Circadian regulation of the transcriptome in a complex polyploid crop.

The circadian clock is a finely balanced timekeeping mechanism that coordinates programmes of gene expression. It is currently unknown how the clock regulates expression of homoeologous genes in polyploids. Here, we generate a high-resolution time-course dataset to investigate the circadian balance between sets of 3 homoeologous genes (triads) from hexaploid bread wheat. We find a large proportion of circadian triads exhibit imbalanced rhythmic expression patterns, with no specific subgenome favoured. In wheat, period lengths of rhythmic transcripts are found to be longer and have a higher level of variance than in other plant species. Expression of transcripts associated with circadian controlled biological processes is largely conserved between wheat and Arabidopsis; however, striking differences are seen in agriculturally critical processes such as starch metabolism. Together, this work highlights the ongoing selection for balance versus diversification in circadian homoeologs and identifies clock-controlled pathways that might provide important targets for future wheat breeding.

Interpreting machine learning models to investigate circadian regulation and facilitate exploration of clock function.

The circadian clock is an important adaptation to life on Earth. Here, we use machine learning to predict complex, temporal, and circadian gene expression patterns in Arabidopsis Most significantly, we classify circadian genes using DNA sequence features generated de novo from public, genomic resources, facilitating downstream application of our methods with no experimental work or prior knowledge needed. We use local model explanation that is transcript specific to rank DNA sequence features, providing a detailed profile of the potential circadian regulatory mechanisms for each transcript. Furthermore, we can discriminate the temporal phase of transcript expression using the local, explanation-derived, and ranked DNA sequence features, revealing hidden subclasses within the circadian class. Model interpretation/explanation provides the backbone of our methodological advances, giving insight into biological processes and experimental design. Next, we use model interpretation to optimize sampling strategies when we predict circadian transcripts using reduced numbers of transcriptomic timepoints. Finally, we predict the circadian time from a single, transcriptomic timepoint, deriving marker transcripts that are most impactful for accurate prediction; this could facilitate the identification of altered clock function from existing datasets.

Whole-genome sequencing uncovers the structural and transcriptomic landscape of hexaploid wheat/Ambylopyrum muticum introgression lines.

Wheat is a globally vital crop, but its limited genetic variation creates a challenge for breeders aiming to maintain or accelerate agricultural improvements over time. Introducing novel genes and alleles from wheat's wild relatives into the wheat breeding pool via introgression lines is an important component of overcoming this low variation but is constrained by poor genomic resolution and limited understanding of the genomic impact of introgression breeding programmes. By sequencing 17 hexaploid wheat/Ambylopyrum muticum introgression lines and the parent lines, we have precisely pinpointed the borders of introgressed segments, most of which occur within genes. We report a genome assembly and annotation of Am. muticum that has facilitated the identification of Am. muticum resistance genes commonly introgressed in lines resistant to stripe rust. Our analysis has identified an abundance of structural disruption and homoeologous pairing across the introgression lines, likely caused by the suppressed Ph1 locus. mRNAseq analysis of six of these introgression lines revealed that novel introgressed genes are rarely expressed and those that directly replace a wheat orthologue have a tendency towards downregulation, with no discernible compensation in the expression of homoeologous copies. This study explores the genomic impact of introgression breeding and provides a schematic that can be followed to characterize introgression lines and identify segments and candidate genes underlying the phenotype. This will facilitate more effective utilization of introgression pre-breeding material in wheat breeding programmes.

Hidden variation in polyploid wheat drives local adaptation.

Wheat has been domesticated into a large number of agricultural environments and has the ability to adapt to diverse environments. To understand this process, we survey genotype, repeat content, and DNA methylation across a bread wheat landrace collection representing global genetic diversity. We identify independent variation in methylation, genotype, and transposon copy number. We show that these, so far unexploited, sources of variation have had a significant impact on the wheat genome and that ancestral methylation states become preferentially "hard coded" as single nucleotide polymorphisms (SNPs) via 5-methylcytosine deamination. These mechanisms also drive local adaption, impacting important traits such as heading date and salt tolerance. Methylation and transposon diversity could therefore be used alongside SNP-based markers for breeding.

Building pangenome graphs.

Pangenome graphs can represent all variation between multiple genomes, but existing methods for constructing them are biased due to reference-guided approaches. In response, we have developed PanGenome Graph Builder (PGGB), a reference-free pipeline for constructing unbi-ased pangenome graphs. PGGB uses all-to-all whole-genome alignments and learned graph embeddings to build and iteratively refine a model in which we can identify variation, measure conservation, detect recombination events, and infer phylogenetic relationships.

Structural and functional analysis of viral siRNAs.

A large amount of short interfering RNA (vsiRNA) is generated from plant viruses during infection, but the function, structure and biogenesis of these is not understood. We profiled vsiRNAs using two different high-throughput sequencing platforms and also developed a hybridisation based array approach. The profiles obtained through the Solexa platform and by hybridisation were very similar to each other but different from the 454 profile. Both deep sequencing techniques revealed a strong bias in vsiRNAs for the positive strand of the virus and identified regions on the viral genome that produced vsiRNA in much higher abundance than other regions. The hybridisation approach also showed that the position of highly abundant vsiRNAs was the same in different plant species and in the absence of RDR6. We used the Terminator 5'-Phosphate-Dependent Exonuclease to study the 5' end of vsiRNAs and showed that a perfect control duplex was not digested by the enzyme without denaturation and that the efficiency of the Terminator was strongly affected by the concentration of the substrate. We found that most vsiRNAs have 5' monophosphates, which was also confirmed by profiling short RNA libraries following either direct ligation of adapters to the 5' end of short RNAs or after replacing any potential 5' ends with monophosphates. The Terminator experiments also showed that vsiRNAs were not perfect duplexes. Using a sensor construct we also found that regions from the viral genome that were complementary to non-abundant vsiRNAs were targeted in planta just as efficiently as regions recognised by abundant vsiRNAs. Different high-throughput sequencing techniques have different reproducible sequence bias and generate different profiles of short RNAs. The Terminator exonuclease does not process double stranded RNA, and because short RNAs can quickly re-anneal at high concentration, this assay can be misleading if the substrate is not denatured and not analysed in a dilution series. The sequence profiles and Terminator digests suggest that CymRSV siRNAs are produced from the structured positive strand rather than from perfect double stranded RNA or by RNA dependent RNA polymerase.

Evidence for GC preference by monocot Dicer-like proteins.

Dicot Dicer-like (DCL) enzymes operate preferably on GC rich regions when producing small interfering (si)RNA and micro (mi)RNA. This GC bias, however, is not generic in monocot miRNA productions. From wild Dactylis glomerata naturally infected by Cocksfoot streak potyvirus (CSV), CSV-siRNAs had a greater GC% than the virus genome, indicating that GC rich regions were also preferred by the grass DCLs. This supports the notion that GC preference is an ancient feature for plant DCLs, and suggests that monocot miRNA genes might have evolved to a high GC% resulting in GC bias being not detectable during mature miRNA production.

Deep sequencing of tomato short RNAs identifies microRNAs targeting genes involved in fruit ripening.

In plants there are several classes of 21-24-nt short RNAs that regulate gene expression. The most conserved class is the microRNAs (miRNAs), although some miRNAs are found only in specific species. We used high-throughput pyrosequencing to identify conserved and nonconserved miRNAs and other short RNAs in tomato fruit and leaf. Several conserved miRNAs showed tissue-specific expression, which, combined with target gene validation results, suggests that miRNAs may play a role in fleshy fruit development. We also identified four new nonconserved miRNAs. One of the validated targets of a novel miRNA is a member of the CTR family involved in fruit ripening. However, 62 predicted targets showing near perfect complementarity to potential new miRNAs did not validate experimentally. This suggests that target prediction of plant short RNAs could have a high false-positive rate and must therefore be validated experimentally. We also found short RNAs from a Solanaceae-specific foldback transposon, which showed a miRNA/miRNA*-like distribution, suggesting that this element may function as a miRNA gene progenitor. The other Solanaceae-specific class of short RNA was derived from an endogenous pararetrovirus sequence inserted into the tomato chromosomes. This study opens a new avenue in the field of fleshy fruit biology by raising the possibility that fruit development and ripening may be under miRNA regulation.