ABSTRACT
Whole -genome sequencing projects of millions of subjects contain enormous genotypes, entailing a huge memory burden and time for computation. Here, we present GBC, a toolkit for rapidly compressing large-scale genotypes into highly addressable byte-encoding blocks under an optimized parallel framework. We demonstrate that GBC is up to 1000 times faster than state-of-the-art methods to access and manage compressed large-scale genotypes while maintaining a competitive compression ratio. We also showed that conventional analysis would be substantially sped up if built on GBC to access genotypes of a large population. GBC's data structure and algorithms are valuable for accelerating large-scale genomic research.
Subject(s)
Data Compression , Software , Humans , Algorithms , Genotype , Data Compression/methods , Genomics/methodsABSTRACT
Increasing evidence shows that genetic interaction across the entire genome may explain a non-trivial fraction of genetic diseases. Digenic interaction is the simplest manifestation of genetic interaction among genes. However, systematic exploration of digenic interactive effects on the whole genome is often discouraged by the high dimension burden. Thus, numerous digenic interactions are yet to be identified for many diseases. Here, we propose a Digenic Interaction Effect Predictor (DIEP), an accurate machine-learning approach to identify the genome-wide pathogenic coding gene pairs with digenic interaction effects. This approach achieved high accuracy and sensitivity in independent testing datasets, outperforming another gene-level digenic predictor (DiGePred). DIEP was also able to discriminate digenic interaction effect from bi-locus effects dual molecular diagnosis (pseudo-digenic). Using DIEP, we provided a valuable resource of genome-wide digenic interactions and demonstrated the enrichment of the digenic interaction effect in Mendelian and Oligogenic diseases. Therefore, DIEP will play a useful role in facilitating the genomic mapping of interactive causal genes for human diseases.
ABSTRACT
Diapause hormone (DH) and pheromone biosynthesis activating neuropeptide (PBAN) are encoded by a single mRNA in the suboesophegeal ganglion (SG) and are responsible for induction of embryonic diapause in Bombyx mori and sex pheromone biosynthesis in lepidopteran insects. PBAN cDNA analyses revealed that the DH-like peptide is present in several species that have a pupal diapause. However, the function of the DH-like peptide remains unknown. In the present study, we cloned the cDNA encoding DH-PBAN in Helicoverpa armigera utilizing the rapid amplification of the cDNA ends method. The nucleotide se quence analysis revealed that the longest open reading frame of this cDNA encodes a 194-amino acid precursor protein that con tains a 33-aa PBAN, a 24-aa DH-like peptide, and three other neuropeptides, all of which have a common C-terminal pentapeptide motif FXPR/KL ( X=G, T, S). A homology search showed that H. armigera DH-like and PBAN are highly homologous to those from other insects. Northern blot analysis demonstrated a single message RNA corresponding to the size of Har-DH-PBAN cDNA from pupal SG with significantly higher expression in the SG of nondiapause pupae than diapausing pupae. Western blot analysis showed DH-like peptide expression from SG of both males and females. When DH-like peptide was injected into nondiapause larvae and pupae, it did not induce diapause, but rather efficiently broke pupal diapause in H. armigera. The ED(50) of DH to terminate pupal diapause is 20 pmol/pupae. The other four FXPRLamide neuropeptides from the DH-PBAN polyprotein precursor have cross activity for diapause termination. These observations therefore suggest a potential role for these FXPRL family peptides in promoting continuous development in several noctuid species. The high expression of this gene in pharate adults and adults indicates that the FXPRL family peptides may have multiple physiological functions.
