Search

Two murine cDNAs (pMIF20/11 and pMIF3/10) coinduced with interferon in mouse cells infected with Newcastle disease virus (NDV) were identified previously. By genomic Southern blot analysis of hamster/mouse somatic cell hybrids, the gene hybridizing with pMIF20/11 has been localized on chromosome 12 and the gene hybridizing with pMIF3/10 on chromosome X.

Temperature-sensitive mutants of Escherichia coli K-12 which cannot form cell wall peptidoglycan at 42 C were isolated. The thermosensitive steps were characterized biochemically, and the genes coding the enzymes of peptidoglycan synthesis were mapped. These genes were in two clusters: one group, located at about 1.5 min between leu and azi, was designated as mra (murein a); the second group, located at about 77.5 min close to argH and metB, was designated as mrb (murein b, with the order metB-argH-mrb). No simple relations were found between the gene location and the order or localization of enzymes involved in the sequence of reactions of cell wall peptidoglycan biosynthesis.

Auxotrophs of Acinetobacter calcoaceticus blocked in each reaction of the synthetic pathway from chorismic acid to tryptophan were obtained after N-methyl-N'-nitro-N-nitrosoguanidine mutagenesis. One novel class was found to be blocked in both anthranilate and p-aminobenzoate synthesis; these mutants (trpG) require p-aminobenzoate or folate as well as tryptophan (or anthranilate) for growth. The loci of six other auxotrophic classes requiring only tryptophan were defined by growth, accumulation, and enzymatic analysis where appropriate. The trp mutations map in three chromosomal locations. One group contains trpC and trpD (indoleglycerol phosphate synthetase and phosphoribosyl transferase) in addition to trpG mutations; this group is closely linked to a locus conferring a glutamate requirement. Another cluster contains trpA and trpB, coding for the two tryptophan synthetase (EC 4.2.1.20) subunits, along with trpF (phosphoribosylanthranilate isomerase); this group is weakly linked to a his marker. The trpE gene, coding for the large subunit of anthranilate synthetase, is unlinked to any of the above. This chromosomal distribution of the trp genes has not been observed in other organisms.

Several diaminopimelic acid (DAP)- and lysine-requiring mutants of Escherichia coli were isolated and studied by genetic, physiological, and biochemical means. The genes concerned with DAP-lysine synthesis map at several different sites on the E. coli chromosome and, therefore, do not constitute a single operon. Three separate loci affecting DAP synthesis are located in the 0 to 2.5 min region of the genetic map. The order of the loci in this region is thr-dapB-pyrA-ara-leu-pan-dapC-tonA-dapD. Two additional DAP genes map in the region between min 47 and 48, with the gene order being gua-dapA-dapE-ctr. The lys locus at min 55 determines the synthesis of the enzyme DAP decarboxylase, which catalyzes the conversion of DAP into lysine. The order of the genes in this region is serA-lysA-thyA.

Background: Germin-like proteins (GLPs) are ubiquitous plant proteins, which play significant role in plant responses against various abiotic stresses. However, the potential functions of GLPs in rice (Oryza sativa) against salt and drought stress are still unclear., Methods and Results: In this study, transcriptional variation of eight OsGLP genes (OsGLP3-6, OsGLP4-1, OsGLP8-4, OsGLP8-7, OsGLP8-10, OsGLP8-11 and OsGLP8-12) was analyzed in leaves and roots of two economically important Indica rice cultivars, KS282 and Super Basmati, under salt and drought stress at early seedling stage. The relative expression analysis from qRT-PCR indicated the highest increase in expression of OsGLP3-6 in leaves and roots of both rice varieties with a significantly higher expression in KS282. Moreover, relative change in expression of OsGLP8-7, OsGLP8-10 and OsGLP8-11 under salt stress and OsGLP8-7 under drought stress was also commonly higher in leaves and roots of KS282 as compared to Super Basmati. Whereas, OsGLP3-7 and OsGLP8-12 after salt stress and OsGLP8-4 and OsGLP8-12 after drought stress were observed with higher relative expression in roots of Super Basmati than KS282. Importantly, the OsGLP3-6 and OsGLP4-1 from chromosome 3 and 4 respectively showed higher expression in leaves whereas most of the OsGLP genes from chromosome 8 exhibited higher expression in roots., Conclusion: Overall, as a result of this comparative analysis, OsGLP genes showed both general and specific expression profiles depending upon a specific rice variety, stress condition as well as tissue type. These results will increase our understanding of role of OsGLP genes in rice crop and provide useful information for the further in-depth research on their regulatory mechanisms in response to these stress conditions., (© 2021. The Author(s), under exclusive licence to Springer Nature B.V.)

The root system architecture is an important complex trait in rice. With changing climatic conditions and soil nutrient deficiencies, there is an immediate need to breed nutrient-use-efficient rice varieties with robust root system architectural (RSA) traits. To map the genomic regions associated with crucial component traits of RSA viz. root length and root volume, a biparental F 2 mapping population was developed using TI-128, an Ethyl Methane Sulphonate (EMS) mutant of a mega variety BPT-5204 having high root length (RL) and root volume (RV) with wild type BPT-5204. Extreme bulks having high RL and RV and low RL and RV were the whole genome re-sequenced along with parents. Genetic mapping using the MutMap QTL-Seq approach elucidated two genomic intervals on Chr.12 (3.14-3.74 Mb, 18.11-20.85 Mb), and on Chr.2 (23.18-23.68 Mb) as potential regions associated with both RL and RV. The Kompetitive Allele Specific PCR (KASP) assays for SNPs with delta SNP index near 1 were associated with higher RL and RV in the panel of sixty-two genotypes varying in root length and volume. The KASP_SNPs viz. Chr12_S4 (C→T; Chr12:3243938), located in the 3' UTR region of LOC_Os12g06670 encoding a protein kinase domain-containing protein and Chr2_S6 (C→T; Chr2:23181622) present upstream in the regulator of chromosomal condensation protein LOC_Os2g38350. Validation of these genes using qRT-PCR and in-silico studies using various online tools and databases revealed higher expression in TI-128 as compared to BPT- 5204 at the seedling and panicle initiation stages implying the functional role in enhancing RL and RV., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Masson SAS. All rights reserved.)

Introduction: Peanut is susceptible to infection of Aspergillus fungi and conducive to aflatoxin contamination, hence developing aflatoxin-resistant variety is highly meaningful. Identifying functional genes or loci conferring aflatoxin resistance and molecular diagnostic marker are crucial for peanut breeding., Objectives: This work aims to (1) identify candidate gene for aflatoxin production resistance, (2) reveal the related resistance mechanism, and (3) develop diagnostic marker for resistance breeding program., Methods: Resistance to aflatoxin production in a recombined inbred line (RIL) population derived from a high-yielding variety Xuhua13 crossed with an aflatoxin-resistant genotype Zhonghua 6 was evaluated under artificial inoculation for three consecutive years. Both genetic linkage analysis and QTL-seq were conducted for QTL mapping. The candidate gene was further fine-mapped using a secondary segregation mapping population and validated by transgenic experiments. RNA-Seq analysis among resistant and susceptible RILs was used to reveal the resistance pathway for the candidate genes., Results: The major effect QTL qAFTRA07.1 for aflatoxin production resistance was mapped to a 1.98 Mbp interval. A gene, AhAftr1 (Arachis hypogaea Aflatoxin resistance 1), was detected structure variation (SV) in leucine rich repeat (LRR) domain of its production, and involved in disease resistance response through the effector-triggered immunity (ETI) pathway. Transgenic plants with overexpression of AhAftr1 (ZH6) exhibited 57.3% aflatoxin reduction compared to that of AhAftr1 (XH13) . A molecular diagnostic marker AFTR.Del.A07 was developed based on the SV. Thirty-six lines, with aflatoxin content decrease by over 77.67% compared to the susceptible control Zhonghua12 (ZH12), were identified from a panel of peanut germplasm accessions and breeding lines through using AFTR.Del.A07., Conclusion: Our findings would provide insights of aflatoxin production resistance mechanisms and laid meaningful foundation for further breeding programs., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Production and hosting by Elsevier B.V.)

Sweetpotato, Ipomoea batatas (L.) Lam., is an important worldwide crop used as feed, food, and fuel. However, its polyploidy, high heterozygosity and self-incompatibility makes it difficult to study its genetics and genomics. Longest vine length (LVL), yield per plant (YPP), dry matter content (DMC), starch content (SC), soluble sugar content (SSC), and carotenoid content (CC) are some of the major agronomic traits being used to evaluate sweetpotato. However limited research has actually examined how these traits are inherited. Therefore, after selecting 212 F 1 from a Xin24 × Yushu10 crossing as the mapping population, this study applied specific-locus amplified fragment sequencing (SLAF-seq), at an average sequencing depth of 26.73 × (parents) and 52.25 × (progeny), to detect single nucleotide polymorphisms (SNPs). This approach generated an integrated genetic map of length 2441.56 cM and a mean distance of 0.51 cM between adjacent markers, encompassing 15 linkage groups (LGs). Based on the linkage map, 26 quantitative trait loci (QTLs), comprising six QTLs for LVL, six QTLs for YPP, ten QTLs for DMC, one QTL for SC, one QTL for SSC, and two QTLs for CC, were identified. Each of these QTLs explained 6.3-10% of the phenotypic variation. It is expected that the findings will be of benefit for marker-assisted breeding and gene cloning of sweetpotato., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Masson SAS. All rights reserved.)

Tobacco is an economically significant industrial crop and model plant for genetic research, yet little is known about its genetic architecture. Quantitative trait loci (QTL) analysis was performed for six agronomic traits on an F_7 population of 341 genotypes, parents, and F 1 plants using 1974 SSR markers across two environments. 31 QTLs contributing single-locus additive effects on 13 linkage groups (LGs) and 6 QTL pairs contributing epistatic effects on 6 LGs, were detected by the QTLNetwork 2.0 which was developed for the mixed-linear-model-based composite interval mapping (MCIM). Notably, 5 QTLs and 1 epistatic QTL pair were found to have pleiotropic effects on some genetically related traits. Moreover, the Broad sense heritability of the detected QTLs ranged from 1.05% to 43.33%, while genotype-by-environment interaction heritability spanned from 27.09% to 56.25%. Based on the results of QTL mapping, the potential superior lines for all or specific environments were designed and evaluated. Five major QTLs were finely dissected based on the tobacco reference genome of K326, and 31 candidate genes were predicted. This study offered new insights into the complicated genetic architecture and QTL resources for efficient breeding design for genetic improvement of agronomic traits in tobacco., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Genome Mapping Technologies (optical and electronic) use ultra-high molecular weight DNA to detect structural variation and have application in constitutional genetic disorders, hematological neoplasms, and solid tumors. Genome mapping can detect balanced and unbalanced structural variation, copy number changes, and haplotypes. The technique is analogous to chromosomal microarray analysis, although genome mapping has the added benefit of being able to detect and ascertain the nature of more abnormalities in a single assay than array, karyotyping, or FISH alone., Key Messages: This paper describes a specific nomenclature for genome mapping that can be used by diagnostic and research centers to report their findings accurately. An international nomenclature is essential for patient results to be understood by different healthcare providers as well as for clear communication in publications and consistency in databases., Summary: Genome mapping can detect aneuploidy, balanced and unbalanced structural variation, as well as copy number changes. The Standing Committee for the International System for Human Cytogenomic Nomenclature (ISCN) recognised there was a need for a specific nomenclature for genome mapping that encompasses the range of abnormalities detected by this technique. This paper explains the general principles of the nomenclature as well as giving specific ISCN examples for the different types of numerical and structural rearrangements., (© 2024 S. Karger AG, Basel.)

Single-cell sequencing provides a new level of granularity in studying the heterogeneous nature of cancer cells. For some cancers, this heterogeneity is the result of copy number changes of genes within the cellular genomes. The ability to accurately determine such copy number changes is critical in tracing and understanding tumorigenesis. Current single-cell genome sequencing methodologies infer copy numbers based on statistical approaches followed by rounding decimal numbers to integer values. Such methodologies are sample dependent, have varying calling sensitivities which heavily depend on the sample's ploidy and are sensitive to noise in sequencing data. In this paper we have demonstrated the concept of integer-counting by using a novel bioinformatic algorithm built on our library construction chemistry in order to detect the discrete nature of the genome., (© 2021. The Author(s).)

Choroidal neovascularization (CNV) is a type of eye disease that can cause vision loss. In recent years, many studies have attempted to investigate the major pathological processes and molecular pathogenic mechanisms of CNV. Because many diseases are related to genes, the genes associated with CNV need to be identified. In this study, we proposed a network-based approach for identifying novel CNV-associated genes. To execute such method, we first employed a protein-protein interaction network reported in STRING. Then, we applied a network diffusion algorithm, Laplacian heat diffusion, on this network by selecting validated CNV-related genes as the seed nodes. As a result, some novel genes that had unknown but strong relationships with validated genes were identified. Furthermore, we used a screening procedure to extract the most essential genes. Eleven latent CNV-related genes were finally obtained. Extensive analyses were performed to confirm that these genes are novel CNV-related genes., Competing Interests: The authors declare that there is no conflict of interest regarding the publication of this paper., (Copyright © 2021 Minjie Sheng et al.)

The increasingly serious problem of traffic congestion has become a critical issue that urban managers need to focus on. However, as urban scale and structure have already taken shape, the use of existing road resources to achieve effective route selection for vehicles is the key to solving this traffic congestion problem. Existing research has mainly focused on the following three points: (1) algorithms for controlling traffic signal lamp period at single intersections; (2) route recommendation algorithms for a single vehicle; and (3) route recommendation algorithms based on the traffic history experienced by a vehicle. These studies, however, have the following limitations: (1) the evaluation factor is singular, and therefore, cannot fully express the advantages and disadvantages of the route selection method; (2) real-time route selection is absent; (3) route selection for a single vehicle is ineffective in avoiding local congestion. In view of these problems, this paper proposes an improved quantum genetic algorithm (IQGA) to solve the problem of traffic congestion in route selection. The algorithm includes the following: (1) proposing a quantum chromosome initialization strategy (QCIS) to convert and code real traffic conditions and to construct quantum chromosomes based on the quantum coding for vehicles and roads; (2) proposing a quantum chromosome mapping algorithm (QCMA) to transform the calculation bits of quantum chromosomes into the results of route selection for different vehicles; (3) proposing a contemporary optimal solution decision strategy (COSDS) to judge the current route selection results; (4) proposing a quantum update algorithm (QUA) to update and iterate the quantum coding of the population. Two types of experiments were conducted in this study: (1) Artificial traffic networks with different scales were designed to carry out comparative experiments between IQGA and other algorithms. The experimental results show that IGQA has better robustness and adaptive ability. (2) Comparative experiments on an actual urban traffic network verified the high-performance and real-time performance capabilities of IQGA. [ABSTRACT FROM AUTHOR]

Genetic maps order genetic markers along chromosomes. They are, for instance, extensively used in marker-assisted selection to accelerate breeding programs. Even for the same species, people often have to deal with several alternative maps obtained using different ordering methods or different datasets, e.g. resulting from different segregating populations. Having efficient tools to identify the consistency and discrepancy of alternative maps is thus essential to facilitate genetic map comparisons. We propose to encode genetic maps by bucket order, a kind of order, which takes into account the blurred parts of the marker order while being an efficient data structure to achieve low complexity algorithms. The main result of this paper is an O(n log(n)) procedure to identify the largest agreements between two bucket orders of n elements, their Longest Common Subsequence (LCS), providing an efficient solution to highlight discrepancies between two genetic maps. The LCS of two maps, being the largest set of their collinear markers, is used as a building block to compute pairwise map congruence, to visually emphasize maker collinearity and in some scaffolding methods relying on genetic maps to improve genome assembly. As the LCS computation is a key subroutine of all these genetic map related tools, replacing the current LCS subroutine of those methods by ours –to do the exact same work but faster– could significantly speed up those methods without changing their accuracy. To ease such transition we provide all required algorithmic details in this self contained paper as well as an R package implementing them, named LCSLCIS, which is freely available at: . [ABSTRACT FROM AUTHOR]

Key Message: This paper reports fine mapping of qCLS for resistance to Cercospora leaf spot disease in mungbean and identified LOC106765332encoding TATA-binding-protein-associated factor 5 (TAF5) as the candidate gene for the resistance Cercospora leaf spot (CLS) caused by the fungus Cercospora canescens is an important disease of mungbean. A QTL mapping using mungbean F 2 and BC 1 F 1 populations developed from the "V4718" (resistant) and "Kamphaeng Saen 1" (KPS1; susceptible) has identified a major QTL controlling CLS resistance (qCLS). In this study, we finely mapped the qCLS and identified candidate genes at this locus. A BC 8 F 2 [KPS1 × (KPS1 × V4718)] population developed in this study and the F 2 (KPS1 × V4718) population used in a previous study were genotyped with 16 newly developed SSR markers. QTL analysis in the BC 8 F 2 and F 2 populations consistently showed that the qCLS was mapped to a genomic region of ~ 13 Kb on chromosome 6, which contains only one annotated gene, LOC106765332 (designated "VrTAF5"), encoding TATA-binding-protein-associated factor 5 (TAF5), a subunit of transcription initiation factor IID and Spt-Ada-Gcn5 acetyltransferase complexes. Sequence comparison of VrTAF5 between KPS1 and V4718 revealed many single nucleotide polymorphisms (SNPs) and inserts/deletions (InDels) in which eight SNPs presented in eight different exons, and an SNP (G4,932C) residing in exon 8 causes amino acid change (S250T) in V4718. An InDel marker was developed to detect a 24-bp InDel polymorphism in VrTAF5 between KPS1 and V4718. Analysis by RT-qPCR showed that expression levels of VrTAF5 in KPS1 and V4718 were not statistically different. These results indicated that mutation in VrTAF5 causing an amino acid change in the VrTAF5 protein is responsible for CLS resistance in V4718.

Background: Cohen syndrome (CS) is a rare multi-system autosomal recessive disorder with a high prevalence in the Finnish population. Clinical features of Finnish-type CS are homogeneous, however, in non-Finnish populations, CS diagnosis is challenging due to broad phenotypic variability., Methods: We studied a consanguineous family having three affected individuals with clinical features of severe intellectual disability and global developmental delay. Clinical diagnosis of the phenotype could not be established based on the features. Therefore, whole genome SNP genotyping and whole exome sequencing (WES) were performed on DNA samples from affected and unaffected family members., Results: Homozygosity mapping identified a shared loss of heterozygosity region on chromosome 8q22.1-q22.3 and WES data analysis revealed an insertion-deletion (indel) mutation (c.11519_11521delCAAinsT) in the VPS13B gene. The indel is predicted to cause a frameshift resulting in a premature termination of the VPS13B protein (NP_060360.3:p.Pro3840Leufs*2)., Conclusion: VPS13B encodes a giant transmembrane protein called vacuolar protein sorting 13 homolog B. VPS13B is known to play a role in the glycosylation of Golgi proteins and in endosomal-lysosomal trafficking. Moreover, it is thought to function in vesicle mediated transport and sorting of proteins within the cell. The mechanism by which abnormalities of the VPS13B protein lead to the phenotype of CS is currently unknown. Here, in this study, we successfully established a clinical diagnosis of CS cases from a family using genomic analyses. Clinical re-examination of the patients revealed characteristic ocular abnormalities., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.)

Key Message: This study uses simulations to explore statistical power and false-positive rates for eQTL mapping in allopolyploid organisms and provides guidelines to apply eQTL mapping in these organisms. In recent years, RNA-seq has become the dominant technology for eQTL studies. However, most work has been in diploid organisms. Many species of economic and environmental importance are polyploid, and approaches for eQTL mapping in polyploids are not well developed. High similarity between duplicated genes in polyploids will cause misassignment of sequence reads and may cause false-positive results and/or lack of power to detect eQTL. In this paper, we first explore the similarity of homoeologous transcripts in polyploid organisms. We find that 5-20% of genes (varying with organism) in important agricultural plants such as wheat, soybean, and switchgrass are not sufficiently diverged between duplicated genomes to allow unambiguous assignment of reads. Second, we examine the impact of misassigned reads on eQTL mapping and show that both false-positive and false-negative rates can be greatly inflated. Third, we compare four strategies for dealing with ambiguous reads: (1) dividing ambiguous reads evenly between homoeologous transcripts, (2) assigning them proportionally, (3) using all reads for all genes, and (4) discarding ambiguous reads. We find that the strategy of discarding ambiguous reads gives the best balance of false-positive and false-negative rates for most genes. However, for genes that are very similar between genomes, using all reads is the only choice. This leads to reduced power, but false-positive rates will be maintained. We also discuss QTL mapping in polyploids using allele-specific expression (ASE) and show how the proportion of ASE-informative reads varies according to the divergence between homoeologous genes.

Sporotrichosis is a chronic subcutaneous mycosis caused by Sporothrix species, of which the main aetiological agents are S. brasiliensis, S. schenckii, and S. globosa. Infection occurs after a traumatic inoculation of Sporothrix propagules in mammals' skin and can follow either a classic route through traumatic inoculation by plant debris (e.g., S. schenckii and S. globosa) or an alternative route through zoonotic transmission from animals (e.g., S. brasiliensis). Epizootics followed by a zoonotic route occur in Brazil, with Rio de Janeiro as the epicenter of a recent cat-transmitted epidemic. DNA-based markers are needed to explore the epidemiology of these Sporothrix expansions using molecular methods. This paper reports the use of amplified-fragment-length polymorphisms (AFLP) to assess the degree of intraspecific variability among Sporothrix species. We used whole-genome sequences from Sporothrix species to generate 2,304 virtual AFLP fingerprints. In silico screening highlighted 6 primer pair combinations to be tested in vitro. The protocol was used to genotype 27 medically relevant Sporothrix. Based on the overall scored AFLP markers (97-137 fragments), the values of polymorphism information content (PIC = 0.2552-0.3113), marker index (MI = 0.002-0.0039), effective multiplex ratio (E = 17.8519-35.2222), resolving power (Rp = 33.6296-63.1852), discriminating power (D = 0.9291-0.9662), expected heterozygosity (H = 0.3003-0.3857), and mean heterozygosity (Havp = 0.0001) demonstrated the utility of these primer combinations for discriminating Sporothrix. AFLP markers revealed cryptic diversity in species previously thought to be the most prevalent clonal type, such as S. brasiliensis, responsible for cat-transmitted sporotrichosis, and S. globosa responsible for large sapronosis outbreaks in Asia. Three combinations (#3 EcoRI-FAM-GA/MseI-TT, #5 EcoRI-FAM-GA/MseI-AG, and #6 EcoRI-FAM-TA/MseI-AA) provide the best diversity indices and lowest error rates. These methods make it easier to track routes of disease transmission during epizooties and zoonosis, and our DNA fingerprint assay can be further transferred between laboratories to give insights into the ecology and evolution of pathogenic Sporothrix species and to inform management and mitigation strategies to tackle the advance of sporotrichosis., Competing Interests: The authors have declared that no competing interests exist.

Social insect colonies exhibit colony-level phenotypes such as social immunity and task coordination, which are produced by the individual phenotypes. Mapping the genetic basis of such phenotypes requires associating the colony-level phenotype with the genotypes in the colony. In this paper, we examine alternative approaches to DNA extraction, library construction, and sequencing for genome wide association studies (GWAS) of colony-level traits using a population sample of Cataglyphis niger ants. We evaluate the accuracy of allele frequency estimation from sequencing a pool of individuals (pool-seq) from each colony using either whole-genome sequencing or reduced representation genomic sequencing. Based on empirical measurement of the experimental noise in sequenced DNA pools, we show that reduced representation pool-seq is drastically less accurate than whole-genome pool-seq. Surprisingly, normalized pooling of samples did not result in greater accuracy than un-normalized pooling. Subsequently, we evaluate the power of the alternative approaches for detecting quantitative trait loci (QTL) of colony-level traits by using simulations that account for an environmental effect on the phenotype. Our results can inform experimental designs and enable optimizing the power of GWAS depending on budget, availability of samples and research goals. We conclude that for a given budget, sequencing un-normalized pools of individuals from each colony provides optimal QTL detection power., Competing Interests: The authors have declared that no competing interests exist.

Background: The genome architecture mapping (GAM) technique can capture genome-wide chromatin interactions. However, besides the known systematic biases in the raw GAM data, we have found a new type of systematic bias. It is necessary to develop and evaluate effective normalization methods to remove all systematic biases in the raw GAM data., Results: We have detected a new type of systematic bias, the fragment length bias, in the genome architecture mapping (GAM) data, which is significantly different from the bias of window detection frequency previously mentioned in the paper introducing the GAM method but is similar to the bias of distances between restriction sites existing in raw Hi-C data. We have found that the normalization method (a normalized variant of the linkage disequilibrium) used in the GAM paper is not able to effectively eliminate the new fragment length bias at 1 Mb resolution (slightly better at 30 kb resolution). We have developed an R package named normGAM for eliminating the new fragment length bias together with the other three biases existing in raw GAM data, which are the biases related to window detection frequency, mappability, and GC content. Five normalization methods have been implemented and included in the R package including Knight-Ruiz 2-norm (KR2, newly designed by us), normalized linkage disequilibrium (NLD), vanilla coverage (VC), sequential component normalization (SCN), and iterative correction and eigenvector decomposition (ICE)., Conclusions: Based on our evaluations, the five normalization methods can eliminate the four biases existing in raw GAM data, with VC and KR2 performing better than the others. We have observed that the KR2-normalized GAM data have a higher correlation with the KR-normalized Hi-C data on the same cell samples indicating that the KR-related methods are better than the others for keeping the consistency between the GAM and Hi-C experiments. Compared with the raw GAM data, the normalized GAM data are more consistent with the normalized distances from the fluorescence in situ hybridization (FISH) experiments. The source code of normGAM can be freely downloaded from http://dna.cs.miami.edu/normGAM/.

Construction of genetic linkage maps has become a routine step for mapping quantitative trait loci (QTL), particularly in animal and plant breeding populations. Many multiparental populations have recently been produced to increase genetic diversity and QTL mapping resolution. However, few software packages are available for map construction in these populations. In this paper, we build a general framework for the construction of genetic linkage maps from genotypic data in diploid populations, including bi- and multiparental populations, cross-pollinated (CP) populations, and breeding pedigrees. The framework is implemented as an automatic pipeline called magicMap, where the maximum multilocus likelihood approach utilizes genotypic information efficiently. We evaluate magicMap by extensive simulations and eight real datasets: one biparental, one CP, four multiparent advanced generation intercross (MAGIC), and two nested association mapping (NAM) populations, the number of markers ranging from a few hundred to tens of thousands. Not only is magicMap the only software capable of accommodating all of these designs, it is more accurate and robust to missing genotypes and genotyping errors than commonly used packages., (Copyright © 2019 by the Genetics Society of America.)

Background: Functional antibody genes are often assembled by VDJ recombination and then diversified by somatic hypermutation. Identifying the combination of sourcing germline genes is critical to understand the process of antibody maturation, which may facilitate the diagnostics and rapid generation of human monoclonal antibodies in therapeutics. Despite of successful efforts in V and J fragment assignment, method in D segment tracing remains weak for immunoglobulin heavy diversity (IGHD)., Results: In this paper, we presented a D-sensitive mapping method called DSab-origin with accuracies around 90% in human monoclonal antibody data and average 95.8% in mouse data. Besides, DSab-origin achieved the best performance in holistic prediction of VDJ segments assignment comparing with other methods commonly used in simulation data. After that, an application example was explored on the antibody response based on a time-series antibody sequencing data after influenza vaccination. The result indicated that, despite the personal response among different donors, IGHV3-7 and IGHD4-17 were likely to be dominated gene segments in these three donors., Conclusions: This work filled in a computational gap in D segment assignment for VDJ germline gene identification in antibody research. And it offered an application example of DSab-origin for studying the antibody maturation process after influenza vaccination.

Background: Genome rearrangements describe changes in the genetic linkage relationship of large chromosomal regions, involving reversals, transpositions, block interchanges, deletions, insertions, fissions, fusions and translocations etc. Many algorithms for calculating rearrangement scenarios between two genomes have been proposed. Very often, the calculated rearrangement scenario is not unique for the same pair of permutations. Hence, how to decide which calculated rearrangement scenario is more biologically meaningful becomes an essential task. Up to now, several mechanisms for genome rearrangements have been studied. One important theory is that genome rearrangement may be mediated by repeats, especially for reversal events. Many reversal regions are found to be flanked by a pair of inverted repeats. As a result, whether there are repeats at the breakpoints of the calculated rearrangement events can shed a light on deciding whether the calculated rearrangement events is biologically meaningful. To our knowledge, there is no tool which can automatically identify rearrangement events and check whether there exist repeats at the breakpoints of each calculated rearrangement event., Results: In this paper, we describe a new tool named GRSR which allows us to compare multiple unichromosomal genomes to identify "independent" (obvious) rearrangement events such as reversals, (inverted) block interchanges and (inverted) transpositions and automatically searches for repeats at the breakpoints of each rearrangement event. We apply our tool on the complete genomes of 28 Mycobacterium tuberculosis strains and 24 Shewanella strains respectively. In both Mycobacterium tuberculosis and Shewanella strains, our tool finds many reversal regions flanked by a pair of inverted repeats. In particular, the GRSR tool also finds an inverted transposition and an inverted block interchange in Shewanella, where the repeats at the ends of rearrangement regions remain unchanged after the rearrangement event. To our knowledge, this is the first time such a phenomenon for inverted transposition and inverted block interchange is reported in Shewanella., Conclusions: From the calculated results, there are many examples supporting the theory that the existence of repeats at the breakpoints of a rearrangement event can make the sequences at the breakpoints remain unchanged before and after the rearrangement events, suggesting that the conservation of ends could possibly be a popular phenomenon in many types of genome rearrangement events.

Assembly of reference-quality genomes from next-generation sequencing data is a key challenge in genomics. Recently, we and others have shown that Hi-C data can be used to address several outstanding challenges in the field of genome assembly. This principle has since been developed in academia and industry, and has been used in the assembly of several major genomes. In this paper, we explore the central principles underlying Hi-C-based assembly approaches, by quantitatively defining and characterizing three invariant Hi-C interaction patterns on which these approaches can build: Intrachromosomal interaction enrichment, distance-dependent interaction decay and local interaction smoothness. Specifically, we evaluate to what degree each invariant pattern holds on a single locus level in different species, cell types and Hi-C map resolutions. We find that these patterns are generally consistent across species and cell types but are affected by sequencing depth, and that matrix balancing improves consistency of loci with all three invariant patterns. Finally, we overview current Hi-C-based assembly approaches in light of these invariant patterns and demonstrate how local interaction smoothness can be used to easily detect scaffolding errors in extremely sparse Hi-C maps. We suggest that simultaneously considering all three invariant patterns may lead to better Hi-C-based genome assembly methods., (Copyright © 2018 Elsevier Inc. All rights reserved.)

The field of 3D genomics grew at increasing rates in the last decade. The volume and complexity of 2D and 3D data produced is progressively outpacing the capacities of the technology previously used for distributing genome sequences. The emergence of new technologies provides also novel opportunities for the development of innovative approaches. In this paper, we review the state-of-the-art computing technology, as well as the solutions adopted by the platforms currently available., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Motivation: Bulked segregant analysis combined with next generation sequencing has proven to be a simple and efficient approach for fast mapping of quantitative trait loci (QTLs). However, how to estimate the proportion of phenotypic variance explained by a QTL (or termed QTL heritability) in such pooled QTL mapping is an unsolved problem., Results: In this paper, we propose a method called PQHE to estimate QTL heritability using pooled sequencing data obtained under different experimental designs. Simulation studies indicated that our method is correct and feasible. Four practical examples from rice and yeast are demonstrated, each representing a different situation., Availability and Implementation: The R scripts of our method are open source under GPLv3 license at http://genetics.fafu.edu.cn/PQHE or https://github.com/biotangweiqi/PQHE. The R scripts require the R package rootSolve., Contact: wuwr@fafu.edu.cn., Supplementary Information: Supplementary data are available at Bioinformatics online.

The analysis of quantitative trait loci (QTLs) aims at mapping and estimating the positions and effects of the genes that may affect the quantitative trait, and evaluating the relationship between the gene variation and the phenotype. In existing studies, most methods mainly focus on the association/linkage between multiple gene loci and one trait, in which some useful joint information of multiple traits may be ignored. In this paper, we proposed a method of simultaneously estimating all QTL parameters in the framework of multiple-trait multiple-interval mapping. Simulation results show that in accuracy aspect, the proposed method outperforms an existing method for mapping multiple traits. A real example is also provided to validate the performance of the new method.

Background: The use of artificial data to evaluate the performance of aligners and peak callers not only improves its accuracy and reliability, but also makes it possible to reduce the computational time. One of the natural ways to achieve such time reduction is by mapping a single chromosome., Results: We investigated whether a single chromosome mapping causes any artefacts in the alignments' performances. In this paper, we compared the accuracy of the performance of seven aligners on well-controlled simulated benchmark data which was sampled from a single chromosome and also from a whole genome. We found that commonly used statistical methods are insufficient to evaluate an aligner performance, and applied a novel measure of a read density distribution similarity, which allowed to reveal artefacts in aligners' performances. We also calculated some interesting mismatch statistics, and constructed mismatch frequency distributions along the read., Conclusions: The generation of artificial data by mapping of reads generated from a single chromosome to a reference chromosome is justified from the point of view of reducing the benchmarking time. The proposed quality assessment method allows to identify the inherent shortcoming of aligners that are not detected by conventional statistical methods, and can affect the quality of alignment of real data.

Multiparent populations (MPP) have become popular resources for complex trait mapping because of their wider allelic diversity and larger population size compared with traditional two-way recombinant inbred (RI) strains. In mice, the collaborative cross (CC) is one of the most popular MPP and is derived from eight genetically diverse inbred founder strains. The strategy of generating RI intercrosses (RIX) from MPP in general and from the CC in particular can produce a large number of completely reproducible heterozygote genomes that better represent the (outbred) human population. Since both maternal and paternal haplotypes of each RIX are readily available, RIX is a powerful resource for studying both standing genetic and epigenetic variations of complex traits, in particular, the parent-of-origin (PoO) effects, which are important contributors to many complex traits. Furthermore, most complex traits are affected by >1 genes, where multiple quantitative trait locus mapping could be more advantageous. In this paper, for MPP-RIX data but taking CC-RIX as a working example, we propose a general Bayesian variable selection procedure to simultaneously search for multiple genes with founder allelic effects and PoO effects. The proposed model respects the complex relationship among RIX samples, and the performance of the proposed method is examined by extensive simulations., (Copyright © 2018 Liu et al.)

One goal of modern day neuroscience is the establishment of molecular maps that assign unique features to individual neuron types. Such maps provide important starting points for neuron classification, for functional analysis, and for developmental studies aimed at defining the molecular mechanisms of neuron identity acquisition and neuron identity diversification. In this resource paper, we describe a nervous system-wide map of the potential expression sites of 244 members of the largest gene family in the C. elegans genome, rhodopsin-like (class A) G-protein-coupled receptor (GPCR) chemoreceptors, using classic gfp reporter gene technology. We cover representatives of all sequence families of chemoreceptor GPCRs, some of which were previously entirely uncharacterized. Most reporters are expressed in a very restricted number of cells, often just in single cells. We assign GPCR reporter expression to all but two of the 37 sensory neuron classes of the sex-shared, core nervous system. Some sensory neurons express a very small number of receptors, while others, particularly nociceptive neurons, coexpress several dozen GPCR reporter genes. GPCR reporters are also expressed in a wide range of inter- and motorneurons, as well as non-neuronal cells, suggesting that GPCRs may constitute receptors not just for environmental signals, but also for internal cues. We observe only one notable, frequent association of coexpression patterns, namely in one nociceptive amphid (ASH) and two nociceptive phasmid sensory neurons (PHA, PHB). We identified GPCRs with sexually dimorphic expression and several GPCR reporters that are expressed in a left/right asymmetric manner. We identified a substantial degree of GPCR expression plasticity; particularly in the context of the environmentally-induced dauer diapause stage when one third of all tested GPCRs alter the cellular specificity of their expression within and outside the nervous system. Intriguingly, in a number of cases, the dauer-specific alterations of GPCR reporter expression in specific neuron classes are maintained during postdauer life and in some case new patterns are induced post-dauer, demonstrating that GPCR gene expression may serve as traits of life history. Taken together, our resource provides an entry point for functional studies and also offers a host of molecular markers for studying molecular patterning and plasticity of the nervous system.

In the present paper, karyotypes of 7 Japanese Podismini species, Anapodisma beybienkoi, Fruhstorferiola okinawaensis, Parapodisma caelestis, P. mikado, P. setouchiensis, P. tenryuensis, and Sinopodisma punctata (2n♂ = 21, all acrocentric), are described and compared on the basis of conventional (C-banding, DAPI/CMA3-staining, Ag-NOR) and molecular (FISH with 18S rDNA and telomeric probes) cytogenetic staining methods. This is the first study to report karyotypes of A. beybienkoi and P. caelestis. Differential staining techniques showed karyotypic diversity in these species. The number of 18S rDNA signals ranged from 2 to 6, and the signals were located on the autosomes or sex chromosomes. In all species, clusters of rDNA coincided with Ag-NORs. Telomeric signals occurred at the chromosome ends at the pachytene stage and seldom at other stages of meiosis. Paracentromeric and some distal and interstitial blocks of constitutive heterochromatin were detected in the chromosomes of Anapodisma, Fruhstorferiola, and Parapodisma species. Staining with DAPI and CMA3 revealed 2 groups of heterochromatin composition. In addition, intraspecific differences in the number of rDNA clusters and C-bands were observed within Parapodisma species. Based on the evidence of cytogenetic characteristics, the monophyly of Tonkinacridina cannot be supported., (© 2018 S. Karger AG, Basel.)

Genome-wide association studies have discovered a large number of genetic variants associated with complex diseases such as Alzheimer's disease. However, the genetic background of such diseases is largely unknown due to the complex mechanisms underlying genetic effects on traits, as well as a small sample size (e.g., 1000) and a large number of genetic variants (e.g., 1 million). Fortunately, datasets that contain genotypes, transcripts, and phenotypes are becoming more readily available, creating new opportunities for detecting disease-associated genetic variants. In this paper, we present a novel approach called "Backward Three-way Association Mapping" (BTAM) for detecting three-way associations among genotypes, transcripts, and phenotypes. Assuming that genotypes affect transcript levels, which in turn affect phenotypes, we first find transcripts associated with the phenotypes, and then find genotypes associated with the chosen transcripts. The backward ordering of association mappings allows us to avoid a large number of association testings between all genotypes and all transcripts, making it possible to identify three-way associations with a small computational cost. In our simulation study, we demonstrate that BTAM significantly improves the statistical power over "forward" three-way association mapping that finds genotypes associated with both transcripts and phenotypes and genotype-phenotype association mapping. Furthermore, we apply BTAM on an Alzheimer's disease dataset and report top 10 genotype-transcript-phenotype associations., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Hi-C experiments generate data in form of large genome contact maps (Hi-C maps). These show that chromosomes are arranged in a hierarchy of three-dimensional compartments. But to understand how these compartments form and by how much they affect genetic processes such as gene regulation, biologists and bioinformaticians need efficient tools to visualize and analyze Hi-C data. However, this is technically challenging because these maps are big. In this paper, we remedied this problem, partly by implementing an efficient file format and developed the genome contact map explorer platform. Apart from tools to process Hi-C data, such as normalization methods and a programmable interface, we made a graphical interface that let users browse, scroll and zoom Hi-C maps to visually search for patterns in the Hi-C data. In the software, it is also possible to browse several maps simultaneously and plot related genomic data. The software is openly accessible to the scientific community., (© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Genomic information has become a ubiquitous and almost essential aspect of biological research. Over the last 10-15 years, the cost of generating sequence data from DNA or RNA samples has dramatically declined and our ability to interpret those data increased just as remarkably. Although it is still possible for biologists to conduct interesting and valuable research on species for which genomic data are not available, the impact of having access to a high quality whole genome reference assembly for a given species is nothing short of transformational. Research on a species for which we have no DNA or RNA sequence data is restricted in fundamental ways. In contrast, even access to an initial draft quality genome (see below for definitions) opens a wide range of opportunities that are simply not available without that reference genome assembly. Although a complete discussion of the impact of genome sequencing and assembly is beyond the scope of this short paper, the goal of this review is to summarize the most common and highest impact contributions that whole genome sequencing and assembly has had on comparative and evolutionary biology., (Copyright © 2016. Published by Elsevier Inc.)

This paper addresses the problem of accounting for confounding factors and expression quantitative trait loci (eQTL) mapping in the study of SNP-gene associations. The existing convex penalty based algorithm has limited capacity to keep main information of matrix in the process of reducing matrix rank. We present an algorithm, which use nonconvex penalty based low-rank representation to account for confounding factors and make use of sparse regression for eQTL mapping (NCLRS). The efficiency of the presented algorithm is evaluated by comparing the results of 18 synthetic datasets given by NCLRS and presented algorithm, respectively. The experimental results or biological dataset show that our approach is an effective tool to account for non-genetic effects than currently existing methods.

High-throughput chromosome-conformation-capture (Hi-C) methods have revealed a multitude of structural insights into interphase chromosomes. In this paper, we elucidate the spatial clusters of genomic regions from Hi-C contact maps by formulating the underlying problem as a global optimization problem. Given its nonconvex objective and nonnegativity constraints, we implement several evolutionary algorithms and compare their performance with non-negative matrix factorization, revealing novel insights into the problem. In order to obtain robust and accurate spatial clusters, we propose and describe a novel hybrid differential evolution algorithm called HiCDE, which adopts non-negative matrix factorization as local search according to each candidate individual provided by differential evolution algorithm. Based on the fitness value of each individual, the population is partitioned into three subpopulations with different sizes; each subpopulation is equipped with a specific mutation strategy for either exploitation or exploration. Finally, all control parameters in the pool have equal probability to be selected for generating trial vectors. The effectiveness and robustness of HiCDE are supported by real-world performance benchmarking on chromosome-wide Hi-C contact maps of yeast and human, time complexity analysis, convergence analysis, parameter analysis, and case studies.

Our understanding of how chromosomes structurally organize and dynamically interact has been revolutionized through the lens of long-chain polymer physics. Major protein contributors to chromosome structure and dynamics are condensin and cohesin that stochastically generate loops within and between chains, and entrap proximal strands of sister chromatids. In this paper, we explore the ability of transient, protein-mediated, gene-gene crosslinks to induce clusters of genes, thereby dynamic architecture, within the highly repeated ribosomal DNA that comprises the nucleolus of budding yeast. We implement three approaches: live cell microscopy; computational modeling of the full genome during G1 in budding yeast, exploring four decades of timescales for transient crosslinks between 5kbp domains (genes) in the nucleolus on Chromosome XII; and, temporal network models with automated community (cluster) detection algorithms applied to the full range of 4D modeling datasets. The data analysis tools detect and track gene clusters, their size, number, persistence time, and their plasticity (deformation). Of biological significance, our analysis reveals an optimal mean crosslink lifetime that promotes pairwise and cluster gene interactions through “flexible” clustering. In this state, large gene clusters self-assemble yet frequently interact (merge and separate), marked by gene exchanges between clusters, which in turn maximizes global gene interactions in the nucleolus. This regime stands between two limiting cases each with far less global gene interactions: with shorter crosslink lifetimes, “rigid” clustering emerges with clusters that interact infrequently; with longer crosslink lifetimes, there is a dissolution of clusters. These observations are compared with imaging experiments on a normal yeast strain and two condensin-modified mutant cell strains. We apply the same image analysis pipeline to the experimental and simulated datasets, providing support for the modeling predictions. [ABSTRACT FROM AUTHOR]

Estimating multiple sequence alignments (MSAs) and inferring phylogenies are essential for many aspects of comparative biology. Yet, many bioinformatics tools for such analyses have focused on specific clades, with greatest attention paid to plants, animals, and fungi. The rapid increase in high-throughput sequencing (HTS) data from diverse lineages now provides opportunities to estimate evolutionary relationships and gene family evolution across the eukaryotic tree of life. At the same time, these types of data are known to be error-prone (e.g. substitutions, contamination). To address these opportunities and challenges, we have refined a phylogenomic pipeline, now named PhyloToL, to allow easy incorporation of data from HTS studies, to automate production of both MSAs and gene trees, and to identify and remove contaminants. PhyloToL is designed for phylogenomic analyses of diverse lineages across the tree of life (i.e. at scales of >100 My). We demonstrate the power of PhyloToL by assessing stop codon usage in Ciliophora, identifying contamination in a taxon- and gene-rich database and exploring the evolutionary history of chromosomes in the kinetoplastid parasite Trypanosoma brucei , the causative agent of African sleeping sickness. Benchmarking PhyloToL's homology assessment against that of OrthoMCL and a published paper on superfamilies of bacterial and eukaryotic organellar outer membrane pore-forming proteins demonstrates the power of our approach for determining gene family membership and inferring gene trees. PhyloToL is highly flexible and allows users to easily explore HTS data, test hypotheses about phylogeny and gene family evolution and combine outputs with third-party tools (e.g. PhyloChromoMap, iGTP). [ABSTRACT FROM AUTHOR]

Genetic risk prediction is an important goal in human genetics research and precision medicine. Accurate prediction models will have great impacts on both disease prevention and early treatment strategies. Despite the identification of thousands of disease-associated genetic variants through genome wide association studies (GWAS), genetic risk prediction accuracy remains moderate for most diseases, which is largely due to the challenges in both identifying all the functionally relevant variants and accurately estimating their effect sizes in the presence of linkage disequilibrium. In this paper, we introduce AnnoPred, a principled framework that leverages diverse types of genomic and epigenomic functional annotations in genetic risk prediction for complex diseases. AnnoPred is trained using GWAS summary statistics in a Bayesian framework in which we explicitly model various functional annotations and allow for linkage disequilibrium estimated from reference genotype data. Compared with state-of-the-art risk prediction methods, AnnoPred achieves consistently improved prediction accuracy in both extensive simulations and real data.

Multi-parent Advanced Generation Intercross (MAGIC) populations are fast becoming mainstream tools for research and breeding, along with the technology and tools for analysis. This paper demonstrates the analysis of a rice MAGIC population from data filtering to imputation and processing of genetic data to characterizing genomic structure, and finally quantitative trait loci (QTL) mapping. In this study, 1316 S6:8 indica MAGIC (MI) lines and the eight founders were sequenced using Genotyping by Sequencing (GBS). As the GBS approach often includes missing data, the first step was to impute the missing SNPs. The observable number of recombinations in the population was then explored. Based on this case study, a general outline of procedures for a MAGIC analysis workflow is provided, as well as for QTL mapping of agronomic traits and biotic and abiotic stress, using the results from both association and interval mapping approaches. QTL for agronomic traits (yield, flowering time, and plant height), physical (grain length and grain width) and cooking properties (amylose content) of the rice grain, abiotic stress (submergence tolerance), and biotic stress (brown spot disease) were mapped. Through presenting this extensive analysis in the MI population in rice, we highlight important considerations when choosing analytical approaches. The methods and results reported in this paper will provide a guide to future genetic analysis methods applied to multi-parent populations., (Copyright © 2017 Raghavan et al.)

A complex disease has, by definition, multiple genetic causes. In theory, these causes could be identified individually, but their identification will likely benefit from informed use of anticipated interactions between causes. In addition, characterizing and understanding interactions must be considered key to revealing the etiology of any complex disease. Large-scale collaborative efforts are now paving the way for comprehensive studies of interaction. As a consequence, there is a need for methods with a computational efficiency sufficient for modern data sets as well as for improvements of statistical accuracy and power. Another issue is that, currently, the relation between different methods for interaction inference is in many cases not transparent, complicating the comparison and interpretation of results between different interaction studies. In this paper we present computationally efficient tests of interaction for the complete family of generalized linear models (GLMs). The tests can be applied for inference of single or multiple interaction parameters, but we show, by simulation, that jointly testing the full set of interaction parameters yields superior power and control of false positive rate. Based on these tests we also describe how to combine results from multiple independent studies of interaction in a meta-analysis. We investigate the impact of several assumptions commonly made when modeling interactions. We also show that, across the important class of models with a full set of interaction parameters, jointly testing the interaction parameters yields identical results. Further, we apply our method to genetic data for cardiovascular disease. This allowed us to identify a putative interaction involved in Lp(a) plasma levels between two 'tag' variants in the LPA locus (p = 2.42 ⋅ 10-09) as well as replicate the interaction (p = 6.97 ⋅ 10-07). Finally, our meta-analysis method is used in a small (N = 16,181) study of interactions in myocardial infarction.

Key Message: The method of graphical genotyping is applied to a panel of tetraploid potato cultivars to visualize haplotype sharing. The method allowed to map genes involved in virus and nematode resistance. The physical coordinates of the amount of linkage drag surrounding these genes are easily interpretable. Graphical genotyping is a visually attractive and easily interpretable method to represent genetic marker data. In this paper, the method is extended from diploids to a panel of tetraploid potato cultivars. Application of filters to select a subset of SNPs allows one to visualize haplotype sharing between individuals that also share a specific locus. The method is illustrated with cultivars resistant to Potato virus Y (PVY), while simultaneously selecting for the absence of the SNPs in susceptible clones. SNP data will then merge into an image which displays the coordinates of a distal genomic region on the northern arm of chromosome 11 where a specific haplotype is introgressed from the wild potato species S. stoloniferum (CPC 2093) carrying a gene (Ny (o,n)sto ) conferring resistance to two PVY strains, PVY O and PVY NTN . Graphical genotyping was also successful in showing the haplotypes on chromosome 12 carrying Ry-f sto , another resistance gene derived from S. stoloniferum conferring broad-spectrum resistance to PVY, as well as chromosome 5 haplotypes from S. vernei, with the Gpa5 locus involved in resistance against Globodera pallida cyst nematodes. The image also shows shortening of linkage drag by meiotic recombination of the introgression segment in more recent breeding material. Identity-by-descent was found to be a requirement for using graphical genotyping, which is proposed as a non-statistical alternative method for gene discovery, as compared with genome-wide association studies. The potential and limitations of the method are discussed.

Genome-wide association studies (GWAS) have identified tens of thousands of genetic variants associated with hundreds of phenotypes and diseases, which have provided clinical and medical benefits to patients with novel biomarkers and therapeutic targets. However, identification of risk variants associated with complex diseases remains challenging as they are often affected by many genetic variants with small or moderate effects. There has been accumulating evidence suggesting that different complex traits share common risk basis, namely pleiotropy. Recently, several statistical methods have been developed to improve statistical power to identify risk variants for complex traits through a joint analysis of multiple GWAS datasets by leveraging pleiotropy. While these methods were shown to improve statistical power for association mapping compared to separate analyses, they are still limited in the number of phenotypes that can be integrated. In order to address this challenge, in this paper, we propose a novel statistical framework, graph-GPA, to integrate a large number of GWAS datasets for multiple phenotypes using a hidden Markov random field approach. Application of graph-GPA to a joint analysis of GWAS datasets for 12 phenotypes shows that graph-GPA improves statistical power to identify risk variants compared to statistical methods based on smaller number of GWAS datasets. In addition, graph-GPA also promotes better understanding of genetic mechanisms shared among phenotypes, which can potentially be useful for the development of improved diagnosis and therapeutics. The R implementation of graph-GPA is currently available at https://dongjunchung.github.io/GGPA/.

Leaf-color mutants have been extensively studied in rice, and many corresponding genes have been identified up to now. However, leaf-color mutation mechanisms are diverse and still need further research through identification of novel genes. In the present paper, we isolated a leaf-color mutant, ys83, in rice (Oryza sativa). The mutant displayed a yellow-green leaf phenotype at seedling stage, and then slowly turned into light-green leaf from late tillering stage. In its yellow leaves, photosynthetic pigment contents significantly decreased and the chloroplast development was retarded. The mutant phenotype was controlled by a recessive mutation in a nuclear gene on the short arm of rice chromosome 2. Map-based cloning and sequencing analysis suggested that the candidate gene was YS83 (LOC_Os02g05890) encoding a protein containing 165 amino acid residues. Gene YS83 was expressed in a wide range of tissues, and its encoded protein was targeted to the chloroplast. In the mutant, a T-to-A substitution occurred in coding sequence of gene YS83, which caused a premature translation of its encoded product. By introduction of the wild-type gene, the ys83 mutant recovered to normal green-leaf phenotype. Taken together, we successfully identified a novel yellow-green leaf gene YS83. In addition, number of productive panicles per plant and number of spikelets per panicle only reduced by 6.7% and 7.6%, respectively, meanwhile its seed setting rate and 1000-grain weight (seed size) were not significantly affected in the mutant, so leaf-color mutant gene ys83 could be used as a trait marker gene in commercial hybrid rice production., (Copyright © 2016. Published by Elsevier Masson SAS.)

Key Message: The paper proposes and validates a robust method for rapid construction of high-density linkage maps suitable for autotetraploid species. Modern genotyping techniques are producing increasingly high numbers of genetic markers that can be scored in experimental populations of plants and animals. Ordering these markers to form a reliable linkage map is computationally challenging. There is a wide literature on this topic, but most has focussed on populations derived from diploid, homozygous parents. The challenge of ordering markers in an autotetraploid population has received little attention, and there is currently no method that runs sufficiently rapidly to investigate the effects of omitting problematic markers on map order in larger datasets. Here, we have explored the use of multidimensional scaling (MDS) to order markers from a cross between autotetraploid parents, using simulated data with 74-152 markers on a linkage group and also experimental data from a potato population. We compared different functions of the recombination fraction and LOD score to form the MDS stress function and found that an LOD 2 weighting generally performed well, including when missing values and genotyping errors are present. We conclude that an initial analysis using unconstrained MDS gives a rapid method to detect and remove problematic markers, and that a subsequent analysis using either constrained MDS or principal curve analysis gives reliable marker orders. The latter approach is also particularly rapid, taking less than 10 s on a set of 258 markers compared to 6 days for the JoinMap software. This MDS approach could also be applied to experimental populations of diploid species.

Genotyping by sequencing (GBS) is an efficient method of genotyping in numerous plant species. One of the crucial steps toward the application of GBS markers in crop improvement is anchoring them on particular chromosomes. In rye (Secale cereale L.), chromosomal localization of GBS markers has not yet been reported. In this paper, the application of GBS markers generated by the DArTseq platform for extending the high-density map of rye is presented. Additionally, their application is used for the localization of the Rfc1 gene that restores male fertility in plants with the C source of sterility-inducing cytoplasm. The total number of markers anchored on the current version of the map is 19,081, of which 18,132 were obtained from the DArTseq platform. Numerous markers co-segregated within the studied mapping population, so, finally, only 3397 unique positions were located on the map of all seven rye chromosomes. The total length of the map is 1593 cM and the average distance between markers is 0.47 cM. In spite of the resolution of the map being not very high, it should be a useful tool for further studies of the Secale cereale genome because of the presence on this map of numerous GBS markers anchored for the first time on rye chromosomes. The Rfc1 gene was located on high-density maps of the long arm of the 4R chromosome obtained for two mapping populations. Genetic maps were composed of DArT, DArTseq, and PCR-based markers. Consistent mapping results were obtained and DArTs tightly linked to the Rfc1 gene were successfully applied for the development of six new PCR-based markers useful in marker-assisted selection., Competing Interests: Compliance with ethical standards This article does not contain any studies with human participants or animals performed by any of the authors. Funding This study was funded by the Polish National Science Center (grant no. NN310 724540). Conflict of interest The authors declare that they have no conflict of interest.

Clubroot disease, caused by Plasmodiophora brassicae, is a threat to the production of Brassica crops including oilseed B. napus. In Canada, several pathotypes of this pathogen, such as pathotypes 2, 3, 5, 6, and 8, were identified, and resistance to these pathotypes was found in a rutabaga (B. napus var. napobrassica) genotype. In this paper, we report the genetic basis and molecular mapping of this resistance by use of F 2 , backcross (BC 1 ), and doubled haploid (DH) populations generated from crossing of this rutabaga line to a susceptible spring B. napus canola line. The F 1 , F 2 , and BC 1 populations were evaluated for resistance to pathotype 3, and the DH population was evaluated for resistance to pathotypes 2, 3, 5, 6, and 8. A 3:1 segregation in F 2 and a 1:1 segregation in BC 1 were found for resistance to pathotype 3, and a 1:1 segregation was found in the DH population for resistance to all pathotypes. Molecular mapping by using the DH population identified a genomic region on chromosome A8 carrying resistance to all five pathotypes. This suggests that a single gene or a cluster of genes, located in this genomic region, is involved in the control of resistance to these pathotypes.

Shortening rye stems to improve lodging resistance is among the major tasks awaiting breeders of this cereal. The most straightforward way to achieve this goal is the implementation of a dominant dwarfing gene into high yielding cultivars. The choice of dominant dwarfing genes in rye is limited to Ddw1 and Ddw3 loci, which are well characterized with respect to map position and tightly linked molecular markers on the long arms of chromosomes 5RL and 1RL, respectively. This paper reports on the identification and preliminary characterization of a novel dominant dwarfing gene, Ddw4, from line S44. This was mapped within the centromeric region of chromosome 3R. The Ddw4 gene is sensitive to exogenous gibberellin. Its introduction into the rye populational cultivar Dańkowskie Amber decreased plant height by c. 54% without any negative effects on spike length and number of kernels per spike. Further genetic studies are needed to determine the perspectives for application of the newly detected dwarfing gene into breeding programs for short-stem rye. [ABSTRACT FROM AUTHOR]