Genic and nongenic contributions to natural variation of quantitative traits in maize

Genetic interaction network of quantitative trait genes for heading date in rice

Several quantitative trait genes (QTGs) related to rice heading date, a key factor for crop development and yield, have been identified, along with complex interactions among genes. However, a comprehensive genetic interaction network for these QTGs has not yet been established. In this study, we use 18K-rice lines to identify QTGs and their epistatic interactions affecting rice heading date. We identify 264 pairs of interacting QTL and construct a comprehensive genetic network of these QTL. On average, the epistatic effects of QTL pairs are estimated to be approximately 12.5% of additive effects of identified QTL. Importantly, epistasis vary among different alleles of several heading date genes. Additionally, 57 pairs of interacting QTGs are also significant in their epistatic effects on 12 other agronomic traits. The identified QTL genetic interactions are further validated using near-isogenic lines, yeast two-hybrid, and split-luciferase complementation assays. Overall, this study provides a genetic network of rice heading date genes, which plays a crucial role in regulating rice heading date and influencing multiple related agronomic traits. This network serves as a foundation for understanding the genetic mechanisms of rice quantitative traits and for advancing rice molecular breeding.

Understanding genetic diversity in drought-adaptive hybrid parental lines in pearl millet

Information on genetic diversity and population structure is helpful to strategize enhancing the genetic base of hybrid parental lines in breeding programs. The present study determined the population structure and genetic diversity of 109 pearl millet hybrid parental lines, known for their better adaptation and performance in drought-prone environments, using 16,472 single nucleotide polymorphic (SNP) markers generated from GBS (genotyping-by-sequencing) platforms. The SNPs were distributed uniformly across the pearl millet genome and showed considerable genetic diversity (0.337), expected heterozygosity (0.334), and observed heterozygosity (0.031). Most of the pairs of lines (78.36%) had Identity-by-State (IBS) based genetic distances of more than 0.3, indicating a significant amount of genetic diversity among the parental lines. Bayesian model-based population stratification, neighbor-joining phylogenetic analysis, and principal coordinate analysis (PCoA) differentiated all hybrid parental lines into two clear-cut major groups, one each for seed parents (B-lines) and pollinators (R-lines). Majority of parental lines sharing common parentages were found grouped in the same cluster. Analysis of molecular variance (AMOVA) revealed 7% of the variation among subpopulations, and 93% of the variation was attributable to within sub-populations. Chromosome 3 had the highest number of LD regions. Genomic LD decay distance was 0.69 Mb and varied across the different chromosomes. Genetic diversity based on 11 agro-morphological and grain quality traits also suggested that the majority of the B- and R-lines were grouped into two major clusters with few overlaps. In addition, the combined analysis of phenotypic and genotypic data showed similarities in the population grouping patterns. The present study revealed the uniqueness of most of the inbred lines, which can be a valuable source of new alleles and help breeders to utilize these inbred lines for the development of hybrids in drought-prone environments.

Identification of Novel QTL for Mercury Accumulation in Maize Using an Enlarged SNP Panel

Mercury (Hg) pollution not only poses a threat to the environment but also adversely affects the growth and development of plants, with potential repercussions for animals and humans through bioaccumulation in the food chain. Maize, a crucial source of food, industrial materials, and livestock feed, requires special attention in understanding the genetic factors influencing mercury accumulation. Developing maize varieties with low mercury accumulation is vital for both maize production and human health. In this study, a comprehensive genome-wide association study (GWAS) was conducted using an enlarged SNP panel comprising 1.25 million single nucleotide polymorphisms (SNPs) in 230 maize inbred lines across three environments. The analysis identified 111 significant SNPs within 78 quantitative trait loci (QTL), involving 169 candidate genes under the Q model. Compared to the previous study, the increased marker density and optimized statistical model led to the discovery of 74 additional QTL, demonstrating improved statistical power. Gene ontology (GO) enrichment analysis revealed that most genes participate in arsenate reduction and stress responses. Notably, GRMZM2G440968, which has been reported in previous studies, is associated with the significant SNP chr6.S_155668107 in axis tissue. It encodes a cysteine proteinase inhibitor, implying its potential role in mitigating mercury toxicity by inhibiting cysteine. Haplotype analyses provided further insights, indicating that lines carrying hap3 exhibited the lowest mercury content compared to other haplotypes. In summary, our study significantly enhances the statistical power of GWAS, identifying additional genes related to mercury accumulation and metabolism. These findings offer valuable insights into unraveling the genetic basis of mercury content in maize and contribute to the development of maize varieties with low mercury accumulation.

Identification of candidate genes associated with less-photosensitive anthocyanin phenotype using an EMS mutant (pind) in eggplant (Solanum melongena L.)

Eggplant (Solanum melongena L.) is a highly nutritious and economically important vegetable crop. However, the fruit peel of eggplant often shows poor coloration owing to low-light intensity during cultivation, especially in the winter. The less-photosensitive varieties produce anthocyanin in low light or even dark conditions, making them valuable breeding materials. Nevertheless, genes responsible for anthocyanin biosynthesis in less-photosensitive eggplant varieties are not characterized. In this study, an EMS mutant, named purple in the dark (pind), was used to identify the key genes responsible for less-photosensitive coloration. Under natural conditions, the peel color and anthocyanin content in pind fruits were similar to that of wildtype '14-345'. The bagged pind fruits were light purple, whereas those of '14-345' were white; and the anthocyanin content in the pind fruit peel was significantly higher than that in '14-345'. Genetic analysis revealed that the less-photosensitive trait was controlled by a single dominant gene. The candidate gene was mapped on chromosome 10 in the region 7.72 Mb to 11.71 Mb. Thirty-five differentially expressed genes, including 12 structural genes, such as CHS, CHI, F3H, DFR, ANS, and UFGT, and three transcription factors MYB113, GL3, and TTG2, were identified in pind using RNA-seq. Four candidate genes EGP21875 (myb domain protein 113), EGP21950 (unknown protein), EGP21953 (CAAX amino-terminal protease family protein), and EGP21961 (CAAX amino-terminal protease family protein) were identified as putative genes associated with less-photosensitive anthocyanin biosynthesis in pind. These findings may clarify the molecular mechanisms underlying less-photosensitive anthocyanin biosynthesis in eggplant.

Identification of southern corn rust resistance QTNs in Chinese summer maize germplasm via multi-locus GWAS and post-GWAS analysis

Southern corn rust (SCR) caused by Puccinia polysora Underw is a major disease leading to severe yield losses in China Summer Corn Belt. Using six multi-locus GWAS methods, we identified a set of SCR resistance QTNs from a diversity panel of 140 inbred lines collected from China Summer Corn Belt. Thirteen QTNs on chromosomes 1, 2, 4, 5, 6, and 8 were grouped into three types of allele effects and their associations with SCR phenotypes were verified by post-GWAS case-control sampling, allele/haplotype effect analysis. Relative resistance (RRR) and relative susceptibility (RRs) catering to its inbred carrier were estimated from single QTN and QTN-QTN combos and epistatitic effects were estimated for QTN-QTN combos. By transcriptomic annotation, a set of candidate genes were predicted to be involved in transcriptional regulation (S5_145, Zm00001d01613, transcription factor GTE4), phosphorylation (S8_123, Zm00001d010672, Pgk2- phosphoglycerate kinase 2), and temperature stress response (S6_164a/S6_164b, Zm00001d038806, hsp101, and S5_211, Zm00001d017978, cellulase25). The breeding implications of the above findings were discussed.

A complete telomere-to-telomere assembly of the maize genome

A complete telomere-to-telomere (T2T) finished genome has been the long pursuit of genomic research. Through generating deep coverage ultralong Oxford Nanopore Technology (ONT) and PacBio HiFi reads, we report here a complete genome assembly of maize with each chromosome entirely traversed in a single contig. The 2,178.6 Mb T2T Mo17 genome with a base accuracy of over 99.99% unveiled the structural features of all repetitive regions of the genome. There were several super-long simple-sequence-repeat arrays having consecutive thymine-adenine-guanine (TAG) tri-nucleotide repeats up to 235 kb. The assembly of the entire nucleolar organizer region of the 26.8 Mb array with 2,974 45S rDNA copies revealed the enormously complex patterns of rDNA duplications and transposon insertions. Additionally, complete assemblies of all ten centromeres enabled us to precisely dissect the repeat compositions of both CentC-rich and CentC-poor centromeres. The complete Mo17 genome represents a major step forward in understanding the complexity of the highly recalcitrant repetitive regions of higher plant genomes.

Genetic Diversification of Starch Branching Enzymes during Maize Domestication and Improvement

Elucidating the genetic basis of starch pasting and gelatinization properties is crucial for enhancing the quality of maize and its utility as feed and industrial raw material. In maize, ZmSBE genes encode important starch branching enzymes in the starch biosynthesis pathway. In this study, we re-sequenced the genomic sequences of ZmSBEI, ZmSBEIIa, ZmSBEIIb, and ZmSBEIII in three lines called 335 inbred lines, 68 landrace lines, and 32 teosinte lines. Analyses of nucleotide polymorphisms and haplotype diversity revealed differences in the selection patterns of ZmSBEI, ZmSBEIIa, ZmSBEIIb, and ZmSBEIII during maize domestication and improvement. A marker-trait association analysis of inbred lines detected 22 significant loci, including 18 SNPs and 4 indels significantly associated with three maize starch physicochemical properties. The allele frequencies of two variants (SNP17249C and SNP5055G) were examined in three lines. The frequency of SNP17249C in ZmSBEIIb was highest in teosinte lines, followed by landrace lines, and inbred lines, whereas there were no significant differences in the frequency of SNP5055G in ZmSBEIII among the three lines. These results suggest that ZmSBE genes play an important role in the phenotypic variations in the starch physicochemical properties in maize. The genetic variants detected in this study may be used to develop functional markers for improving maize starch quality.

QTL mapping identifies novel major loci for kernel row number-associated ear fasciation, ear prolificacy and tillering in maize (Zea mays L.)

Maize ear fasciation originates from excessive or abnormal proliferation of the ear meristem and usually manifests as flattened multiple-tipped ear and/or disordered kernel arrangement. Ear prolificacy expresses as multiple ears per plant or per node. Both ear fasciation and prolificacy can affect grain yield. The genetic control of the two traits was studied using two recombinant inbred line populations (B73 × Lo1016 and Lo964 × Lo1016) with Lo1016 and Lo964 as donors of ear fasciation and prolificacy, respectively. Ear fasciation-related traits, number of kernel rows (KRN), ear prolificacy and number of tillers were phenotyped in multi-year field experiments. Ear fasciation traits and KRN showed relatively high heritability (h ² > 0.5) except ratio of ear diameters. For all ear fasciation-related traits, fasciation level positively correlated with KRN (0.30 ≤ r ≤ 0.68). Prolificacy and tillering were not correlated and their h ² ranged from 0.41 to 0.78. QTL mapping identified four QTLs for ear fasciation, on chromosomes 1 (two QTLs), 5 and 7, the latter two overlapping with QTLs for number of kernel rows. Notably, at these QTLs, the Lo1016 alleles increased both ear fasciation and KRN across populations, thus showing potential breeding applicability. Four and five non-overlapping QTLs were mapped for ear prolificacy and tillering, respectively. Two ear fasciation QTLs, qFas1.2 and qFas7, overlapped with fasciation QTLs mapped in other studies and spanned compact plant2 and ramosa1 candidate genes. Our study identified novel ear fasciation loci and alleles positively affecting grain yield components, and ear prolificacy and tillering loci which are unexpectedly still segregating in elite maize materials, contributing useful information for genomics-assisted breeding programs.

ABA-inducible DEEPER ROOTING 1 improves adaptation of maize to water deficiency

Root architecture remodelling is critical for forage moisture in water-limited soil. DEEPER ROOTING 1 (DRO1) in Oryza, Arabidopsis, and Prunus has been reported to improve drought avoidance by promoting roots to grow downward and acquire water from deeper soil. In the present study, we found that ZmDRO1 responded more strongly to abscisic acid (ABA)/drought induction in Zea mays ssp. mexicana, an ancestral species of cultivated maize, than in B73. It was proposed that this is one of the reasons why Zea mays ssp. mexicana has a more noticeable change in the downward direction angle of the root and fewer biomass penalties under water-deficient conditions. Thus, a robust, synthetic ABA/drought-inducible promoter was used to control the expression of ZmDRO1^B73 in Arabidopsis and cultivated maize for drought-resistant breeding. Interestingly, ABA-inducible ZmDRO1 promoted a larger downward root angle and improved grain yield by more than 40% under water-limited conditions. Collectively, these results revealed that different responses to ABA/drought induction of ZmDRO1 confer different drought avoidance abilities, and we demonstrated the application of ZmDRO1 via an ABA-inducible strategy to alter the root architecture of modern maize to improve drought adaptation in the field.

A comprehensive map of preferentially located motifs reveals distinct proximal cis-regulatory sequences in plants

Identification of cis-regulatory sequences controlling gene expression is an arduous challenge that is being actively explored to discover key genetic factors responsible for traits of agronomic interest. Here, we used a genome-wide de novo approach to investigate preferentially located motifs (PLMs) in the proximal cis-regulatory landscape of Arabidopsis thaliana and Zea mays. We report three groups of PLMs in both the 5'- and 3'-gene-proximal regions and emphasize conserved PLMs in both species, particularly in the 3'-gene-proximal region. Comparison with resources from transcription factor and microRNA binding sites shows that 79% of the identified PLMs are unassigned, although some are supported by MNase-defined cistrome occupancy analysis. Enrichment analyses further reveal that unassigned PLMs provide functional predictions that differ from those derived from transcription factor and microRNA binding sites. Our study provides a comprehensive map of PLMs and demonstrates their potential utility for future characterization of orphan genes in plants.

Whole genome resequencing reveals signatures of rapid selection in a virus-affected commercial fishery

Infectious diseases are recognized as one of the greatest global threats to biodiversity and ecosystem functioning. Consequently, there is a growing urgency to understand the speed at which adaptive phenotypes can evolve and spread in natural populations to inform future management. Here we provide evidence of rapid genomic changes in wild Australian blacklip abalone (Haliotis rubra) following a major population crash associated with an infectious disease. Genome scans on H. rubra were performed using pooled whole genome resequencing data from commercial fishing stocks varying in historical exposure to haliotid herpesvirus-1 (HaHV-1). Approximately 25,000 single nucleotide polymorphism loci associated with virus exposure were identified, many of which mapped to genes known to contribute to HaHV-1 immunity in the New Zealand pāua (Haliotis iris) and herpesvirus response pathways in haliotids and other animal systems. These findings indicate genetic changes across a single generation in H. rubra fishing stocks decimated by HaHV-1, with stock recovery potentially determined by rapid evolutionary changes leading to virus resistance. This is a novel example of apparently rapid adaptation in natural populations of a nonmodel marine organism, highlighting the pace at which selection can potentially act to counter disease in wildlife communities.

Exploring the diversity of promoter and 5'UTR sequences in ancestral, historic and modern wheat

A data set of promoter and 5'UTR sequences of homoeo-alleles of 459 wheat genes that contribute to agriculturally important traits in 95 ancestral and commercial wheat cultivars is presented here. The high-stringency myBaits technology used made individual capture of homoeo-allele promoters possible, which is reported here for the first time. Promoters of most genes are remarkably conserved across the 83 hexaploid cultivars used with <7 haplotypes per promoter and 21% being identical to the reference Chinese Spring. InDels and many high-confidence SNPs are located within predicted plant transcription factor binding sites, potentially changing gene expression. Most haplotypes found in the Watkins landraces and a few haplotypes found in Triticum monococcum, germplasms hitherto not thought to have been used in modern wheat breeding, are already found in many commercial hexaploid wheats. The full data set which is useful for genomic and gene function studies and wheat breeding is available at https://rrescloud.rothamsted.ac.uk/index.php/s/DMCFDu5iAGTl50u/authenticate.

Impacts of environmental conditions, and allelic variation of cytosolic glutamine synthetase on maize hybrid kernel production

Cytosolic glutamine synthetase (GS1) is the enzyme mainly responsible of ammonium assimilation and reassimilation in maize leaves. The agronomic potential of GS1 in maize kernel production was investigated by examining the impact of an overexpression of the enzyme in the leaf cells. Transgenic hybrids exhibiting a three-fold increase in leaf GS activity were produced and characterized using plants grown in the field. Several independent hybrids overexpressing Gln1-3, a gene encoding cytosolic (GS1), in the leaf and bundle sheath mesophyll cells were grown over five years in different locations. On average, a 3.8% increase in kernel yield was obtained in the transgenic hybrids compared to controls. However, we observed that such an increase was simultaneously dependent upon both the environmental conditions and the transgenic event for a given field trial. Although variable from one environment to another, significant associations were also found between two GS1 genes (Gln1-3 and Gln1-4) polymorphic regions and kernel yield in different locations. We propose that the GS1 enzyme is a potential lead for producing high yielding maize hybrids using either genetic engineering or marker-assisted selection. However, for these hybrids, yield increases will be largely dependent upon the environmental conditions used to grow the plants.

Amiour et al. use a multi-year field trial evaluation and association mapping to determine if increased enzyme activity and native allelic variations at the GS1 loci in maize contribute to differences in grain yield. Overexpression of GS1 and polymorphisms in the corresponding loci were associated with kernel yield, indicating that GS1 expression can directly control kernel production and that GS1 has a potential lead in the production of high yielding maize hybrids depending on environmental conditions.

A forward genetics approach integrating genome-wide association study and expression quantitative trait locus mapping to dissect leaf development in maize (Zea mays)

The characterization of the genetic basis of maize (Zea mays) leaf development may support breeding efforts to obtain plants with higher vigor and productivity. In this study, a mapping panel of 197 biparental and multiparental maize recombinant inbred lines (RILs) was analyzed for multiple leaf traits at the seedling stage. RNA sequencing was used to estimate the transcription levels of 29 573 gene models in RILs and to derive 373 769 single nucleotide polymorphisms (SNPs), and a forward genetics approach combining these data was used to pinpoint candidate genes involved in leaf development. First, leaf traits were correlated with gene expression levels to identify transcript-trait correlations. Then, leaf traits were associated with SNPs in a genome-wide association (GWA) study. An expression quantitative trait locus mapping approach was followed to associate SNPs with gene expression levels, prioritizing candidate genes identified based on transcript-trait correlations and GWAs. Finally, a network analysis was conducted to cluster all transcripts in 38 co-expression modules. By integrating forward genetics approaches, we identified 25 candidate genes highly enriched for specific functional categories, providing evidence supporting the role of vacuolar proton pumps, cell wall effectors, and vesicular traffic controllers in leaf growth. These results tackle the complexity of leaf trait determination and may support precision breeding in maize.

A quantitative genomics map of rice provides genetic insights and guides breeding

Extensive allelic variation in agronomically important genes serves as the basis of rice breeding. Here, we present a comprehensive map of rice quantitative trait nucleotides (QTNs) and inferred QTN effects based on eight genome-wide association study cohorts. Population genetic analyses revealed that domestication, local adaptation and heterosis are all associated with QTN allele frequency changes. A genome navigation system, RiceNavi, was developed for QTN pyramiding and breeding route optimization, and implemented in the improvement of a widely cultivated indica variety. This work presents an efficient platform that bridges ever-increasing genomic knowledge and diverse improvement needs in rice.

Using single-plant-omics in the field to link maize genes to functions and phenotypes

Most of our current knowledge on plant molecular biology is based on experiments in controlled laboratory environments. However, translating this knowledge from the laboratory to the field is often not straightforward, in part because field growth conditions are very different from laboratory conditions. Here, we test a new experimental design to unravel the molecular wiring of plants and study gene-phenotype relationships directly in the field. We molecularly profiled a set of individual maize plants of the same inbred background grown in the same field and used the resulting data to predict the phenotypes of individual plants and the function of maize genes. We show that the field transcriptomes of individual plants contain as much information on maize gene function as traditional laboratory-generated transcriptomes of pooled plant samples subject to controlled perturbations. Moreover, we show that field-generated transcriptome and metabolome data can be used to quantitatively predict individual plant phenotypes. Our results show that profiling individual plants in the field is a promising experimental design that could help narrow the lab-field gap.

Profiling Novel Alternative Splicing within Multiple Tissues Provides Useful Insights into Porcine Genome Annotation

Alternative splicing (AS) is a process during gene expression that results in a single gene coding for different protein variants. AS contributes to transcriptome and proteome diversity. In order to characterize AS in pigs, genome-wide transcripts and AS events were detected using RNA sequencing of 34 different tissues in Duroc pigs. In total, 138,403 AS events and 29,270 expressed genes were identified. An alternative donor site was the most common AS form and accounted for 44% of the total AS events. The percentage of the other three AS forms (exon skipping, alternative acceptor site, and intron retention) was approximately 19%. The results showed that the most common AS events involving alternative donor sites could produce different transcripts or proteins that affect the biological processes. The expression of genes with tissue-specific AS events showed that gene functions were consistent with tissue functions. AS increased proteome diversity and resulted in novel proteins that gained or lost important functional domains. In summary, these findings extend porcine genome annotation and highlight roles that AS could play in determining tissue identity.

Genomic Prediction Informed by Biological Processes Expands Our Understanding of the Genetic Architecture Underlying Free Amino Acid Traits in Dry Arabidopsis Seeds

Plant growth, development, and nutritional quality depends upon amino acid homeostasis, especially in seeds. However, our understanding of the underlying genetics influencing amino acid content and composition remains limited, with only a few candidate genes and quantitative trait loci identified to date. Improved knowledge of the genetics and biological processes that determine amino acid levels will enable researchers to use this information for plant breeding and biological discovery. Toward this goal, we used genomic prediction to identify biological processes that are associated with, and therefore potentially influence, free amino acid (FAA) composition in seeds of the model plant Arabidopsis thaliana. Markers were split into categories based on metabolic pathway annotations and fit using a genomic partitioning model to evaluate the influence of each pathway on heritability explained, model fit, and predictive ability. Selected pathways included processes known to influence FAA composition, albeit to an unknown degree, and spanned four categories: amino acid, core, specialized, and protein metabolism. Using this approach, we identified associations for pathways containing known variants for FAA traits, in addition to finding new trait-pathway associations. Markers related to amino acid metabolism, which are directly involved in FAA regulation, improved predictive ability for branched chain amino acids and histidine. The use of genomic partitioning also revealed patterns across biochemical families, in which serine-derived FAAs were associated with protein related annotations and aromatic FAAs were associated with specialized metabolic pathways. Taken together, these findings provide evidence that genomic partitioning is a viable strategy to uncover the relative contributions of biological processes to FAA traits in seeds, offering a promising framework to guide hypothesis testing and narrow the search space for candidate genes.

Evolutionary and functional genomics of DNA methylation in maize domestication and improvement

DNA methylation is a ubiquitous chromatin feature, present in 25% of cytosines in the maize genome, but variation and evolution of the methylation landscape during maize domestication remain largely unknown. Here, we leverage whole-genome sequencing (WGS) and whole-genome bisulfite sequencing (WGBS) data on populations of modern maize, landrace, and teosinte (Zea mays ssp. parviglumis) to estimate epimutation rates and selection coefficients. We find weak evidence for direct selection on DNA methylation in any context, but thousands of differentially methylated regions (DMRs) are identified population-wide that are correlated with recent selection. For two trait-associated DMRs, vgt1-DMR and tb1-DMR, HiChIP data indicate that the interactive loops between DMRs and respective downstream genes are present in B73, a modern maize line, but absent in teosinte. Our results enable a better understanding of the evolutionary forces acting on patterns of DNA methylation and suggest a role of methylation variation in adaptive evolution.

Variation and evolution of DNA methylation during maize domestication remain largely unknown. Here, the authors generate genome and methylome sequencing data as well as HiChIP-based interactome data to investigate the adaptive and phenotypic consequences of methylation variations in maize.

Construction of a dense genetic map of the Malus fusca fire blight resistant accession MAL0045 using tunable genotyping-by-sequencing SNPs and microsatellites

Although, the Pacific crabapple, Malus fusca, is a hardy and disease resistant species, studies relating to the genetics of its unique traits are very limited partly due to the lack of a genetic map of this interesting wild apple. An accession of M. fusca (MAL0045) of Julius Kühn-Institut collection in Germany is highly resistant to fire blight disease, incited by different strains of the causative pathogen—Erwinia amylovora. This is the most destructive bacterial disease of Malus of which most of the domesticated apples (Malus domestica) are susceptible. Using a scarcely dense genetic map derived from a population of 134 individuals of MAL0045 × ‘Idared’, the locus (Mfu10) controlling fire blight resistance mapped on linkage group 10 (LG10) and explained up to 66% of the phenotypic variance with different strains. Although the development of robust and tightly linked molecular markers on LG10 through chromosome walking approach led to the identification of a major candidate gene, any minor effect locus remained elusive possibly due to the lack of marker density of the entire genetic map. Therefore, we have developed a dense genetic map of M. fusca using tunable genotyping-by-sequencing (tGBS) approach. Of thousands of de novo SNPs identified, 2677 were informative in M. fusca and 90.5% of these successfully mapped. In addition, integration of SNP data and microsatellite (SSR) data resulted in a final map comprising 17 LGs with 613 loci spanning 1081.35 centi Morgan (cM). This map will serve as a template for mapping using different strains of the pathogen.

Two Clubroot-Resistance Genes, Rcr3 and Rcr9wa, Mapped in Brassica rapa Using Bulk Segregant RNA Sequencing

Genetic resistance is widely used to manage clubroot (Plasmodiophora brassicae) in brassica crops, but new pathotypes have recently been identified on canola (Brassica napus) on the Canadian prairies. Resistance effective against both the most prevalent pathotype (3H, based on the Canadian Clubroot Differential system) and the new pathotypes is needed. BC₁ plants of Brassica rapa from a cross of line 96-6990-2 (clubroot resistance originating from turnip cultivar ‘Waaslander’) and a susceptible doubled-haploid line, ACDC, exhibited a 1:1 segregation for resistance against pathotypes 3H and 5X. A resistance gene designated as Rcr3 was mapped initially based on the percentage of polymorphic variants using bulked segregant RNA sequencing (BSR-Seq) and further mapped using Kompetitive Allele Specific PCR. DNA variants were identified by assembling short reads against a reference genome of B. rapa. Rcr3 was mapped into chromosome A08. It was flanked by single nucleotide polymorphisms (SNP) markers (A90_A08_SNP_M12 and M16) between 10.00 and 10.23 Mb, in an interval of 231.6 Kb. There were 32 genes in the Rcr3 interval. Three genes (Bra020951, Bra020974, and Bra020979) were annotated with disease resistance mechanisms, which are potential candidates for Rcr3. Another resistance gene, designated as Rcr9^wa, for resistance to pathotype 5X was mapped, with the flanking markers (A90_A08_SNP_M28 and M79) between 10.85 and 11.17 Mb using the SNP sites identified through BSR-Seq for Rcr3. There were 44 genes in the Rcr9^wa interval, three of which (Bra020827, Bra020828, Bra020814) were annotated as immune-system-process related genes, which are potential candidates for Rcr9^wa.

Common gardens in teosintes reveal the establishment of a syndrome of adaptation to altitude

In plants, local adaptation across species range is frequent. Yet, much has to be discovered on its environmental drivers, the underlying functional traits and their molecular determinants. Genome scans are popular to uncover outlier loci potentially involved in the genetic architecture of local adaptation, however links between outliers and phenotypic variation are rarely addressed. Here we focused on adaptation of teosinte populations along two elevation gradients in Mexico that display continuous environmental changes at a short geographical scale. We used two common gardens, and phenotyped 18 traits in 1664 plants from 11 populations of annual teosintes. In parallel, we genotyped these plants for 38 microsatellite markers as well as for 171 outlier single nucleotide polymorphisms (SNPs) that displayed excess of allele differentiation between pairs of lowland and highland populations and/or correlation with environmental variables. Our results revealed that phenotypic differentiation at 10 out of the 18 traits was driven by local selection. Trait covariation along the elevation gradient indicated that adaptation to altitude results from the assembly of multiple co-adapted traits into a complex syndrome: as elevation increases, plants flower earlier, produce less tillers, display lower stomata density and carry larger, longer and heavier grains. The proportion of outlier SNPs associating with phenotypic variation, however, largely depended on whether we considered a neutral structure with 5 genetic groups (73.7%) or 11 populations (13.5%), indicating that population stratification greatly affected our results. Finally, chromosomal inversions were enriched for both SNPs whose allele frequencies shifted along elevation as well as phenotypically-associated SNPs. Altogether, our results are consistent with the establishment of an altitudinal syndrome promoted by local selective forces in teosinte populations in spite of detectable gene flow. Because elevation mimics climate change through space, SNPs that we found underlying phenotypic variation at adaptive traits may be relevant for future maize breeding.

Challenges of Translating Gene Regulatory Information into Agronomic Improvements

Improvement of agricultural species has exploited the genetic variation responsible for complex quantitative traits. Much of the functional variation is regulatory, in cis-regulatory elements and trans-acting factors that ultimately contribute to gene expression differences. However, the identification of gene regulatory network components that, when modulated, will increase plant productivity or resilience, is challenging, yet essential to provide increased predictive power for genome engineering approaches that are likely to benefit useful traits. Here, we discuss the opportunities and limitations of using data obtained from gene coexpression, transcription factor binding, and genome-wide association mapping analyses to predict regulatory interactions that impact crop improvement. It is apparent that a combination of information from these data types is necessary for the reliable identification and utilization of important regulatory interactions that underlie complex agronomic traits.

Dynamic Patterns of Transcript Abundance of Transposable Element Families in Maize

Transposable Elements (TEs) are mobile elements that contribute the majority of DNA sequences in the maize genome. Due to their repetitive nature, genomic studies of TEs are complicated by the difficulty of properly attributing multi-mapped short reads to specific genomic loci. Here, we utilize a method to attribute RNA-seq reads to TE families rather than particular loci in order to characterize transcript abundance for TE families in the maize genome. We applied this method to assess per-family expression of transposable elements in >800 published RNA-seq libraries representing a range of maize development, genotypes, and hybrids. While a relatively small proportion of TE families are transcribed, expression is highly dynamic with most families exhibiting tissue-specific expression. A large number of TE families were specifically detected in pollen and endosperm, consistent with reproductive dynamics that maintain silencing of TEs in the germ line. We find that B73 transcript abundance is a poor predictor of TE expression in other genotypes and that transcript levels can differ even for shared TEs. Finally, by assessing recombinant inbred line and hybrid transcriptomes, complex patterns of TE transcript abundance across genotypes emerged. Taken together, this study reveals a dynamic contribution of TEs to maize transcriptomes.

Identification of Markers Associated with Yield Traits and Morphological Features in Maize (Zea mays L.)

Association mapping is a powerful approach to detect associations between traits of interest and genetic markers based on linkage disequilibrium in molecular plant breeding. The aim of this study was the identification of single nucleotide polymorphisms (SNPs) and SilicoDArT markers associated with yield traits and morphological features in maize. Plant material constituted inbred lines. The field experiment with inbred lines was established on 10 m² plots in a set of complete random blocks in three replicates. We observed 22 quantitative traits. Association mapping was performed in this study using a method based on the mixed linear model with the population structure estimated by eigenanalysis (principal component analysis applied to all markers) and modeled by random effects. As a result of mapping, 969 markers (346 SNPs and 623 SilocoDArT) were selected from 49,911 identified polymorphic molecular markers, which were significantly associated with the analyzed morphological features and yield structure traits. Markers associated with five or six traits were selected during further analyses, including SilicoDArT 4591115 (anthocyanin coloration of anthers, length of main axis above the highest lateral branch, cob length, number of grains per cob, weight of fresh grains per cob and weight of fresh grains per cob at 15% moisture), SilicoDArT 7059939 (anthocyanin coloration of glumes of cob, time of anthesis—50% of flowering plants, time of silk emergence—50% of flowering plants, anthocyanin coloration of anthers and cob diameter), SilicoDArT 5587991 (anthocyanin coloration of glumes of cob, time of anthesis—50% of flowering plants, anthocyanin coloration of anthers, curvature of lateral branches and number of rows of grain). The two genetic similarity dendrograms between the inbred lines were constructed based on all significant SNPs and SilicoDArT markers. On both dendrograms lines clustered according to the kernel structure (flint, dent) and origin. The selected markers may be useful in predicting hybrid formulas in a heterosis culture. The present study demonstrated that molecular SNP and Silico DArT markers could be used in this species to group lines in terms of origin and lines with incomplete origin data. They can also be useful in maize in predicting the hybrid formula and can find applications in the selection of parental components for heterosis crossings.

Identifying loci with breeding potential across temperate and tropical adaptation via EigenGWAS and EnvGWAS

Understanding the genomic basis of adaptation in maize is important for gene discovery and the improvement of breeding germplasm, but much remains a mystery in spite of significant population genetics and archaeological research. Identifying the signals underpinning adaptation are challenging as adaptation often coincided with genetic drift, and the base genomic diversity of the species in massive. In this study, tGBS technology was used to genotype 1,143 diverse maize accessions including landraces collected from 20 countries and elite breeding lines of tropical lowland, highland, subtropical/midaltitude and temperate ecological zones. Based on 355,442 high‐quality single nucleotide polymorphisms, 13 genomic regions were detected as being under selection using the bottom‐up searching strategy, EigenGWAS. Of the 13 selection regions, 10 were first reported, two were associated with environmental parameters via EnvGWAS, and 146 genes were enriched. Combining large‐scale genomic and ecological data in this diverse maize panel, our study supports a polygenic adaptation model of maize and offers a framework to enhance our understanding of both the mechanistic basis and the evolutionary consequences of maize domestication and adaptation. The regions identified here are promising candidates for further, targeted exploration to identify beneficial alleles and haplotypes for deployment in maize breeding.

Perspectives on the Application of Genome-Editing Technologies in Crop Breeding

Most conventional and modern crop-improvement methods exploit natural or artificially induced genetic variations and require laborious characterization of the progenies of multiple generations derived from time-consuming genetic crosses. Genome-editing systems, in contrast, provide the means to rapidly modify genomes in a precise and predictable way, making it possible to introduce improvements directly into elite varieties. Here, we describe the range of applications available to agricultural researchers using existing genome-editing tools. In addition to providing examples of genome-editing applications in crop breeding, we discuss the technical and social challenges faced by breeders using genome-editing tools for crop improvement.

Analysis of trait heritability in functionally partitioned rice genomes

Knowledge of the genetic architecture of importantly agronomical traits can speed up genetic improvement in cultivated rice (Oryza sativa L.). Many recent investigations have leveraged genome-wide association studies (GWAS) to identify single nucleotide polymorphisms (SNPs), associated with agronomic traits in various rice populations. The reported trait-relevant SNPs appear to be arbitrarily distributed along the genome, including genic and nongenic regions. Whether the SNPs in different genomic regions play different roles in trait heritability and which region is more responsible for phenotypic variation remains opaque. We analyzed a natural rice population of 524 accessions with 3,616,597 SNPs to compare the genetic contributions of functionally distinct genomic regions for five agronomic traits, i.e., yield, heading date, plant height, grain length, and grain width. An analysis of heritability in the functionally partitioned rice genome showed that regulatory or intergenic regions account for the most trait heritability. A close look at the trait-associated SNPs (TASs) indicated that the majority of the TASs are located in nongenic regions, and the genetic effects of the TASs in nongenic regions are generally greater than those in genic regions. We further compared the predictabilities using the genetic variants from genic regions with those using nongenic regions. The results revealed that nongenic regions play a more important role than genic regions in trait heritability in rice, which is consistent with findings in humans and maize. This conclusion not only offers clues for basic research to disclose genetics behind these agronomic traits, but also provides a new perspective to facilitate genomic selection in rice.

Association of candidate genes with drought tolerance traits in zoysiagrass germplasm

Drought stress negatively influences the growth and physiology of perennial grasses. The objective of this study was to identify associations of candidate genes with drought tolerance traits in 96 zoysiagrass (Zoysia Willd.) accessions. Germplasm varied largely in leaf wilting, canopy and air temperature difference (CAD), leaf water content (LWC), chlorophyll fluorescence (Fv/Fm), leaf dry weight (LDW), stolon dry weight (SDW), rhizome dry weight (RZW), and root dry weight (RDW) under drought stress across the two experiments in 2014 and 2015 in a greenhouse. The population exhibited three subgroups based on molecular marker analysis and had minimum relative kinship. Associations between single nucleotide polymorphisms (SNPs) in BADH encoding betaine aldehyde dehydrogenase, DREB1 encoding DREB-like protein 1, Ndhf encoding NADH dehydrogenase subunit F, CAT encoding catalase, and VP1 encoding H⁺-pyrophosphatase were analyzed with trait under drought stress (D) and relative values compared to the control (R). Twenty-seven mark and trait associations were detected in year 2014, 2015, and a two-year combination across four genes, including 13 associations in 7 SNP loci in BADH, 9 associations in 5 SNP loci in DREB1, 3 associations in one SNP locus in Ndhf, and 2 associations in one SNP locus in CAT. Of them, one SNP in BADH was associated with D-RDW or D-SDW, three SNPs in DREB1 were associated with D-RZW, D-RDW, R-LWC, and D-CAD, and one SNP in CAT was associated with D-SDW. Nucleotide changes in these SNP loci caused non-synonymous amino acid substitutions. The results indicated that allelic diversity in genes involved in antioxidant metabolism, osmotic homeostasis, and dehydration responsive transcription factor could contribute to growth and physiological variations in zoysiagrass under drought stress.

Genome-wide nucleotide patterns and potential mechanisms of genome divergence following domestication in maize and soybean

BACKGROUND

Plant domestication provides a unique model to study genome evolution. Many studies have been conducted to examine genes, genetic diversity, genome structure, and epigenome changes associated with domestication. Interestingly, domesticated accessions have significantly higher [A] and [T] values across genome-wide polymorphic sites than accessions sampled from the corresponding progenitor species. However, the relative contributions of different genomic regions to this genome divergence pattern and underlying mechanisms have not been well characterized.

RESULTS

Here, we investigate the genome-wide base-composition patterns by analyzing millions of SNPs segregating among 100 accessions from a teosinte-maize comparison set and among 302 accessions from a wild-domesticated soybean comparison set. We show that non-genic part of the genome has a greater contribution than genic SNPs to the [AT]-increase observed between wild and domesticated accessions in maize and soybean. The separation between wild and domesticated accessions in [AT] values is significantly enlarged in non-genic and pericentromeric regions. Motif frequency and sequence context analyses show the motifs (PyCG) related to solar-UV signature are enriched in these regions, particularly when they are methylated. Additional analysis using population-private SNPs also implicates the role of these motifs in relatively recent mutations. With base-composition across polymorphic sites as a genome phenotype, genome scans identify a set of putative candidate genes involved in UV damage repair pathways.

CONCLUSIONS

The [AT]-increase is more pronounced in genomic regions that are non-genic, pericentromeric, transposable elements; methylated; and with low recombination. Our findings establish important links among UV radiation, mutation, DNA repair, methylation, and genome evolution.

Natural variation of ZmHKT1 affects root morphology in maize at the seedling stage

Eight variants in ZmHKT1 promoter were significantly associated with root diameter, four haplotypes based on these significant variants were found, and Hap2 has the largest root diameter. Roots play an important role in uptake of water, nutrients and plant anchorage. Identification of gene and corresponding SNPs associated with root traits would enable develop maize lines with better root traits that might help to improve capacity for absorbing nutrients and water acquisition. The genomic sequences of a salt tolerance gene ZmHKT1 was resequenced in 349 maize inbred lines, and the association between nucleotide polymorphisms and seedling root traits was detected. A total of 269 variants in ZmHKT1 were identified, including 226 single nucleotide polymorphisms and 43 insertions and deletions. The gene displayed high level of nucleotide diversity, especially in non-genic regions. A total of 19 variations in untranslated region of ZmHKT1 were found to be associated with six seedling traits. Eight variants in promoter region were significantly associated with average root diameter (ARD), four haplotypes were found based on these significant variants, and Hap2 has the largest ARD. Two SNPs in high-linkage disequilibrium (SNP-415 and SNP 2169) with pleiotropic effects were significantly associated with plant height, root surface area, root volume, and shoot dry weight. This result revealed that ZmHKT1 was an important contributor to the phenotypic variations of seedling root traits in maize, these significant variants could use to develop functional markers to improve root traits.

Technological advances in maize breeding: past, present and future

Maize has for many decades been both one of the most important crops worldwide and one of the primary genetic model organisms. More recently, maize breeding has been impacted by rapid technological advances in sequencing and genotyping technology, transformation including genome editing, doubled haploid technology, parallelled by progress in data sciences and the development of novel breeding approaches utilizing genomic information. Herein, we report on past, current and future developments relevant for maize breeding with regard to (1) genome analysis, (2) germplasm diversity characterization and utilization, (3) manipulation of genetic diversity by transformation and genome editing, (4) inbred line development and hybrid seed production, (5) understanding and prediction of hybrid performance, (6) breeding methodology and (7) synthesis of opportunities and challenges for future maize breeding.

Next-Generation Sequencing Accelerates Crop Gene Discovery

The identification and isolation of genes underlying quantitative trait loci (QTLs) associated with agronomic traits in crops have been recently accelerated thanks to next-generation sequencing (NGS)-based technologies combined with plant genetics. With NGS, various revisited genetic approaches, which benefited from higher marker density, have been elaborated. These approaches improved resolution in QTL position and assisted in determining functional causative variations in genes. Examples of QTLs/genes associated with agronomic traits in crops and identified using different strategies based on whole-genome sequencing (WGS)/whole-genome resequencing (WGR) or RNA-seq are presented and discussed in this review. More specifically, we summarize and illustrate how NGS boosted bulk-segregant analysis (BSA), expression profiling, and the construction of polymorphism databases to facilitate the detection of QTLs and causative genes.

Stability Analysis of Kernel Quality Traits in Exotic-Derived Doubled Haploid Maize Lines

Variation in kernel composition across maize ( L.) germplasm is affected by a combination of the plant's genotype, the environment in which it is grown, and the interaction between these two elements. Adapting exotic germplasm to the US Corn Belt is highly dependent on the plant's genotype, the environment where it is grown, and the interaction between these components. Phenotypic plasticity is ill-defined when specific exotic germplasm is moved over large latitudinal distances and for the adapted variants being created. Reduced plasticity (or stability) is desired for the adapted variants, as it allows for a more rapid implementation into breeding programs throughout the Corn Belt. Here, doubled haploid lines derived from exotic maize and adapted through backcrossing exotic germplasm to elite adapted lines were used in conjunction with genome-wide association studies to explore stability in four kernel composition traits. Genotypes demonstrated a response to environments that paralleled the mean response of all genotypes used across all traits, with protein content and kernel density exhibiting the highest levels of Type II stability. Genes such as , , and were identified as potential candidates within quantitative trait locus regions. The findings within this study aid in validating previously identified genomic regions and identified novel genomic regions affecting kernel quality traits.

Genomic prediction of bull fertility in US Jersey dairy cattle

Service sire has a major effect on reproductive success in dairy cattle. Recent studies have reported accurate predictions for Holstein bull fertility using genomic data. The objective of this study was to assess the feasibility of genomic prediction of sire conception rate (SCR) in US Jersey cattle using alternative predictive models. Data set consisted of 1.5k Jersey bulls with SCR records and 95k SNP covering the entire genome. The analyses included the use of linear and Gaussian kernel-based models fitting either all the SNP or subsets of markers with presumed functional roles, such as SNP significantly associated with SCR or SNP located within or close to annotated genes. Model predictive ability was evaluated using 5-fold cross-validation with 10 replicates. The entire SNP set exhibited predictive correlations around 0.30. Interestingly, either SNP marginally associated with SCR or genic SNP achieved higher predictive abilities than their counterparts using random sets of SNP. Among alternative SNP subsets, Gaussian kernel models fitting significant SNP achieved the best performance with increases in predictive correlation up to 7% compared with the standard whole-genome approach. Notably, the use of a multi-breed reference population including the entire US Holstein SCR data set (11.5k bulls) allowed us to achieve predictive correlations up to 0.315, gaining 8% in accuracy compared with the standard model fitting a pure Jersey reference set. Overall, our findings indicate that genomic prediction of Jersey bull fertility is feasible. The use of Gaussian kernels fitting markers with relevant roles and the inclusion of Holstein records in the training set seem to be promising alternatives to the standard whole-genome approach. These results have the potential to help the dairy industry improve US Jersey sire fertility through accurate genome-guided decisions.

Semiautomated Feature Extraction from RGB Images for Sorghum Panicle Architecture GWAS

Because structural variation in the inflorescence architecture of cereal crops can influence yield, it is of interest to identify the genes responsible for this variation. However, the manual collection of inflorescence phenotypes can be time consuming for the large populations needed to conduct genome-wide association studies (GWAS) and is difficult for multidimensional traits such as volume. A semiautomated phenotyping pipeline, TIM (Toolkit for Inflorescence Measurement), was developed and used to extract unidimensional and multidimensional features from images of 1,064 sorghum (Sorghum bicolor) panicles from 272 genotypes comprising a subset of the Sorghum Association Panel. GWAS detected 35 unique single-nucleotide polymorphisms associated with variation in inflorescence architecture. The accuracy of the TIM pipeline is supported by the fact that several of these trait-associated single-nucleotide polymorphisms (TASs) are located within chromosomal regions associated with similar traits in previously published quantitative trait locus and GWAS analyses of sorghum. Additionally, sorghum homologs of maize (Zea mays) and rice (Oryza sativa) genes known to affect inflorescence architecture are enriched in the vicinities of TASs. Finally, our TASs are enriched within genomic regions that exhibit high levels of divergence between converted tropical lines and cultivars, consistent with the hypothesis that these chromosomal intervals were targets of selection during modern breeding.

Genetic architecture underlying the lignin biosynthesis pathway involves noncoding RNAs and transcription factors for growth and wood properties in Populus

Lignin provides structural support in perennial woody plants and is a complex phenolic polymer derived from phenylpropanoid pathway. Lignin biosynthesis is regulated by coordinated networks involving transcription factors (TFs), microRNAs (miRNAs) and long noncoding RNAs (lncRNAs). However, the genetic networks underlying the lignin biosynthesis pathway for tree growth and wood properties remain unknown. Here, we used association genetics (additive, dominant and epistasis) and expression quantitative trait nucleotide (eQTN) mapping to decipher the genetic networks for tree growth and wood properties in 435 unrelated individuals of Populus tomentosa. We detected 124 significant associations (P ≤ 6.89E-05) for 10 growth and wood property traits using 30 265 single nucleotide polymorphisms from 203 lignin biosynthetic genes, 81 TF genes, 36 miRNA genes and 71 lncRNA loci, implying their common roles in wood formation. Epistasis analysis uncovered 745 significant pairwise interactions, which helped to construct proposed genetic networks of lignin biosynthesis pathway and found that these regulators might affect phenotypes by linking two lignin biosynthetic genes. eQTNs were used to interpret how causal genes contributed to phenotypes. Lastly, we investigated the possible functions of the genes encoding 4-coumarate: CoA ligase and cinnamate-4-hydroxylase in wood traits using epistasis, eQTN mapping and enzymatic activity assays. Our study provides new insights into the lignin biosynthesis pathway in poplar and enables the novel genetic factors as biomarkers for facilitating genetic improvement of trees.

The western Mediterranean region provided the founder population of domesticated narrow-leafed lupin

This study revealed that the western Mediterranean provided the founder population for domesticated narrow-leafed lupin and that genetic diversity decreased significantly during narrow-leafed lupin domestication. The evolutionary history of plants during domestication profoundly shaped the genome structure and genetic diversity of today's crops. Advances in next-generation sequencing technologies allow unprecedented opportunities to understand genome evolution in minor crops, which constitute the majority of plant domestications. A diverse set of 231 wild and domesticated narrow-leafed lupin (Lupinus angustifolius L.) accessions were subjected to genotyping-by-sequencing using diversity arrays technology. Phylogenetic, genome-wide divergence and linkage disequilibrium analyses were applied to identify the founder population of domesticated narrow-leafed lupin and the genome-wide effect of domestication on its genome. We found wild western Mediterranean population as the founder of domesticated narrow-leafed lupin. Domestication was associated with an almost threefold reduction in genome diversity in domesticated accessions compared to their wild relatives. Selective sweep analysis identified no significant footprints of selection around domestication loci. A genome-wide association study identified single nucleotide polymorphism markers associated with pod dehiscence. This new understanding of the genomic consequences of narrow-leafed lupin domestication along with molecular marker tools developed here will assist plant breeders more effectively access wild genetic diversity for crop improvement.

Empirical Comparisons of Different Statistical Models To Identify and Validate Kernel Row Number-Associated Variants from Structured Multi-parent Mapping Populations of Maize

Advances in next generation sequencing technologies and statistical approaches enable genome-wide dissection of phenotypic traits via genome-wide association studies (GWAS). Although multiple statistical approaches for conducting GWAS are available, the power and cross-validation rates of many approaches have been mostly tested using simulated data. Empirical comparisons of single variant (SV) and multi-variant (MV) GWAS approaches have not been conducted to test if a single approach or a combination of SV and MV is effective, through identification and cross-validation of trait-associated loci. In this study, kernel row number (KRN) data were collected from a set of 6,230 entries derived from the Nested Association Mapping (NAM) population and related populations. Three different types of GWAS analyses were performed: 1) single-variant (SV), 2) stepwise regression (STR) and 3) a Bayesian-based multi-variant (BMV) model. Using SV, STR, and BMV models, 257, 300, and 442 KRN-associated variants (KAVs) were identified in the initial GWAS analyses. Of these, 231 KAVs were subjected to genetic validation using three unrelated populations that were not included in the initial GWAS. Genetic validation results suggest that the three GWAS approaches are complementary. Interestingly, KAVs in low recombination regions were more likely to exhibit associations in independent populations than KAVs in recombinationally active regions, probably as a consequence of linkage disequilibrium. The KAVs identified in this study have the potential to enhance our understanding of the genetic basis of ear development.

Genome-wide discovery of DNA polymorphisms by whole genome sequencing differentiates weedy and cultivated rice

Analyzing the genome level DNA polymorphisms between weedy and cultivated rice is crucial to elucidate the molecular basis of weedy and agronomic traits, which in turn can enhance our ability to control weedy rice and its utilization for rice improvement. Here, we presented the genome-wide genetic variations between a weedy rice accession PSRR-1 and two cultivated rice accessions, Bengal and Nona Bokra, belonging to japonica and indica subspecies, respectively. The total number of SNPs and InDels in PSRR/Bengal was similar to that of Nona Bokra/Bengal, but was three times greater than that of PSRR/Nona Bokra. There were 11546 large-effect SNPs/InDels affecting 5673 genes, which most likely differentiated weedy rice from cultivated rice. These large effect DNA polymorphisms were mostly resulted in stop codon gain and least by start codon loss. Analysis of the molecular functions and biological processes of weedy rice specific SNPs/InDels indicated that most of these genes were involved in protein modification/phosphorylation, protein kinase activity, and protein/nucleotide binding. By integrating previous QTL mapping results with the DNA polymorphisms data, the candidate genes for seed dormancy and seed shattering were narrowed down. The genomic resource generated in this study will facilitate discovery of functional variants for weedy and agronomic traits.

Phenotypic Data from Inbred Parents Can Improve Genomic Prediction in Pearl Millet Hybrids

Pearl millet is a non-model grain and fodder crop adapted to extremely hot and dry environments globally. In India, a great deal of public and private sectors' investment has focused on developing pearl millet single cross hybrids based on the cytoplasmic-genetic male sterility (CMS) system, while in Africa most pearl millet production relies on open pollinated varieties. Pearl millet lines were phenotyped for both the inbred parents and hybrids stage. Many breeding efforts focus on phenotypic selection of inbred parents to generate improved parental lines and hybrids. This study evaluated two genotyping techniques and four genomic selection schemes in pearl millet. Despite the fact that 6× more sequencing data were generated per sample for RAD-seq than for tGBS, tGBS yielded more than 2× as many informative SNPs (defined as those having MAF > 0.05) than RAD-seq. A genomic prediction scheme utilizing only data from hybrids generated prediction accuracies (median) ranging from 0.73-0.74 (1000-grain weight), 0.87-0.89 (days to flowering time), 0.48-0.51 (grain yield) and 0.72-0.73 (plant height). For traits with little to no heterosis, hybrid only and hybrid/inbred prediction schemes performed almost equivalently. For traits with significant mid-parent heterosis, the direct inclusion of phenotypic data from inbred lines significantly (P < 0.05) reduced prediction accuracy when all lines were analyzed together. However, when inbreds and hybrid trait values were both scored relative to the mean trait values for the respective populations, the inclusion of inbred phenotypic datasets moderately improved genomic predictions of the hybrid genomic estimated breeding values. Here we show that modern approaches to genotyping by sequencing can enable genomic selection in pearl millet. While historical pearl millet breeding records include a wealth of phenotypic data from inbred lines, we demonstrate that the naive incorporation of this data into a hybrid breeding program can reduce prediction accuracy, while controlling for the effects of heterosis per se allowed inbred genotype and trait data to improve the accuracy of genomic estimated breeding values for pearl millet hybrids.

Development of Target Sequence Capture and Estimation of Genomic Relatedness in a Mixed Oak Stand

Anticipating the evolutionary responses of long-lived organisms, such as trees, to environmental changes, requires the assessment of genetic variation of adaptive traits in natural populations. To this end, high-density markers are needed to calculate genomic relatedness between individuals allowing to estimate the genetic variance of traits in wild populations. We designed a targeted capture-based, next-generation sequencing assay based on the highly heterozygous pedunculate oak (Quercus robur) reference genome, for the sequencing of 3 Mb of genic and intergenic regions. Using a mixed stand of 293 Q. robur and Q. petraea genotypes we successfully captured over 97% of the target sequences, corresponding to 0.39% of the oak genome, with sufficient depth (97×) for the detection of about 190,000 SNPs evenly spread over the targeted regions. We validated the technique by evaluating its reproducibility, and comparing the genomic relatedness of trees with their known pedigree relationship. We explored the use of the technique on other related species and highlighted the advantages and limitations of this approach. We found that 92.07% of target sequences in Q. suber and 70.36% of sequences in Fagus sylvatica were captured. We used this SNP resource to estimate genetic relatedness in the mixed oak stand. Mean pairwise genetic relatedness was low within each species with a few values exceeding 0.25 (half-sibs) or 0.5 (full-sibs). Finally, we applied the technique to a long-standing issue in population genetics of trees regarding the relationship between inbreeding and components of fitness. We found very weak signals for inbreeding depression for reproductive success and no signal for growth within both species.

Construction of a High-Density Genetic Map from RNA-Seq Data for an Arabidopsis Bay-0 × Shahdara RIL Population

High-density genetic maps are essential for high resolution mapping of quantitative traits. Here, we present a new genetic map for an Arabidopsis Bayreuth × Shahdara recombinant inbred line (RIL) population, built on RNA-seq data. RNA-seq analysis on 160 RILs of this population identified 30,049 single-nucleotide polymorphisms (SNPs) covering the whole genome. Based on a 100-kbp window SNP binning method, 1059 bin-markers were identified, physically anchored on the genome. The total length of the RNA-seq genetic map spans 471.70 centimorgans (cM) with an average marker distance of 0.45 cM and a maximum marker distance of 4.81 cM. This high resolution genotyping revealed new recombination breakpoints in the population. To highlight the advantages of such high-density map, we compared it to two publicly available genetic maps for the same population, comprising 69 PCR-based markers and 497 gene expression markers derived from microarray data, respectively. In this study, we show that SNP markers can effectively be derived from RNA-seq data. The new RNA-seq map closes many existing gaps in marker coverage, saturating the previously available genetic maps. Quantitative trait locus (QTL) analysis for published phenotypes using the available genetic maps showed increased QTL mapping resolution and reduced QTL confidence interval using the RNA-seq map. The new high-density map is a valuable resource that facilitates the identification of candidate genes and map-based cloning approaches.

tGBS® genotyping-by-sequencing enables reliable genotyping of heterozygous loci

Conventional genotyping-by-sequencing (cGBS) strategies suffer from high rates of missing data and genotyping errors, particularly at heterozygous sites. tGBS® genotyping-by-sequencing is a novel method of genome reduction that employs two restriction enzymes to generate overhangs in opposite orientations to which (single-strand) oligos rather than (double-stranded) adaptors are ligated. This strategy ensures that only double-digested fragments are amplified and sequenced. The use of oligos avoids the necessity of preparing adaptors and the problems associated with inter-adaptor annealing/ligation. Hence, the tGBS protocol simplifies the preparation of high-quality GBS sequencing libraries. During polymerase chain reaction (PCR) amplification, selective nucleotides included at the 3'-end of the PCR primers result in additional genome reduction as compared to cGBS. By adjusting the number of selective bases, different numbers of genomic sites are targeted for sequencing. Therefore, for equivalent amounts of sequencing, more reads per site are available for SNP calling. Hence, as compared to cGBS, tGBS delivers higher SNP calling accuracy (>97-99%), even at heterozygous sites, less missing data per marker across a population of samples, and an enhanced ability to genotype rare alleles. tGBS is particularly well suited for genomic selection, which often requires the ability to genotype populations of individuals that are heterozygous at many loci.

Genome resequencing and transcriptome profiling reveal structural diversity and expression patterns of constitutive disease resistance genes in Huanglongbing-tolerant Poncirus trifoliata and its hybrids

Huanglongbing (HLB) is the most destructive bacterial disease of citrus worldwide. While most citrus varieties are susceptible to HLB, Poncirus trifoliata, a close relative of Citrus, and some of its hybrids with Citrus are tolerant to HLB. No specific HLB tolerance genes have been identified in P. trifoliata but recent studies have shown that constitutive disease resistance (CDR) genes were expressed at much higher levels in HLB-tolerant Poncirus hybrids and the expression of CDR genes was modulated by Candidatus Liberibacter asiaticus (CLas), the pathogen of HLB. The current study was undertaken to mine and characterize the CDR gene family in Citrus and Poncirus and to understand its association with HLB tolerance in Poncirus. We identified 17 CDR genes in two citrus genomes, deduced their structures, and investigated their phylogenetic relationships. We revealed that the expansion of the CDR family in Citrus seems to be due to segmental and tandem duplication events. Through genome resequencing and transcriptome sequencing, we identified eight CDR genes in the Poncirus genome (PtCDR1-PtCDR8). The number of SNPs was the highest in PtCDR2 and the lowest in PtCDR7. Most of the deletion and insertion events were observed in the UTR regions of Citrus and Poncirus CDR genes. PtCDR2 and PtCDR8 were in abundance in the leaf transcriptomes of two HLB-tolerant Poncirus genotypes and were also upregulated in HLB-tolerant, Poncirus hybrids as revealed by real-time PCR analysis. These two CDR genes seem to be good candidate genes for future studies of their role in citrus-CLas interactions.

Substantial contribution of genetic variation in the expression of transcription factors to phenotypic variation revealed by eRD-GWAS

BACKGROUND

There are significant limitations in existing methods for the genome-wide identification of genes whose expression patterns affect traits.

RESULTS

The transcriptomes of five tissues from 27 genetically diverse maize inbred lines were deeply sequenced to identify genes exhibiting high and low levels of expression variation across tissues or genotypes. Transcription factors are enriched among genes with the most variation in expression across tissues, as well as among genes with higher-than-median levels of variation in expression across genotypes. In contrast, transcription factors are depleted among genes whose expression is either highly stable or highly variable across genotypes. We developed a Bayesian-based method for genome-wide association studies (GWAS) in which RNA-seq-based measures of transcript accumulation are used as explanatory variables (eRD-GWAS). The ability of eRD-GWAS to identify true associations between gene expression variation and phenotypic diversity is supported by analyses of RNA co-expression networks, protein-protein interaction networks, and gene regulatory networks. Genes associated with 13 traits were identified using eRD-GWAS on a panel of 369 maize inbred lines. Predicted functions of many of the resulting trait-associated genes are consistent with the analyzed traits. Importantly, transcription factors are significantly enriched among trait-associated genes identified with eRD-GWAS.

CONCLUSIONS

eRD-GWAS is a powerful tool for associating genes with traits and is complementary to SNP-based GWAS. Our eRD-GWAS results are consistent with the hypothesis that genetic variation in transcription factor expression contributes substantially to phenotypic diversity.

Distinct genetic architectures for phenotype means and plasticities in Zea mays

Phenotypic plasticity describes the phenotypic variation of a trait when a genotype is exposed to different environments. Understanding the genetic control of phenotypic plasticity in crops such as maize is of paramount importance for maintaining and increasing yields in a world experiencing climate change. Here, we report the results of genome-wide association analyses of multiple phenotypes and two measures of phenotypic plasticity in a maize nested association mapping (US-NAM) population grown in multiple environments and genotyped with ~2.5 million single-nucleotide polymorphisms. We show that across all traits the candidate genes for mean phenotype values and plasticity measures form structurally and functionally distinct groups. Such independent genetic control suggests that breeders will be able to select semi-independently for mean phenotype values and plasticity, thereby generating varieties with both high mean phenotype values and levels of plasticity that are appropriate for the target performance environments.

Increased Power To Dissect Adaptive Traits in Global Sorghum Diversity Using a Nested Association Mapping Population

Adaptation of domesticated species to diverse agroclimatic regions has led to abundant trait diversity. However, the resulting population structure and genetic heterogeneity confounds association mapping of adaptive traits. To address this challenge in sorghum [Sorghum bicolor (L.) Moench]-a widely adapted cereal crop-we developed a nested association mapping (NAM) population using 10 diverse global lines crossed with an elite reference line RTx430. We characterized the population of 2214 recombinant inbred lines at 90,000 SNPs using genotyping-by-sequencing. The population captures ∼70% of known global SNP variation in sorghum, and 57,411 recombination events. Notably, recombination events were four- to fivefold enriched in coding sequences and 5' untranslated regions of genes. To test the power of the NAM population for trait dissection, we conducted joint linkage mapping for two major adaptive traits, flowering time and plant height. We precisely mapped several known genes for these two traits, and identified several additional QTL. Considering all SNPs simultaneously, genetic variation accounted for 65% of flowering time variance and 75% of plant height variance. Further, we directly compared NAM to genome-wide association mapping (using panels of the same size) and found that flowering time and plant height QTL were more consistently identified with the NAM population. Finally, for simulated QTL under strong selection in diversity panels, the power of QTL detection was up to three times greater for NAM vs. association mapping with a diverse panel. These findings validate the NAM resource for trait mapping in sorghum, and demonstrate the value of NAM for dissection of adaptive traits.