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Background: Maize requires more water than most other crops; therefore, the water use efficiency of this crop must be improved for maize production under undesirable land and changing environmental conditions. Results: To elucidate the genetic control of drought in maize, we evaluated approximately 5000 inbred lines from 30 linkage-association joint mapping populations under two contrasting water regimes for seven drought-related traits, including yield and anthesis-silking interval (ASI). The joint linkage analysis was conducted to identify 220 quantitative trait loci (QTLs) under well-watered conditions and 169 QTLs under water-stressed conditions. The genome-wide association analysis identified 365 single nucleotide polymorphisms (SNPs) associated with drought-related traits, and these SNPs were located in 354 candidate genes. Fifty-two of these genes showed significant differential expression in the inbred line B73 under the well-watered and water-stressed conditions. In addition, genomic predictions suggested that the moderate-density SNPs obtained through genotyping-by-sequencing were able to make accurate predictions in the nested association mapping population for drought-related traits with moderate-to-high heritability under the water-stressed conditions. Conclusions: The results of the present study provide important information that can be used to understand the genetic basis of drought stress responses and facilitate the use of beneficial alleles for the improvement of drought tolerance in maize. [ABSTRACT FROM AUTHOR]

Background: A genome-wide association study (GWAS) is the foremost strategy used for finding genes that control human diseases and agriculturally important traits, but it often reports false positives. In contrast, its complementary method, linkage analysis, provides direct genetic confirmation, but with limited resolution. A joint approach, using multiple linkage populations, dramatically improves resolution and statistical power. For example, this approach has been used to confirm that many complex traits, such as flowering time controlling adaptation in maize, are controlled by multiple genes with small effects. In addition, genotyping by sequencing (GBS) at low coverage not only produces genotyping errors, but also results in large datasets, making the use of high-throughput sequencing technologies computationally inefficient or unfeasible. Results: In this study, we converted raw SNPs into effective recombination bins. The reduced bins not only retain the original information, but also correct sequencing errors from low-coverage genomic sequencing. To further increase the statistical power and resolution, we merged a new temperate maize nested association mapping (NAM) population derived in China (CN-NAM) with the existing maize NAM population developed in the US (US-NAM). Together, the two populations contain 36 families and 7,000 recombinant inbred lines (RILs). One million SNPs were generated for all the RILs with GBS at low coverage. We developed high-quality recombination maps for each NAM population to correct genotyping errors and improve the computational efficiency of the joint linkage analysis. The original one million SNPs were reduced to 4,932 and 5,296 recombination bins with average interval distances of 0.34 cM and 0.28 cM for CN-NAM and US-NAM, respectively. The quantitative trait locus (QTL) mapping for flowering time (days to tasseling) indicated that the high-density, recombination bin map improved resolution of QTL mapping by 50 % compared with that using a medium-density map. We also demonstrated that combining the CN-NAM and US-NAM populations improves the power to detect QTL by 50 % compared to single NAM population mapping. Among the QTLs mapped by joint usage of the US-NAM and CN-NAM maps, 25 % of the QTLs overlapped with known flowering-time genes in maize. Conclusion: This study provides directions and resources for the research community, especially maize researchers, for future studies using the recombination bin strategy for joint linkage analysis. Available resources include efficient usage of low-coverage genomic sequencing, detailed positions for genes controlling maize flowering, and recombination bin maps and flowering- time data for both CN and US NAMs. Maize researchers even have the opportunity to grow both CN and US NAM populations to study the traits of their interest, as the seeds of both NAM populations are available from the seed repository in China and the US. [ABSTRACT FROM AUTHOR]

Background: Exploring genetic differentiation and genomic variation is important for both the utilization of heterosis and the dissection of the genetic bases of complex traits. Methods: We integrated 1857 diverse maize accessions from America, Africa, Europe and Asia to investigatetheir genetic differentiation, genomic variation using 43,252 high-quality single-nucleotide polymorphisms(SNPs),combing GWAS and linkage analysis strategy to exploring the function of relevant genetic segments. Results: We uncovered many more subpopulations that recently or historically formed during the breeding process. These patterns are represented by the following lines: Mo17, GB, E28, Ye8112, HZS, Shen137, PHG39, B73, 207, A634, Oh43, Reid Yellow Dent, and the Tropical/subtropical (TS) germplasm. A total of 85 highly differentiated regions with a DEST of more than 0.2 were identified between the TS and temperate subpopulations. These regions comprised 79 % of the genetic variation, and most were significantly associated with adaptive traits. For example, the region containing the SNP tag PZE.108075114 was highly differentiated, and this region was significantly associated with flowering time (FT)-related traits, as supported by a genome-wide association study (GWAS) within the interval of FTrelated quantitative trait loci (QTL). This region was also closely linked to zcn8 and vgt1, which were shown to be involved in maize adaptation. Most importantly, 197 highly differentiated regions between different subpopulation pairs were located within an FT- or plant architecture-related QTL. Conclusions: Here we reported that 700-1000 SNPs were necessary needed to robustly estimate the genetic differentiation of a naturally diverse panel. In addition, 13 subpopulations were observed in maize germplasm, 85 genetic regions with higher differentiation between TS and temperate maize germplasm, 197 highly differentiated regions between different subpopulation pairs, which contained some FT-related QTNs/QTLs/genes supported by GWAS and linkage analysis, and these regions were expected to play important roles in maize adaptation. [ABSTRACT FROM AUTHOR]