A High-Resolution Map of Arabidopsis Recombinant Inbred Lines by Whole-Genome Exon Array Hybridization

Recombinant populations were the basis for Mendel's first genetic experiments and continue to be key to the study of genes, heredity, and genetic variation today. Genotyping several hundred thousand loci in a single assay by hybridizing genomic DNA to oligonucleotide arrays provides a powerful technique to improve precision linkage mapping. The genotypes of two accessions of Arabidopsis were compared by using a 400,000 feature exon-specific oligonucleotide array. Around 16,000 single feature polymorphisms (SFPs) were detected in ~8,000 of the ~26,000 genes represented on the array. Allelic variation at these loci was measured in a recombinant inbred line population, which defined the location of 815 recombination breakpoints. The genetic linkage map had a total length of 422.5 cM, with 676 informative SFP markers representing intervals of ~0.6 cM. One hundred fifteen single gene intervals were identified. Recombination rate, SFP distribution, and segregation in this population are not uniform. Many genomic regions show a clustering of recombination events including significant hot spots. The precise haplotype structure of the recombinant population was defined with unprecedented accuracy and resolution. The resulting linkage map allows further refinement of the hundreds of quantitative trait loci identified in this well-studied population. Highly variable recombination rates along each chromosome and extensive segregation distortion were observed in the population

Transposable element-initiated enhancer-like elements generate the subgenome-biased spike specificity of polyploid wheat

Transposable elements (TEs) comprise ~85% of the common wheat genome, which are highly diverse among subgenomes, possibly contribute to polyploid plasticity, but the causality is only assumed. Here, by integrating data from gene expression cap analysis and epigenome profiling via hidden Markov model in common wheat, we detect a large proportion of enhancer-like elements (ELEs) derived from TEs producing nascent noncoding transcripts, namely ELE-RNAs, which are well indicative of the regulatory activity of ELEs. Quantifying ELE-RNA transcriptome across typical developmental stages reveals that TE-initiated ELE-RNAs are mainly from RLG_famc7.3 specifically expanded in subgenome A. Acquisition of spike-specific transcription factor binding likely confers spike-specific expression of RLG_famc7.3-initiated ELE-RNAs. Knockdown of RLG_famc7.3-initiated ELE-RNAs resulted in global downregulation of spike-specific genes and abnormal spike development. These findings link TE expansion to regulatory specificity and polyploid developmental plasticity, highlighting the functional impact of TE-driven regulatory innovation on polyploid evolution

Comparative Proteomic Analysis Provides New Insights Into Low Nitrogen-Promoted Primary Root Growth in Hexaploid Wheat

Nitrogen deficient environments can promote wheat primary root growth (PRG) that allows for nitrogen uptake in deep soil. However, the mechanisms of low nitrogen-promoted root growth remain largely unknown. Here, an integrated comparative proteome study using iTRAQ analysis on the roots of two wheat varieties and their descendants with contrasting response to low nitrogen (LN) stress was performed under control (CK) and LN conditions. In total, 84 differentially abundant proteins (DAPs) specifically involved in the process of LN-promoted PRG were identified and 11 pathways were significantly enriched. The Glutathione metabolism, endocytosis, lipid metabolism, and phenylpropanoid biosynthesis pathways may play crucial roles in the regulation of LN-promoted PRG. We also identified 59 DAPs involved in the common response to LN stress in different genetic backgrounds. The common responsive DAPs to LN stress were mainly involved in nitrogen uptake, transportation and remobilization, and LN stress tolerance. Taken together, our results provide new insights into the metabolic and molecular changes taking place in contrasting varieties under LN conditions, which provide useful information for the genetic improvement of root traits and nitrogen use efficiency in wheat

Dissection of Pleiotropic QTL Regions Controlling Wheat Spike Characteristics Under Different Nitrogen Treatments Using Traditional and Conditional QTL Mapping

Optimal spike characteristics are critical in improving the sink capacity and yield potential of wheat even in harsh environments. However, the genetic basis of their response to nitrogen deficiency is still unclear. In this study, quantitative trait loci (QTL) for six spike-related traits, including heading date (HD), spike length (SL), spikelet number (SN), spike compactness (SC), fertile spikelet number (FSN), and sterile spikelet number (SSN), were detected under two different nitrogen (N) supplies, based on a high-density genetic linkage map constructed by PCR markers, DArTs, and Affymetrix Wheat 660 K SNP chips. A total of 157 traditional QTLand 54 conditional loci were detected by inclusive composite interval mapping, among which three completely low N-stress induced QTL for SN and FSN (qSn-1A.1, qFsn-1B, and qFsn-7D) were found to maintain the desired spikelet fertility and kernel numbers even under N deficiency through pyramiding elite alleles. Twenty-eight stable QTL showing significant differencet in QTL detection model were found and seven genomic regions (R2D, R4A, R4B, R5A, R7A, R7B, and R7D) clustered by these stable QTL were highlighted. Among them, the effect of R4B on controlling spike characteristics might be contributed from Rht-B1. R7A harboring three major stable QTL (qSn-7A.2, qSc-7A, and qFsn-7A.3) might be one of the valuable candidate regions for further genetic improvement. In addition, the R7A was found to show syntenic with R7B, indicating the possibly exsting homoeologous candidate genes in both regions. The SNP markers involved with the above highlighted regions will eventually facilitate positional cloning or marker-assisted selection for the optimal spike characteristics under various N input conditions

QTL Detection for Kernel Size and Weight in Bread Wheat (Triticum aestivum L.) Using a High-Density SNP and SSR-Based Linkage Map

High-density genetic linkage maps are essential for precise mapping quantitative trait loci (QTL) in wheat (Triticum aestivum L.). In this study, a high-density genetic linkage map consisted of 6312 SNP and SSR markers was developed to identify QTL controlling kernel size and weight, based on a recombinant inbred line (RIL) population derived from the cross of Shixin828 and Kenong2007. Seventy-eight putative QTL for kernel length (KL), kernel width (KW), kernel diameter ratio (KDR), and thousand kernel weight (TKW) were detected over eight environments by inclusive composite interval mapping (ICIM). Of these, six stable QTL were identified in more than four environments, including two for KL (qKL-2D and qKL-6B.2), one for KW (qKW-2D.1), one for KDR (qKDR-2D.1) and two for TKW (qTKW-5A and qTKW-5B.2). Unconditional and multivariable conditional QTL mapping for TKW with respect to TKW component (TKWC) revealed that kernel dimensions played an important role in regulating the kernel weight. Seven QTL-rich genetic regions including seventeen QTL were found on chromosomes 1A (2), 2D, 3A, 4B and 5B (2) exhibiting pleiotropic effects. In particular, clusters on chromosomes 2D and 5B possessing significant QTL for kernel-related traits were highlighted. Markers tightly linked to these QTL or clusters will eventually facilitate further studies for fine mapping, candidate gene discovery and marker-assisted selection (MAS) in wheat breeding