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Abstract Background Genome-wide association studies (GWAS) aim to correlate phenotypic changes with genotypic variation. Upon transcription, single nucleotide variants (SNVs) may alter mRNA structure, with potential impacts on transcript stability, macromolecular interactions, and translation. However, plant genomes have not been assessed for the presence of these structure-altering polymorphisms or “riboSNitches.” Results We experimentally demonstrate the presence of riboSNitches in transcripts of two Arabidopsis genes, ZINC RIBBON 3 ( ZR3 ) and COTTON GOLGI-RELATED 3 ( CGR3 ), which are associated with continentality and temperature variation in the natural environment. These riboSNitches are also associated with differences in the abundance of their respective transcripts, implying a role in regulating the gene's expression in adaptation to local climate conditions. We then computationally predict riboSNitches transcriptome-wide in mRNAs of 879 naturally inbred Arabidopsis accessions. We characterize correlations between SNPs/riboSNitches in these accessions and 434 climate descriptors of their local environments, suggesting a role of these variants in local adaptation. We integrate this information in CLIMtools V2.0 and provide a new web resource, T-CLIM, that reveals associations between transcript abundance variation and local environmental variation. Conclusion We functionally validate two plant riboSNitches and, for the first time, demonstrate riboSNitch conditionality dependent on temperature, coining the term “conditional riboSNitch.” We provide the first pan-genome-wide prediction of riboSNitches in plants. We expand our previous CLIMtools web resource with riboSNitch information and with 1868 additional Arabidopsis genomes and 269 additional climate conditions, which will greatly facilitate in silico studies of natural genetic variation, its phenotypic consequences, and its role in local adaptation. 

In plants, vegetative and reproductive development are associated with agronomically important traits that contribute to grain yield and biomass. Zinc finger homeodomain (ZF-HD) transcription factors (TFs) constitute a relatively small gene family that has been studied in several model plants, including Arabidopsis thaliana L. and Oryza sativa L. The ZF-HD family members play important roles in plant growth and development, but their contribution to the regulation of plant architecture remains largely unknown due to their functional redundancy. To understand the gene regulatory network controlled by ZF-HD TFs, we analyzed multiple loss-of-function mutants of ZF-HD TFs in Arabidopsis that exhibited morphological abnormalities in branching and flowering architecture. We found that ZF-HD TFs, especially HB34, negatively regulate the expression of miR157 and positively regulate SQUAMOSA PROMOTER BINDING–LIKE 10 (SPL10), a target of miR157. Genome-wide chromatin immunoprecipitation sequencing (ChIP-Seq) analysis revealed that miR157D and SPL10 are direct targets of HB34, creating a feed-forward loop that constitutes a robust miRNA regulatory module. Network motif analysis contains overrepresented coherent type IV feedforward motifs in the amiR zf-HD and hbq mutant background. This finding indicates that miRNA-mediated ZF-HD feedforward modules modify branching and inflorescence architecture in Arabidopsis. Taken together, these findings reveal a guiding role of ZF-HD TFs in the regulatory network module and demonstrate its role in plant architecture in Arabidopsis. 

The genome sequence of the diploid and highly homozygous Vitis vinifera genotype PN40024 serves as the reference for many grapevine studies. Despite several improvements to the PN40024 genome assembly, its current version PN12X.v2 is quite fragmented and only represents the haploid state of the genome with mixed haplotypes. In fact, being nearly homozygous, this genome contains several heterozygous regions that are yet to be resolved. Taking the opportunity of improvements that long-read sequencing technologies offer to fully discriminate haplotype sequences, an improved version of the reference, called PN40024.v4, was generated. Through incorporating long genomic sequencing reads to the assembly, the continuity of the 12X.v2 scaffolds was highly increased with a total number decreasing from 2,059 to 640 and a reduction in N bases of 88%. Additionally, the full alternative haplotype sequence was built for the first time, the chromosome anchoring was improved and the number of unplaced scaffolds was reduced by half. To obtain a high-quality gene annotation that outperforms previous versions, a liftover approach was complemented with an optimized annotation workflow for Vitis. Integration of the gene reference catalogue and its manual curation have also assisted in improving the annotation, while defining the most reliable estimation of 35,230 genes to date. Finally, we demonstrated that PN40024 resulted from 9 selfings of cv. “Helfensteiner” (cross of cv. “Pinot noir” and “Schiava grossa”) instead of a single “Pinot noir”. These advances will help maintain the PN40024 genome as a gold-standard reference, also contributing toward the eventual elaboration of the grapevine pangenome.

 

Abstract We review how a data infrastructure for the Plant Cell Atlas might be built using existing infrastructure and platforms. The Human Cell Atlas has developed an extensive infrastructure for human and mouse single cell data, while the European Bioinformatics Institute has developed a Single Cell Expression Atlas, that currently houses several plant data sets. We discuss issues related to appropriate ontologies for describing a plant single cell experiment. We imagine how such an infrastructure will enable biologists and data scientists to glean new insights into plant biology in the coming decades, as long as such data are made accessible to the community in an open manner. 

Haplotype phasing maize genetic variants is important for genome interpretation, population genetic analysis and functional analysis of allelic activity. We performed an isoform-level phasing study using two maize inbred lines and their reciprocal crosses, based on single-molecule, full-length cDNA sequencing. To phase and analyze transcripts between hybrids and parents, we developed IsoPhase. Using this tool, we validated the majority of SNPs called against matching short-read data from embryo, endosperm and root tissues, and identified allele-specific, gene-level and isoform-level differential expression between the inbred parental lines and hybrid offspring. After phasing 6907 genes in the reciprocal hybrids, we annotated the SNPs and identified large-effect genes. In addition, we identified parent-of-origin isoforms, distinct novel isoforms in maize parent and hybrid lines, and imprinted genes from different tissues. Finally, we characterized variation in cis- and trans-regulatory effects. Our study provides measures of haplotypic expression that could increase accuracy in studies of allelic expression.

 

The PacBio^®HiFi sequencing method yields highly accurate long-read sequencing datasets with read lengths averaging 10–25 kb and accuracies greater than 99.5%. These accurate long reads can be used to improve results for complex applications such as single nucleotide and structural variant detection, genome assembly, assembly of difficult polyploid or highly repetitive genomes, and assembly of metagenomes. Currently, there is a need for sample data sets to both evaluate the benefits of these long accurate reads as well as for development of bioinformatic tools including genome assemblers, variant callers, and haplotyping algorithms. We present deep coverage HiFi datasets for five complex samples including the two inbred model genomesMus musculusandZea mays, as well as two complex genomes, octoploidFragaria × ananassaand the diploid anuranRana muscosa. Additionally, we release sequence data from a mock metagenome community. The datasets reported here can be used without restriction to develop new algorithms and explore complex genome structure and evolution. Data were generated on the PacBio Sequel II System.

 

The rapid accumulation of both sequence and phenotype data generated by high-throughput methods has increased the need to store and analyze data on distributed storage and computing systems. Efficient data management across these heterogeneous systems requires a workflow management system to simplify the task of analysis through automation and make large-scale bioinformatics analyses accessible and reproducible.

We developed SciApps, a web-based platform for reproducible bioinformatics workflows. The platform is designed to automate the execution of modular Agave apps and support execution of workflows on local clusters or in a cloud. Two workflows, one for association and one for annotation, are provided as exemplar scientific use cases.

https://www.sciapps.org

Supplementary data are available at Bioinformatics online.