Optimizing sequence design strategies for perturbation MPRAs: a computational evaluation framework.

The advent of perturbation-based massively parallel reporter assays (MPRAs) technique has facilitated the delineation of the roles of non-coding regulatory elements in orchestrating gene expression. However, computational efforts remain scant to evaluate and establish guidelines for sequence design strategies for perturbation MPRAs. In this study, we propose a framework for evaluating and comparing various perturbation strategies for MPRA experiments. Within this framework, we benchmark three different perturbation approaches from the perspectives of alteration in motif-based profiles, consistency of MPRA outputs, and robustness of models that predict the activities of putative regulatory motifs. While our analyses show very similar results across multiple benchmarking metrics, the predictive modeling for the approach involving random nucleotide shuffling shows significant robustness compared with the other two approaches. Thus, we recommend designing sequences by randomly shuffling the nucleotides of the perturbed site in perturbation-MPRA, followed by a coherence check to prevent the introduction of other variations of the target motifs. In summary, our evaluation framework and the benchmarking findings create a resource of computational pipelines and highlight the potential of perturbation-MPRA in predicting non-coding regulatory activities.

A systematic evaluation of the design and context dependencies of massively parallel reporter assays.

Massively parallel reporter assays (MPRAs) functionally screen thousands of sequences for regulatory activity in parallel. To date, there are limited studies that systematically compare differences in MPRA design. Here, we screen a library of 2,440 candidate liver enhancers and controls for regulatory activity in HepG2 cells using nine different MPRA designs. We identify subtle but significant differences that correlate with epigenetic and sequence-level features, as well as differences in dynamic range and reproducibility. We also validate that enhancer activity is largely independent of orientation, at least for our library and designs. Finally, we assemble and test the same enhancers as 192-mers, 354-mers and 678-mers and observe sizable differences. This work provides a framework for the experimental design of high-throughput reporter assays, suggesting that the extended sequence context of tested elements and to a lesser degree the precise assay, influence MPRA results.

Characterization of De Novo Promoter Variants in Autism Spectrum Disorder with Massively Parallel Reporter Assays.

Autism spectrum disorder (ASD) is a common, complex, and highly heritable condition with contributions from both common and rare genetic variations. While disruptive, rare variants in protein-coding regions clearly contribute to symptoms, the role of rare non-coding remains unclear. Variants in these regions, including promoters, can alter downstream RNA and protein quantity; however, the functional impacts of specific variants observed in ASD cohorts remain largely uncharacterized. Here, we analyzed 3600 de novo mutations in promoter regions previously identified by whole-genome sequencing of autistic probands and neurotypical siblings to test the hypothesis that mutations in cases have a greater functional impact than those in controls. We leveraged massively parallel reporter assays (MPRAs) to detect transcriptional consequences of these variants in neural progenitor cells and identified 165 functionally high confidence de novo variants (HcDNVs). While these HcDNVs are enriched for markers of active transcription, disruption to transcription factor binding sites, and open chromatin, we did not identify differences in functional impact based on ASD diagnostic status.

A systematic comparison reveals substantial differences in chromosomal versus episomal encoding of enhancer activity.

Candidate enhancers can be identified on the basis of chromatin modifications, the binding of chromatin modifiers and transcription factors and cofactors, or chromatin accessibility. However, validating such candidates as bona fide enhancers requires functional characterization, typically achieved through reporter assays that test whether a sequence can increase expression of a transcriptional reporter via a minimal promoter. A longstanding concern is that reporter assays are mainly implemented on episomes, which are thought to lack physiological chromatin. However, the magnitude and determinants of differences in cis-regulation for regulatory sequences residing in episomes versus chromosomes remain almost completely unknown. To address this systematically, we developed and applied a novel lentivirus-based massively parallel reporter assay (lentiMPRA) to directly compare the functional activities of 2236 candidate liver enhancers in an episomal versus a chromosomally integrated context. We find that the activities of chromosomally integrated sequences are substantially different from the activities of the identical sequences assayed on episomes, and furthermore are correlated with different subsets of ENCODE annotations. The results of chromosomally based reporter assays are also more reproducible and more strongly predictable by both ENCODE annotations and sequence-based models. With a linear model that combines chromatin annotations and sequence information, we achieve a Pearson's R2 of 0.362 for predicting the results of chromosomally integrated reporter assays. This level of prediction is better than with either chromatin annotations or sequence information alone and also outperforms predictive models of episomal assays. Our results have broad implications for how cis-regulatory elements are identified, prioritized and functionally validated.

Integration of multiple epigenomic marks improves prediction of variant impact in saturation mutagenesis reporter assay.

The integrative analysis of high-throughput reporter assays, machine learning, and profiles of epigenomic chromatin state in a broad array of cells and tissues has the potential to significantly improve our understanding of noncoding regulatory element function and its contribution to human disease. Here, we report results from the CAGI 5 regulation saturation challenge where participants were asked to predict the impact of nucleotide substitution at every base pair within five disease-associated human enhancers and nine disease-associated promoters. A library of mutations covering all bases was generated by saturation mutagenesis and altered activity was assessed in a massively parallel reporter assay (MPRA) in relevant cell lines. Reporter expression was measured relative to plasmid DNA to determine the impact of variants. The challenge was to predict the functional effects of variants on reporter expression. Comparative analysis of the full range of submitted prediction results identifies the most successful models of transcription factor binding sites, machine learning algorithms, and ways to choose among or incorporate diverse datatypes and cell-types for training computational models. These results have the potential to improve the design of future studies on more diverse sets of regulatory elements and aid the interpretation of disease-associated genetic variation.

Decoding enhancers using massively parallel reporter assays.

Enhancers control the timing, location and expression levels of their target genes. Nucleotide variation in enhancers has been shown to lead to numerous phenotypes, including human disease. While putative enhancer sequences and nucleotide variation within them can now be detected in a rapid manner using various genomic technologies, the understanding of the functional consequences of these variants still remains largely unknown. Massively parallel reporter assays (MPRAs) can overcome this hurdle by providing the ability to test thousands of sequences and nucleotide variants within them for enhancer activity en masse. Here, we describe this technology and specifically focus on how it is being used to obtain an increased understanding of enhancer regulatory code and grammar.

Problems with using total serum bilirubin as a criterion for phototherapy in extremely low-birthweight infants.

BACKGROUND: Despite the early use of phototherapy and exchange transfusion in premature infants based on total serum bilirubin (TSB), the reemergence of kernicterus has been reported. The aim of this study was to assess the validity of using TSB as the criterion for phototherapy in extremely low-birthweight infants (ELBWI). METHODS: We reviewed the medical charts of 43 ELBWI admitted to hospital between January 2009 and December 2010, and analyzed the relationship between TSB and unbound bilirubin (UB). RESULTS: No infant underwent exchange transfusion or developed acute bilirubin encephalopathy. There was a significant correlation between TSB and UB measured immediately before phototherapy during the first 7 days of life (r = 0.657, P < 0.001), but none thereafter (r = 0.120, P = 0.213). Thirty-seven percent of infants who underwent phototherapy during the first 7 days of life had suprathreshold USB but subthreshold TSB, whereas this rose to 97% thereafter. CONCLUSIONS: No correlation was observed between TSB and UB in ELBWI after the first 7 days of life, and almost all phototherapy sessions were initiated based on the UB criterion, even though TSB was below the accepted threshold. UB may be high if jaundice is evaluated solely on the basis of TSB.

Comprehensive network modeling approaches unravel dynamic enhancer-promoter interactions across neural differentiation.

BACKGROUND: Increasing evidence suggests that a substantial proportion of disease-associated mutations occur in enhancers, regions of non-coding DNA essential to gene regulation. Understanding the structures and mechanisms of the regulatory programs this variation affects can shed light on the apparatuses of human diseases. RESULTS: We collect epigenetic and gene expression datasets from seven early time points during neural differentiation. Focusing on this model system, we construct networks of enhancer-promoter interactions, each at an individual stage of neural induction. These networks serve as the base for a rich series of analyses, through which we demonstrate their temporal dynamics and enrichment for various disease-associated variants. We apply the Girvan-Newman clustering algorithm to these networks to reveal biologically relevant substructures of regulation. Additionally, we demonstrate methods to validate predicted enhancer-promoter interactions using transcription factor overexpression and massively parallel reporter assays. CONCLUSIONS: Our findings suggest a generalizable framework for exploring gene regulatory programs and their dynamics across developmental processes; this includes a comprehensive approach to studying the effects of disease-associated variation on transcriptional networks. The techniques applied to our networks have been published alongside our findings as a computational tool, E-P-INAnalyzer. Our procedure can be utilized across different cellular contexts and disorders.

Comprehensive network modeling approaches unravel dynamic enhancer-promoter interactions across neural differentiation.

Background: Increasing evidence suggests that a substantial proportion of disease-associated mutations occur in enhancers, regions of non-coding DNA essential to gene regulation. Understanding the structures and mechanisms of regulatory programs this variation affects can shed light on the apparatuses of human diseases. Results: We collected epigenetic and gene expression datasets from seven early time points during neural differentiation. Focusing on this model system, we constructed networks of enhancer-promoter interactions, each at an individual stage of neural induction. These networks served as the base for a rich series of analyses, through which we demonstrated their temporal dynamics and enrichment for various disease-associated variants. We applied the Girvan-Newman clustering algorithm to these networks to reveal biologically relevant substructures of regulation. Additionally, we demonstrated methods to validate predicted enhancer-promoter interactions using transcription factor overexpression and massively parallel reporter assays. Conclusions: Our findings suggest a generalizable framework for exploring gene regulatory programs and their dynamics across developmental processes. This includes a comprehensive approach to studying the effects of disease-associated variation on transcriptional networks. The techniques applied to our networks have been published alongside our findings as a computational tool, E-P-INAnalyzer. Our procedure can be utilized across different cellular contexts and disorders.

Characterization of enhancer activity in early human neurodevelopment using Massively Parallel Reporter Assay (MPRA) and forebrain organoids.

Regulation of gene expression through enhancers is one of the major processes shaping the structure and function of the human brain during development. High-throughput assays have predicted thousands of enhancers involved in neurodevelopment, and confirming their activity through orthogonal functional assays is crucial. Here, we utilized Massively Parallel Reporter Assays (MPRAs) in stem cells and forebrain organoids to evaluate the activity of ~ 7000 gene-linked enhancers previously identified in human fetal tissues and brain organoids. We used a Gaussian mixture model to evaluate the contribution of background noise in the measured activity signal to confirm the activity of ~ 35% of the tested enhancers, with most showing temporal-specific activity, suggesting their evolving role in neurodevelopment. The temporal specificity was further supported by the correlation of activity with gene expression. Our findings provide a valuable gene regulatory resource to the scientific community.

Massively parallel characterization of regulatory elements in the developing human cortex.

Nucleotide changes in gene regulatory elements are important determinants of neuronal development and diseases. Using massively parallel reporter assays in primary human cells from mid-gestation cortex and cerebral organoids, we interrogated the cis-regulatory activity of 102,767 open chromatin regions, including thousands of sequences with cell type-specific accessibility and variants associated with brain gene regulation. In primary cells, we identified 46,802 active enhancer sequences and 164 variants that alter enhancer activity. Activity was comparable in organoids and primary cells, suggesting that organoids provide an adequate model for the developing cortex. Using deep learning we decoded the sequence basis and upstream regulators of enhancer activity. This work establishes a comprehensive catalog of functional gene regulatory elements and variants in human neuronal development.

Integrative functional genomic analyses identify genetic variants influencing skin pigmentation in Africans.

Skin color is highly variable in Africans, yet little is known about the underlying molecular mechanism. Here we applied massively parallel reporter assays to screen 1,157 candidate variants influencing skin pigmentation in Africans and identified 165 single-nucleotide polymorphisms showing differential regulatory activities between alleles. We combine Hi-C, genome editing and melanin assays to identify regulatory elements for MFSD12, HMG20B, OCA2, MITF, LEF1, TRPS1, BLOC1S6 and CYB561A3 that impact melanin levels in vitro and modulate human skin color. We found that independent mutations in an OCA2 enhancer contribute to the evolution of human skin color diversity and detect signals of local adaptation at enhancers of MITF, LEF1 and TRPS1, which may contribute to the light skin color of Khoesan-speaking populations from Southern Africa. Additionally, we identified CYB561A3 as a novel pigmentation regulator that impacts genes involved in oxidative phosphorylation and melanogenesis. These results provide insights into the mechanisms underlying human skin color diversity and adaptive evolution.

The same enhancer regulates the earliest Emx2 expression in caudal forebrain primordium, subsequent expression in dorsal telencephalon and later expression in the cortical ventricular zone.

We have analyzed Emx2 enhancers to determine how Emx2 functions during forebrain development are regulated. The FB (forebrain) enhancer we identified immediately 3' downstream of the last coding exon is well conserved among tetrapods and unexpectedly directed all the Emx2 expression in forebrain: caudal forebrain primordium at E8.5, dorsal telencephalon at E9.5-E10.5 and the cortical ventricular zone after E12.5. Otx, Tcf, Smad and two unknown transcription factor binding sites were essential to all these activities. The mutant that lacked this enhancer demonstrated that Emx2 expression under the enhancer is solely responsible for diencephalon development. However, in telencephalon, the FB enhancer did not have activities in cortical hem or Cajal-Retzius cells, nor was its activity in the cortex graded. Emx2 expression was greatly reduced, but persisted in the telencephalon of the enhancer mutant, indicating that there exists another enhancer for Emx2 expression unique to mammalian telencephalon.

Feeding interval and postprandial intestinal blood flow in premature infants.

BACKGROUND: The feeding interval is an important factor in enteral feeding of premature infants. We investigated postprandial intestinal blood flow in stable very-low-birthweight infants fed at 2-h and 3-h intervals. METHODS: We used pulsed wave Doppler ultrasound to measure blood flow velocity of the superior mesenteric artery (SMA) before feeding and at 15, 30, 45, and 60 min after feeding. Measurements were made on the day of starting enteral nutrition (1 or 2 days of age), and at 3 and 5 days of age. A total of 21 studies were performed in seven infants fed every 2 h, and 54 studies were performed in 18 infants fed every 3 h. RESULTS: In infants fed every 2 h, SMA blood flow velocity increased from before feeding to 30 min after feeding and then decreased at 60 min after feeding. In infants fed every 3 h, SMA blood flow velocity increased after feeding, reaching a peak at 30 min. The correlation coefficients between the volume of milk per feed and the postprandial increase in time-averaged mean blood flow velocity were 0.398 (P = 0.074, n = 21) and 0.597 (P = 0.000, n = 54) in infants fed at 2-h and 3-h intervals, respectively. CONCLUSIONS: SMA blood flow velocity significantly increased after feeding in infants fed at 2-h and 3-h intervals. The volume of milk per feed might affect the postprandial increase in SMA blood flow velocity.

[A case of crescentic glomerulonephritis developed under oral anastrozole treatment].

A 69-year-old postmenopausal woman who was prescribed anastrozole for 10 months after surgical removal of her breast cancer, was referred to our hospital for acute renal failure. Because it was possible that her renal failure was related to her treatment with anastrozole, the treatment was immediately discontinued. After renal biopsy was performed to examine her renal failure, she was diagnosed as crescentic glomerulonephritis, probably related with the treatment of anastrozole. Twenty mg of oral prednisolone was administered daily after methylprednisolone pulse therapy(500 mg/day intravenous administration for three days). Her renal dysfunction was gradually improved. Renal dysfunction was considered to be a rare complication of anastrozole. Patients who are prescribed anastrozole should be watched carefully for the development of renal dysfunction.

Best practices for perturbation MPRA-a computational evaluation framework of sequence design strategies.

The advent of the perturbation-based massively parallel reporter assays (MPRAs) technique has enabled delineating of the roles of non-coding regulatory elements in orchestrating gene expression. However, computational efforts remain scant to evaluate and establish guidelines for sequence design strategies for perturbation MPRAs. Here, we propose a framework for evaluating and comparing various perturbation strategies for MPRA experiments. Under this framework, we benchmark three different perturbation approaches from the perspectives of alteration in motif-based profiles, consistency of MPRA outputs, and robustness of models that predict the activities of putative regulatory motifs. Although our analyses show similar while significant results in multiple metrics, the method of randomly shuffling nucleotides outperform the other two methods. Thus, we still recommend designing sequences by randomly shuffling the nucleotides of the perturbed site in perturbation-MPRA. The evaluation framework, together with the benchmarking findings in our work, creates a resource of computational pipelines and illustrates the promise of perturbation-MPRA for predicting non-coding regulatory activities.

Characterization of enhancer activity in early human neurodevelopment using Massively parallel reporter assay (MPRA) and forebrain organoids.

Regulation of gene expression through enhancers is one of the major processes shaping the structure and function of the human brain during development. High-throughput assays have predicted thousands of enhancers involved in neurodevelopment, and confirming their activity through orthogonal functional assays is crucial. Here, we utilized Massively Parallel Reporter Assays (MPRAs) in stem cells and forebrain organoids to evaluate the activity of ~7,000 gene-linked enhancers previously identified in human fetal tissues and brain organoids. We used a Gaussian mixture model to evaluate the contribution of background noise in the measured activity signal to confirm the activity of ~35% of the tested enhancers, with most showing temporal-specific activity, suggesting their evolving role in neurodevelopment. The temporal specificity was further supported by the correlation of activity with gene expression. Our findings provide a valuable gene regulatory resource to the scientific community.

A Nosocomial Outbreak Caused by Human Rhinovirus Species A Type 61 in a Welfare Facility in Gunma Prefecture, Japan.

Human rhinovirus (HRV) infections are generally referred to as the common cold, and are the main cause of mild symptoms. HRV is less frequently implicated in the development of severe respiratory infections. This study reports a nosocomial outbreak of bronchitis and pneumonia caused by HRV in a hospital during the COVID-19 epidemic in September 2022 in Gunma Prefecture, Japan. The patient continued to be symptomatic for nine days. During this outbreak, all 15 residents displayed respiratory symptoms. HRV-A was detected in 12 of the 12 samples, and phylogenetic analysis classified the strain as HRV-A type 61. HRV, COVID-19, and other respiratory infections cannot be differentiated based solely on clinical symptoms. A surveillance system to monitor them is thus needed.

Transcription factor binding site orientation and order are major drivers of gene regulatory activity.

The gene regulatory code and grammar remain largely unknown, precluding our ability to link phenotype to genotype in regulatory sequences. Here, using a massively parallel reporter assay (MPRA) of 209,440 sequences, we examine all possible pair and triplet combinations, permutations and orientations of eighteen liver-associated transcription factor binding sites (TFBS). We find that TFBS orientation and order have a major effect on gene regulatory activity. Corroborating these results with genomic analyses, we find clear human promoter TFBS orientation biases and similar TFBS orientation and order transcriptional effects in an MPRA that tested 164,307 liver candidate regulatory elements. Additionally, by adding TFBS orientation to a model that predicts expression from sequence we improve performance by 7.7%. Collectively, our results show that TFBS orientation and order have a significant effect on gene regulatory activity and need to be considered when analyzing the functional effect of variants on the activity of these sequences.