Allelic genome structural variations in maize detected by array comparative genome hybridization

Accurate prediction of quantitative traits with failed SNP calls in canola and maize

In modern plant breeding, genomic selection is becoming the gold standard to select superior genotypes in large breeding populations that are only partially phenotyped. Many breeding programs commonly rely on single-nucleotide polymorphism (SNP) markers to capture genome-wide data for selection candidates. For this purpose, SNP arrays with moderate to high marker density represent a robust and cost-effective tool to generate reproducible, easy-to-handle, high-throughput genotype data from large-scale breeding populations. However, SNP arrays are prone to technical errors that lead to failed allele calls. To overcome this problem, failed calls are often imputed, based on the assumption that failed SNP calls are purely technical. However, this ignores the biological causes for failed calls-for example: deletions-and there is increasing evidence that gene presence-absence and other kinds of genome structural variants can play a role in phenotypic expression. Because deletions are frequently not in linkage disequilibrium with their flanking SNPs, permutation of missing SNP calls can potentially obscure valuable marker-trait associations. In this study, we analyze published datasets for canola and maize using four parametric and two machine learning models and demonstrate that failed allele calls in genomic prediction are highly predictive for important agronomic traits. We present two statistical pipelines, based on population structure and linkage disequilibrium, that enable the filtering of failed SNP calls that are likely caused by biological reasons. For the population and trait examined, prediction accuracy based on these filtered failed allele calls was competitive to standard SNP-based prediction, underlying the potential value of missing data in genomic prediction approaches. The combination of SNPs with all failed allele calls or the filtered allele calls did not outperform predictions with only SNP-based prediction due to redundancy in genomic relationship estimates.

Copy Number Variation among Resistance Genes Analogues in Brassica napus

Copy number variations (CNVs) are defined as deletions, duplications and insertions among individuals of a species. There is growing evidence that CNV is a major factor underlining various autoimmune disorders and diseases in humans; however, in plants, especially oilseed crops, the role of CNVs in disease resistance is not well studied. Here, we investigate the genome-wide diversity and genetic properties of CNVs in resistance gene analogues (RGAs) across eight Brassica napus lines. A total of 1137 CNV events (704 deletions and 433 duplications) were detected across 563 RGAs. The results show CNVs are more likely to occur across clustered RGAs compared to singletons. In addition, 112 RGAs were linked to a blackleg resistance QTL, of which 25 were affected by CNV. Overall, we show that the presence and abundance of CNVs differ between lines, suggesting that in B. napus, the distribution of CNVs depends on genetic background. Our findings advance the understanding of CNV as an important type of genomic structural variation in B. napus and provide a resource to support breeding of advanced canola lines.

Advances and applications of single-cell omics technologies in plant research

Single-cell sequencing approaches reveal the intracellular dynamics of individual cells and answer biological questions with high-dimensional catalogs of millions of cells, including genomics, transcriptomics, chromatin accessibility, epigenomics, and proteomics data across species. These emerging yet thriving technologies have been fully embraced by the field of plant biology, with a constantly expanding portfolio of applications. Here, we introduce the current technical advances used for single-cell omics, especially single-cell genome and transcriptome sequencing. Firstly, we overview methods for protoplast and nucleus isolation and genome and transcriptome amplification. Subsequently, we use well-executed benchmarking studies to highlight advances made through the application of single-cell omics techniques. Looking forward, we offer a glimpse of additional hurdles and future opportunities that will introduce broad adoption of single-cell sequencing with revolutionary perspectives in plant biology.

Genomic structural variation in tomato and its role in plant immunity

It is well known that large genomic variations can greatly impact the phenotype of an organism. Structural Variants (SVs) encompass any genomic variation larger than 30 base pairs, and include changes caused by deletions, inversions, duplications, transversions, and other genome modifications. Due to their size and complex nature, until recently, it has been difficult to truly capture these variations. Recent advances in sequencing technology and computational analyses now permit more extensive studies of SVs in plant genomes. In tomato, advances in sequencing technology have allowed researchers to sequence hundreds of genomes from tomatoes, and tomato relatives. These studies have identified SVs related to fruit size and flavor, as well as plant disease response, resistance/susceptibility, and the ability of plants to detect pathogens (immunity). In this review, we discuss the implications for genomic structural variation in plants with a focus on its role in tomato immunity. We also discuss how advances in sequencing technology have led to new discoveries of SVs in more complex genomes, the current evidence for the role of SVs in biotic and abiotic stress responses, and the outlook for genetic modification of SVs to advance plant breeding objectives.

Megabase-scale presence-absence variation with Tripsacum origin was under selection during maize domestication and adaptation

BACKGROUND

Structural variants (SVs) significantly drive genome diversity and environmental adaptation for diverse species. Unlike the prevalent small SVs (< kilobase-scale) in higher eukaryotes, large-size SVs rarely exist in the genome, but they function as one of the key evolutionary forces for speciation and adaptation.

RESULTS

In this study, we discover and characterize several megabase-scale presence-absence variations (PAVs) in the maize genome. Surprisingly, we identify a 3.2 Mb PAV fragment that shows high integrity and is present as complete presence or absence in the natural diversity panel. This PAV is embedded within the nucleolus organizer region (NOR), where the suppressed recombination is found to maintain the PAV against the evolutionary variation. Interestingly, by analyzing the sequence of this PAV, we not only reveal the domestication trace from teosinte to modern maize, but also the footprints of its origin from Tripsacum, shedding light on a previously unknown contribution from Tripsacum to the speciation of Zea species. The functional consequence of the Tripsacum segment migration is also investigated, and environmental fitness conferred by the PAV may explain the whole segment as a selection target during maize domestication and improvement.

CONCLUSIONS

These findings provide a novel perspective that Tripsacum contributes to Zea speciation, and also instantiate a strategy for evolutionary and functional analysis of the "fossil" structure variations during genome evolution and speciation.

CRISPR-Cas9-mediated 75.5-Mb inversion in maize

CRISPR-Cas is a powerful double-strand-break technology with wide-ranging applications from gene discovery to commercial product development. Thus far, this tool has been almost exclusively used for gene knockouts and deletions, with a few examples of gene edits and targeted gene insertions. Here, we demonstrate the application of CRISPR-Cas9 technology to mediate targeted 75.5-Mb pericentric inversion in chromosome 2 in one of the elite maize inbred lines from Corteva Agriscience. This inversion unlocks a large chromosomal region containing substantial genetic variance for recombination, thus providing opportunities for the development of new maize varieties with improved phenotypes.

A multigenotype maize silk expression atlas reveals how exposure-related stresses are mitigated following emergence from husk leaves

The extraordinarily long stigmatic silks of corn (Zea mays L.) are critical for grain production but the biology of their growth and emergence from husk leaves has remained underexplored. Accordingly, gene expression was assayed for inbreds 'B73' and 'Mo17' across five contiguous silk sections. Half of the maize genes (∼20,000) are expressed in silks, mostly in spatiotemporally dynamic patterns. In particular, emergence triggers strong differential expression of ∼1,500 genes collectively enriched for gene ontology terms associated with abiotic and biotic stress responses, hormone signaling, cell-cell communication, and defense metabolism. Further, a meta-analysis of published maize transcriptomic studies on seedling stress showed that silk emergence elicits an upregulated transcriptomic response that overlaps strongly with both abiotic and biotic stress responses. Although the two inbreds revealed similar silk transcriptomic programs overall, genotypic expression differences were observed for 5,643 B73-Mo17 syntenic gene pairs and collectively account for >50% of genome-wide expression variance. Coexpression clusters, including many based on genotypic divergence, were identified and interrogated via ontology-term enrichment analyses to generate biological hypotheses for future research. Ultimately, dissecting how gene expression changes along the length of silks and between husk-encased and emerged states offers testable models for silk development and plant response to environmental stresses.

Genome-wide variations analysis of sorghum cultivar Hongyingzi for brewing Moutai liquor

Background

Hongyingzi is a sorghum (Sorghum bicolor L. Moench) cultivar for brewing Moutai liquor. For an overall understanding of the whole genome of Hongyingzi, we performed whole-genome resequencing technology to reveal its comprehensive variations.

Results

Compared with the BTx623 reference genome, we uncovered 1,885,774 single nucleotide polymorphisms (SNPs), 309,381 small fragments insertions and deletions (Indels), 31,966 structural variations (SVs), and 217,273 copy number variations (CNVs). These alterations conferred 29,614 gene variations. It was also predicted that 35 gene variations were related to the multidrug and toxic efflux (MATE) transporter, chalcone synthase (CHS), ATPase isoform 10 (AHA10) transporter, dihydroflavonol-4-reductase (DFR), the laccase 15 (LAC15), flavonol 3′-hydroxylase (F3′H), flavanone 3-hydroxylase (F3H), O-methyltransferase (OMT), flavonoid 3′5′ hydroxylase (F3′5′H), UDP-glucose:sterol-glucosyltransferase (SGT), flavonol synthase (FLS), and chalcone isomerase (CHI) involved in the tannin synthesis.

Conclusions

These results would provide theoretical supports for the molecular markers developments and gene function studies related to the tannin synthesis, and the genetic improvement of liquor-making sorghum based on the genome editing technology.

Gene presence-absence variation associates with quantitative Verticillium longisporum disease resistance in Brassica napus

Although copy number variation (CNV) and presence-absence variation (PAV) have been discovered in selected gene families in most crop species, the global prevalence of these polymorphisms in most complex genomes is still unclear and their influence on quantitatively inherited agronomic traits is still largely unknown. Here we analyze the association of gene PAV with resistance of oilseed rape (Brassica napus) against the important fungal pathogen Verticillium longisporum, as an example for a complex, quantitative disease resistance in the strongly rearranged genome of a recent allopolyploid crop species. Using Single Nucleotide absence Polymorphism (SNaP) markers to efficiently trace PAV in breeding populations, we significantly increased the resolution of loci influencing V. longisporum resistance in biparental and multi-parental mapping populations. Gene PAV, assayed by resequencing mapping parents, was observed in 23-51% of the genes within confidence intervals of quantitative trait loci (QTL) for V. longisporum resistance, and high-priority candidate genes identified within QTL were all affected by PAV. The results demonstrate the prominent role of gene PAV in determining agronomic traits, suggesting that this important class of polymorphism should be exploited more systematically in future plant breeding.

Structural genome analysis in cultivated potato taxa

KEY MESSAGE

Twelve potato accessions were selected to represent two principal views on potato taxonomy. The genomes were sequenced and analyzed for structural variation (copy number variation) against three published potato genomes. The common potato (Solanum tuberosum L.) is an important staple crop with a highly heterozygous and complex tetraploid genome. The other taxa of cultivated potato contain varying ploidy levels (2X-5X), and structural variations are common in the genomes of these species, likely contributing to the diversification or agronomic traits during domestication. Increased understanding of the genomes and genomic variation will aid in the exploration of novel agronomic traits. Thus, sequencing data from twelve potato landraces, representing the four ploidy levels, were used to identify structural genomic variation compared to the two currently available reference genomes, a double monoploid potato genome and a diploid inbred clone of S. chacoense. The results of a copy number variation analysis showed that in the majority of the genomes, while the number of deletions is greater than the number of duplications, the number of duplicated genes is greater than the number of deleted ones. Specific regions in the twelve potato genomes have a high density of CNV events. Further, the auxin-induced SAUR genes (involved in abiotic stress), disease resistance genes and the 2-oxoglutarate/Fe(II)-dependent oxygenase superfamily proteins, among others, had increased copy numbers in these sequenced genomes relative to the references.

CNVmap: A Method and Software To Detect and Map Copy Number Variants from Segregation Data

Single nucleotide polymorphisms (SNPs) are used widely for detecting quantitative trait loci, or for searching for causal variants of diseases. Nevertheless, structural variations such as copy-number variants (CNVs) represent a large part of natural genetic diversity, and contribute significantly to trait variation. Numerous methods and softwares based on different technologies (amplicons, CGH, tiling, or SNP arrays, or sequencing) have already been developed to detect CNVs, but they bypass a wealth of information such as genotyping data from segregating populations, produced, e.g., for QTL mapping. Here, we propose an original method to both detect and genetically map CNVs using mapping panels. Specifically, we exploit the apparent heterozygous state of duplicated loci: peaks in appropriately defined genome-wide allelic profiles provide highly specific signatures that identify the nature and position of the CNVs. Our original method and software can detect and map automatically up to 33 different predefined types of CNVs based on segregation data only. We validate this approach on simulated and experimental biparental mapping panels in two maize populations and one wheat population. Most of the events found correspond to having just one extra copy in one of the parental lines, but the corresponding allelic value can be that of either parent. We also find cases with two or more additional copies, especially in wheat, where these copies locate to homeologues. More generally, our computational tool can be used to give additional value, at no cost, to many datasets produced over the past decade from genetic mapping panels.

High throughput genotyping of structural variations in a complex plant genome using an original Affymetrix® axiom® array

Background

Insertions/deletions (InDels) and more specifically presence/absence variations (PAVs) are pervasive in several species and have strong functional and phenotypic effect by removing or drastically modifying genes. Genotyping of such variants on large panels remains poorly addressed, while necessary for approaches such as association mapping or genomic selection.

Results

We have developed, as a proof of concept, a new high-throughput and affordable approach to genotype InDels. We first identified 141,000 InDels by aligning reads from the B73 line against the genome of three temperate maize inbred lines (F2, PH207, and C103) and reciprocally. Next, we designed an Affymetrix® Axiom® array to target these InDels, with a combination of probes selected at breakpoint sites (13%) or within the InDel sequence, either at polymorphic (25%) or non-polymorphic sites (63%) sites. The final array design is composed of 662,772 probes and targets 105,927 InDels, including PAVs ranging from 35 bp to 129kbp. After Affymetrix® quality control, we successfully genotyped 86,648 polymorphic InDels (82% of all InDels interrogated by the array) on 445 maize DNA samples with 422,369 probes. Genotyping InDels using this approach produced a highly reliable dataset, with low genotyping error (~ 3%), high call rate (~ 98%), and high reproducibility (> 95%). This reliability can be further increased by combining genotyping of several probes calling the same InDels (< 0.1% error rate and > 99.9% of call rate for 5 probes). This “proof of concept” tool was used to estimate the kinship matrix between 362 maize lines with 57,824 polymorphic InDels. This InDels kinship matrix was highly correlated with kinship estimated using SNPs from Illumina 50 K SNP arrays.

Conclusions

We efficiently genotyped thousands of small to large InDels on a sizeable number of individuals using a new Affymetrix® Axiom® array. This powerful approach opens the way to studying the contribution of InDels to trait variation and heterosis in maize. The approach is easily extendable to other species and should contribute to decipher the biological impact of InDels at a larger scale.

Expression profiles of cell-wall related genes vary broadly between two common maize inbreds during stem development

Background

The cellular machinery for cell wall synthesis and metabolism is encoded by members of large multi-gene families. Maize is both a genetic model for grass species and a potential source of lignocellulosic biomass from crop residues. Genetic improvement of maize for its utility as a bioenergy feedstock depends on identification of the specific gene family members expressed during secondary wall development in stems.

Results

High-throughput sequencing of transcripts expressed in developing rind tissues of stem internodes provided a comprehensive inventory of cell wall-related genes in maize (Zea mays, cultivar B73). Of 1239 of these genes, 854 were expressed among the internodes at ≥95 reads per 20 M, and 693 of them at ≥500 reads per 20 M. Grasses have cell wall compositions distinct from non-commelinid species; only one-quarter of maize cell wall-related genes expressed in stems were putatively orthologous with those of the eudicot Arabidopsis. Using a slope-metric algorithm, five distinct patterns for sub-sets of co-expressed genes were defined across a time course of stem development. For the subset of genes associated with secondary wall formation, fifteen sequence motifs were found in promoter regions. The same members of gene families were often expressed in two maize inbreds, B73 and Mo17, but levels of gene expression between them varied, with 30% of all genes exhibiting at least a 5-fold difference at any stage. Although presence-absence and copy-number variation might account for much of these differences, fold-changes of expression of a CADa and a FLA11 gene were attributed to polymorphisms in promoter response elements.

Conclusions

Large genetic variation in maize as a species precludes the extrapolation of cell wall-related gene expression networks even from one common inbred line to another. Elucidation of genotype-specific expression patterns and their regulatory controls will be needed for association panels of inbreds and landraces to fully exploit genetic variation in maize and other bioenergy grass species.

Connecting genome structural variation with complex traits in crop plants

Structural genome variation is a major determinant of useful trait diversity. We describe how genome analysis methods are enabling discovery of trait-associated structural variants and their potential impact on breeding. As our understanding of complex crop genomes continues to grow, there is growing evidence that structural genome variation plays a major role in determining traits important for breeding and agriculture. Identifying the extent and impact of structural variants in crop genomes is becoming increasingly feasible with ongoing advances in the sophistication of genome sequencing technologies, particularly as it becomes easier to generate accurate long sequence reads on a genome-wide scale. In this article, we discuss the origins of structural genome variation in crops from ancient and recent genome duplication and polyploidization events and review high-throughput methods to assay such variants in crop populations in order to find associations with phenotypic traits. There is increasing evidence from such studies that gene presence-absence and copy number variation resulting from segmental chromosome exchanges may be at the heart of adaptive variation of crops to counter abiotic and biotic stress factors. We present examples from major crops that demonstrate the potential of pangenomic diversity as a key resource for future plant breeding for resilience and sustainability.

Variational Inference for Coupled Hidden Markov Models Applied to the Joint Detection of Copy Number Variations

Hidden Markov models provide a natural statistical framework for the detection of the copy number variations (CNV) in genomics. In this context, we define a hidden Markov process that underlies all individuals jointly in order to detect and to classify genomics regions in different states (typically, deletion, normal or amplification). Structural variations from different individuals may be dependent. It is the case in agronomy where varietal selection program exists and species share a common phylogenetic past. We propose to take into account these dependencies inthe HMM model. When dealing with a large number of series, maximum likelihood inference (performed classically using the EM algorithm) becomes intractable. We thus propose an approximate inference algorithm based on a variational approach (VEM), implemented in the CHMM R package. A simulation study is performed to assess the performance of the proposed method and an application to the detection of structural variations in plant genomes is presented.

Modeling copy number variation in the genomic prediction of maize hybrids

Our study indicates that copy variants may play an essential role in the phenotypic variation of complex traits in maize hybrids. Moreover, predicting hybrid phenotypes by combining additive-dominance effects with copy variants has the potential to be a viable predictive model. Non-additive effects resulting from the actions of multiple loci may influence trait variation in single-cross hybrids. In addition, complementation of allelic variation could be a valuable contributor to hybrid genetic variation, especially when crossing inbred lines with higher contents of copy gains. With this in mind, we aimed (1) to study the association between copy number variation (CNV) and hybrid phenotype, and (2) to compare the predictive ability (PA) of additive and additive-dominance genomic best linear unbiased prediction model when combined with the effects of CNV in two datasets of maize hybrids (USP and HELIX). In the USP dataset, we observed a significant negative phenotypic correlation of low magnitude between copy number loss and plant height, revealing a tendency that more copy losses lead to lower plants. In the same set, when CNV was combined with the additive plus dominance effects, the PA significantly increased only for plant height under low nitrogen. In this case, CNV effects explicitly capture relatedness between individuals and add extra information to the model. In the HELIX dataset, we observed a pronounced difference in PA between additive (0.50) and additive-dominance (0.71) models for predicting grain yield, suggesting a significant contribution of dominance. We conclude that copy variants may play an essential role in the phenotypic variation of complex traits in maize hybrids, although the inclusion of CNVs into datasets does not return significant gains concerning PA.

The Genome Sequence of the Wild Tomato Solanum pimpinellifolium Provides Insights Into Salinity Tolerance

Solanum pimpinellifolium, a wild relative of cultivated tomato, offers a wealth of breeding potential for desirable traits such as tolerance to abiotic and biotic stresses. Here, we report the genome assembly and annotation of S. pimpinellifolium 'LA0480.' Moreover, we present phenotypic data from one field experiment that demonstrate a greater salinity tolerance for fruit- and yield-related traits in S. pimpinellifolium compared with cultivated tomato. The 'LA0480' genome assembly size (811 Mb) and the number of annotated genes (25,970) are within the range observed for other sequenced tomato species. We developed and utilized the Dragon Eukaryotic Analyses Platform (DEAP) to functionally annotate the 'LA0480' protein-coding genes. Additionally, we used DEAP to compare protein function between S. pimpinellifolium and cultivated tomato. Our data suggest enrichment in genes involved in biotic and abiotic stress responses. To understand the genomic basis for these differences in S. pimpinellifolium and S. lycopersicum, we analyzed 15 genes that have previously been shown to mediate salinity tolerance in plants. We show that S. pimpinellifolium has a higher copy number of the inositol-3-phosphate synthase and phosphatase genes, which are both key enzymes in the production of inositol and its derivatives. Moreover, our analysis indicates that changes occurring in the inositol phosphate pathway may contribute to the observed higher salinity tolerance in 'LA0480.' Altogether, our work provides essential resources to understand and unlock the genetic and breeding potential of S. pimpinellifolium, and to discover the genomic basis underlying its environmental robustness.

Gene copy number variations involved in balsam poplar (Populus balsamifera L.) adaptive variations

Gene copy number variations (CNVs) involved in phenotypic variations have already been shown in plants, but genomewide testing of CNVs for adaptive variation was not doable until recent technological developments. Thus, reports of the genomic architecture of adaptation involving CNVs remain scarce to date. Here, we investigated F₁ progenies of an intraprovenance cross (north-north cross, 58th parallel) and an interprovenances cross (north-south cross, 58th/49th parallels) for CNVs using comparative genomic hybridization on arrays of probes targeting gene sequences in balsam poplar (Populus balsamifera L.), a widespread North American forest tree. A total of 1,721 genes were found in varying copy numbers over the set of 19,823 tested genes. These gene CNVs presented an estimated average size of 8.3 kb and were distributed over poplar's 19 chromosomes including 22 hotspot regions. Gene CNVs number was higher for the interprovenance progeny in accordance with an expected higher genetic diversity related to the composite origin of this family. Regression analyses between gene CNVs and seven adaptive trait variations resulted in 23 significant links; among these adaptive gene CNVs, 30% were located in hotspots. One-to-five gene CNVs were found related to each of the measured adaptive traits and annotated for both biotic and abiotic stress responses. These annotations can be related to the occurrence of a higher pathogenic pressure in the southern parts of balsam poplar's distribution, and higher photosynthetic assimilation rates and water-use efficiency at high latitudes. Overall, our findings suggest that gene CNVs typically having higher mutation rates than SNPs may in fact represent efficient adaptive variations against fast-evolving pathogens.

Extensive intraspecific gene order and gene structural variations between Mo17 and other maize genomes

Maize is an important crop with a high level of genome diversity and heterosis. The genome sequence of a typical female line, B73, was previously released. Here, we report a de novo genome assembly of a corresponding male representative line, Mo17. More than 96.4% of the 2,183 Mb assembled genome can be accounted for by 362 scaffolds in ten pseudochromosomes with 38,620 annotated protein-coding genes. Comparative analysis revealed large gene-order and gene structural variations: approximately 10% of the annotated genes were mutually nonsyntenic, and more than 20% of the predicted genes had either large-effect mutations or large structural variations, which might cause considerable protein divergence between the two inbred lines. Our study provides a high-quality reference-genome sequence of an important maize germplasm, and the intraspecific gene order and gene structural variations identified should have implications for heterosis and genome evolution.

Analysis of Extreme Phenotype Bulk Copy Number Variation (XP-CNV) Identified the Association of rp1 with Resistance to Goss's Wilt of Maize

Goss's wilt (GW) of maize is caused by the Gram-positive bacterium Clavibacter michiganensis subsp. nebraskensis (Cmn) and has spread in recent years throughout the Great Plains, posing a threat to production. The genetic basis of plant resistance is unknown. Here, a simple method for quantifying disease symptoms was developed and used to select cohorts of highly resistant and highly susceptible lines known as extreme phenotypes (XP). Copy number variation (CNV) analyses using whole genome sequences of bulked XP revealed 141 genes containing CNV between the two XP groups. The CNV genes include the previously identified common rust resistant locus rp1. Multiple Rp1 accessions with distinct rp1 haplotypes in an otherwise susceptible accession exhibited hypersensitive responses upon inoculation. GW provides an excellent system for the genetic dissection of diseases caused by closely related subspecies of C. michiganesis. Further work will facilitate breeding strategies to control GW and provide needed insight into the resistance mechanism of important related diseases such as bacterial canker of tomato and bacterial ring rot of potato.

Sequence analysis of European maize inbred line F2 provides new insights into molecular and chromosomal characteristics of presence/absence variants

BACKGROUND

Maize is well known for its exceptional structural diversity, including copy number variants (CNVs) and presence/absence variants (PAVs), and there is growing evidence for the role of structural variation in maize adaptation. While PAVs have been described in this important crop species, they have been only scarcely characterized at the sequence level and the extent of presence/absence variation and relative chromosomal landscape of inbred-specific regions remain to be elucidated.

RESULTS

De novo genome sequencing of the French F2 maize inbred line revealed 10,044 novel genomic regions larger than 1 kb, making up 88 Mb of DNA, that are present in F2 but not in B73 (PAV). This set of maize PAV sequences allowed us to annotate PAV content and to analyze sequence breakpoints. Using PAV genotyping on a collection of 25 temperate lines, we also analyzed Linkage Disequilibrium in PAVs and flanking regions, and PAV frequencies within maize genetic groups.

CONCLUSIONS

We highlight the possible role of MMEJ-type double strand break repair in maize PAV formation and discover 395 new genes with transcriptional support. Pattern of linkage disequilibrium within PAVs strikingly differs from this of flanking regions and is in accordance with the intuition that PAVs may recombine less than other genomic regions. We show that most PAVs are ancient, while some are found only in European Flint material, thus pinpointing structural features that may be at the origin of adaptive traits involved in the success of this material. Characterization of such PAVs will provide useful material for further association genetic studies in European and temperate maize.

Circular RNAs mediated by transposons are associated with transcriptomic and phenotypic variation in maize

Circular RNAs (circRNAs) are covalently closed RNA molecules. Recent studies have shown that circRNAs can arise from the transcripts of transposons. Given the prevalence of transposons in the maize genome and dramatic genomic variation driven by transposons, we hypothesize that transposons in maize may be involved in the formation of circRNAs and further modulate phenotypic variation. We performed circRNA-Seq on B73 seedling leaves and uncovered 2804 high-confidence maize circRNAs, which show distinct genomic features. Comprehensive analyses demonstrated that sequences related to LINE1-like elements (LLEs) and their Reverse Complementary Pairs (LLERCPs) are significantly enriched in the flanking regions of circRNAs. Interestingly, as the number of LLERCPs increase, the accumulation of circRNAs varies, whereas that of linear transcripts decreases. Furthermore, genes with LLERCP-mediated circRNAs are enriched among loci that are associated with phenotypic variation. These results suggest that circRNAs are likely to be involved in the modulation of phenotypic variation by LLERCPs. Further, we showed that the presence/absence variation of LLERCPs was associated with expression variation of circRNA-circ1690 and was related to ear height, potentially through the interplay between circRNAs and functional linear transcripts. Our first study of maize circRNAs uncovers a potential new way for transposons to modulate transcriptomic and phenotypic variations.

Copy number variation and disease resistance in plants

Plant genome diversity varies from single nucleotide polymorphisms to large-scale deletions, insertions, duplications, or re-arrangements. These re-arrangements of sequences resulting from duplication, gains or losses of DNA segments are termed copy number variations (CNVs). During the last decade, numerous studies have emphasized the importance of CNVs as a factor affecting human phenotype; in particular, CNVs have been associated with risks for several severe diseases. In plants, the exploration of the extent and role of CNVs in resistance against pathogens and pests is just beginning. Since CNVs are likely to be associated with disease resistance in plants, an understanding of the distribution of CNVs could assist in the identification of novel plant disease-resistance genes. In this paper, we review existing information about CNVs; their importance, role and function, as well as their association with disease resistance in plants.

Gene copy number variations in adaptive evolution: The genomic distribution of gene copy number variations revealed by genetic mapping and their adaptive role in an undomesticated species, white spruce (Picea glauca)

Gene copy number variation (CNV) has been associated with phenotypic variability in animals and plants, but a genomewide understanding of their impacts on phenotypes is largely restricted to human and agricultural systems. As such, CNVs have rarely been considered in investigations of the genomic architecture of adaptation in wild species. Here, we report on the genetic mapping of gene CNVs in white spruce, which lacks a contiguous assembly of its large genome (~20 Gb), and their relationships with adaptive phenotypic variation. We detected 3,911 gene CNVs including de novo structural variations using comparative genome hybridization on arrays (aCGH) in a large progeny set. We inferred the heterozygosity at CNV loci within parents by comparing haploid and diploid tissues and genetically mapped 82 gene CNVs. Our analysis showed that CNVs were distributed over 10 linkage groups and identified four CNV hotspots that we predict to occur in other species of the Pinaceae. Significant relationships were found between 29 of the gene CNVs and adaptive traits based on regression analyses with timings of bud set and bud flush, and height growth, suggesting a role for CNVs in climate adaptation. The importance of CNVs in adaptive evolution of white spruce was also indicated by functional gene annotations and the clustering of 31% of the mapped adaptive gene CNVs in CNV hotspots. Taken together, these results illustrate the feasibility of studying CNVs in undomesticated species and represent a major step towards a better understanding of the roles of CNVs in adaptive evolution.

Crop Breeding Chips and Genotyping Platforms: Progress, Challenges, and Perspectives

There is a rapidly rising trend in the development and application of molecular marker assays for gene mapping and discovery in field crops and trees. Thus far, more than 50 SNP arrays and 15 different types of genotyping-by-sequencing (GBS) platforms have been developed in over 25 crop species and perennial trees. However, much less effort has been made on developing ultra-high-throughput and cost-effective genotyping platforms for applied breeding programs. In this review, we discuss the scientific bottlenecks in existing SNP arrays and GBS technologies and the strategies to develop targeted platforms for crop molecular breeding. We propose that future practical breeding platforms should adopt automated genotyping technologies, either array or sequencing based, target functional polymorphisms underpinning economic traits, and provide desirable prediction accuracy for quantitative traits, with universal applications under wide genetic backgrounds in crops. The development of such platforms faces serious challenges at both the technological level due to cost ineffectiveness, and the knowledge level due to large genotype-phenotype gaps in crop plants. It is expected that such genotyping platforms will be achieved in the next ten years in major crops in consideration of (a) rapid development in gene discovery of important traits, (b) deepened understanding of quantitative traits through new analytical models and population designs, (c) integration of multi-layer -omics data leading to identification of genes and pathways responsible for important breeding traits, and (d) improvement in cost effectiveness of large-scale genotyping. Crop breeding chips and genotyping platforms will provide unprecedented opportunities to accelerate the development of cultivars with desired yield potential, quality, and enhanced adaptation to mitigate the effects of climate change.

Exploiting the great potential of Sequence Capture data by a new tool, SUPER-CAP

The recent development of Sequence Capture methodology represents a powerful strategy for enhancing data generation to assess genetic variation of targeted genomic regions. Here, we present SUPER-CAP, a bioinformatics web tool aimed at handling Sequence Capture data, fine calculating the allele frequency of variations and building genotype-specific sequence of captured genes. The dataset used to develop this in silico strategy consists of 378 loci and related regulative regions in a collection of 44 tomato landraces. About 14,000 high-quality variants were identified. The high depth (>40×) of coverage and adopting the correct filtering criteria allowed identification of about 4,000 rare variants and 10 genes with a different copy number variation. We also show that the tool is capable to reconstruct genotype-specific sequences for each genotype by using the detected variants. This allows evaluating the combined effect of multiple variants in the same protein. The architecture and functionality of SUPER-CAP makes the software appropriate for a broad set of analyses including SNP discovery and mining. Its functionality, together with the capability to process large data sets and efficient detection of sequence variation, makes SUPER-CAP a valuable bioinformatics tool for genomics and breeding purposes.

MLPA-Based Analysis of Copy Number Variation in Plant Populations

Copy number variants (CNVs) are intraspecies duplications/deletions of large DNA segments (>1 kb). A growing number of reports highlight the functional and evolutionary impact of CNV in plants, increasing the need for appropriate tools that enable locus-specific CNV genotyping on a population scale. Multiplex ligation-dependent probe amplification (MLPA) is considered a gold standard in genotyping CNV in humans. Consequently, numerous commercial MLPA assays for CNV-related human diseases have been created. We routinely genotype complex multiallelic CNVs in human and plant genomes using the modified MLPA procedure based on fully synthesized oligonucleotide probes (90-200 nt), which greatly simplifies the design process and allows for the development of custom assays. Here, we present a step-by-step protocol for gene-specific MLPA probe design, multiplexed assay setup and data analysis in a copy number genotyping experiment in plants. As a case study, we present the results of a custom assay designed to genotype the copy number status of 12 protein coding genes in a population of 80 Arabidopsis accessions. The genes were pre-selected based on whole genome sequencing data and are localized in the genomic regions that display different levels of population-scale variation (non-variable, biallelic, or multiallelic, as well as CNVs overlapping whole genes or their fragments). The presented approach is suitable for population-scale validation of the CNV regions inferred from whole genome sequencing data analysis and for focused analysis of selected genes of interest. It can also be very easily adopted for any plant species, following optimization of the template amount and design of the appropriate control probes, according to the general guidelines presented in this paper.

Unbiased K-mer Analysis Reveals Changes in Copy Number of Highly Repetitive Sequences During Maize Domestication and Improvement

The major component of complex genomes is repetitive elements, which remain recalcitrant to characterization. Using maize as a model system, we analyzed whole genome shotgun (WGS) sequences for the two maize inbred lines B73 and Mo17 using k-mer analysis to quantify the differences between the two genomes. Significant differences were identified in highly repetitive sequences, including centromere, 45S ribosomal DNA (rDNA), knob, and telomere repeats. Genotype specific 45S rDNA sequences were discovered. The B73 and Mo17 polymorphic k-mers were used to examine allele-specific expression of 45S rDNA in the hybrids. Although Mo17 contains higher copy number than B73, equivalent levels of overall 45S rDNA expression indicates that transcriptional or post-transcriptional regulation mechanisms operate for the 45S rDNA in the hybrids. Using WGS sequences of B73xMo17 doubled haploids, genomic locations showing differential repetitive contents were genetically mapped, which displayed different organization of highly repetitive sequences in the two genomes. In an analysis of WGS sequences of HapMap2 lines, including maize wild progenitor, landraces, and improved lines, decreases and increases in abundance of additional sets of k-mers associated with centromere, 45S rDNA, knob, and retrotransposons were found among groups, revealing global evolutionary trends of genomic repeats during maize domestication and improvement.

Genetic properties of the MAGIC maize population: a new platform for high definition QTL mapping in Zea mays

BACKGROUND

Maize (Zea mays) is a globally produced crop with broad genetic and phenotypic variation. New tools that improve our understanding of the genetic basis of quantitative traits are needed to guide predictive crop breeding. We have produced the first balanced multi-parental population in maize, a tool that provides high diversity and dense recombination events to allow routine quantitative trait loci (QTL) mapping in maize.

RESULTS

We produced 1,636 MAGIC maize recombinant inbred lines derived from eight genetically diverse founder lines. The characterization of 529 MAGIC maize lines shows that the population is a balanced, evenly differentiated mosaic of the eight founders, with mapping power and resolution strengthened by high minor allele frequencies and a fast decay of linkage disequilibrium. We show how MAGIC maize may find strong candidate genes by incorporating genome sequencing and transcriptomics data. We discuss three QTL for grain yield and three for flowering time, reporting candidate genes. Power simulations show that subsets of MAGIC maize might achieve high-power and high-definition QTL mapping.

CONCLUSIONS

We demonstrate MAGIC maize's value in identifying the genetic bases of complex traits of agronomic relevance. The design of MAGIC maize allows the accumulation of sequencing and transcriptomics layers to guide the identification of candidate genes for a number of maize traits at different developmental stages. The characterization of the full MAGIC maize population will lead to higher power and definition in QTL mapping, and lay the basis for improved understanding of maize phenotypes, heterosis included. MAGIC maize is available to researchers.

Targeted Sequencing Reveals Large-Scale Sequence Polymorphism in Maize Candidate Genes for Biomass Production and Composition

A major goal of maize genomic research is to identify sequence polymorphisms responsible for phenotypic variation in traits of economic importance. Large-scale detection of sequence variation is critical for linking genes, or genomic regions, to phenotypes. However, due to its size and complexity, it remains expensive to generate whole genome sequences of sufficient coverage for divergent maize lines, even with access to next generation sequencing (NGS) technology. Because methods involving reduction of genome complexity, such as genotyping-by-sequencing (GBS), assess only a limited fraction of sequence variation, targeted sequencing of selected genomic loci offers an attractive alternative. We therefore designed a sequence capture assay to target 29 Mb genomic regions and surveyed a total of 4,648 genes possibly affecting biomass production in 21 diverse inbred maize lines (7 flints, 14 dents). Captured and enriched genomic DNA was sequenced using the 454 NGS platform to 19.6-fold average depth coverage, and a broad evaluation of read alignment and variant calling methods was performed to select optimal procedures for variant discovery. Sequence alignment with the B73 reference and de novo assembly identified 383,145 putative single nucleotide polymorphisms (SNPs), of which 42,685 were non-synonymous alterations and 7,139 caused frameshifts. Presence/absence variation (PAV) of genes was also detected. We found that substantial sequence variation exists among genomic regions targeted in this study, which was particularly evident within coding regions. This diversification has the potential to broaden functional diversity and generate phenotypic variation that may lead to new adaptations and the modification of important agronomic traits. Further, annotated SNPs identified here will serve as useful genetic tools and as candidates in searches for phenotype-altering DNA variation. In summary, we demonstrated that sequencing of captured DNA is a powerful approach for variant discovery in maize genes.

Structural variations in plant genomes

Differences between plant genomes range from single nucleotide polymorphisms to large-scale duplications, deletions and rearrangements. The large polymorphisms are termed structural variants (SVs). SVs have received significant attention in human genetics and were found to be responsible for various chronic diseases. However, little effort has been directed towards understanding the role of SVs in plants. Many recent advances in plant genetics have resulted from improvements in high-resolution technologies for measuring SVs, including microarray-based techniques, and more recently, high-throughput DNA sequencing. In this review we describe recent reports of SV in plants and describe the genomic technologies currently used to measure these SVs.

Copy number variation detection using next generation sequencing read counts

Background

A copy number variation (CNV) is a difference between genotypes in the number of copies of a genomic region. Next generation sequencing (NGS) technologies provide sensitive and accurate tools for detecting genomic variations that include CNVs. However, statistical approaches for CNV identification using NGS are limited. We propose a new methodology for detecting CNVs using NGS data. This method (henceforth denoted by m-HMM) is based on a hidden Markov model with emission probabilities that are governed by mixture distributions. We use the Expectation-Maximization (EM) algorithm to estimate the parameters in the model.

Results

A simulation study demonstrates that our proposed m-HMM approach has greater power for detecting copy number gains and losses relative to existing methods. Furthermore, application of our m-HMM to DNA sequencing data from the two maize inbred lines B73 and Mo17 to identify CNVs that may play a role in creating phenotypic differences between these inbred lines provides results concordant with previous array-based efforts to identify CNVs.

Conclusions

The new m-HMM method is a powerful and practical approach for identifying CNVs from NGS data.

A high-density gene map of loblolly pine (Pinus taeda L.) based on exome sequence capture genotyping

Loblolly pine (Pinus taeda L.) is an economically and ecologically important conifer for which a suite of genomic resources is being generated. Despite recent attempts to sequence the large genome of conifers, their assembly and the positioning of genes remains largely incomplete. The interspecific synteny in pines suggests that a gene-based map would be useful to support genome assemblies and analysis of conifers. To establish a reference gene-based genetic map, we performed exome sequencing of 14729 genes on a mapping population of 72 haploid samples, generating a resource of 7434 sequence variants segregating for 3787 genes. Most markers are single-nucleotide polymorphisms, although short insertions/deletions and multiple nucleotide polymorphisms also were used. Marker segregation in the population was used to generate a high-density, gene-based genetic map. A total of 2841 genes were mapped to pine’s 12 linkage groups with an average of one marker every 0.58 cM. Capture data were used to detect gene presence/absence variations and position 65 genes on the map. We compared the marker order of genes previously mapped in loblolly pine and found high agreement. We estimated that 4123 genes had enough sequencing depth for reliable detection of markers, suggesting a high marker conversation rate of 92% (3787/4123). This is possible because a significant portion of the gene is captured and sequenced, increasing the chances of identifying a polymorphic site for characterization and mapping. This sub-centiMorgan genetic map provides a valuable resource for gene positioning on chromosomes and guide for the assembly of a reference pine genome.

Copy number polymorphism in plant genomes

Copy number variants (CNVs) are genomic rearrangements resulting from gains or losses of DNA segments. Typically, the term refers to rearrangements of sequences larger than 1 kb. This type of polymorphism has recently been shown to be a key contributor to intra-species genetic variation, along with single-nucleotide polymorphisms and short insertion-deletion polymorphisms. Over the last decade, a growing number of studies have highlighted the importance of copy number variation (CNV) as a factor affecting human phenotype and individual CNVs have been linked to risks for severe diseases. In plants, the exploration of the extent and role of CNV is still just beginning. Initial genomic analyses indicate that CNVs are prevalent in plants and have greatly affected plant genome evolution. Many CNV events have been observed in outcrossing and autogamous species. CNVs are usually found on all chromosomes, with CNV hotspots interspersed with regions of very low genetic variation. Although CNV is mainly associated with intergenic regions, many CNVs encompass protein-coding genes. The collected data suggest that CNV mainly affects the members of large families of functionally redundant genes. Thus, the effects of individual CNV events on phenotype are usually modest. Nevertheless, there are many cases in which CNVs for specific genes have been linked to important traits such as flowering time, plant height and resistance to biotic and abiotic stress. Recent reports suggest that CNVs may form rapidly in response to stress.

Genome-wide patterns of large-size presence/absence variants in sorghum

The presence/absence variants (PAVs) are a major source of genome structural variation and have profound effects on phenotypic and genomic variation in animals and humans. However, little is understood about PAVs in plant genomes. Our previous resequencing effort on three sorghum (Sorghum bicolour L.) genomes, each 12× coverage, uncovered 5 364 PAVs. Here, we report a detailed characterization of 51 large-size (>30 kb) PAVs. These PAVs spanned a total size of 2.92 Mb of the sorghum genome containing 202 known and predicted genes, including 38 genes annotated to encode cell death and stress response genes. The PAVs varied considerably for repeat sequences and mobile elements with DNA transposons as the major components. The frequency and distribution of these PAVs differed substantially across 96 sorghum inbred lines, and the low- and high frequency PAVs differed in their gene categories. This report shed new light on the occurrence and diversity of PAVs in sorghum genomes. Our research exemplifies a new perspective to explore genome structural variation for genetic improvement in plant breeding.

A BAC physical map of aus rice cultivar 'Kasalath', and the map-based genomic sequence of 'Kasalath' chromosome 1

Comparative analysis using available genomic resources within closely related species is an effective way to investigate genomic sequence and structural diversity. Rice (Oryza sativa L.) has undergone significant physiological and morphological changes during its domestication and local adaptation. We present a complete bacterial artificial chromosome (BAC) physical map for the aus rice cultivar 'Kasalath', which covers 90% of the sequence of temperate japonica rice cultivar 'Nipponbare'. Examination of physical distances between computational and experimental measurements of 'Kasalath' BAC insert size revealed the presence of more than 500 genomic regions that appear to have significant chromosome structural changes between the two cultivars. In particular, a genomic region on the long arm of 'Kasalath' chromosome 11 carrying a disease-resistance gene cluster was greatly expanded relative to the 'Nipponbare' genome. We also decoded 41.37 Mb of high-quality genomic sequence from 'Kasalath' chromosome 1. Extensive comparisons of chromosome 1 between 'Kasalath' and 'Nipponbare' led to the discovery of 317,843 single-nucleotide polymorphisms (SNPs) and 66,331 insertion/deletion (indel) sites. Nearly two-thirds of the expressed genes on rice chromosome 1 carried natural variations involving SNPs and/or indels that resulted in substitutions, insertions or deletions of amino acids in one cultivar relative to the other. We also observed gain and loss of genes caused by large indels. This study provides an important framework and an invaluable dataset for further understanding of the molecular mechanisms underlying the evolution and functions of the rice genome.

Genome-wide copy number variations in Oryza sativa L

Background

Copy number variation (CNV) can lead to intra-specific genome variations. It is not only part of normal genetic variation, but also is the source of phenotypic differences. Rice (Oryza sativa L.) is a model organism with a well-annotated genome, but investigation of CNVs in rice lags behind its mammalian counterparts.

Results

We comprehensively assayed CNVs using high-density array comparative genomic hybridization in a panel of 20 Asian cultivated rice comprising six indica, three aus, two rayada, two aromatic, three tropical japonica, and four temperate japonica varieties. We used a stringent criterion to identify a total of 2886 high-confidence copy number variable regions (CNVRs), which span 10.28 Mb (or 2.69%) of the rice genome, overlapping 1321 genes. These genes were significantly enriched for specific biological functions involved in cell death, protein phosphorylation, and defense response. Transposable elements (TEs) and other repetitive sequences were identified in the majority of CNVRs. Chromosome 11 showed the greatest enrichment for CNVs. Of subspecies-specific CNVRs, 55.75% and 61.96% were observed in only one cultivar of ssp. indica and ssp. japonica, respectively. Some CNVs with high frequency differences among groups resided in genes underlying rice adaptation.

Conclusions

Higher recombination rates and the presence of homologous gene clusters are probably predispositions for generation of the higher number of CNVs on chromosome 11 by non-allelic homologous recombination events. The subspecies-specific variants are enriched for rare alleles, which suggests that CNVs are relatively recent events that have arisen within breeding populations. A number of the CNVs identified in this study are candidates for generation of group-specific phenotypes.

Distribution, functional impact, and origin mechanisms of copy number variation in the barley genome

Background

There is growing evidence for the prevalence of copy number variation (CNV) and its role in phenotypic variation in many eukaryotic species. Here we use array comparative genomic hybridization to explore the extent of this type of structural variation in domesticated barley cultivars and wild barleys.

Results

A collection of 14 barley genotypes including eight cultivars and six wild barleys were used for comparative genomic hybridization. CNV affects 14.9% of all the sequences that were assessed. Higher levels of CNV diversity are present in the wild accessions relative to cultivated barley. CNVs are enriched near the ends of all chromosomes except 4H, which exhibits the lowest frequency of CNVs. CNV affects 9.5% of the coding sequences represented on the array and the genes affected by CNV are enriched for sequences annotated as disease-resistance proteins and protein kinases. Sequence-based comparisons of CNV between cultivars Barke and Morex provided evidence that DNA repair mechanisms of double-strand breaks via single-stranded annealing and synthesis-dependent strand annealing play an important role in the origin of CNV in barley.

Conclusions

We present the first catalog of CNVs in a diploid Triticeae species, which opens the door for future genome diversity research in a tribe that comprises the economically important cereal species wheat, barley, and rye. Our findings constitute a valuable resource for the identification of CNV affecting genes of agronomic importance. We also identify potential mechanisms that can generate variation in copy number in plant genomes.

A developmental transcriptional network for maize defines coexpression modules

Here, we present a genome-wide overview of transcriptional circuits in the agriculturally significant crop species maize (Zea mays). We examined transcript abundance data at 50 developmental stages, from embryogenesis to senescence, for 34,876 gene models and classified genes into 24 robust coexpression modules. Modules were strongly associated with tissue types and related biological processes. Sixteen of the 24 modules (67%) have preferential transcript abundance within specific tissues. One-third of modules had an absence of gene expression in specific tissues. Genes within a number of modules also correlated with the developmental age of tissues. Coexpression of genes is likely due to transcriptional control. For a number of modules, key genes involved in transcriptional control have expression profiles that mimic the expression profiles of module genes, although the expression of transcriptional control genes is not unusually representative of module gene expression. Known regulatory motifs are enriched in several modules. Finally, of the 13 network modules with more than 200 genes, three contain genes that are notably clustered (P < 0.05) within the genome. This work, based on a carefully selected set of major tissues representing diverse stages of maize development, demonstrates the remarkable power of transcript-level coexpression networks to identify underlying biological processes and their molecular components.

Advances in biotechnology and informatics to link variation in the genome to phenotypes in plants and animals

Advances in our understanding of genome structure provide consistent evidence for the existence of a core genome representing species classically defined by phenotype, as well as conditionally dispensable components of the genome that shows extensive variation between individuals of a given species. Generally, conservation of phenotypic features between species reflects conserved features of the genome; however, this is evidently not necessarily always the case as demonstrated by the analysis of the tunicate chordate Oikopleura dioica. In both plants and animals, the methylation activity of DNA and histones continues to present new variables for modifying (eventually) the phenotype of an organism and provides for structural variation that builds on the point mutations, rearrangements, indels, and amplification of retrotransposable elements traditionally considered. The translation of the advances in the structure/function analysis of the genome to industry is facilitated through the capture of research outputs in "toolboxes" that remain accessible in the public domain.

Mendelian and non-Mendelian regulation of gene expression in maize

Transcriptome variation plays an important role in affecting the phenotype of an organism. However, an understanding of the underlying mechanisms regulating transcriptome variation in segregating populations is still largely unknown. We sought to assess and map variation in transcript abundance in maize shoot apices in the intermated B73×Mo17 recombinant inbred line population. RNA–based sequencing (RNA–seq) allowed for the detection and quantification of the transcript abundance derived from 28,603 genes. For a majority of these genes, the population mean, coefficient of variation, and segregation patterns could be predicted by the parental expression levels. Expression quantitative trait loci (eQTL) mapping identified 30,774 eQTL including 96 trans-eQTL “hotspots,” each of which regulates the expression of a large number of genes. Interestingly, genes regulated by a trans-eQTL hotspot tend to be enriched for a specific function or act in the same genetic pathway. Also, genomic structural variation appeared to contribute to cis-regulation of gene expression. Besides genes showing Mendelian inheritance in the RIL population, we also found genes whose expression level and variation in the progeny could not be predicted based on parental difference, indicating that non-Mendelian factors also contribute to expression variation. Specifically, we found 145 genes that show patterns of expression reminiscent of paramutation such that all the progeny had expression levels similar to one of the two parents. Furthermore, we identified another 210 genes that exhibited unexpected patterns of transcript presence/absence. Many of these genes are likely to be gene fragments resulting from transposition, and the presence/absence of their transcripts could influence expression levels of their ancestral syntenic genes. Overall, our results contribute to the identification of novel expression patterns and broaden the understanding of transcriptional variation in plants.

Phenotypes are determined by the expression of genes, the environment, and the interaction of gene expression and the environment. However, a complete understanding of the inheritance of and genome-wide regulation of gene expression is lacking. One approach, called expression quantitative trait locus (eQTL) mapping provides the opportunity to examine the genome-wide inheritance and regulation of gene expression. In this paper, we conducted high-throughput sequencing of gene transcripts to examine gene expression in the shoot apex of a maize biparental mapping population. We quantified expression levels from 28,603 genes in the population and showed that the vast majority of genes exhibited the expected pattern of Mendelian inheritance. We genetically mapped the expression patterns and identified genomic regions associated with gene expression. Notably, we detected gene expression patterns that exhibited non-Mendelian inheritance. These included 145 genes that exhibited expression patterns in the progeny that were similar to only one of the parents and 210 genes with unexpected presence/absence expression patterns. The findings of non-Mendelian inheritance underscore the complexity of gene expression and provide a framework for understanding these complexities.

A bountiful harvest: genomic insights into crop domestication phenotypes

Human selection during crop domestication has resulted in remarkable transformations of plant phenotypes, providing a window into the genetic basis of morphological evolution. Recent progress in our understanding of the genetic architecture of novel plant traits has emerged from combining advanced molecular technologies with improved experimental designs, including nested association mapping, genome-wide association studies, population genetic screens for signatures of selection, and candidate gene approaches. These studies reveal a diversity of underlying causative mutations affecting phenotypes important in plant domestication and crop improvement, including coding sequence substitutions, presence/absence and copy number variation, transposon activation leading to novel gene structures and expression patterns, diversification following gene duplication, and polyploidy leading to altered combinatorial capabilities. The genomic regions unknowingly targeted by human selection include both structural and regulatory genes, often with results that propagate through the transcriptome as well as to other levels in the biosynthetic and morphogenetic networks.

Changes in genome content generated via segregation of non-allelic homologs

A careful analysis of two maize recombinant inbred lines (RILs) relative to their inbred parents revealed the presence of several hundred apparently de novo copy number variants (CNVs). These changes in genome content were validated via both PCR and whole exome-array capture-and-sequencing experiments. One hundred and eighty-five genomic regions, which overlap with 38 high-confidence genes, exhibited apparently de novo copy number variation (CNV) in these two RILs and in many instances the same apparently de novo CNV events were observed in multiple RILs. Further analyses revealed that these recurrent apparently de novo CNVs were caused by segregation of single-copy homologous sequences that are located in non-allelic positions in the two parental inbred lines. F(1) individuals derived from these inbred lines will be hemizygous for each of these non-allelic homologs but RIL genotypes will contain these sequences at zero, one or two genomic loci. Hence, the segregation of non-allelic homologs may contribute to transgressive segregation. Indeed, statistical associations between phenotypic quantitative trait loci and genomic losses were observed for two of 14 tested pairs of non-allelic homologs.

Structural variants in the soybean genome localize to clusters of biotic stress-response genes

Genome-wide structural and gene content variations are hypothesized to drive important phenotypic variation within a species. Structural and gene content variations were assessed among four soybean (Glycine max) genotypes using array hybridization and targeted resequencing. Many chromosomes exhibited relatively low rates of structural variation (SV) among genotypes. However, several regions exhibited both copy number and presence-absence variation, the most prominent found on chromosomes 3, 6, 7, 16, and 18. Interestingly, the regions most enriched for SV were specifically localized to gene-rich regions that harbor clustered multigene families. The most abundant classes of gene families associated with these regions were the nucleotide-binding and receptor-like protein classes, both of which are important for plant biotic defense. The colocalization of SV with plant defense response signal transduction pathways provides insight into the mechanisms of soybean resistance gene evolution and may inform the development of new approaches to resistance gene cloning.

Characterization of heterotic quantitative trait loci in maize by evaluation of near-isogenic lines and their crosses at two competition levels

In a previous study on a maize (Zea mays L.) population of recombinant inbreds derived from B73 × H99, we identified several quantitative trait loci (QTL) for agronomic traits with high dominance-additive ratio. Then, for four of these QTL, we developed families of near-isogenic lines (NILs) homozygous either for the QTL allele from B73 (BB) or from H99 (HH); for two of these QTL, the NILs' families were produced in two different genetic backgrounds. The present study was conducted to: (1) characterize these QTL for agronomic traits and (2) verify whether their effects were influenced by the genetic background, inbreeding level and plant density (PD). The six NILs' families were tested across 3 years and in three experiments at different inbreeding levels as NILs per se and their reciprocal crosses (Experiment 1), NILs crossed to related inbreds B73 and H99 (Experiment 2) and NILs crossed to four unrelated inbreds (Experiment 3). Experiment 2 was conducted at two PDs (4.5 and 9.0 plants m(-2)). Results of Experiments 1 and 2 confirmed previous findings as to QTL effects, with dominance-additive ratio superior to 1 for several traits; as a tendency, dominance effects were more pronounced in Experiment 1. The QTL effects were also confirmed in Experiment 3. The interactions involving QTL effects, families and PD were generally negligible, suggesting a certain stability of the QTL. Results emphasize the importance of dominance effects for these QTL, suggesting that they might deserve further studies, using the NILs' families and their crosses as base materials.

Genome-wide patterns of genetic variation in sweet and grain sorghum (Sorghum bicolor)

Background

Sorghum (Sorghum bicolor) is globally produced as a source of food, feed, fiber and fuel. Grain and sweet sorghums differ in a number of important traits, including stem sugar and juice accumulation, plant height as well as grain and biomass production. The first whole genome sequence of a grain sorghum is available, but additional genome sequences are required to study genome-wide and intraspecific variation for dissecting the genetic basis of these important traits and for tailor-designed breeding of this important C₄ crop.

Results

We resequenced two sweet and one grain sorghum inbred lines, and identified a set of nearly 1,500 genes differentiating sweet and grain sorghum. These genes fall into ten major metabolic pathways involved in sugar and starch metabolisms, lignin and coumarin biosynthesis, nucleic acid metabolism, stress responses and DNA damage repair. In addition, we uncovered 1,057,018 SNPs, 99,948 indels of 1 to 10 bp in length and 16,487 presence/absence variations as well as 17,111 copy number variations. The majority of the large-effect SNPs, indels and presence/absence variations resided in the genes containing leucine rich repeats, PPR repeats and disease resistance R genes possessing diverse biological functions or under diversifying selection, but were absent in genes that are essential for life.

Conclusions

This is a first report of the identification of genome-wide patterns of genetic variation in sorghum. High-density SNP and indel markers reported here will be a valuable resource for future gene-phenotype studies and the molecular breeding of this important crop and related species.

Heritable epigenetic variation among maize inbreds

Epigenetic variation describes heritable differences that are not attributable to changes in DNA sequence. There is the potential for pure epigenetic variation that occurs in the absence of any genetic change or for more complex situations that involve both genetic and epigenetic differences. Methylation of cytosine residues provides one mechanism for the inheritance of epigenetic information. A genome-wide profiling of DNA methylation in two different genotypes of Zea mays (ssp. mays), an organism with a complex genome of interspersed genes and repetitive elements, allowed the identification and characterization of examples of natural epigenetic variation. The distribution of DNA methylation was profiled using immunoprecipitation of methylated DNA followed by hybridization to a high-density tiling microarray. The comparison of the DNA methylation levels in the two genotypes, B73 and Mo17, allowed for the identification of approximately 700 differentially methylated regions (DMRs). Several of these DMRs occur in genomic regions that are apparently identical by descent in B73 and Mo17 suggesting that they may be examples of pure epigenetic variation. The methylation levels of the DMRs were further studied in a panel of near-isogenic lines to evaluate the stable inheritance of the methylation levels and to assess the contribution of cis- and trans- acting information to natural epigenetic variation. The majority of DMRs that occur in genomic regions without genetic variation are controlled by cis-acting differences and exhibit relatively stable inheritance. This study provides evidence for naturally occurring epigenetic variation in maize, including examples of pure epigenetic variation that is not conditioned by genetic differences. The epigenetic differences are variable within maize populations and exhibit relatively stable trans-generational inheritance. The detected examples of epigenetic variation, including some without tightly linked genetic variation, may contribute to complex trait variation.

Heritable variation within a species provides the basis for natural and artificial selection. A substantial portion of heritable variation is based on alterations in DNA sequence among individuals and is termed genetic variation. There is also evidence for epigenetic variation, which refers to heritable differences that are not caused by DNA sequence changes. Methylation of cytosine residues provides one molecular mechanism for epigenetic variation in many eukaryotic species. The genome-wide distribution of DNA methylation was assessed in two different inbred genotypes of maize to identify differentially methylated regions that may contribute to epigenetic variation. There are hundreds of genomic regions that have differences in DNA methylation levels in these two different genotypes, including methylation differences in regions without genetic variation. By studying the inheritance of the differential methylation in near-isogenic progeny of the two inbred lines, it is possible to demonstrate relatively stable inheritance of epigenetic variation, even in the absence of DNA sequence changes. The epigenetic variation among individuals of the same species may provide important contributions to phenotypic variation within a species even in the absence of genetic differences.