RNA polymerase mapping in plants identifies intergenic regulatory elements enriched in causal variants.

Control of gene expression is fundamental at every level of cell function. Promoter-proximal pausing and divergent transcription at promoters and enhancers, which are prominent features in animals, have only been studied in a handful of research experiments in plants. PRO-Seq analysis in cassava (Manihot esculenta) identified peaks of transcriptionally engaged RNA polymerase at both the 5' and 3' end of genes, consistent with paused or slowly moving Polymerase. In addition, we identified divergent transcription at intergenic sites. A full genome search for bi-directional transcription using an algorithm for enhancer detection developed in mammals (dREG) identified many intergenic regulatory element (IRE) candidates. These sites showed distinct patterns of methylation and nucleotide conservation based on genomic evolutionary rate profiling (GERP). SNPs within these IRE candidates explained significantly more variation in fitness and root composition than SNPs in chromosomal segments randomly ascertained from the same intergenic distribution, strongly suggesting a functional importance of these sites. Maize GRO-Seq data showed RNA polymerase occupancy at IREs consistent with patterns in cassava. Furthermore, these IREs in maize significantly overlapped with sites previously identified on the basis of open chromatin, histone marks, and methylation, and were enriched for reported eQTL. Our results suggest that bidirectional transcription can identify intergenic genomic regions in plants that play an important role in transcription regulation and whose identification has the potential to aid crop improvement.

A Peptide Pair Coordinates Regular Ovule Initiation Patterns with Seed Number and Fruit Size.

Ovule development in Arabidopsis thaliana involves pattern formation, which ensures that ovules are regularly arranged in the pistils to reduce competition for nutrients and space. Mechanisms underlying pattern formation in plants, such as phyllotaxis, flower morphogenesis, or lateral root initiation, have been extensively studied, and genes controlling the initiation of ovules have been identified. However, the fundamental patterning mechanism that determines the spacing of ovule anlagen within the placenta remained unexplored. Using natural variation analysis combined with quantitative trait locus analysis, we found that the spacing of ovules in the developing gynoecium and fruits is controlled by two secreted peptides, EPFL2 and EPFL9 (also known as Stomagen), and their receptors from the ERECTA (ER) family that act from the carpel wall and the placental tissue. We found that a signaling pathway controlled by EPFL9 acting from the carpel wall through the LRR-receptor kinases ER, ERL1, and ERL2 promotes fruit growth. Regular spacing of ovules depends on EPFL2 expression in the carpel wall and in the inter-ovule spaces, where it acts through ERL1 and ERL2. Loss of EPFL2 signaling results in shorter gynoecia and fruits and irregular spacing of ovules or even ovule twinning. We propose that the EPFL2 signaling module evolved to control the initiation and regular, equidistant spacing of ovule primordia, which may serve to minimize competition between seeds or facilitate equal resource allocation. Together, EPFL2 and EPFL9 help to coordinate ovule patterning and thereby seed number with gynoecium and fruit growth through a set of shared receptors.

Prospects for Genomic Selection in Cassava Breeding.

Cassava ( Crantz) is a clonally propagated staple food crop in the tropics. Genomic selection (GS) has been implemented at three breeding institutions in Africa to reduce cycle times. Initial studies provided promising estimates of predictive abilities. Here, we expand on previous analyses by assessing the accuracy of seven prediction models for seven traits in three prediction scenarios: cross-validation within populations, cross-population prediction and cross-generation prediction. We also evaluated the impact of increasing the training population (TP) size by phenotyping progenies selected either at random or with a genetic algorithm. Cross-validation results were mostly consistent across programs, with nonadditive models predicting of 10% better on average. Cross-population accuracy was generally low (mean = 0.18) but prediction of cassava mosaic disease increased up to 57% in one Nigerian population when data from another related population were combined. Accuracy across generations was poorer than within-generation accuracy, as expected, but accuracy for dry matter content and mosaic disease severity should be sufficient for rapid-cycling GS. Selection of a prediction model made some difference across generations, but increasing TP size was more important. With a genetic algorithm, selection of one-third of progeny could achieve an accuracy equivalent to phenotyping all progeny. We are in the early stages of GS for this crop but the results are promising for some traits. General guidelines that are emerging are that TPs need to continue to grow but phenotyping can be done on a cleverly selected subset of individuals, reducing the overall phenotyping burden.

A Systems Genetics Approach Identifies Gene Regulatory Networks Associated with Fatty Acid Composition in Brassica rapa Seed.

Fatty acids in seeds affect seed germination and seedling vigor, and fatty acid composition determines the quality of seed oil. In this study, quantitative trait locus (QTL) mapping of fatty acid and transcript abundance was integrated with gene network analysis to unravel the genetic regulation of seed fatty acid composition in a Brassica rapa doubled haploid population from a cross between a yellow sarson oil type and a black-seeded pak choi. The distribution of major QTLs for fatty acids showed a relationship with the fatty acid types: linkage group A03 for monounsaturated fatty acids, A04 for saturated fatty acids, and A05 for polyunsaturated fatty acids. Using a genetical genomics approach, expression quantitative trait locus (eQTL) hotspots were found at major fatty acid QTLs on linkage groups A03, A04, A05, and A09. An eQTL-guided gene coexpression network of lipid metabolism-related genes showed major hubs at the genes BrPLA2-ALPHA, BrWD-40, a number of seed storage protein genes, and the transcription factor BrMD-2, suggesting essential roles for these genes in lipid metabolism. Three subnetworks were extracted for the economically important and most abundant fatty acids erucic, oleic, linoleic, and linolenic acids. Network analysis, combined with comparison of the genome positions of cis- or trans-eQTLs with fatty acid QTLs, allowed the identification of candidate genes for genetic regulation of these fatty acids. The generated insights in the genetic architecture of fatty acid composition and the underlying complex gene regulatory networks in B. rapa seeds are discussed.

Design of a Brassica rapa core collection for association mapping studies.

A Brassica rapa collection of 239 accessions, based on two core collections representing different morphotypes from different geographical origins, is presented and its use for association mapping is illustrated for flowering time. We analyzed phenotypic variation of leaf and seed pod traits, plant architecture, and flowering time using data collected from three field experiments and evaluated the genetic diversity with a set of SSR markers. The Wageningen University and Research Centre (WUR) and the Vavilov Research Institute of Plant Industry (VIR) core collections had similar representations of most morphotypes, as illustrated by the phenotypic and genetic variation within these groups. The analysis of population structure revealed five subgroups in the collection, whereas previous studies of the WUR core collection indicated four subgroups; the fifth group identified consisted mainly of oil accessions from the VIR core collection, winter oils from Pakistan, and a number of other types. A very small group of summer oils is described, that is not related to other oil accessions. A candidate gene approach was chosen for association mapping of flowering time with a BrFLC1 biallelic CAPS marker and a BrFLC2 multiallelic SSR marker. The two markers were significantly associated with flowering time, but their effects were confined to certain morphotypes and (or) alleles. Based on these results, we discuss the optimal design for an association mapping population and the need to fix the heterogeneous accessions to facilitate phenotyping and genotyping.

BrFLC2 (FLOWERING LOCUS C) as a candidate gene for a vernalization response QTL in Brassica rapa.

Flowering time is an important agronomic trait, and wide variation exists among Brassica rapa. In Arabidopsis, FLOWERING LOCUS C (FLC) plays an important role in modulating flowering time and the response to vernalization. Brassica rapa contains several paralogues of FLC at syntenic regions. BrFLC2 maps under a major flowering time and vernalization response quantitative trait locus (QTL) at the top of A02. Here the effects of vernalization on flowering time in a double haploid (DH) population and on BrFLC2 expression in selected lines of a DH population in B. rapa are descibed. The effect of the major flowering time QTL on the top of A02 where BrFLC2 maps clearly decreases upon vernalization, which points to a role for BrFLC2 underlying the QTL. In all developmental stages and tissues (seedlings, cotyledons, and leaves), BrFLC2 transcript levels are higher in late flowering pools of DH lines than in pools of early flowering DH lines. BrFLC2 expression diminished after different durations of seedling vernalization in both early and late DH lines. The reduction of BrFLC2 expression upon seedling vernalization of both early and late flowering DH lines was strongest at the seedling stage and diminished in subsequent growth stages, which suggests that the commitment to flowering is already set at very early developmental stages. Taken together, these data support the hypothesis that BrFLC2 is a candidate gene for the flowering time and vernalization response QTL in B. rapa.

Quantitative trait loci for flowering time and morphological traits in multiple populations of Brassica rapa.

Wide variation for morphological traits exists in Brassica rapa and the genetic basis of this morphological variation is largely unknown. Here is a report on quantitative trait loci (QTL) analysis of flowering time, seed and pod traits, growth-related traits, leaf morphology, and turnip formation in B. rapa using multiple populations. The populations resulted from crosses between the following accessions: Rapid cycling, Chinese cabbage, Yellow sarson, Pak choi, and a Japanese vegetable turnip variety. A total of 27 QTL affecting 20 morphological traits were detected, including eight QTL for flowering time, six for seed traits, three for growth-related traits and 10 for leaf traits. One major QTL was found for turnip formation. Principal component analysis and co-localization of QTL indicated that some loci controlling leaf and seed-related traits and those for flowering time and turnip formation might be the same. The major flowering time QTL detected in all populations on linkage group R02 co-localized with BrFLC2. One major QTL, controlling turnip formation, was also mapped at this locus. The genes that may underly this QTL and comparative analyses between the four populations and with Arabidopsis thaliana are discussed.