Genome-wide analysis of alternative splicing events inHordeum vulgare: Highlighting retention of intron-based splicing and its possible function through network analysis

Trancriptome data mining in combination with co-expression network analysis identifies the functional modules and critical regulators in Hordeum vulgare L. in response to cold stress

Cold stress, as an abiotic stress, is one of the most limiting factors which pose a great threat to the plant's productivity. To understand the transcriptional regulation and connectivity pattern of genes involved in barley cold stress responses, co-expression network analysis was performed based on the global transcriptome profiling. The microarray datasets related to cold stress treatments were retrieved from the Gene Expression Omnibus (GEO) and Array express databases. Four microarray datasets related to cold stress-responsive transcriptome in barley were included in our study. Gene co-expression analysis was constructed using WGCNA method. Module-Trait Relationships (MTR) analysis and hub genes determination and validation were carried out. Finally, transcription factor and kinase regulatory networks were Inferred using machine learning algorithm. The co-expression modules were determined using beta index = 10. In total 13 co-expressed modules were identified with an average size of 153 genes. Functional enrichment based on gene ontology (GO) showed that each of the stress related significant modules were enriched in different biological processes. Annotation of significant modules identifies some TFs and Kinases such as ethylene-responsive transcription factor 1-like, transcription factor PCL1-like, transcription factor MYC2, WRKY, serine/threonine-protein kinase PBL7, and receptor-like protein kinase At2g42960 were contributed in barley cold stress response. Our analysis highlighted the functional importance of ABA signaling pathway, ROS signaling, defensive and protective proteins, degrading protein, Ca2+ related signaling, ribosome-mediated translation and etc. in responding of barley to cold stress condition. The current findings add substantially to our understanding of the cold responsive underlying mechanism of barley which can serve in future studies and breeding programs.

Identification of let-7f and miR-338 as plasma-based biomarkers for sporadic amyotrophic lateral sclerosis using meta-analysis and empirical validation

Amyotrophic lateral sclerosis (ALS) is a lethal neurodegenerative disease that in most cases occurs sporadic (sALS). The disease is not curable, and its pathogenesis mechanisms are not well understood yet. Given the intricacy of underlying molecular interactions and heterogeneity of ALS, the discovery of molecules contributing to disease onset and progression will open a new avenue for advancement in early diagnosis and therapeutic intervention. Here we conducted a meta-analysis of 12 circulating miRNA profiling studies using the robust rank aggregation (RRA) method, followed by enrichment analysis and experimental verification. We identified miR-451a and let-7f-5p as meta-signature miRNAs whose targets are involved in critical pathogenic pathways underlying ALS, including ‘FoxO signaling pathway’, ‘MAPK signaling pathway’, and ‘apoptosis’. A systematic review of 7 circulating gene profiling studies elucidated that 241 genes up-regulated in sALS circulation with concomitant being targets of the meta-signature miRNAs. Protein–protein interaction (PPI) network analysis of the candidate targets using MCODE algorithm revealed the main subcluster is involved in multiple cascades eventually leads apoptosis, including ‘positive regulation of neuron apoptosis. Besides, we validated the meta-analysis results using RT-qPCR. Indeed, relative expression analysis verified let-7f-5p and miR-338-3p as significantly down-regulated and up-regulated biomarkers in the plasma of sALS patients, respectively. Receiver operating characteristic (ROC) analysis also highlighted the let-7f-5p and miR-338-3p potential as robustness plasma biomarkers for diagnosis and potential therapeutic targets of sALS disease.

EORNA, a barley gene and transcript abundance database

A high-quality, barley gene reference transcript dataset (BaRTv1.0), was used to quantify gene and transcript abundances from 22 RNA-seq experiments, covering 843 separate samples. Using the abundance data we developed a Barley Expression Database (EORNA*) to underpin a visualisation tool that displays comparative gene and transcript abundance data on demand as transcripts per million (TPM) across all samples and all the genes. EORNA provides gene and transcript models for all of the transcripts contained in BaRTV1.0, and these can be conveniently identified through either BaRT or HORVU gene names, or by direct BLAST of query sequences. Browsing the quantification data reveals cultivar, tissue and condition specific gene expression and shows changes in the proportions of individual transcripts that have arisen via alternative splicing. TPM values can be easily extracted to allow users to determine the statistical significance of observed transcript abundance variation among samples or perform meta analyses on multiple RNA-seq experiments. * Eòrna is the Scottish Gaelic word for Barley.

EORNA, a barley gene and transcript abundance database

A high-quality, barley gene reference transcript dataset (BaRTv1.0), was used to quantify gene and transcript abundances from 22 RNA-seq experiments, covering 843 separate samples. Using the abundance data we developed a Barley Expression Database (EORNA*) to underpin a visualisation tool that displays comparative gene and transcript abundance data on demand as transcripts per million (TPM) across all samples and all the genes. EORNA provides gene and transcript models for all of the transcripts contained in BaRTV1.0, and these can be conveniently identified through either BaRT or HORVU gene names, or by direct BLAST of query sequences. Browsing the quantification data reveals cultivar, tissue and condition specific gene expression and shows changes in the proportions of individual transcripts that have arisen via alternative splicing. TPM values can be easily extracted to allow users to determine the statistical significance of observed transcript abundance variation among samples or perform meta analyses on multiple RNA-seq experiments. * Eòrna is the Scottish Gaelic word for Barley.

Weighted gene co-expression network analysis identifies modules and functionally enriched pathways in the lactation process

The exponential growth in knowledge has resulted in a better understanding of the lactation process in a wide variety of animals. However, the underlying genetic mechanisms are not yet clearly known. In order to identify the mechanisms involved in the lactation process, various mehods, including meta-analysis, weighted gene co-express network analysis (WGCNA), hub genes identification, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment at before peak (BP), peak (P), and after peak (AP) stages of the lactation processes have been employed. A total of 104, 85, and 26 differentially expressed genes were identified based on PB vs. P, BP vs. AP, and P vs. AP comparisons, respectively. GO and KEGG pathway enrichment analysis revealed that DEGs were significantly enriched in the "ubiquitin-dependent ERAD" and the "chaperone cofactor-dependent protein refolding" in BP vs. P and P vs. P, respectively. WGCNA identified five significant functional modules related to the lactation process. Moreover, GJA1, AP2A2, and NPAS3 were defined as hub genes in the identified modules, highlighting the importance of their regulatory impacts on the lactation process. The findings of this study provide new insights into the complex regulatory networks of the lactation process at three distinct stages, while suggesting several candidate genes that may be useful for future animal breeding programs. Furthermore, this study supports the notion that in combination with a meta-analysis, the WGCNA represents an opportunity to achieve a higher resolution analysis that can better predict the most important functional genes that might provide a more robust bio-signature for phenotypic traits, thus providing more suitable biomarker candidates for future studies.

Weighted gene co-expression network analysis of the salt-responsive transcriptomes reveals novel hub genes in green halophytic microalgae Dunaliella salina

Despite responses to salinity stress in Dunaliella salina, a unicellular halotolerant green alga, being subject to extensive study, but the underlying molecular mechanism remains unknown. Here, Empirical Bayes method was applied to identify the common differentially expressed genes (DEGs) between hypersaline and normal conditions. Then, using weighted gene co-expression network analysis (WGCNA), which takes advantage of a graph theoretical approach, highly correlated genes were clustered as a module. Subsequently, connectivity patterns of the identified modules in two conditions were surveyed to define preserved and non-preserved modules by combining the Zsummary and medianRank measures. Finally, common and specific hub genes in non-preserved modules were determined using Eigengene-based module connectivity or module membership (k_ME) measures and validation was performed by using leave-one-out cross-validation (LOOCV). In this study, the power of beta = 12 (scale-free R2 = 0.8) was selected as the soft-thresholding to ensure a scale-free network, which led to the identification of 15 co-expression modules. Results also indicate that green, blue, brown, and yellow modules are non-preserved in salinity stress conditions. Examples of enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in non-preserved modules are Sulfur metabolism, Oxidative phosphorylation, Porphyrin and chlorophyll metabolism, Vitamin B6 metabolism. Moreover, the systems biology approach was applied here, proposed some salinity specific hub genes, such as radical-induced cell death1 protein (RCD1), mitogen-activated protein kinase kinase kinase 13 (MAP3K13), long-chain acyl-CoA synthetase (ACSL), acetyl-CoA carboxylase, biotin carboxylase subunit (AccC), and fructose-bisphosphate aldolase (ALDO), for the development of metabolites accumulating strains in D. salina.

Global Analysis of Cereal microProteins Suggests Diverse Roles in Crop Development and Environmental Adaptation

MicroProteins are a class of small single-domain proteins that post-translationally regulate larger multidomain proteins from which they evolved or which they relate to. They disrupt the normal function of their targets by forming microProtein-target heterodimers through compatible protein-protein interaction (PPI) domains. Recent studies confirm the significance of microProteins in the fine-tuning of plant developmental processes such as shoot apical meristem maintenance and flowering time regulation. While there are a number of well-characterized microProteins in Arabidopsis thaliana, studies from more complex plant genomes are still missing. We have previously developed miPFinder, a software for identifying microProteins from annotated genomes. Here we present an improved version where we have updated the algorithm to increase its accuracy and speed, and used it to analyze five cereal crop genomes – wheat, rice, barley, maize and sorghum. We found 20,064 potential microProteins from a total of 258,029 proteins in these five organisms, of which approximately 2000 are high-confidence, i.e., likely to function as actual microProteins. Gene ontology analysis of these 2000 microProtein candidates revealed their roles in stress, light and growth responses, hormone signaling and transcriptional regulation. Using a recently developed rice gene co-expression database, we analyzed 347 potential rice microProteins that are also conserved in other cereal crops and found over 50 of these rice microProteins to be co-regulated with their identified interaction partners. Overall, our study reveals a rich source of biotechnologically interesting small proteins that regulate fundamental plant processes such a growth and stress response that could be utilized in crop bioengineering.

Transcriptome signature of two lactation stages in Ghezel sheep identifies using RNA-Sequencing

The expression of genes and their regulation during lactation in Ghezel sheep breed remains less understood. To explore the underlying molecular mechanism of the lactation process in the mammary gland, transcriptome profiles of Iranian fat-tailed Ghezel sheep breed milk at two stages, before (BF) and after peak (AF) stages of lactation were investigated. Functional impacts of differentially expressed genes (DEGs) between BF and AF stages were surveyed using Gene Ontology (GO) and Protein-Protein Interaction (PPI) network analysis. Totally, 75 DEGs were identified between BF and AF stages of lactation. The RNA-Seq results were validated by Q-RT-PCR. Gene ontology of DEGs mainly enriched in metabolic process and oxidative phosphorylation. PPI network analysis also highlighted the contribution of peroxisome proliferator-activated receptors (PPAR) signaling, oxidative phosphorylation and metabolic pathways in the lactation process. Intriguingly, the genes involved in fat metabolism dominantly down-regulated at AF stage. Our results provide new insight into transcriptional changes and add to growing body of knowledge on the lactation process in fat-tailed sheep breeds.

Integrative analysis of gene expression and alternative splicing in microalgae grown under heterotrophic condition

Heterotrophic cultures are the most effective approach to overcome low growth rate challenge in the most commercial microalgae. However, the mechanism through which heterotrophic condition regulates algae metabolism are not completely clear. Alternative Splicing (AS) is a common posttranscriptional process by which transcriptome and proteome plasticity increases at different environmental conditions. To identify and characterize of AS events in Auxenochlorella protothecoides microalga grown in autotrophic and heterotrophic, RNA-Seq data were analysed. We found that AS increased with the transition from autotrophic to heterotrophic condition. 705 and 660 differentially expressed (DEG) and spliced (DAS) genes were identified for A.protothecoides was transferred from autotrophic to heterotrophic condition, respectively. Moreover, there was slight coverage between DEG and DAS genes. Furthermore, functional analysis showed that the DAS genes are most frequently related to ion binding and stimulus response. The results also indicated that prevalence of Intron retention is associated with down-regulation of the genes involved in carotenoid biosynthesis. This study provides valuable insights into transcriptional and posttranscriptional plasticity of microalgae during growth mode change.

Systems biology approach identifies functional modules and regulatory hubs related to secondary metabolites accumulation after transition from autotrophic to heterotrophic growth condition in microalgae

Heterotrophic growth mode is among the most promising strategies put forth to overcome the low biomass and secondary metabolites productivity challenge. To shedding light on the underlying molecular mechanisms, transcriptome meta-analysis was integrated with weighted gene co-expression network analysis (WGCNA), connectivity analysis, functional enrichment, and hubs identification. Meta-analysis and Functional enrichment analysis demonstrated that most of the biological processes are up-regulated at heterotrophic growth condition, which leads to change of genetic architectures and phenotypic outcomes. WGNCA analysis of meta-genes also resulted four significant functional modules across logarithmic (LG), transition (TR), and production peak (PR) phases. The expression pattern and connectivity characteristics of the brown module as a non-preserved module vary across LG, TR, and PR phases. Functional analysis identified Carotenoid biosynthesis, Fatty acid metabolism and Methane metabolism as enriched pathways in the non-preserved module. Our integrated approach was applied here, identified some hubs, such as a serine hydroxymethyltransferase (SHMT1), which is the best candidate for development of metabolites accumulating strains in microalgae. Current study provided a new insight into underlying metabolite accumulation mechanisms and opens new avenue for the future applied studies in the microalgae field.

BaRTv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome using RNA-seq

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.

BaRTv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome using RNA-seq

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.

Integration of Cross Species RNA-seq Meta-Analysis and Machine-Learning Models Identifies the Most Important Salt Stress-Responsive Pathways in Microalga Dunaliella

Photosynthetic microalgae are potentially yielding sources of different high-value secondary metabolites. Salinity is a complex stress that influences various metabolite-related pathways in microalgae. To obtain a clear view of the underlying metabolic pathways and resolve contradictory information concerning the transcriptional regulation of Dunaliella species in salt stress conditions, RNA-seq meta-analysis along with systems levels analysis was conducted. A p-value combination technique with Fisher method was used for cross species meta-analysis on the transcriptomes of two Dunaliella salina and Dunaliellatertiolecta species. The potential functional impacts of core meta-genes were surveyed based on gene ontology and network analysis. In the current study, the integration of supervised machine-learning algorithms with RNA-seq meta-analysis was performed. The analysis shows that the lipid and nitrogen metabolism, structural proteins of photosynthesis apparatus, chaperone-mediated autophagy, and ROS-related genes are the keys and core elements of the Dunaliella salt stress response system. Cross-talk between Ca²⁺ signal transduction, lipid accumulation, and ROS signaling network in salt stress conditions are also proposed. Our novel approach opens new avenues for better understanding of microalgae stress response mechanisms and for selection of candidate gene targets for metabolite production in microalgae.

Genome-wide identification and co-expression network analysis of nuclear factor-Y in barley revealed potential functions in salt stress

Nuclear factor-Ys (NF-Ys) were previously shown to have important regulatory impacts in different developmental and physiological process. However, in barley the function of the NF-Y genes at system levels is not well known. To identify barley NF-Ys, Arabidopsis and wheat NF-Y protein sequences were retrieved and the BLAST program along with the hidden Markov model were used. Multiple sequence alignments of identified NF-Ys were constructed using ClustalW. Expression patterns of the NF-Ys at different physiological and developmental conditions were also surveyed based on microarray datasets in public databases and subsequently co-expression network were constructed. Validation of in silico expression analysis was performed by real-time qPCR under salt stress condition. In total, 23 barley NF-Ys (8 NF-YA, 11 NF-YB and 4 NF-YC) were identified. Based on the sequence homology, the subunits of the NF-Y complex were divided into three to five groups. Structural analysis highlighted the conserved domains of HvNF-YA, HvNF-YB and HvNF-YC. Co-expression network analysis indicated the potential functions of HvNF-Ys in photosynthesis, starch biosynthesis and osmotic stress tolerance. The results of qRT-PCR also confirmed the HvNF-Ys roles in adaptation responses of barley to salt stress. We identified some potential candidate genes which could be used for improvements of cereals tolerance to salinity stress.

Genome-wide analysis of the SPL/miR156 module and its interaction with the AP2/miR172 unit in barley

The SQUAMOSA-promoter binding like (SPL) gene family encodes transcription factors that have been shown in many species to influence plant growth and development, but information about these genes in barley (Hordeum vulgare L.) is limited. This study identified 17 barley SPL genes, within eight distinct groups, that are orthologs of SPL genes described in Arabidopsis, wheat, and rice. Sixteen barley SPLs undergo alternative splicing. Seven SPLs contain a putative miR156 target site and the transcript levels of the miR156-targeted HvSPLs (HvSPL3, 13 and 23) were lower in vegetative than in reproductive phase but this was true also for some SPL genes such as HvSPL6 that were not regulated by miR156. Because SPL gene products regulate miR172, which is also involved in floral development, the expression of miR172 was studied. An antagonistic expression pattern of miR156 and miR172b during the vegetative and the reproductive phases signifies their apparent function in barley growth phase transition. Characterization of a barley mir172 mutant having an abnormal, indeterminate spikelet phenotype suggests the possible feedback role of AP2/miR172 module on HvSPL genes. This is the first comprehensive analysis of the miR156/SPL/miR172 axis in barley that provides a basis to elucidate their roles in various biological processes.

Position-specific intron retention is mediated by the histone methyltransferase SDG725

BACKGROUND

Intron retention (IR), the most prevalent alternative splicing form in plants, plays a critical role in gene expression during plant development and stress response. However, the molecular mechanisms underlying IR regulation remain largely unknown.

RESULTS

Knockdown of SDG725, a histone H3 lysine 36 (H3K36)-specific methyltransferase in rice, leads to alterations of IR in more than 4700 genes. Surprisingly, IR events are globally increased at the 5' region but decreased at the 3' region of the gene body in the SDG725-knockdown mutant. Chromatin immunoprecipitation sequencing analyses reveal that SDG725 depletion results in a genome-wide increase of the H3K36 mono-methylation (H3K36me1) but, unexpectedly, promoter-proximal shifts of H3K36 di- and tri-methylation (H3K36me2 and H3K36me3). Consistent with the results in animals, the levels of H3K36me1/me2/me3 in rice positively correlate with gene expression levels, whereas shifts of H3K36me2/me3 coincide with position-specific alterations of IR. We find that either H3K36me2 or H3K36me3 alone contributes to the positional change of IR caused by SDG725 knockdown, although IR shift is more significant when both H3K36me2 and H3K36me3 modifications are simultaneously shifted.

CONCLUSIONS

Our results revealed that SDG725 modulates IR in a position-specific manner, indicating that H3K36 methylation plays a role in RNA splicing, probably by marking the retained introns in plants.

SpliceDetector: a software for detection of alternative splicing events in human and model organisms directly from transcript IDs

In eukaryotes, different combinations of exons lead to multiple transcripts with various functions in protein level, in a process called alternative splicing (AS). Unfolding the complexity of functional genomics through genome-wide profiling of AS and determining the altered ultimate products provide new insights for better understanding of many biological processes, disease progress as well as drug development programs to target harmful splicing variants. The current available tools of alternative splicing work with raw data and include heavy computation. In particular, there is a shortcoming in tools to discover AS events directly from transcripts. Here, we developed a Windows-based user-friendly tool for identifying AS events from transcripts without the need to any advanced computer skill or database download. Meanwhile, due to online working mode, our application employs the updated SpliceGraphs without the need to any resource updating. First, SpliceGraph forms based on the frequency of active splice sites in pre-mRNA. Then, the presented approach compares query transcript exons to SpliceGraph exons. The tool provides the possibility of statistical analysis of AS events as well as AS visualization compared to SpliceGraph. The developed application works for transcript sets in human and model organisms.

50/50 Expressional Odds of Retention Signifies the Distinction between Retained Introns and Constitutively Spliced Introns in Arabidopsis thaliana

Intron retention, one of the most prevalent alternative splicing events in plants, can lead to introns retained in mature mRNAs. However, in comparison with constitutively spliced introns (CSIs), the relevantly distinguishable features for retained introns (RIs) are still poorly understood. This work proposes a computational pipeline to discover novel RIs from multiple next-generation RNA sequencing (RNA-Seq) datasets of Arabidopsis thaliana. Using this pipeline, we detected 3,472 novel RIs from 18 RNA-Seq datasets and re-confirmed 1,384 RIs which are currently annotated in the TAIR10 database. We also use the expression of intron-containing isoforms as a new feature in addition to the conventional features. Based on these features, RIs are highly distinguishable from CSIs by machine learning methods, especially when the expressional odds of retention (i.e., the expression ratio of the RI-containing isoforms relative to the isoforms without RIs for the same gene) reaches to or larger than 50/50. In this case, the RIs and CSIs can be clearly separated by the Random Forest with an outstanding performance of 0.95 on AUC (the area under a receiver operating characteristics curve). The closely related characteristics to the RIs include the low strength of splice sites, high similarity with the flanking exon sequences, low occurrence percentage of YTRAY near the acceptor site, existence of putative intronic splicing silencers (ISSs, i.e., AG/GA-rich motifs) and intronic splicing enhancers (ISEs, i.e., TTTT-containing motifs), and enrichment of Serine/Arginine-Rich (SR) proteins and heterogeneous nuclear ribonucleoparticle proteins (hnRNPs).

Domestication reduces alternative splicing expression variations in sorghum

Domestication is known to strongly reduce genomic diversity through population bottlenecks. The resulting loss of polymorphism has been thoroughly documented in numerous cultivated species. Here we investigate the impact of domestication on the diversity of alternative transcript expressions using RNAseq data obtained on cultivated and wild sorghum accessions (ten accessions for each pool). In that aim, we focus on genes expressing two isoforms in sorghum and estimate the ratio between expression levels of those isoforms in each accession. Noticeably, for a given gene, one isoform can either be overexpressed or underexpressed in some wild accessions, whereas in the cultivated accessions, the balance between the two isoforms of the same gene appears to be much more homogenous. Indeed, we observe in sorghum significantly more variation in isoform expression balance among wild accessions than among domesticated accessions. The possibility exists that the loss of nucleotide diversity due to domestication could affect regulatory elements, controlling transcription or degradation of these isoforms. Impact on the isoform expression balance is discussed. As far as we know, this is the first time that the impact of domestication on transcript isoform balance has been studied at the genomic scale. This could pave the way towards the identification of key domestication genes with finely tuned isoform expressions in domesticated accessions while being highly variable in their wild relatives.

An improved assembly and annotation of the allohexaploid wheat genome identifies complete families of agronomic genes and provides genomic evidence for chromosomal translocations

Advances in genome sequencing and assembly technologies are generating many high-quality genome sequences, but assemblies of large, repeat-rich polyploid genomes, such as that of bread wheat, remain fragmented and incomplete. We have generated a new wheat whole-genome shotgun sequence assembly using a combination of optimized data types and an assembly algorithm designed to deal with large and complex genomes. The new assembly represents >78% of the genome with a scaffold N50 of 88.8 kb that has a high fidelity to the input data. Our new annotation combines strand-specific Illumina RNA-seq and Pacific Biosciences (PacBio) full-length cDNAs to identify 104,091 high-confidence protein-coding genes and 10,156 noncoding RNA genes. We confirmed three known and identified one novel genome rearrangements. Our approach enables the rapid and scalable assembly of wheat genomes, the identification of structural variants, and the definition of complete gene models, all powerful resources for trait analysis and breeding of this key global crop.

Natural variation in CIRCADIAN CLOCK ASSOCIATED 1 is associated with flowering time in Brassica rapa

Flowering time is a very important agronomic trait and the development of molecular markers associated with this trait can facilitate crop breeding. CIRCADIAN CLOCK ASSOCIATED 1 (CCA1), a core oscillator component of circadian rhythms that affect metabolic pathways in plants, has been implicated in flowering time control in species of Brassica. CCA1 gene sequences from three Brassica rapa inbred lines, showing either early flowering or late flowering phenotypes, were analyzed and a high level of sequence variation was identified, especially within the fourth intron. Using this information, three PCR primer sets were designed and tested using various inbred lines of B. rapa. The usage of InDel markers was further validated by evaluation of flowering time and high resolution melting (HRM) analysis. Both methods, PCR and HRM, validated the use of newly developed markers. Additional sequence analyses of Brassica plants with diploid (AA, BB, or CC) and allotetraploid genomes further confirmed a large number of sequence polymorphisms in the CCA1 gene, including insertions/deletions in the fourth intron. Our results demonstrated that sequence variations in CCA1 can be used to develop valuable trait-related molecular markers for Brassica crop breeding.