BackgroundPlant architecture attributes, such as plant height, ear height, and internode number, have played an important role in the historical increases in grain yield, lodging resistance, and biomass in maize (Zea mays L.). Analyzing the genetic basis of variation in plant architecture using high density QTL mapping will be of benefit for the breeding of maize for many traits. However, the low density of molecular markers in existing genetic maps has limited the efficiency and accuracy of QTL mapping. Genotyping by sequencing (GBS) is an improved strategy for addressing a complex genome via next-generation sequencing technology. GBS has been a powerful tool for SNP discovery and high-density genetic map construction. The creation of ultra-high density genetic maps using large populations of advanced recombinant inbred lines (RILs) is an efficient way to identify QTL for complex agronomic traits.ResultsA set of 314 RILs derived from inbreds Ye478 and Qi319 were generated and subjected to GBS. A total of 137,699,000 reads with an average of 357,376 reads per individual RIL were generated, which is equivalent to approximately 0.07-fold coverage of the maize B73 RefGen_V3 genome for each individual RIL. A high-density genetic map was constructed using 4183 bin markers (100-Kb intervals with no recombination events). The total genetic distance covered by the linkage map was 1545.65 cM and the average distance between adjacent markers was 0.37 cM with a physical distance of about 0.51 Mb. Our results demonstrated a relatively high degree of collinearity between the genetic map and the B73 reference genome. The quality and accuracy of the bin map for QTL detection was verified by the mapping of a known gene, pericarp color 1 (P1), which controls the color of the cob, with a high LOD value of 80.78 on chromosome 1. Using this high-density bin map, 35 QTL affecting plant architecture, including 14 for plant height, 14 for ear height, and seven for internode number were detected across three environments. Interestingly, pQTL10, which influences all three of these traits, was stably detected in three environments on chromosome 10 within an interval of 14.6 Mb. Two MYB transcription factor genes, GRMZM2G325907 and GRMZM2G108892, which might regulate plant cell wall metabolism are the candidate genes for qPH10.ConclusionsHere, an ultra-high density accurate linkage map for a set of maize RILs was constructed using a GBS strategy. This map will facilitate identification of genes and exploration of QTL for plant architecture in maize. It will also be helpful for further research into the mechanisms that control plant architecture while also providing a basis for marker-assisted selection.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2555-z) contains supplementary material, which is available to authorized users.

Background Maize ( Zea mays L.) is one of the main agricultural crops with the largest yield and acreage in the world. However, maize germplasm is very sensitive to low temperatures, mainly during germination, and low temperatures significantly affect plant growth and crop yield. Therefore, the identification of genes capable of increasing tolerance to low temperature has become necessary. Results In this study, fourteen phenotypic traits related to seed germination were used to assess the genetic diversity of maize through genome-wide association study (GWAS). A total of 30 single-nucleotide polymorphisms (SNPs) linked to low-temperature tolerance were detected (−log10( P ) > 4), fourteen candidate genes were found to be directly related to the SNPs, further additional 68 genes were identified when the screen was extended to include a linkage disequilibrium (LD) decay distance of r 2 ≥ 0.2 from the SNPs. RNA-sequencing (RNA-seq) analysis was then used to confirm the linkage between the candidate gene and low-temperature tolerance. A total of ten differentially expressed genes (DEGs) (|log 2 fold change (FC)| ≥ 0.585, P < 0.05) were found within the set distance of LD decay ( r 2 ≥ 0.2). Among these genes, the expression of six DEGs was verified using qRT-PCR. Zm00001d039219 and Zm00001d034319 were putatively involved in ‘mitogen activated protein kinase (MAPK) signal transduction’ and ‘fatty acid metabolic process’, respectively, based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Thus, these genes appeared to be related to low-temperature signal transduction and cell membrane fluidity. Conclusion Overall, by integrating the results of our GWAS and DEG analysis of low-temperature tolerance during germination in maize, we were able to identify a total of 30 SNPs and 82 related candidate genes, including 10 DEGs, two of which were involved in the response to tolerance to low temperature. Functional analysis will provide valuable information for understanding the genetic mechanism of low-temperature tolerance during germination in maize.

Grain moisture in maize at harvest depends on the grain drying rate (GDR) after physiological maturity. The maize plants with high GDR can reduce grain moisture rapidly, which will shorten the drying time after harvest and prevent the grain to be mildew and enhance maize quality. In this study, A total of 280 recombinant inbred lines that were derived from a cross between Ji846 (high drying rate, 1.18 % day -1 ) and Ye3189 (slow drying rate, 0.39 % day -1 ) were used to construct genetic linkage map and identify QTL underlying GDR in different environments. A genetic linkage map was constructed containing 97 SSR and 49 AFLP markers, which covered 2356.8 cM of the maize genome, with an average distance of 16.1 cM. Composite interval mapping identified 14 QTL for GDR after physiological maturity located on chromosomes 2, 3, 5, 6 and 8. The additive effects of QTL were all from Ji846. The range of phenotypic variation explained by the QTL was 5.05-16.28 %. But only two QTL (qKdr-2-1, qKdr-3-6) were identified across both locations. qKdr-2-1 positioned between the markers phi090-umc1560 on chromosome 2 explained 15.59 % of the phenotypic variance, and the other qKdr-3-6 positioned between the markers phi046-bnlg1754 on chromosome 3 explained 10.28 % of the phenotypic variance.

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Rice black-streaked dwarf virus (RBSDV), a Fijivirus, causes maize rough dwarf disease and rice black-streaked dwarf disease in the summer maize-growing regions of the Yellow and Huai rivers, respectively, in China. Nevertheless, the diversification and selection of the entire genome from S1 to S10 have not been illuminated. Molecular variation, evolution, conserved regions, and other genomic properties were analyzed in 21 RBSDV isolates from maize (Zea mays L.) and rice (Oryza sativa) hosts sampled from nine geographic locations in China. Low codon adaptation index values ranging from 0.1878 to 0.2918 indicated a low degree of codon-usage bias and low potential expression for all 13 RBSDV open reading frames (ORFs). ORF9-2 showed a stronger effect of codon usage bias than did other ORFs, as the majority of points for this ORF lay close to the standard curve in the Nc plot (the effective number of codons [Nc] versus the frequency of G+C at synonymous third-base positions [GC3]). A 9-bp deletion mutation was detected in the RBSDV genome in the 3′ UTR of S8. Nucleotide diversity analysis indicated that the structural proteins of RBSDV, such as S2 and S4, were all more conserved than nonstructural proteins such as S9. Nucleotide diversity (π) was highest among S9 sequences (0.0656), and was significantly higher than among S4 sequences (0.0225, P < 0.01). The number of conserved regions among the 10 segments varied substantially. The highest number of conserved regions (5) was found in S5, whereas no conserved regions were identified in S9. Nucleotide diversity and the number of conserved regions were independent of the lengths of segments. Nucleotide diversity was also not correlated with the number of conserved regions in segments. Ten recombination events in 21 isolates were found in seven segments with breakpoint positions in UTRs, intergenic spacer regions, and gene coding regions. The number of recombination events was also independent of the lengths of segments. RBSDV isolates from China could be phylogenetically classified into two groups using either 10 segment sequences or the concatenated sequence of S1 through S10, regardless of host or geographical location. The phylogenetic tree generated from pairwise nucleotide identities of individual RBSDV segments such as S9 and S3, with nucleotide identity values of 93.74% and 95.86%, respectively, is similar to the tree constructed from the concatenated sequences of the entire RBSDV genome. The 13 RBSDV ORFs were under negative and purifying selection (Ka/Ks < 1). ORF5-2 was under the greatest selection pressure; however, ORF2, which encodes the core protein of RBSDV, was under the lowest selection pressure.