SARS-CoV-2-infection- and vaccine-induced antibody responses are long lasting with an initial waning phase followed by a stabilization phase.

It is thought that mRNA-based vaccine-induced immunity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) wanes quickly, based mostly on short-term studies. Here, we analyzed the kinetics and durability of the humoral responses to SARS-CoV-2 infection and vaccination using >8,000 longitudinal samples collected over a 3-year period in New York City. Upon primary immunization, participants with pre-existing immunity mounted higher antibody responses faster and achieved higher steady-state antibody titers than naive individuals. Antibody kinetics were characterized by two phases: an initial rapid decay, followed by a stabilization phase with very slow decay. Booster vaccination equalized the differences in antibody concentration between participants with and without hybrid immunity, but the peak antibody titers decreased with each successive antigen exposure. Breakthrough infections increased antibodies to similar titers as an additional vaccine dose in naive individuals. Our study provides strong evidence that SARS-CoV-2 antibody responses are long lasting, with initial waning followed by stabilization.

HLTF resolves G4s and promotes G4-induced replication fork slowing to maintain genome stability.

G-quadruplexes (G4s) form throughout the genome and influence important cellular processes. Their deregulation can challenge DNA replication fork progression and threaten genome stability. Here, we demonstrate an unexpected role for the double-stranded DNA (dsDNA) translocase helicase-like transcription factor (HLTF) in responding to G4s. We show that HLTF, which is enriched at G4s in the human genome, can directly unfold G4s in vitro and uses this ATP-dependent translocase function to suppress G4 accumulation throughout the cell cycle. Additionally, MSH2 (a component of MutS heterodimers that bind G4s) and HLTF act synergistically to suppress G4 accumulation, restrict alternative lengthening of telomeres, and promote resistance to G4-stabilizing drugs. In a discrete but complementary role, HLTF restrains DNA synthesis when G4s are stabilized by suppressing primase-polymerase (PrimPol)-dependent repriming. Together, the distinct roles of HLTF in the G4 response prevent DNA damage and potentially mutagenic replication to safeguard genome stability.

Tolerance thresholds underlie responses to DNA damage during germline development.

Selfish DNA modules like transposable elements (TEs) are particularly active in the germline, the lineage that passes genetic information across generations. New TE insertions can disrupt genes and impair the functionality and viability of germ cells. However, we found that in P-M hybrid dysgenesis in Drosophila, a sterility syndrome triggered by the P-element DNA transposon, germ cells harbor unexpectedly few new TE insertions despite accumulating DNA double-strand breaks (DSBs) and inducing cell cycle arrest. Using an engineered CRISPR-Cas9 system, we show that generating DSBs at silenced P-elements or other noncoding sequences is sufficient to induce germ cell loss independently of gene disruption. Indeed, we demonstrate that both developing and adult mitotic germ cells are sensitive to DSBs in a dosage-dependent manner. Following the mitotic-to-meiotic transition, however, germ cells become more tolerant to DSBs, completing oogenesis regardless of the accumulated genome damage. Our findings establish DNA damage tolerance thresholds as crucial safeguards of genome integrity during germline development.

Dominance and multi-locus interaction.

Dominance is usually considered a constant value that describes the relative difference in fitness or phenotype between heterozygotes and the average of homozygotes at a focal polymorphic locus. However, the observed dominance can vary with the genetic background of the focal locus. Here, alleles at other loci modify the observed phenotype through position effects or dominance modifiers that are sometimes associated with pathogen resistance, lineage, sex, or mating type. Theoretical models have illustrated how variable dominance appears in the context of multi-locus interaction (epistasis). Here, we review empirical evidence for variable dominance and how the observed patterns may be captured by proposed epistatic models. We highlight how integrating epistasis and dominance is crucial for comprehensively understanding adaptation and speciation.

The genetic landscape of age-related hearing loss.

Age-related hearing loss (ARHL) is a prevalent concern in the elderly population. Recent genome-wide and phenome-wide association studies (GWASs and PheWASs) have delved into the identification of causative variants and the understanding of pleiotropy, highlighting the polygenic intricacies of this complex condition. While recent large-scale GWASs have pinpointed significant SNPs and risk variants associated with ARHL, the detailed mechanisms, encompassing both genetic and epigenetic modifications, remain to be fully elucidated. This review presents the latest advances in association studies, integrating findings from both human studies and model organisms. By juxtaposing historical perspectives with contemporary genomics, we aim to catalyze innovative research and foster the development of novel therapeutic strategies for ARHL.

KnockoffHybrid: A knockoff framework for hybrid analysis of trio and population designs in genome-wide association studies.

Both trio and population designs are popular study designs for identifying risk genetic variants in genome-wide association studies (GWASs). The trio design, as a family-based design, is robust to confounding due to population structure, whereas the population design is often more powerful due to larger sample sizes. Here, we propose KnockoffHybrid, a knockoff-based statistical method for hybrid analysis of both the trio and population designs. KnockoffHybrid provides a unified framework that brings together the advantages of both designs and produces powerful hybrid analysis while controlling the false discovery rate (FDR) in the presence of linkage disequilibrium and population structure. Furthermore, KnockoffHybrid has the flexibility to leverage different types of summary statistics for hybrid analyses, including expression quantitative trait loci (eQTL) and GWAS summary statistics. We demonstrate in simulations that KnockoffHybrid offers power gains over non-hybrid methods for the trio and population designs with the same number of cases while controlling the FDR with complex correlation among variants and population structure among subjects. In hybrid analyses of three trio cohorts for autism spectrum disorders (ASDs) from the Autism Speaks MSSNG, Autism Sequencing Consortium, and Autism Genome Project with GWAS summary statistics from the iPSYCH project and eQTL summary statistics from the MetaBrain project, KnockoffHybrid outperforms conventional methods by replicating several known risk genes for ASDs and identifying additional associations with variants in other genes, including the PRAME family genes involved in axon guidance and which may act as common targets for human speech/language evolution and related disorders.

Evolution of the regulation of developmental gene expression in blind Mexican cavefish.

Developmental evolution and diversification of morphology can arise through changes in the regulation of gene expression or protein-coding sequence. To unravel mechanisms underlying early developmental evolution in cavefish of the species Astyanax mexicanus, we compared transcriptomes of surface-dwelling and blind cave-adapted morphs at the end of gastrulation. Twenty percent of the transcriptome was differentially expressed. Allelic expression ratios in cave X surface hybrids showed that cis-regulatory changes are the quasi-exclusive contributors to inter-morph variations in gene expression. Among a list of 108 genes with change at the cis-regulatory level, we explored the control of expression of rx3, which is a master eye gene. We discovered that cellular rx3 levels are cis-regulated in a cell-autonomous manner, whereas rx3 domain size depends on non-autonomous Wnt and Bmp signalling. These results highlight how uncoupled mechanisms and regulatory modules control developmental gene expression and shape morphological changes. Finally, a transcriptome-wide search for fixed coding mutations and differential exon use suggested that variations in coding sequence have a minor contribution. Thus, during early embryogenesis, changes in gene expression regulation are the main drivers of cavefish developmental evolution.

Mapping seasonal migration in a songbird hybrid zone -- heritability, genetic correlations, and genomic patterns linked to speciation.

Seasonal migration is a widespread behavior relevant for adaptation and speciation, yet knowledge of its genetic basis is limited. We leveraged advances in tracking and sequencing technologies to bridge this gap in a well-characterized hybrid zone between songbirds that differ in migratory behavior. Migration requires the coordinated action of many traits, including orientation, timing, and wing morphology. We used genetic mapping to show these traits are highly heritable and genetically correlated, explaining how migration has evolved so rapidly in the past and suggesting future responses to climate change may be possible. Many of these traits mapped to the same genomic regions and small structural variants indicating the same, or tightly linked, genes underlie them. Analyses integrating transcriptomic data indicate cholinergic receptors could control multiple traits. Furthermore, analyses integrating genomic differentiation further suggested genes underlying migratory traits help maintain reproductive isolation in this hybrid zone.

A predisposed motor bias shapes individuality in vocal learning.

The development of individuality during learned behavior is a common trait observed across animal species; however, the underlying biological mechanisms remain understood. Similar to human speech, songbirds develop individually unique songs with species-specific traits through vocal learning. In this study, we investigate the developmental and molecular mechanisms underlying individuality in vocal learning by utilizing F1 hybrid songbirds (Taeniopygia guttata cross with Taeniopygia bichenovii), taking an integrating approach combining experimentally controlled systematic song tutoring, unbiased discriminant analysis of song features, and single-cell transcriptomics. When tutoring with songs from both parental species, F1 hybrid individuals exhibit evident diversity in their acquired songs. Approximately 30% of F1 hybrids selectively learn either song of the two parental species, while others develop merged songs that combine traits from both species. Vocal acoustic biases during vocal babbling initially appear as individual differences in songs among F1 juveniles and are maintained through the sensitive period of song vocal learning. These vocal acoustic biases emerge independently of the initial auditory experience of hearing the biological father's and passive tutored songs. We identify individual differences in transcriptional signatures in a subset of cell types, including the glutamatergic neurons projecting from the cortical vocal output nucleus to the hypoglossal nuclei, which are associated with variations of vocal acoustic features. These findings suggest that a genetically predisposed vocal motor bias serves as the initial origin of individual variation in vocal learning, influencing learning constraints and preferences.

The role of mitochondria in sex- and age-specific gene expression in a species without sex chromosomes.

Mitochondria perform an array of functions, many of which involve interactions with gene products encoded by the nucleus. These mitochondrial functions, particularly those involving energy production, can be expected to differ between sexes and across ages. Here, we measured mitochondrial effects on sex- and age-specific gene expression in parental and reciprocal F1 hybrids between allopatric populations of Tigriopus californicus with over 20% mitochondrial DNA divergence. Because the species lacks sex chromosomes, sex-biased mitochondrial effects are not confounded by the effects of sex chromosomes. Results revealed pervasive sex differences in mitochondrial effects, including effects on energetics and aging involving nuclear interactions throughout the genome. Using single-individual RNA sequencing, sex differences were found to explain more than 80% of the variance in gene expression. Males had higher expression of mitochondrial genes and mitochondrially targeted proteins (MTPs) involved in oxidative phosphorylation (OXPHOS), while females had elevated expression of non-OXPHOS MTPs, indicating strongly sex-dimorphic energy metabolism at the whole organism level. Comparison of reciprocal F1 hybrids allowed insights into the nature of mito-nuclear interactions, showing both mitochondrial effects on nuclear expression, and nuclear effects on mitochondrial expression. While based on a small set of crosses, sex-specific increases in mitochondrial expression with age were associated with longer life. Network analyses identified nuclear components of strong mito-nuclear interactions and found them to be sexually dimorphic. These results highlight the profound impact of mitochondria and mito-nuclear interactions on sex- and age-specific gene expression.

Regulation of the d-band center of metal-organic frameworks for energy-saving hydrogen generation coupled with selective glycerol oxidation.

The hybrid electrolyzer coupled glycerol oxidation (GOR) with hydrogen evolution reaction (HER) is fascinating to simultaneously generate H2 and high value-added chemicals with low energy input, yet facing a challenge. Herein, Cu-based metal-organic frameworks (Cu-MOFs) are reported as model catalysts for both HER and GOR through doping of atomically dispersed precious and nonprecious metals. Remarkably, the HER activity of Ru-doped Cu-MOF outperformed a Pt/C catalyst, with its Faradaic efficiency for formate formation at 90% at a low potential of 1.40 V. Furthermore, the hybrid electrolyzer only needed 1.36 V to achieve 10 mA cm-2, 340 mV lower than that for splitting pure water. Theoretical calculations demonstrated that electronic interactions between the host and guest (doped) metals shifted downward the d-band centers (εd) of MOFs. This consequently lowered water adsorption and dissociation energy barriers and optimized hydrogen adsorption energy, leading to significantly enhanced HER activities. Meanwhile, the downshift of εd centers reduced energy barriers for rate-limiting step and the formation energy of OH*, synergistically enhancing the activity of MOFs for GOR. These findings offered an effective means for simultaneous productions of hydrogen fuel and high value-added chemicals using one hybrid electrolyzer with low energy input.

A hybrid photocatalytic system enables direct glucose utilization for methanogenesis.

Integration of methanogenic archaea with photocatalysts presents a sustainable solution for solar-driven methanogenesis. However, maximizing CH4 conversion efficiency remains challenging due to the intrinsic energy conservation and strictly restricted substrates of methanogenic archaea. Here, we report a solar-driven biotic-abiotic hybrid (biohybrid) system by incorporating cadmium sulfide (CdS) nanoparticles with a rationally designed methanogenic archaeon Methanosarcina acetivorans C2A, in which the glucose synergist protein and glucose kinase, an energy-efficient route for glucose transport and phosphorylation from Zymomonas mobilis, were implemented to facilitate nonnative substrate glucose for methanogenesis. We demonstrate that the photo-excited electrons facilitate membrane-bound electron transport chain, thereby augmenting the Na+ and H+ ion gradients across membrane to enhance adenosine triphosphate (ATP) synthesis. Additionally, this biohybrid system promotes the metabolism of pyruvate to acetyl coenzyme A (AcCoA) and inhibits the flow of AcCoA to the tricarboxylic acid (TCA) cycle, resulting in a 1.26-fold augmentation in CH4 production from glucose-derived carbon. Our results provide a unique strategy for enhancing methanogenesis through rational biohybrid design and reprogramming, which gives a promising avenue for sustainably manufacturing value-added chemicals.

In-person learning during the pandemic: Student take-up and school-level effects of remote and hybrid instruction on student outcomes.

While studies have examined the effects of schools offering in-person learning during the pandemic, this study provides analysis of student enrollment decisions (remote versus in-person) in response to schools providing in-person learning opportunities. In Connecticut during the 2020-21 school year, we find that student take-up of in-person learning opportunities was low with students on average enrolled in-person for only half of the days offered, and take-up was even lower in schools with larger shares of disadvantaged students. The provision of in-person learning opportunities has been previously shown to mitigate pandemic learning losses. By exploiting data on actual enrollment, we show that the protective benefits of in-person learning are twice as large as previously estimated once we account for the low rates of student take-up. Finally, we provide evidence suggesting that a key mechanism behind the benefits of in-person learning is alleviating the burden faced by schools and teachers in delivering remote education. First, we show that the benefits to individual students of their in-person learning are substantially smaller than the overall benefits a student receives from their school average level of in-person enrollment. Second, we show that a combination of remote and in-person learning (hybrid) with a full-time on-line presence of students when at home was worse than hybrid learning with students never or only partially online. This second finding is consistent with qualitative evidence showing that teachers found hybrid learning especially challenging when having to manage both in-person and remote students for the entire class period.

Approaching the catalytic mechanism of protein lysine methyltransferases by biochemical and simulation techniques.

Protein lysine methyltransferases (PKMTs) transfer up to three methyl groups to the side chains of lysine residues in proteins and fulfill important regulatory functions by controlling protein stability, localization and protein/protein interactions. The methylation reactions are highly regulated, and aberrant methylation of proteins is associated with several types of diseases including neurologic disorders, cardiovascular diseases, and various types of cancer. This review describes novel insights into the catalytic machinery of various PKMTs achieved by the combined application of biochemical experiments and simulation approaches during the last years, focusing on clinically relevant and well-studied enzymes of this group like DOT1L, SMYD1-3, SET7/9, G9a/GLP, SETD2, SUV420H2, NSD1/2, different MLLs and EZH2. Biochemical experiments have unraveled many mechanistic features of PKMTs concerning their substrate and product specificity, processivity and the effects of somatic mutations observed in PKMTs in cancer cells. Structural data additionally provided information about the substrate recognition, enzyme-substrate complex formation, and allowed for simulations of the substrate peptide interaction and mechanism of PKMTs with atomistic resolution by molecular dynamics and hybrid quantum mechanics/molecular mechanics methods. These simulation technologies uncovered important mechanistic details of the PKMT reaction mechanism including the processes responsible for the deprotonation of the target lysine residue, essential conformational changes of the PKMT upon substrate binding, but also rationalized regulatory principles like PKMT autoinhibition. Further developments are discussed that could bring us closer to a mechanistic understanding of catalysis of this important class of enzymes in the near future. The results described here illustrate the power of the investigation of enzyme mechanisms by the combined application of biochemical experiments and simulation technologies.

xSiGra: explainable model for single-cell spatial data elucidation.

Recent advancements in spatial imaging technologies have revolutionized the acquisition of high-resolution multichannel images, gene expressions, and spatial locations at the single-cell level. Our study introduces xSiGra, an interpretable graph-based AI model, designed to elucidate interpretable features of identified spatial cell types, by harnessing multimodal features from spatial imaging technologies. By constructing a spatial cellular graph with immunohistology images and gene expression as node attributes, xSiGra employs hybrid graph transformer models to delineate spatial cell types. Additionally, xSiGra integrates a novel variant of gradient-weighted class activation mapping component to uncover interpretable features, including pivotal genes and cells for various cell types, thereby facilitating deeper biological insights from spatial data. Through rigorous benchmarking against existing methods, xSiGra demonstrates superior performance across diverse spatial imaging datasets. Application of xSiGra on a lung tumor slice unveils the importance score of cells, illustrating that cellular activity is not solely determined by itself but also impacted by neighboring cells. Moreover, leveraging the identified interpretable genes, xSiGra reveals endothelial cell subset interacting with tumor cells, indicating its heterogeneous underlying mechanisms within complex cellular interactions.

A hybrid demultiplexing strategy that improves performance and robustness of cell hashing.

Cell hashing, a nucleotide barcode-based method that allows users to pool multiple samples and demultiplex in downstream analysis, has gained widespread popularity in single-cell sequencing due to its compatibility, simplicity, and cost-effectiveness. Despite these advantages, the performance of this method remains unsatisfactory under certain circumstances, especially in experiments that have imbalanced sample sizes or use many hashtag antibodies. Here, we introduce a hybrid demultiplexing strategy that increases accuracy and cell recovery in multi-sample single-cell experiments. This approach correlates the results of cell hashing and genetic variant clustering, enabling precise and efficient cell identity determination without additional experimental costs or efforts. In addition, we developed HTOreader, a demultiplexing tool for cell hashing that improves the accuracy of cut-off calling by avoiding the dominance of negative signals in experiments with many hashtags or imbalanced sample sizes. When compared to existing methods using real-world datasets, this hybrid approach and HTOreader consistently generate reliable results with increased accuracy and cell recovery.

A comprehensive review and comparison of existing computational methods for protein function prediction.

Protein function prediction is critical for understanding the cellular physiological and biochemical processes, and it opens up new possibilities for advancements in fields such as disease research and drug discovery. During the past decades, with the exponential growth of protein sequence data, many computational methods for predicting protein function have been proposed. Therefore, a systematic review and comparison of these methods are necessary. In this study, we divide these methods into four different categories, including sequence-based methods, 3D structure-based methods, PPI network-based methods and hybrid information-based methods. Furthermore, their advantages and disadvantages are discussed, and then their performance is comprehensively evaluated and compared. Finally, we discuss the challenges and opportunities present in this field.

A structural basis of T cell cross-reactivity to native and spliced self-antigens presented by HLA-DQ8.

Type 1 diabetes (T1D) is a T cell-mediated autoimmune disease that has a strong HLA association, where a number of self-epitopes have been implicated in disease pathogenesis. Human pancreatic islet-infiltrating CD4+ T cell clones not only respond to proinsulin C-peptide (PI40-54; GQVELGGGPGAGSLQ) but also cross-react with a hybrid insulin peptide (HIP; PI40-47-IAPP74-80; GQVELGGG-NAVEVLK) presented by HLA-DQ8. How T cell receptors recognize self-peptide and cross-react to HIPs is unclear. We investigated the cross-reactivity of the CD4+ T cell clones reactive to native PI40-54 epitope and multiple HIPs fused at the same N-terminus (PI40-54) to the degradation products of two highly expressed pancreatic islet proteins, neuropeptide Y (NPY68-74) and amyloid polypeptide (IAPP23-29 and IAPP74-80). We observed that five out of the seven selected SKW3 T cell lines expressing TCRs isolated from CD4+ T cells of people with T1D responded to multiple HIPs. Despite shared TRAV26-1-TRBV5-1 gene usage in some T cells, these clones cross-reacted to varying degrees with the PI40-54 and HIP epitopes. Crystal structures of two TRAV26-1+-TRBV5-1+ T cell receptors (TCRs) in complex with PI40-54 and HIPs bound to HLA-DQ8 revealed that the two TCRs had distinct mechanisms responsible for their differential recognition of the PI40-54 and HIP epitopes. Alanine scanning mutagenesis of the PI40-54 and HIPs determined that the P2, P7, and P8 residues in these epitopes were key determinants of TCR specificity. Accordingly, we provide a molecular basis for cross-reactivity towards native insulin and HIP epitopes presented by HLA-DQ8.

Genome-wide chromatin accessibility reveals transcriptional regulation of heterosis in inter-subspecific hybrid rice.

The utilization of rice heterosis is essential for ensuring global food security; however, its molecular mechanism remains unclear. In this study, comprehensive analyses of accessible chromatin regions (ACRs), DNA methylation, and gene expression in inter-subspecific hybrid and its parents were performed to determine the potential role of chromatin accessibility in rice heterosis. The hybrid exhibited abundant ACRs, in which the gene ACRs and proximal ACRs were directly related to transcriptional activation rather than the distal ACRs. Regarding the dynamic accessibility contribution of the parents, paternal ZHF1015 transmitted a greater number of ACRs to the hybrid. Accessible genotype-specific target genes were enriched with overrepresented transcription factors, indicating a unique regulatory network of genes in the hybrid. Compared with its parents, the differentially accessible chromatin regions with upregulated chromatin accessibility were much greater than those with downregulated chromatin accessibility, reflecting a stronger regulation in the hybrid. Furthermore, DNA methylation levels were negatively correlated with ACR intensity, and genes were strongly affected by CHH methylation in the hybrid. Chromatin accessibility positively regulated the overall expression level of each genotype. ACR-related genes with maternal Z04A-bias allele-specific expression tended to be enriched during carotenoid biosynthesis, whereas paternal ZHF1015-bias genes were more active in carbohydrate metabolism. Our findings provide a new perspective on the mechanism of heterosis based on chromatin accessibility in inter-subspecific hybrid rice.

The OsMYC2-JA feedback loop regulates diurnal flower-opening time via cell wall loosening in rice.

Diurnal flower-opening time (DFOT), the time of spikelet opening during the day, is an important trait for hybrid rice (Oryza sativa L.) seed production. Hybrids between indica and japonica rice varieties have strong heterosis, but the parental lines usually have different, nonoverlapping DFOTs. This reduces the success of hybrid seed production in crosses between indica and japonica subspecies, thus hindering the utilization of indica and japonica inter-subspecies heterosis. However, little is known about the molecular mechanisms regulating DFOT in rice. Here, we obtained japonica rice lines with a DFOT 1.5 h earlier than the wild type by overexpressing OsMYC2, a gene encoding a key transcription factor in the jasmonate (JA) signaling pathway. OsMYC2 is activated by JA signaling and directly regulates the transcription of genes related to JA biosynthesis and cell wall metabolism. Overexpressing OsMYC2 led to significantly increased JA contents and decreased cellulose and hemicellulose contents in lodicule cells, as well as the softening of lodicule cell walls. This may facilitate the swelling of lodicules, resulting in early diurnal flower-opening. These results suggest that the OsMYC2-JA feedback loop regulates DFOT in rice via cell wall remodeling. These findings shed light on the understanding of regulatory mechanism of the DFOT of plants, which should promote the development of indica and japonica varieties suitable for hybrid rice breeding.