Real-time quantitative PCR is a technique that can measure the content of the target nucleic acid sequence of interest in a given sample. It is mainly divided into absolute and relative quantitative methods. The relative quantification is mainly used in gene expressions for functional genomic and transcriptome studies. However, to use this technology accurately, there are some key points to master. First, specific primers need to be designed to ensure amplification of the gene of interest (GOI). Second, the appropriate reference gene or reference gene combination has to be selected. Finally, scientific gene expression level calculations and statistics are required to obtain accurate results. Therefore, this work proposes a workflow for relative quantitative PCR and introduces the relevant points so that beginners can better understand and use this technology.

Background: Reducing the dependence of crop production on chemical fertilizer with its associated costs, carbon footprint and other environmental problems is a challenge for agriculture. New solutions are required to solve this problem, and crop breeding for high nitrogen use efficiency or tolerance of low nitrogen availability has been widely considered to be a promising approach. However, the molecular mechanisms of high nitrogen use efficiency or low-nitrogen tolerance in crop plants are still to be elucidated, including the role of long non-coding RNAs (lncRNAs). Results: In this study, we identified 498 lncRNAs in barley (Hordeum vulgare) landrace B968 (Liuzhutouzidamai), of which 487 were novel, and characterised 56 that were responsive to low-nitrogen stress. For functional analysis of differentially-expressed lncRNAs, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment of co-expressed and co-located protein-coding genes were analyzed, and interactions with annotated co-expressed protein coding genes or micro RNAs (miRNAs) were further predicted. Target mimicry prediction between differentially-expressed lncRNAs and miRNAs identified 40 putative target mimics of lncRNAs and 58 target miRNAs. Six differentially-expressed lncRNAs were further validated by qPCR, and one in particular showed consistent differential expression using both techniques. Expression levels of most of the lncRNAs were found to be very low, and this may be the reason for the apparent inconsistency between RNA-seq and qPCR data. Conclusions: The analysis of lncRNAs that are differentially-expressed under low-nitrogen stress, as well as their co-expressed or co-located protein coding genes and target mimics, could elucidate complex and hitherto uncharacterised mechanisms involved in the adaptation to low-nitrogen stress in barley and other crop plants.

In vitro mutagenesis via isolated microspore culture provides an efficient way to produce numerous double haploid (DH) lines with mutation introduction and homozygosity stabilization, which can be used for screening directly. In this study, 356 DH lines were produced from the malt barley (Hordeum vulgare L.) cultivar Hua-30 via microspore mutagenic treatment with ethyl methane sulfonate or pingyangmycin during in vitro culture. The lines were subjected to field screening under high nitrogen (HN) and low nitrogen (LN) conditions, and the number of productive tillers was used as the main screening index. Five mutant lines (A1-28, A1-84, A1-226, A16-11, and A9-29) with high numbers of productive tillers were obtained over three consecutive years of screening. In the fifth year, components related to N-use efficiency (NUE), including N accumulation, utilization, and translocation, were characterized for these lines based on N uptake efficiency (NUpE), N utilization efficiency (NUtE), and N translocation efficiency (NTE). The results show that the NUpE of four mutant lines (A1-84, A1-226, A9-29, and A16-11) improved significantly under HN, whereas that of two lines (A1-84 and A9-29) improved under LN. As a result, their NUE improved greatly. No improvement in NUtE was observed in any of the five mutant lines. A1-84 and A9-29 were selected as an enhanced genotype in N uptake, and A1-28 showed improved NTE at the grain-filling stage. Our results imply that high-NUpE mutants can be produced through microspore mutagenesis and field screening, and that improvement of NUE in barley depends on enhancement of N uptake.

Background: Sucrose nonfermenting-1 (SNF1)-related protein kinases (SnRKs) play important roles in regulating metabolism and stress responses in plants, providing a conduit for crosstalk between metabolic and stress signalling, in some cases involving the stress hormone, abscisic acid (ABA). The burgeoning and divergence of the plant gene family has led to the evolution of three subfamilies,SnRK1,SnRK2andSnRK3, of whichSnRK2andSnRK3are unique to plants. Therefore, the study of SnRKs in crops may lead to the development of strategies for breeding crop varieties that are more resilient under stress conditions. In the present study, we describe theSnRKgene family of barley (Hordeum vulgare), the widespread cultivation of which can be attributed to its good adaptation to different environments.Results: The barleyHvSnRKgene family was elucidated in its entirety from publicly-available genome data and found to comprise 50 genes. Phylogenetic analyses assigned six of the genes to theHvSnRK1subfamily, 10 toHvSnRK2and 34 toHvSnRK3. The search was validated by applying it to Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) genome data, identifying 50SnRKgenes in rice (fourOsSnRK1, 11OsSnRK2and 35OsSnRK3) and 39 in Arabidopsis (threeAtSnRK1, 10AtSnRK2and 26AtSnRK3). Specific motifs were identified in the encoded barley proteins, and multiple putative regulatory elements were found in the gene promoters, with light-regulated elements (LRE), ABA response elements (ABRE) and methyl jasmonate response elements (MeJa) the most common. RNA-seq analysis showed that many of theHvSnRKgenes responded to ABA, some positively, some negatively and some with complex time-dependent responses.Conclusions: The barleyHvSnRKgene family is large, comprising 50 members, subdivided intoHvSnRK1(6 members),HvSnRK2(10 members) andHvSnRK3(34 members), showing differential positive and negative responses to ABA.