The unicellular red alga Cyanidioschyzon merolae is a valuable model organism for studying pre-mRNA splicing, stress adaptation, and biotechnological applications. However, the limited availability of selectable markers has constrained its potential in genetic engineering. In this study, we evaluated the sul1 gene, which encodes a sulfadiazine-resistant variant of dihydropteroate synthase, as a new selectable marker (SUL) for C. merolae transformation. SUL has previously been used for this purpose in plants and green algae. We analyzed the sensitivity of C. merolae to sulfadiazine and determined the concentration that effectively inhibited cell growth. To test the effectiveness of SUL as a selectable marker, we designed a transformation construct containing SUL directed to the algal mitochondria through a native targeting peptide, along with mVenus to visualize transformation. We integrated the construct into a neutral genomic locus via homologous recombination. Fluorescence microscopy confirmed stable mVenus expression, and sulfadiazine selection successfully enriched transformed cells. As a demonstration of the utility of this marker, we rescued the large-cell phenotype of a cell division cycle-like kinase 2 (CmClk2) mutant by replacing the CAT-marked kinase domain deletion with the SUL-marked native kinase domain, thereby restoring CmClk2 function and recycling the CAT marker. The deletion phenotype provides evidence for a conserved cell-cycle regulatory role for CmClk2 in C. merolae. Beyond establishing SUL as an effective selectable marker, this highlights how SUL facilitates functional genetic studies of essential cellular regulators.

From molecules to field: Integrated insights into cuticle-mediated drought tolerance in plants.

TIAM2 and ADCY7 polymorphisms and their association with feed efficiency in Huaibei partridge chickens.

Piaractus brachypomus (red-bellied pacu), native to the Amazon River Basin, is widely known for its rapid growth, disease resistance, and cost-effective feeding, which have led to its widespread introduction and high commercial value worldwide. Despite this, the lack of a reference genome has hindered both genetic and evolutionary studies, as well as the genetic improvement of aquaculture traits. Here, to address this gap, we report the first chromosome-level genome assembly of P. brachypomus using PacBio HiFi long-reads and Hi-C sequencing technologies. The final genome assembly has a total size of 1.34 Gb and exhibits high continuity, with contig N50 of 40.61 Mb. Approximately 99.35% of assembled sequences were anchored into 27 chromosomes, with a BUSCO completeness score of 99.8%. Genome annotation identified 44.83% of repetitive elements and predicted 25,501 protein-coding genes with 99.2% receiving functional annotations. Overall, these findings offer a framework for evolutionary studies and genetic improvement, facilitating marker-assisted and genome-wide selection for the sustainable enhancement of P. brachypomus aquaculture stocks.

Muttony flavor is a species-specific characteristic of ovine meat and a critical determinant of consumer acceptance and market demand worldwide. The characteristic flavor primarily originates from two key classes of compounds: Branched-chain fatty acids (BCFAs), particularly 4-methyloctanoic acid (4-MOA), 4-ethyloctanoic acid (4-EOA), and 4-methylnonanoic acid (4-MNA); and skatole (3-methylindole), a ruminal microbial metabolite of tryptophan. Genetic analysis based on candidate genes is considered an effective approach to elucidate the physiological mechanisms regulating the expression of complex traits. This review systematically examines the biosynthetic pathways of these compounds, clarifying the roles of ruminal microorganisms, host genetic factors, and key regulatory genes including FASN, CYP2E1, CYP2A6, and MMUT, thereby providing genetic strategies and methods for the regulation of muttony flavor, while also supplementing nongenetic approaches for flavor control. The integration of these strategies indicates that the identification of candidate genes and the elucidation of their expression regulatory networks provide a theoretical basis for future marker-assisted selection programs, thereby potentially enhancing the precision and sustainability of ovine industry breeding strategies, while nongenetic regulation can further assist in fine-tuning flavor control. As a validation, this review also provides a systematic overview of analytical methods for muttony flavor evaluation, tracing the evolutionary trajectory from traditional sensory evaluation through instrumental analysis to intelligent sensory technologies, and clarifying the applicable scenarios and complementary relationships among various techniques. By integrating the current understanding of formation mechanisms, regulatory networks, and evaluation technologies, this review establishes a theoretical framework for developing market-oriented flavor control strategies.

CRISPR-based tools have quickly moved from specialist techniques to routine instruments in biology and medicine, and they are now central to large-scale loss-of-function and perturbation screens. In this review, we focus on how pooled CRISPR screens are used to interrogate gene function in living cells, most often through cell fitness or simple selectable markers, and contrast this with arrayed formats that trade throughput for richer molecular readouts, such as transcriptome-wide changes. We bring together current strategies for library design, delivery, and selection and show how different Cas nucleases, including Cas9, Cas12, and Cas13, broaden the range of genome and transcriptome perturbations that can be assayed. We then discuss recent applications in drug response, viral infection, and cancer biology and consider how improvements in high-content technologies, data analysis, and emerging diagnostic uses are likely to shape the next generation of CRISPR-based screening studies.

Histological analysis traditionally relies on thin tissue sections, providing inherently two-dimensional (2D) information. However, this approach captures only a fraction of the entire sample and lacks the spatial context necessary for comprehensive tissue assessment. Recent advancements in multimodal imaging have introduced the fusion of histological data with three-dimensional (3D) imaging techniques, such as Light Sheet Fluorescence Microscopy (LSFM), to enhance tissue analysis by integrating complementary spatial information. A key challenge in this fusion process is the accurate alignment of corresponding structures across modalities, which is complicated by differences in resolution, sectioning-induced deformations, and varying imaging orientations. This is further complicating in the case of 2D-to-3D registration where the initial alignment of the image inside the volume is unknown and registration processes are computationally expensive due to six degrees of freedom in the placement. Here, existing solutions often require manual selection of image pairs, fiducial markers or technical expertise, limiting accessibility to non-specialist users. To address these limitations, we introduce LitSHi (Light Sheet meets Histology), a novel registration tool that enables the automated and precise alignment of LSFM and histological images. LitSHi allows multimodal image fusion to be performed fully automatically, which significantly reduces the need for manual intervention. Using testicular tumor and pancreatic specimens, we evaluated LitSHi and demonstrated its ability to enhance structural correspondence between LSFM and histological images. The automated registration process markedly improved both efficiency and alignment accuracy compared with conventional manual or semi-automated approaches. Overall, LitSHi holds significant potential to advance digital pathology by enabling optimized multimodal tissue analysis and supporting future developments in computational pathology and AI-driven diagnostics.

Sesame (Sesamum indicum L.) is a major oilseed crop with numerous oil and nutritional benefits. However, the genetic basis of complex agronomic traits remains fragmented across individual quantitative trait loci (QTL) studies. Meta-QTL (MQTL) analysis provides a robust framework for identifying stable genomic regions that control quantitatively inherited traits in diverse environments and genetic backgrounds. Here, we present the first comprehensive MQTL analysis of sesame, targeting morphological and yield components, oil content and quality, and seed and capsule traits. All published QTLs were compiled using LOD scores, phenotypic variance explained (PVE), and confidence intervals (CI), and projected onto a high-density consensus map comprising 38,972 markers using BioMercator v4.2. In total, 321 QTLs (54.9%) were effectively projected and summarized into 92 MQTLs. The average CI of MQTLs was 4.01cM, indicating a 2.41-fold (58.57%) reduction compared with the initial QTLs (9.68cM). Nineteen high-confidence MQTLs (CI ≤ 5cM and ≥ 4 initial QTLs) were selected for candidate gene mining, which collectively encompassed 1,678 unique gene models. Using orthology-based prioritization, we identified 160 orthologous candidates, and functional annotation revealed 43 genes that were strongly associated with key traits within the MQTL regions. Several MQTLs co-localize with marker-trait associations reported in previous genome-wide association studies, thereby reinforcing their significance in the regulation of traits. These findings indicate that MQTL analysis substantially improves the mapping precision and provides reliable genomic targets for sesame breeding. Integrating tightly linked markers from these MQTLs into marker-assisted and genomic selection schemes offers a powerful strategy to accelerate the genetic improvement of sesame in terms of yield, plant architecture, seed, and oil quality.

The unambiguous identification of protein O-GlcNAcylation remains challenging because O-GlcNAc and O-GalNAc are isobaric and produce nearly indistinguishable fragmentation patterns under standard higher-energy collisional dissociation (HCD) conditions. Here, we report a chemoenzymatic strategy that enables selective detection of O-GlcNAc through enzymatic deacetylation. We show that the Cyclobacterium marinum deacetylase CmCBDA uniquely and efficiently converts beta-O-GlcNAc, but not alpha-O-GlcNAc, alpha-O-GalNAc, or N-glycans, into the corresponding beta-O-GlcN glycoform. This transformation introduces a non-native primary amine that fundamentally alters glycopeptide ionization and fragmentation behavior, generating characteristic diagnostic ions under HCD-MS/MS. The resulting O-GlcN modification serves as a selective chemical marker for beta-O-GlcNAc, enabling confident site localization using widely available mass spectrometers. Application of this workflow to O-GlcNAcylated model proteins and complex cell lysates demonstrates robust discrimination of O-GlcNAc sites without enrichment or specialized fragmentation methods. This deacetylation-assisted approach provides a general and practical solution to a long-standing analytical challenge in O-GlcNAc proteomics.

Sorghum (Sorghum bicolor L. Moench) is a drought-tolerant crop, with its resilience essentially attributed to high transpiration efficiency (TE), and simply defined as the biomass produced per unit of water transpired. Understanding the genetic architecture of TE is crucial for breeding water-efficient varieties. This study undertook a genome-wide association study (GWAS) using SNP marker on 112 sorghum genotypes to identify genomic regions controlling TE and related physiological traits at the flag leaf stage using 17,637 imputed SNP markers. Phenotypic evaluation revealed significant variation for key traits like root dry wight (RDW), shoot dry weight (SDW), plant dry weight (PDW), water used efficiency (WUE), Root plant ratio (RTR), chlorophyll a concentration (Chla), Transpiration rate (TR) and TE, with moderate to high heritability. Using a multi-locus GWAS approach, we identified 23 robust quantitative trait nucleotides (QTNs) associated with eight traits except WUE. Notably, we discovered pleiotropic genomic hotspots on chromosomes 2, 3, 6, and 9 that simultaneously influence biomass (PDW, SDW) and TE. A meta-analysis showed that 86.9% of these QTNs co-located with previously reported QTLs, validating these regions, while three QTNs were novel. Candidate gene analysis within the QTN regions pinpointed 218 genes with different functions such as hormone signaling (auxin, cytokinin), stomatal regulation (S-type anion channel), root development (glutamate synthase), and photosynthesis (chlorophyll biosynthesis). Six QTNs also found intergenic, between start/end regions of the genes. Our findings provide valuable molecular tools for marker-assisted selection and highlight key candidate genes for enhancing transpiration efficiency and drought adaptation in sorghum.

This study aimed to evaluate the prognostic value of late-stage vacuolization in Day 4 embryos relative to compaction status. We retrospectively analyzed 9,779 embryos from 2,409 patients undergoing fresh D4 transfers between 2018 and 2024. Embryos were stratified by compaction status (full, part, non-compaction) and assessed for vacuolization. Predictive performance for blastocyst formation was evaluated using ROC curves and logistic regression. The results showed that late-stage vacuolization correlated with higher maternal and paternal age, increased gonadotropin (Gn) dosage, and lower Anti-Müllerian Hormone (AMH)/estradiol (P<0.001), but comparable oocyte yield and intracytoplasmic sperm injection (ICSI) rates (P>0.05). False-compaction subgroup​ (77.6% of vacuolized embryos) showed reduced transferable blastocyst (38.7% vs. 53.3%, P=0.021), high-quality blastocyst (9.8% vs. 23.4%, P=0.001), and day 5 blastocyst rates (20.6% vs. 35.1%, P=0.007). A significant interaction was observed between late-stage vacuolization and compaction status affecting both transferable and high-quality blastocyst formation (P for interaction<0.001). Specifically, late-stage vacuolization significantly increased the rates of transferable (OR = 3.34, 95% CI = 2.54-4.39, P<0.001) and high-quality blastocyst formation (OR=2.51, 95% CI=1.60-3.96, P<0.001) in the non-compacted subgroup. Conversely, it decreased the high-quality blastocyst formation rate in the fully compacted subgroup (OR=0.37, 95% CI=0.15-0.89, P=0.026), while showing no significant effect on transferable blastocyst formation in this group (OR=0.83, 95% CI=0.28-2.48, P=0.740). In conclusion, late-stage vacuolization is a compaction-dependent prognostic marker, detrimental in compacted embryos yet potentially beneficial in non-compacted ones. We hypothesize that its effects may be mediated through mechanical stress-induced pseudo-compaction, suggesting that it should be integrated into D4 embryo grading systems in a context-specific manner. This study looked at over 9,700 embryos used in IVF. We found that tiny, bubble-like structures (called "vacuolization") inside a 4-day-old embryo can be either good or bad news, depending on whether the embryo's cells are tightly or loosely packed together. In tightly packed embryos, these bubbles are harmful and reduce the chance of forming a high-quality embryo. In loosely packed embryos, the same bubbles can be helpful and increase the chance of successful development. This is different from other embryo problems, which are always bad. By checking for these bubbles and how packed the cells are, we can predict which embryo is most likely to lead to a baby 10% more accurately than before. To use this new method, embryos need to be grown for 4 days instead of 3.

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a globally devastating wheat disease. The identification of novel loci for durable resistance is crucial for sustainable control of the disease. Chinese wheat landrace Xuxumai (XXM) has exhibited consistent high-level adult-plant resistance to stripe rust in China. To elucidate the genetic basis of its resistance, a recombinant inbred line (RIL) population was developed from a cross between XXM and susceptible cultivar Taichung 29. Disease severity (DS) of the parents and 149 RILs was evaluated across multiple field seasons. High-density SNP genotyping facilitated the construction of a genetic linkage map, which was used for quantitative trait locus (QTL) mapping. Three stable QTL, designated QYr.XXM-1AL, QYr.TC29-1BL, and QYr.TC29-2BS, were identified on chromosomes 1A, 1B, and 2B, respectively. Collectively, they explained up to 20.86% of the phenotypic variance. Comparative analysis indicated that QYr.XXM-1AL and QYr.TC29-1BL are likely novel loci, while QYr.TC29-2BS coincides with a known gene-rich region. RILs possessing all three QTL showed significantly lower DS (mean reduction of 50%) compared to those with 0 to 2 QTL. Furthermore, Kompetitive allele-specific PCR (KASP) markers closely linked to QYr.XXM-1A were developed and validated. This study reveals novel genetic resources for stripe rust resistance in XXM. The major QTL QYr.XXM-1A and its associated KASP markers hold substantial promise for enhancing the efficiency of marker-assisted selection in wheat breeding programs.

Chalkiness is a critical trait that negatively affects rice grain appearance, milling quality, cooking properties, and consumer acceptance, and its incidence is increasing under climate change as elevated temperatures during grain filling become more frequent. As a complex quantitative trait shaped by strong genotype × environment interactions, heat-induced chalkiness arises from coordinated disruption of endosperm development, storage-substance metabolism, and stress-response pathways. This review synthesizes current understanding of the molecular, physiological, and genetic mechanisms underlying heat-induced chalkiness in rice. We distinguish constitutive regulators that govern grain development under all conditions from heat-responsive genes and pathways specifically activated under thermal stress, thereby providing a conceptual framework for temperature-dependent grain quality deterioration. We examine temperature-sensitive developmental windows, source-sink coordination, and heat-mediated disruption of starch, storage-protein, and lipid metabolism, with emphasis on the critical grain-filling stage during which elevated temperatures irreversibly impair endosperm structure. We integrate recent advances in heat sensing and signalling, including phytohormone, calcium, reactive oxygen species, endoplasmic reticulum stress, and membrane-lipid remodelling pathways and show how these signals converge through multilayered regulatory networks involving epigenetic, transcriptional, post-transcriptional, and protein-quality control. Finally, we discuss varietal variation in heat tolerance, the nutritional and post-harvest implications of chalkiness including its valorization across brewing, food-processing, and bio-economy markets, and emerging mitigation strategies spanning marker-assisted selection, genome editing, genomic selection, and optimized agronomic management. By integrating mechanistic insights with translational applications, this review provides a systems-level framework for developing climate-resilient rice varieties capable of maintaining grain quality in a warming climate.

Proteases are promiscuous enzymes acting on multiple substrates. Inhibiting pathogenic proteolysis while sparing physiological ones is essential for the development of effective and safe inhibitors. By engineering β-lactamase and levansucrase as selection and counterselection markers in E. coli periplasm, this study established functional positive and negative selections for the facile discovery of protease inhibitory mAbs rendering substrate specificity. Isolated anti-matrix metalloproteinase (MMP)-14 inhibitory mAbs exhibited nanomolar binding affinities and inhibitory potencies, exclusive selectivity, high proteolysis stability, and substrate-specific (SS) inhibition, that is, blocking MMP-14 mediated proteolysis of pro-tumorigenic syndecan-1 (Sdc-1) while allowing cleavage of anti-inflammatory macrophage chemoattractant protein 3 (MCP-3). Mechanistic studies suggested that the isolated Fabs were active-site competitive inhibitors and their substrate specificity was achieved by recognizing the protease's prime subsites shared with Sdc-1 but distinct to that of MCP-3. Given the pharmaceutical significance of SS inhibition, we envision the dual functional selection can be widely applicable to important protease targets.

This study describes a genome-editing-based approach for transcriptional silencing of geranylgeranyl pyrophosphate synthase (GGPPS) expression in Chlamydomonas reinhardtii to investigate cellular farnesyl pyrophosphate (FPP) availability and to redirect isoprenoid precursors toward sesquiterpene biosynthesis. Using Cas9-mediated integration of a selection marker into the GGPPS promoter region, the assembly of the transcriptional complex was successfully disturbed. Two independent editing events resulted in stable knockdown mutants with position-dependent reductions in GGPPS expression, and the stronger knockdown caused decreases in total chlorophyll and carotenoid contents and increased isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP) precursor pools in the chloroplast without impairing cell viability. Overexpression of various sesquiterpene synthases was used to assess the impact on heterologous terpenoid bioproduction, and specific bisabolene and patchoulol production were increased by more than 2-fold. Expression of the C. nootkatensis valencene synthase in combination with a heterologous farnesyl pyrophosphate synthase resulted in a 10.9-fold increase in specific valencene production. These results demonstrate that transcriptional interference via targeted DNA integration enables robust, position-dependent tuning of essential gene expression.

Stripe rust, caused by Puccinia striiformis f. sp. tritici, can cause severe yield losses in wheat (Triticum aestivum L.) during epidemics. Breeding resistant wheat varieties remains the most cost-effective approach to manage this disease; and the identification of new resistance loci is essential for maintaining genetic diversity. The CIMMYT-derived wheat line 'Kijil' was highly resistant to stripe rust in both Mexican and Chinese environments. A population of 153 F₅ recombinant inbred lines (RILs) was derived from a cross between Kijil and the susceptible parent 'Apav#1'. The population was phenotyped for stripe rust resistance across seven environments in two countries and genotyped using a genotyping-by-sequencing (GBS) platform. Inclusive composite interval mapping (ICIM) was used to construct a genetic map and identify significant resistance quantitative trait loci (QTLs) using 5,468 polymorphic markers. Mapping revealed the known resistance loci Yr29, Yr30 and QYr.hzau-3AS, along with two novel loci, QYr.hzau-2BS and QYr.hzau-5DL, across both Chinese and Mexican rust environments. Among these, QYr.hzau-2BS accounted for 11.75% to 19.19% of the phenotypic variance. A corresponding KASP marker, KASP_2BS, was developed to facilitate marker-assisted selection. Based on the mapping interval, two candidate genes underlying this locus were predicted. Further analysis revealed that Yr29 showed significant additive effects with other stripe rust resistance genes/loci, and the combination of Yr29, Yr30, and QYr.hzau-2BS reduced disease severity by up to 67.8%. Our findings suggest that Kijil and RILs carrying Yr29, Yr30, and QYr.hzau-2BS can serve as valuable donors for breeding wheat varieties with improved stripe rust resistance.

Transcriptomic insights into temperature regulation of proliferation and differentiation in skeletal muscle cells of Nibea albiflora.

The proteomics and phosphoproteomics landscape of melanoma under T cell attack.

Elucidating the genetic architecture of body weight (BW), body conformation, and coat color (CC) is vital for the precision breeding of Gamba sheep, a unique high-altitude indigenous breed. While previous studies focused primarily on general plateau adaptation, the specific genetic drivers regulating economic traits in this extreme-altitude population remain poorly understood. In this study, we characterized six key phenotypic traits and conducted genome-wide association studies (GWAS) leveraging whole-genome resequencing data from 296 individuals. To ensure the robustness of our findings, we systematically evaluated five statistical models (GLM, MLM, CMLM, MLMM, and the SUPER model) across different trait categories. The SUPER model was ultimately selected for growth-related traits due to its superior power in balancing signal sensitivity and false-positive control, whereas the MLMM model demonstrated the optimal fitting performance for the binary coat color phenotype, with both models consistently yielding genomic inflation factors ( λ ) close to the theoretical expectation ( 1.0). Phenotypic investigation revealed distinct sexual dimorphism in growth determinants: cannon bone circumference was the primary driver of body weight in rams, whereas body height and heart girth dominated in ewes. The GWAS identified 82 genome-wide significant SNPs, leading to the mapping of a prominent novel genomic region on chromosome 5 associated with body height. Functional annotation highlighted PRKCE and SGIP1 as plausible positional candidate genes for growth characteristics, while SPIRE2 was pinpointed as a primary genomic driver regulating coat color variation. These findings provide novel insights into the genetic blueprint governing growth and pigmentation in this unique livestock, offering precise molecular targets for future marker-assisted selection.

ABSTRACT Dogs are a critical non‐rodent species used in preclinical safety studies, particularly, in the pharmaceutical field, due to their physiological, metabolic, and immunological similarities to humans. As such, immunophenotyping of canine peripheral blood mononuclear cells (PBMCs) plays a crucial role in translational research, immune monitoring, and safety evaluations in drug development. However, the limited availability of canine‐specific antibodies restricts detailed and accurate immune profiling, which is essential for advancing safety evaluations in drug development. To address this challenge, we developed a 15‐marker panel for comprehensive mass cytometry‐based immunophenotyping of cryopreserved canine PBMCs. This panel encompasses major leukocyte subsets, including B cells, CD4+ T helper cells, regulatory T cells, CD8+ cytotoxic T cells, memory T cell subsets, natural killer T cells, natural killer cells, dendritic cells, CD4+ monocytes, classical monocytes, and neutrophils. We utilized both extracellular and intracellular markers to facilitate in‐depth immune profiling, despite the limited availability of canine‐specific antibodies. The panel was thoroughly optimized in terms of marker selection, antibody clone validation, and metal isotope pairing. Additionally, by the use of mass cytometry, several channels remain unoccupied, providing flexibility for future panel expansion.