The Kernel Size-Related Quantitative Trait Locus qKW9 Encodes a Pentatricopeptide Repeat Protein That Aaffects Photosynthesis and Grain Filling

Molecular mechanisms controlling grain size and weight and their biotechnological breeding applications in maize and other cereal crops

BACKGROUND

Cereal crops are a primary energy source for humans. Grain size and weight affect both evolutionary fitness and grain yield of cereals. Although studies on gene mining and molecular mechanisms controlling grain size and weight are constantly emerging in cereal crops, only a few systematic reviews on the underlying molecular mechanisms and their breeding applications are available so far.

AIM OF REVIEW

This review provides a general state-of-the-art overview of molecular mechanisms and targeted strategies for improving grain size and weight of cereals as well as insights for future yield-improving biotechnology-assisted breeding.

KEY SCIENTIFIC CONCEPTS OF REVIEW

In this review, the evolution of research on grain size and weight over the last 20 years is traced based on a bibliometric analysis of 1158 publications and the main signaling pathways and transcriptional factors involved are summarized. In addition, the roles of post-transcriptional regulation and photosynthetic product accumulation affecting grain size and weight in maize and rice are outlined. State-of-the-art strategies for discovering novel genes related to grain size and weight in maize and other cereal crops as well as advanced breeding biotechnology strategies being used for improving yield including marker-assisted selection, genomic selection, transgenic breeding, and genome editing are also discussed.

Understanding grain development in the Poaceae family by comparing conserved and distinctive pathways through omics studies in wheat and maize

The Poaceae family, commonly known as the grass family, encompasses a diverse group of crops that play an essential role in providing food, fodder, biofuels, environmental conservation, and cultural value for both human and environmental well-being. Crops in Poaceae family are deeply intertwined with human societies, economies, and ecosystems, making it one of the most significant plant families in the world. As the major reservoirs of essential nutrients, seed grain of these crops has garnered substantial attention from researchers. Understanding the molecular and genetic processes that controls seed formation, development and maturation can provide insights for improving crop yield, nutritional quality, and stress tolerance. The diversity in photosynthetic pathways between C3 and C4 plants introduces intriguing variations in their physiological and biochemical processes, potentially affecting seed development. In this review, we explore recent studies performed with omics technologies, such as genomics, transcriptomics, proteomics and metabolomics that shed light on the mechanisms underlying seed development in wheat and maize, as representatives of C3 and C4 plants respectively, providing insights into their unique adaptations and strategies for reproductive success.

Genetic variation in ZmKW1 contributes to kernel weight and size in dent corn and popcorn

Kernel weight is a critical factor that essentially affects maize (Zea mays) yield. In natural inbred lines, popcorn kernels exhibit overtly smaller sizes compared to dent corn kernels, and kernel weight, which is controlled by multiple genetic loci, varies widely. Here, we characterized a major quantitative trait locus on chromosome 1, responsible for controlling kernel weight (qKW1) and size. The qKW1 locus encodes a protein containing a seven in absentia domain with E3 ubiquitin ligase activity, expressed prominently from the top to the middle region of the endosperm. The presence and function of qKW1 were confirmed through ZmKW1 gene editing, where the mutations in ZmKW1 within dent corn significantly increased kernel weight, consistent with alterations in kernel size, while overexpression of ZmKW1 had the opposite effect. ZmKW1 acts as a negative regulator of kernel weight and size by reducing both the number and size of the endosperm cells and impacting endosperm filling. Notably, the popcorn allele qKW1N and the dent corn allele qKW1D encode identical proteins; however, the differences in promoter activity arise due to the insertion of an Indel-1346 sequence in the qKW1N promoter, resulting in higher expression levels compared to qKW1D, thus contributing to the variation in kernel weight and size between popcorn and dent corn kernels. Linkage disequilibrium analysis of the 2.8 kb promoter region of ZmKW1 in a dataset comprising 111 maize association panels identified two distinct haplotypes. Our results provide insight into the mechanisms underlying kernel development and yield regulation in dent corn and popcorn, with a specific focus on the role of the ubiquitination system.

Chloroplast C-to-U editing, regulated by a PPR protein BoYgl-2, is important for chlorophyll biosynthesis in cabbage

Leaf color is an important agronomic trait in cabbage (Brassica oleracea L. var. capitata), but the detailed mechanism underlying leaf color formation remains unclear. In this study, we characterized a Brassica oleracea yellow-green leaf 2 (BoYgl-2) mutant 4036Y, which has significantly reduced chlorophyll content and abnormal chloroplasts during early leaf development. Genetic analysis revealed that the yellow-green leaf trait is controlled by a single recessive gene. Map-based cloning revealed that BoYgl-2 encodes a novel nuclear-targeted P-type PPR protein, which is absent in the 4036Y mutant. Functional complementation showed that BoYgl-2 from the normal-green leaf 4036G can rescue the yellow-green leaf phenotype of 4036Y. The C-to-U editing efficiency and expression levels of atpF, rps14, petL and ndhD were significantly reduced in 4036Y than that in 4036G, and significantly increased in BoYgl-2 overexpression lines than that in 4036Y. The expression levels of many plastid- and nuclear-encoded genes associated with chloroplast development in BoYgl-2 mutant were also significantly altered. These results suggest that BoYgl-2 participates in chloroplast C-to-U editing and development, which provides rare insight into the molecular mechanism underlying leaf color formation in cabbage.

Multi-year field trials provide a massive repository of trait data on a highly diverse population of tomato and uncover novel determinants of tomato productivity

Tomato (Solanum lycopersicum) is a prominent fruit with rich genetic resources for crop improvement. By using a phenotype-guided screen of over 7900 tomato accessions from around the world, we identified new associations for complex traits such as fruit weight and total soluble solids (Brix). Here, we present the phenotypic data from several years of trials. To illustrate the power of this dataset we use two case studies. First, evaluation of color revealed allelic variation in phytoene synthase 1 that resulted in differently colored or even bicolored fruit. Secondly, in view of the negative relationship between fruit weight and Brix, we pre-selected a subset of the collection that includes high and low Brix values in each category of fruit size. Genome-wide association analysis allowed us to detect novel loci associated with total soluble solid content and fruit weight. In addition, we developed eight F2 biparental intraspecific populations. Furthermore, by taking a phenotype-guided approach we were able to isolate individuals with high Brix values that were not compromised in terms of yield. In addition, the demonstration of novel results despite the high number of previous genome-wide association studies of these traits in tomato suggests that adoption of a phenotype-guided pre-selection of germplasm may represent a useful strategy for finding target genes for breeding.

A Plate Growth Assay to Quantify Embryonic Root Development of Zea mays

Murashige-Skoog medium solutions have been used in a variety of plant plate growth assays, yet most research uses Arabidopsis thaliana as the study organism. For larger seeds such as maize (Zea mays), most protocols employ a paper towel roll method for experiments, which often involves wrapping maize seedlings in wet, sterile germination paper. What the paper towel roll method lacks, however, is the ability to image the roots over time without risk of contamination. Here, we describe a sterile plate growth assay that contains Murashige-Skoog medium to grow seedlings starting two days after germination. This protocol uses a section of a paper towel roll method to achieve uniform germination of maize seedlings, which are sterilely transferred onto large acrylic plates for the duration of the experiment. The media can undergo modification to include an assortment of plant hormones, exogenous sugars, and other chemicals. The acrylic plates allow researchers to freely image the plate without disturbing the seedlings and control the environment in which the seedlings are grown, such as modifications in temperature and light. Additionally, the protocol is widely adaptable for use with other cereal crops. Key features • Builds upon plate growth methods routinely used for Arabidopsis seedlings but that are inadequate for maize. • Real-time photographic analysis of seedlings up to two weeks following germination. • Allows for testing of various growth conditions involving an assortment of additives and/or modification of environmental conditions. • Samples are able to be collected for genotype screening.

Evaluating the Genetic Background Effect on Dissecting the Genetic Basis of Kernel Traits in Reciprocal Maize Introgression Lines

Maize yield is mostly determined by its grain size. Although numerous quantitative trait loci (QTL) have been identified for kernel-related traits, the application of these QTL in breeding programs has been strongly hindered because the populations used for QTL mapping are often different from breeding populations. However, the effect of genetic background on the efficiency of QTL and the accuracy of trait genomic prediction has not been fully studied. Here, we used a set of reciprocal introgression lines (ILs) derived from 417F × 517F to evaluate how genetic background affects the detection of QTLassociated with kernel shape traits. A total of 51 QTL for kernel size were identified by chromosome segment lines (CSL) and genome-wide association studies (GWAS) methods. These were subsequently clustered into 13 common QTL based on their physical position, including 7 genetic-background-independent and 6 genetic-background-dependent QTL, respectively. Additionally, different digenic epistatic marker pairs were identified in the 417F and 517F ILs. Therefore, our results demonstrated that genetic background strongly affected not only the kernel size QTL mapping via CSL and GWAS but also the genomic prediction accuracy and epistatic detection, thereby enhancing our understanding of how genetic background affects the genetic dissection of grain size-related traits.

Genome-Wide Association Study for Grain Protein, Thousand Kernel Weight, and Normalized Difference Vegetation Index in Bread Wheat (Triticum aestivum L.)

Genomic regions governing grain protein content (GPC), 1000 kernel weight (TKW), and normalized difference vegetation index (NDVI) were studied in a set of 280 bread wheat genotypes. The genome-wide association (GWAS) panel was genotyped using a 35K Axiom array and phenotyped in three environments. A total of 26 marker-trait associations (MTAs) were detected on 18 chromosomes covering the A, B, and D subgenomes of bread wheat. The GPC showed the maximum MTAs (16), followed by NDVI (6), and TKW (4). A maximum of 10 MTAs was located on the B subgenome, whereas, 8 MTAs each were mapped on the A and D subgenomes. In silico analysis suggest that the SNPs were located on important putative candidate genes such as NAC domain superfamily, zinc finger RING-H2-type, aspartic peptidase domain, folylpolyglutamate synthase, serine/threonine-protein kinase LRK10, pentatricopeptide repeat, protein kinase-like domain superfamily, cytochrome P450, and expansin. These candidate genes were found to have different roles including regulation of stress tolerance, nutrient remobilization, protein accumulation, nitrogen utilization, photosynthesis, grain filling, mitochondrial function, and kernel development. The effects of newly identified MTAs will be validated in different genetic backgrounds for further utilization in marker-aided breeding.

A multi-locus linear mixed model methodology for detecting small-effect QTLs for quantitative traits in MAGIC, NAM, and ROAM populations

Although multi-parent populations (MPPs) integrate the advantages of linkage and association mapping populations in the genetic dissection of complex traits and especially combine genetic analysis with crop breeding, it is difficult to detect small-effect quantitative trait loci (QTL) for complex traits in multiparent advanced generation intercross (MAGIC), nested association mapping (NAM), and random-open-parent association mapping (ROAM) populations. To address this issue, here we proposed a multi-locus linear mixed model method, namely mppQTL, to detect QTLs, especially small-effect QTLs, in these MPPs. The new method includes two steps. The first is genome-wide scanning based on a single-locus linear mixed model; the P-values are obtained from likelihood-ratio test, the peaks of negative logarithm P-value curve are selected by group-lasso, and all the selected peaks are regarded as potential QTLs. In the second step, all the potential QTLs are placed on a multi-locus linear mixed model, all the effects are estimated using expectation-maximization empirical Bayes algorithm, and all the non-zero effect vectors are further evaluated via likelihood-ratio test for significant QTLs. In Monte Carlo simulation studies, the new method has higher power in QTL detection, lower false positive rate, lower mean absolute deviation for QTL position estimate, and lower mean squared error for the estimate of QTL size (r²) than existing methods because the new method increases the power of detecting small-effect QTLs. In real dataset analysis, the new method (19) identified five more known genes than the existing three methods (14). This study provides an effective method for detecting small-effect QTLs in any MPPs.

A Systemic Investigation of Genetic Architecture and Gene Resources Controlling Kernel Size-Related Traits in Maize

Grain yield is the most critical and complex quantitative trait in maize. Kernel length (KL), kernel width (KW), kernel thickness (KT) and hundred-kernel weight (HKW) associated with kernel size are essential components of yield-related traits in maize. With the extensive use of quantitative trait locus (QTL) mapping and genome-wide association study (GWAS) analyses, thousands of QTLs and quantitative trait nucleotides (QTNs) have been discovered for controlling these traits. However, only some of them have been cloned and successfully utilized in breeding programs. In this study, we exhaustively collected reported genes, QTLs and QTNs associated with the four traits, performed cluster identification of QTLs and QTNs, then combined QTL and QTN clusters to detect consensus hotspot regions. In total, 31 hotspots were identified for kernel size-related traits. Their candidate genes were predicted to be related to well-known pathways regulating the kernel developmental process. The identified hotspots can be further explored for fine mapping and candidate gene validation. Finally, we provided a strategy for high yield and quality maize. This study will not only facilitate causal genes cloning, but also guide the breeding practice for maize.

Mapping QTL for Phenological and Grain-Related Traits in a Mapping Population Derived from High-Zinc-Biofortified Wheat

Genomic regions governing days to heading (DH), days to maturity (DM), plant height (PH), thousand-kernel weight (TKW), and test weight (TW) were investigated in a set of 190 RILs derived from a cross between a widely cultivated wheat-variety, Kachu (DPW-621-50), and a high-zinc variety, Zinc-Shakti. The RIL population was genotyped using 909 DArTseq markers and phenotyped in three environments. The constructed genetic map had a total genetic length of 4665 cM, with an average marker density of 5.13 cM. A total of thirty-seven novel quantitative trait loci (QTL), including twelve for PH, six for DH, five for DM, eight for TKW and six for TW were identified. A set of 20 stable QTLs associated with the expression of DH, DM, PH, TKW, and TW were identified in two or more environments. Three novel pleiotropic genomic-regions harboring co-localized QTLs governing two or more traits were also identified. In silico analysis revealed that the DArTseq markers were located on important putative candidate genes such as MLO-like protein, Phytochrome, Zinc finger and RING-type, Cytochrome P450 and pentatricopeptide repeat, involved in the regulation of pollen maturity, the photoperiodic modulation of flowering-time, abiotic-stress tolerance, grain-filling duration, thousand-kernel weight, seed morphology, and plant growth and development. The identified novel QTLs, particularly stable and co-localized QTLs, will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection (MAS).

A NAC-EXPANSIN module enhances maize kernel size by controlling nucellus elimination

Maize early endosperm development is initiated in coordination with elimination of maternal nucellar tissues. However, the underlying mechanisms are largely unknown. Here, we characterize a major quantitative trait locus for maize kernel size and weight that encodes an EXPANSIN gene, ZmEXPB15. The encoded β-expansin protein is expressed specifically in nucellus, and positively controls kernel size and weight by promoting nucellus elimination. We further show that two nucellus-enriched transcription factors (TFs), ZmNAC11 and ZmNAC29, activate ZmEXPB15 expression. Accordingly, these two TFs also promote kernel size and weight through nucellus elimination regulation, and genetic analyses support their interaction with ZmEXPB15. Importantly, hybrids derived from a ZmEXPB15 overexpression line have increased kernel weight, demonstrates its potential value in breeding. Together, we reveal a pathway modulating the cellular processes of maternal nucellus elimination and early endosperm development, and an approach to improve kernel weight.

T. MP, Das S, Pawar PAM, Kumar A, Tripathi K, Kumar RR, Yadava DK, Kumar S, Dikshit HK. Comparative transcriptome analysis, unfolding the pathways regulating the seed-size trait in cultivated lentil (Lens culinaris Medik.)

Market class, cooking time, quality, and milled grain yield are largely influenced by the seed size and shape of the lentil (Lens culinaris Medik.); thus, they are considered to be important quality traits. To unfold the pathways regulating seed size in lentils, a transcriptomic approach was performed using large-seeded (L4602) and small-seeded (L830) genotypes. The study has generated nearly 375 million high-quality reads, of which 98.70% were properly aligned to the reference genome. Among biological replicates, very high similarity in fragments per kilobase of exon per million mapped fragments values (R > 0.9) showed the consistency of RNA-seq results. Various differentially expressed genes associated mainly with the hormone signaling and cell division pathways, transcription factors, kinases, etc. were identified as having a role in cell expansion and seed growth. A total of 106,996 unigenes were used for differential expression (DE) analysis. String analysis identified various modules having certain key proteins like Ser/Thr protein kinase, seed storage protein, DNA-binding protein, microtubule-associated protein, etc. In addition, some growth and cell division–related micro-RNAs like miR3457 (cell wall formation), miR1440 (cell proliferation and cell cycles), and miR1533 (biosynthesis of plant hormones) were identified as having a role in seed size determination. Using RNA-seq data, 5254 EST-SSR primers were generated as a source for future studies aiming for the identification of linked markers. In silico validation using Genevestigator^® was done for the Ser/Thr protein kinase, ethylene response factor, and Myb transcription factor genes. It is of interest that the xyloglucan endotransglucosylase gene was found differentially regulated, suggesting their role during seed development; however, at maturity, no significant differences were recorded for various cell wall parameters including cellulose, lignin, and xylose content. This is the first report on lentils that has unfolded the key seed size regulating pathways and unveiled a theoretical way for the development of lentil genotypes having customized seed sizes.

Molecular mapping of QTLs for grain dimension traits in Basmati rice

Basmati rice is known for its extra-long slender grains, exceptional kernel dimensions after cooking, high volume expansion, and strong aroma. Developing high yielding Basmati rice varieties with good cooking quality is a gigantic task. Therefore, identifying the genomic regions governing the grain and cooked kernel dimension traits is of utmost importance for its use in marker-assisted breeding. Although several QTLs governing grain dimension traits have been reported, limited attempts have been made to map QTLs for grain and cooked kernel dimension traits of Basmati rice. In the current study, a population of recombinant inbred lines (RIL) was generated from a cross of Sonasal and Pusa Basmati 1121 (PB1121). In the RIL population, there was a significant positive correlation among the length (RRL: rough rice length, MRL: milled rice length, CKL: cooked kernel length) and breadth (RRB: rough rice breadth, MRB: milled rice breadth and CKB: cooked kernel breadth) of the related traits, while there was significant negative correlation between them. QTL mapping has led to the identification of four major genomic regions governing MRL and CKL. Two QTLs co-localize with the earlier reported major gene GS3 and a QTL qGRL7.1, while the remaining two QTLs viz., qCKL3.2 (qMRL3.2) and qCKL4.1 (qMRL4.1) were novel. The QTL qCKL3.2 has been bracketed to a genomic region of 0.78 Mb between the markers RM15247 and RM15281. Annotation of this region identified 18 gene models, of which the genes predicted to encode pentatricopeptides and brassinosteroid insensitive 1-associated receptor kinase 1 precursor may be the putative candidate genes. Furthermore, we identified a novel QTL qKER2.1 governing kernel elongation ratio (KER) in Basmati rice.

Identification of major genomic regions for soybean seed weight by genome-wide association study

The hundred-seed weight (HSW) is an important yield component and one of the principal breeding traits in soybean. More than 250 quantitative trait loci (QTL) for soybean HSW have been identified. However, most of them have a large genomic region or are environmentally sensitive, which provide limited information for improving the phenotype in marker-assisted selection (MAS) and identifying the candidate genes. Here, we utilized 281 soybean accessions with 58,112 single nucleotide polymorphisms (SNPs) to dissect the genetic basis of HSW in across years in the northern Shaanxi province of China through one single-locus (SL) and three multi-locus (ML) genome-wide association study (GWAS) models. As a result, one hundred and fifty-four SNPs were detected to be significantly associated with HSW in at least one environment via SL-GWAS model, and 27 of these 154 SNPs were detected in all (three) environments and located within 7 linkage disequilibrium (LD) block regions with the distance of each block ranged from 40 to 610 Kb. A total of 15 quantitative trait nucleotides (QTNs) were identified by three ML-GWAS models. Combined with the results of different GWAS models, the 7 LD block regions associated with HSW detected by SL-GWAS model could be verified directly or indirectly by the results of ML-GWAS models. Eleven candidate genes underlying the stable loci that may regulate seed weight in soybean were predicted. The significantly associated SNPs and the stable loci as well as predicted candidate genes may be of great importance for marker-assisted breeding, polymerization breeding, and gene discovery for HSW in soybean.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01310-y.

Genome-Wide Association Analysis for Candidate Genes Contributing to Kernel-Related Traits in Maize

Maize grain size is the main factor determining grain yield. Dissecting the genetic basis of maize grain size may help reveal the regulatory mechanism of maize seed development and yield formation. In this study, two associated populations were used for genome-wide association analysis of kernel length, kernel width, kernel thickness, and hundred-kernel weight from multiple locations in AM122 and AM180, respectively. Then, genome-wide association mapping was performed based on the maize 6H90K SNP chip. A total of 139 loci were identified as associated with the four traits with p < 1 × 10^-4 using two models (FarmCPU and MLM). The transcriptome data showed that 15 of them were expressed differentially in two maize-inbred lines KB182 (small kernel) and KB020 (big kernel) during kernel development. These candidate genes were enriched in regulating peroxidase activity, oxidoreductase, and leaf senescence. The molecular function was major in binding and catalytic activity. This study provided important reference information for exploring maize kernel development mechanisms and applying molecular markers in high-yield breeding.

Identification of a candidate gene underlying qHKW3, a QTL for hundred-kernel weight in maize

qHKW3, a quantitative trait locus for hundred-kernel weight, harbors the proposed causal gene Zm00001d044081, encoding a homeobox-leucine zipper protein (ATHB-4) that might affect kernel size and weight. Kernel size and weight are key traits that contribute greatly to grain yield per year in maize (Zea mays). Here, we developed the chromosome segment substitution line (CSSL), H15-6-2, with smaller kernel size and lower kernel weight across environments compared to the background line Ye478. Histological analysis suggested that a slower kernel filling rate of H15-6-2 contributes to its small-kernel size and reduced hundred-kernel weight. We identified a quantitative trait locus (QTL) explaining 23% of the phenotypic variation in hundred-kernel weight. This QTL, qHKW3, was fine mapped to an interval of approximately 40.66-kb harboring the gene Zm00001d044081. The upstream sequence and its expression level of Zm00001d044081 in kernels at 6 days after pollination (DAP) showed obvious differences between the near-isogenic lines HKW3^Ye478 and HKW3^H15-6-2. We further confirmed the effects of the Zm00001d044081 promoter on maize kernel size and weight in an independent association mapping panel with 513 lines by candidate regional association analysis. We propose that Zm00001d044081, which encodes the homeobox-leucine zipper protein ATHB-4, is the causal gene of qHKW3, representing an attractive target for the genetic improvement of maize yield.

DEK48 Is Required for RNA Editing at Multiple Mitochondrial Sites and Seed Development in Maize

In flowering plants, C-to-U RNA editing can be critical to normal functions of mitochondrion-encoded proteins. Mitochondrial C-to-U RNA editing is facilitated by many factors from diverse protein families, of which the pentatricopeptide repeat (PPR) proteins play an important role. Owing to their large number and frequent embryo lethality in mutants, functions of many PPRs remain unknown. In this study, we characterized a mitochondrion-localized DYW-type PPR protein, DEK48, functioning in the C-to-U RNA editing at multiple mitochondrial transcripts in maize. Null mutation of Dek48 severely arrests embryo and endosperm development, causing a defective kernel (dek) phenotype, named dek48. DEK48 loss of function abolishes the C-to-U editing at nad3-185, -215, and nad4-376, -977 sites and decreases the editing at 11 other sites, resulting in the alteration of the corresponding amino acids. Consequently, the absence of editing caused reduced assembly and activity of complex I in dek48. Interestingly, we identified a point mutation in dek48-3 causing a deletion of the Tryptophan (W) residue in the DYW motif that abolishes the editing function. In sum, this study reveals the function of DEK48 in the C-to-U editing in mitochondrial transcripts and seed development in maize, and it demonstrates a critical role of the W residue in the DYW triplet motif of DEK48 for the C-to-U editing function in vivo.

Genetic Architecture of Grain Yield-Related Traits in Sorghum and Maize

Grain size, grain number per panicle, and grain weight are crucial determinants of yield-related traits in cereals. Understanding the genetic basis of grain yield-related traits has been the main research object and nodal in crop science. Sorghum and maize, as very close C4 crops with high photosynthetic rates, stress tolerance and large biomass characteristics, are extensively used to produce food, feed, and biofuels worldwide. In this review, we comprehensively summarize a large number of quantitative trait loci (QTLs) associated with grain yield in sorghum and maize. We placed great emphasis on discussing 22 fine-mapped QTLs and 30 functionally characterized genes, which greatly hinders our deep understanding at the molecular mechanism level. This review provides a general overview of the comprehensive findings on grain yield QTLs and discusses the emerging trend in molecular marker-assisted breeding with these QTLs.

Functions of PPR Proteins in Plant Growth and Development

Pentatricopeptide repeat (PPR) proteins form a large protein family in land plants, with hundreds of different members in angiosperms. In the last decade, a number of studies have shown that PPR proteins are sequence-specific RNA-binding proteins involved in multiple aspects of plant organellar RNA processing, and perform numerous functions in plants throughout their life cycle. Recently, computational and structural studies have provided new insights into the working mechanisms of PPR proteins in RNA recognition and cytidine deamination. In this review, we summarized the research progress on the functions of PPR proteins in plant growth and development, with a particular focus on their effects on cytoplasmic male sterility, stress responses, and seed development. We also documented the molecular mechanisms of PPR proteins in mediating RNA processing in plant mitochondria and chloroplasts.

ZmPPR26, a DYW-type pentatricopeptide repeat protein, is required for C-to-U RNA editing at atpA-1148 in maize chloroplasts

Pentatricopeptide repeat (PPR) proteins are involved in the C-to-U RNA editing of organellar transcripts. The maize genome contains over 600 PPR proteins and few have been found to function in the C-to-U RNA editing in chloroplasts. Here, we report the function of ZmPPR26 in the C-to-U RNA editing and chloroplast biogenesis in maize. ZmPPR26 encodes a DYW-type PPR protein targeted to chloroplasts. The zmppr26 mutant exhibits albino seedling-lethal phenotype. Loss of function of ZmPPR26 abolishes the editing at atpA-1148 site, and decreases the editing at ndhF-62, rpl20-308, rpl2-2, rpoC2-2774, petB-668, rps8-182, and ndhA-50 sites. Overexpression of ZmPPR26 in zmppr26 restores the editing efficiency and rescues the albino seedling-lethal phenotype. Abolished editing at atpA-1148 causes a Leu to Ser change at AtpA-383 that leads to a reduction in the abundance of chloroplast ATP synthase in zmppr26. The accumulation of photosynthetic complexes are also markedly reduced in zmppr26, providing an explanation for the albino seedling-lethal phenotype. These results indicate that ZmPPR26 is required for the editing at atpA-1148 and is important for editing at the other seven sites in maize chloroplasts. The editing at atpA-1148 is critical for AtpA function, assembly of ATP synthase complex, and chloroplast biogenesis in maize.

Natural Variation in Crops: Realized Understanding, Continuing Promise

Crops feed the world's population and shape human civilization. The improvement of crop productivity has been ongoing for almost 10,000 years and has evolved from an experience-based to a knowledge-driven practice over the past three decades. Natural alleles and their reshuffling are long-standing genetic changes that affect how crops respond to various environmental conditions and agricultural practices. Decoding the genetic basis of natural variation is central to understanding crop evolution and, in turn, improving crop breeding. Here, we review current advances in the approaches used to map the causal alleles of natural variation, provide refined insights into the genetics and evolution of natural variation, and outline how this knowledge promises to drive the development of sustainable agriculture under the dome of emerging technologies.

Nitrogen Starvation-Responsive MicroRNAs Are Affected by Transgenerational Stress in Durum Wheat Seedlings

Stress events have transgenerational effects on plant growth and development. In Mediterranean regions, water-deficit and heat (WH) stress is a frequent issue that negatively affects crop yield and quality. Nitrogen (N) is an essential plant macronutrient and often a yield-limiting factor for crops. Here, the response of durum wheat seedlings to N starvation under the transgenerational effects of WH stress was investigated in two genotypes. Both genotypes showed a significant reduction in seedling height, leaf number, shoot and root weight (fresh and dry), primary root length, and chlorophyll content under N starvation stress. However, in the WH stress-tolerant genotype, the percentage reduction of most traits was lower in progeny from the stressed parents than progeny from the control parents. Small RNA sequencing identified 1534 microRNAs in different treatment groups. Differentially expressed microRNAs (DEMs) were characterized subject to N starvation, parental stress and genotype factors, with their target genes identified in silico. GO and KEGG enrichment analyses revealed the biological functions, associated with DEM-target modules in stress adaptation processes, that could contribute to the phenotypic differences observed between the two genotypes. The study provides the first evidence of the transgenerational effects of WH stress on the N starvation response in durum wheat.

A Major and Stable Quantitative Trait Locus qSS2 for Seed Size and Shape Traits in a Soybean RIL Population

Seed size and shape traits are important determinants of seed yield and appearance quality in soybean [Glycine max (L.) Merr.]. Understanding the genetic architecture of these traits is important to enable their genetic improvement through efficient and targeted selection in soybean breeding, and for the identification of underlying causal genes. To map seed size and shape traits in soybean, a recombinant inbred line (RIL) population developed from K099 (small seed size) × Fendou 16 (large seed size), was phenotyped in three growing seasons. A genetic map of the RIL population was developed using 1,485 genotyping by random amplicon sequencing-direct (GRAS-Di) and 177 SSR markers. Quantitative trait locus (QTL) mapping was conducted by inclusive composite interval mapping. As a result, 53 significant QTLs for seed size traits and 27 significant QTLs for seed shape traits were identified. Six of these QTLs (qSW8.1, qSW16.1, qSLW2.1, qSLT2.1, qSWT1.2, and qSWT4.3) were identified with LOD scores of 3.80-14.0 and R ² of 2.36%-39.49% in at least two growing seasons. Among the above significant QTLs, 24 QTLs were grouped into 11 QTL clusters, such as, three major QTLs (qSL2.3, qSLW2.1, and qSLT2.1) were clustered into a major QTL on Chr.02, named as qSS2. The effect of qSS2 was validated in a pair of near isogenic lines, and its candidate genes (Glyma.02G269400, Glyma.02G272100, Glyma.02G274900, Glyma.02G277200, and Glyma.02G277600) were mined. The results of this study will assist in the breeding programs aiming at improvement of seed size and shape traits in soybean.

Genetic and molecular control of grain yield in maize

Understanding the genetic and molecular basis of grain yield is important for maize improvement. Here, we identified 49 consensus quantitative trait loci (cQTL) controlling maize yield-related traits using QTL meta-analysis. Then, we collected yield-related traits associated SNPs detected by association mapping and identified 17 consensus significant loci. Comparing the physical positions of cQTL with those of significant SNPs revealed that 47 significant SNPs were located within 20 cQTL regions. Furthermore, intensive reviews of 31 genes regulating maize yield-related traits found that the functions of many genes were conservative in maize and other plant species. The functional conservation indicated that some of the 575 maize genes (orthologous to 247 genes controlling yield or seed traits in other plant species) might be functionally related to maize yield-related traits, especially the 49 maize orthologous genes in cQTL regions, and 41 orthologous genes close to the physical positions of significant SNPs. In the end, we prospected on the integration of the public sources for exploring the genetic and molecular mechanisms of maize yield-related traits, and on the utilization of genetic and molecular mechanisms for maize improvement.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01214-3.

Comprehensive Transcriptome Analyses Reveal Candidate Genes for Variation in Seed Size/Weight During Peanut (Arachis hypogaea L.) Domestication

Seed size/weight, a key domestication trait, is also an important selection target during peanut breeding. However, the mechanisms that regulate peanut seed development are unknown. We re-sequenced 12 RNA samples from developing seeds of two cultivated peanut accessions (Lines 8106 and 8107) and wild Arachis monticola at 15, 30, 45, and 60 days past flowering (DPF). Transcriptome analyses showed that ∼36,000 gene loci were expressed in each of the 12 RNA samples, with nearly half exhibiting moderate (2 ≤ FPKM < 10) expression levels. Of these genes, 12.2% (4,523) were specifically expressed during seed development, mainly at 15 DPF. Also, ∼12,000 genes showed significant differential expression at 30, 45, and/or 60 DPF within each of the three peanut accessions, accounting for 31.8-34.1% of the total expressed genes. Using a method that combined comprehensive transcriptome analysis and previously mapped QTLs, we identified several candidate genes that encode transcription factor TGA7, topless-related protein 2, IAA-amino acid hydrolase ILR1-like 5, and putative pentatricopeptide repeat-containing (PPR) protein. Based on sequence variations identified in these genes, SNP markers were developed and used to genotype both 30 peanut landraces and a genetic segregated population, implying that EVM0025654 encoding a PPR protein may be associated with the increased seed size/weight of the cultivated accessions in comparison with the allotetraploid wild peanut. Our results provide additional knowledge for the identification and functional research into candidate genes responsible for the seed size/weight phenotype in peanut.

Maize kernel development

Maize (Zea mays) is a leading cereal crop in the world. The maize kernel is the storage organ and the harvest portion of this crop and is closely related to its yield and quality. The development of maize kernel is initiated by the double fertilization event, leading to the formation of a diploid embryo and a triploid endosperm. The embryo and endosperm are then undergone independent developmental programs, resulting in a mature maize kernel which is comprised of a persistent endosperm, a large embryo, and a maternal pericarp. Due to the well-characterized morphogenesis and powerful genetics, maize kernel has long been an excellent model for the study of cereal kernel development. In recent years, with the release of the maize reference genome and the development of new genomic technologies, there has been an explosive expansion of new knowledge for maize kernel development. In this review, we overviewed recent progress in the study of maize kernel development, with an emphasis on genetic mapping of kernel traits, transcriptome analysis during kernel development, functional gene cloning of kernel mutants, and genetic engineering of kernel traits.