Integration of mRNA and miRNA analysis reveals the molecular mechanisms of sugar beet (Beta vulgaris L.) response to salt stress.

The continuous increase of saline-alkali areas worldwide has led to the emergence of saline-alkali conditions, which are the primary abiotic stress or hindering the growth of plants. Beet is among the main sources of sugar, and its yield and sugar content are notably affected by saline-alkali stress. Despite sugar beet being known as a salt-tolerant crop, there are few studies on the mechanisms underlying its salt tolerance, and previous studies have mainly delineated the crop's response to stress induced by NaCl. Recently, advancements in miRNA-mRNA network analysis have led to an increased understanding of how plants, including sugar beet, respond to stress. In this study, seedlings of beet variety "N98122" were grown in the laboratory using hydroponics culture and were exposed to salt stress at 40 days of growth. According to the phenotypic adaptation of the seedlings' leaves from a state of turgidity to wilting and then back to turgidity before and after exposure, 18 different time points were selected to collect samples for analysis. Subsequently, based on the data of real-time quantitative PCR (qRT-PCR) of salt-responsive genes, the samples collected at the 0, 2.5, 7.5, and 16 h time points were subjected to further analysis with experimental materials. Next, mRNA-seq data led to the identification of 8455 differentially expressed mRNAs (DEMs) under exposure to salt stress. In addition, miRNA-seq based investigation retrieved 3558 miRNAs under exposure to salt stress, encompassing 887 known miRNAs belonging to 783 families and 2,671 novel miRNAs. With the integrated analysis of miRNA-mRNA network, 57 miRNA-target gene pairs were obtained, consisting of 55 DEMIs and 57 DEMs. Afterwards, we determined the pivotal involvement of aldh2b7, thic, and δ-oat genes in the response of sugar beet to the effect of salt stress. Subsequently, we identified the miRNAs novel-m035-5p and novel-m0365-5p regulating the aldh gene and miRNA novel-m0979-3p regulating the thic gene. The findings of miRNA and mRNA expression were validated by qRT-PCR.

Association analysis of agronomic traits and construction of genetic networks by resequencing of 306 sugar beet (Beta vulgaris L.) lines.

Due to the relatively brief domestication history of sugar beet (Beta vulgaris ssp. vulgaris), our understanding of the genomic diversity and functional genes in its cultivars is limited, resulting in slow breeding progress. To address this issue, a total of 306 germplasm materials of major cultivars and breeding lines from China, the USA, and Europe were selected for genome resequencing. We investigated population structure and genetic diversity and performed selective scanning of genomic regions, identifying six novel genes associated with important agronomic traits: the candidate genes DFAX2 and P5CS for skin roughness; the candidate genes FRO5, GL24, and PPR91 for root yield and sugar yield, and the pleiotropic candidate gene POLX for flourishing growth vigour, plant height, crown size, flesh coarseness, and sugar yield. In addition, we constructed a protein-protein interaction network map and a phenotype-gene network map, which provide valuable information for identifying and characterizing functional genes affecting agronomic traits in sugar beet. Overall, our study sheds light on the future improvement of sugar beet agronomic traits at the molecular level.

Genomic and transcriptomic-based analysis of agronomic traits in sugar beet (Beta vulgaris L.) pure line IMA1.

Sugar beet (Beta vulgaris L.) is an important sugar-producing and energy crop worldwide. The sugar beet pure line IMA1 independently bred by Chinese scientists is a standard diploid parent material that is widely used in hybrid-breeding programs. In this study, a high-quality, chromosome-level genome assembly for IMA1was conducted, and 99.1% of genome sequences were assigned to nine chromosomes. A total of 35,003 protein-coding genes were annotated, with 91.56% functionally annotated by public databases. Compared with previously released sugar beet assemblies, the new genome was larger with at least 1.6 times larger N50 size, thereby substantially improving the completeness and continuity of the sugar beet genome. A Genome-Wide Association Studies analysis identified 10 disease-resistance genes associated with three important beet diseases and five genes associated with sugar yield per hectare, which could be key targets to improve sugar productivity. Nine highly expressed genes associated with pollen fertility of sugar beet were also identified. The results of this study provide valuable information to identify and dissect functional genes affecting sugar beet agronomic traits, which can increase sugar beet production and help screen for excellent sugar beet breeding materials. In addition, information is provided that can precisely incorporate biotechnology tools into breeding efforts.