Patients with inborn errors of immunity (IEI) have a higher risk of developing cancer, especially lymphoma. However, the molecular basis for IEI-related lymphoma is complex and remains elusive. Here, we perform an in-depth analysis of lymphoma genomes derived from 23 IEI patients. We identified and validated disease-causing or -associated germline mutations in 14 of 23 patients involving ATM, BACH2, BLM, CD70, G6PD, NBN, PIK3CD, PTEN, and TNFRSF13B. Furthermore, we profiled somatic mutations in the lymphoma genome and identified 8 genes that were mutated at a significantly higher level in IEI-associated diffuse large B-cell lymphomas (DLBCLs) than in non-IEI DLBCLs, such as BRCA2, NCOR1, KLF2, FAS, CCND3, and BRWD3. The latter, BRWD3, is furthermore preferentially mutated in tumors of a subgroup of activated phosphoinositide 3-kinase δ syndrome patients. We also identified 5 genomic mutational signatures, including 2 DNA repair deficiency-related signatures, in IEI-associated lymphomas and a strikingly high number of inter- and intrachromosomal structural variants in the tumor genome of a Bloom syndrome patient. In summary, our comprehensive genomic characterization of lymphomas derived from patients with rare genetic disorders expands our understanding of lymphomagenesis and provides new insights for targeted therapy.

The Pacific oyster Crassostrea gigas is an important cultivated shellfish that is rich in nutrients. It contains high levels of glycogen, which is of high nutritional value. To investigate the genetic basis of this high glycogen content and its variation, we conducted a candidate gene association analysis using a wild population, and confirmed our results using an independent population, via targeted gene resequencing and mRNA expression analysis.

New high-throughput technologies, such as massively parallel sequencing, have transformed the life sciences into a data-intensive field. The most common e-infrastructure for analyzing this data consists of batch systems that are based on high-performance computing resources; however, the bioinformatics software that is built on this platform does not scale well in the general case. Recently, the Hadoop platform has emerged as an interesting option to address the challenges of increasingly large datasets with distributed storage, distributed processing, built-in data locality, fault tolerance, and an appealing programming methodology.

Poor central nervous system penetration of cytotoxic drugs due to the blood brain barrier (BBB) is a major limiting factor in the treatment of brain tumors. Most recurrent glioblastomas (GBM) occur within the peritumoral region. In this study, we describe a hyperthemic method to induce temporary disruption of the peritumoral BBB that can potentially be used to enhance drug delivery.

To explore the clinical and molecular characteristics of a Chinese Zhuang minority patient with leukocyte adhesion deficiency type-1 (LAD-1) and glucose-6-phosphate dehydrogenase deficiency (G6PDD).

As the most common inherited retinal degenerations, retinitis pigmentosa (RP) is clinically and genetically heterogeneous. Some of the RP genes are also associated with other retinal diseases, such as LCA (Leber's congenital amaurosis) and CORD (cone-rod dystrophy). Here, in our molecular diagnosis of 99 Chinese RP patients using targeted gene capture sequencing, three probands were found to carry mutations of RPGRIP1, which was known to be associated with pathogenesis of LCA and CORD. By further clinical analysis, two probands were confirmed to be RP patients and one was confirmed to be LCA patient. These novel mutations were co-segregated with the disease phenotype in their families. Our result not only expands the mutational spectrum of the RPGRIP1 gene but also gives supports to clinical diagnosis and molecular treatment of RP patients.

Thrombophilia is a multifactorial disorder involving environmental and genetic factors. Well‑known factors that result in predisposition to congenital disorders associated with thrombophilia include antithrombin deficiency, protein C and S deficiency, Factor V Leiden mutation, abnormal prothrombin and antiphospholipid syndrome. The present study revealed an association between a mutation of the F2 gene, which codes for coagulation factor II, thrombin, and the risk of thrombophilia in a Han Chinese family, of which four members (I‑2, II‑2, II‑3 and III‑1) had a history of deep venous thromboembolism. The disease was measured in this family using laboratory measurements and computed tomography angiography. To identify the abnormality underlying the increased thrombophilia risk, whole‑exome sequencing technology was used to analyze two affected individuals (II‑2 and III‑1). An exonic missense F2 mutation, T165M (NM_000506:c.C494T:p.T165M;rs5896), was identified from a total of 2,222 and 2,203 genetic variations observed in the two affected individuals, respectively, which were subsequently filtered and confirmed using Sanger sequencing. I‑2, II‑3 and III‑1 shared this mutation with the proband (II‑2), and II‑6 had a heterozygous form of the mutation. This deleterious mutation was not identified in normal controls. The present study may improve understanding of the function of the F2 gene.

Quantifying biophysical and biochemical vegetation variables is of great importance in precision agriculture. Here, the ability of artificial neural networks (ANNs) to generate multiple outputs is exploited to simultaneously retrieve Leaf area index (LAI), leaf sheath moisture (LSM), leaf chlorophyll content (LCC), and leaf nitrogen concentration (LNC) of sugarcane from Sentinel-2 spectra. We apply a type of ANNs, Bayesian Regularized ANN (BRANN), which incorporates the Bayes' theorem into a regularization scheme to tackle the overfitting problem of ANN and improve its generalizability. Quantitatively assessing the result accuracy indicated RMSE values of 0.48 (m2/m2) for LAI, 2.36 (% wb) for LSM, 5.85 (μg/cm2) for LCC, and 0.23 (%) for LNC, applying simultaneous retrieval. It was demonstrated that simultaneous retrievals of the variables outperformed the individual retrievals. The superiority of the proposed BRANN over a conventional ANN trained with the Levenberg-Marquardt algorithm was confirmed through statistical comparison of their results. The model was applied over the entire Sentinel-2 images to map the considered variables. The maps were probed to qualitatively evaluate the model performance. The results indicated that the retrievals reasonably represent spatial and temporal variations of the variables. Generally, this study demonstrated that the BRANN simultaneous retrieval model can provide faster and more accurate retrievals than those obtained from conventional ANNs and individual retrievals.

Reward is often employed as reinforcement in behavioral paradigms but it is unclear how the visuospatial aspect of a stimulus-reward association affects the cortical representation of visual space. Using a head-fixed paradigm, we conditioned mice to associate the same visual pattern in adjacent retinotopic regions with availability and absence of reward. Time-lapse intrinsic optical signal imaging under anesthesia showed that conditioning increased the spatial separation of mesoscale cortical representations of reward predicting- and non-reward predicting stimuli. Subsequent in vivo two-photon calcium imaging revealed that this improved separation correlated with enhanced population coding for retinotopic location, specifically for the trained orientation and spatially confined to the V1 region where rewarded and non-rewarded stimulus representations bordered. These results are corroborated by conditioning-induced differences in the correlation structure of population activity. Thus, the cortical representation of visual space is sharpened as consequence of associative stimulus-reward learning while the overall retinotopic map remains unaltered.

X-linked sideroblastic anemia (XLSA) is the most common form of congenital sideroblastic anemia (CSA), and is associated with the mutations in the 5-aminolevulinate synthase 2 (ALAS2). The genetic basis of more than 40% of CSA cases remains unknown.

Genetic diversities or favorable genes within distantly related species are the important resources for crop genetic improvement and germplasm innovation. Spike-Stalk injection method (SSI) has long been applied in rice genetic improvement by directly introducing genetic materials from non-mating donor species, while its inheritance patterns and the underlying mechanisms are poorly elucidated. In this study, a rice variant ERV1 with improved yield-related traits was screened out in the way of introducing genomic DNA of Oryza eichingeri (2n=24, CC genome) into RH78 (Oryza sativa L. 2n=24, AA genome) using SSI method. Genome-wide comparison revealed that the genomic heterozygosity of ERV1 was approximately 8-fold higher than RH78. Restriction-site associated DNA sequencing technology (RAD-seq) and association analysis of the ERV1 inbred F2 population identified 5 quantitative trait loci (QTLs) regions responsible for these yield-related traits, and found that genomic heterozygosity of ERV1 inbred lines was significantly lower than ERV1, while spontaneous mutation rate of the ERV1 inbred lines was significantly higher than ERV1. Our results preliminarily uncovered the inheritance patterns of SSI variant rice, and the potential genomic regions for traits changes, which yielded novel insights into the mechanisms of SSI method, and may accelerate our understanding of plant genome evolution, domestication, and speciation in nature.

Insecticide resistance is a substantial problem in controlling agricultural and medical pests. Detecting target site mutations is crucial to manage insecticide resistance. Though PCR-based methods have been widely used in this field, they are time-consuming and inefficient, and typically have a high false positive rate. Acetylcholinesterases (Ace) is the neural target of the widely used organophosphate (OP) and carbamate insecticides. However, there is not any software available to detect insecticide resistance associated mutations in RNA-Seq data at present.

Polygenic Scores (PGSs) summarize an individual's genetic propensity for a given trait in a single value, based on SNP effect sizes derived from Genome-Wide Association Study (GWAS) results. Methods have been developed that apply Bayesian approaches to improve the prediction accuracy of PGSs through optimization of estimated effect sizes. While these methods are generally well-calibrated for continuous traits (implying the predicted values are on average equal to the true trait values), they are not well-calibrated for binary disorder traits in ascertained samples. This is a problem because well-calibrated PGSs are needed to reliably compute the absolute disorder probability for an individual to facilitate future clinical implementation. Here we introduce the Bayesian polygenic score Probability Conversion (BPC) approach, which computes an individual's predicted disorder probability using GWAS summary statistics, an existing Bayesian PGS method (e.g. PRScs, SBayesR), the individual's genotype data, and a prior disorder probability. The BPC approach transforms the PGS to its underlying liability scale, computes the variances of the PGS in cases and controls, and applies Bayes' Theorem to compute the absolute disorder probability; it is practical in its application as it does not require a tuning dataset with both genotype and phenotype data. We applied the BPC approach to extensive simulated data and empirical data of nine disorders. The BPC approach yielded well-calibrated results that were consistently better than the results of another recently published approach.

We study genome-wide nucleotide diversity in three subspecies of extant chimpanzees using exome capture. After strict filtering, Single Nucleotide Polymorphisms and indels were called and genotyped for greater than 50% of exons at a mean coverage of 35× per individual. Central chimpanzees (Pan troglodytes troglodytes) are the most polymorphic (nucleotide diversity, θw = 0.0023 per site) followed by Eastern (P. t. schweinfurthii) chimpanzees (θw = 0.0016) and Western (P. t. verus) chimpanzees (θw = 0.0008). A demographic scenario of divergence without gene flow fits the patterns of autosomal synonymous nucleotide diversity well except for a signal of recent gene flow from Western into Eastern chimpanzees. The striking contrast in X-linked versus autosomal polymorphism and divergence previously reported in Central chimpanzees is also found in Eastern and Western chimpanzees. We show that the direction of selection statistic exhibits a strong nonmonotonic relationship with the strength of purifying selection S, making it inappropriate for estimating S. We instead use counts in synonymous versus nonsynonymous frequency classes to infer the distribution of S coefficients acting on nonsynonymous mutations in each subspecies. The strength of purifying selection we infer is congruent with the differences in effective sizes of each subspecies: Central chimpanzees are undergoing the strongest purifying selection followed by Eastern and Western chimpanzees. Coding indels show stronger selection against indels changing the reading frame than observed in human populations.

Screening of compound libraries against panels of targets yields profiling matrices. Such matrices typically contain structurally diverse screening compounds, large numbers of inactives, and small numbers of hits per assay. As such, they represent interesting and challenging test cases for computational screening and activity predictions. In this work, modeling of large compound profiling matrices was attempted that were extracted from publicly available screening data. Different machine learning methods including deep learning were compared and different prediction strategies explored. Prediction accuracy varied for assays with different numbers of active compounds, and alternative machine learning approaches often produced comparable results. Deep learning did not further increase the prediction accuracy of standard methods such as random forests or support vector machines. Target-based random forest models were prioritized and yielded successful predictions of active compounds for many assays.

The human macula is more susceptible than the peripheral retina to developing blinding conditions such as age-related macular degeneration, diabetic retinopathy. A key difference between them may be the nature of their Müller cells. We found primary cultured Müller cells from macula and peripheral retina display significant morphological and transcriptomic differences. Macular Müller cells expressed more phosphoglycerate dehydrogenase (PHGDH, a rate-limiting enzyme in serine synthesis) than peripheral Müller cells. The serine synthesis, glycolytic and mitochondrial function were more activated in macular than peripheral Müller cells. Serine biosynthesis is critical in defending against oxidative stress. Intracellular reactive oxygen species and glutathione levels were increased in primary cultured macular Müller cells which were more susceptible to oxidative stress after inhibition of PHGDH. Our findings indicate serine biosynthesis is a critical part of the macular defence against oxidative stress and suggest dysregulation of this pathway as a potential cause of macular pathology.

PMM2-CDG, is the most common N-linked glycosylation disorder and subtype among all CDG syndromes, which are a series of genetic disorders involving the synthesis and attachment of glycoproteins and glycolipid glycans. The mutations of PMM2-CDG might lead to the loss of PMM2, which is responsible for the conversion of mannose 6- phosphate into mannose 1-phosphate. Most patients with PMM2-CDG have central nervous system involvement, abnormal coagulation, and hepatopathy. The neurological symptoms of PMM2-CDG are intellectual disability (ID), cerebellar ataxia, and peripheral neuropathy. Now, over 100 new CDG cases have been reported. However, each type of CDG is very rare, and CDGs are problematic to diagnose. In addition, few CDGs have been reported in the Chinese population.

Single-nucleotide polymorphism (SNP) markers and high-density genetic maps are important resources for marker-assisted selection, mapping of quantitative trait loci (QTLs) and genome structure analysis. Although linkage maps in certain catfish species have been obtained, high-density maps remain unavailable in the economically important southern catfish (Silurus meridionalis). Recently developed restriction site-associated DNA (RAD) markers have proved to be a promising tool for SNP detection and genetic map construction. The objective of the present study was to construct a high-density linkage map using SNPs generated by next-generation RAD sequencing in S. meridionalis for future genetic and genomic studies. An F1 population of 100 individuals was obtained by intraspecific crossing of two wild heterozygous individuals. In total, 77 634 putative high-quality bi-allelic SNPs between the parents were discovered by mapping the parents' paired-end RAD reads onto the reference contigs from both parents, of which 54.7% were transitions and 45.3% were transversions (transition/transversion ratio of 1.2). Finally, 26 714 high-quality RAD markers were grouped into 29 linkage groups by using de novo clustering methods (Stacks). Among these markers, 4514 were linked to the female genetic map, 23 718 to the male map and 6715 effective loci were linked to the integrated map spanning 5918.31 centimorgans (cM), with an average marker interval of 0.89 cM. High-resolution genetic maps are a useful tool for both marker-assisted breeding and various genome investigations in catfish, such as sequence assembly, gene localization, QTL detection and genome structure comparison. Hence, such a high-density linkage map will serve as a valuable resource for comparative genomics and fine-scale QTL mapping in catfish species.

To establish a three-step programmed method to find gene mutations related to maturity onset diabetes of the young (MODY). Target region capture and next-generation sequencing (NGS) were performed using customized oligonucleotide probes designed to capture suspected genes for MODY in 11 probands with clinically diagnosed MODY. The suspected associations of certain genes with MODY were then confirmed by Sanger sequencing in the probands and their family members. Finally, to validate variants of one of the genes of interest (glucokinase, GCK) as pathogenic mutations, protein function editing by the variant genes was assessed. In the target region capture and NGS phase, a total of nine variants of seven genes (GCK, WFS1, SLC19A2, SH2B1, SERPINB4, RFX6, and GATA6) were identified in eight probands. Two heterozygous GCK mutations located on the same allele (p.Leu77Arg and p.Val101Met) were identified in a MODY family. Sanger sequencing was used to confirm the variants identified by NGS to be present in probands and their diabetic family members, but not in non-diabetic family members. Finally, enzyme kinetic and thermal stability analyses revealed that the p.Leu77Arg mutation or the p.Leu77Arg mutation in combination with the p.Val101Met mutation inactivates GCK function and stability, while mutation of p.Val101Met alone does not. The p.Leu77Arg but not p.Val101Met GCK mutation is therefore considered a pathogenic mutation associated with MODY. Genetic screening coupled with gene-editing protein function testing is an effective and reliable method by which causative gene mutations of MODY can be identified.

Recently, the heterogeneity that arises from stochastic fate decisions has been reported for several types of cancer-derived cell lines and several types of clonal cells grown under constant environmental conditions. However, the relation between this stochasticity and the responsiveness to extracellular stimuli remains largely unknown. Here we focused on the fate decisions of the PC12 cell line, which was derived from rat pheochromocytoma, and is a model system to study differentiation into sympathetic neurons. Whereas epidermal growth factor (EGF) stimulates the proliferation of populations of PC12 cells, nerve growth factor (NGF) promotes the differentiation of neurites to neuron-like cells. We found that phenotypic heterogeneity increased with time at several surrounding serum concentrations, suggesting stochastic cell-fate decisions in single cells. We made a simple mathematical model assuming Markovian transitions of the cell fates, and estimated the transition rates based on Bayes' theorem. The model suggests that depending on the serum concentration, EGF (NGF) even directs differentiation (proliferation) at the single-cell level. The maximum effects of the growth factors were ensured when the transition rates were appropriately controlled by the serum concentration to produce a nonextremal, moderate amount of cell-fate heterogeneity. Our model was validated by the experimental finding that the means and variances of the local cell densities obey a power-law relationship. These results suggest that even when efficient responses to growth factors are observed at the population level, the growth factors stochastically direct the cell-fate decisions in different directions at the single-cell level.