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Information on the karyotypes of Turkish species of Cerambycidae is scanty. Our study contributes to the knowledge of the karyological data (chromosomal number and mechanism of sex determination) of five Turkish longicorn beetles; karyotypes of four taxa, one endemic, are described for the first time and for the remaining one, Purpuricenus budensis (Götz, 1783), the previously published chromosome count is confirmed. The chromosome number of Purpuricenus desfontainii inhumeralis Pic, 1891 and Purpuricenus budensis (Götz, 1783) (Cerambycinae, Trachyderini) was found to be 2n = 28 (13 + Xyp); Clytus rhamni Germar, 1817 and Plagionotus floralis (Pallas, 1773) (Cerambycinae, Clytini) 2n = 20 (9 + Xyp); and the endemic Dorcadion triste phrygicum Peks, 1993 (Lamiinae, Dorcadionini) 2n = 24 (11 + Xyp). In view of the paucity of data available until now, our study is important for both to improve the poor karyological knowledge of Turkish Cerambycidae and to provide an incentive for other researchers.

How genetic variations affect gene expression dynamics of field-grown plants remains unclear. Expression quantitative trait loci (eQTL) analysis is frequently used to find genomic regions underlying gene expression polymorphisms. This approach requires transcriptome data for the complete set of the QTL mapping population under the given conditions. Therefore, only a limited range of environmental conditions is covered by a conventional eQTL analysis. We sampled sparse time series of field-grown rice from chromosome segment substitution lines (CSSLs) and conducted RNA sequencing (RNA-Seq). Then, by using statistical analysis integrating meteorological data and the RNA-Seq data, we identified 1,675 eQTLs leading to polymorphisms in expression dynamics under field conditions. A genomic region on chromosome 11 influences the expression of several defense-related genes in a time-of-day- and scaled-age-dependent manner. This includes the eQTLs that possibly influence the time-of-day- and scaled-age-dependent differences in the innate immunity between Koshihikari and Takanari. Based on the eQTL and meteorological data, we successfully predicted gene expression under environments different from training environments and in rice cultivars with more complex genotypes than the CSSLs. Our novel approach of eQTL identification facilitated the understanding of the genetic architecture of expression dynamics under field conditions, which is difficult to assess by conventional eQTL studies. The prediction of expression based on eQTLs and environmental information could contribute to the understanding of plant traits under diverse field conditions.

The 5p inverted duplication deletion syndrome, also known as inv dup del 5p, is a rare genetic disorder with a prevalence of below 1:1 000 000, whose underlying abnormality lies in a segmental trisomy and simultaneous segmental monosomy of the short arm of chromosome 5. The syndrome was first described by A. Kleczkowska et al. in 1987. According to the literature, large duplications of the chromosome 5 short arm are associated with pronounced phenotypic manifestations, delayed speech and mental development, as well as congenital cardiac, brain and musculoskeletal malformations. We present a description of a clinical case of extended inverted duplication with deletion of the chromosome 5 short arm in a girl with a mild phenotype and no visceral or musculoskeletal abnormalities; we also discuss the pathogenetic mechanisms of chromosomal rearrangement, and conduct a comparative analysis of phenotypic manifestations based on the available literature. Comprehensive molecular cytogenetic assessments have demonstrated that the duplicated site has a length of 29 Mb (5p13.3p15.33), and the deleted site of the subtelomeric region distal to 5p15.33 has a length of 110 kb.

Recent transcriptomics and bioinformatics studies have shown that ncRNAs can affect chromosome structure and gene transcription, participate in the epigenetic regulation, and take part in diseases such as tumorigenesis. Biologists have found that most ncRNAs usually work by interacting with the corresponding RNA-binding proteins. Therefore, ncRNA-protein interaction is a very popular study in both the biological and medical fields. However, due to the limitations of manual experiments in the laboratory, machine-learning methods for predicting ncRNA-protein interactions are increasingly favored by the researchers. In this review, we summarize several machine learning predictive models of ncRNA-protein interactions over the past few years, and briefly describe the characteristics of these machine learning models. In order to optimize the performance of machine learning models to better predict ncRNA-protein interactions, we give some promising future computational directions at the end.

Background We tested the hypothesis that breeding schemes with a pre-selection step, in which carriers of a lethal recessive allele (LRA) were culled, and with optimum-contribution selection (OCS) reduce the frequency of a LRA, control rate of inbreeding, and realise as much genetic gain as breeding schemes without a pre-selection step. Methods We used stochastic simulation to estimate true genetic gain realised at a 0.01 rate of true inbreeding (ΔFtrue) by breeding schemes that combined one of four pre-selection strategies with one of three selection strategies. The four pre-selection strategies were: (1) no carriers culled, (2) male carriers culled, (3) female carriers culled, and (4) all carriers culled. Carrier-status was known prior to selection. The three selection strategies were: (1) OCS in which $$\Delta {\text{F}}_{{{\text{true}}}}$$ Δ F true was predicted and controlled using pedigree relationships (POCS), (2) OCS in which $$\Delta {\text{F}}_{{{\text{true}}}}$$ Δ F true was predicted and controlled using genomic relationships (GOCS), and (3) truncation selection of parents. All combinations of pre-selection strategies and selection strategies were tested for three starting frequencies of the LRA (0.05, 0.10, and 0.15) and two linkage statuses with the locus that has the LRA being on a chromosome with or without loci affecting the breeding goal trait. The breeding schemes were simulated for 10 discrete generations (t = 1, …, 10). In all breeding schemes, ΔFtrue was calibrated to be 0.01 per generation in generations t = 4, …, 10. Each breeding scheme was replicated 100 times. Results We found no significant difference in true genetic gain from generations t = 4, …, 10 between breeding schemes with or without pre-selection within selection strategy. POCS and GOCS schemes realised similar true genetic gains from generations t = 4, …, 10. POCS and GOCS schemes realised 12% more true genetic gain from generations t = 4, …, 10 than truncation selection schemes. Conclusions We advocate for OCS schemes with pre-selection against the LRA that cause animal suffering and high costs. At LRA frequencies of 0.10 or lower, OCS schemes in which male carriers are culled reduce the frequency of LRA, control rate of inbreeding, and realise no significant reduction in true genetic gain compared to OCS schemes without pre-selection against LRA.

G-quadruplexes are non-B secondary structures with regulatory functions and therapeutic potential. Improvements in sequencing methods recently allowed the completion of the first human chromosome which is now available as a gapless, end-to-end assembly, with the previously remaining spaces filled and newly identified regions added. We compared the presence of G-quadruplex forming sequences in the current human reference genome (GRCh38) and in the new end-to-end assembly of the X chromosome constructed by high-coverage ultra-long-read nanopore sequencing. This comparison revealed that, even though the corrected length of the chromosome X assembly is surprisingly 1.14% shorter than expected, the number of G-quadruplex forming sequences found in this gapless chromosome is significantly higher, with 493 new motifs having G4Hunter scores above 1.4 and 23 new sequences with G4Hunter scores above 3.5. This observation reflects an improved precision of the new sequencing approaches and points to an underestimation of G-quadruplex propensity in the previous, widely used version of the human genome assembly, especially for motifs with a high G4Hunter score, expected to be very stable. These G-quadruplex forming sequences probably remained undiscovered in earlier genome datasets due to previously unsolved G-rich and repetitive genomic regions. These observations allow a precise targeting of these important regulatory regions.

Modern next generation sequencing technologies produce huge amounts of genome-wide data that allow researchers to have a deeper understanding of genomics of organisms. Despite these huge amounts of data, our understanding of the transcriptional regulatory networks is still incomplete. Conformation dependent chromosome interaction maps technologies (Hi-C) have enabled us to detect elements in the genome which interact with each other and regulate the genes. Summarizing these interactions as a data network leads to investigation of the most important properties of the 3D genome structure such as gene co-expression networks. In this work, a Pareto-Based Multi-Objective Optimization algorithm is proposed to detect the co-expressed genomic regions in Hi-C interactions. The proposed method uses fixed sized genomic regions as the vertices of the graph. Number of read between two interacting genomic regions indicate the weight of each edge. The performance of our proposed algorithm was compared to the Multi-Objective PSO algorithm on five networks derived from cis genomic interactions in three Hi-C datasets (GM12878, CD34+ and ESCs). The experimental results show that our proposed algorithm outperforms Multi-Objective PSO technique in the identification of co-interacting genomic regions.

Se revisa los informes que explican la pérdida de Y, así como los factores ambientales que causan el mosaicismo. Se resume los diferentes procesos patológicos que se desarrollan debido a la falta de Y, incluidas las neoplasias, enfermedades autoinmunes y procesos neurodegenerativos. Un grupo de casos de recién nacidos con anomalías cromosómicas numéricas (45 X/46 XY) presentan un fenotipo característico, por lo que deben ser considerados como una forma de pérdida de Y congénita.

We describe twins with an interstitial deletion of chromosome 1 with a severe phenotype compared to previously described cases. As genetic testing is more frequently performed, it is important for clinicians to understand the spectrum of clinical findings that can occur with this particular deletion.

Next generation sequencing is an emerging technology that has been widely used in the detection of genomic variants. However, since its depth of coverage, a main signature used for variant calling, is affected greatly by biases such as GC content and mappability, some callings are false positives. In this study, we utilized paired-end read mapping, another signature that is not affected by the aforementioned biases, to detect false-positive deletions in the database of genomic variants. We first identified 1923 suspicious variants that may be false positives and then conducted validation studies on each suspicious variant, which detected 583 false-positive deletions. Finally we analysed the distribution of these false positives by chromosome, sample, and size. Hopefully, incorrect documentation and annotations in downstream studies can be avoided by correcting these false positives in public repositories.

We bring together conceptual readings of time and temporality to discuss evolutionary theories of Y chromosome degeneration as they are spoken about in scientific and popular forums. In doing so, we suggest that debates over Y chromosome degeneration involve a form of abduction – tacking back and forth between different pasts, presents, futures – that frames templates for producing and securing sexed and gendered presents. Here we are using ‘sexed’ as a way of talking about physical bodies and ‘gendered’ as social ways of constructing those sexed bodies. We suggest that arguments over Y chromosome degeneration are as important for current debates surrounding sex, gender, science, molecular biology and a “crisis of masculinity” as they are for (ascertaining) the future of human evolution.

Alterations in DNA methylation have been linked to the development and progression of many diseases. The bisulfite sequencing technique presents methylation profiles at base resolution. Count data on methylated and unmethylated reads provide information on the methylation level at each CpG site. As more bisulfite sequencing data become available, these data are increasingly needed to infer methylation aberrations in diseases. Automated and powerful algorithms also need to be developed to accurately identify differentially methylated regions between treatment groups. This study adopts a Bayesian approach using the hidden Markov model to account for inherent dependence in read count data. Given the expense of sequencing experiments, few replicates are available for each treatment group. A Bayesian approach that borrows information across an entire chromosome improves the reliability of statistical inferences. The proposed hidden Markov model considers location dependence among genomic loci by incorporating correlation structures as a function of genomic distance. An iterative algorithm based on expectation-maximization is designed for parameter estimation. Methylation states are inferred by identifying the optimal sequence of latent states from observations. Real datasets and simulation studies that mimic the real datasets are used to illustrate the reliability and success of the proposed method.

The Y chromosome is the most gene-deficient chromosome in the human genome (though not the smallest chromosome) and has largely been sequestered away from large-scale studies of the effects of genetics on human health. Here I review the literature, focusing on the last 2 years, for recent evidence of the role of the Y chromosome in protecting from or contributing to disease. Although many studies have focused on Y chromosome gene copy number and variants in fertility, the role of the Y chromosome in human health is now known to extend too many other conditions including the development of multiple cancers and Alzheimer’s disease. I further include the discussion of current technology and methods for analyzing Y chromosome variation. The true role of the Y chromosome and associated genetic variants in human disease will only become clear when the Y chromosome is integrated into larger studies of human genetic variation, rather than being analyzed in isolation.

Background Mathematical models are needed for the design of breeding programs using genomic prediction. While deterministic models for selection on pedigree-based estimates of breeding values (PEBV) are available, these have not been fully developed for genomic selection, with a key missing component being the accuracy of genomic EBV (GEBV) of selection candidates. Here, a deterministic method was developed to predict this accuracy within a closed breeding population based on the accuracy of GEBV and PEBV in the reference population and the distance of selection candidates from their closest ancestors in the reference population. Methods The accuracy of GEBV was modeled as a combination of the accuracy of PEBV and of EBV based on genomic relationships deviated from pedigree (DEBV). Loss of the accuracy of DEBV from the reference to the target population was modeled based on the effective number of independent chromosome segments in the reference population (Me). Measures of Me derived from the inverse of the variance of relationships and from the accuracies of GEBV and PEBV in the reference population, derived using either a Fisher information or a selection index approach, were compared by simulation. Results Using simulation, both the Fisher and the selection index approach correctly predicted accuracy in the target population over time, both with and without selection. The index approach, however, resulted in estimates of Me that were less affected by heritability, reference size, and selection, and which are, therefore, more appropriate as a population parameter. The variance of relationships underpredicted Me and was greatly affected by selection. A leave-one-out cross-validation approach was proposed to estimate required accuracies of EBV in the reference population. Aspects of the methods were validated using real data. Conclusions A deterministic method was developed to predict the accuracy of GEBV in selection candidates in a closed breeding population. The population parameter Me that is required for these predictions can be derived from an available reference data set, and applied to other reference data sets and traits for that population. This method can be used to evaluate the benefit of genomic prediction and to optimize genomic selection breeding programs.

Healthcare providers treating newborns with asymmetric cry syndrome should consider 22q11.2 microdeletion within the differential diagnosis list and order appropriate genetic testing.

Key message In polyploids, linkage mapping is carried out using genotyping with discrete dosage scores. Here, we use probabilistic genotypes and we validate it for the construction of polyploid linkage maps. Abstract Marker genotypes are generally called as discrete values: homozygous versus heterozygous in the case of diploids, or an integer allele dosage in the case of polyploids. Software for linkage map construction and/or QTL analysis usually relies on such discrete genotypes. However, it may not always be possible, or desirable, to assign definite values to genotype observations in the presence of uncertainty in the genotype calling. Here, we present an approach that uses probabilistic marker dosages for linkage map construction in polyploids. We compare our method to an approach based on discrete dosages, using simulated SNP array and sequence reads data with varying levels of data quality. We validate our approach using experimental data from a potato (Solanum tuberosum L.) SNP array applied to an F1 mapping population. In comparison to the approach based on discrete dosages, we mapped an additional 562 markers. All but three of these were mapped to the expected chromosome and marker position. For the remaining three markers, no physical position was known. The use of dosage probabilities is of particular relevance for map construction in polyploids using sequencing data, as these often result in a higher level of uncertainty regarding allele dosage.

Chromosome segregation—the partitioning of genetic material into two daughter cells—is one of the most crucial processes in cell division. In all Eukaryotes, chromosome segregation is driven by the spindle, a microtubule-based, self-organizing subcellular structure. Extensive research performed over the past 150 years has identified numerous commonalities and contrasts between spindles in different systems. In this review, we use simple coarse-grained models to organize and integrate previous studies of chromosome segregation. We discuss sites of force generation in spindles and fundamental mechanical principles that any understanding of chromosome segregation must be based upon. We argue that conserved sites of force generation may interact differently in different spindles, leading to distinct mechanical mechanisms of chromosome segregation. We suggest experiments to determine which mechanical mechanism is operative in a particular spindle under study. Finally, we propose that combining biophysical experiments, coarse-grained theories, and evolutionary genetics will be a productive approach to enhance our understanding of chromosome segregation in the future.

BACKGROUNDSquamosal sutures are minor sutures of the human skull. Early isolated fusion of the sutures (squamosal synostosis) is rarely found.OBSERVATIONSThe authors report a case of a girl who presented with an abnormal head shape and bilateral squamosal synostosis. Genetic testing revealed a chromosome 1p12–1p13.3 deletion. She has been managed with conservative treatment of the synostosis. She has global developmental delay and multiple anomalies due to the chromosome abnormality.LESSONSIsolated squamosal suture synostosis could be an uncommon feature of chromosome 1p12–1p13.3 deletion.

Ring chromosome 18 (r[18]) is a rare syndrome in which one or both ends of chromosome 18 are lost and the remaining chromosome rejoins to form ring-shaped figures. It is characterized by developmental delay/cognitive disability, facial dysmorphisms, and immunological problems. The phenotype associated with epilepsy is rare and has not yet been reported in China. We report herein the case of a 12-year-old Chinese girl who presented with typical facial dysmorphisms, developmental delay, cognitive disability, hyperactivity, and epilepsy and discuss the clinical features of r(18) syndromes through comparison with previously described cases worldwide. We describe the characteristics of all seizures that have been reported in these cases and propose that the appearance of epilepsy in r(18) patients may be associated with the abnormality of chromosome karyotypes. Further studies are warranted to confirm this.

Made available in DSpace on 2022-04-28T19:50:06Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-01-01 Advances in genomic sequencing have recently offered vast opportunities for biological exploration, unraveling the evolution and improving our understanding of Earth biodiversity. Due to distinct plant species characteristics in terms of genome size, ploidy and heterozygosity, transposable elements (TEs) are common characteristics of many genomes. TEs are ubiquitous and dispersed repetitive DNA sequences that frequently impact the evolution and composition of the genome, mainly due to their redundancy and rearrangements. For this study, we provided an atlas of TE data by employing an easy-to-use portal ( APTE website ). To our knowledge, this is the most extensive and standardized analysis of TEs in plant genomes. We evaluated 67 plant genomes assembled at chromosome scale, recovering a total of 49,802,023 TE records, representing a total of 47,992,091,043 (~47,62%) base pairs (bp) of the total genomic space. We observed that new types of TEs were identified and annotated compared to other data repositories. By establishing a standardized catalog of TE annotation on 67 genomes, new hypotheses, exploration of TE data and their influences on the genomes may allow a better understanding of their function and processes. All original code and an example of how we developed the TE annotation strategy is available on GitHub ( Extended data). Department of Computer Science; Bioinformatics and Pattern Recognition Group, Graduation Program in Bioinformatics, Federal University of Technology - Paraná (UTFPR), Cornélio Procópio, Paraná, 86300000, Brazil Departament of Agricultural and Environmental Biotechnology School of Agricultural and Veterinary Sciences São Paulo State University (UNESP) Institut de Recherche pour le Développement IRD University of Montpellier Department of Electronics and Automatization Universidad Autónoma de Manizales Group of Genomics and Transcriptomes in Plants Institute of Biosciences São Paulo State University (UNESP) Departament of Agricultural and Environmental Biotechnology School of Agricultural and Veterinary Sciences São Paulo State University (UNESP) Group of Genomics and Transcriptomes in Plants Institute of Biosciences São Paulo State University (UNESP)

For numerically small breeds, obtaining a sufficiently large breed‐specific reference population for genomic prediction is challenging or simply not possible, but may be overcome by adding individuals from another breed. To prioritize among available breeds, the effective number of chromosome segments (M e) can be used as an indicator of relatedness between individuals from different breeds. The M e is also an important parameter in determining the accuracy of genomic prediction. The M e can be estimated both within a population and between two populations or breeds, as the reciprocal of the variance of genomic relationships. However, the threshold for number of individuals needed to accurately estimate within or between populations M e is currently unknown. It is also unknown if a discrepancy in number of genotyped individuals in two breeds affects the estimates of M e between populations. In this study, we conducted a simulation that mimics current domestic cattle populations in order to investigate how estimated M e is affected by number of genotyped individuals, single‐nucleotide polymorphism (SNP) density and pedigree availability. Our results show that a small sample of 10 genotyped individuals may result in substantial over or underestimation of M e. While estimates of within population M e were hardly affected by SNP density, between population M e values were highly dependent on the number of available SNPs, with higher SNP densities being able to detect more independent chromosome segments. When subtracting pedigree from genomic relationships before computing M e, estimates of within population M e were three to four times higher than estimates with genotypes only; however, between M e estimates remained the same. For accurate estimation of within and between population M e, at least 50 individuals should be genotyped per population. Estimates of within M e were highly affected by whether pedigree was used or not. For within M e, even the smallest SNP density (~11k) resulted in accurate representation of family relationships in the population; however, for between M e, many more markers are needed to capture all independent segments.

Genomic information has a limited dimensionality (number of independent chromosome segments [Me]) related to the effective population size. Under the additive model, the persistence of genomic accuracies over generations should be high when the nongenomic information (pedigree and phenotypes) is equivalent to Me animals with high accuracy. The objective of this study was to evaluate the decay in accuracy over time and to compare the magnitude of decay with varying quantities of data and with traits of low and moderate heritability. The dataset included 161,897 phenotypic records for a growth trait (GT) and 27,669 phenotypic records for a fitness trait (FT) related to prolificacy in a population with dimensionality around 5,000. The pedigree included 404,979 animals from 2008 to 2020, of which 55,118 were genotyped. Two single-trait models were used with all ancestral data and sliding subsets of 3-, 2-, and 1-generation intervals. Single-step genomic best linear unbiased prediction (ssGBLUP) was used to compute genomic estimated breeding values (GEBV). Estimated accuracies were calculated by the linear regression (LR) method. The validation population consisted of single generations succeeding the training population and continued forward for all generations available. The average accuracy for the first generation after training with all ancestral data was 0.69 and 0.46 for GT and FT, respectively. The average decay in accuracy from the first generation after training to generation 9 was −0.13 and −0.19 for GT and FT, respectively. The persistence of accuracy improves with more data. Old data have a limited impact on the predictions for young animals for a trait with a large amount of information but a bigger impact for a trait with less information.

Motivation Long read sequencing and Bionano Genomics optical maps are two techniques that, when used together, make it possible to reconstruct entire chromosome or chromosome arms structure. However, the existing tools are often too conservative and organization of contigs into scaffolds is not always optimal. Results We developed BiSCoT (Bionano SCaffolding COrrection Tool), a tool that post-processes files generated during a Bionano scaffolding in order to produce an assembly of greater contiguity and quality. BiSCoT was tested on a human genome and four publicly available plant genomes sequenced with Nanopore long reads and improved significantly the contiguity and quality of the assemblies. BiSCoT generates a fasta file of the assembly as well as an AGP file which describes the new organization of the input assembly. Availability BiSCoT and improved assemblies are freely available on GitHub at http://www.genoscope.cns.fr/biscot and Pypi at https://pypi.org/project/biscot/.

Quantitative trait locus (QTL) analysis is a statistical method that links two types of information such as phenotypic data (trait measurements) and genotypic data (usually molecular markers). There a number of QTL tools have been developed for gene linkage mapping. Standard Interval Mapping (SIM) or Simple Interval Mapping or Interval Mapping (IM), Haley Knott, Extended Haley Knott and Multiple Imputation (IMP) method when the single-QTL is unlinked and Composite Interval Mapping (CIM) is designed to map the genetic linkage for both linked and unlinked genes in the chromosome. Performance of these methods is measured based on calculated LOD score. The QTLs are considered significant above the threshold LOD score 3.0. For backcross-simulated data, the CIM method performs significantly in detecting QTLs compare to other SIM mapping methods. CIM detected three QTLs in chromosome 1 and 4 whereas the other methods were unable to detect any significant marker positions for simulated data. For a real rice dataset, CIM also showed performance considerably in detecting marker positions compared to other four interval mapping methods. CIM finally detected 12 QTL positions while each of the other four SIM methods detected only six positions.

There is an agreement about joint genetic and environmental background of musical reception and performance. Musical abilities tend to cluster in families. The studies done on a random population, twins and families of gifted musicians provided a strong support for genetic contribution. Modern biomolecular techniques exploring linkage analysis, variation of gene copy number, scanning for whole-genome expression helped to identify genes, or chromosome regions associated with musical aptitude. Some studies were focused on rare ability to recognize tone without reference that is known as a perfect pitch where a far ethnic differentiation was established. On the other hand, gene deletion leading to dysfunction in amusical individuals also indicated appropriate loci “by negation.” The strongest support for an association of genes with musicality was provided for genes: AVPR1 (12q14.2), SLC6A4 (17q11.2), GALM (2p22), PCDH7 (4p15.1), GATA2 (3q21.3), and few others as well for 4q22, 4q23, and 8q13–21 chromosome bands.

Genome-wide association studies often collect multiple phenotypes for complex diseases. Multivariate joint analyses have higher power to detect genetic variants compared with the marginal analysis of each phenotype and are also able to identify loci with pleiotropic effects. We extend the unified score-based association test to incorporate family structure, apply different approaches to analyze multiple traits in GAW20 real samples, and compare the results. Through simulation studies, we confirm that the Type I error rate of the pedigree-based unified score association test is appropriately controlled. In marginalanalysis of triglyceride levels, we found 1 subgenome-wide significant variant on chromosome 6. Joint analyses identified several suggestive genome-wide significant signals, with the pedigree-based unified score association test yielding the greatest number of significant results.

Health care providers remain ill prepared to recognize these conditions and support patients and their families.

Rules to generate the inverse additive relationship matrix (A −1 ) are defined to enable the adoption restricted maximum likelihood (REML) and best linear unbiased prediction (BLUP) in autopolyploid populations with multiple ploidy levels. Many important agronomic, horticultural, ornamental, forestry, and aquaculture species are autopolyploids. However, the adoption of restricted maximum likelihood (REML), for estimating co/variance components, and best linear unbiased prediction (BLUP), for predicting breeding values, has been hampered in autopolyploid breeding by the absence of an appropriate means of generating the inverse additive relationship matrix (A −1 ). This paper defines rules to generate the A −1 of autopolyploid populations comprised of individuals of the same or different ploidy-levels, including populations exhibiting (1) odd-numbered ploidy levels (e.g. triploids), (2) sex-based differences in the probability that gametic genes are identical by descent and (3) somatic chromosome doubling. Inbreeding, due to double reduction, in autopolyploid founders in the absence of mating among relatives is also accounted for. A previously defined approach is modified, whereby rules are initially defined to build an inverse matrix of kinship coefficients (K −1 ), which is then used to generate A −1 . An R package (polyAinv; https://github.com/mghamilton/polyAinv ) to implement these rules has been developed and examples of analyses provided. The adoption of REML and BLUP methods made possible by these new rules has the potential to provide further insights into the quantitative genetic architecture of autopolyploid and multiple-ploidy populations, improve estimates of breeding values, and increase genetic gains made through recurrent selection.

Preaxial polydactyly (PPD) is congenital hand malformation characterized by the duplication of digit. Herein, we scan the genome-wide SNPs for a large Chinese family with PPD-II/III. We employ the refined IBD algorithm to identify the identity-by-decent (IBD) segments and compare the frequency among the patients and normal relatives. A total of 72 markers of 0.01 percentile of the permutation are identified as the peak signals. Among of them, 57markers locate on chromosome 7q36 which is associated with PPD. Further analyses refine the mapping of candidate region in chromosome 7q36 into two 380 Kb fragments within LMBR1 and SHH respectively. IBD approach is a suitable method for mapping causal gene of human disease. Target-enrichment sequencing as well as functional experiments are required to illustrate the pathogenic mechanisms for PPD in the future. Electronic supplementary material The online version of this article (doi:10.1186/s41065-017-0040-6) contains supplementary material, which is available to authorized users.

Transposable elements (TEs) are the main components of genomes. However, due to their repetitive nature, they are very difficult to study using data obtained with short-read sequencing technologies. Here, we describe an efficient pipeline to accurately recover TE insertion (TEI) sites and sequences from long reads obtained by Oxford Nanopore Technology (ONT) sequencing. With this pipeline, we could precisely describe the landscapes of the most recent TEIs in wild-type strains of Drosophila melanogaster and Drosophila simulans. Their comparison suggests that this subset of TE sequences is more similar than previously thought in these two species. The chromosome assemblies obtained using this pipeline also allowed recovering piRNA cluster sequences, which was impossible using short-read sequencing. Finally, we used our pipeline to analyze ONT sequencing data from a D. melanogaster unstable line in which LTR transposition was derepressed for 73 successive generations. We could rely on single reads to identify new insertions with intact target site duplications. Moreover, the detailed analysis of TEIs in the wild-type strains and the unstable line did not support the trap model claiming that piRNA clusters are hotspots of TE insertions., This research was funded by the Fondation pour la Recherche Médicale, grant number “DEQ20180339167” to S.C, by the ANR Exhyb to C.V., by the CNRS.

BackgroundA multi-population genomic prediction (GP) model in which important pre-selected single nucleotide polymorphisms (SNPs) are differentially weighted (MPMG) has been shown to result in better prediction accuracy than a multi-population, single genomic relationship matrix ($${\mathbf{GRM}}$$GRM) GP model (MPSG) in which all SNPs are weighted equally. Our objective was to underpin theoretically the advantages and limits of the MPMG model over the MPSG model, by deriving and validating a deterministic prediction equation for its accuracy.MethodsUsing selection index theory, we derived an equation to predict the accuracy of estimated total genomic values of selection candidates from population$$A$$A($$r_{{{\mathbf{EGV}}_{{A_{T} }} }}$$rEGVAT), when individuals from two populations,$$A$$Aand$$B$$B, are combined in the training population and two$${\mathbf{GRM}}$$GRM, made respectively from pre-selected and remaining SNPs, are fitted simultaneously in MPMG. We used simulations to validate the prediction equation in scenarios that differed in the level of genetic correlation between populations, heritability, and proportion of genetic variance explained by the pre-selected SNPs. Empirical accuracy of the MPMG model in each scenario was calculated and compared to the predicted accuracy from the equation.ResultsIn general, the derived prediction equation resulted in accurate predictions of$$r_{{{\mathbf{EGV}}_{{A_{T} }} }}$$rEGVATfor the scenarios evaluated. Using the prediction equation, we showed that an important advantage of the MPMG model over the MPSG model is its ability to benefit from the small number of independent chromosome segments ($$M_{e}$$Me) due to the pre-selected SNPs, both within and across populations, whereas for the MPSG model, there is only a single value for$$M_{e}$$Me, calculated based on all SNPs, which is very large. However, this advantage is dependent on the pre-selected SNPs that explain some proportion of the total genetic variance for the trait.ConclusionsWe developed an equation that gives insight into why, and under which conditions the MPMG outperforms the MPSG model for GP. The equation can be used as a deterministic tool to assess the potential benefit of combining information from different populations, e.g., different breeds or lines for GP in livestock or plants, or different groups of people based on their ethnic background for prediction of disease risk scores.

A large number of computer-based prediction methods to determine the potential of chemicals to induce mutations at the gene level has been developed over the last decades. Conversely, only few such methods are currently available to predict potential structural and numerical chromosome aberrations. Even fewer of these are based on the preferred testing method for this endpoint, i.e. the micronucleus test. For the present work, in vivo micronucleus test results of 718 structurally diverse compounds were collected and applied for the construction of new models by means of the freely available SARpy in silico model building software. Multiple QSAR models were created using parameter variation and manual verification of (non-) alerting structures. To this extent, the original set of 718 compounds was split into a training (80 %) and a test (20 %) set. SARpy was applied on the training set to automatically extract sets of rules by generating and selecting substructures based on their prediction performance whereas the test set was used to evaluate model performance. Five different splits were made randomly, each of which had a similar balance between positive and negative substances compared to the full dataset. All generated models were characterised by an overall better performance than existing free and commercial models for the same endpoint, while demonstrating high coverage.

With the rise in genetic screening both pre- and postnatally, new variances in genes are being recognized. Some are of unknown significance, while other known genetic expressions have obvious phenotypical expressions. Transient neonatal diabetes mellitus is a result of the duplication of chromosome 6q24, but little is known about the phenotypic expression of a triplication of chromosome 6q24. This case study presents an infant with a postnatally diagnosed triplication of chromosome 6q24, meconium pseudocyst, and multiple congenital anomalies with unknown genetic significance.

Objective Parentage analysis is a technology that uses genetic methods to verify or exclude relationships between individuals. STR technology is often used in parentage analysis. We received three sets of samples from three families. Each set of samples consisted of a male individual and a female individual. Their test requirements were meant to determine whether they were a paternity relationship, a sibling relationship, or grandparent-grandchild relationship. However, only one STR locus mismatch was detected in each group. Other family members to assist in testing could not be identified; therefore, other methods were needed to assist in judgment. Using high-density SNP microarrays, we analyzed the feasibility of its application in paternity analysis. Results A total of 180 samples were tested, including 100 unrelated samples, and 74 samples from 30 families, and six samples from three families. The data were analyzed, grouped according to the chromosome of SNP, and the mismatching rate was counted. The total mismatching rate of SNP in unrelated individuals was 8–10 times higher than that of parent-child individuals. Individuals with a total mismatch rate of more than 5.3% were defined as individuals with no kinship, and the individuals with a total mismatch rate of less than 0.6% were defined as the individuals with a parent-child relationship. Conclusions Through the use of high-density gene chips for analysis, we also completed an auxiliary analysis of the kinship of the three families. The gene chip is a better method for auxiliary analysis of the kinship between individuals.

Chromothripsis has been defined as complex patterns of alternating genes copy number changes (normal, gain or loss) along the length of a chromosome or chromosome segment (International System for Human Cytogenomic Nomenclature 2020). The phenomenon of chromothripsis was discovered in 2011 and changed the concept of genome variability, mechanisms of oncogenic transformation, and hereditary diseases. This review describes the phenomenon of chromothripsis, its prevalence in genomes, the mechanisms underlying this phenomenon, and methods of its detection. Due to the fact that most often the phenomenon of chromothripsis occurs in cancer cells, in this review, we will separately discuss the issue of the contribution of chromothripsis to the process of oncogenesis.

Genetic algorithms are evolutionary techniques used for optimization purposes according to survival of the fittest idea. These methods do not ensure optimal solutions; however, they give good approximation usually in time. The genetic algorithms are useful for NP-hard problems, especially the traveling salesman problem. The genetic algorithm depends on selection criteria, crossover, and mutation operators. To tackle the traveling salesman problem using genetic algorithms, there are various representations such as binary, path, adjacency, ordinal, and matrix representations. In this article, we propose a new crossover operator for traveling salesman problem to minimize the total distance. This approach has been linked with path representation, which is the most natural way to represent a legal tour. Computational results are also reported with some traditional path representation methods like partially mapped and order crossovers along with new cycle crossover operator for some benchmark TSPLIB instances and found improvements.

Finding rare variants and gene-environment interactions (GXE) is critical in dissecting complex diseases. We consider the problem of detecting GXE where G is a rare haplotype and E is a nongenetic factor. Such methods typically assume G-E independence, which may not hold in many applications. A pertinent example is lung cancer-there is evidence that variants on Chromosome 15q25.1 interact with smoking to affect the risk. However, these variants are associated with smoking behavior rendering the assumption of G-E independence inappropriate. With the motivation of detecting GXE under G-E dependence, we extend an existing approach, logistic Bayesian LASSO, which assumes G-E independence (LBL-GXE-I) by modeling G-E dependence through a multinomial logistic regression (referred to as LBL-GXE-D). Unlike LBL-GXE-I, LBL-GXE-D controls type I error rates in all situations; however, it has reduced power when G-E independence holds. To control type I error without sacrificing power, we further propose a unified approach, LBL-GXE, to incorporate uncertainty in the G-E independence assumption by employing a reversible jump Markov chain Monte Carlo method. Our simulations show that LBL-GXE has power similar to that of LBL-GXE-I when G-E independence holds, yet has well-controlled type I errors in all situations. To illustrate the utility of LBL-GXE, we analyzed a lung cancer dataset and found several significant interactions in the 15q25.1 region, including one between a specific rare haplotype and smoking.

Trisomy 12 is a rare aneuploidy and fetuses with this defect tend to spontaneously abort. However, mosaicism allows this anomaly to manifest itself in live births. Due to the fact that mosaicism represents a common genetic abnormality, trisomy 12 is encountered more frequently than expected at a rate of 1 in 500 live births. Thus, it is imperative that medical practitioners are aware of this aneuploidy. Moreover, this genetic disorder may result from a complete or partial duplication of chromosome 12. A partial duplication may refer to a specific segment on the chromosome, or one of the arms. On the other hand, a complete duplication refers to duplication of both arms of chromosome 12. The combination of mosaicism and the variable duplication sites has led to variable phenotypes ranging from normal phenotype to Potter sequence to gross physical defects of the various organ systems. This article provides a review of the common anatomical variation of the different types of trisomy 12. This review revealed that further documentation is needed for trisomy 12q and complete trisomy 12 to clearly delineate the constellation of anomalies that characterize each genetic defect. Clin. Anat. 29:633-637, 2016. © 2016 Wiley Periodicals, Inc.

Key Clinical Message We present a male patient with constitutional ring 1 chromosome and subsequent 6 Mb deletion at 1q43q44. The patient displays overlapping clinical features with reported patients with ring 1 chromosome and 1q43q44 microdeletion syndrome. To our knowledge, this is the first patient with ring 1 chromosome characterized by comparative genomic hybridization.

Background: Data sets from long-read sequencing platforms (Oxford Nanopore Technologies and Pacific Biosciences) allow for most prokaryote genomes to be completely assembled – one contig per chromosome or plasmid. However, the high per-read error rate of long-read sequencing necessitates different approaches to assembly than those used for short-read sequencing. Multiple assembly tools (assemblers) exist, which use a variety of algorithms for long-read assembly. Methods: We used 500 simulated read sets and 120 real read sets to assess the performance of eight long-read assemblers (Canu, Flye, Miniasm/Minipolish, NECAT, NextDenovo/NextPolish, Raven, Redbean and Shasta) across a wide variety of genomes and read parameters. Assemblies were assessed on their structural accuracy/completeness, sequence identity, contig circularisation and computational resources used. Results: Canu v2.1 produced reliable assemblies and was good with plasmids, but it performed poorly with circularisation and had the longest runtimes of all assemblers tested. Flye v2.8 was also reliable and made the smallest sequence errors, though it used the most RAM. Miniasm/Minipolish v0.3/v0.1.3 was the most likely to produce clean contig circularisation. NECAT v20200803 was reliable and good at circularisation but tended to make larger sequence errors. NextDenovo/NextPolish v2.3.1/v1.3.1 was reliable with chromosome assembly but bad with plasmid assembly. Raven v1.3.0 was reliable for chromosome assembly, though it did not perform well on small plasmids and had circularisation issues. Redbean v2.5 and Shasta v0.7.0 were computationally efficient but more likely to produce incomplete assemblies. Conclusions: Of the assemblers tested, Flye, Miniasm/Minipolish, NextDenovo/NextPolish and Raven performed best overall. However, no single tool performed well on all metrics, highlighting the need for continued development on long-read assembly algorithms.