A subcomponent-guided deep learning method for interpretable cancer drug response prediction

Accurate prediction of cancer drug response (CDR) is a longstanding challenge in modern oncology that underpins personalized treatment. Current computational methods implement CDR prediction by modeling responses between entire drugs and cell lines, without the consideration that response outcomes may primarily attribute to a few finer-level 'subcomponents', such as privileged substructures of the drug or gene signatures of the cancer cell, thus producing predictions that are hard to explain. Herein, we present SubCDR, a subcomponent-guided deep learning method for interpretable CDR prediction, to recognize the most relevant subcomponents driving response outcomes. Technically, SubCDR is built upon a line of deep neural networks that enables a set of functional subcomponents to be extracted from each drug and cell line profile, and breaks the CDR prediction down to identifying pairwise interactions between subcomponents. Such a subcomponent interaction form can offer a traceable path to explicitly indicate which subcomponents contribute more to the response outcome. We verify the superiority of SubCDR over state-of-the-art CDR prediction methods through extensive computational experiments on the GDSC dataset. Crucially, we found many predicted cases that demonstrate the strength of SubCDR in finding the key subcomponents driving responses and exploiting these subcomponents to discover new therapeutic drugs. These results suggest that SubCDR will be highly useful for biomedical researchers, particularly in anti-cancer drug design.

Duality of immune recognition by tomato and virulence activity of the Ralstonia solanacearum exo-polygalacturonase PehC

Ralstonia solanacearum is a devastating soil-borne bacterial pathogen capable of infecting many plant species, including tomato (Solanum lycopersicum). However, the perception of Ralstonia by the tomato immune system and the pathogen's counter-defense strategy remain largely unknown. Here, we show that PehC, a specific exo-polygalacturonase secreted by Ralstonia, acts as an elicitor that triggers typical immune responses in tomato and other Solanaceous plants. The elicitor activity of PehC depends on its N-terminal epitope, and not on its polygalacturonase activity. The recognition of PehC specifically occurs in tomato roots and relies on unknown receptor-like kinase(s). Moreover, PehC hydrolyzes plant pectin-derived oligogalacturonic acids (OGs), a type of damage-associated molecular pattern (DAMP), which leads to the release of galacturonic acid (GalA), thereby dampening DAMP-triggered immunity (DTI). Ralstonia depends on PehC for its growth and early infection and can utilize GalA as a carbon source in the xylem. Our findings demonstrate the specialized and dual functions of Ralstonia PehC, which enhance virulence by degrading DAMPs to evade DTI and produce nutrients, a strategy used by pathogens to attenuate plant immunity. Solanaceous plants have evolved to recognize PehC and induce immune responses, which highlights the significance of PehC. Overall, this study provides insight into the arms race between plants and pathogens.

A Ralstonia solanacearum effector targets TGA transcription factors to subvert salicylic acid signaling

The bacterial pathogen Ralstonia solanacearum causes wilt disease on Arabidopsis thaliana and tomato (Solanum lycopersicum). This pathogen uses type III effectors to inhibit the plant immune system; however, how individual effectors interfere with plant immune responses, including transcriptional reprograming, remain elusive. Here, we show that the type III effector RipAB targets Arabidopsis TGACG SEQUENCE-SPECIFIC BINDING PROTEIN (TGA) transcription factors, the central regulators of plant immune gene regulation, via physical interaction in the nucleus to dampen immune responses. RipAB was required for R. solanacearum virulence on wild-type tomato and Arabidopsis but not Arabidopsis tga1 tga4 and tga2 tga5 tga6 mutants. Stable expression of RipAB in Arabidopsis suppressed the pathogen-associated molecular pattern-triggered reactive oxygen species (ROS) burst and immune gene induction as well as salicylic acid (SA) regulons including RBOHD and RBOHF, responsible for ROS production, all of which were phenocopied by the tga1 tga4 and tga2 tga5 tga6 mutants. We found that TGAs directly activate RBOHD and RBOHF expression and that RipAB inhibits this through interfering with the recruitment of RNA polymerase II. These results suggest that TGAs are the bona fide and major virulence targets of RipAB, which disrupts SA signaling by inhibiting TGA activity to achieve successful infection.

SnRK1 stimulates the histone H3K27me3 demethylase JMJ705 to regulate a transcriptional switch to control energy homeostasis

Plant SNF1-Related Kinase1 (SnRK1) is an evolutionarily conserved energy-sensing protein kinase that orchestrates transcriptional networks to maintain cellular energy homeostasis when energy supplies become limited. However, the mechanism by which SnRK1 regulates this gene expression switch to gauge cellular energy status remains largely unclear. In this work, we show that the rice histone H3K27me3 demethylase JMJ705 is required for low energy stress tolerance in rice plants. The genetic inactivation of JMJ705 resulted in similar effects as those of the rice snrk1 mutant on the transcriptome, which impairs not only the promotion of the low energy stress-triggered transcriptional program but also the repression of the program under an energy-sufficient state. We show that the α-subunit of OsSnRK1 interacts with and phosphorylates JMJ705 to stimulate its H3K27me3 demethylase activity. Further analysis revealed that JMJ705 directly targets a set of low energy stress-responsive transcription factor genes. These results uncover the chromatin mechanism of SnRK1-regulated gene expression in both energy-sufficient and -limited states in plants and suggest that JMJ705 functions as an upstream regulator of the SnRK1α-controlled transcriptional network.

Gene expression evolution in pattern-triggered immunity within Arabidopsis thaliana and across Brassicaceae species

Plants recognize surrounding microbes by sensing microbe-associated molecular patterns (MAMPs) to activate pattern-triggered immunity (PTI). Despite their significance for microbial control, the evolution of PTI responses remains largely uncharacterized. Here, by employing comparative transcriptomics of six Arabidopsis thaliana accessions and three additional Brassicaceae species to investigate PTI responses, we identified a set of genes that commonly respond to the MAMP flg22 and genes that exhibit species-specific expression signatures. Variation in flg22-triggered transcriptome responses across Brassicaceae species was incongruent with their phylogeny, while expression changes were strongly conserved within A. thaliana. We found the enrichment of WRKY transcription factor binding sites in the 5'-regulatory regions of conserved and species-specific responsive genes, linking the emergence of WRKY-binding sites with the evolution of gene expression patterns during PTI. Our findings advance our understanding of the evolution of the transcriptome during biotic stress.

Parental variation in CHG methylation is associated with allelic-specific expression in elite hybrid rice

Heterosis refers to the superior performance of hybrid lines over inbred parental lines. Besides genetic variation, epigenetic differences between parental lines are suggested to contribute to heterosis. However, the precise nature and extent of differences between the parental epigenomes and the reprograming in hybrids that govern heterotic gene expression remain unclear. In this work, we analyzed DNA methylomes and transcriptomes of the widely cultivated and genetically studied elite hybrid rice (Oryza sativa) SY63, the reciprocal hybrid, and the parental varieties ZS97 and MH63, for which high-quality reference genomic sequences are available. We showed that the parental varieties displayed substantial variation in genic methylation at CG and CHG (H = A, C, or T) sequences. Compared with their parents, the hybrids displayed dynamic methylation variation during development. However, many parental differentially methylated regions (DMRs) at CG and CHG sites were maintained in the hybrid. Only a small fraction of the DMRs displayed non-additive DNA methylation variation, which, however, showed no overall correlation relationship with gene expression variation. In contrast, most of the allelic-specific expression (ASE) genes in the hybrid were associated with DNA methylation, and the ASE negatively associated with allelic-specific methylation (ASM) at CHG. These results revealed a specific DNA methylation reprogramming pattern in the hybrid rice and pointed to a role for parental CHG methylation divergence in ASE, which is associated with phenotype variation and hybrid vigor in several plant species.

The ATR-WEE1 kinase module inhibits the MAC complex to regulate replication stress response

DNA damage response is a fundamental mechanism to maintain genome stability. The ATR-WEE1 kinase module plays a central role in response to replication stress. Although the ATR-WEE1 pathway has been well studied in yeasts and animals, how ATR-WEE1 functions in plants remains unclear. Through a genetic screen for suppressors of the Arabidopsis atr mutant, we found that loss of function of PRL1, a core subunit of the evolutionarily conserved MAC complex involved in alternative splicing, suppresses the hypersensitivity of atr and wee1 to replication stress. Biochemical studies revealed that WEE1 directly interacts with and phosphorylates PRL1 at Serine 145, which promotes PRL1 ubiquitination and subsequent degradation. In line with the genetic and biochemical data, replication stress induces intron retention of cell cycle genes including CYCD1;1 and CYCD3;1, which is abolished in wee1 but restored in wee1 prl1. Remarkably, co-expressing the coding sequences of CYCD1;1 and CYCD3;1 partially restores the root length and HU response in wee1 prl1. These data suggested that the ATR-WEE1 module inhibits the MAC complex to regulate replication stress responses. Our study discovered PRL1 or the MAC complex as a key downstream regulator of the ATR-WEE1 module and revealed a novel cell cycle control mechanism.

Population-level analysis reveals the widespread occurrence and phenotypic consequence of DNA methylation variation not tagged by genetic variation in maize

BACKGROUND

DNA methylation can provide a source of heritable information that is sometimes entirely uncoupled from genetic variation. However, the extent of this uncoupling and the roles of DNA methylation in shaping diversity of both gene expression and phenotypes are hotly debated. Here, we investigate the genetic basis and biological functions of DNA methylation at a population scale in maize.

RESULTS

We perform targeted DNA methylation profiling for a diverse panel of 263 maize inbred genotypes. All genotypes show similar levels of DNA methylation globally, highlighting the importance of DNA methylation in maize development. Nevertheless, we identify more than 16,000 differentially methylated regions (DMRs) that are distributed across the 10 maize chromosomes. Genome-wide association analysis with high-density genetic markers reveals that over 60% of the DMRs are not tagged by SNPs, suggesting the presence of unique information in DMRs. Strong associations between DMRs and the expression of many genes are identified in both the leaf and kernel tissues, pointing to the biological significance of methylation variation. Association analysis with 986 metabolic traits suggests that DNA methylation is associated with phenotypic variation of 156 traits. There are some traits that only show significant associations with DMRs and not with SNPs.

CONCLUSIONS

These results suggest that DNA methylation can provide unique information to explain phenotypic variation in maize.

A network embedding-based multiple information integration method for the MiRNA-disease association prediction

BACKGROUND

MiRNAs play significant roles in many fundamental and important biological processes, and predicting potential miRNA-disease associations makes contributions to understanding the molecular mechanism of human diseases. Existing state-of-the-art methods make use of miRNA-target associations, miRNA-family associations, miRNA functional similarity, disease semantic similarity and known miRNA-disease associations, but the known miRNA-disease associations are not well exploited.

RESULTS

In this paper, a network embedding-based multiple information integration method (NEMII) is proposed for the miRNA-disease association prediction. First, known miRNA-disease associations are formulated as a bipartite network, and the network embedding method Structural Deep Network Embedding (SDNE) is adopted to learn embeddings of nodes in the bipartite network. Second, the embedding representations of miRNAs and diseases are combined with biological features about miRNAs and diseases (miRNA-family associations and disease semantic similarities) to represent miRNA-disease pairs. Third, the prediction models are constructed based on the miRNA-disease pairs by using the random forest. In computational experiments, NEMII achieves high-accuracy performances and outperforms other state-of-the-art methods: GRNMF, NTSMDA and PBMDA. The usefulness of NEMII is further validated by case studies. The studies demonstrate the great potential of network embedding method for the miRNA-disease association prediction, and SDNE outperforms other popular network embedding methods: DeepWalk, High-Order Proximity preserved Embedding (HOPE) and Laplacian Eigenmaps (LE).

CONCLUSION

We propose a new method, named NEMII, for predicting miRNA-disease associations, which has great potential to benefit the field of miRNA-disease association prediction.

Amplification-free library preparation with SAFE Hi-C uses ligation products for deep sequencing to improve traditional Hi-C analysis

PCR amplification of Hi-C libraries introduces unusable duplicates and results in a biased representation of chromatin interactions. We present a simplified, fast, and economically efficient Hi-C library preparation procedure, SAFE Hi-C, which generates sufficient non-amplified ligation products for deep sequencing from 30 million Drosophila cells. Comprehensive analysis of the resulting data shows that amplification-free Hi-C preserves higher complexity of chromatin interaction and lowers sequencing depth for the same number of unique paired reads. For human cells which have a large genome, SAFE Hi-C recovers enough ligated fragments for direct high-throughput sequencing without amplification from as few as 250,000 cells. Comparison with published in situ Hi-C data from millions of human cells demonstrates that amplification introduces distance-dependent amplification bias, which results in an increased background noise level against genomic distance. With amplification bias avoided, SAFE Hi-C may produce a chromatin interaction network more faithfully reflecting the real three-dimensional genomic architecture.

The RCC1 family protein SAB1 negatively regulates ABI5 through multidimensional mechanisms during postgermination in Arabidopsis

Abscisic acid-insensitive 5 (ABI5) is an essential and conserved plant basic leucine zipper transcription factor whose level controls seed germination and postgerminative development. It has been demonstrated that activity of ABI5 is transcriptionally and post-translationally regulated. However, transcriptional regulation of ABI5 is not fully understood. Here, we identified SAB1 (Sensitive to ABA 1) as a novel negative regulator of ABI5 that simultaneously regulates its stability, promoter binding activity and histone methylation-mediated gene silencing of ABI5. SAB1 encodes a Regulator of Chromatin Condensation 1 (RCC1) family protein and is expressed in an opposite pattern to that of ABI5 during early seedling growth in response to abscisic acid (ABA). SAB1 mutation results in enhanced ABA sensitivity and acts upstream of ABI5. SAB1 physically interacts with ABI5 at phosphoamino acid Ser-145, and reduces the phosphorylation of ABI5 and the protein stability. SAB1 reduces ABI5 binding activity to its own promoter, leading to reduced transcriptional level of ABI5. SAB1 inactivates ABI5 transcription by increasing the level of histone H3K27me2 in the ABI5 promoter. Our findings have identified SAB1 as a crucial new component of ABA signaling which modulates early development of plant by precisely controlling ABI5 activity through multiple mechanisms.

An integrated omics analysis reveals molecular mechanisms that are associated with differences in seed oil content between Glycine max and Brassica napus

BACKGROUND

Rapeseed (Brassica napus L.) and soybean (Glycine max L.) seeds are rich in both protein and oil, which are major sources of biofuels and nutrition. Although the difference in seed oil content between soybean (~ 20%) and rapeseed (~ 40%) exists, little is known about its underlying molecular mechanism.

RESULTS

An integrated omics analysis was performed in soybean, rapeseed, Arabidopsis (Arabidopsis thaliana L. Heynh), and sesame (Sesamum indicum L.), based on Arabidopsis acyl-lipid metabolism- and carbon metabolism-related genes. As a result, candidate genes and their transcription factors and microRNAs, along with phylogenetic analysis and co-expression network analysis of the PEPC gene family, were found to be largely associated with the difference between the two species. First, three soybean genes (Glyma.13G148600, Glyma.13G207900 and Glyma.12G122900) co-expressed with GmPEPC1 are specifically enriched during seed storage protein accumulation stages, while the expression of BnPEPC1 is putatively inhibited by bna-miR169, and two genes BnSTKA and BnCKII are co-expressed with BnPEPC1 and are specifically associated with plant circadian rhythm, which are related to seed oil biosynthesis. Then, in de novo fatty acid synthesis there are rapeseed-specific genes encoding subunits β-CT (BnaC05g37990D) and BCCP1 (BnaA03g06000D) of heterogeneous ACCase, which could interfere with synthesis rate, and β-CT is positively regulated by four transcription factors (BnaA01g37250D, BnaA02g26190D, BnaC01g01040D and BnaC07g21470D). In triglyceride synthesis, GmLPAAT2 is putatively inhibited by three miRNAs (gma-miR171, gma-miR1516 and gma-miR5775). Finally, in rapeseed there was evidence for the expansion of gene families, CALO, OBO and STERO, related to lipid storage, and the contraction of gene families, LOX, LAH and HSI2, related to oil degradation.

CONCLUSIONS

The molecular mechanisms associated with differences in seed oil content provide the basis for future breeding efforts to improve seed oil content.

The miR172c-NNC1 module modulates root plastic development in response to salt in soybean

BACKGROUND

Plant roots are highly plastic to high salinity. However, the molecular mechanism by which root developmental plasticity is regulated remains largely unknown. Previously we reported that miR172c-NNC1 module plays a key role in soybean-rhizobial symbiosis. The fact that the miR172c promoter contains several stress-related cis elements indicates that miR172c may have a role in root response to abiotic stress.

RESULTS

Here we showed that miR172c is greatly induced by salt stress in soybean. Overexpression of miR172c and knockdown of miR172c activity resulted in substantially increased and reduced root sensitivity to salt stress, respectively. Furthermore, we show that the target gene NNC1 (Nodule Number Control 1) of miR172c was downregulated by salt stress. The transgenic roots overexpressing or knocking down NNC1 expression also exhibited the altered root sensitivity to salt stress.

CONCLUSION

The study reveals the crucial role of miR172c-NNC1 module in root stress tolerance to salt stress in soybean.

SCFAtPP2-B11 modulates ABA signaling by facilitating SnRK2.3 degradation in Arabidopsis thaliana

The phytohormone abscisic acid (ABA) is an essential part of the plant response to abiotic stressors such as drought. Upon the perception of ABA, pyrabactin resistance (PYR)/PYR1-like (PYL)/regulatory components of ABA receptor (RCAR) proteins interact with co-receptor protein phosphatase type 2Cs to permit activation Snf1-related protein kinase2 (SnRK2) kinases, which switch on ABA signaling by phosphorylating various target proteins. Thus, SnRK2 kinases are central regulators of ABA signaling. However, the mechanisms that regulate SnRK2 degradation remain elusive. Here, we show that SnRK2.3 is degradated by 26S proteasome system and ABA promotes its degradation. We found that SnRK2.3 interacts with AtPP2-B11 directly. AtPP2-B11 is an F-box protein that is part of a SKP1/Cullin/F-box E3 ubiquitin ligase complex that negatively regulates plant responses to ABA by specifically promoting the degradation of SnRK2.3. AtPP2-B11 was induced by ABA, and the knockdown of AtPP2-B11 expression markedly increased the ABA sensitivity of plants during seed germination and postgerminative development. Overexpression of AtPP2-B11 does not affect ABA sensitivity, but inhibits the ABA hypersensitive phenotypes of SnRK2.3 overexpression lines. These results reveal a novel mechanism through which AtPP2-B11 specifically degrades SnRK2.3 to attenuate ABA signaling and the abiotic stress response in Arabidopsis.