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

The maize genome experienced an ancient whole genome duplication approximately 10 million years ago and the duplicate subgenomes have since experienced reciprocal gene loss (fractionation) such that many genes have returned to single-copy status. This process has not affected the subgenomes equally; reduced gene expression in one of the subgenomes mitigates the consequences of mutations and gene deletions and is thought to drive higher rates of fractionation. Here we take advantage of published genome-wide SNP and phenotype association data to show that, in accordance with predictions of this model, paralogs with greater expression contribute more to phenotypic variation compared to their lowly expressed counterparts. Furthermore, paralogous genes in the least-fractionated subgenome account for a greater degree of phenotypic diversity than those resident on the more-fractionated subgenome. We also show that the two subgenomes of maize are distinct in epigenetic characteristics. Intriguingly, analysis of singleton genes reveals that these differences persist even after fractionation is complete.

Dioecy has evolved numerous times in plants, but heteromorphic sex chromosomes are apparently rare. Sex determination has been studied in multiple Salix and Populus (Salicaceae) species, and P. trichocarpa has an XY sex determination system on chromosome 19, while S. suchowensis and S. viminalis have a ZW system on chromosome 15. Here we use whole genome sequencing coupled with quantitative trait locus mapping and a genome-wide association study to characterize the genomic composition of the non-recombining portion of the sex determination region. We demonstrate that Salix purpurea also has a ZW system on chromosome 15. The sex determination region has reduced recombination, high structural polymorphism, an abundance of transposable elements, and contains genes that are involved in sex expression in other plants. We also show that chromosome 19 contains sex-associated markers in this S. purpurea assembly, along with other autosomes. This raises the intriguing possibility of a translocation of the sex determination region within the Salicaceae lineage, suggesting a common evolutionary origin of the Populus and Salix sex determination loci.

Among the fundamental evolutionary forces, recombination arguably has the largest impact on the practical work of plant breeders. Varying over 1,000-fold across the maize genome, the local meiotic recombination rate limits the resolving power of quantitative trait mapping and the precision of favorable allele introgression. The consequences of low recombination also theoretically extend to the species-wide scale by decreasing the power of selection relative to genetic drift, and thereby hindering the purging of deleterious mutations. In this study, we used genotyping-by-sequencing (GBS) to identify 136,000 recombination breakpoints at high resolution within US and Chinese maize nested association mapping populations. We find that the pattern of cross-overs is highly predictable on the broad scale, following the distribution of gene density and CpG methylation. Several large inversions also suppress recombination in distinct regions of several families. We also identify recombination hotspots ranging in size from 1 kb to 30 kb. We find these hotspots to be historically stable and, compared with similar regions with low recombination, to have strongly differentiated patterns of DNA methylation and GC content. We also provide evidence for the historical action of GC-biased gene conversion in recombination hotspots. Finally, using genomic evolutionary rate profiling (GERP) to identify putative deleterious polymorphisms, we find evidence for reduced genetic load in hotspot regions, a phenomenon that may have considerable practical importance for breeding programs worldwide.

Cellular processes mediated through nuclear DNA must contend with chromatin. Chromatin structural assays can efficiently integrate information across diverse regulatory elements, revealing the functional noncoding genome. In this study, we use a differential nuclease sensitivity assay based on micrococcal nuclease (MNase) digestion to discover open chromatin regions in the maize genome. We find that maize MNase-hypersensitive (MNase HS) regions localize around active genes and within recombination hotspots, focusing biased gene conversion at their flanks. Although MNase HS regions map to less than 1% of the genome, they consistently explain a remarkably large amount (∼40%) of heritable phenotypic variance in diverse complex traits. MNase HS regions are therefore on par with coding sequences as annotations that demarcate the functional parts of the maize genome. These results imply that less than 3% of the maize genome (coding and MNase HS regions) may give rise to the overwhelming majority of phenotypic variation, greatly narrowing the scope of the functional genome.

Comparative analysis of multiple angiosperm genomes has implicated gene duplication in the expansion and diversification of many gene families. However, empirical data and theory suggest that whole-genome and small-scale duplication events differ with respect to the types of genes preserved as duplicate pairs. We compared gene duplicates resulting from a recent whole genome duplication to a set of tandemly duplicated genes in the model forest tree Populus trichocarpa. We used a combination of microarray expression analyses of a diverse set of tissues and functional annotation to assess factors related to the preservation of duplicate genes of both types. Whole genome duplicates are 700 bp longer and are expressed in 20% more tissues than tandem duplicates. Furthermore, certain functional categories are over-represented in each class of duplicates. In particular, disease resistance genes and receptor-like kinases commonly occur in tandem but are significantly under-retained following whole genome duplication, while whole genome duplicate pairs are enriched for members of signal transduction cascades and transcription factors. The shape of the distribution of expression divergence for duplicated pairs suggests that nearly half of the whole genome duplicates have diverged in expression by a random degeneration process. The remaining pairs have more conserved gene expression than expected by chance, consistent with a role for selection under the constraints of gene balance. We hypothesize that duplicate gene preservation in Populus is driven by a combination of subfunctionalization of duplicate pairs and purifying selection favoring retention of genes encoding proteins with large numbers of interactions.

Background A genome-wide association study (GWAS) is the foremost strategy used for finding genes that control human diseases and agriculturally important traits, but it often reports false positives. In contrast, its complementary method, linkage analysis, provides direct genetic confirmation, but with limited resolution. A joint approach, using multiple linkage populations, dramatically improves resolution and statistical power. For example, this approach has been used to confirm that many complex traits, such as flowering time controlling adaptation in maize, are controlled by multiple genes with small effects. In addition, genotyping by sequencing (GBS) at low coverage not only produces genotyping errors, but also results in large datasets, making the use of high-throughput sequencing technologies computationally inefficient or unfeasible. Results In this study, we converted raw SNPs into effective recombination bins. The reduced bins not only retain the original information, but also correct sequencing errors from low-coverage genomic sequencing. To further increase the statistical power and resolution, we merged a new temperate maize nested association mapping (NAM) population derived in China (CN-NAM) with the existing maize NAM population developed in the US (US-NAM). Together, the two populations contain 36 families and 7,000 recombinant inbred lines (RILs). One million SNPs were generated for all the RILs with GBS at low coverage. We developed high-quality recombination maps for each NAM population to correct genotyping errors and improve the computational efficiency of the joint linkage analysis. The original one million SNPs were reduced to 4,932 and 5,296 recombination bins with average interval distances of 0.34 cM and 0.28 cM for CN-NAM and US-NAM, respectively. The quantitative trait locus (QTL) mapping for flowering time (days to tasseling) indicated that the high-density, recombination bin map improved resolution of QTL mapping by 50 % compared with that using a medium-density map. We also demonstrated that combining the CN-NAM and US-NAM populations improves the power to detect QTL by 50 % compared to single NAM population mapping. Among the QTLs mapped by joint usage of the US-NAM and CN-NAM maps, 25 % of the QTLs overlapped with known flowering-time genes in maize. Conclusion This study provides directions and resources for the research community, especially maize researchers, for future studies using the recombination bin strategy for joint linkage analysis. Available resources include efficient usage of low-coverage genomic sequencing, detailed positions for genes controlling maize flowering, and recombination bin maps and flowering- time data for both CN and US NAMs. Maize researchers even have the opportunity to grow both CN and US NAM populations to study the traits of their interest, as the seeds of both NAM populations are available from the seed repository in China and the US. Electronic supplementary material The online version of this article (doi:10.1186/s12915-015-0187-4) contains supplementary material, which is available to authorized users.

Forest trees are dominant components of terrestrial ecosystems that have global ecological and economic importance. Despite distributions that span wide environmental gradients, many tree populations are locally adapted, and mechanisms underlying this adaptation are poorly understood. Here we use a combination of whole-genome selection scans and association analyses of 544 Populus trichocarpa trees to reveal genomic bases of adaptive variation across a wide latitudinal range. Three hundred ninety-seven genomic regions showed evidence of recent positive and/or divergent selection and enrichment for associations with adaptive traits that also displayed patterns consistent with natural selection. These regions also provide unexpected insights into the evolutionary dynamics of duplicated genes and their roles in adaptive trait variation.

Summary • Plant population genomics informs evolutionary biology, breeding, conservation and bioenergy feedstock development. For example, the detection of reliable phenotype–genotype associations and molecular signatures of selection requires a detailed knowledge about genome-wide patterns of allele frequency variation, linkage disequilibrium and recombination. • We resequenced 16 genomes of the model tree Populus trichocarpa and genotyped 120 trees from 10 subpopulations using 29 213 single-nucleotide polymorphisms. • Significant geographic differentiation was present at multiple spatial scales, and range-wide latitudinal allele frequency gradients were strikingly common across the genome. The decay of linkage disequilibrium with physical distance was slower than expected from previous studies in Populus, with r 2 dropping below 0.2 within 3–6 kb. Consistent with this, estimates of recent effective population size from linkage disequilibrium (Ne 4000–6000) were remarkably low relative to the large census sizes of P. trichocarpa stands. Fine-scale rates of recombination varied widely across the genome, but were largely predictable on the basis of DNA sequence and methylation features. • Our results suggest that genetic drift has played a significant role in the recent evolutionary history of P. trichocarpa. Most importantly, the extensive linkage disequilibrium detected suggests that genome-wide association studies and genomic selection in undomesticated populations may be more feasible in Populus than previously assumed.

The signatures of evolutionary change are encoded in the structure and composition of the Populus trichocarpa genome, which is currently the most extensively characterized among forest trees. We report on genome-scale analyses of 580 trees collected from across the range of this species, including whole genome resequencing of over 50 trees. Several lines of evidence suggest a relatively strong bottleneck in the recent evolutionary past of this species, including reduced nucleotide diversity compared to other Populus species and relatively high Linkage Disequilibrium (LD). Furthermore, there is a preponderance of strong latitudinal gradients in allele frequencies, and loci with strong gradients tend to have high frequencies of derived alleles and occur in regions of high LD. This suggests a complex interplay between post-glacial migration and selection in shaping nucleotide diversity in this species. Further insights can be gained by examining prevailing patterns within the genome of this species. For example, the recent whole genome duplication is well-documented, but close examination of patterns of loss and retention of duplicated genes lends support to the Gene Balance Hypothesis as a driving force behind the maintenance of duplicated gene pairs, with positive selection driven by subfunctionalization playing a secondary role. Retained duplicate pairs tend to belong to functional classes that are characterized by high protein-protein interactions, as predicted by Gene Balance (members of signal transduction cascades and transcription factors). Patterns of expression across a diverse set of tissues are consistent with two classes of duplicated genes: one group with retained ancestral functions, and a smaller group with divergent functions driven by alternate degeneration of ancestral functions. A major factor reflecting genome structure and content is the population recombination rate. We will show that this rate is highly variable across the genome, characterized by large regions of relatively low recombination punctuated by hotspots with greatly elevated recombination. There is a strong relationship between recombination rates determined by a very dense genetic map and recombination inferred from population resequencing data. Recombination rate is inversely correlated with methylation status and repeat density, with the correlation being strongest for LTR Gypsy elements and AT low complexity repeats. Hotspots of recombination appear to be associated with a short sequence motif, and preferentially occur 5’ of genes. Whole genome resequencing is steadily increasing the resolution with which we can dissect the evolutionary legacy of this important species, and is therefore enhancing our understanding of current distributions and, potentially, future responses to artificial and natural selection. As information continues to accumulate about this and other related species, including congeners and a host of organisms with ecological associations, we will begin to piece together the complex web of genetic, ecological, and evolutionary forces that shape extant communities. We will thereby approach the ultimate goal of understanding the molecular bases of adaptive evolutionary change in a community context.

Background The large-scale identification of physical protein-protein interactions (PPIs) is an important step toward understanding how biological networks evolve and generate emergent phenotypes. However, experimental identification of PPIs is a laborious and error-prone process, and current methods of PPI prediction tend to be highly conservative or require large amounts of functional data that may not be available for newly-sequenced organisms. Results In this study we demonstrate a random-forest based technique, ENTS, for the computational prediction of protein-protein interactions based only on primary sequence data. Our approach is able to efficiently predict interactions on a whole-genome scale for any eukaryotic organism, using pairwise combinations of conserved domains and predicted subcellular localization of proteins as input features. We present the first predicted interactome for the forest tree Populus trichocarpa in addition to the predicted interactomes for Saccharomyces cerevisiae, Homo sapiens, Mus musculus, and Arabidopsis thaliana. Comparing our approach to other PPI predictors, we find that ENTS performs comparably to or better than a number of existing approaches, including several that utilize a variety of functional information for their predictions. We also find that the predicted interactions are biologically meaningful, as indicated by similarity in functional annotations and enrichment of co-expressed genes in public microarray datasets. Furthermore, we demonstrate some of the biological insights that can be gained from these predicted interaction networks. We show that the predicted interactions yield informative groupings of P. trichocarpa metabolic pathways, literature-supported associations among human disease states, and theory-supported insight into the evolutionary dynamics of duplicated genes in paleopolyploid plants. Conclusion We conclude that the ENTS classifier will be a valuable tool for the de novo annotation of genome sequences, providing initial clues about regulatory and metabolic network topology, and revealing relationships that are not immediately obvious from traditional homology-based annotations.