3 Mb. More than 222.9 Mb scaffolds were anchored to 54 pseudochromosomes with a BUSCO score of 96.0%. We identified 76.5 Mb (33.9%) repetitive sequences across the genome. A total of 23,613 protein-coding genes were predicted in this genome, of which 22,847 (96.8%) were functionally annotated. A whole-genome duplication event was found after the divergence of Carex littledalei and Rhynchospora breviuscula, indicating the rich genetic resources of this species for adaptive evolution. Several significantly enriched GO terms were related to invasiveness of the yellow nutsedge, which may explain its plastic adaptability. In addition, several enriched Kyoto Encyclopedia of Genes and Genomes pathways and expanded gene families were closely related with substances in tubers, partially explaining the genomic basis of characteristics of this oil-rich tuber.

Combined GWAS and Transcriptome Analyses Provide New Insights Into the Response Mechanisms of Sunflower Against Drought Stress.

Sunflower is one of the most important oil crops in the world, and drought stress can severely limit its production and quality. To understand the underlying mechanism of drought tolerance, and identify candidate genes for drought tolerance breeding, we conducted a combined genome-wide association studies (GWAS) and RNA-seq analysis. A total of 226 sunflower inbred lines were collected from different regions of China and other countries. Eight phenotypic traits were evaluated under control and drought stress conditions. Genotyping was performed using a Specific-Locus Amplified Fragment Sequencing (SLAF-seq) approach. A total of 934.08 M paired-end reads were generated, with an average Q30 of 91.97%. Based on the 243,291 polymorphic SLAF tags, a total of 94,162 high-quality SNPs were identified. Subsequent analysis of linkage disequilibrium (LD) and population structure in the 226 accessions was carried out based on the 94,162 high-quality SNPs. The average LD decay across the genome was 20 kb. Admixture analysis indicated that the entire population most likely originated from 11 ancestors. GWAS was performed using three methods (MLM, FarmCPU, and BLINK) simultaneously. A total of 80 SNPs showed significant associations with the 8 traits (p < 1.062 × 10-6). Next, a total of 118 candidate genes were found. To obtain more reliable candidate genes, RNA-seq analysis was subsequently performed. An inbred line with the highest drought tolerance was selected according to phenotypic traits. RNA was extracted from leaves at 0, 7, and 14 days of drought treatment. A total of 18,922 differentially expressed genes were obtained. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed up-regulated genes were mainly enriched in the branched-chain amino acid catabolic process, while the down-regulated genes were mainly enriched in the photosynthesis-related process. Six DEGs were randomly selected from all DEGs for validation; these genes showed similar patterns in RNA-seq and RT-qPCR analysis, with a correlation coefficient of 0.8167. Through the integration of the genome-wide association study and the RNA-sequencing, 14 candidate genes were identified. Four of them (LOC110885273, LOC110872899, LOC110891369, LOC110920644) were abscisic acid related protein kinases and transcription factors. These genes may play an important role in sunflower drought response and will be used for further study. Our findings provide new insights into the response mechanisms of sunflowers against drought stress and contribute to further genetic breeding.

Time-course transcriptome and WGCNA analysis revealed the drought response mechanism of two sunflower inbred lines.

Drought is one of the most serious abiotic stress factors limiting crop yields. Although sunflower is considered a moderate drought-tolerant plant, drought stress still has a negative impact on sunflower yield as cultivation expands into arid regions. The extent of drought stress is varieties and time-dependent, however, the molecular response mechanisms of drought tolerance in sunflower with different varieties are still unclear. Here, we performed comparative physiological and transcriptome analyses on two sunflower inbred lines with different drought tolerance at the seedling stage. The analysis of nine physiological and biochemical indicators showed that the leaf surface area, leaf relative water content, and cell membrane integrity of drought tolerance inbred line were higher than those of drought-sensitive inbred line under drought stress, indicating that DT had stronger drought resistance. Transcriptome analyses identified 24,234 differentially expressed genes (DEGs). Gene ontology (GO) analysis showed the up-regulated genes were mainly enriched in gibberellin metabolism and rRNA processing, while the down-regulated genes were mainly enriched in cell-wall, photosynthesis, and terpene metabolism. Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis showed genes related to GABAergic synapse, ribosome biogenesis were up-regulated, while genes related with amino sugar and nucleotide sugar metabolism, starch and sucrose metabolism, photosynthesis were down-regulated. Mapman analysis revealed differences in plant hormone-signaling genes over time and between samples. A total of 1,311 unique putative transcription factors (TFs) were identified from all DEGs by iTAK, among which the high abundance of transcription factor families include bHLH, AP2/ERF, MYB, C2H2, etc. Weighted gene co-expression network analysis (WGCNA) revealed a total of 2,251 genes belonging to two modules(blue 4, lightslateblue), respectively, which were significantly associated with six traits. GO and KEGG enrichment analysis of these genes was performed, followed by visualization with Cytoscape software, and the top 20 Hub genes were screened using the CytoHubba plugin.

ANPrAod: Identify Antioxidant Proteins by Fusing Amino Acid Clustering Strategy and N-Peptide Combination.

Antioxidant proteins perform significant functions in disease control and delaying aging which can prevent free radicals from damaging organisms. Accurate identification of antioxidant proteins has important implications for the development of new drugs and the treatment of related diseases, as they play a critical role in the control or prevention of cancer and aging-related conditions. Since experimental identification techniques are time-consuming and expensive, many computational methods have been proposed to identify antioxidant proteins. Although the accuracy of these methods is acceptable, there are still some challenges. In this study, we developed a computational model called ANPrAod to identify antioxidant proteins based on a support vector machine. In order to eliminate potential redundant features and improve prediction accuracy, 673 amino acid reduction alphabets were calculated by us to find the optimal feature representation scheme. The final model could produce an overall accuracy of 87.53% with the ROC of 0.7266 in five-fold cross-validation, which was better than the existing methods. The results of the independent dataset also demonstrated the excellent robustness and reliability of ANPrAod, which could be a promising tool for antioxidant protein identification and contribute to hypothesis-driven experimental design.

Construction of an SNP-based high-density linkage map for flax (Linum usitatissimum L.) using specific length amplified fragment sequencing (SLAF-seq) technology.

Flax is an important crop for oil and fiber, however, no high-density genetic maps have been reported for this species. Specific length amplified fragment sequencing (SLAF-seq) is a high-resolution strategy for large scale de novo discovery and genotyping of single nucleotide polymorphisms. In this study, SLAF-seq was employed to develop SNP markers in an F2 population to construct a high-density genetic map for flax. In total, 196.29 million paired-end reads were obtained. The average sequencing depth was 25.08 in male parent, 32.17 in the female parent, and 9.64 in each F2 progeny. In total, 389,288 polymorphic SLAFs were detected, from which 260,380 polymorphic SNPs were developed. After filtering, 4,638 SNPs were found suitable for genetic map construction. The final genetic map included 4,145 SNP markers on 15 linkage groups and was 2,632.94 cM in length, with an average distance of 0.64 cM between adjacent markers. To our knowledge, this map is the densest SNP-based genetic map for flax. The SNP markers and genetic map reported in here will serve as a foundation for the fine mapping of quantitative trait loci (QTLs), map-based gene cloning and marker assisted selection (MAS) for flax.