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Soil salinity severely threatens plant growth and crop performance. Hydrogen sulfide (H2S), a plant signal molecule, has been implicated in the regulation of plant responses to salinity stress. However, it is unclear how the transcriptional network regulates H2S biosynthesis during salt stress response. In this study, we identify a rice NAC (NAM, ATAF and CUC) transcription factor, OsNAC35-like (OsNACL35), from a salt-tolerant cultivar ‘Sea Rice 86′ (SR86) and further show that it may have improved salt tolerance via enhanced H2S production. The expression of OsNACL35 was significantly upregulated by high salinity and hydrogen peroxide (H2O2). The OsNACL35 protein was localized predominantly in the nucleus and was found to have transactivation activity in yeast. The overexpression of OsNACL35 (OsNACL35-OE) in japonica cultivar Nipponbare ramatically increased resistance to salinity stress, whereas its dominant-negative constructs (SUPERMAN repression domain, SRDX) conferred hypersensitivity to salt stress in the transgenic lines at the vegetative stage. Moreover, the quantitative real-time PCR analysis showed that many stress-associated genes were differentially expressed in the OsNACL35-OE and OsNACL35-SRDX lines. Interestingly, the ectopic expression of OsNACL35 triggered a sharp increase in H2S content by upregulating the expression of a H2S biosynthetic gene, OsDCD1, upon salinity stress. Furthermore, the dual luciferase and yeast one-hybrid assays indicated that OsNACL35 directly upregulated the expression of OsDCD1 by binding to the promoter sequence of OsDCD1. Taken together, our observations illustrate that OsNACL35 acts as a positive regulator that links H2S production to salt stress tolerance, which may hold promising utility in breeding salt-tolerant rice cultivar.

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Leaf angle (LA) is a key component of maize plant architecture that can simultaneously govern planting density and improve final yield. However, the genetic mechanisms underlying LA have not been fully addressed. To broaden our understanding of its genetic basis, we scored three LA-related traits on upper, middle, and low leaves of 492 maize inbred lines in five environments. Phenotypic data revealed that the three LA-related traits were normally distributed, and significant variation was observed among environments and genotypes. A genome-wide association study (GWAS) was then performed to dissect the genetic factors that control natural variation in maize LA. In total, 85 significant SNPs (involving 32 non-redundant QTLs) were detected (p ≤ 2.04 × 10–6), and individual QTL explained 4.80%–24.09% of the phenotypic variation. Five co-located QTL were detected in at least two environments, and two QTLs were co-located with multiple LA-related traits. Forty-seven meta-QTLs were identified based on meta-analysis combing 294 LA-related QTLs extracted from 18 previously published studies, 816 genes were identified within these meta-QTLs, and seven co-located QTLs were jointly identified by both GWAS and meta-analysis. ZmULA1 was located in one of the co-located QTLs, qLA7, and its haplotypes, hap1 and hap2, differed significantly in LA-related traits. Interestingly, the temperate materials with hap2 had smallest LA. Finally, we also performed haplotype analysis using the reported genes that regulate LA, and identified a lot of maize germplasms that aggregated favorable haplotypes. These results will be helpful for elucidating the genetic basis of LA and breeding new maize varieties with ideal plant architecture.

Background The chlorophyll content (CC) is a key factor affecting plant photosynthetic efficiency and the final yield. However, its genetic basis remains unclear. The development of statistical methods has enabled researchers to design and apply various GWAS models, including MLM, MLMM, SUPER, FarmCPU, BLINK and 3VmrMLM. Comparative analysis of their results can lead to more effective mining of key genes.Results The heritability of CC was 0.86. Six statistical models (MLM, BLINK, MLMM, FarmCPU, SUPER, and 3VmrMLM) and 1.25 million SNPs were used for the GWAS. A total of 140 quantitative trait nucleotides (QTNs) were detected, with 3VmrMLM and MLM detecting the most (118) and fewest (3) QTNs, respectively. The QTNs were associated with 481 genes and explained 0.29%-10.28% of the phenotypic variation. Additionally, 10 co-located QTNs were detected by at least two different models or methods, three co-located QTNs were identified in at least two different environments, and six co-located QTNs were detected by different models or methods in different environments. Moreover, 69 candidate genes within or near these stable QTNs were screened based on the B73 (RefGen_v2) genome. GRMZM2G110408 (ZmCCS3) was identified by multiple models and in multiple environments. The functional characterization of this gene indicated the encoded protein likely contributes to chlorophyll biosynthesis. In addition, the CC differed significantly between the haplotypes of the significant QTN in this gene, and CC was higher for haplotype 1.Conclusion This study results broaden our understanding of the genetic basis of CC, mining key genes related to CC and may be relevant for the ideotype-based breeding of new maize varieties with high photosynthetic efficiency.