Genomic Traits Research Articles

Genomic prediction and quantitative trait locus discovery in a cassava training population constructed from multiple breeding stages

AbstractAssembly of a training population (TP) is an important component of effective genomic selection‐based breeding programs. In this study, we examined the power of diverse germplasm assembled from two cassava (Manihot esculenta Crantz) breeding programs in Tanzania at different breeding stages to predict traits and discover quantitative trait loci (QTL). This is the first genomic selection and genome‐wide association study (GWAS) on Tanzanian cassava data. We detected QTL associated with cassava mosaic disease (CMD) resistance on chromosomes 12 and 16; QTL conferring resistance to cassava brown streak disease (CBSD) on chromosomes 9 and 11; and QTL on chromosomes 2, 3, 8, and 10 associated with resistance to CBSD for root necrosis. We detected a QTL on chromosome 4 and two QTL on chromosome 12 conferring dual resistance to CMD and CBSD. The use of clones in the same stage to construct TPs provided higher trait prediction accuracy than TPs with a mixture of clones from multiple breeding stages. Moreover, clones in the early breeding stage provided more reliable trait prediction accuracy and are better candidates for constructing a TP. Although larger TP sizes have been associated with improved accuracy, in this study, adding clones from Kibaha to those from Ukiriguru and vice versa did not improve the prediction accuracy of either population. Including the Ugandan TP in either population did not improve trait prediction accuracy. This study applied genomic prediction to understand the implications of constructing TP from clones at different breeding stages pooled from different locations on trait accuracy.

Comparative genomic analysis of Bordetella bronchiseptica isolates from the lungs of pigs with porcine respiratory disease complex (PRDC)

BackgroundBordetella bronchiseptica (B. bronchiseptica), as an opportunistic pathogen, can cause respiratory diseases in a variety of animals, including humans. In additional to being involved in porcine atrophic rhinitis through coinfection with Pasteurella multocida, B. bronchiseptica is associated with porcine respiratory disease complex (PRDC). While there are genomic data available from different host species, little is known about B. bronchiseptica isolates from pig lungs, especially from lungs characterized as having PRDC. ResultsA total of five B. bronchiseptica isolates were identified from pig lungs characterized as PRDC. The draft genomes of these strains were generated. In comparison with the other reported genomes, these five isolates showed the similar general characteristic including G+C content, rRNAs/tRNA, and clusters of orthologous groups of proteins (COGs). Phylogenetic analysis of all B. Bronchiseptica isolates of different species available at GenBank based on core genome multilocus sequence typing (cgMLST) classified them into two genogroups. All five isolates from this study, with the other isolates from pigs, were placed into a subclade of genogroup I consisting of only mammalian isolates. By contrast, genogroup II contained the isolates from an avian species (turkey) and some mammals (human and dog). Moreover, genome annotation revealed the presence of antibiotic resistance genes and virulence genes among these five genomes, consistent with the similarity and variety in genomic traits. Finally, comparative analysis of insertion sequence (IS) and prophages in five genomes further showed the similarity and variety in genomic characteristic. ConclusionsThis is the first study to provide comparative genomics of B. bronchiseptica strains from pig lungs characterized as having PRDC. Importantly, the findings presented in this study reveal novel genomic characteristic of B. bronchiseptica, which should provide insightful information on genome evolution.

Metabolic and Genomic Traits of Phytobeneficial Phenazine-Producing Pseudomonas spp. Are Linked to Rhizosphere Colonization in Arabidopsis thaliana and Solanum tuberosum.

Bacterial rhizosphere colonization is critical for phytobeneficial rhizobacteria such as phenazine-producing Pseudomonas spp. To better understand this colonization process, potential metabolic and genomic determinants required for rhizosphere colonization were identified using a collection of 60 phenazine-producing Pseudomonas strains isolated from multiple plant species and representative of the worldwide diversity. Arabidopsis thaliana and Solanum tuberosum (potato) were used as host plants. Bacterial rhizosphere colonization was measured by quantitative PCR using a newly designed primer pair and TaqMan probe targeting a conserved region of the phenazine biosynthetic operon. The metabolic abilities of the strains were assessed on 758 substrates using Biolog phenotype microarray technology. These data, along with available genomic sequences for all strains, were analyzed in light of rhizosphere colonization. Strains belonging to the P. chlororaphis subgroup colonized the rhizospheres of both plants more efficiently than strains belonging to the P. fluorescens subgroup. Metabolic results indicated that the ability to use amines and amino acids was associated with an increase in rhizosphere colonization capability in A. thaliana and/or in S. tuberosum The presence of multiple genetic determinants in the genomes of the different strains involved in catabolic pathways and plant-microbe and microbe-microbe interactions correlated with increased or decreased rhizosphere colonization capabilities in both plants. These results suggest that the metabolic and genomic traits found in different phenazine-producing Pseudomonas strains reflect their rhizosphere competence in A. thaliana and S. tuberosum Interestingly, most of these traits are associated with similar rhizosphere colonizing capabilities in both plant species.IMPORTANCE Rhizosphere colonization is crucial for plant growth promotion and biocontrol by antibiotic-producing Pseudomonas spp. This colonization process relies on different bacterial determinants which partly remain to be uncovered. In this study, we combined a metabolic and a genomic approach to decipher new rhizosphere colonization determinants which could improve our understanding of this process in Pseudomonas spp. Using 60 distinct strains of phenazine-producing Pseudomonas spp., we show that rhizosphere colonization abilities correlated with both metabolic and genomic traits when these bacteria were inoculated on two distant plants, Arabidopsis thaliana and Solanum tuberosum Key metabolic and genomic determinants presumably required for efficient colonization of both plant species were identified. Upon further validation, these targets could lead to the development of simple screening tests to rapidly identify efficient rhizosphere colonizers.

In the presence of population structure: From genomics to candidate genes underlying local adaptation.

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. To identify loci underlying local adaptation, models that combine allelic and environmental variation while controlling for the effects of population structure have emerged as the method of choice. Despite being evaluated in simulation studies, there has not been a thorough investigation of empirical evidence supporting local adaptation across these alleles. To evaluate these methods, we use 875 Arabidopsis thaliana Eurasian accessions and two mixed models (GEMMA and LFMM) to identify candidate SNPs underlying local adaptation to climate. Subsequently, to assess evidence of local adaptation and function among significant SNPs, we examine allele frequency differentiation and recent selection across Eurasian populations, in addition to their distribution along quantitative trait loci (QTL) explaining fitness variation between Italy and Sweden populations and cis‐regulatory/nonsynonymous sites showing significant selective constraint. Our results indicate that significant LFMM/GEMMA SNPs show low allele frequency differentiation and linkage disequilibrium across locally adapted Italy and Sweden populations, in addition to a poor association with fitness QTL peaks (highest logarithm of odds score). Furthermore, when examining derived allele frequencies across the Eurasian range, we find that these SNPs are enriched in low‐frequency variants that show very large climatic differentiation but low levels of linkage disequilibrium. These results suggest that their enrichment along putative functional sites most likely represents deleterious variation that is independent of local adaptation. Among all the genomic signatures examined, only SNPs showing high absolute allele frequency differentiation (AFD) and linkage disequilibrium (LD) between Italy and Sweden populations showed a strong association with fitness QTL peaks and were enriched along selectively constrained cis‐regulatory/nonsynonymous sites. Using these SNPs, we find strong evidence linking flowering time, freezing tolerance, and the abscisic‐acid pathway to local adaptation.

The Impact of Non-additive Effects on the Genetic Correlation Between Populations.

Average effects of alleles can show considerable differences between populations. The magnitude of these differences can be measured by the additive genetic correlation between populations (). This can be lower than one due to the presence of non-additive genetic effects together with differences in allele frequencies between populations. However, the relationship between the nature of non-additive effects, differences in allele frequencies, and the value of remains unclear, and was therefore the focus of this study. We simulated genotype data of two populations that have diverged under drift only, or under drift and selection, and we simulated traits where the genetic model and magnitude of non-additive effects were varied. Results showed that larger differences in allele frequencies and larger non-additive effects resulted in lower values of . In addition, we found that with epistasis, decreases with an increase of the number of interactions per locus. For both dominance and epistasis, we found that, when non-additive effects became extremely large, had a lower bound that was determined by the type of inter-allelic interaction, and the difference in allele frequencies between populations. Given that dominance variance is usually small, our results show that it is unlikely that true values lower than 0.80 are due to dominance effects alone. With realistic levels of epistasis, dropped as low as 0.45. These results may contribute to the understanding of differences in genetic expression of complex traits between populations, and may help in explaining the inefficiency of genomic trait prediction across populations.

Peculiar genomic traits in the stress-adapted cryptoendolithic Antarctic fungus Friedmanniomyces endolithicus

Friedmanniomyces endolithicus is a highly melanized fungus endemic to the Antarctic, occurring exclusively in endolithic communities of the ice-free areas of the Victoria Land, including the McMurdo Dry Valleys, the coldest and most hyper-arid desert on Earth and accounted as the Martian analog on our planet. F. endolithicus is highly successful in these inhospitable environments, the most widespread and commonly isolated species from these peculiar niches, indicating a high degree of adaptation. The nature of its extremo tolerance has not been previously studied. To investigate this, we sequenced genome of F. endolithicus CCFEE 5311 to explore gene content and genomic patterns that could be attributed to its specialization. The predicted functional potential of the genes was assigned by similarity to InterPro and CAZy domains. The genome was compared to phylogenetically close relatives which are also melanized fungi occurring in extreme environments including Friedmanniomyces simplex, Baudoinia panamericana, Acidomyces acidophilus, Hortaea thailandica and Hortaea werneckii. We tested if shared genomic traits existed among these species and hyper-extremotolerant fungus F. endolithicus. We found that some characters for stress tolerance such as meristematic growth and cold tolerance are enriched in F. endolithicus that may be triggered by the exposure to Antarctic prohibitive conditions.

Genomic adaptations in information processing underpin trophic strategy in a whole-ecosystem nutrient enrichment experiment.

Several universal genomic traits affect trade-offs in the capacity, cost, and efficiency of the biochemical information processing that underpins metabolism and reproduction. We analyzed the role of these traits in mediating the responses of a planktonic microbial community to nutrient enrichment in an oligotrophic, phosphorus-deficient pond in Cuatro Ciénegas, Mexico. This is one of the first whole-ecosystem experiments to involve replicated metagenomic assessment. Mean bacterial genome size, GC content, total number of tRNA genes, total number of rRNA genes, and codon usage bias in ribosomal protein sequences were all higher in the fertilized treatment, as predicted on the basis of the assumption that oligotrophy favors lower information-processing costs whereas copiotrophy favors higher processing rates. Contrasting changes in trait variances also suggested differences between traits in mediating assembly under copiotrophic versus oligotrophic conditions. Trade-offs in information-processing traits are apparently sufficiently pronounced to play a role in community assembly because the major components of metabolism-information, energy, and nutrient requirements-are fine-tuned to an organism's growth and trophic strategy.

Distinct genomic traits of acral and mucosal melanomas revealed by targeted mutational profiling.

The incidence of melanoma is rising globally including China. Comparing to Caucasians, the incidence of non-cutaneous melanomas is significantly higher in Chinese. Herein, we performed genomic profiling of 89 Chinese surgically resected primary melanomas, including acral (n=54), cutaneous (n=22), and mucosal (n=13), by hybrid capture-based next-generation sequencing. We show that mucosal melanomas tended to harbor more pathogenic mutations than other types of melanoma, though the biological significance of this finding remains uncertain. Chromosomal arm-level alterations including 6q, 9p, and 10p/q loss were highly recurrent in all subtypes, but mucosal melanoma was significantly associated with increased genomic instability. Importantly, 7p gain significantly correlated with unfavorable clinical outcomes in non-cutaneous melanomas, representing an intriguing prognostic biomarker of those subtypes. Furthermore, focal amplification of 4q12 (KIT, KDR, and PDGFRα) and RAD51 deletion were more abundant in mucosal melanoma, while NOTCH2 amplification was enriched in acral melanoma. Additionally, cutaneous melanomas had higher mutation load than acral melanomas, while mucosal melanomas did not differ from other subtypes in mutation burden. Together, our data revealed important features of acral and mucosal melanomas in Chinese including distinctive driver mutation pattern and increased genomic instability. These findings highlight the possibilities of combination therapies in the clinical management of melanoma.

Rariglobus hedericola gen. nov., sp. nov., belonging to the Verrucomicrobia, isolated from a temperate freshwater habitat.

The bacterial strain 53C-WASEF was isolated from a small freshwater ditch located in Eugendorf, Austria. Phylogenetic reconstructions with 16S rRNA gene sequences and genome based, with amino acid sequences obtained from 105 single copy genes, suggested that the strain represents a new genus and a new species within the family Opitutaceae, which belongs to the class Opitutae of the phylum Verrucomicrobia. Comparisons of the 16S rRNA gene sequence of strain 53C-WASEF with those of related type strains revealed a highest sequence similarity of 93.5 % to Nibricoccus aquaticus and of 92.9 % to Geminisphaera colitermitum. Interestingly, phylogentic trees indicated the latter as being the closest known relative of the new strain. Phenotypic, chemotaxonomic and genomic traits were investigated. Cells were observed to be small, spherical, motile and unpigmented, and grew chemoorganotrophically and aerobically. The respiratory quinone was MK-7, the predominant fatty acids were anteiso-C15 : 0, C16 : 1ω5c and C16 : 0. The identified polar lipids were phosphatidylethanolamine, phosphatidylglycerol and diphosphatidylglycerol. Genome sequencing revealed genes putatively encoding for flagella synthesis and cellulose degradation. The genome size was 4.1 Mbp and the G+C content 60.6 mol%. For the new genus and the new species, we propose the name Rariglobus hedericola gen. nov., sp. nov. (=CIP 111665T=DSM 109123T).

Evolutionary relationships among bifidobacteria and their hosts and environments

BackgroundThe assembly of animal microbiomes is influenced by multiple environmental factors and host genetics, although the relative importance of these factors remains unclear. Bifidobacteria (genus Bifidobacterium, phylum Actinobacteria) are common first colonizers of gut microbiomes in humans and inhabit other mammals, social insects, food, and sewages. In humans, the presence of bifidobacteria in the gut has been correlated with health-promoting benefits. Here, we compared the genome sequences of a subset of the over 400 Bifidobacterium strains publicly available to investigate the adaptation of bifidobacteria diversity. We tested 1) whether bifidobacteria show a phylogenetic signal with their isolation sources (hosts and environments) and 2) whether key traits encoded by the bifidobacteria genomes depend on the host or environment from which they were isolated. We analyzed Bifidobacterium genomes available in the PATRIC and NCBI repositories and identified the hosts and/or environment from which they were isolated. A multilocus phylogenetic analysis was conducted to compare the genetic relatedness the strains harbored by different hosts and environments. Furthermore, we examined differences in genomic traits and genes related to amino acid biosynthesis and degradation of carbohydrates.ResultsWe found that bifidobacteria diversity appears to have evolved with their hosts as strains isolated from the same host were non-randomly associated with their phylogenetic relatedness. Moreover, bifidobacteria isolated from different sources displayed differences in genomic traits such as genome size and accessory gene composition and on particular traits related to amino acid production and degradation of carbohydrates. In contrast, when analyzing diversity within human-derived bifidobacteria, we observed no phylogenetic signal or differences on specific traits (amino acid biosynthesis genes and CAZymes).ConclusionsOverall, our study shows that bifidobacteria diversity is strongly adapted to specific hosts and environments and that several genomic traits were associated with their isolation sources. However, this signal is not observed in human-derived strains alone. Looking into the genomic signatures of bifidobacteria strains in different environments can give insights into how this bacterial group adapts to their environment and what types of traits are important for these adaptations.

Chryseobacterium binzhouense sp. nov., isolated from activated sludge.

A golden-pigmented, Gram-strain-negative, aerobic, rod-shaped, non-flagellated and non-gliding bacterium, designated strain lm2T, was isolated from activated sludge obtained from a wastewater treatment plant in Binzhou (Shandong province, PR China). Growth occurred at 15-45°C (optimum, 30 °C), in the presence of 0-5.0 % (w/v) NaCl (optimum, 0-2.0 %) and at pH 6.5-8.0 (optimum, pH 7.0-7.5). The chemotaxonomic, phenotypic and genomic traits were investigated. Phylogenetic analysis based on 16S rRNA gene sequence showed that strain lm2T belonged to the genus Chryseobacterium, with highest sequence similarity to Chryseobacterium echinoideorum CC-CZW010T (97.1 %). Genome sequencing revealed a genome size of 3 611 894 bp and a G+C content of 34.9 mol%. The average nucleotide identity value and the digital DNA-DNA hybridization (dDDH) value between strain lm2T and C. echinoideorum JCM 30470T were 87.8 and 34.7 %, respectively. The major respiratory quinone was Menaquinone-6 (MK-6). The major fatty acids were iso-C15 : 0, iso-C17 : 0 3-OH and iso-C17 : 1 ω9c and its polar lipids consisted of phosphatidylethanolamine (PE), unidentified lipids (L1-5) and unidentified aminolipids (AL1-4). On the basis of these data, strain lm2T is considered to represent a novel species of the genus Chryseobacterium, for which the name Chryseobacterium binzhouense sp. nov. is proposed. The type strain is lm2T (=KCTC 72529T=CCTCC AB2019126T).

MaizeCUBIC: a comprehensive variation database for a maize synthetic population.

MaizeCUBIC is a free database that describes genomic variations, gene expression, phenotypes and quantitative trait locus (QTLs) for a maize CUBIC population (24 founders and 1404 inbred offspring). The database not only includes information for over 14M single nucleotide polymorphism (SNPs) and 43K indels previously identified but also contains 660K structure variations (SVs) and 600M novel sequences newly identified in the present study, which represents a comprehensive high-density variant map for a diverse population. Based on these genomic variations, the database would demonstrate the mosaic structure for each progeny, reflecting a high-resolution reshuffle across parental genomes. A total of 23 agronomic traits measured on parents and progeny in five locations, where are representative of the maize main growing regions in China, were also included in the database. To further explore the genotype–phenotype relationships, two different methods of genome-wide association studies (GWAS) were employed for dissecting the genetic architecture of 23 agronomic traits. Additionally, the Basic Local Alignment Search Tool and primer design tools are developed to promote follow-up analysis and experimental verification. All the original data and corresponding analytical results can be accessed through user-friendly online queries and web interface dynamic visualization, as well as downloadable files. These data and tools provide valuable resources on genetic and genomic studies of maize and other crops.

Construction of High-Density Genetic Map and Identification of QTLs Associated with Seed Vigor after Exposure to Artificial Aging Conditions in Sweet Corn Using SLAF-seq.

Seed vigor is a key factor that determines the quality of seeds, which is of great significance for agricultural production, with the potential to promote growth and productivity. However, the underlying molecular mechanisms and genetic basis for seed vigor remain unknown. High-density genetic linkage mapping is an effective method for genomic study and quantitative trait loci (QTL) mapping. In this study, a high-density genetic map was constructed from a 148 BC4F3 population cross between ‘M03’ and ‘M08’ strains based on specific-locus amplified fragment (SLAF) sequencing. The constructed high-density genetic linkage map (HDGM) included 3876 SNP markers on ten chromosomes covering 2413.25 cM in length, with a mean distance between markers of 0.62 cM. QTL analysis was performed on four sweet corn germination traits that are related to seed vigor under artificial aging conditions. A total of 18 QTLs were identified in two seasons. Interestingly, a stable QTL was detected in two seasons on chromosome 10—termed qGR10—within an interval of 1.37 Mb. Within this interval, combined with gene annotation, we found four candidate genes (GRMZM2G074309, GRMZM2G117319, GRMZM2G465812, and GRMZM2G343519) which may be related to seed vigor after artificial aging.

Comparative Genomics of Streptococcus thermophilus Support Important Traits Concerning the Evolution, Biology and Technological Properties of the Species.

Streptococcus thermophilus is a major starter for the dairy industry with great economic importance. In this study we analyzed 23 fully sequenced genomes of S. thermophilus to highlight novel aspects of the evolution, biology and technological properties of this species. Pan/core genome analysis revealed that the species has an important number of conserved genes and that the pan genome is probably going to be closed soon. According to whole genome phylogeny and average nucleotide identity (ANI) analysis, most S. thermophilus strains were grouped in two major clusters (i.e., clusters A and B). More specifically, cluster A includes strains with chromosomes above 1.83 Mbp, while cluster B includes chromosomes below this threshold. This observation suggests that strains belonging to the two clusters may be differentiated by gene gain or gene loss events. Furthermore, certain strains of cluster A could be further subdivided in subgroups, i.e., subgroup I (ASCC 1275, DGCC 7710, KLDS SM, MN-BM-A02, and ND07), II (MN-BM-A01 and MN-ZLW-002), III (LMD-9 and SMQ-301), and IV (APC151 and ND03). In cluster B certain strains formed one distinct subgroup, i.e., subgroup I (CNRZ1066, CS8, EPS, and S9). Clusters and subgroups observed for S. thermophilus indicate the existence of lineages within the species, an observation which was further supported to a variable degree by the distribution and/or the architecture of several genomic traits. These would include exopolysaccharide (EPS) gene clusters, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs)-CRISPR associated (Cas) systems, as well as restriction-modification (R-M) systems and genomic islands (GIs). Of note, the histidine biosynthetic cluster was found present in all cluster A strains (plus strain NCTC12958T) but was absent from all strains in cluster B. Other loci related to lactose/galactose catabolism and urea metabolism, aminopeptidases, the majority of amino acid and peptide transporters, as well as amino acid biosynthetic pathways were found to be conserved in all strains suggesting their central role for the species. Our study highlights the necessity of sequencing and analyzing more S. thermophilus complete genomes to further elucidate important aspects of strain diversity within this starter culture that may be related to its application in the dairy industry.

Analysis of Screen-detected Lung Cancers' Genomic Traits

Analysis of Screen-detected Lung Cancers' Genomic Traits

Genomes of early-diverging streptophyte algae shed light on plant terrestrialization

Mounting evidence suggests that terrestrialization of plants started in streptophyte green algae, favoured by their dual existence in freshwater and subaerial/terrestrial environments. Here, we present the genomes of Mesostigma viride and Chlorokybus atmophyticus, two sister taxa in the earliest-diverging clade of streptophyte algae dwelling in freshwater and subaerial/terrestrial environments, respectively. We provide evidence that the common ancestor of M. viride and C. atmophyticus (and thus of streptophytes) had already developed traits associated with a subaerial/terrestrial environment, such as embryophyte-type photorespiration, canonical plant phytochrome, several phytohormones and transcription factors involved in responses to environmental stresses, and evolution of cellulose synthase and cellulose synthase-like genes characteristic of embryophytes. Both genomes differed markedly in genome size and structure, and in gene family composition, revealing their dynamic nature, presumably in response to adaptations to their contrasting environments. The ancestor of M. viride possibly lost several genomic traits associated with a subaerial/terrestrial environment following transition to a freshwater habitat.

Rhodoferax bucti sp. nov., isolated from fresh water.

A Gram-reaction-negative, peach-brown-pigmented, slightly curved-rod-shaped, aerobic, non-motile bacterium, designated GSA243-2T, was isolated from fresh water samples collected from the Chishui River flowing through Maotai, Guizhou, south-west PR China. Phenotypic, chemotaxonomic and genomic traits were investigated. Results of phylogenetic analysis based on 16S rRNA gene sequences showed that the isolate belonged to the genus Rhodoferax. The closest phylogenetic relative was Rhodoferax saidenbachensis ATCC BAA-1852T (98.35 %). The major fatty acids were C16: 0 and C16 : 1ω6c and/or C16 : 1ω7c. The major respiratory quinone was ubiquinone Q-8 and the major polar lipid was phosphatidylethanolamine. Genome sequencing revealed a genome size of 3.67 Mbp and a G+C content of 61.17 mol%. Pairwise-determined whole genome average nucleotide identity values and digital DNA-DNA hybridization values suggested that strain GSA243-2T represents a new species, for which we propose the name Rhodoferaxbucti sp. nov. with the type strain GSA243-2T (=CGMCC 1.16288T=KCTC 62564T).

Deep mixed model for marginal epistasis detection and population stratification correction in genome-wide association studies

BackgroundGenome-wide Association Studies (GWAS) have contributed to unraveling associations between genetic variants in the human genome and complex traits for more than a decade. While many works have been invented as follow-ups to detect interactions between SNPs, epistasis are still yet to be modeled and discovered more thoroughly.ResultsIn this paper, following the previous study of detecting marginal epistasis signals, and motivated by the universal approximation power of deep learning, we propose a neural network method that can potentially model arbitrary interactions between SNPs in genetic association studies as an extension to the mixed models in correcting confounding factors. Our method, namely Deep Mixed Model, consists of two components: 1) a confounding factor correction component, which is a large-kernel convolution neural network that focuses on calibrating the residual phenotypes by removing factors such as population stratification, and 2) a fixed-effect estimation component, which mainly consists of an Long-short Term Memory (LSTM) model that estimates the association effect size of SNPs with the residual phenotype.ConclusionsAfter validating the performance of our method using simulation experiments, we further apply it to Alzheimer’s disease data sets. Our results help gain some explorative understandings of the genetic architecture of Alzheimer’s disease.

Identification of 12 cancer types through genome deep learning

Cancer is a major cause of death worldwide, and an early diagnosis is required for a favorable prognosis. Histological examination is the gold standard for cancer identification; however, large amount of inter-observer variability exists in histological diagnosis. Numerous studies have shown cancer genesis is accompanied by an accumulation of harmful mutations, potentiating the identification of cancer based on genomic information. We have proposed a method, GDL (genome deep learning), to study the relationship between genomic variations and traits based on deep neural networks. We analyzed 6,083 samples’ WES (Whole Exon Sequencing) mutations files from 12 cancer types obtained from the TCGA (The Cancer Genome Atlas) and 1,991 healthy samples’ WES data from the 1000 Genomes project. We constructed 12 specific models to distinguish between certain type of cancer and healthy tissues, a total-specific model that can identify healthy and cancer tissues, and a mixture model to distinguish between all 12 types of cancer based on GDL. We demonstrate that the accuracy of specific, mixture and total specific model are 97.47%, 70.08% and 94.70% for cancer identification. We developed an efficient method for the identification of cancer based on genomic information that offers a new direction for disease diagnosis.

Precision medicine, agriculture, and genome editing: science and ethics.

The era of precision medicine has generated advances in various fields of science and medicine with the potential for a paradigm shift in healthcare delivery that will ultimately lead to an individualized approach to medicine. Such timely topics were explored in 2018 at a workshop held at the Third International Conference on One Medicine One Science (iCOMOS), in Minneapolis, Minnesota. A broad range of scientists and regulatory experts provided detailed insights into the challenges and opportunities associated with precision medicine and gene editing. There was a general consensus that advances in studying the genomic traits driving differential pharmacogenomics will undoubtedly enhance individualized treatments for a wide variety of diseases. Ethical considerations, societal implications, approaches for prioritizing safe and secure use of treatment modalities, and the advent of high-throughput computing and analysis of large, complex datasets were discussed. Large biobanks, such as the All of Us Research Program and the Veterans Affairs Million Veterans Program, can aid studies of various conditions in massive cohorts of patients. As the applications of precision medicine continue to mature, the full potential and promise of these individualized approaches will continue to yield important advances in transplant medicine, oncology, public health, agriculture, pharmacology, and bioinformatics.