A Kinesin-14 Motor Activates Neocentromeres to Promote Meiotic Drive in Maize.

Maize abnormal chromosome 10 (Ab10) encodes a classic example of true meiotic drive that converts heterochromatic regions called knobs into motile neocentromeres that are preferentially transmitted to egg cells. Here, we identify a cluster of eight genes on Ab10, called the Kinesin driver (Kindr) complex, that are required for both neocentromere motility and preferential transmission. Two meiotic drive mutants that lack neocentromere activity proved to be kindr epimutants with increased DNA methylation across the entire gene cluster. RNAi of Kindr induced a third epimutant and corresponding loss of meiotic drive. Kinesin gliding assays and immunolocalization revealed that KINDR is a functional minus-end-directed kinesin that localizes specifically to knobs containing 180 bp repeats. Sequence comparisons suggest that Kindr diverged from a Kinesin-14A ancestor ∼12 mya and has driven the accumulation of > 500 Mb of knob repeats and affected the segregation of thousands of genes linked to knobs on all 10 chromosomes.

On the Road to Breeding 4.0: Unraveling the Good, the Bad, and the Boring of Crop Quantitative Genomics.

Understanding the quantitative genetics of crops has been and will continue to be central to maintaining and improving global food security. We outline four stages that plant breeding either has already achieved or will probably soon achieve. Top-of-the-line breeding programs are currently in Breeding 3.0, where inexpensive, genome-wide data coupled with powerful algorithms allow us to start breeding on predicted instead of measured phenotypes. We focus on three major questions that must be answered to move from current Breeding 3.0 practices to Breeding 4.0: ( a) How do we adapt crops to better fit agricultural environments? ( b) What is the nature of the diversity upon which breeding can act? ( c) How do we deal with deleterious variants? Answering these questions and then translating them to actual gains for farmers will be a significant part of achieving global food security in the twenty-first century.

Eleven biosynthetic genes explain the majority of natural variation in carotenoid levels in maize grain.

Vitamin A deficiency remains prevalent in parts of Asia, Latin America, and sub-Saharan Africa where maize (Zea mays) is a food staple. Extensive natural variation exists for carotenoids in maize grain. Here, to understand its genetic basis, we conducted a joint linkage and genome-wide association study of the US maize nested association mapping panel. Eleven of the 44 detected quantitative trait loci (QTL) were resolved to individual genes. Six of these were correlated expression and effect QTL (ceeQTL), showing strong correlations between RNA-seq expression abundances and QTL allelic effect estimates across six stages of grain development. These six ceeQTL also had the largest percentage of phenotypic variance explained, and in major part comprised the three to five loci capturing the bulk of genetic variation for each trait. Most of these ceeQTL had strongly correlated QTL allelic effect estimates across multiple traits. These findings provide an in-depth genome-level understanding of the genetic and molecular control of carotenoids in plants. In addition, these findings provide a roadmap to accelerate breeding for provitamin A and other priority carotenoid traits in maize grain that should be readily extendable to other cereals.

Genome-wide association mapping of resistance to the sorghum aphid in Sorghum bicolor.

Since 2013, the sorghum aphid (SA), Melanaphis sorghi (Theobald), has been a serious pest that hampers all types of sorghum production in the U.S. Known sorghum aphid resistance in sorghum is limited to a few genetic regions on SBI-06. In this study, a subset of the Sorghum Association Panel (SAP) was used along with some additional lines to identify genomic regions that confer sorghum aphid resistance. SAP lines were grown in the field and visually evaluated for SA resistance during the growing seasons of 2019 and 2020 in Tifton, GA. In 2020, the SAP accessions were also evaluated for SA resistance in the field using drone-based high throughput phenotyping (HTP). Flowering time was recorded in the field to confirm that our methods were sufficient for identifying known quantitative trait loci (QTL). This study combined phenotypic data from field-based visual ratings and reflectance data to identify genome-wide associated (GWAS) marker-trait associations (MTA) using genotyping-by-sequencing (GBS) data. Several MTAs were identified for SA-related traits across the genome, with a few common markers that were consistently identified on SBI-08 and SBI-10 for aphid count and plant damage, as well as loci for reflectance-based traits on SBI-02, SBI-03, and SBI-05. Candidate genes encoding leucine-rich repeats (LRR), Avr proteins, lipoxygenases (LOXs), calmodulins (CAM) dependent protein kinase, WRKY transcription factors, flavonoid biosynthesis genes, and 12-oxo-phytodienoic acid reductase were identified near SNPs that had significant associations with different SA traits. In this study, flowering time-related genes were also identified as a positive control for the methods. The total phenotypic variation explained by significant SNPs across SA-scored traits, reflectance data, and flowering time ranged from 6 to 61%, while the heritability value ranged from 4 to 69%. This study identified three new sources of resistant lines to sorghum aphid. These results supported the existing literature, and also revealed several new loci. Markers identified in this study will support marker-assisted breeding for sorghum aphid resistance.

Large-scale replicated field study of maize rhizosphere identifies heritable microbes.

Soil microbes that colonize plant roots and are responsive to differences in plant genotype remain to be ascertained for agronomically important crops. From a very large-scale longitudinal field study of 27 maize inbred lines planted in three fields, with partial replication 5 y later, we identify root-associated microbiota exhibiting reproducible associations with plant genotype. Analysis of 4,866 samples identified 143 operational taxonomic units (OTUs) whose variation in relative abundances across the samples was significantly regulated by plant genotype, and included five of seven core OTUs present in all samples. Plant genetic effects were significant amid the large effects of plant age on the rhizosphere microbiome, regardless of the specific community of each field, and despite microbiome responses to climate events. Seasonal patterns showed that the plant root microbiome is locally seeded, changes with plant growth, and responds to weather events. However, against this background of variation, specific taxa responded to differences in host genotype. If shown to have beneficial functions, microbes may be considered candidate traits for selective breeding.

Maize YABBY Genes drooping leaf1 and drooping leaf2 Regulate Plant Architecture.

Leaf architecture directly influences canopy structure, consequentially affecting yield. We discovered a maize (Zea mays) mutant with aberrant leaf architecture, which we named drooping leaf1 (drl1). Pleiotropic mutations in drl1 affect leaf length and width, leaf angle, and internode length and diameter. These phenotypes are enhanced by natural variation at the drl2 enhancer locus, including reduced expression of the drl2-Mo17 allele in the Mo17 inbred. A second drl2 allele, produced by transposon mutagenesis, interacted synergistically with drl1 mutants and reduced drl2 transcript levels. The drl genes are required for proper leaf patterning, development and cell proliferation of leaf support tissues, and for restricting auricle expansion at the midrib. The paralogous loci encode maize CRABS CLAW co-orthologs in the YABBY family of transcriptional regulators. The drl genes are coexpressed in incipient and emergent leaf primordia at the shoot apex, but not in the vegetative meristem or stem. Genome-wide association studies using maize NAM-RIL (nested association mapping-recombinant inbred line) populations indicated that the drl loci reside within quantitative trait locus regions for leaf angle, leaf width, and internode length and identified rare single nucleotide polymorphisms with large phenotypic effects for the latter two traits. This study demonstrates that drl genes control the development of key agronomic traits in maize.

Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain.

Tocopherols, tocotrienols, and plastochromanols (collectively termed tocochromanols) are lipid-soluble antioxidants synthesized by all plants. Their dietary intake, primarily from seed oils, provides vitamin E and other health benefits. Tocochromanol biosynthesis has been dissected in the dicot Arabidopsis thaliana, which has green, photosynthetic seeds, but our understanding of tocochromanol accumulation in major crops, whose seeds are nonphotosynthetic, remains limited. To understand the genetic control of tocochromanols in grain, we conducted a joint linkage and genome-wide association study in the 5000-line U.S. maize (Zea mays) nested association mapping panel. Fifty-two quantitative trait loci for individual and total tocochromanols were identified, and of the 14 resolved to individual genes, six encode novel activities affecting tocochromanols in plants. These include two chlorophyll biosynthetic enzymes that explain the majority of tocopherol variation, which was not predicted given that, like most major cereal crops, maize grain is nonphotosynthetic. This comprehensive assessment of natural variation in vitamin E levels in maize establishes the foundation for improving tocochromanol and vitamin E content in seeds of maize and other major cereal crops.

Mapping a male-fertility restoration locus for the A4 cytoplasmic-genic male-sterility system in pearl millet using a genotyping-by-sequencing-based linkage map.

BACKGROUND: Pearl millet (Pennisetum glaucum (L.) R. Br., syn. Cenchrus americanus (L.) R. Br) is an important cereal and fodder crop in hot and arid environments. There is great potential to improve pearl millet production through hybrid breeding. Cytoplasmic male sterility (CMS) and the corresponding nuclear fertility restoration / sterility maintenance genes (Rfs) are essential tools for economic hybrid seed production in pearl millet. Mapping the Rf genes of the A4 CMS system in pearl millet would enable more efficient introgression of both dominant male-fertility restoration alleles (Rf) and their recessive male-sterility maintenance counterparts (rf). RESULTS: A high density linkage map based on single nucleotide polymorphism (SNP) markers was generated using an F2 mapping population and genotyping-by-sequencing (GBS). The parents of this cross were 'ICMA 02777' and 'ICMR 08888', which segregate for the A4 Rf locus. The linkage map consists of 460 SNP markers distributed mostly evenly and has a total length of 462 cM. The segregation ratio of male-fertile and male-sterile plants (3:1) based on pollen production (presence/absence) indicated monogenic dominant inheritance of male-fertility restoration. Correspondingly, a major quantitative trait locus (QTL) for pollen production was found on linkage group 2, with cross-validation showing a very high QTL occurrence (97%). The major QTL was confirmed using selfed seed set as phenotypic trait, though with a lower precision. However, these QTL explained only 14.5% and 9.9% of the phenotypic variance of pollen production and selfed seed set, respectively, which was below expectation. Two functional KASP markers were developed for the identified locus. CONCLUSION: This study identified a major QTL for male-fertility restoration using a GBS-based linkage map and developed KASP markers which support high-throughput screening of the haploblock. This is a first step toward marker-assisted selection of A4 male-fertility restoration and male-sterility maintenance in pearl millet.

Association mapping across numerous traits reveals patterns of functional variation in maize.

Phenotypic variation in natural populations results from a combination of genetic effects, environmental effects, and gene-by-environment interactions. Despite the vast amount of genomic data becoming available, many pressing questions remain about the nature of genetic mutations that underlie functional variation. We present the results of combining genome-wide association analysis of 41 different phenotypes in ∼ 5,000 inbred maize lines to analyze patterns of high-resolution genetic association among of 28.9 million single-nucleotide polymorphisms (SNPs) and ∼ 800,000 copy-number variants (CNVs). We show that genic and intergenic regions have opposite patterns of enrichment, minor allele frequencies, and effect sizes, implying tradeoffs among the probability that a given polymorphism will have an effect, the detectable size of that effect, and its frequency in the population. We also find that genes tagged by GWAS are enriched for regulatory functions and are ∼ 50% more likely to have a paralog than expected by chance, indicating that gene regulation and gene duplication are strong drivers of phenotypic variation. These results will likely apply to many other organisms, especially ones with large and complex genomes like maize.

Genome-wide association of carbon and nitrogen metabolism in the maize nested association mapping population.

Carbon (C) and nitrogen (N) metabolism are critical to plant growth and development and are at the basis of crop yield and adaptation. We performed high-throughput metabolite analyses on over 12,000 samples from the nested association mapping population to identify genetic variation in C and N metabolism in maize (Zea mays ssp. mays). All samples were grown in the same field and used to identify natural variation controlling the levels of 12 key C and N metabolites, namely chlorophyll a, chlorophyll b, fructose, fumarate, glucose, glutamate, malate, nitrate, starch, sucrose, total amino acids, and total protein, along with the first two principal components derived from them. Our genome-wide association results frequently identified hits with single-gene resolution. In addition to expected genes such as invertases, natural variation was identified in key C4 metabolism genes, including carbonic anhydrases and a malate transporter. Unlike several prior maize studies, extensive pleiotropy was found for C and N metabolites. This integration of field-derived metabolite data with powerful mapping and genomics resources allows for the dissection of key metabolic pathways, providing avenues for future genetic improvement.

OLE RNA protects extremophilic bacteria from alcohol toxicity.

OLE (Ornate, Large, Extremophilic) RNAs represent a recently discovered non-coding RNA class found in extremophilic anaerobic bacteria, including certain human pathogens. OLE RNAs exhibit several unusual characteristics that indicate a potentially novel function, including exceptionally high expression and localization to cell membranes via interaction with a protein partner called OLE-associated protein (OAP). In the current study, new genetic and phenotypic characteristics of OLE RNA from Bacillus halodurans C-125 were established. OLE RNA is transcribed at high levels from its own promoter under normal growth conditions and the transcript is exceptionally stable compared to most other RNAs. Expression is increased by ∼ 7-fold when cells are exposed to near lethal concentrations of short-chain alcohols such as ethanol or methanol. Strains wherein the genes for OLE and/or OAP are deleted are more susceptible to growth inhibition by alcohol and also become more sensitive to cold. Normal growth characteristics can be restored by expressing the genes for OLE and OAP from plasmids or from elsewhere on the chromosome. Our findings confirm a functional link between OLE and OAP and reveal the importance of a large non-coding RNA in the response to alcohol-induced stress.

Sampling the Maize (Zea mays) Leaf Microbiome.

The microbiota of maize leaves can be beneficial or detrimental to the host. Foliar diseases are the most obvious detrimental impact of the leaf microbiome, though more subtle effects of the normal (nondisease) community are an active area of research. This protocol describes two specific methodologies to sample the maize leaf microbiome: one sampling the surface (epiphyte) microbiome and one sampling the interior (endophyte) microbiome. Each method begins with collected leaf tissue and finishes with a cell suspension suitable for either isolating live microbes or extracting DNA for sequencing.

Preparation of Illumina 16s Amplicon Sequencing Libraries with Peptide Nucleic Acids (PNAs) for the Analysis of Maize-Associated Microbiomes.

One of the most common methods to survey bacterial communities is targeted amplification of the hypervariable regions of the 16s rRNA gene followed by sequencing. This protocol details Illumina library preparation of such amplicons from communities isolated from maize. We include both staggered PCR primers to improve Illumina base calling and peptide nucleic acids (PNAs) to reduce the presence of plant organelles. Primers are designed with Illumina adapter sequences for the addition of sample-specific indexes (barcodes). We also briefly discuss alternative primer sets, including ones that directly discriminate against plant organelles or that amplify different organisms (e.g., fungal internal transcribed spacer [ITS] sequences).

Sampling Maize (Zea mays) Seed Endophytes.

For most farmers, the production of maize grain is the ultimate goal of the entire field season. From the point of view of plant microbiome studies, seeds are particularly interesting in that they are the only avenue for vertical transmission of microbes from parent to offspring, though microbes can also enter maize seeds via wounds or silks. Although the presence of seed endophytes is well documented, their role, if any, in seed health and their effects on the next generation of plants are largely unknown. This protocol describes the isolation of seed endophytes. Its primary focus is properly sterilizing the seed surface, followed by grinding to release the endophytes. The end product is a cell suspension suitable for either culturing or DNA analysis.

Sampling Root-Associated Microbiome Communities of Maize (Zea mays).

The soil microbiome of maize shapes its fitness, sustainability, and productivity. Accurately sampling maize's belowground microbial communities is important for identifying and characterizing these functions. Here, we describe a protocol to sample the maize rhizosphere (including the rhizoplane and endorhizosphere) and root zone (still influential but further from the root) in a form suitable for downstream analyses like culturing and DNA extractions. Although this protocol is written with Zea mays as the focus, these methods can generally be applied to any plant with similar fibrous root systems.

Sampling and Analysis of the Maize Microbiome.

Maize is an important plant for both global food security and genetics research. As the importance of microorganisms to plant health is becoming clearer, there is a growing interest in understanding the relationship between maize and its associated microbiome; i.e., the collection of microorganisms living on, around, and inside the plant. The ultimate goal of this research is to use these microbial communities to support more robust and sustainable maize production. Here, we provide an overview of recent progress in the field of maize microbiome research. We discuss the major microbiome compartments (rhizosphere, phyllosphere, and endosphere) and known functions of the microbiome. We also review the methods currently available to study the maize microbiome and its functions, and discuss how to carry out maize microbiome experiments, including both a general workflow (suitable for most microbiome analyses) and maize-specific experimental considerations.

Manipulating the Maize (Zea mays) Microbiome.

Maize (Zea mays) is a multifaceted cereal grass used globally for nutrition, animal feed, food processing, and biofuels, and a model system in genetics research. Studying the maize microbiome sometimes requires its manipulation to identify the contributions of specific taxa and ecological traits (i.e., diversity, richness, network structure) to maize growth and physiology. Due to regulatory constraints on applying engineered microorganisms in field settings, greenhouse-based experimentation is often the first step for understanding the contribution of root-associated microbiota-whether natural or engineered-to plant phenotypes. In this protocol, we describe methods to inoculate maize with a specific microbiome as a tool for understanding the microbiota's influence on its host plant. The protocol involves removal of the native seed microbiome followed by inoculation of new microorganisms; separate protocols are provided for inoculations from pure culture, from soil slurry, or by mixing in live soil. These protocols cover the most common methods for manipulating the maize microbiome in soil-grown plants in the greenhouse. The methods outlined will ultimately result in rhizosphere microbial assemblages with varying degrees of microbial diversity, ranging from low diversity (individual strain and synthetic community [SynCom] inoculation) to high diversity (percent live inoculation), with the slurry inoculation method representing an "intermediate diversity" treatment.

Genome-wide assessment of population structure and association mapping for agronomic and grain nutritional traits in proso millet (Panicum miliaceum L.).

Proso millet is an important but under-researched and underutilized crop with the potential to become a future smart crop because of its climate-resilient features and high nutrient content. Assessing diversity and marker-trait associations are essential to support the genomics-assisted improvement of proso millet. This study aimed to assess the population structure and diversity of a proso millet diversity panel and identify marker-trait associations for agronomic and grain nutrient traits. In this study, genome-wide single nucleotide polymorphisms (SNPs) were identified by mapping raw genotyping-by-sequencing (GBS) data onto the proso millet genome, resulting in 5621 quality-filtered SNPs in 160 diverse accessions. The modified Roger's Distance assessment indicated an average distance of 0.268 among accessions, with the race miliaceum exhibiting the highest diversity and ovatum the lowest. Proso millet germplasm diversity was structured according to geographic centers of origin and domestication. Genome-wide association mapping identified 40 marker-trait associations (MTAs), including 34 MTAs for agronomic traits and 6 for grain nutrients; 20 of these MTAs were located within genes. Favourable alleles and phenotypic values were estimated for all MTAs. This study provides valuable insights into the population structure and diversity of proso millet, identified marker-trait associations, and reported favourable alleles and their phenotypic values for supporting genomics-assisted improvement efforts in proso millet.

Maize seed endophytes.

Maize is a vital global crop, and each seed (kernel) hosts an ecosystem of microbes living inside it. However, we know very little about these endophytes and what their role is in plant production and physiology. In this Microreview, I summarize the major questions around maize seed endophytes, including what organisms are present, how they get there, whether and how they transmit across generations, and how they and the plant affect each other. Although several studies touch on each of these areas, ultimately there are far more questions than answers. Future priorities for research on maize seed endophytes should include understanding what adaptations allow microbes to be seed endophytes, how the host genetics and the environment affect these communities, and how maize seed endophytes ultimately contribute to the next generation of plants.

kGWASflow: a modular, flexible, and reproducible Snakemake workflow for k-mers-based GWAS.

Genome-wide association studies (GWAS) have been widely used to identify genetic variation associated with complex traits. Despite its success and popularity, the traditional GWAS approach comes with a variety of limitations. For this reason, newer methods for GWAS have been developed, including the use of pan-genomes instead of a reference genome and the utilization of markers beyond single-nucleotide polymorphisms, such as structural variations and k-mers. The k-mers-based GWAS approach has especially gained attention from researchers in recent years. However, these new methodologies can be complicated and challenging to implement. Here, we present kGWASflow, a modular, user-friendly, and scalable workflow to perform GWAS using k-mers. We adopted an existing kmersGWAS method into an easier and more accessible workflow using management tools like Snakemake and Conda and eliminated the challenges caused by missing dependencies and version conflicts. kGWASflow increases the reproducibility of the kmersGWAS method by automating each step with Snakemake and using containerization tools like Docker. The workflow encompasses supplemental components such as quality control, read-trimming procedures, and generating summary statistics. kGWASflow also offers post-GWAS analysis options to identify the genomic location and context of trait-associated k-mers. kGWASflow can be applied to any organism and requires minimal programming skills. kGWASflow is freely available on GitHub (https://github.com/akcorut/kGWASflow) and Bioconda (https://anaconda.org/bioconda/kgwasflow).