cis-Regulatory variation affecting gene expression contributes to the improvement of maize kernel size.

cis-Regulatory variations contribute to trait evolution and adaptation during crop domestication and improvement. As the most important harvested organ in maize (Zea mays L.), kernel size has undergone intensive selection for size. However, the associations between maize kernel size and cis-regulatory variations remain unclear. We chose two independent association populations to dissect the genetic architecture of maize kernel size together with transcriptomic and genotypic data. The resulting phenotypes reflected a strong influence of population structure on kernel size. Compared with genome-wide association studies (GWASs), which accounted for population structure and relatedness, GWAS based on a naïve or simple linear model revealed additional associated single-nucleotide polymorphisms significantly involved in the conserved pathways controlling seed size in plants. Regulation analyses through expression quantitative trait locus mapping revealed that cis-regulatory variations likely control kernel size by fine-tuning the expression of proximal genes, among which ZmKL1 (GRMZM2G098305) was transgenically validated. We also proved that the pyramiding of the favorable cis-regulatory variations has contributed to the improvement of maize kernel size. Collectively, our results demonstrate that cis-regulatory variations, together with their regulatory genes, provide excellent targets for future maize improvement.

Fine mapping qKRN5.04 provides a functional gene negatively regulating maize kernel row number.

KEY MESSAGE: Zm00001d016075 was identified by fine mapping qKRN5.04. The function of Zm00001d016075, negatively modulating maize (Zea Mays L.) kernel row number (KRN), was verified by CRISPR-Cas9. InDel308 located in the promoter of Zm00001d016075 has potential for use as a molecular marker to identify KRN in maize breeding. Kernel row number (KRN), controlled by multiple quantitative trait loci (QTLs), is one of the most important traits that relate to maize production and domestication. Here, fine mapping was conducted to study a major QTL, qKRN5.04, to a 65-kb genomic region using a progeny test strategy in an advanced backcross population, in which Nong531 (N531) and the inbred line of Silunuo (SLN) were employed as the recurrent and the donor parent, respectively. Within this region, there was only one gene (Zm00001d016075) based on the B73 reference genome. Furthermore, we performed regional association mapping using a panel of 236 diverse inbred lines and observed that all significant SNPs were located within Zm00001d016075. The expression of Zm00001d016075 was significantly higher in N531 and qKRN5.04N531 than qKRN5.04SLN, resulting from the different promoter activity of Zm00001d016075. Sequence analysis revealed that InDel308, located in the promoter of Zm00001d016075, was related to the KRN variation in different maize inbred lines. Using the CRISPR-Cas9 strategy, we determined Zm00001d016075 played a role in negatively regulating KRN and had a moderate effect on 10-kernel width, 100-kernel weight, kernels per ear, and grain yield per ear. These results provide critical insights on the genetic basis and quantitative variation for KRN.

Genome-Wide Identification and Analysis of the NF-Y Transcription Factor Family Reveal Its Potential Roles in Salt Stress in Alfalfa (Medicago sativa L.).

Nuclear factor Y (NF-Y) is a heterotrimeric transcription factor that plays an important role in various biological processes in plants, such as flowering regulation, drought resistance, and salt stress. However, few in-depth studies investigated the alfalfa NF-Y gene family. In this study, in total, 60 MsNF-Y genes, including 9 MsNF-YAs, 26 MsNF-YBs, and 25 MsNF-YCs, were identified in the alfalfa genome. The genomic locations, gene structures, protein molecular weights, conserved domains, phylogenetic relationships, and gene expression patterns in different tissues and under different stresses (cold stress, drought stress, and salt stress) of these NF-Y genes were analyzed. The illustration of the conserved domains and specific domains of the different subfamilies of the MsNF-Y genes implicates the conservation and diversity of their functions in alfalfa growth, development, and stress resistance. The gene expression analysis showed that 48 MsNF-Y genes (7 MsNF-YAs, 22 MsNF-YBs, and 19 MsNF-YCs) were expressed in all tissues at different expression levels, indicating that these genes have tissue expression specificity and different biological functions. In total, seven, seven, six, and eight MsNF-Y genes responded to cold stress, the ABA treatment, drought stress, and salt stress in alfalfa, respectively. According to the WGCNA, molecular regulatory networks related to salt stress were constructed for MsNF-YB2, MsNF-YB5, MsNF-YB7, MsNF-YB15, MsNF-YC5, and MsNF-YC6. This study could provide valuable information for further elucidating the biological functions of MsNF-Ys and improving salt tolerance and other abiotic stress resistance in alfalfa.

Genome-wide association studies and whole-genome prediction reveal the genetic architecture of KRN in maize.

BACKGROUND: Kernel row number (KRN) is an important trait for the domestication and improvement of maize. Exploring the genetic basis of KRN has great research significance and can provide valuable information for molecular assisted selection. RESULTS: In this study, one single-locus method (MLM) and six multilocus methods (mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB and ISIS EM-BLASSO) of genome-wide association studies (GWASs) were used to identify significant quantitative trait nucleotides (QTNs) for KRN in an association panel including 639 maize inbred lines that were genotyped by the MaizeSNP50 BeadChip. In three phenotyping environments and with best linear unbiased prediction (BLUP) values, the seven GWAS methods revealed different numbers of KRN-associated QTNs, ranging from 11 to 177. Based on these results, seven important regions for KRN located on chromosomes 1, 2, 3, 5, 9, and 10 were identified by at least three methods and in at least two environments. Moreover, 49 genes from the seven regions were expressed in different maize tissues. Among the 49 genes, ARF29 (Zm00001d026540, encoding auxin response factor 29) and CKO4 (Zm00001d043293, encoding cytokinin oxidase protein) were significantly related to KRN, based on expression analysis and candidate gene association mapping. Whole-genome prediction (WGP) of KRN was also performed, and we found that the KRN-associated tagSNPs achieved a high prediction accuracy. The best strategy was to integrate all of the KRN-associated tagSNPs identified by all GWAS models. CONCLUSIONS: These results aid in our understanding of the genetic architecture of KRN and provide useful information for genomic selection for KRN in maize breeding.

Candidate loci for the kernel row number in maize revealed by a combination of transcriptome analysis and regional association mapping.

BACKGROUND: The kernel row number (KRN) of an ear is an important trait related to yield and domestication in maize. Exploring the underlying genetic mechanisms of KRN has great research significance and application potential. RESULTS: In the present study, N531 with a KRN of 18-22 and SLN with a KRN of 4-6 were used as the recurrent parent and the donor parent, respectively, to develop two introgression lines (ILs), IL_A and IL_B, both of which have common negative-effect alleles from SLN on chromosomes 1, 5 and 10 and significantly reduced inflorescence meristem (IM) diameter and KRN compared with those of N531. We used RNA-Seq to investigate the transcriptome profiles of 5-mm immature ears of N531, IL_A and IL_B. We identified a total of 2872 differentially expressed genes (DEGs) between N531 and IL_A, 2428 DEGs between N531 and IL_B and 1811 DEGs between IL_A and IL_B. A total of 1252 DEGs were detected as overlapping DEGs, and 89 DEGs were located on the common introgression fragments. Furthermore, three DEGs (Zm00001d013277, Zm00001d015310 and Zm00001d015377) containing three SNPs associated with KRN were identified using regional association mapping. CONCLUSIONS: These results will facilitate our understanding of ear development and provide important candidate genes for further study on KRN.

Characterization and fine mapping of qkrnw4, a major QTL controlling kernel row number in maize.

KEY MESSAGE: A major QTL controlling kernel row number, qkrnw4, was identified by combining linkage analysis and association mapping. Within qkrnw4, on the basis of its expression and bioinformatics analysis, Zm00001d052910 was supposed to be the candidate gene for kernel row number. Kernel row number (KRN) is an important yield-related trait that affects kernel number in maize. Understanding the genetic basis of KRN is important for increasing maize yields. In the present study, by the use of a near-isogenic line (NIL) that has a B73 background and that consistently displays a low KRN across environments, qkrnw4, a major quantitative trait locus (QTL) associated with KRN within a yield trait-related QTL hotspot in bin 4.08, was finely mapped to an ~ 33-kb interval. Regional association analysis of a nested association mapping population comprising 5000 recombinant inbred lines revealed Zm00001d052910, which encodes a protein with an unknown function, as the important candidate gene responsible for qkrnw4. Different expression levels of this candidate gene in immature ears were detected between the NIL and its recurrent parent. Moreover, the expression of several auxin-related genes was consistent with that of the candidate gene. Furthermore, the potential associations of this candidate gene with well-known inflorescence-related genes were discussed. The results of this study provide important information for the genetic elucidation of KRN variation in maize.

Translational Landscape of Medicago truncatula Seedlings under Salt Stress.

The expression of plant genes under salt stress at the transcriptional level has been extensively studied. However, less attention has been paid to gene translation regulation under salt stress. In this study, Ribo-seq and RNA-seq analyses were conducted in Medicago truncatula seedlings grown under normal and salt stress conditions. The results showed that salt stress significantly altered the gene expression at the transcriptional and translational levels, with 2755 genes showing significant changes only at the translational level. Salt stress significantly inhibited the gene translation efficiency. Small ORFs (including uORFs in the 5'UTR, dORFs in 3'UTRs, and sORFs in lncRNAs) were identified throughout the genome of M. truncatula. The efficiency of gene translation was simultaneously regulated by the uORFs, dORFs, and miRNAs. In summary, our results provide valuable information about translatomic resources and new insights into plant responses to salt stress.

Integrated Analysis of Coding and Non-coding RNAs Reveals the Molecular Mechanism Underlying Salt Stress Response in Medicago truncatula.

Salt stress is among the most severe abiotic stresses in plants worldwide. Medicago truncatula is a model plant for legumes and analysis of its response to salt stress is helpful for providing valuable insights into breeding. However, few studies have focused on illustrating the whole-transcriptome molecular mechanism underlying salt stress response in Medicago truncatula. Herein, we sampled the leaves of Medicago truncatula treated with water or NaCl and analyzed the characteristics of its coding and non-coding RNAs. We identified a total of 4,693 differentially expressed mRNAs (DEmRNAs), 505 DElncRNAs, 21 DEcircRNAs, and 55 DEmiRNAs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses revealed that their functions were mostly associated with metabolic processes. We classified the lncRNAs and circRNAs into different types and analyzed their genomic distributions. Furthermore, we predicted the interactions between different RNAs based on the competing endogenous RNA (ceRNA) theory and identified multiple correlation networks, including 27 DEmiRNAs, 43 DEmRNAs, 19 lncRNAs, and 5 DEcircRNAs. In addition, we comprehensively analyzed the candidate DEmRNAs and ceRNAs and found that they were involved in Ca+ signaling, starch and sucrose biosynthesis, phenylpropanoid and lignin metabolism, auxin and jasmonate biosynthesis, and transduction pathways. Our integrated analyses in salt stress response in Medicago truncatula revealed multiple differentially expressed coding and non-coding RNAs, including mRNAs, lncRNAs, circRNAs, and miRNAs, and identified multiple DEmRNA and ceRNA interaction pairs that function in many pathways, providing insights into salt stress response in leguminous plants.

Candidate Loci for Yield-Related Traits in Maize Revealed by a Combination of MetaQTL Analysis and Regional Association Mapping.

Maize grain yield and related traits are complex and are controlled by a large number of genes of small effect or quantitative trait loci (QTL). Over the years, a large number of yield-related QTLs have been identified in maize and deposited in public databases. However, integrating and re-analyzing these data and mining candidate loci for yield-related traits has become a major issue in maize. In this study, we collected information on QTLs conferring maize yield-related traits from 33 published studies. Then, 999 of these QTLs were iteratively projected and subjected to meta-analysis to obtain metaQTLs (MQTLs). A total of 76 MQTLs were found across the maize genome. Based on a comparative genomics strategy, several maize orthologs of rice yield-related genes were identified in these MQTL regions. Furthermore, three potential candidate genes (Gene ID: GRMZM2G359974, GRMZM2G301884, and GRMZM2G083894) associated with kernel size and weight within three MQTL regions were identified using regional association mapping, based on the results of the meta-analysis. This strategy, combining MQTL analysis and regional association mapping, is helpful for functional marker development and rapid identification of candidate genes or loci.