Integrated Analysis of Small RNA, Transcriptome and Degradome Sequencing Provides New Insights into Floral Development and Abscission in Yellow Lupine (Lupinus luteus L.)

Abstract

The floral development in an important legume crop yellow lupine (Lupinus luteus L., Taper cv.) is often affected by the abscission of flowers leading to significant economic losses. Small non-coding RNAs (sncRNAs), which have a proven effect on almost all developmental processes in other plants, might be of key players in a complex net of molecular interactions regulating flower development and abscission. This study represents the first comprehensive sncRNA identification and analysis of small RNA, transcriptome and degradome sequencing data in lupine flowers to elucidate their role in the regulation of lupine generative development. As shedding in lupine primarily concerns flowers formed at the upper part of the inflorescence, we analyzed samples from extreme parts of raceme separately and conducted an additional analysis of pedicels from abscising and non-abscising flowers where abscission zone forms. A total of 394 known and 28 novel miRNAs and 316 phased siRNAs were identified. In flowers at different stages of development 59 miRNAs displayed differential expression (DE) and 46 DE miRNAs were found while comparing the upper and lower flowers. Identified tasiR-ARFs were DE in developing flowers and were strongly expressed in flower pedicels. The DEmiR-targeted genes were preferentially enriched in the functional categories related to carbohydrate metabolism and plant hormone transduction pathways. This study not only contributes to the current understanding of how lupine flowers develop or undergo abscission but also holds potential for research aimed at crop improvement.

LuluDB—The Database Created Based on Small RNA, Transcriptome, and Degradome Sequencing Shows the Wide Landscape of Non-coding and Coding RNA in Yellow Lupine (Lupinus luteus L.) Flowers and Pods

“…The database contains sequences of 456 known and 32 novel miRNAs, as well as 318 phased siRNAs identified in yellow lupine along with information about their expression and target transcripts. In our previous paper (Glazinska et al, 2019) in which part of the data described here supported the evidence that sRNAs are involved in yellow lupine flower development and abscission, each miRNA received a unique ID number on a slightly different principle than it is presented in LuluDB. Namely, known miRNAs [i.e., having identical hits in miRBase (Kozomara et al, 2019)] were assigned IDs from Ll-miR1 to Ll-miR456, and the numbering of novel miRNAs [identified with ShortStack (Axtell, 2013b)] started from the beginning, with the "n" inset before the number (e.g., Ll-miRn22).…”

“…Because the reference yellow lupine genome sequencing is still in progress (Iqbal et al, 2020), the transcripts were assembled de novo. This assembly was carried out separately for libraries derived from flowers (already published in Glazinska et al, 2019) and pods with Trinity toolkit, which assigned an ID for each transcript (e.g., TRINITY_DN10038_c0_g1_i1) within each batch separately. This created the risk that completely FIGURE 1 | Screenshot of LuluDB home page and of the interface to submit BLAST searches.…”

“…Therefore, current research focuses on the development of varieties of yellow lupine and cultivation conditions that would prevent massive flower and pod dropping, consequently stabilizing the yield in various environmental conditions (Lucas et al, 2015). Besides its practical significance, yellow lupine is also an excellent model plant for basic research on nodulation (Frankowski et al, 2015) or abscission of generative organs (Glazinska et al, 2017(Glazinska et al, , 2019.…”

“…Detailed analysis of the data concerning miRNA and siRNA in yellow lupine flowers has been already published (Glazinska et al, 2019), while similar analysis conducted for pods is presented here for the first time. Similarly, data on putative lncRNA in lupine have not been published yet.…”

Integrated Analysis of Small RNA, Transcriptome, and Degradome Sequencing Reveals the Water-Deficit and Heat Stress Response Network in Durum Wheat

“…This could only be achieved with a multi-omics analysis that collectively analyzes datasets of sRNA-seq, mRNA-seq, and degradome-seq at the same time. Previous research has successfully employed such a multi-omics approach in species like rice, maize, and chickpea [ 66 , 67 , 68 , 69 ]. However, it has not been previously undertaken in durum wheat.…”