Whole-genome Single Nucleotide Polymorphism Research Articles

Application of chromosome microarray analysis in patients with unexplained developmental delay/intellectual disability in South China

Chromosome microarray analysis (CMA) is currently the first-tier diagnostic assay for the evaluation of developmental delay (DD) and intellectual disability (ID) with unknown etiology. Here, we present our clinical experience in implementing whole-genome high-resolution single nucleotide polymorphism (SNP) arrays to investigate 489 patients with unexplained DD/ID in whom standard karyotyping analyses showed normal karyotypes. This study aimed to assess the usefulness of CMA for clinical diagnostic testing in the Chinese population. A total of 489 children were classified into three groups: isolated DD/ID (n=358), DD/ID with epilepsy (n=49), and DD/ID with other structural anomalies (n=82). We identified 126 cases (25.8%, 126/489) of pathogenic copy number variants (CNVs) by CMA, including 89 (24.9%, 89/358) with isolated DD/ID, 13 (26.5%, 13/49) with DD/ID with epilepsy, and 24 (29.3%, 24/82) with DD/ID with other structural anomalies. Among the 126 cases of pathogenic CNVs, 79 cases were identified as microdeletion/microduplication syndromes, among which 76 cases were classified as common syndromes, and 3 cases were classified as rare syndromes, including 15q24 microdeletion syndrome, Xq28 microduplication syndrome and Lowe syndrome. Additionally, there were forty-seven cases of non-syndromic pathogenic CNVs. The ABAT, FTSJ1, DYNC1H1, and SETBP1 genes were identified as DD/ID candidate genes. Our findings suggest the necessity of CMA as a routine diagnostic test for unexplained DD/ID in South China.

A nested mixture model for genomic prediction using whole-genome SNP genotypes.

Genomic prediction exploits single nucleotide polymorphisms (SNPs) across the whole genome for predicting genetic merit of selection candidates. In most models for genomic prediction, e.g. BayesA, B, C, R and GBLUP, independence of SNP effects is assumed. However, SNP effects are expected to be locally dependent given the presence of a nearby QTL because SNPs surrounding the QTL do not segregate independently. A consequence of ignoring this dependence is that SNPs with small effects may be overly shrunk, e.g. effects from markers with high minor allele frequencies (MAF) that flank QTL with low MAF. A nested mixture model (BayesN) is developed to account for the dependence of effects of SNPs that are closely linked, where the effects of SNPs in every non-overlapping genomic window a priori follow a point mass at zero for all SNPs or a mixture of some SNPs with nonzero effects and others with zero effects. It can be regarded as a parsimonious alternative to the existing antedependence model, antiBayesB, which allow a nonstationary dependence of SNP effects. Illumina 777K BovineHD genotypes from 948 Angus cattle were used to simulate 5,000 offspring, with 4,000 used for training and 1,000 for validation. Scenarios with 300 common (MAF > 0.05) or rare (MAF < 0.05) QTL randomly selected from segregating SNPs were replicated 8 times. SNPs corresponding to QTL were masked from a 600k panel comprising SNPs with MAF > 0.05 or a 50k evenly spaced subset of these. Compared with BayesB and a modified antiBayesB, BayesN improved the accuracy of prediction up to 2.0% with 50k SNPs and up to 7.0% with 600k SNPs, most improvements occurring in the rare QTL scenario. Computing time was reduced up to 60% with 50k SNPs and up to 75% with 600k SNPs. BayesN is an accurate and computationally efficient method for genomic prediction with whole-genome SNPs, especially for traits with rare QTL.

Regional Heritability Mapping Provides Insights into Dry Matter Content in African White and Yellow Cassava Populations.

The HarvestPlus program for cassava (Manihot esculenta Crantz) fortifies cassava with β-carotene by breeding for carotene-rich tubers (yellow cassava). However, a negative correlation between yellowness and dry matter (DM) content has been identified. We investigated the genetic control of DM in white and yellow cassava. We used regional heritability mapping (RHM) to associate DM with genomic segments in both subpopulations. Significant segments were subjected to candidate gene analysis and candidates were validated with prediction accuracies. The RHM procedure was validated via a simulation approach and revealed significant hits for white cassava on chromosomes 1, 4, 5, 10, 17, and 18, whereas hits for the yellow were on chromosome 1. Candidate gene analysis revealed genes in the carbohydrate biosynthesis pathway including plant serine–threonine protein kinases (SnRKs), UDP (uridine diphosphate)-glycosyltransferases, UDP-sugar transporters, invertases, pectinases, and regulons. Validation using 1252 unique identifiers from the SnRK gene family genome-wide recovered 50% of the predictive accuracy of whole-genome single nucleotide polymorphisms for DM, whereas validation using 53 likely genes (extracted from the literature) from significant segments recovered 32%. Genes including an acid invertase, a neutral or alkaline invertase, and a glucose-6-phosphate isomerase were validated on the basis of an a priori list for the cassava starch pathway, and also a fructose-biphosphate aldolase from the Calvin cycle pathway. The power of the RHM procedure was estimated as 47% when the causal quantitative trait loci generated 10% of the phenotypic variance (sample size = 451). Cassava DM genetics are complex and RHM may be useful for complex traits.

Salmonella Gallinarum field isolates and its relationship to vaccine strain SG9R

ABSTRACT1. The aim of the present study was to determine if the 9R-strain of the Salmonella Gallinarum live vaccine was responsible for having fowl typhoid outbreaks in chicken flocks from both chicken and turkey breeders as well as to verify the antimicrobial resistance of the isolates from the outbreaks.2. The triplex polymerase chain reaction, standard antimicrobial test, beta-lactamase genes identification and Ion Torrent PMG whole-genome sequence were used in the field isolates and in the vaccine strain of S. Gallinarum.3. The 60 tested isolates were not from vaccine origin and manifested high resistance to drugs from macrolide and quinolone groups. Whole-genome sequencing (WGS) and single nucleotide polymorphism analysis on selected isolates for core genes from Salmonella enterica confirmed the wild origin of these isolates and showed two possible sources of S. Gallinarum in the studied outbreaks.4. S. Gallinarum isolated from fowl typhoid outbreaks in the studied period were not caused by the use of the SG9R live vaccine. The source of strains sequenced was diverse.

Evaluation of methods and marker Systems in Genomic Selection of oil palm (Elaeis guineensis Jacq.)

BackgroundGenomic selection (GS) uses genome-wide markers as an attempt to accelerate genetic gain in breeding programs of both animals and plants. This approach is particularly useful for perennial crops such as oil palm, which have long breeding cycles, and for which the optimal method for GS is still under debate. In this study, we evaluated the effect of different marker systems and modeling methods for implementing GS in an introgressed dura family derived from a Deli dura x Nigerian dura (Deli x Nigerian) with 112 individuals. This family is an important breeding source for developing new mother palms for superior oil yield and bunch characters. The traits of interest selected for this study were fruit-to-bunch (F/B), shell-to-fruit (S/F), kernel-to-fruit (K/F), mesocarp-to-fruit (M/F), oil per palm (O/P) and oil-to-dry mesocarp (O/DM). The marker systems evaluated were simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). RR-BLUP, Bayesian A, B, Cπ, LASSO, Ridge Regression and two machine learning methods (SVM and Random Forest) were used to evaluate GS accuracy of the traits.ResultsThe kinship coefficient between individuals in this family ranged from 0.35 to 0.62. S/F and O/DM had the highest genomic heritability, whereas F/B and O/P had the lowest. The accuracies using 135 SSRs were low, with accuracies of the traits around 0.20. The average accuracy of machine learning methods was 0.24, as compared to 0.20 achieved by other methods. The trait with the highest mean accuracy was F/B (0.28), while the lowest were both M/F and O/P (0.18). By using whole genomic SNPs, the accuracies for all traits, especially for O/DM (0.43), S/F (0.39) and M/F (0.30) were improved. The average accuracy of machine learning methods was 0.32, compared to 0.31 achieved by other methods.ConclusionDue to high genomic resolution, the use of whole-genome SNPs improved the efficiency of GS dramatically for oil palm and is recommended for dura breeding programs. Machine learning slightly outperformed other methods, but required parameters optimization for GS implementation.

Rationale and design of GENEiUS: a prospective observational study on the genetic and environmental determinants of body mass index evolution in Canadian undergraduate students

IntroductionObesity is a global epidemic and is a risk factor for developing other comorbidities. Young adulthood is a critical period for body weight change and establishing healthy lifestyle behaviours. The...

Investigation on the relationship between oxidative stress and cognitive neuropsychology status in patients with MS

Salmonella enterica serovar Gallinarum biovar Pullorum (S. Pullorum) is the cause of pullorum disease, characterized by white diarrhea, which leads to high mortality in poultry. In this study, we aimed to assess the genetic diversity of 655 S. Pullorum strains from 1962 to 2015 in China, Europe, and South America. A sequence typing scheme based on clustered regularly interspaced short palindromic repeats (CRISPR) was used to reveal the genetic relationships among these strains in this study. Overall, a total of 20 Pullorum sequence types (PSTs) of CRISPR were identified in the 655 isolates with PST7 (74%, 486/655) and PST3 (13%, 86/655) to be the most two frequent PSTs belonging to two different lineages, which confirmed the genetic conservation of S. Pullorum strains isolated from six provinces and two direct-controlled municipalities (Beijing and Shanghai) in China. However, the identification of seven new PSTs distributed in strains isolated since 2001 implied that genetic variation continues to develop in S. Pullorum. Interestingly, the whole-genome single-nucleotide polymorphism typing (WGST) of 96 strains out of the 655 isolates divided them into four lineages based on SNP analysis of core genomic sequence and exhibit good correspondence with the CRISPR subtyping method. Notably, 22 out of 26 isolates from Europe and South America were distributed in five distinctive PSTs (with no Chinese strains). Additionally, CRISPR data of spacers and their arrangement exhibit subtle but distinct specificity between different strains, and the dynamic adaptive nature of CRISPR loci provides critical insights into the evolution of S. Pullorum as the bacteria are influenced by their environment.

Genome-Wide Association Study of Major Agronomic Traits Related to Domestication in Peanut.

Peanut (Arachis hypogaea) consists of two subspecies, hypogaea and fastigiata, and has been cultivated worldwide for hundreds of years. Here, 158 peanut accessions were selected to dissect the molecular footprint of agronomic traits related to domestication using specific-locus amplified fragment sequencing (SLAF-seq method). Then, a total of 17,338 high-quality single nucleotide polymorphisms (SNPs) in the whole peanut genome were revealed. Eleven agronomic traits in 158 peanut accessions were subsequently analyzed using genome-wide association studies (GWAS). Candidate genes responsible for corresponding traits were then analyzed in genomic regions surrounding the peak SNPs, and 1,429 genes were found within 200 kb windows centerd on GWAS-identified peak SNPs related to domestication. Highly differentiated genomic regions were observed between hypogaea and fastigiata accessions using FST values and sequence diversity (π) ratios. Among the 1,429 genes, 662 were located on chromosome A3, suggesting the presence of major selective sweeps caused by artificial selection during long domestication. These findings provide a promising insight into the complicated genetic architecture of domestication-related traits in peanut, and reveal whole-genome SNP markers of beneficial candidate genes for marker-assisted selection (MAS) in future breeding programs.

696 Whole-genome single nucleotide polymorphism study of Romanov sheep

696 Whole-genome single nucleotide polymorphism study of Romanov sheep

Clonal composition of human ovarian cancer based on copy number analysis reveals a reciprocal relation with oncogenic mutation status

Intratumoral heterogeneity of cancer cells remains largely unexplored. Here we investigated the composition of ovarian cancer and its biological relevance. A whole-genome single nucleotide polymorphism array was applied to detect the clonal composition of 24 formalin-fixed, paraffin-embedded samples of human ovarian cancer. Genome-wide segmentation data consisting of the log2 ratio (log2R) and B allele frequency (BAF) were used to calculate an estimate of the clonal composition number (CC number) for each tumor. Somatic mutation profiles of cancer-related genes were also determined for the same 24 samples by next-generation sequencing. The CC number was estimated successfully for 23 of the 24 cancer samples. The mean ± SD value for the CC number was 1.7 ± 1.1 (range of 0–4). A somatic mutation in at least one gene was identified in 22 of the 24 ovarian cancer samples, with the mutations including those in the oncogenes KRAS (29.2%), PIK3CA (12.5%), BRAF (8.3%), FGFR2 (4.2%), and JAK2 (4.2%) as well as those in the tumor suppressor genes TP53 (54.2%), FBXW7 (8.3%), PTEN (4.2%), and RB1 (4.2%). Tumors with one or more oncogenic mutations had a significantly lower CC number than did those without such a mutation (1.0 ± 0.8 versus 2.3 ± 0.9, P = 0.0027), suggesting that cancers with driver oncogene mutations are less heterogeneous than those with other mutations. Our results thus reveal a reciprocal relation between oncogenic mutation status and clonal composition in ovarian cancer using the established method for the estimation of the CC number.

TSGSIS: a high-dimensional grouped variable selection approach for detection of whole-genome SNP-SNP interactions.

Identification of single nucleotide polymorphism (SNP) interactions is an important and challenging topic in genome-wide association studies (GWAS). Many approaches have been applied to detecting whole-genome interactions. However, these approaches to interaction analysis tend to miss causal interaction effects when the individual marginal effects are uncorrelated to trait, while their interaction effects are highly associated with the trait. A grouped variable selection technique, called two-stage grouped sure independence screening (TS-GSIS), is developed to study interactions that may not have marginal effects. The proposed TS-GSIS is shown to be very helpful in identifying not only causal SNP effects that are uncorrelated to trait but also their corresponding SNP-SNP interaction effects. The benefit of TS-GSIS are gaining detection of interaction effects by taking the joint information among the SNPs and determining the size of candidate sets in the model. Simulation studies under various scenarios are performed to compare performance of TS-GSIS and current approaches. We also apply our approach to a real rheumatoid arthritis (RA) dataset. Both the simulation and real data studies show that the TS-GSIS performs very well in detecting SNP-SNP interactions. R-package is delivered through CRAN and is available at: https://cran.r-project.org/web/packages/TSGSIS/index.html. hsiung@nhri.org.tw. Supplementary data are available at Bioinformatics online.

Prediction of maize phenotype based on whole-genome single nucleotide polymorphisms using deep belief networks

Selection in plant breeding could be more effective and more efficient if it is based on genomic data. Genomic selection (GS) is a new approach for plant-breeding selection that exploits genomic data through a mechanism called genomic prediction (GP). Most of GP models used linear methods that ignore effects of interaction among genes and effects of higher order nonlinearities. Deep belief network (DBN), one of the architectural in deep learning methods, is able to model data in high level of abstraction that involves nonlinearities effects of the data. This study implemented DBN for developing a GP model utilizing whole-genome Single Nucleotide Polymorphisms (SNPs) as data for training and testing. The case study was a set of traits in maize. The maize dataset was acquisitioned from CIMMYT’s (International Maize and Wheat Improvement Center) Global Maize program. Based on Pearson correlation, DBN is outperformed than other methods, kernel Hilbert space (RKHS) regression, Bayesian LASSO (BL), best linear unbiased predictor (BLUP), in case allegedly non-additive traits. DBN achieves correlation of 0.579 within -1 to 1 range.

Genetic analysis of Salmonella enterica serovar Gallinarum biovar Pullorum based on characterization and evolution of CRISPR sequence

Salmonella enterica serovar Gallinarum biovar Pullorum (S. Pullorum) is the cause of pullorum disease, characterized by white diarrhea, which leads to high mortality in poultry. In this study, we aimed to assess the genetic diversity of 655 S. Pullorum strains from 1962 to 2015 in China, Europe, and South America. A sequence typing scheme based on clustered regularly interspaced short palindromic repeats (CRISPR) was used to reveal the genetic relationships among these strains in this study. Overall, a total of 20 Pullorum sequence types (PSTs) of CRISPR were identified in the 655 isolates with PST7 (74%, 486/655) and PST3 (13%, 86/655) to be the most two frequent PSTs belonging to two different lineages, which confirmed the genetic conservation of S. Pullorum strains isolated from six provinces and two direct-controlled municipalities (Beijing and Shanghai) in China. However, the identification of seven new PSTs distributed in strains isolated since 2001 implied that genetic variation continues to develop in S. Pullorum. Interestingly, the whole-genome single-nucleotide polymorphism typing (WGST) of 96 strains out of the 655 isolates divided them into four lineages based on SNP analysis of core genomic sequence and exhibit good correspondence with the CRISPR subtyping method. Notably, 22 out of 26 isolates from Europe and South America were distributed in five distinctive PSTs (with no Chinese strains). Additionally, CRISPR data of spacers and their arrangement exhibit subtle but distinct specificity between different strains, and the dynamic adaptive nature of CRISPR loci provides critical insights into the evolution of S. Pullorum as the bacteria are influenced by their environment.

Pudong White pig: a unique genetic resource disclosed by sequencing data

Pudong White (PW) pigs are distributed in the Taihu region of China and are characterized by their completely white coats. A heated debate concerning this genetic resource and its relationship to Taihu and western pig breeds has arisen, due to the white coat of the animals. To determine whether PW is a unique genetic resource, we performed a detailed assessment of the genetic relationships among PW, six breeds from the Taihu population and three western pig breeds, based on whole-genome single nucleotide polymorphism (SNP) data. A total of 68 102 SNPs were identified in the genomes of the tested populations by next-generation sequencing technology, of which, 64 were determined as the potentially specific to PW breed. The genetic distance between PW pigs and the Taihu population was shorter than that between PW and western breeds. The genetic distance within the PW population was small and neighbour-joining tree analysis revealed that all PW individuals clustered into a separated group, indicating a close genetic relationship among PW individuals which may result from a small effective population size (Ne) and inbreeding. The results of both principal component analysis and evaluation using fastSTRUCTURE demonstrated that PW was clearly differentiated from other breeds. Together, these results indicate that PW is a distinctive genetic resource with a unique genetic structure separate from other Taihu and western pig breeds. Furthermore, this genome-wide comprehensive survey of the relationships among PW, Taihu and western pig breeds, demonstrates the rationality of the current breed classification of PW. The results also provide evidence about the unique genetic resource of PW, based on genome-wide genetic markers. These data will improve our understanding of the genetic structure and current state of PW breed, and facilitate the development of a national project for the conservation and utilization of these pigs.

A Common Ancestral Asn242Ser Mutation in TMEM67 Identified in Multiple Iranian Families with Joubert Syndrome

Background: Joubert syndrome (JS) is a clinically and genetically heterogeneous group of rare neurodevelopmental disorder characterised by peculiar midbrain-hindbrain malformation, known as the “molar tooth” sign. JS can manifest a broad range of signs and symptoms. The most common features of JS are hypotonia, ataxia, developmental delay/intellectual disability, abnormal eye movements, and neonatal breathing abnormalities. To date, 29 genes have been shown to cause JS. Methods: We employed whole-genome single nucleotide polymorphism genotyping in a group of Iranian families with JS and Sanger sequencing of a known mutation associated with JS located in a single homozygous regions shared by affected members of the families. Results: Homozygosity mapping uncovered a shared ∼2.2-Mb run of homozygosity on chromosome 8q21.3-q22.1 encompassing the known JS-causing TMEM67 gene. Sanger sequencing of a known mutation (NM_153704.5: c.725A>G; p.Asn242Ser) in TMEM67 identified from studying another Iranian family using whole-exome sequencing confirmed the presence of the homozygous mutation in 22 affected members of 12 nuclear families. “Molar tooth” sign of brain magnetic resonance imaging, moderate-to-severe neurodevelopmental delay, and abnormal eye movements were the most common features of affected individuals. In addition, liver disease, seizure, behavioural abnormalities, failure to thrive, and kidney disease were observed variably in some of the patients. Conclusion: We propose that Asn242Ser is a founder mutation in the Iranian population, which might explain a significant proportion of JS cases from eastern Iran. Therefore, screening for this variant should be considered for genetic testing in Iranian patients with JS. In addition, this finding is important for developing population-specific genetic testing in Iran.

Whole-genome single-nucleotide polymorphism (SNP) marker discovery and association analysis with the eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) content in Larimichthys crocea.

Whole-genome single-nucleotide polymorphism (SNP) markers are valuable genetic resources for the association and conservation studies. Genome-wide SNP development in many teleost species are still challenging because of the genome complexity and the cost of re-sequencing. Genotyping-By-Sequencing (GBS) provided an efficient reduced representative method to squeeze cost for SNP detection; however, most of recent GBS applications were reported on plant organisms. In this work, we used an EcoRI-NlaIII based GBS protocol to teleost large yellow croaker, an important commercial fish in China and East-Asia, and reported the first whole-genome SNP development for the species. 69,845 high quality SNP markers that evenly distributed along genome were detected in at least 80% of 500 individuals. Nearly 95% randomly selected genotypes were successfully validated by Sequenom MassARRAY assay. The association studies with the muscle eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) content discovered 39 significant SNP markers, contributing as high up to ∼63% genetic variance that explained by all markers. Functional genes that involved in fat digestion and absorption pathway were identified, such as APOB, CRAT and OSBPL10. Notably, PPT2 Gene, previously identified in the association study of the plasma n-3 and n-6 polyunsaturated fatty acid level in human, was re-discovered in large yellow croaker. Our study verified that EcoRI-NlaIII based GBS could produce quality SNP markers in a cost-efficient manner in teleost genome. The developed SNP markers and the EPA and DHA associated SNP loci provided invaluable resources for the population structure, conservation genetics and genomic selection of large yellow croaker and other fish organisms.

Comparative genomics of Bacillus anthracis from the wool industry highlights polymorphisms of lineage A.Br.Vollum

BackgroundWith the advent of affordable next-generation sequencing (NGS) technologies, major progress has been made in the understanding of the population structure and evolution of the B. anthracis species. Here we report the use of whole genome sequencing and computer-based comparative analyses to characterize six strains belonging to the A.Br.Vollum lineage. These strains were isolated in Switzerland, in 1981, during iterative cases of anthrax involving workers in a textile plant processing cashmere wool from the Indian subcontinent. ResultsWe took advantage of the hundreds of currently available B. anthracis genomes in public databases, to investigate the genetic diversity existing within the A.Br.Vollum lineage and to position the six Swiss isolates into the worldwide B. anthracis phylogeny. Thirty additional genomes related to the A.Br.Vollum group were identified by whole-genome single nucleotide polymorphism (SNP) analysis, including two strains forming a new evolutionary branch at the basis of the A.Br.Vollum lineage. This new phylogenetic lineage (termed A.Br.H9401) splits off the branch leading to the A.Br.Vollum group soon after its divergence to the other lineages of the major A clade (i.e. 6 SNPs). The available dataset of A.Br.Vollum genomes were resolved into 2 distinct groups. Isolates from the Swiss wool processing facility clustered together with two strains from Pakistan and one strain of unknown origin isolated from yarn. They were clearly differentiated (69 SNPs) from the twenty-five other A.Br.Vollum strains located on the branch leading to the terminal reference strain A0488 of the lineage. Novel analytic assays specific to these new subgroups were developed for the purpose of rapid molecular epidemiology. ConclusionsWhole genome SNP surveys greatly expand upon our knowledge on the sub-structure of the A.Br.Vollum lineage. Possible origin and route of spread of this lineage worldwide are discussed.

Copy-number variation is an important contributor to the genetic causality of inherited retinal degenerations.

PurposeDespite substantial progress in sequencing, current strategies can genetically solve only about 55–60% of inherited retinal degeneration (IRD) cases. This can partially be attributed to elusive mutations in the known IRD genes, which are not easily identified by the targeted next-generation sequencing (NGS) or Sanger sequencing approaches. We hypothesized that copy number variations (CNVs) are a major contributor to the elusive genetic causality of IRDs.MethodsTwenty-eight patients, previously unsolved with a targeted NGS, were investigated with whole-genome SNP and CGH arrays.ResultsDeletions in the IRD genes were detected in five of twenty-eight families, including a de novo deletion. We suggest that the de novo deletion occurred through non-allelic homologous recombination (NAHR) and we constructed a genomic map of NAHR-prone regions with overlapping IRD genes. In this study we also report an unusual case of recessive retinitis pigmentosa due to compound heterozygous mutations in SNRNP200, a gene that is typically associated with the dominant form of this disease.ConclusionsCNV mapping substantially increased the genetic diagnostic rate of IRDs, detecting genetic causality in 18% of previously unsolved cases. Extending the search to other structural variations (SVs) will likely demonstrate an even higher contribution to genetic causality of IRDs.

Molecular Breeding of Rice Restorer Lines and Hybrids for Brown Planthopper (BPH) Resistance Using the Bph14 and Bph15 Genes.

BackgroundThe development of hybrid rice is a practical approach for increasing rice production. However, the brown planthopper (BPH), Nilaparvata lugens Stål, causes severe yield loss of rice (Oryza sativa L.) and can threaten food security. Therefore, breeding hybrid rice resistant to BPH is the most effective and economical strategy to maintain high and stable production. Fortunately, numerous BPH resistance genes have been identified, and abundant linkage markers are available for molecular marker-assisted selection (MAS) in breeding programs. Hence, we pyramided two BPH resistance genes, Bph14 and Bph15, into a susceptive CMS restorer line Huahui938 and its derived hybrids using MAS to improve the BPH resistance of hybrid rice.ResultsThree near-isogenic lines (NILs) with pyramided Bph14 and Bph15 were obtained by molecular marker-assisted backcross (MAB) and phenotypic selection. The genomic components of these NILs were detected using the whole-genome SNP (Single nucleotide polymorphism) array, RICE6K, suggesting that the recurrent parent genome (RPG) recovery of the NILs was 87.88, 87.70 and 86.62 %, respectively. BPH bioassays showed that the improved NILs and their derived hybrids carrying homozygous Bph14 and Bph15 were resistant to BPH. However, the hybrids with heterozygous Bph14 and Bph15 remained susceptible to BPH. The developed NILs showed no significant differences in major agronomic traits and rice qualities compared with the recurrent parent. Moreover, the improved hybrids derived from the NILs exhibited better agronomic performance and rice quality compared with the controls under natural field conditions.ConclusionsThis study demonstrates that it is essential to stack Bph14 and Bph15 into both the maternal and paternal parents for developing BPH-resistant hybrid rice varieties. The SNP array with abundant DNA markers is an efficient tool for analyzing the RPG recovery of progenies and can be used to monitor the donor segments in NILs, thus being extremely important for rice molecular breeding.

A Bacillus anthracis Genome Sequence from the Sverdlovsk 1979 Autopsy Specimens.

ABSTRACTAnthrax is a zoonotic disease that occurs naturally in wild and domestic animals but has been used by both state-sponsored programs and terrorists as a biological weapon. A Soviet industrial production facility in Sverdlovsk, USSR, proved deficient in 1979 when a plume of spores was accidentally released and resulted in one of the largest known human anthrax outbreaks. In order to understand this outbreak and others, we generated a Bacillus anthracis population genetic database based upon whole-genome analysis to identify all single-nucleotide polymorphisms (SNPs) across a reference genome. Phylogenetic analysis has defined three major clades (A, B, and C), B and C being relatively rare compared to A. The A clade has numerous subclades, including a major polytomy named the trans-Eurasian (TEA) group. The TEA radiation is a dominant evolutionary feature of B. anthracis, with many contemporary populations having resulted from a large spatial dispersal of spores from a single source. Two autopsy specimens from the Sverdlovsk outbreak were deep sequenced to produce draft B. anthracis genomes. This allowed the phylogenetic placement of the Sverdlovsk strain into a clade with two Asian live vaccine strains, including the Russian Tsiankovskii strain. The genome was examined for evidence of drug resistance manipulation or other genetic engineering, but none was found. The Soviet Sverdlovsk strain genome is consistent with a wild-type strain from Russia that had no evidence of genetic manipulation during its industrial production. This work provides insights into the world’s largest biological weapons program and provides an extensive B. anthracis phylogenetic reference.