DNA methylation-based high-resolution mapping of long-distance chromosomal interactions in nucleosome-depleted regions.

3C-based methods have significantly advanced our understanding of 3D genome organization. However, it remains a formidable task to precisely capture long-range chromosomal interactions between individual loci, such as those between promoters and distal enhancers. Here, we present Methyltransferase Targeting-based chromosome Architecture Capture (MTAC), a method that maps the contacts between a target site (viewpoint) and the rest of the genome in budding yeast with high resolution and sensitivity. MTAC detects hundreds of intra- and inter-chromosomal interactions within nucleosome-depleted regions (NDRs) that cannot be captured by 4C, Hi-C, or Micro-C. By applying MTAC to various viewpoints, we find that (1) most long-distance chromosomal interactions detected by MTAC reflect tethering by the nuclear pore complexes (NPCs), (2) genes co-regulated by methionine assemble into inter-chromosomal clusters near NPCs upon activation, (3) mediated by condensin, the mating locus forms a highly specific interaction with the recombination enhancer (RE) in a mating-type specific manner, and (4) correlation of MTAC signals among NDRs reveal spatial mixing and segregation of the genome. Overall, these results demonstrate MTAC as a powerful tool to resolve fine-scale long-distance chromosomal interactions and provide insights into the 3D genome organization.

Human telomere length is chromosome end-specific and conserved across individuals.

Short telomeres cause age-related disease, and long telomeres contribute to cancer; however, the mechanisms regulating telomere length are unclear. We developed a nanopore-based method, which we call Telomere Profiling, to determine telomere length at nearly single-nucleotide resolution. Mapping telomere reads to chromosome ends showed chromosome end-specific length distributions that could differ by more than six kilobases. Examination of telomere lengths in 147 individuals revealed that certain chromosome ends were consistently longer or shorter. The same rank order was found in newborn cord blood, suggesting that telomere length is determined at birth and that chromosome end-specific telomere length differences are maintained as telomeres shorten with age. Telomere Profiling makes precision investigation of telomere length widely accessible for laboratory, clinical, and drug discovery efforts and will allow deeper insights into telomere biology.

A k-mer-based bulked segregant analysis approach to map seed traits in unphased heterozygous potato genomes.

High-throughput sequencing-based methods for bulked segregant analysis (BSA) allow for the rapid identification of genetic markers associated with traits of interest. BSA studies have successfully identified qualitative (binary) and quantitative trait loci (QTLs) using QTL mapping. However, most require population structures that fit the models available and a reference genome. Instead, high-throughput short-read sequencing can be combined with BSA of k-mers (BSA-k-mer) to map traits that appear refractory to standard approaches. This method can be applied to any organism and is particularly useful for species with genomes diverged from the closest sequenced genome. It is also instrumental when dealing with highly heterozygous and potentially polyploid genomes without phased haplotype assemblies and for which a single haplotype can control a trait. Finally, it is flexible in terms of population structure. Here, we apply the BSA-k-mer method for the rapid identification of candidate regions related to seed spot and seed size in diploid potato. Using a mixture of F1 and F2 individuals from a cross between 2 highly heterozygous parents, candidate sequences were identified for each trait using the BSA-k-mer approach. Using parental reads, we were able to determine the parental origin of the loci. Finally, we mapped the identified k-mers to a closely related potato genome to validate the method and determine the genomic loci underlying these sequences. The location identified for the seed spot matches with previously identified loci associated with pigmentation in potato. The loci associated with seed size are novel. Both loci are relevant in future breeding toward true seeds in potato.

Joint Linkage and Association Analysis Using GENEHUNTER-MODSCORE with an Application to Familial Pancreatic Cancer.

INTRODUCTION: Joint linkage and association (JLA) analysis combines two disease gene mapping strategies: linkage information contained in families and association information contained in populations. Such a JLA analysis can increase mapping power, especially when the evidence for both linkage and association is low to moderate. Similarly, an association analysis based on haplotypes instead of single markers can increase mapping power when the association pattern is complex. METHODS: In this paper, we present an extension to the GENEHUNTER-MODSCORE software package that enables a JLA analysis based on haplotypes and uses information from arbitrary pedigree types and unrelated individuals. Our new JLA method is an extension of the MOD score approach for linkage analysis, which allows the estimation of trait-model and linkage disequilibrium (LD) parameters, i.e., penetrance, disease-allele frequency, and haplotype frequencies. LD is modeled between alleles at a single diallelic disease locus and up to three diallelic test markers. Linkage information is contributed by additional multi-allelic flanking markers. We investigated the statistical properties of our JLA implementation using extensive simulations, and we compared our approach to another commonly used single-marker JLA test. To demonstrate the applicability of our new method in practice, we analyzed pedigree data from the German National Case Collection for Familial Pancreatic Cancer (FaPaCa). RESULTS: Based on the simulated data, we demonstrated the validity of our JLA-MOD score analysis implementation and identified scenarios in which haplotype-based tests outperformed the single-marker test. The estimated trait-model and LD parameters were in good accordance with the simulated values. Our method outperformed another commonly used JLA single-marker test when the LD pattern was complex. The exploratory analysis of the FaPaCa families led to the identification of a promising genetic region on chromosome 22q13.33, which can serve as a starting point for future mutation analysis and molecular research in pancreatic cancer. CONCLUSION: Our newly proposed JLA-MOD score method proves to be a valuable gene mapping and characterization tool, especially when either linkage or association information alone provide insufficient power to identify the disease-causing genetic variants.

Engineering homoeologs provide a fine scale for quantitative traits in polyploid.

Numerous staple crops exhibit polyploidy and are difficult to genetically modify. However, recent advances in genome sequencing and editing have enabled polyploid genome engineering. The hexaploid black nightshade species Solanum nigrum has immense potential as a beneficial food supplement. We assembled its genome at the scaffold level. After functional annotations, we identified homoeologous gene sets, with similar sequence and expression profiles, based on comparative analyses of orthologous genes with close diploid relatives Solanum americanum and S. lycopersicum. Using CRISPR-Cas9-mediated mutagenesis, we generated various mutation combinations in homoeologous genes. Multiple mutants showed quantitative phenotypic changes based on the genotype, resulting in a broad-spectrum effect on the quantitative traits of hexaploid S. nigrum. Furthermore, we successfully improved the fruit productivity of Boranong, an orphan cultivar of S. nigrum suggesting that engineering homoeologous genes could be useful for agricultural improvement of polyploid crops.

Integrating de novo QTL-seq and linkage mapping to identify quantitative trait loci conditioning physiological resistance and avoidance to white mold disease in dry bean.

White mold (WM), caused by the ubiquitous fungus Sclerotinia sclerotiorum, is a devastating disease that limits production and quality of dry bean globally. In the present study, classic linkage mapping combined with QTL-seq were employed in two recombinant inbred line (RIL) populations, "Montrose"/I9365-25 (M25) and "Raven"/I9365-31 (R31), with the initial goal of fine-mapping QTL WM5.4 and WM7.5 that condition WM resistance. The RILs were phenotyped for WM reactions under greenhouse (straw test) and field environments. The general region of WM5.4 and WM7.5 were reconfirmed with both mapping strategies within each population. Combining the results from both mapping strategies, WM5.4 was delimited to a 22.60-36.25 Mb interval in the heterochromatic regions on Pv05, while WM7.5 was narrowed to a 0.83 Mb (3.99-4.82 Mb) region on the Pv07 chromosome. Furthermore, additional QTL WM2.2a (3.81-7.24 Mb), WM2.2b (11.18-17.37 Mb, heterochromatic region), and WM2.2c (23.33-25.94 Mb) were mapped to a narrowed genomic interval on Pv02 and WM4.2 in a 0.89 Mb physical interval at the distal end of Pv04 chromosome. Gene models encoding gibberellin 2-oxidase proteins regulating plant architecture are likely candidate genes associated with WM2.2a resistance. Nine gene models encoding a disease resistance protein (quinone reductase family protein and ATWRKY69) found within the WM5.4 QTL interval are putative candidate genes. Clusters of 13 and 5 copies of gene models encoding cysteine-rich receptor-like kinase and receptor-like protein kinase-related family proteins, respectively, are potential candidate genes associated with WM7.5 resistance and most likely trigger physiological resistance to WM. Acquired knowledge of the narrowed major QTL intervals, flanking markers, and candidate genes provides promising opportunities to develop functional molecular markers to implement marker-assisted selection for WM resistant dry bean cultivars.

Mapping of major QTL and candidate gene analysis for hull colour in foxtail millet (Setaria italica (L.) P. Beauv.).

BACKGROUND: Hull colour is an important morphological marker for selection in seed production of foxtail millet. However, the molecular mechanisms underlying hull colour variation remain unknown. RESULTS: An F7 recombinant inbred line (RIL) population containing 215 lines derived from Hongjiugu × Yugu18 was used to analyze inheritance and detect the quantitative trait loci (QTL) for four hull colour traits using major gene plus polygene mixed inheritance analysis and composite interval mapping (CIM) in four environments. Genetic analysis revealed that the hull colour L* value (HCL*) was controlled by two major genes plus additive polygenes, the hull colour a* value (HCa*) was controlled by three major genes, the hull colour b* value (HCb*) was controlled by two major genes plus polygenes, and the hull colour C* value (HCC*) was controlled by four major genes. A high-density genetic linkage map covering 1227.383 cM of the foxtail millet genome, with an average interval of 0.879 cM between adjacent bin markers, was constructed using 1420 bin markers. Based on the genetic linkage map and the phenotypic data, a total of 39 QTL were detected for these four hull colour traits across four environments, each explaining 1.50%-49.20% of the phenotypic variation. Of these, six environmentally stable major QTL were co-localized to regions on chromosomes 1 and 9, playing a major role in hull colour. There were 556 annotated genes within the two QTL regions. Based on the functions of homologous genes in Arabidopsis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) gene annotations, five genes were predicted as candidate genes for further studies. CONCLUSIONS: This is the first study to use an inheritance model and QTL mapping to determine the genetic mechanisms of hull colour trait in foxtail millet. We identified six major environmentally stable QTL and predicted five potential candidate genes to be associated with hull colour. These results advance the current understanding of the genetic mechanisms underlying hull colour traits in foxtail millet and provide additional resources for application in genomics-assisted breeding and potential isolation and functional characterization of the candidate genes.

Identification of quantitative trait loci controlling soybean seed protein and oil content.

Soybean is a major source of seed protein and oil globally with an average composition of 40% protein and 20% oil in the seed. The goal of this study was to identify quantitative trait loci (QTL) conferring seed protein and oil content utilizing a population constructed by crossing an above average protein content line, PI 399084 to another line that had a low protein content value, PI 507429, both from the USDA soybean germplasm collection. The recombinant inbred line (RIL) population, PI 507429 x PI 399084, was evaluated in two replications over four years (2018-2021); the seeds were analyzed for seed protein and oil content using near-infrared reflectance spectroscopy. The recombinant inbred lines and the two parents were re-sequenced using genotyping by sequencing. A total of 12,761 molecular markers, which came from genotyping by sequencing, the SoySNP6k BeadChip and selected simple sequence repeat (SSR) markers from known protein QTL chromosomal regions were used for mapping. One QTL was identified on chromosome 2 explaining up to 56.8% of the variation for seed protein content and up to 43% for seed oil content. Another QTL identified on chromosome 15 explained up to 27.2% of the variation for seed protein and up to 41% of the variation for seed oil content. The protein and oil QTLs of this study and their associated molecular markers will be useful in breeding to improve nutritional quality in soybean.

Getting an A with the 3Cs: Chromosome Conformation Capture for Undergraduates.

Chromosome conformation capture (3C) is a powerful tool that has spawned a family of similar techniques (e.g., Hi-C, 4C, and 5C, referred to here as 3C techniques) that provide detailed information of the three-dimensional organization of chromatin. The 3C techniques have been used in a wide range of studies, from monitoring the changes in chromatin organization in cancer cells to identifying enhancer contacts made with gene promoters. While many of the studies using these techniques are asking big genome-wide questions with intricate sample types (i.e., single-cell analysis), what is often lost is that the 3C techniques are grounded in basic molecular biology methods that are applicable to a broad range of studies. By addressing tightly focused questions of chromatin organization, this cutting-edge technique can be used to enhance the undergraduate research and teaching lab experience. This paper presents a 3C protocol and provides adaptations and points of emphasis for implementation at primarily undergraduate institutions in undergraduate research and teaching experiences.

An unbiased AAV-STARR-seq screen revealing the enhancer activity map of genomic regions in the mouse brain in vivo.

Enhancers are important cis-regulatory elements controlling cell-type specific expression patterns of genes. Furthermore, combinations of enhancers and minimal promoters are utilized to construct small, artificial promoters for gene delivery vectors. Large-scale functional screening methodology to construct genomic maps of enhancer activities has been successfully established in cultured cell lines, however, not yet applied to terminally differentiated cells and tissues in a living animal. Here, we transposed the Self-Transcribing Active Regulatory Region Sequencing (STARR-seq) technique to the mouse brain using adeno-associated-viruses (AAV) for the delivery of a highly complex screening library tiling entire genomic regions and covering in total 3 Mb of the mouse genome. We identified 483 sequences with enhancer activity, including sequences that were not predicted by DNA accessibility or histone marks. Characterizing the expression patterns of fluorescent reporters controlled by nine candidate sequences, we observed differential expression patterns also in sparse cell types. Together, our study provides an entry point for the unbiased study of enhancer activities in organisms during health and disease.

Genetic analysis and exploration of major effect QTLs underlying oil content in peanut.

KEY MESSAGE: AhyHOF1, likely encoding a WRI1 transcription factor, plays critical roles in peanut oil synthesis. Although increasing the oil content of peanut to meet growing demand has long been a primary aim of breeding programs worldwide, the mining of genetic resources to achieve this objective has obviously lagged behind that of other oil crops. In the present study, we developed an advanced recombinant inbred line population containing 192 F9:11 families derived from parents JH5 and KX01-6. We then constructed a high-resolution genetic map covering 3,706.382 cM, with an average length of 185.32 cM per linkage group, using 2840 polymorphic SNPs. Two stable QTLs, qCOA08_1 and qCOA08_2 having the highest contributions to genetic variation (16.1% and 20.7%, respectively), were simultaneously detected in multiple environments and closely mapped within physical intervals of approximately 2.9 Mb and 1.7 Mb, respectively, on chromosome A08. In addition, combined analysis of whole-genome and transcriptome resequencing data uncovered a strong candidate gene encoding a WRI1 transcription factor and differentially expressed between the two parents. This gene, designated as High Oil Favorable gene 1 in Arachis hypogaea (AhyHOF1), was hypothesized to play roles in oil accumulation. Examination of near-inbred lines of #AhyHOF1/#Ahyhof1 provided further evidence that AhyHOF1 increases oil content, mainly by affecting the contents of several fatty acids. Taken together, our results provide valuable information for cloning the favorable allele for oil content in peanut. In addition, the closely linked polymorphic SNP markers within qCOA08_1 and qCOA08_2 loci may be useful for accelerating marker-assisted selection breeding of peanut.

Genetic architecture of protein and oil content in soybean seed and meal.

Soybean is grown primarily for the protein and oil extracted from its seed and its value is influenced by these components. The objective of this study was to map marker-trait associations (MTAs) for the concentration of seed protein, oil, and meal protein using the soybean nested association mapping (SoyNAM) population. The composition traits were evaluated on seed harvested from over 5000 inbred lines of the SoyNAM population grown in 10 field locations across 3 years. Estimated heritabilities were at least 0.85 for all three traits. The genotyping of lines with single nucleotide polymorphism markers resulted in the identification of 107 MTAs for the three traits. When MTAs for the three traits that mapped within 5 cM intervals were binned together, the MTAs were mapped to 64 intervals on 19 of the 20 soybean chromosomes. The majority of the MTA effects were small and of the 107 MTAs, 37 were for protein content, 39 for meal protein, and 31 for oil content. For cases where a protein and oil MTAs mapped to the same interval, most (94%) significant effects were opposite for the two traits, consistent with the negative correlation between these traits. A coexpression analysis identified candidate genes linked to MTAs and 18 candidate genes were identified. The large number of small effect MTAs for the composition traits suggest that genomic prediction would be more effective in improving these traits than marker-assisted selection.

Identification and Mapping of QTLs for Sulfur-Containing Amino Acids in Soybean (Glycine max L.).

Soybean is a major source of high-quality protein for humans and animals. The content of sulfur-containing amino acids (SAA) in soybean is insufficient, which has become the main factor limiting soybean nutrition. In this study, we used the high-density genetic maps derived from Guizao 1 and Brazil 13 to evaluate the quantitative trait loci of cysteine (Cys), methionine (Met), SAA, glycinin (7S), ß-conglycinin (11S), ratio of glycinin to ß-conglycinin (RGC), and protein content (PC). In genetic map linkage analysis, the major and stable 44 QTLs were detected, which shared nine bin intervals. Among them, the bin interval (bin157-bin160) on chromosome 5 was detected in multiple environments as a stable QTL, which was linked to 11S, 7S, RGC, and SSA. Based on the analysis of bioinformatics and RNA-sequencing data, 16 differentially expressed genes (DEGs) within these QTLs were selected as candidate genes. These results will help to elucidate the genetic mechanism of soybean SAA-related traits and provide the basis for the gene mining of sulfur-containing amino acids.

Detection of Transgene Location in the CYP2A13/2B6/2F1-transgenic Mouse Model using Optical Genome Mapping Technology.

Most transgenic mouse models are generated through random integration of the transgene. The location of the transgene provides valuable information for assessing potential effects of the transgenesis on the host and for designing genotyping protocols that can amplify across the integration site, but it is challenging to identify. Here, we report the successful utility of optical genome mapping technology to identify the transgene insertion site in a CYP2A13/2B6/2F1-transgenic mouse model, which produces three human cytochrome P450 (P450) enzymes (CYP2A13, CYP2B6, and CYP2F1) that are encoded by neighboring genes on human chromosome 19. These enzymes metabolize many drugs, respiratory toxicants, and chemical carcinogens. Initial efforts to identify candidate insertion sites by whole genome sequencing was unsuccessful, apparently because the transgene is located in a region of the mouse genome that contains highly repetitive sequences. Subsequent utility of the optical genome mapping approach, which compares genome-wide marker distribution between the transgenic mouse genome and a reference mouse (GRCm38) or human (GRCh38) genome, localized the insertion site to mouse chromosome 14, between two marker positions at 4451324 base pair and 4485032 base pair. A transgene-mouse genome junction sequence was further identified through long-polymerase chain reaction amplification and DNA sequencing at GRCm38 Chr.14:4484726. The transgene insertion (∼2.4 megabase pair) contained 5-7 copies of the human transgenes, which replaced a 26.9-33.4 kilobase pair mouse genomic region, including exons 1-4 of Gm3182, a predicted and highly redundant gene. Finally, the sequencing results enabled the design of a new genotyping protocol that can distinguish between hemizygous and homozygous CYP2A13/2B6/2F1-transgenic mice. SIGNIFICANCE STATEMENT: This study characterizes the genomic structure of, and provides a new genotyping method for, a transgenic mouse model that expresses three human P450 enzymes, CYP2A13, CYP2B6, and CYP2F1, that are important in xenobiotic metabolism and toxicity. The demonstrated success in applying the optical genome mapping technology for identification of transgene insertion sites should encourage others to do the same for other transgenic models generated through random integration, including most of the currently available human P450 transgenic mouse models.

Development of a 135K SNP genotyping array for Actinidia arguta and its applications for genetic mapping and QTL analysis in kiwifruit.

Kiwifruit (Actinidia spp) is a woody, perennial and deciduous vine. In this genus, there are multiple ploidy levels but the main cultivated cultivars are polyploid. Despite the availability of many genomic resources in kiwifruit, SNP genotyping is still a challenge given these different levels of polyploidy. Recent advances in SNP array technologies have offered a high-throughput genotyping platform for genome-wide DNA polymorphisms. In this study, we developed a high-density SNP genotyping array to facilitate genetic studies and breeding applications in kiwifruit. SNP discovery was performed by genome-wide DNA sequencing of 40 kiwifruit genotypes. The identified SNPs were stringently filtered for sequence quality, predicted conversion performance and distribution over the available Actinidia chinensis genome. A total of 134 729 unique SNPs were put on the array. The array was evaluated by genotyping 400 kiwifruit individuals. We performed a multidimensional scaling analysis to assess the diversity of kiwifruit germplasm, showing that the array was effective to distinguish kiwifruit accessions. Using a tetraploid F1 population, we constructed an integrated linkage map covering 3060.9 cM across 29 linkage groups and performed QTL analysis for the sex locus that has been identified on Linkage Group 3 (LG3) in Actinidia arguta. Finally, our dataset presented evidence of tetrasomic inheritance with partial preferential pairing in A. arguta. In conclusion, we developed and evaluated a 135K SNP genotyping array for kiwifruit. It has the advantage of a comprehensive design that can be an effective tool in genetic studies and breeding applications in this high-value crop.

Admixture Mapping in African Americans Identifies New Risk Loci for HCV-Related Cirrhosis.

BACKGROUND & AIMS: Cirrhosis is the main predisposing condition for hepatocellular carcinoma. Host genetic risk factors have been reported for cirrhosis; however, whether there is a genetic contribution to racial disparities in cirrhosis requires further investigation. METHODS: We used an affected-only mapping by admixture linkage disequilibrium analysis to characterize the genetic risk of cirrhosis in 227 African American patients with cirrhosis genotyped at 19,804 ancestry-informative marker single nucleotide polymorphisms. We additionally performed analyses stratified by hepatitis C virus (HCV) infection status. To replicate our findings, we conducted a case-control analysis in an external study population (452 cases and 196 controls). RESULTS: The mean age of patients was 63.3 years and 98.2% were male. Risk factors for cirrhosis included HCV infection (83.7%) and alcohol abuse (56.4%). In the admixture mapping analysis, we found that European ancestry on chromosome 2q21.1 and African ancestry on chromosome 6p21.2 were associated with increased risk of cirrhosis in African Americans. In the fine-mapping analysis, we identified regions near POTEKP on 2q21.1 (P = .0001) and DNAH8 on 6p21.2 (P = .0017) that were associated with cirrhosis. As the admixture peaks in the HCV-positive patients were the same as those in the overall group, findings in the analysis are reflective of the HCV-positive group. In the replication analysis, the results on chromosome 2 were not significant after adjusting for multiple comparisons, and we could not replicate the results on chromosome 6. CONCLUSIONS: We used admixture mapping to identify novel genomic regions on 2q21.1 and 6p21.2 that may be associated with HCV-related cirrhosis risk in African Americans.

Genotyping by sequencing-based linkage map construction and identification of quantitative trait loci for yield-related traits and oil content in Jatropha (Jatropha curcas L.).

BACKGROUND: Jatropha (Jatropha curcas L.) has been considered as a potential bioenergy crop and its genetic improvement is essential for higher seed yield and oil content which has been hampered due to lack of desirable molecular markers. METHODS AND RESULTS: An F2 population was created using an intraspecific cross involving a Central American line RJCA9 and an Asiatic species RJCS-9 to develop a dense genetic map and for Quantitative trait loci (QTL) identification. The genotyping-by-sequencing (GBS) approach was used to genotype the mapping population of 136 F2 individuals along with the two parental lines for classification of the genotypes based on single nucleotide polymorphism (SNPs). NextSeq 2500 sequencing technology provided a total of 517.23 million clean reads, with an average of ~ 3.8 million reads per sample. We analysed 411 SNP markers and developed 11 linkage groups. The total length of the genetic map was 4092.3 cM with an average marker interval of 10.04 cM. We have identified a total of 83 QTLs for various yield and oil content governing traits. The percentage of phenotypic variation (PV) was found to be in the range of 8.81 to 65.31%, and a QTL showed the maximum PV of 65.3% for a total seed number on the 6th linkage group (LG). CONCLUSIONS: The QTLs detected in this study for various phenotypic traits will lay down the path for marker-assisted breeding in the future and cloning of genes that are responsible for phenotypic variation.

Identification of quantitative trait loci (QTLs) and candidate genes of seed Iron and zinc content in soybean [Glycine max (L.) Merr.].

BACKGROUND: Deciphering the hereditary mechanism of seed iron (Fe) and zinc (Zn) content in soybean is important and sustainable to address the "hidden hunger" that presently affects approximately 2 billion people worldwide. Therefore, in order to detect genomic regions related to soybean seed Fe and Zn content, a recombinant inbred line (RIL) population with 248 lines was assessed in four environments to detect Quantitative Trait Loci (QTLs) related to soybean seed Fe and Zn content. RESULT: Wide variation was found in seed Fe and Zn content in four environments, and genotype, environment, and genotype × environment interactions had significant influences on both the seed Fe and Zn content. A positive correlation was observed between seed Fe content and seed Zn content, and broad-sense heritability (H2) of seed Fe and Zn content were 0.73 and 0.75, respectively. In this study, five QTLs for seed Fe content were detected with 4.57 - 32.71% of phenotypic variation explained (PVE) and logarithm of odds (LOD) scores ranging from 3.60 to 33.79. Five QTLs controlling the seed Zn content were detected, and they individually explained 3.35 to 26.48% of the phenotypic variation, with LOD scores ranging from 3.64 to 20.4. Meanwhile, 409,541 high-quality single-nucleotide variants (SNVs) and 85,102 InDels (except intergenic regions) between two bi-parental lines were identified by whole genome resequencing. A total of 12 candidate genes were reported in one major QTL for seed Fe content and two major QTLs for seed Zn content, with the help of RNA-Seq analysis, gene ontology (GO) enrichment, gene annotation, and bi-parental whole genome sequencing (WGS) data. CONCLUSIONS: Limited studies were performed about microelement of soybean, so these results may play an important role in the biofortification of Fe and Zn and accelerate the development of marker-assisted selection (MAS) for breeding soybeans fortified with iron and zinc.

Optimizing the diagnostic workflow for acute lymphoblastic leukemia by optical genome mapping.

Acute lymphoblastic leukemia (ALL) is a malignancy that can be subdivided into distinct entities based on clinical, immunophenotypic and genomic features, including mutations, structural variants (SVs), and copy number alterations (CNA). Chromosome banding analysis (CBA) and Fluorescent In-Situ Hybridization (FISH) together with Multiple Ligation-dependent Probe Amplification (MLPA), array and PCR-based methods form the backbone of routine diagnostics. This approach is labor-intensive, time-consuming and costly. New molecular technologies now exist that can detect SVs and CNAs in one test. Here we apply one such technology, optical genome mapping (OGM), to the diagnostic work-up of 41 ALL cases. Compared to our standard testing pathway, OGM identified all recurrent CNAs and SVs as well as additional recurrent SVs and the resulting fusion genes. Based on the genomic profile obtained by OGM, 32 patients could be assigned to one of the major cytogenetic risk groups compared to 23 with the standard approach. The latter identified 24/34 recurrent chromosomal abnormalities, while OGM identified 33/34, misinterpreting only 1 case with low hypodiploidy. The results of MLPA were concordant in 100% of cases. Overall, there was excellent concordance between the results. OGM increased the detection rate and cytogenetic resolution, and abrogated the need for cascade testing, resulting in reduced turnaround times. OGM also provided opportunities for better patient stratification and accurate treatment options. However, for comprehensive cytogenomic testing, OGM still needs to be complemented with CBA or SNP-array to detect ploidy changes and with BCR::ABL1 FISH to assign patients as soon as possible to targeted therapy.

The three-dimensional structure of Epstein-Barr virus genome varies by latency type and is regulated by PARP1 enzymatic activity.

Epstein-Barr virus (EBV) persists in human B-cells by maintaining its chromatinized episomes within the nucleus. We have previously shown that cellular factor Poly [ADP-ribose] polymerase 1 (PARP1) binds the EBV genome, stabilizes CTCF binding at specific loci, and that PARP1 enzymatic activity correlates with maintaining a transcriptionally active latency program. To better understand PARP1's role in regulating EBV latency, here we functionally characterize the effect of PARP enzymatic inhibition on episomal structure through in situ HiC mapping, generating a complete 3D structure of the EBV genome. We also map intragenomic contact changes after PARP inhibition to global binding of chromatin looping factors CTCF and cohesin across the EBV genome. We find that PARP inhibition leads to fewer total unique intragenomic interactions within the EBV episome, yet new chromatin loops distinct from the untreated episome are also formed. This study also illustrates that PARP inhibition alters gene expression at the regions where chromatin looping is most effected. We observe that PARP1 inhibition does not alter cohesin binding sites but does increase its frequency of binding at those sites. Taken together, these findings demonstrate that PARP has an essential role in regulating global EBV chromatin structure and latent gene expression.