Germination Assays for Comparable Seed Dormancy Depth and Distinction of Seed Color by Multiplex PCR in Wheat.

Seed dormancy is an important trait in cereal breeding, as it prevents preharvest sprouting (PHS). Although seed dormancy is a multifactorial trait, seed color has been demonstrated to be a major dormancy-related factor controlled by few genes. The R-1 gene is a seed color regulator that encodes a MYB-type transcription factor in wheat. A set of genetic markers designed against R-1 can provide a powerful tool for swift wheat breeding. Depth of seed dormancy varies not only among lines but also during seed development in each line. In this chapter, we describe how developmental seeds can be collected to perform germination tests, how seed color can be observed after NaOH staining, and how to genotype wheat R-1 genes using multiplex PCR.

Classification accuracy of machine learning algorithms for Chinese local cattle breeds using genomic markers.

Accurate breed classification is required for the conservation and utilization of farm animal genetic resources. Traditional classification methods mainly rely on phenotypic characterization. However, it is difficult to distinguish between the highly similar breeds due to the challenges in qualifying the phenotypic character. Machine learning algorithms show unique advantages in breed classification using genomic information. To evaluate the classification methods for Chinese cattle breeds, this study utilized genomic SNP data from 213 individuals across seven Chinese local breeds and compared the classification accuracies of three feature selection methods (FST value sorting and screening, mRMR, and Relief-F) and three machine learning algorithms (Random Forest, Support Vector Machine, and Naive Bayes). Results showed that: 1) using the FST method to screen more than 1500 SNPs, or using the mRMR algorithm to screen more than 1000 SNPs, the SVM classification algorithm can achieve more than 99.47% classification accuracy; 2) the most effective algorithm was SVM, followed by NB, while the best SNP selection method was FST and mRMR, followed by Relief-F; 3) species misclassification often occurs between breeds with high similarity. This study demonstrates that machine learning classification models combined with genomic data are effective methods for the classification of local cattle breeds, providing a technical basis for the rapid and accurate classification of cattle breeds in China.

Directly selecting cell-type marker genes for single-cell clustering analyses.

In single-cell RNA sequencing (scRNA-seq) studies, cell types and their marker genes are often identified by clustering and differentially expressed gene (DEG) analysis. A common practice is to select genes using surrogate criteria such as variance and deviance, then cluster them using selected genes and detect markers by DEG analysis assuming known cell types. The surrogate criteria can miss important genes or select unimportant genes, while DEG analysis has the selection-bias problem. We present Festem, a statistical method for the direct selection of cell-type markers for downstream clustering. Festem distinguishes marker genes with heterogeneous distribution across cells that are cluster informative. Simulation and scRNA-seq applications demonstrate that Festem can sensitively select markers with high precision and enables the identification of cell types often missed by other methods. In a large intrahepatic cholangiocarcinoma dataset, we identify diverse CD8+ T cell types and potential prognostic marker genes.

Development of a marker recyclable CRISPR/Cas9 system for scarless and multigene editing in Fusarium fujikuroi.

Iterative metabolic engineering of Fusarium fujikuroi has traditionally been hampered by its low homologous recombination efficiency and scarcity of genetic markers. Thus, the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated proteins (Cas9) system has emerged as a promising tool for precise genome editing in this organism. Some integrated CRISPR/Cas9 strategies have been used to engineer F. fujikuroi to improve GA3 production capabilities, but low editing efficiency and possible genomic instability became the major obstacle. Herein, we developed a marker recyclable CRISPR/Cas9 system for scarless and multigene editing in F. fujikuroi. This system, based on an autonomously replicating sequence, demonstrated the capability of a single plasmid harboring all editing components to achieve 100%, 75%, and 37.5% editing efficiency for single, double, and triple gene targets, respectively. Remarkably, even with a reduction in homologous arms to 50 bp, we achieved a 12.5% gene editing efficiency. By employing this system, we successfully achieved multicopy integration of the truncated 3-hydroxy-3-methyl glutaryl coenzyme A reductase gene (tHMGR), leading to enhanced GA3 production. A key advantage of our plasmid-based gene editing approach was the ability to recycle selective markers through a simplified protoplast preparation and recovery process, which eliminated the need for additional genetic markers. These findings demonstrated that the single-plasmid CRISPR/Cas9 system enables rapid and precise multiple gene deletions/integrations, laying a solid foundation for future metabolic engineering efforts aimed at industrial GA3 production.

Implications of accounting for marker-based population structure in the quantitative genetic evaluation of genetic parameters related to growth and wood properties in Norway spruce.

BACKGROUND: Forest geneticists typically use provenances to account for population differences in their improvement schemes; however, the historical records of the imported materials might not be very precise or well-aligned with the genetic clusters derived from advanced molecular techniques. The main objective of this study was to assess the impact of marker-based population structure on genetic parameter estimates related to growth and wood properties and their trade-offs in Norway spruce, by either incorporating it as a fixed effect (model-A) or excluding it entirely from the analysis (model-B). RESULTS: Our results indicate that models incorporating population structure significantly reduce estimates of additive genetic variance, resulting in substantial reduction of narrow-sense heritability. However, these models considerably improve prediction accuracies. This was particularly significant for growth and solid-wood properties, which showed to have the highest population genetic differentiation (QST) among the studied traits. Additionally, although the pattern of correlations remained similar across the models, their magnitude was slightly lower for models that included population structure as a fixed effect. This suggests that selection, consistently performed within populations, might be less affected by unfavourable genetic correlations compared to mass selection conducted without pedigree restrictions. CONCLUSION: We conclude that the results of models properly accounting for population structure are more accurate and less biased compared to those neglecting this effect. This might have practical implications for breeders and forest managers where, decisions based on imprecise selections can pose a high risk to economic efficiency.

The role of hsa-miR-193a-5p as an important factor for control of inositol in alopecia areata.

BACKGROUND: MicroRNAs (miRNAs) are small RNA molecules that play a regulatory role in various biological processes by acting as intracellular mediators. They hold great potential as therapeutic agents for targeting human disease pathways; however, there is still much to be uncovered about their mechanism of gene regulation. Alopecia areata (AA) is a commonly occurring inflammatory condition characterized by the infiltration of T cells that specifically target the anagen-stage hair follicle. The limited understanding of its precise cellular mechanism may be the reason behind the scarcity of effective treatments for AA. AIM: The significance and function of hsa-miR-193a-5p as a genetic marker for AA and its potential influence on the advancement of the disease. SUBJECTS AND METHODS: A case-control study comprised 77 individuals diagnosed with AA who were matched with 75 healthy controls. In order to measure the expression of miR-200c-3p in both groups, the real-time PCR technique was utilized. The prediction of suitable genes for hsa-miR-193a-5p, as well as the identification of pathways and gene-gene interactions, were carried out using bioinformatic tools. RESULTS: The levels of hsa-miR-193a-5p expression were notably elevated in AA patients in comparison to healthy controls. Our prediction suggests that the involvement of hsa-miR-193a-5p in the development of AA is significant due to its influence on the inositol phosphorylation pathway and the Phosphatidylinositol signaling system, achieved through its direct impact on the IPPK gene. CONCLUSION: For the first time, our study demonstrates the significant over-expression of a new miRNA, hsa-miR-193a-5p, in the blood of AA patients compared to controls, and highlights its impact on the IPPK gene and the inositol phosphorylation and Phosphatidylinositol signaling pathways, suggesting a potential therapeutic role for hsa-miR-193a-5p in AA.

Molecular and agro-morphological characterization of new barley genotypes in arid environments.

BACKGROUND: Genetic diversity, population structure, agro-morphological traits, and molecular characteristics, are crucial for either preserving genetic resources or developing new cultivars. Due to climate change, water availability for agricultural use is progressively diminishing. This study used 100 molecular markers (25 TRAP, 22 SRAP, 23 ISTR, and 30 SSR). Additionally, 15 morphological characteristics were utilized to evaluate the optimal agronomic traits of 12 different barley genotypes under arid conditions. RESULTS: Substantial variations, ranging from significant to highly significant, were observed in the 15 agromorphological parameters evaluated among the 12 genotypes. The KSU-B101 barley genotype demonstrated superior performance in five specific traits: spike number per plant, 100-grain weight, spike number per square meter, harvest index, and grain yield. These results indicate its potential for achieving high yields in arid regions. The Sahrawy barley genotype exhibited the highest values across five parameters, namely leaf area, spike weight per plant, spike length, spike weight per square meter, and biological yield, making it a promising candidate for animal feed. The KSU-B105 genotype exhibited early maturity and a high grain count per spike, which reflects its early maturity and ability to produce a high number of grains per spike. This suggests its suitability for both animal feed and human food in arid areas. Based on marker data, the molecular study found that the similarity coefficients between the barley genotypes ranged from 0.48 to 0.80, with an average of 0.64. The dendrogram constructed from these data revealed three distinct clusters with a similarity coefficient of 0.80. Notably, the correlation between the dendrogram and its similarity matrix was high (0.903), indicating its accuracy in depicting the genetic relationships. The combined analysis revealed a moderate correlation between the morphological and molecular analysis, suggesting alignment between the two characterization methods. CONCLUSIONS: The morphological and molecular analyses of the 12 barley genotypes in this study effectively revealed the varied genetic characteristics of their agro-performance in arid conditions. KSU-B101, Sahrawy, and KSU-B105 have emerged as promising candidates for different agricultural applications in arid regions. Further research on these genotypes could reveal their full potential for breeding programs.

Genomic tools for early selection among Thoroughbreds and Polo Argentino horses for practicing polo.

The Polo Argentino (PA) horse is a recognized breed, developed originally by mixing crossbred and Thoroughbred (TB) horses to play polo. Early PA selection is difficult due to unreliable performance estimations. This study investigated the usefulness of genomic markers previously linked to morphological and functional traits as a tool for the early selection of PA. To this, we genotyped 520 PA and 30 TB horses using the Equine GGPArray (Illumina, n = 71,778 SNPs). Analyses included a genetic characterization of six genetic markers associated with behavioral (DRD4), muscular development (MSTN), and body size (LCORL, HMGA6, ZFAT, and LASP1) genes. Genetic differences in the DRD4, MSTN, and LCORL SNP were found between the two breeds, in the last two FST index between breeds was 0.13 and 0.6, respectively (p < 0.01). In DRD4, G allele was the more prevalent in PA (0.56 vs 0.45 in TB, p < 0.05), but no differences were observed between the genotypes associated with phenotypes. In MSTN, heterozygous genotypes were the most common in PA (48 %), with a significant decrease in AA (Hardy-Weinberg p < 0.05), suggesting a negative selection against it in polo horses. In body size, HMGA2 was monomorphic in all horses, while ZFAT and LASP1 SNP showed higher variability. Interestingly, 99 % of PA showed a TT genotype in LCORL (only 66 % in TB), demonstrating selection for smaller horses. Our results suggest that empirical selection in PA has generated an incipient genomic differentiation in discrete traits which could be used as a marker-assisted selection tool for early selection of polo horses.

Identification of Sex-Associated Genetic Markers in Pistacia lentiscus var. chia for Early Male Detection.

Pistacia lentiscus var. chia is a valuable crop for its high-added-value mastic, a resin with proven pharmaceutical and cosmeceutical properties harvested from the male tree trunk. To achieve the maximum economic benefits from the cultivation of male mastic trees, it is important to develop early sex diagnosis molecular tools for distinguishing the sex type. Thus far, the work on sex identification has focused on Pistacia vera with promising results; however, the low transferability rates of these markers in P. lentiscus necessitates the development of species-specific sex-linked markers for P. lentiscus var. chia. To our knowledge, this is the first report regarding: (i) the development of species-specific novel transcriptome-based markers for P. lentiscus var. chia and their assessment on male, female and monoecious individuals using PCR-HRM analysis, thus, introducing a cost-effective method for sex identification with high accuracy that can be applied with minimum infrastructure, (ii) the effective sex identification in mastic tree using a combination of different sex-linked ISSR and SCAR markers with 100% accuracy, and (iii) the impact evaluation of sex type on the genetic diversity of different P. lentiscus var. chia cultivars. The results of this study are expected to provide species-specific markers for accurate sex identification that could contribute to the selection process of male mastic trees at an early stage for mass propagation systems and to facilitate future breeding efforts related to sex-linked productivity and quality of mastic resin.

Linkage Mapping and Genome-Wide Association Study Identified Two Peanut Late Leaf Spot Resistance Loci, PLLSR-1 and PLLSR-2, Using Nested Association Mapping.

Identification of candidate genes and molecular markers for late leaf spot (LLS) disease resistance in peanut (Arachis hypogaea) has been a focus of molecular breeding for the U.S. industry-funded peanut genome project. Efforts have been hindered by limited mapping resolution due to low levels of genetic recombination and marker density available in traditional biparental mapping populations. To address this, a multi-parental nested association mapping population has been genotyped with the peanut 58K single-nucleotide polymorphism (SNP) array and phenotyped for LLS severity in the field for 3 years. Joint linkage-based quantitative trait locus (QTL) mapping identified nine QTLs for LLS resistance with significant phenotypic variance explained up to 47.7%. A genome-wide association study identified 13 SNPs consistently associated with LLS resistance. Two genomic regions harboring the consistent QTLs and SNPs were identified from 1,336 to 1,520 kb (184 kb) on chromosome B02 and from 1,026.9 to 1,793.2 kb (767 kb) on chromosome B03, designated as peanut LLS resistance loci, PLLSR-1 and PLLSR-2, respectively. PLLSR-1 contains 10 nucleotide-binding site leucine-rich repeat disease resistance genes. A nucleotide-binding site leucine-rich repeat disease resistance gene, Arahy.VKVT6A, was also identified on homoeologous chromosome A02. PLLSR-2 contains five significant SNPs associated with five different genes encoding callose synthase, pollen defective in guidance protein, pentatricopeptide repeat, acyl-activating enzyme, and C2 GRAM domains-containing protein. This study highlights the power of multi-parent populations such as nested association mapping for genetic mapping and marker-trait association studies in peanuts. Validation of these two LLS resistance loci will be needed for marker-assisted breeding.

Potential Single Nucleotide Polymorphisms markers for radiation dermatitis in head and neck cancer patients: a meta-analysis.

PURPOSE: To identify potential Single Nucleotide Polymorphisms (SNPs) of susceptibility for the development of acute radiation dermatitis in head and neck cancer patients, and also to verify the association between SNPs and the severity of RD. METHODS: This systematic review was reported according to the PRISMA guideline. The proportion meta-analysis was performed to identify the prevalence of genetic markers by geographical region and radiation dermatitis severity. The meta-analysis was performed to verify the association between genetic markers and RD severity. The certainty of the evidence was assessed by GRADE. RESULTS: Thirteen studies were included. The most prevalent SNPs were XRCC3 (rs861639) (36%), TGFß1 (rs1800469) (35%), and RAD51 (rs1801321) (34%). There are prevalence studies in Europe and Asia, with a similar prevalence for all SNPs (29-40%). The prevalence was higher in patients who developed radiation dermatitis ≤2 for any subtype of genes (75-76%). No SNP showed a statistically significant association with very low certainty of evidence. CONCLUSION: The most prevalent SNPs may be predictors of acute RD. The analysis of SNP before starting radiation therapy may be a promising method to predict the risk of developing radiation dermatitis and allow radiosensitive patients to have a customized treatment. This current review provides new research directions.

Factors Influencing Mortality in Children with Central Nervous System Tumors: A Cohort Study on Clinical Characteristics and Genetic Markers.

Multidrug resistance (MDR) commonly leads to cancer treatment failure because cancer cells often expel chemotherapeutic drugs using ATP-binding cassette (ABC) transporters, which reduce drug levels within the cells. This study investigated the clinical characteristics and single nucleotide variant (SNV) in ABCB1, ABCC1, ABCC2, ABCC4, and ABCG2, and their association with mortality in pediatric patients with central nervous system tumors (CNST). Using TaqMan probes, a real-time polymerase chain reaction genotyped 15 SNPs in 111 samples. Patients were followed up until death or the last follow-up day using the Cox proportional hazards model. An association was found between the rs1045642 (ABCB1) in the recessive model (HR = 2.433, 95% CI 1.098-5.392, p = 0.029), and the ICE scheme in the codominant model (HR = 9.810, 95% CI 2.74-35.06, p ≤ 0.001), dominant model (HR = 6.807, 95% CI 2.87-16.103, p ≤ 0.001), and recessive model (HR = 6.903, 95% CI 2.915-16.544, p = 0.038) significantly increased mortality in this cohort of patients. An association was also observed between the variant rs3114020 (ABCG2) and mortality in the codominant model (HR = 5.35, 95% CI 1.83-15.39, p = 0.002) and the dominant model (HR = 4.421, 95% CI 1.747-11.185, p = 0.002). A significant association between the ICE treatment schedule and increased mortality risk in the codominant model (HR = 6.351, 95% CI 1.831-22.02, p = 0.004, HR = 9.571, 95% CI 2.856-32.07, p ≤ 0.001), dominant model (HR = 6.592, 95% CI 2.669-16.280, p ≤ 0.001), and recessive model (HR = 5.798, 95% CI 2.411-13.940, p ≤ 0.001). The genetic variants rs3114020 in the ABCG2 gene and rs1045642 in the ABCB1 gene and the ICE chemotherapy schedule were associated with an increased mortality risk in this cohort of pediatric patients with CNST.

Assessing the reproducibility of machine-learning-based biomarker discovery in Parkinson's disease.

Feature selection and machine learning algorithms can be used to analyze Single Nucleotide Polymorphisms (SNPs) data and identify potential disease biomarkers. Reproducibility of identified biomarkers is critical for them to be useful for clinical research; however, genotyping platforms and selection criteria for individuals to be genotyped affect the reproducibility of identified biomarkers. To assess biomarkers reproducibility, we collected five SNPs datasets from the database of Genotypes and Phenotypes (dbGaP) and explored several data integration strategies. While combining datasets can lead to a reduction in classification accuracy, it has the potential to improve the reproducibility of potential biomarkers. We evaluated the agreement among different strategies in terms of the SNPs that were identified as potential Parkinson's disease (PD) biomarkers. Our findings indicate that, on average, 93% of the SNPs identified in a single dataset fail to be identified in other datasets. However, through dataset integration, this lack of replication is reduced to 62%. We discovered fifty SNPs that were identified at least twice, which could potentially serve as novel PD biomarkers. These SNPs are indirectly linked to PD in the literature but have not been directly associated with PD before. These findings open up new potential avenues of investigation.

Development and validation of a new multiplex panel using SNaPshot-based DIP-TriSNP markers for forensic DNA mixtures.

Short tandem repeat analysis is challenging when dealing with unbalanced mixtures in forensic cases due to the presence of stutter peaks and large amplicons. In this research, we propose a novel genetic marker called DIP-TriSNP, which combines deletion/insertion polymorphism (DIP) with tri-allelic single nucleotide polymorphism in less than 230 bp length of human genome. Based on multiplex PCR and SNaPShot, a panel, including 14 autosomal DIP-TriSNPs and one Y chromosomal DIP-SNP, had been developed and applied to genotyping 102 unrelated Han Chinese individuals in Sichuan of China and simulated a mixture study. The panel sensitivity can reach as low as 0.1 ng DNA template, and the minor contributor of DNA can be detected with the highest ratio of 19:1, as indicated by the obtained results. In the Sichuan Han population, the cumulative probability of informative genotypes reached 0.997092, with a combined power of discrimination of 0.999999998801. The panel was estimated to detect more than two alleles in at least one locus in 99.69% of mixtures of the Sichuan Han population. In conclusion, DIP-TriSNPs have shown promising as an innovative DNA marker for identifying the minor contributor in unbalanced DNA mixtures, offering advantages such as short amplifications, increased polymorphism, and heightened sensitivity.

A Scalable and Robust Chloroplast Genotyping Solution: Development and Application of SNP and InDel Markers in the Maize Chloroplast Genome.

Maize(Zea mays. L) is a globally important crop, and understanding its genetic diversity is crucial for plant breeding phylogenetic analyses and comparative genetics. While nuclear markers have been extensively used for mapping agriculturally important genes, they are limited in recognizing characteristics, such as cytoplasmic male sterility and reciprocal cross hybrids. In this study, we performed next-generation sequencing of 176samples, and the maize cultivars represented five distinct groups. A total of 89 single nucleotide polymorphisms (SNPs) and 11 insertion/deletion polymorphisms (InDels) were identified. To enable high-throughput detection, we successfully amplified and confirmed 49 SNP and InDel markers, which were defined as a Varietal Chloroplast Panel (VCP) using the Kompetitive Allele Specific PCR (KASP). The specific markers provided a valuable tool for identifying chloroplast groups. The verification experiment, focusing on the identification of reciprocal cross hybrids and cytoplasmic male sterility hybrids, demonstrated the significant advantages of VCP markers in maternal inheritance characterization. Furthermore, only a small subset of these markers is needed to provide useful information, showcasing the effectiveness of these markers in elucidating the artificial selection process of elite maize lines.

Strategies to deal with genetic analyzer-specific DNA methylation measurements.

Targeted bisulfite sequencing using single-base extension (SBE) can be used to measure DNA methylation via capillary electrophoresis on genetic analyzers in forensic labs. Several accurate age prediction models have been reported using this method. However, using different genetic analyzers with different software settings can generate different methylation values, leading to significant errors in age prediction. To address this issue, the study proposes and compares four methods as follows: (1) adjusting methylation values using numerous actual body fluid DNA samples, (2) adjusting methylation values using control DNAs with varying methylation ratios, (3) constructing new age prediction models for each genetic analyzer type, and (4) constructing new age prediction models that could be applied to all types of genetic analyzers. To test the methods for adjusting values using actual body fluid DNA samples, previously reported adjusting equations were used for blood/saliva DNA age prediction markers (ELOVL2, FHL2, KLF14, MIR29B2CHG/C1orf132, and TRIM59). New equations were generated for semen DNA age prediction markers (TTC7B, LOC401324/cg12837463, and LOC729960/NOX4) by drawing polynomial regression lines between the results of the three types of genetic analyzers (3130, 3500, and SeqStudio). The same method was applied to obtain adjustment equations using 11 control DNA samples. To develop new age prediction models for each genetic analyzer type, linear regression analysis was conducted using DNA methylation data from 150 blood, 150 saliva, and 62 semen samples. For the genetic analyzer-independent models, control DNAs were used to formulate equations for calibrating the bias of the data from each genetic analyzer, and linear regression analysis was performed using calibrated body fluid DNA data. In the comparison results, the genetic analyzer-specific models showed the highest accuracy. However, genetic analyzer-independent models through bias adjustment also provided accurate age prediction results, suggesting its use as an alternative in situations with multiple constraints.

Comparison of Clinical and Genetic Characteristics Between Younger and Older Lung Cancer Patients

Introduction The aim of this study was to analyze the clinical and genetic characteristics of young lung cancer cases, and to compare them with those of older cases. Methods We used the Thoracic Tumors Registry (TTR) as a data source representative of lung cancer cases diagnosed in Spain, and included all cases registered until 9/01/2023 which had information on age at diagnosis or the data needed to calculate it. We performed a descriptive statistical analysis and fitted logistic regressions to analyze how different characteristics influenced being a younger lung cancer patient. Results A total of 26,336 subjects were included. Lung cancer cases <50 years old had a higher probability of being women (OR: 1.38; 95% CI: 1.21–1.57), being in stage III or IV (OR: 1.32; 95% CI: 1.08–1.62), not having comorbidities (OR: 5.21; 95% CI: 4.59–5.91), presenting with symptoms at diagnosis (OR: 1.53; 95% CI: 1.29–1.81), and having ALK translocation (OR: 7.61; 95% CI: 1.25–46.32) and HER2 mutation (OR: 5.71; 95% CI: 1.34–24.33), compared with subjects ≥50 years. Among subjects <35 years old (n=61), our study observed a higher proportion of women (59.0% vs. 26.6%; p<0.001), never smokers (45.8% vs. 10.3%; p<0.001), no comorbidities (21.3% vs. 74.0%; p<0.001); ALK translocation (33.3% vs. 4.4%; p<0.001) and ROS1 mutation (14.3% vs. 2.3%; p=0.01), compared with subjects ≥35 years. Conclusions Lung cancer displays differences by age at diagnosis which may have important implications for its clinical management (AU)

Recycling selectable markers via Cre/loxP system for constructing Komagataella phaffii strains co-expressing multiple proteins.

OBJECTIVE: A convenient strategy was developed to recycle selectable markers using Cre/loxP system for constructing Komagataella phaffii strains co-expressing multiple proteins. RESULTS: A plasmid in this strategy was generated from pPICZαA with integration of lox71-Sh ble-lox66. Firstly, the plasmid was inserted with one target protein gene and then transformed into K. phaffii KM71. Secondly, the auxiliary plasmid pPICZαA/cre/his4 containing CRE recombinase gene was further chromosomally inserted to Sh ble gene therein. Finally, methanol induction was conducted to produce CRE for Cre/loxP-mediated recombination, and consequently, the sequence between lox71 and lox66 was deleted, leading to recycling of ZeoR and His- markers. Then the resulted strain expressing the one target protein was used as the host to which another target protein gene could be inserted by the same procedures. CONCLUSIONS: With easy manipulation, the method was effective in recycling of the selectable markers, and consequently two protein genes were sequential integrated chromosomally and successfully co-expressed in the yeast.

An examination of differences in epigenetic methylation of saliva type samples based on collection method.

In the context of forensic casework, it is imperative to both establish a DNA profile from biological specimens and accurately identify the specific bodily fluid source. To achieve this, DNA methylation markers have been developed for the differentiation of blood, semen, vaginal epithelial secretions, and saliva samples. Saliva, alternatively referred to as oral fluid, is recognized for its heterogeneous cellular composition, characterized by a mixture of epithelial, leukocytic, and bacterial cells. Consequently, our research has revealed variations in methylation percentages that correlate with the method employed for collecting saliva samples. To investigate these concepts, we scrutinized four CpG markers situated within or in proximity to the BCAS4, SLC12A8, SOX2OT, and FAM43A genes. Subsequently, we designed primers based on bioinformatically transformed reference sequences for these markers and rigorously assessed their quality by examining dimer and hairpin formation, melting temperature, and specificity. These loci were identified as saliva markers based on either buccal swabs or spit collection. Yet, there has been minimal or no research conducted to explore the variations in methylation between different collection methods. For this study, buccal, lip, tongue, spit, and nasal swabs were collected from 20 individuals (N = 100). Mock forensic samples, which include chewing gum (N = 10) and cigarettes (N = 10), were also tested. DNA was extracted, bisulfite converted, then amplified using in-house designed assays, and pyrosequenced. The methylation levels were compared to other body fluids (semen, blood, vaginal epithelia, and menstrual blood [N = 32]). A total of 608 pyrosequencing results demonstrated that sampling location and collection method can greatly influence the level of methylation, highlighting the importance of examining multiple collection/deposition methods for body fluids when developing epigenetic markers.

Mapping of a Recessive Gene for All-Stage Resistance to Stripe Rust in a Wheat Line Derived from Cultivated Einkorn (Triticum monococcum).

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most destructive fungal diseases of wheat. Cultivated einkorn (Triticum monococcum L. ssp. monococcum, 2n = 2x = 14, AmAm), one of the founder crops of agriculture, harbors unexploited genetic sources for wheat improvement. An advanced wheat line, Z15-1949, with 42 chromosomes, selected from the hybrids of Pst-susceptible common wheat cultivar Crocus and resistant T. monococcum accession 10-1, exhibits high resistance to a mixture of the prevalent Chinese Pst races. Genetic analysis on F1, F2, and F2:3 generations of the cross between Z15-1949 and Pst-susceptible common wheat SY95-71 indicated that the resistance of Z15-1949 was conferred by a recessive gene, tentatively designated as YrZ15-1949. This gene was mapped to the short arm of chromosome 7D using the Wheat 55K single nucleotide polymorphism array, flanked by markers KASP-1949-2 and KASP-1949-10 within a 3.3-cM genetic interval corresponding to a 1.12-Mb physical region in the Chinese Spring reference genome V2.0. The gene differs from previously reported Yr genes on 7D based on their physical positions and is probably a novel gene. YrZ15-1949 would be a valuable resource for developing Pst-resistant wheat cultivars, and the linked markers could be used for marker-assisted selection.