Springer Science and Business Media LLC

Copy number variation (CNV) in the human genome is recognised as a widespread and important source of human genetic variation. Now the challenge is to screen for these CNVs at high resolution in a reliable, accurate and cost-effective way. Multiplex Amplifiable Probe Hybridisation (MAPH) is a sensitive, high-resolution technology appropriate for screening for CNVs in a defined region, for a targeted population. We have developed MAPH to a highly multiplexed format ("QuadMAPH") that allows the user a four-fold increase in the number of loci tested simultaneously. We have used this method to analyse a genomic region of 210 kb, including the MSH2 gene and 120 kb of flanking DNA. We show that the QuadMAPH probes report copy number with equivalent accuracy to simplex MAPH, reliably demonstrating diploid copy number in control samples and accurately detecting deletions in Hereditary Non-Polyposis Colorectal Cancer (HNPCC) samples. QuadMAPH is an accurate, high-resolution method that allows targeted screening of large numbers of subjects without the expense of genome-wide approaches. Whilst we have applied this technique to a region of the human genome, it is equally applicable to the genomes of other organisms.

Chimeric transcripts, including partial and internal tandem duplications (PTDs, ITDs) and gene fusions, are important in the detection, prognosis, and treatment of human cancers. We describe Barnacle, a production-grade analysis tool that detects such chimeras in de novo assemblies of RNA-seq data, and supports prioritizing them for review and validation by reporting the relative coverage of co-occurring chimeric and wild-type transcripts. We demonstrate applications in large-scale disease studies, by identifying PTDs in MLL, ITDs in FLT3, and reciprocal fusions between PML and RARA, in two deeply sequenced acute myeloid leukemia (AML) RNA-seq datasets. Our analyses of real and simulated data sets show that, with appropriate filter settings, Barnacle makes highly specific predictions for three types of chimeric transcripts that are important in a range of cancers: PTDs, ITDs, and fusions. High specificity makes manual review and validation efficient, which is necessary in large-scale disease studies. Characterizing an extended range of chimera types will help generate insights into progression, treatment, and outcomes for complex diseases.

In cold regions, low temperature is the main limiting factor affecting grape production. As an important breeding resource, V. amurensis Rupr. has played a crucial role in the discovery of genes which confer cold resistance in grapes. Thus far, many cold-resistance genes have been reported based on the study of V. amurensis. In order to identify more candidate genes related to cold resistance in V. amurensis, QTL mapping and RNA-seq was conducted based on the hybrid population and different cold-resistance cultivars in this study. In this study, highly cold-resistant grape cultivar ‘Shuangyou’ (SY) which belongs to V. amurensis, and cold-sensitive cultivar ‘Red Globe’ (RG) which belongs to Vitis vinifera L. were used to identify cold resistance genes. Cold-resistance quantitative trait locus (QTL) mapping was performed based on genetic population construction through interspecific crossing of ‘Shuangyou’ and ‘Red Globe’. Additionally, transcriptome analysis was conducted for the dormant buds of these two cultivars at different periods. Based on transcriptome analysis and QTL mapping, many new structural genes and transcription factors which relate to V. amurensis cold resistance were discovered, including CORs (VaCOR413IM), GSTs (VaGST-APIC, VaGST-PARB, VaGSTF9 and VaGSTF13), ARFs (VaIAA27 and VaSAUR71), ERFs (VaAIL1), MYBs (VaMYBR2, VaMYBLL and VaMYB3R-1) and bHLHs (VaICE1 and VabHLH30). This discovery of candidate cold-resistance genes will provide an important theoretical reference for grape cold-resistance mechanisms, research, and cold-resistant grape cultivar breeding in the future.

Genome-wide association studies (GWAS) have generated a wealth of valuable genotyping data for complex diseases/traits. A large proportion of these data are embedded with many weakly associated markers that have been missed in traditional single marker analyses, but they may provide valuable insights in dissecting the genetic components of diseases. Gene set analysis (GSA) augmented by protein-protein interaction network data provides a promising way to examine GWAS data by analyzing the combined effects of multiple genes/markers, each of which may have only individually weak to moderate association effects. A critical issue in GSA of GWAS data is the definition of gene-wise P values based on multiple SNPs mapped to a gene. In this study, we proposed an alternative restricted search approach based on our previously developed dense module search algorithm, and we demonstrated it in the CATIE GWAS dataset for schizophrenia. Specifically, we explored three ways of computing gene-wise P values and examined their effects on the resultant module genes. These methods calculate gene-wise P values based on all the SNPs, the top ranked SNPs, or the most significant SNP among all the SNPs mapped to a gene. We applied the restricted search approach and identified a module gene set for each of the gene-wise P value data set. In our evaluation using an independent method, ALIGATOR, we showed that although each of these input datasets generated a unique set of module genes, all of them were significant in the GWAS dataset. Further functional enrichment analysis of these module genes showed that at the pathway level, they were all consistently related to neuro- and immune-related pathways. Finally, we compared our method with a previously reported method. Our results showed that the approaches to computing gene-wise P values in GWAS data are critical in GSA. This work is useful for evaluating key factors in GSA of GWAS data.

The Djallonke sheep is well adapted to harsh environmental conditions, and is relatively resistant to Haemonchosis and resilient to animal trypanosomiasis. The larger Sahelian sheep, which cohabit the same region, is less well adapted to these disease challenges. Haemonchosis and Trypanosomiasis collectively cost the worldwide animal industry billions of dollars in production losses annually. Here, we separately sequenced and then pooled according to breed the genomes from five unrelated individuals from each of the Djallonke and Sahelian sheep breeds (sourced from Ghana), at greater than 22-fold combined coverage for each breed. A total of approximately 404 million (97%) and 343 million (97%) sequence reads from the Djallonke and Sahelian breeds respectively, were successfully mapped to the sheep reference genome Oar v3.1. We identified approximately 11.1 million and 10.9 million single nucleotide polymorphisms (SNPs) in the Djallonke and Sahelian breeds, with approximately 15 and 16% respectively of these not previously reported in sheep. Multiple regions of reduced heterozygosity were also found; 70 co-localised within genomic regions harbouring genes that mediate disease resistance, immune response and adaptation in sheep or cattle. Thirty- three of the regions of reduced heterozygosity co-localised with previously reported genes for resistance to haemonchosis and trypanosomiasis. Our analyses suggest that these regions of reduced heterozygosity may be signatures of selection for these economically important diseases.

Valsa canker is a serious disease in the stem of Malus sieversii, caused by Valsa mali. However, little is known about the global response mechanism in M. sieversii to V. mali infection. Phytohormone jasmonic acid (JA) and salicylic acid (SA) profiles and transcriptome analysis were used to elaborate on the dynamic response mechanism. We determined that the JA was initially produced to respond to the necrotrophic pathogen V. mali infection at the early response stage, then get synergistically transduced with SA to respond at the late response stage. Furthermore, we adopted Pacific Biosciences (PacBio) full-length sequencing to identify differentially expressed transcripts (DETs) during the canker response stage. We obtained 52,538 full-length transcripts, of which 8139 were DETs. Total 1336 lncRNAs, 23,737 alternative polyadenylation (APA) sites and 3780 putative transcription factors (TFs) were identified. Additionally, functional annotation analysis of DETs indicated that the wild apple response to the infection of V. mali involves plant-pathogen interaction, plant hormone signal transduction, flavonoid biosynthesis, and phenylpropanoid biosynthesis. The co-expression network of the differentially expressed TFs revealed 264 candidate TF transcripts. Among these candidates, the WRKY family was the most abundant. The MsWRKY7 and MsWRKY33 were highly correlated at the early response stage, and MsWRKY6, MsWRKY7, MsWRKY19, MsWRKY33, MsWRKY40, MsWRKY45, MsWRKY51, MsWRKY61, MsWRKY75 were highly correlated at the late stage. The full-length transcriptomic analysis revealed a series of immune responsive events in M. sieversii in response to V. mali infection. The phytohormone signal pathway regulatory played an important role in the response stage. Additionally, the enriched disease resistance pathways and differentially expressed TFs dynamics collectively contributed to the immune response. This study provides valuable insights into a dynamic response in M. sieversii upon the necrotrophic pathogen V. mali infection, facilitates understanding of response mechanisms to canker disease for apple, and provides supports in the identification of potential resistance genes in M. sieversii.

The homeodomain-leucine zipper (HD-Zip) gene family is one of the plant-specific transcription factor families, involved in plant development, growth, and in the response to diverse stresses. However, comprehensive analysis of the HD-Zip genes, especially those involved in response to drought and salinity stresses is lacking in sesame (Sesamum indicum L.), an important oil crop in tropical and subtropical areas. In this study, 45 HD-Zip genes were identified in sesame, and denominated as SiHDZ01-SiHDZ45. Members of SiHDZ family were classified into four groups (HD-Zip I-IV) based on the phylogenetic relationship of Arabidopsis HD-Zip proteins, which was further supported by the analysis of their conserved motifs and gene structures. Expression analyses of SiHDZ genes based on transcriptome data showed that the expression patterns of these genes were varied in different tissues. Additionally, we showed that at least 75% of the SiHDZ genes were differentially expressed in responses to drought and salinity treatments, and highlighted the important role of HD-Zip I and II genes in stress responses in sesame. This study provides important information for functional characterization of stress-responsive HD-Zip genes and may contribute to the better understanding of the molecular basis of stress tolerance in sesame.

High growth (hg) modifier and background independent quantitative trait loci (QTL) affecting growth, adiposity and carcass composition were previously identified on mouse chromosomes (MMU) 1, 2, 5, 8, 9, 11 and 17. To confirm and further characterize each QTL, two panels of speed congenic strains were developed by introgressing CAST/EiJ (CAST) QTL alleles onto either mutant C57Bl/6J-hg/hg (HG) or wild type C57Bl/6J (B6) genetic backgrounds. The first speed congenic panel was developed by introgressing four overlapping donor regions spanning MMU2 in its entirety onto both HG and B6 backgrounds, for a total of eight strains. Phenotypic characterization of the MMU2 panel confirmed the segregation of multiple growth and obesity QTL and strongly suggested that a subset of these loci modify the effects of the hg deletion. The second panel consisted of individual donor regions on an HG background for each QTL on MMU1, 5, 8, 9, 11 and 17. Of the six developed strains, five were successfully characterized and displayed significant differences in growth and/or obesity as compared to controls. All five displayed phenotypes similar to those originally attributed to each QTL, however, novel phenotypes were unmasked in several of the strains including sex-specific effects. The speed congenic strains developed herein constitute an invaluable genomic resource and provide the foundation to identify the specific nature of genetic variation influencing growth and obesity.

Cucumber Fusarium wilt, caused by Fusarium oxysporum f. sp. cucumerinum (Foc), is one of the most notorious diseases in cucumber production. Our previous research showed the virulence of Foc significantly increases over consecutive rounds of infection in a resistant cultivar. To understand the virulence variation of Foc under host pressure, the mildly virulent strain foc-3b (WT) and its virulence-enhanced variant Ra-4 (InVir) were selected and their transcriptome profiles in infected cucumber roots were analyzed at 24 h after inoculation (hai) and 120 hai. A series of differentially expressed genes (DEGs) potentially involved in fungal pathogenicity and pathogenicity variation were identified and prove mainly involved in metabolic, transport, oxidation-reduction, cell wall degradation, macromolecules modification, and stress and defense. Among these DEGs, 190 up- and 360 down-regulated genes were expressed in both strains, indicating their importance in Foc infection. Besides, 286 and 366 DEGs showed up-regulated expression, while 492 and 214 showed down-regulated expression in InVir at 24 and 120 hai, respectively. These DEGs may be involved in increased virulence. Notably, transposases were more active in InVir than WT, indicating transposons may contribute to adaptive evolution. By a comparative transcriptome analysis of the mildly and highly virulent strains of Foc during infection of cucumber, a series of DEGs were identified that may be associated with virulence. Hence, this study provides new insight into the transcriptomic profile underlying pathogenicity and virulence differentiation of Foc.