BackgroundQuinoa (Chenopodium quinoa Willd.) is a balanced nutritional crop, but its breeding improvement has been limited by the lack of information on its genetics and genomics. Therefore, it is necessary to obtain knowledge on genomic variation, population structure, and genetic diversity and to develop novel Insertion/Deletion (InDel) markers for quinoa by whole-genome re-sequencing.ResultsWe re-sequenced 11 quinoa accessions and obtained a coverage depth between approximately 7× to 23× the quinoa genome. Based on the 1453-megabase (Mb) assembly from the reference accession Riobamba, 8,441,022 filtered bi-allelic single nucleotide polymorphisms (SNPs) and 842,783 filtered InDels were identified, with an estimated SNP and InDel density of 5.81 and 0.58 per kilobase (kb). From the genomic InDel variations, 85 dimorphic InDel markers were newly developed and validated. Together with the 62 simple sequence repeat (SSR) markers reported, a total of 147 markers were used for genotyping the 129 quinoa accessions. Molecular grouping analysis showed classification into two major groups, the Andean highland (composed of the northern and southern highland subgroups) and Chilean coastal, based on combined STRUCTURE, phylogenetic tree and PCA (Principle Component Analysis) analyses. Further analysis of the genetic diversity exhibited a decreasing tendency from the Chilean coast group to the Andean highland group, and the gene flow between subgroups was more frequent than that between the two subgroups and the Chilean coastal group. The majority of the variations (approximately 70%) were found through an analysis of molecular variation (AMOVA) due to the diversity between the groups. This was congruent with the observation of a highly significant FST value (0.705) between the groups, demonstrating significant genetic differentiation between the Andean highland type of quinoa and the Chilean coastal type. Moreover, a core set of 16 quinoa germplasms that capture all 362 alleles was selected using a simulated annealing method.ConclusionsThe large number of SNPs and InDels identified in this study demonstrated that the quinoa genome is enriched with genomic variations. Genetic population structure, genetic core germplasms and dimorphic InDel markers are useful resources for genetic analysis and quinoa breeding.Electronic supplementary materialThe online version of this article (10.1186/s12864-017-4093-8) contains supplementary material, which is available to authorized users.

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Maize exhibits marked growth and yield response to supplemental nitrogen (N). Here, we report the functional characterization of a maize NIN-like protein ZmNLP5 as a central hub in a molecular network associated with N metabolism. Predominantly expressed and accumulated in roots and vascular tissues, ZmNLP5 was shown to rapidly respond to nitrate treatment. Under limited N supply, compared with that of wildtype (WT) seedlings, the zmnlp5 mutant seedlings accumulated less nitrate and nitrite in the root tissues and ammonium in the shoot tissues. The zmnlp5 mutant plants accumulated less nitrogen than the WT plants in the ear leaves and seed kernels. Furthermore, the mutants carrying the transgenic ZmNLP5 cDNA fragment significantly increased the nitrate content in the root tissues compared with that of the zmnlp5 mutants. In the zmnlp5 mutant plants, loss of the ZmNLP5 function led to changes in expression for a significant number of genes involved in N signalling and metabolism. We further show that ZmNLP5 directly regulates the expression of nitrite reductase 1.1 (ZmNIR1.1) by binding to the nitrate-responsive cis-element at the 5 0 UTR of the gene. Interestingly, a natural loss-of-function allele of ZmNLP5 in Mo17 conferred less N accumulation in the ear leaves and seed kernels resembling that of the zmnlp5 mutant plants. Our findings show that ZmNLP5 is involved in mediating the plant response to N in maize.

Fluctuations in nitrogen (N) availability influence protein and starch levels in maize (Zea mays) seeds, yet the underlying mechanism is not well understood. Here, we report that N limitation impacted the expression of many key genes in N and carbon (C) metabolism in the developing endosperm of maize. Notably, the promoter regions of those genes were enriched for P-box sequences, the binding motif of the transcription factor prolamin-box binding factor 1 (PBF1). Loss of PBF1 altered accumulation of starch and proteins in endosperm. Under different N conditions, PBF1 protein levels remained stable but PBF1 bound different sets of target genes, especially genes related to the biosynthesis and accumulation of N and C storage products. Upon N-starvation, the absence of PBF1 from the promoters of some zein genes coincided with their reduced expression, suggesting that PBF1 promotes zein accumulation in the endosperm. In addition, PBF1 repressed the expression of sugary1 (Su1) and starch branching enzyme 2b (Sbe2b) under normal N supply, suggesting that, under N-deficiency, PBF1 redirects the flow of C skeletons for zein toward the formation of C compounds. Overall, our study demonstrates that PBF1 modulates C and N metabolism during endosperm development in an N-dependent manner.

Background: Maize is one of the most important cereal crop all over the world with a complex genome of about 2.3 gigabase, and exhibits tremendous phenotypic and molecular diversity among different germplasms. Along with the phenotype identification, molecular markers have been accepted extensively as an alternative tool to discriminate different genotypes. Results: By using previous re-sequencing data of 205 lines, bi-allelic insertions and deletions (InDels) all over maize genome were screened, and a barcode system was constructed consisting of 37 bi-allelic insertion-deletion markers with high polymorphism information content (PIC) values, large discriminative size among varieties. The barcode system was measured and determined, different maize hybrids and inbreds were clearly discriminated efficiently with these markers, and hybrids responding parents were accurately determined. Compared with microarray data of more than 200 maize lines, the barcode system can discriminate maize varieties with 1.57% of different loci as a threshold. The barcode system can be used in standardized easy and quick operation with very low cost and minimum equipment requirements. Conclusion: A barcode system was constructed for genetic discrimination of maize lines, including 37 InDel markers with high PIC values and user-friendly. The barcode system was measured and determined for efficient identification of maize lines.