Pangenomes are collections of annotated genome sequences of multiple individuals of a species¹. The structural variants uncovered by these datasets are a major asset to genetic analysis in crop plants². Here we report a pangenome of barley comprising long-read sequence assemblies of 76 wild and domesticated genomes and short-read sequence data of 1,315 genotypes. An expanded catalogue of sequence variation in the crop includes structurally complex loci that are rich in gene copy number variation. To demonstrate the utility of the pangenome, we focus on four loci involved in disease resistance, plant architecture, nutrient release and trichome development. Novel allelic variation at a powdery mildew resistance locus and population-specific copy number gains in a regulator of vegetative branching were found. Expansion of a family of starch-cleaving enzymes in elite malting barleys was linked to shifts in enzymatic activity in micro-malting trials. Deletion of an enhancer motif is likely to change the developmental trajectory of the hairy appendages on barley grains. Our findings indicate that allelic diversity at structurally complex loci may have helped crop plants to adapt to new selective regimes in agricultural ecosystems.

RNA-binding protein SR45, a negative regulator of glucose and abscisic acid (ABA) signaling, promotes the proteasomal degradation of SnRK1, an energy sensor tha

A pan-transcriptome describes the transcriptional and post-transcriptional consequences of genome diversity from multiple individuals within a species. We developed a barley pan-transcriptome using 20 inbred genotypes representing domesticated barley diversity by generating and analyzing short- and long-read RNA-sequencing datasets from multiple tissues. To overcome single reference bias in transcript quantification, we constructed genotype-specific reference transcript datasets (RTDs) and integrated these into a linear pan-genome framework to create a pan-RTD, allowing transcript categorization as core, shell or cloud. Focusing on the core (expressed in all genotypes), we observed significant transcript abundance variation among tissues and between genotypes driven partly by RNA processing, gene copy number, structural rearrangements and conservation of promotor motifs. Network analyses revealed conserved co-expression module::tissue correlations and frequent functional diversification. To complement the pan-transcriptome, we constructed a comprehensive cultivar (cv.) Morex gene-expression atlas and illustrate how these combined datasets can be used to guide biological inquiry.

Background: The time required to analyse RNA-seq data varies considerably, due to discrete steps for computational assembly, quantification of gene expression and splicing analysis. Recent fast non-alignment tools such as Kallisto and Salmon overcome these problems, but these tools require a high quality, comprehensive reference transcripts dataset (RTD), which are rarely available in plants.Results: A high-quality, non-redundant barley gene RTD and database (Barley Reference Transcripts – BaRTv1.0) has been generated. BaRTv1.0, was constructed from a range of tissues, cultivars and abiotic treatments and transcripts assembled and aligned to the barley cv. Morex reference genome (Mascher et al. Nature; 544: 427–433, 2017). Full-length cDNAs from the barley variety Haruna nijo (Matsumoto et al. Plant Physiol; 156: 20–28, 2011) determined transcript coverage, and high-resolution RT-PCR validated alternatively spliced (AS) transcripts of 86 genes in five different organs and tissue. These methods were used as benchmarks to select an optimal barley RTD. BaRTv1.0-Quantification of Alternatively Spliced Isoforms (QUASI) was also made to overcome inaccurate quantification due to variation in 5′ and 3′ UTR ends of transcripts. BaRTv1.0-QUASI was used for accurate transcript quantification of RNA-seq data of five barley organs/tissues. This analysis identified 20,972 significant differentially expressed genes, 2791 differentially alternatively spliced genes and 2768 transcripts with differential transcript usage.Conclusion: A high confidence barley reference transcript dataset consisting of 60,444 genes with 177,240 transcripts has been generated. Compared to current barley transcripts, BaRTv1.0 transcripts are generally longer, have less fragmentation and improved gene models that are well supported by splice junction reads. Precise transcript quantification using BaRTv1.0 allows routine analysis of gene expression and AS.

The RNA helicase and ATPase UPF1 affects transcriptome homeostasis and gene expression through nonsense-mediated RNA decay, splicing, and translation in Arabido

The changing climate is altering timing of key fruit ripening processes and increasing the occurrence of fruit defects. To improve our understanding of the genetic control of raspberry fruit development an enhanced genetic linkage map was developed and used to examine ripening phenotypic data. In this study we developed an enhanced genetic linkage map for the raspberry cvs. Glen Moy x Latham reference mapping population using genotyping by sequencing (GbS). Alignment to a newly sequenced draft reference genome of red raspberry, cultivar (cv.) Glen Moy, identified 8019 single nucleotide polymorphisms (SNPs). After stringent filtering to take account of read coverage over all the progeny individuals, association with a single chromosome, heterozygosity and marker regression mapping, 2348 high confidence SNPs were retained and integrated with an existing raspberry genetic map. The linkage map contained many more SNPs segregating in Latham than in Glen Moy. This caused difficulties in quantitative trait loci (QTL) mapping with standard software and a novel analysis based on a hidden Markov model was used to improve the mapping. QTL mapping using the newly generated dense genetic map not only corroborated previously identified genetic locations but also provided additional genetic elements controlling fruit ripening in raspberry. The high-density GbS map located the QTL peaks more precisely than in earlier studies, aligned the QTLs with Glen Moy genome scaffolds, narrowed the range of potential candidate genes to these regions that can be utilised in other populations or in gene expression studies to confirm their role and increased the repertoire of markers available to understand the genetic control of fruit ripening traits.