BACKGROUND: It is apparent that genomes harbor much structural variation that is largely undetected for technical reasons. Such variation can cause artifacts when short-read sequencing data are mapped to a reference genome. Spurious SNPs may result from mapping of reads to unrecognized duplicated regions. Calling SNP using the raw reads of the 1001 Arabidopsis Genomes Project we identified 3.3 million (44%) heterozygous SNPs. Given that Arabidopsis thaliana (A. thaliana) is highly selfing, and that extensively heterozygous individuals have been removed, we hypothesize that these SNPs reflected cryptic copy number variation. RESULTS: The heterozygosity we observe consists of particular SNPs being heterozygous across individuals in a manner that strongly suggests it reflects shared segregating duplications rather than random tracts of residual heterozygosity due to occasional outcrossing. Focusing on such pseudo-heterozygosity in annotated genes, we use genome-wide association to map the position of the duplicates. We identify 2500 putatively duplicated genes and validate them using de novo genome assemblies from six lines. Specific examples included an annotated gene and nearby transposon that transpose together. We also demonstrate that cryptic structural variation produces highly inaccurate estimates of DNA methylation polymorphism. CONCLUSIONS: Our study confirms that most heterozygous SNP calls in A. thaliana are artifacts and suggest that great caution is needed when analyzing SNP data from short-read sequencing. The finding that 10% of annotated genes exhibit copy-number variation, and the realization that neither gene- nor transposon-annotation necessarily tells us what is actually mobile in the genome suggests that future analyses based on independently assembled genomes will be very informative.

Inference and analysis of gene regulatory networks (GRNs) require software that integrates multi-omic data from various sources. The Network Zoo (netZoo; netzoo.github.io) is a collection of open-source methods to infer GRNs, conduct differential network analyses, estimate community structure, and explore the transitions between biological states. The netZoo builds on our ongoing development of network methods, harmonizing the implementations in various computing languages and between methods to allow better integration of these tools into analytical pipelines. We demonstrate the utility using multi-omic data from the Cancer Cell Line Encyclopedia. We will continue to expand the netZoo to incorporate additional methods.

BACKGROUND: Reptiles exhibit a wide variety of skin colors, which serve essential roles in survival and reproduction. However, the molecular basis of these conspicuous colors remains unresolved. RESULTS: We investigate color morph-enriched Asian vine snakes (Ahaetulla prasina), to explore the mechanism underpinning color variations. Transmission electron microscopy imaging and metabolomics analysis indicates that chromatophore morphology (mainly iridophores) is the main basis for differences in skin color. Additionally, we assemble a 1.77-Gb high-quality chromosome-anchored genome of the snake. Genome-wide association study and RNA sequencing reveal a conservative amino acid substitution (p.P20S) in SMARCE1, which may be involved in the regulation of chromatophore development initiated from neural crest cells. SMARCE1 knockdown in zebrafish and immunofluorescence verify the interactions among SMARCE1, iridophores, and tfec, which may determine color variations in the Asian vine snake. CONCLUSIONS: This study reveals the genetic associations of color variation in Asian vine snakes, providing insights and important resources for a deeper understanding of the molecular and genetic mechanisms related to reptilian coloration.

Chemical modifications of RNAs, known as the epitranscriptome, are emerging as widespread regulatory mechanisms underlying gene regulation. The field of epitranscriptomics advances recently due to improved transcriptome-wide sequencing strategies for mapping RNA modifications and intensive characterization of writers, erasers, and readers that deposit, remove, and recognize RNA modifications, respectively. Herein, we review recent advances in characterizing plant epitranscriptome and its regulatory mechanisms in post-transcriptional gene regulation and diverse physiological processes, with main emphasis on N6-methyladenosine (m6A) and 5-methylcytosine (m5C). We also discuss the potential and challenges for utilization of epitranscriptome editing in crop improvement.

BACKGROUND: Increased expression of the complement component 4A (C4A) gene is associated with a greater lifetime risk of schizophrenia. In the brain, C4A is involved in synaptic pruning; yet, it remains unclear the extent to which upregulation of C4A alters brain development or is associated with the risk for psychotic symptoms in childhood. Here, we perform a multi-ancestry phenome-wide association study in 7789 children aged 9-12 years to examine the relationship between genetically regulated expression (GREx) of C4A, childhood brain structure, cognition, and psychiatric symptoms. RESULTS: While C4A GREx is not related to childhood psychotic experiences, cognition, or global measures of brain structure, it is associated with a localized reduction in regional surface area (SA) of the entorhinal cortex. Furthermore, we show that reduced entorhinal cortex SA at 9-10 years predicts a greater number and severity of psychosis-like events at 1-year and 2-year follow-up time points. We also demonstrate that the effects of C4A on the entorhinal cortex are independent of genome-wide polygenic risk for schizophrenia. CONCLUSIONS: Our results suggest neurodevelopmental effects of C4A on childhood medial temporal lobe structure, which may serve as a biomarker for schizophrenia risk prior to symptom onset.

Spatially resolved transcriptomics (SRT)-specific computational methods are often developed, tested, validated, and evaluated in silico using simulated data. Unfortunately, existing simulated SRT data are often poorly documented, hard to reproduce, or unrealistic. Single-cell simulators are not directly applicable for SRT simulation as they cannot incorporate spatial information. We present SRTsim, an SRT-specific simulator for scalable, reproducible, and realistic SRT simulations. SRTsim not only maintains various expression characteristics of SRT data but also preserves spatial patterns. We illustrate the benefits of SRTsim in benchmarking methods for spatial clustering, spatial expression pattern detection, and cell-cell communication identification.

BACKGROUND: There is widespread interest in the three-dimensional chromatin conformation of the genome and its impact on gene expression. However, these studies frequently do not consider parent-of-origin differences, such as genomic imprinting, which result in monoallelic expression. In addition, genome-wide allele-specific chromatin conformation associations have not been extensively explored. There are few accessible bioinformatic workflows for investigating allelic conformation differences and these require pre-phased haplotypes which are not widely available. RESULTS: We developed a bioinformatic pipeline, "HiCFlow," that performs haplotype assembly and visualization of parental chromatin architecture. We benchmarked the pipeline using prototype haplotype phased Hi-C data from GM12878 cells at three disease-associated imprinted gene clusters. Using Region Capture Hi-C and Hi-C data from human cell lines (1-7HB2, IMR-90, and H1-hESCs), we can robustly identify the known stable allele-specific interactions at the IGF2-H19 locus. Other imprinted loci (DLK1 and SNRPN) are more variable and there is no "canonical imprinted 3D structure," but we could detect allele-specific differences in A/B compartmentalization. Genome-wide, when topologically associating domains (TADs) are unbiasedly ranked according to their allele-specific contact frequencies, a set of allele-specific TADs could be defined. These occur in genomic regions of high sequence variation. In addition to imprinted genes, allele-specific TADs are also enriched for allele-specific expressed genes. We find loci that have not previously been identified as allele-specific expressed genes such as the bitter taste receptors (TAS2Rs). CONCLUSIONS: This study highlights the widespread differences in chromatin conformation between heterozygous loci and provides a new framework for understanding allele-specific expressed genes.

BACKGROUND: Enhancers are essential in defining cell fates through the control of cell-type-specific gene expression. Enhancer activation is a multi-step process involving chromatin remodelers and histone modifiers including the monomethylation of H3K4 (H3K4me1) by MLL3 (KMT2C) and MLL4 (KMT2D). MLL3/4 are thought to be critical for enhancer activation and cognate gene expression including through the recruitment of acetyltransferases for H3K27. RESULTS: Here we test this model by evaluating the impact of MLL3/4 loss on chromatin and transcription during early differentiation of mouse embryonic stem cells. We find that MLL3/4 activity is required at most if not all sites that gain or lose H3K4me1 but is largely dispensable at sites that remain stably methylated during this transition. This requirement extends to H3K27 acetylation (H3K27ac) at most transitional sites. However, many sites gain H3K27ac independent of MLL3/4 or H3K4me1 including enhancers regulating key factors in early differentiation. Furthermore, despite the failure to gain active histone marks at thousands of enhancers, transcriptional activation of nearby genes is largely unaffected, thus uncoupling the regulation of these chromatin events from transcriptional changes during this transition. These data challenge current models of enhancer activation and imply distinct mechanisms between stable and dynamically changing enhancers. CONCLUSIONS: Collectively, our study highlights gaps in knowledge about the steps and epistatic relationships of enzymes necessary for enhancer activation and cognate gene transcription.

Epigenetic modifications of histones are associated with development and pathogenesis of disease. Existing approaches cannot provide insights into long-range interactions and represent the average chromatin state. Here we describe BIND&MODIFY, a method using long-read sequencing for profiling histone modifications and transcription factors on individual DNA fibers. We use recombinant fused protein A-M.EcoGII to tether methyltransferase M.EcoGII to protein binding sites to label neighboring regions by methylation. Aggregated BIND&MODIFY signal matches bulk ChIP-seq and CUT&TAG. BIND&MODIFY can simultaneously measure histone modification status, transcription factor binding, and CpG 5mC methylation at single-molecule resolution and also quantifies correlation between local and distal elements.

BACKGROUND: Genome-wide association studies (GWAS) have identified > 200 loci associated with breast cancer risk. The majority of candidate causal variants are in non-coding regions and likely modulate cancer risk by regulating gene expression. However, pinpointing the exact target of the association, and identifying the phenotype it mediates, is a major challenge in the interpretation and translation of GWAS. RESULTS: Here, we show that pooled CRISPR screens are highly effective at identifying GWAS target genes and defining the cancer phenotypes they mediate. Following CRISPR mediated gene activation or suppression, we measure proliferation in 2D, 3D, and in immune-deficient mice, as well as the effect on DNA repair. We perform 60 CRISPR screens and identify 20 genes predicted with high confidence to be GWAS targets that promote cancer by driving proliferation or modulating the DNA damage response in breast cells. We validate the regulation of a subset of these genes by breast cancer risk variants. CONCLUSIONS: We demonstrate that phenotypic CRISPR screens can accurately pinpoint the gene target of a risk locus. In addition to defining gene targets of risk loci associated with increased breast cancer risk, we provide a platform for identifying gene targets and phenotypes mediated by risk variants.

BACKGROUND: Maize (Zea mays L.) is one of the most important crops worldwide. Although sophisticated maize gene regulatory networks (GRNs) have been constructed for functional genomics and phenotypic dissection, a multi-omics GRN connecting the translatome and transcriptome is lacking, hampering our understanding and exploration of the maize regulatome. RESULTS: We collect spatio-temporal translatome and transcriptome data and systematically explore the landscape of gene transcription and translation across 33 tissues or developmental stages of maize. Using this comprehensive transcriptome and translatome atlas, we construct a multi-omics GRN integrating mRNAs and translated mRNAs, demonstrating that translatome-related GRNs outperform GRNs solely using transcriptomic data and inter-omics GRNs outperform intra-omics GRNs in most cases. With the aid of the multi-omics GRN, we reconcile some known regulatory networks. We identify a novel transcription factor, ZmGRF6, which is associated with growth. Furthermore, we characterize a function related to drought response for the classic transcription factor ZmMYB31. CONCLUSIONS: Our findings provide insights into spatio-temporal changes across maize development at both the transcriptome and translatome levels. Multi-omics GRNs represent a useful resource for dissection of the regulatory mechanisms underlying phenotypic variation.

Ageing is inherent to all human beings, yet why we age remains a hotly contested topic. Most mechanistic explanations of ageing posit that ageing is caused by the accumulation of one or more forms of molecular damage. Here, I propose that we age not because of inevitable damage to the hardware but rather because of intrinsic design flaws in the software, defined as the DNA code that orchestrates how a single cell develops into an adult organism. As the developmental software runs, its sequence of events is reflected in shifting cellular epigenetic states. Overall, I suggest that to understand ageing we need to decode our software and the flow of epigenetic information throughout the life course.

The annual Genome Informatics conference was held at the Wellcome Genome Campus on September 21-23, 2022. The conference covered a remarkable range of topics of which we highlight a few in this report.

Significant improvements in long-read sequencing technologies have unlocked complex genomic areas, such as centromeres, in the genome and introduced the centromere annotation problem. Currently, centromeres are annotated in a semi-manual way. Here, we propose HiCAT, a generalizable automatic centromere annotation tool, based on hierarchical tandem repeat mining to facilitate decoding of centromere architecture. We apply HiCAT to simulated datasets, human CHM13-T2T and gapless Arabidopsis thaliana genomes. Our results are generally consistent with previous inferences but also greatly improve annotation continuity and reveal additional fine structures, demonstrating HiCAT's performance and general applicability.

BACKGROUND: The largest sequence-based models of transcription control to date are obtained by predicting genome-wide gene regulatory assays across the human genome. This setting is fundamentally correlative, as those models are exposed during training solely to the sequence variation between human genes that arose through evolution, questioning the extent to which those models capture genuine causal signals. RESULTS: Here we confront predictions of state-of-the-art models of transcription regulation against data from two large-scale observational studies and five deep perturbation assays. The most advanced of these sequence-based models, Enformer, by and large, captures causal determinants of human promoters. However, models fail to capture the causal effects of enhancers on expression, notably in medium to long distances and particularly for highly expressed promoters. More generally, the predicted impact of distal elements on gene expression predictions is small and the ability to correctly integrate long-range information is significantly more limited than the receptive fields of the models suggest. This is likely caused by the escalating class imbalance between actual and candidate regulatory elements as distance increases. CONCLUSIONS: Our results suggest that sequence-based models have advanced to the point that in silico study of promoter regions and promoter variants can provide meaningful insights and we provide practical guidance on how to use them. Moreover, we foresee that it will require significantly more and particularly new kinds of data to train models accurately accounting for distal elements.

We present GenEra ( https://github.com/josuebarrera/GenEra ), a DIAMOND-fueled gene-family founder inference framework that addresses previously raised limitations and biases in genomic phylostratigraphy, such as homology detection failure. GenEra also reduces computational time from several months to a few days for any genome of interest. We analyze the emergence of taxonomically restricted gene families during major evolutionary transitions in plants, animals, and fungi. Our results indicate that the impact of homology detection failure on inferred patterns of gene emergence is lineage-dependent, suggesting that plants are more prone to evolve novelty through the emergence of new genes compared to animals and fungi.

BACKGROUND: Transcription bridges genetic information and phenotypes. Here, we evaluated how changes in transcriptional regulation enable maize (Zea mays), a crop originally domesticated in the tropics, to adapt to temperate environments. RESULT: We generated 572 unique RNA-seq datasets from the roots of 340 maize genotypes. Genes involved in core processes such as cell division, chromosome organization and cytoskeleton organization showed lower heritability of gene expression, while genes involved in anti-oxidation activity exhibited higher expression heritability. An expression genome-wide association study (eGWAS) identified 19,602 expression quantitative trait loci (eQTLs) associated with the expression of 11,444 genes. A GWAS for alternative splicing identified 49,897 splicing QTLs (sQTLs) for 7614 genes. Genes harboring both cis-eQTLs and cis-sQTLs in linkage disequilibrium were disproportionately likely to encode transcription factors or were annotated as responding to one or more stresses. Independent component analysis of gene expression data identified loci regulating co-expression modules involved in oxidation reduction, response to water deprivation, plastid biogenesis, protein biogenesis, and plant-pathogen interaction. Several genes involved in cell proliferation, flower development, DNA replication, and gene silencing showed lower gene expression variation explained by genetic factors between temperate and tropical maize lines. A GWAS of 27 previously published phenotypes identified several candidate genes overlapping with genomic intervals showing signatures of selection during adaptation to temperate environments. CONCLUSION: Our results illustrate how maize transcriptional regulatory networks enable changes in transcriptional regulation to adapt to temperate regions.

BACKGROUND: Alternative splicing is a widespread regulatory phenomenon that enables a single gene to produce multiple transcripts. Among the different types of alternative splicing, intron retention is one of the least explored despite its high prevalence in both plants and animals. The recent discovery that the majority of splicing is co-transcriptional has led to the finding that chromatin state affects alternative splicing. Therefore, it is plausible that transcription factors can regulate splicing outcomes. RESULTS: We provide evidence for the hypothesis that transcription factors are involved in the regulation of intron retention by studying regions of open chromatin in retained and excised introns. Using deep learning models designed to distinguish between regions of open chromatin in retained introns and non-retained introns, we identified motifs enriched in IR events with significant hits to known human transcription factors. Our model predicts that the majority of transcription factors that affect intron retention come from the zinc finger family. We demonstrate the validity of these predictions using ChIP-seq data for multiple zinc finger transcription factors and find strong over-representation for their peaks in intron retention events. CONCLUSIONS: This work opens up opportunities for further studies that elucidate the mechanisms by which transcription factors affect intron retention and other forms of splicing. AVAILABILITY: Source code available at https://github.com/fahadahaf/chromir.

BACKGROUND: Phosphorylation of proteins is a key step in the regulation of many cellular processes including activation of enzymes and signaling cascades. The abundance of a phosphorylated peptide (phosphopeptide) is determined by the abundance of its parent protein and the proportion of target sites that are phosphorylated. RESULTS: We quantified phosphopeptides, proteins, and transcripts in heart, liver, and kidney tissue samples of mice from 58 strains of the Collaborative Cross strain panel. We mapped ~700 phosphorylation quantitative trait loci (phQTL) across the three tissues and applied genetic mediation analysis to identify causal drivers of phosphorylation. We identified kinases, phosphatases, cytokines, and other factors, including both known and potentially novel interactions between target proteins and genes that regulate site-specific phosphorylation. Our analysis highlights multiple targets of pyruvate dehydrogenase kinase 1 (PDK1), a regulator of mitochondrial function that shows reduced activity in the NZO/HILtJ mouse, a polygenic model of obesity and type 2 diabetes. CONCLUSIONS: Together, this integrative multi-omics analysis in genetically diverse CC strains provides a powerful tool to identify regulators of protein phosphorylation. The data generated in this study provides a resource for further exploration.

Cis-regulatory elements are coordinated to regulate the expression of their targeted genes. However, the joint measurement of cis-regulatory elements' activities and their interactions in spatial proximity is limited by the current sequencing approaches. We describe a method, NOMe-HiC, which simultaneously captures single-nucleotide polymorphisms, DNA methylation, chromatin accessibility (GpC methyltransferase footprints), and chromosome conformation changes from the same DNA molecule, together with the transcriptome, in a single assay. NOMe-HiC shows high concordance with state-of-the-art mono-omic assays across different molecular measurements and reveals coordinated chromatin accessibility at distal genomic segments in spatial proximity and novel types of long-range allele-specific chromatin accessibility.

BACKGROUND: Genomic imprinting affects gene expression in a parent-of-origin manner and has a profound impact on complex traits including growth and behavior. While the rat is widely used to model human pathophysiology, few imprinted genes have been identified in this murid. To systematically identify imprinted genes and genomic imprints in the rat, we use low input methods for genome-wide analyses of gene expression and DNA methylation to profile embryonic and extraembryonic tissues at allele-specific resolution. RESULTS: We identify 14 and 26 imprinted genes in these tissues, respectively, with 10 of these genes imprinted in both tissues. Comparative analyses with mouse reveal that orthologous imprinted gene expression and associated canonical DNA methylation imprints are conserved in the embryo proper of the Muridae family. However, only 3 paternally expressed imprinted genes are conserved in the extraembryonic tissue of murids, all of which are associated with non-canonical H3K27me3 imprints. The discovery of 8 novel non-canonical imprinted genes unique to the rat is consistent with more rapid evolution of extraembryonic imprinting. Meta-analysis of novel imprinted genes reveals multiple mechanisms by which species-specific imprinted expression may be established, including H3K27me3 deposition in the oocyte, the appearance of ZFP57 binding motifs, and the insertion of endogenous retroviral promoters. CONCLUSIONS: In summary, we provide an expanded list of imprinted loci in the rat, reveal the extent of conservation of imprinted gene expression, and identify potential mechanisms responsible for the evolution of species-specific imprinting.

BACKGROUND: The epidermis of cotton ovule produces fibers, the most important natural cellulose source for the global textile industry. However, the molecular mechanism of fiber cell growth is still poorly understood. RESULTS: Here, we develop an optimized protoplasting method, and integrate single-cell RNA sequencing (scRNA-seq) and single-cell ATAC sequencing (scATAC-seq) to systematically characterize the cells of the outer integument of ovules from wild type and fuzzless/lintless (fl) cotton (Gossypium hirsutum). By jointly analyzing the scRNA-seq data from wildtype and fl, we identify five cell populations including the fiber cell type and construct the development trajectory for fiber lineage cells. Interestingly, by time-course diurnal transcriptomic analysis, we demonstrate that the primary growth of fiber cells is a highly regulated circadian rhythmic process. Moreover, we identify a small peptide GhRALF1 that circadian rhythmically controls fiber growth possibly through oscillating auxin signaling and proton pump activity in the plasma membrane. Combining with scATAC-seq, we further identify two cardinal cis-regulatory elements (CREs, TCP motif, and TCP-like motif) which are bound by the trans factors GhTCP14s to modulate the circadian rhythmic metabolism of mitochondria and protein translation through regulating approximately one third of genes that are highly expressed in fiber cells. CONCLUSIONS: We uncover a fiber-specific circadian clock-controlled gene expression program in regulating fiber growth. This study unprecedentedly reveals a new route to improve fiber traits by engineering the circadian clock of fiber cells.