Foxtail millet (Setaria italica) is an important grain crop that is grown in arid regions. Here we sequenced 916 diverse foxtail millet varieties, identified 2.58 million SNPs and used 0.8 million common SNPs to construct a haplotype map of the foxtail millet genome. We classified the foxtail millet varieties into two divergent groups that are strongly correlated with early and late flowering times. We phenotyped the 916 varieties under five different environments and identified 512 loci associated with 47 agronomic traits by genome-wide association studies. We performed a de novo assembly of deeply sequenced genomes of a Setaria viridis accession (the wild progenitor of S. italica) and an S. italica variety and identified complex interspecies and intraspecies variants. We also identified 36 selective sweeps that seem to have occurred during modern breeding. This study provides fundamental resources for genetics research and genetic improvement in foxtail millet.

Foxtail millet (Setaria italica), a very important grain crop in China, has become a new model plant for cereal crops and biofuel grasses. Although its reference genome sequence was released recently, quantitative trait loci (QTLs) controlling complex agronomic traits remains limited. The development of massively parallel genotyping methods and next-generation sequencing technologies provides an excellent opportunity for developing single-nucleotide polymorphisms (SNPs) for linkage map construction and QTL analysis of complex quantitative traits. In this study, a high-throughput and cost-effective RAD-seq approach was employed to generate a high-density genetic map for foxtail millet. A total of 2,668,587 SNP loci were detected according to the reference genome sequence; meanwhile, 9,968 SNP markers were used to genotype 124 F2 progenies derived from the cross between Hongmiaozhangu and Changnong35; a high-density genetic map spanning 1648.8 cM, with an average distance of 0.17 cM between adjacent markers was constructed; 11 major QTLs for eight agronomic traits were identified; five co-dominant DNA markers were developed. These findings will be of value for the identification of candidate genes and marker-assisted selection in foxtail millet.

Fertilization is a key agricultural practice for increasing millet yields and influencing soil properties, enzyme activities and rhizosphere bacterial communities. High throughput Illumina sequencing of the 16S rDNA was applied to compare the bacterial community structures and diversities among six different soil samples. The experiments involved the following: no fertilizer (CK), phosphate (P) and potassium (K) plus organic manure (M) (PKM), nitrogen (N) and K plus M (NKM), NPM, NPK and NPKM fertilization. The results showed that the NPKM fertilization of the millet field had a maximal yield of 3617 kg ha among the six different treatments. The abundances of the Actinobacteria and Bacteroidetes phyla, especially the Devosia, Mycobacterium, Opitutus and Chitinophaga genera, were higher in NPKM than those in the other samples. Redundancy analysis showed that the soil organic matter (SOM), available phosphorus (AP), and urease (UR) activity were significantly correlated with bacterial communities, while SOM and AP were strongly correlated with soil enzyme activities. Pearson's correlation showed that the available nitrogen was strongly correlated with Devosia and Mycobacterium, and SOM was strongly correlated with Opitutus and Chitinophaga. Besides, catalase was significantly related to Iamia, the UR was significantly related to Devosia, phosphatase was significantly related to Luteimonas and Chitinophaga. Based on the soil quality and millet yield, NPKM treatment was a better choice for the millet field fertilization practices. These findings provide a better understanding of the importance of fertilization in influencing millet yield, soil fertility and microbial diversity, and they lead to a choice of scientific fertilization practices for sustainable development of the agroecosystem.

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