The GATK joint genotyping workflow is appropriate for calling variants in RNA-seq experiments

Regulation of a single inositol 1-phosphate synthase homeologue by HSFA6B contributes to fibre yield maintenance under drought conditions in upland cotton

Drought stress substantially impacts crop physiology resulting in alteration of growth and productivity. Understanding the genetic and molecular crosstalk between stress responses and agronomically important traits such as fibre yield is particularly complicated in the allopolyploid species, upland cotton (Gossypium hirsutum), due to reduced sequence variability between A and D subgenomes. To better understand how drought stress impacts yield, the transcriptomes of 22 genetically and phenotypically diverse upland cotton accessions grown under well-watered and water-limited conditions in the Arizona low desert were sequenced. Gene co-expression analyses were performed, uncovering a group of stress response genes, in particular transcription factors GhDREB2A-A and GhHSFA6B-D, associated with improved yield under water-limited conditions in an ABA-independent manner. DNA affinity purification sequencing (DAP-seq), as well as public cistrome data from Arabidopsis, were used to identify targets of these two TFs. Among these targets were two lint yield-associated genes previously identified through genome-wide association studies (GWAS)-based approaches, GhABP-D and GhIPS1-A. Biochemical and phylogenetic approaches were used to determine that GhIPS1-A is positively regulated by GhHSFA6B-D, and that this regulatory mechanism is specific to Gossypium spp. containing the A (old world) genome. Finally, an SNP was identified within the GhHSFA6B-D binding site in GhIPS1-A that is positively associated with yield under water-limiting conditions. These data lay out a regulatory connection between abiotic stress and fibre yield in cotton that appears conserved in other systems such as Arabidopsis.

A single-cell strategy for the identification of intronic variants related to mis-splicing in pancreatic cancer

Most clinical diagnostic and genomic research setups focus almost exclusively on coding regions and essential splice sites, thereby overlooking other non-coding variants. As a result, intronic variants that can promote mis-splicing events across a range of diseases, including cancer, are yet to be systematically investigated. Such investigations would require both genomic and transcriptomic data, but there currently exist very few datasets that satisfy these requirements. We address this by developing a single-nucleus full-length RNA-sequencing approach that allows for the detection of potentially pathogenic intronic variants. We exemplify the potency of our approach by applying pancreatic cancer tumor and tumor-derived specimens and linking intronic variants to splicing dysregulation. We specifically find that prominent intron retention and pseudo-exon activation events are shared by the tumors and affect genes encoding key transcriptional regulators. Our work paves the way for the assessment and exploitation of intronic mutations as powerful prognostic markers and potential therapeutic targets in cancer.

Natural variations of heterosis-related allele-specific expression genes in promoter regions lead to allele-specific expression in maize

BACKGROUND

Heterosis has successfully enhanced maize productivity and quality. Although significant progress has been made in delineating the genetic basis of heterosis, the molecular mechanisms underlying its genetic components remain less explored. Allele-specific expression (ASE), the imbalanced expression between two parental alleles in hybrids, is increasingly being recognized as a factor contributing to heterosis. ASE is a complex process regulated by both epigenetic and genetic variations in response to developmental and environmental conditions.

RESULTS

In this study, we explored the differential characteristics of ASE by analyzing the transcriptome data of two maize hybrids and their parents under four light conditions. On the basis of allele expression patterns in different hybrids under various conditions, ASE genes were divided into three categories: bias-consistent genes involved in basal metabolic processes in a functionally complementary manner, bias-reversal genes adapting to the light environment, and bias-specific genes maintaining cell homeostasis. We observed that 758 ASE genes (ASEGs) were significantly overlapped with heterosis quantitative trait loci (QTLs), and high-frequency variations in the promoter regions of heterosis-related ASEGs were identified between parents. In addition, 10 heterosis-related ASEGs participating in yield heterosis were selected during domestication.

CONCLUSIONS

The comprehensive analysis of ASEGs offers a distinctive perspective on how light quality influences gene expression patterns and gene-environment interactions, with implications for the identification of heterosis-related ASEGs to enhance maize yield.

The contribution of an X chromosome QTL to non-Mendelian inheritance and unequal chromosomal segregation in Auanema freiburgense

Auanema freiburgense is a nematode with males, females, and selfing hermaphrodites. When XO males mate with XX females, they typically produce a low proportion of XO offspring because they eliminate nullo-X spermatids. This process ensures that most sperm carry an X chromosome, increasing the likelihood of X chromosome transmission compared to random segregation. This occurs because of an unequal distribution of essential cellular organelles during sperm formation, likely dependent on the X chromosome. Some sperm components are selectively segregated into the X chromosome's daughter cell, while others are discarded with the nullo-X daughter cell. Intriguingly, the interbreeding of 2 A. freiburgense strains results in hybrid males capable of producing viable nullo-X sperm. Consequently, when these hybrid males mate with females, they yield a high percentage of male offspring. To uncover the genetic basis of nullo-spermatid elimination and X chromosome drive, we generated a genome assembly for A. freiburgense and genotyped the intercrossed lines. This analysis identified a quantitative trait locus spanning several X chromosome genes linked to the non-Mendelian inheritance patterns observed in A. freiburgense. This finding provides valuable clues to the underlying factors involved in asymmetric organelle partitioning during male meiotic division and thus non-Mendelian transmission of the X chromosome and sex ratios.

Novel putative causal mutations associated with fat traits in Nellore cattle uncovered by eQTLs located in open chromatin regions

Intramuscular fat (IMF) and backfat thickness (BFT) are critical economic traits impacting meat quality. However, the genetic variants controlling these traits need to be better understood. To advance knowledge in this area, we integrated RNA-seq and single nucleotide polymorphisms (SNPs) identified in genomic and transcriptomic data to generate a linkage disequilibrium filtered panel of 553,581 variants. Expression quantitative trait loci (eQTL) analysis revealed 36,916 cis-eQTLs and 14,408 trans-eQTLs. Association analysis resulted in three eQTLs associated with BFT and 24 with IMF. Functional enrichment analysis of genes regulated by these 27 eQTLs revealed noteworthy pathways that can play a fundamental role in lipid metabolism and fat deposition, such as immune response, cytoskeleton remodeling, iron transport, and phospholipid metabolism. We next used ATAC-Seq assay to identify and overlap eQTL and open chromatin regions. Six eQTLs were in regulatory regions, four in predicted insulators and possible CCCTC-binding factor DNA binding sites, one in an active enhancer region, and the last in a low signal region. Our results provided novel insights into the transcriptional regulation of IMF and BFT, unraveling putative regulatory variants.

Genetic Modifiers of Sickle Cell Anemia Phenotype in a Cohort of Angolan Children

The aim of this study was to identify genetic markers in the HBB Cluster; HBS1L-MYB intergenic region; and BCL11A, KLF1, FOX3, and ZBTB7A genes associated with the heterogeneous phenotypes of Sickle Cell Anemia (SCA) using next-generation sequencing, as well as to assess their influence and prevalence in an Angolan population. Hematological, biochemical, and clinical data were considered to determine patients' severity phenotypes. Samples from 192 patients were sequenced, and 5,019,378 variants of high quality were registered. A catalog of candidate modifier genes that clustered in pathophysiological pathways important for SCA was generated, and candidate genes associated with increasing vaso-occlusive crises (VOC) and with lower fetal hemoglobin (HbF) were identified. These data support the polygenic view of the genetic architecture of SCA phenotypic variability. Two single nucleotide polymorphisms in the intronic region of 2q16.1, harboring the BCL11A gene, are genome-wide and significantly associated with decreasing HbF. A set of variants was identified to nominally be associated with increasing VOC and are potential genetic modifiers harboring phenotypic variation among patients. To the best of our knowledge, this is the first investigation of clinical variation in SCA in Angola using a well-customized and targeted sequencing approach.

Multiomics Analyses Provide New Insight into Genetic Variation of Reproductive Adaptability in Tibetan Sheep

Domestication and artificial selection during production-oriented breeding have greatly shaped the level of genomic variability in sheep. However, the genetic variation associated with increased reproduction remains elusive. Here, two groups of samples from consecutively monotocous and polytocous sheep were collected for genome-wide association, transcriptomic, proteomic, and metabolomic analyses to explore the genetic variation in fecundity in Tibetan sheep. Genome-wide association study revealed strong associations between BMPR1B (p.Q249R) and litter size, as well as between PAPPA and lambing interval; these findings were validated in 1,130 individuals. Furthermore, we constructed the first single-cell atlas of Tibetan sheep ovary tissues and identified a specific mural granulosa cell subtype with PAPPA-specific expression and differential expression of BMPR1B between the two groups. Bulk RNA-seq indicated that BMPR1B and PAPPA expressions were similar between the two groups of sheep. 3D protein structure prediction and coimmunoprecipitation analysis indicated that mutation and mutually exclusive exons of BMPR1B are the main mechanisms for prolific Tibetan sheep. We propose that PAPPA is a key gene for stimulating ovarian follicular growth and development, and steroidogenesis. Our work reveals the genetic variation in reproductive performance in Tibetan sheep, providing insights and valuable genetic resources for the discovery of genes and regulatory mechanisms that improve reproductive success.

A high-performance computational workflow to accelerate GATK SNP detection across a 25-genome dataset

BACKGROUND

Single-nucleotide polymorphisms (SNPs) are the most widely used form of molecular genetic variation studies. As reference genomes and resequencing data sets expand exponentially, tools must be in place to call SNPs at a similar pace. The genome analysis toolkit (GATK) is one of the most widely used SNP calling software tools publicly available, but unfortunately, high-performance computing versions of this tool have yet to become widely available and affordable.

RESULTS

Here we report an open-source high-performance computing genome variant calling workflow (HPC-GVCW) for GATK that can run on multiple computing platforms from supercomputers to desktop machines. We benchmarked HPC-GVCW on multiple crop species for performance and accuracy with comparable results with previously published reports (using GATK alone). Finally, we used HPC-GVCW in production mode to call SNPs on a "subpopulation aware" 16-genome rice reference panel with ~ 3000 resequenced rice accessions. The entire process took ~ 16 weeks and resulted in the identification of an average of 27.3 M SNPs/genome and the discovery of ~ 2.3 million novel SNPs that were not present in the flagship reference genome for rice (i.e., IRGSP RefSeq).

CONCLUSIONS

This study developed an open-source pipeline (HPC-GVCW) to run GATK on HPC platforms, which significantly improved the speed at which SNPs can be called. The workflow is widely applicable as demonstrated successfully for four major crop species with genomes ranging in size from 400 Mb to 2.4 Gb. Using HPC-GVCW in production mode to call SNPs on a 25 multi-crop-reference genome data set produced over 1.1 billion SNPs that were publicly released for functional and breeding studies. For rice, many novel SNPs were identified and were found to reside within genes and open chromatin regions that are predicted to have functional consequences. Combined, our results demonstrate the usefulness of combining a high-performance SNP calling architecture solution with a subpopulation-aware reference genome panel for rapid SNP discovery and public deployment.

High-content phenotypic analysis of a C. elegans recombinant inbred population identifies genetic and molecular regulators of lifespan

Lifespan is influenced by complex interactions between genetic and environmental factors. Studying those factors in model organisms of a single genetic background limits their translational value for humans. Here, we mapped lifespan determinants in 85 genetically diverse C. elegans recombinant intercross advanced inbred lines (RIAILs). We assessed molecular profiles - transcriptome, proteome, and lipidome - and life-history traits, including lifespan, development, growth dynamics, and reproduction. RIAILs exhibited large variations in lifespan, which positively correlated with developmental time. Among the top candidates obtained from multi-omics data integration and QTL mapping, we validated known and novel longevity modulators, including rict-1, gfm-1 and mltn-1. We translated their relevance to humans using UK Biobank data and showed that variants in RICTOR and GFM1 are associated with an elevated risk of age-related heart disease, dementia, diabetes, kidney, and liver diseases. We organized our dataset as a resource (https://lisp-lms.shinyapps.io/RIAILs/) that allows interactive explorations for new longevity targets.

SETD2 mutations do not contribute to clonal fitness in response to chemotherapy in childhood B cell acute lymphoblastic leukemia

Mutations in genes encoding epigenetic regulators are commonly observed at relapse in B cell acute lymphoblastic leukemia (B-ALL). Loss-of-function mutations in SETD2, an H3K36 methyltransferase, have been observed in B-ALL and other cancers. Previous studies on mutated SETD2 in solid tumors and acute myelogenous leukemia support a role in promoting resistance to DNA damaging agents. We did not observe chemoresistance, an impaired DNA damage response, nor increased mutation frequency in response to thiopurines using CRISPR-mediated knockout in wild-type B-ALL cell lines. Likewise, restoration of SETD2 in cell lines with hemizygous mutations did not increase sensitivity. SETD2 mutations affected the chromatin landscape and transcriptional output that was unique to each cell line. Collectively our data does not support a role for SETD2 mutations in driving clonal evolution and relapse in B-ALL, which is consistent with the lack of enrichment of SETD2 mutations at relapse in most studies.

EpiTyping: analysis of epigenetic aberrations in parental imprinting and X-chromosome inactivation using RNA-seq

Human pluripotent stem cells (hPSCs) hold a central role in studying human development, in disease modeling and in regenerative medicine. These cells not only acquire genetic modifications when kept in culture, but they may also harbor epigenetic aberrations, mainly involving parental imprinting and X-chromosome inactivation. Here we present a detailed bioinformatic protocol for detecting such aberrations using RNA sequencing data. We provide a pipeline designed to process and analyze RNA sequencing data for the identification of abnormal biallelic expression of imprinted genes, and thus detect loss of imprinting. Furthermore, we show how to differentiate among X-chromosome inactivation, full activation and aberrant erosion of X chromosome in female hPSCs. In addition to providing bioinformatic tools, we discuss the impact of such epigenetic variations in hPSCs on their utility for various purposes. This pipeline can be used by any user with basic understanding of the Linux command line. It is available on GitHub as a software container ( https://github.com/Gal-Keshet/EpiTyping ) and produces reliable results in 1-4 d.

From beasts to bytes: Revolutionizing zoological research with artificial intelligence

Since the late 2010s, Artificial Intelligence (AI) including machine learning, boosted through deep learning, has boomed as a vital tool to leverage computer vision, natural language processing and speech recognition in revolutionizing zoological research. This review provides an overview of the primary tasks, core models, datasets, and applications of AI in zoological research, including animal classification, resource conservation, behavior, development, genetics and evolution, breeding and health, disease models, and paleontology. Additionally, we explore the challenges and future directions of integrating AI into this field. Based on numerous case studies, this review outlines various avenues for incorporating AI into zoological research and underscores its potential to enhance our understanding of the intricate relationships that exist within the animal kingdom. As we build a bridge between beast and byte realms, this review serves as a resource for envisioning novel AI applications in zoological research that have not yet been explored.

A novel pathogenic splicing mutation of RPGR in a Chinese family with X-linked retinitis pigmentosa verified by minigene splicing assay

AIM

To report a novel splicing mutation in the RPGR gene (encoding retinitis pigmentosa GTPase regulator) in a three-generation Chinese family with X-linked retinitis pigmentosa (XLRP).

METHODS

Comprehensive ophthalmic examinations including best corrected visual acuity, fundus photography, vision field, and pattern-visual evoked potential were performed to identify the disease phenotype of a six-year-old boy from the family (proband). Genomic DNA was extracted from peripheral blood of five available members of the pedigree. Whole-exome sequencing (WES), Sanger sequencing, and pSPL3-based exon trapping were used to investigate the aberrant splicing of RPGR. Human Splice Finder v3.1 and NNSPLICE v0.9 were used for in silico prediction of splice site variants.

RESULTS

The proband was diagnosed as having retinitis pigmentosa (RP). He had severe symptoms with early onset. A novel splicing mutation, c.619+1G>C in RPGR was identified in the proband by WES and in four family members by Sanger sequencing. Minigene splicing assays verified that c.619+1G>C in RPGR would result in the formation of a damaging alternative transcript in which the last 91 bp of exon 6 were skipped, leading to the subsequent deletion of 623 correct amino acids (c.529_619del p.Val177Glnfs*16).

CONCLUSION

We identify a novel splice donor site mutation causing aberrant splicing of RPGR. Our findings add to the catalog of pathological mutations of RPGR and further emphasize the functional importance of RPGR in RP pathogenesis and its complex clinical phenotypes.

Genome sequencing-based transcriptomic analysis reveals novel genes in Peucedanum praeruptorum

BACKGROUND

Peucedanum praeruptorum Dunn, a traditional Chinese herbal medicine, contains coumarin and volatile oil components that have clinical application value. However, early bolting often occurs in the medicinal materials of Apiaceae plants. The rhizomes of the medicinal parts are gradually lignified after bolting, resulting in a sharp decrease in the content of coumarins. At present, the link between coumarin biosynthesis and early bolting in P. praeruptorum has not been elucidated.

RESULTS

Combining the genome sequencing and the previous transcriptome sequencing results, we reanalyzed the differential transcripts of P. praeruptorum before and after bolting. A total of 62,088 new transcripts were identified, of which 31,500 were unknown transcripts. Functional classification and annotation showed that many genes were involved in the regulation of transcription, defense response, and carbohydrate metabolic processes. The main domains are the pentatricopeptide repeat, protein kinase, RNA recognition motif, leucine-rich repeat, and ankyrin repeat domains, indicating their pivotal roles in protein modification and signal transduction. Gene structure analysis showed that skipped exon (SE) was the most dominant alternative splicing, followed by the alternative 3' splice site (A3SS) and the alternative 5' splice site (A5SS). Functional enrichment of differentially expressed genes showed that these differentially expressed genes mainly include transmembrane transporters, channel proteins, DNA-binding proteins, polysaccharide-binding proteins, etc. In addition, genes involved in peroxisome, hexose phosphate pathway, phosphatidylinositol signaling system, and inositol phosphate metabolism pathway were greatly enriched. A protein-protein interaction network analysis discoverd 1,457 pairs of proteins that interact with each other. The expression levels of six UbiA genes, three UGT genes, and four OMT genes were higher during the bolting stage. This observation suggests their potential involvement in the catalytic processes of prenylation, glycosylation, and methylation of coumarins, respectively. A total of 100 peroxidase (PRX) genes were identified being involved in lignin polymerization, but only nine PRX genes were highly expressed at the bolting stage. It is worth noting that 73 autophagy-related genes (ATGs) were first identified from the KEGG pathway-enriched genes. Some ATGs, such as BHQH00009837, BHQH00013830, and novel8944, had higher expression levels after bolting.

CONCLUSIONS

Comparative transcriptome analysis and large-scale genome screening provide guidance and new opinions for the identification of bolting-related genes in P. praeruptorum.

kcnj13 regulates pigment cell shapes in zebrafish and has diverged by cis-regulatory evolution between Danio species

Teleost fish of the genus Danio are excellent models to study the genetic and cellular bases of pigment pattern variation in vertebrates. The two sister species Danio rerio and Danio aesculapii show divergent patterns of horizontal stripes and vertical bars that are partly caused by the divergence of the potassium channel gene kcnj13. Here, we show that kcnj13 is required only in melanophores for interactions with xanthophores and iridophores, which cause location-specific pigment cell shapes and thereby influence colour pattern and contrast in D. rerio. Cis-regulatory rather than protein coding changes underlie kcnj13 divergence between the two Danio species. Our results suggest that homotypic and heterotypic interactions between the pigment cells and their shapes diverged between species by quantitative changes in kcnj13 expression during pigment pattern diversification.

Direct inference and control of genetic population structure from RNA sequencing data

RNAseq data can be used to infer genetic variants, yet its use for estimating genetic population structure remains underexplored. Here, we construct a freely available computational tool (RGStraP) to estimate RNAseq-based genetic principal components (RG-PCs) and assess whether RG-PCs can be used to control for population structure in gene expression analyses. Using whole blood samples from understudied Nepalese populations and the Geuvadis study, we show that RG-PCs had comparable results to paired array-based genotypes, with high genotype concordance and high correlations of genetic principal components, capturing subpopulations within the dataset. In differential gene expression analysis, we found that inclusion of RG-PCs as covariates reduced test statistic inflation. Our paper demonstrates that genetic population structure can be directly inferred and controlled for using RNAseq data, thus facilitating improved retrospective and future analyses of transcriptomic data.

BBmix: a Bayesian beta-binomial mixture model for accurate genotyping from RNA-sequencing

MOTIVATION

While many pipelines have been developed for calling genotypes using RNA-sequencing (RNA-Seq) data, they all have adapted DNA genotype callers that do not model biases specific to RNA-Seq such as allele-specific expression (ASE).

RESULTS

Here, we present Bayesian beta-binomial mixture model (BBmix), a Bayesian beta-binomial mixture model that first learns the expected distribution of read counts for each genotype, and then deploys those learned parameters to call genotypes probabilistically. We benchmarked our model on a wide variety of datasets and showed that our method generally performed better than competitors, mainly due to an increase of up to 1.4% in the accuracy of heterozygous calls, which may have a big impact in reducing false positive rate in applications sensitive to genotyping error such as ASE. Moreover, BBmix can be easily incorporated into standard pipelines for calling genotypes. We further show that parameters are generally transferable within datasets, such that a single learning run of less than 1 h is sufficient to call genotypes in a large number of samples.

AVAILABILITY AND IMPLEMENTATION

We implemented BBmix as an R package that is available for free under a GPL-2 licence at https://gitlab.com/evigorito/bbmix and https://cran.r-project.org/package=bbmix with accompanying pipeline at https://gitlab.com/evigorito/bbmix_pipeline.

A deep-learning-based RNA-seq germline variant caller

Summary

RNA sequencing (RNA-seq) can be applied to diverse tasks including quantifying gene expression, discovering quantitative trait loci and identifying gene fusion events. Although RNA-seq can detect germline variants, the complexities of variable transcript abundance, target capture and amplification introduce challenging sources of error. Here, we extend DeepVariant, a deep-learning-based variant caller, to learn and account for the unique challenges presented by RNA-seq data. Our DeepVariant RNA-seq model produces highly accurate variant calls from RNA-sequencing data, and outperforms existing approaches such as Platypus and GATK. We examine factors that influence accuracy, how our model addresses RNA editing events and how additional thresholding can be used to facilitate our models' use in a production pipeline.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Integrated microbiome-metabolome-genome axis data of Laiwu and Lulai pigs

Excessive fat deposition can trigger metabolic diseases, and it is crucial to identify factors that can break the link between fat deposition and metabolic diseases. Healthy obese Laiwu pigs (LW) are high in fat content but resistant to metabolic diseases. In this study, we compared the fecal microbiome, fecal and blood metabolome, and genome of LW and Lulai pigs (LU) to identify factors that can block the link between fat deposition and metabolic diseases. Our results show significant differences in Spirochetes and Treponema, which are involved in carbohydrate metabolism, between LW and LU. The fecal and blood metabolome composition was similar, and some anti-metabolic disease components of blood metabolites were different between the two breeds of pigs. The predicted differential RNA is mainly enriched in lipid metabolism and glucose metabolism, which is consistent with the functions of differential microbiota and metabolites. The down-regulated gene RGP1 is strongly negatively correlated with Treponema. Our omics data would provide valuable resources for further scientific research on healthy obesity in both human and porcine.

Robust identification of regulatory variants (eQTLs) using a differential expression framework developed for RNA-sequencing

BACKGROUND

A gap currently exists between genetic variants and the underlying cell and tissue biology of a trait, and expression quantitative trait loci (eQTL) studies provide important information to help close that gap. However, two concerns that arise with eQTL analyses using RNA-sequencing data are normalization of data across samples and the data not following a normal distribution. Multiple pipelines have been suggested to address this. For instance, the most recent analysis of the human and farm Genotype-Tissue Expression (GTEx) project proposes using trimmed means of M-values (TMM) to normalize the data followed by an inverse normal transformation.

RESULTS

In this study, we reasoned that eQTL analysis could be carried out using the same framework used for differential gene expression (DGE), which uses a negative binomial model, a statistical test feasible for count data. Using the GTEx framework, we identified 35 significant eQTLs (P < 5 × 10^-8) following the ANOVA model and 39 significant eQTLs (P < 5 × 10^-8) following the additive model. Using a differential gene expression framework, we identified 930 and six significant eQTLs (P < 5 × 10^-8) following an analytical framework equivalent to the ANOVA and additive model, respectively. When we compared the two approaches, there was no overlap of significant eQTLs between the two frameworks. Because we defined specific contrasts, we identified trans eQTLs that more closely resembled what we expect from genetic variants showing complete dominance between alleles. Yet, these were not identified by the GTEx framework.

CONCLUSIONS

Our results show that transforming RNA-sequencing data to fit a normal distribution prior to eQTL analysis is not required when the DGE framework is employed. Our proposed approach detected biologically relevant variants that otherwise would not have been identified due to data transformation to fit a normal distribution.

Genome assembly, resequencing and genome-wide association analyses provide novel insights into the origin, evolution and flower colour variations of flowering cherry

Flowering cherry is a very popular species around the world. High-quality genome resources for different elite cultivars are needed, and the understanding of their origins and the regulation of key ornamental traits are limited for this tree. Here, a high-quality chromosome-scale genome of Prunus campanulata 'Plena' (PCP), which is a native and elite flowering cherry cultivar in China, was generated. The contig N50 of the genome was 18.31 Mb, and 99.98% of its contigs were anchored to eight chromosomes. Furthermore, a total of 306 accessions of flowering cherry germplasm and six lines of outgroups were collected. Resequencing of these 312 lines was performed, and 761 267 high-quality genomic variants were obtained. The origins of flowering cherry were predicted, and these 306 accessions could be classified into three clades, A, B and C. According to phylogenetic analysis, we predicted two origins of flowering cherry. Flowering cherry in clade A originated in southern China, such as in the Himalayan Mountains, while clades B and C originated in northeastern China. Finally, a genome-wide association study of flower colour was performed for all 312 accessions of flowering cherry germplasm. A total of seven quantitative trait loci (QTLs) were identified. One gene encoding glycosylate transferase was predicted as the candidate gene for one QTL. Taken together, our results provide a valuable genomic resource and novel insights into the origin, evolution and flower colour variations of flowering cherry.

Genetic Variants and Their Putative Effects on microRNA-Seed Sites: Characterization of the 3' Untranslated Region of Genes Associated with Temperament

The 3' untranslated region has an important role in gene regulation through microRNAs, and it has been estimated that microRNAs regulate up to 50% of coding genes in mammals. With the aim of allelic variant identification of 3' untranslated region microRNA seed sites, the 3' untranslated region was searched for seed sites of four temperament-associated genes (CACNG4, EXOC4, NRXN3, and SLC9A4). The microRNA seed sites were predicted in the four genes, and the CACNG4 gene had the greatest number with 12 predictions. To search for variants affecting the predicted microRNA seed sites, the four 3' untranslated regions were re-sequenced in a Brahman cattle population. Eleven single nucleotide polymorphisms were identified in the CACNG4, and eleven in the SLC9A4. Rs522648682:T>G of the CACNG4 gene was located at the predicted seed site for bta-miR-191. Rs522648682:T>G evidenced an association with both exit velocity (p = 0.0054) and temperament score (p = 0.0097). The genotype TT had a lower mean exit velocity (2.93 ± 0.4 m/s) compared with the TG and GG genotypes (3.91 ± 0.46 m/s and 3.67 ± 0.46 m/s, respectively). The allele associated with the temperamental phenotype antagonizes the seed site, disrupting the bta-miR-191 recognition. The G allele of CACNG4-rs522648682 has the potential to influence bovine temperament through a mechanism associated with unspecific recognition of bta-miR-191.

Strain-Level Dynamics Reveal Regulatory Roles in Atopic Eczema by Gut Bacterial Phages

The vast population of bacterial phages or viruses (virome) plays pivotal roles in the ecology of human microbial flora and health conditions. Obstacles, including poor viral sequence inference, strain-sensitive virus-host relationship, and the high diversity among individuals, hinder the in-depth understanding of the human virome. We conducted longitudinal studies of the virome based on constructing a high-quality personal reference metagenome (PRM). By applying long-read sequencing for representative samples, we could build a PRM of high continuity that allows accurate annotation and abundance estimation of viruses and bacterial species in all samples of the same individual by aligning short sequencing reads to the PRM. We applied this approach to a series of fecal samples collected for 6 months from a 2-year-old boy who had experienced a 2-month flare-up of atopic eczema (dermatitis) in this period. We identified 31 viral strains in the patient's gut microbiota and deciphered their strain-level relationship to their bacterial hosts. Among them, a lytic crAssphage developed into a dozen substrains and coordinated downregulation in the catabolism of aromatic amino acids (AAAs) in their host bacteria which govern the production of immune-active AAA derivates. The metabolic alterations confirmed based on metabolomic assays cooccurred with symptom remission. Our PRM-based analysis provides an easy approach for deciphering the dynamics of the strain-level human gut virome in the context of entire microbiota. Close temporal correlations among virome alteration, microbial metabolism, and disease remission suggest a potential mechanism for how bacterial phages in microbiota are intimately related to human health. IMPORTANCE The vast populations of viruses or bacteriophages in human gut flora remain mysterious. However, poor annotation and abundance estimation remain obstacles to strain-level analysis and clarification of their roles in microbiome ecology and metabolism associated with human health and diseases. We demonstrate that a personal reference metagenome (PRM)-based approach provides strain-level resolution for analyzing the gut microbiota-associated virome. When applying such an approach to longitudinal samples collected from a 2-year-old boy who has experienced a 2-month flare-up of atopic eczema, we observed thriving substrains of a lytic crAssphage, showing temporal correlation with downregulated catabolism of aromatic amino acids, lower production of immune-active metabolites, and remission of the disease. The PRM-based approach is practical and powerful for strain-centric analysis of the human gut virome, and the underlying mechanism of how strain-level virome dynamics affect disease deserves further investigation.

DNA methylation entropy is associated with DNA sequence features and developmental epigenetic divergence

Epigenetic information defines tissue identity and is largely inherited in development through DNA methylation. While studied mostly for mean differences, methylation also encodes stochastic change, defined as entropy in information theory. Analyzing allele-specific methylation in 49 human tissue sample datasets, we find that methylation entropy is associated with specific DNA binding motifs, regulatory DNA, and CpG density. Then applying information theory to 42 mouse embryo methylation datasets, we find that the contribution of methylation entropy to time- and tissue-specific patterns of development is comparable to the contribution of methylation mean, and methylation entropy is associated with sequence and chromatin features conserved with human. Moreover, methylation entropy is directly related to gene expression variability in development, suggesting a role for epigenetic entropy in developmental plasticity.

Aneuploidy and gene dosage regulate filamentation and host colonization by Candida albicans

Aneuploidy is a frequent occurrence in fungal species where it can alter gene expression and promote adaptation to a variety of environmental cues. Multiple forms of aneuploidy have been observed in the opportunistic fungal pathogen Candida albicans, which is a common component of the human gut mycobiome but can escape this niche and cause life-threatening systemic disease. Using a barcode sequencing (Bar-seq) approach, we evaluated a set of diploid C. albicans strains and found that a strain carrying a third copy of chromosome (Chr) 7 was associated with increased fitness during both gastrointestinal (GI) colonization and systemic infection. Our analysis revealed that the presence of a Chr 7 trisomy resulted in decreased filamentation, both in vitro and during GI colonization, relative to isogenic euploid controls. A target gene approach demonstrated that NRG1, encoding a negative regulator of filamentation located on Chr 7, contributes to increased fitness of the aneuploid strain due to inhibition of filamentation in a gene dosage-dependent fashion. Together, these experiments establish how aneuploidy enables the reversible adaptation of C. albicans to its host via gene dosage-dependent regulation of morphology.

Genomic evidence reveals intraspecific divergence of the hot-spring snake (Thermophis baileyi), an endangered reptile endemic to the Qinghai-Tibet plateau

Understanding how and why species evolve requires knowledge on intraspecific divergence. In this study, we examined intraspecific divergence in the endangered hot-spring snake (Thermophis baileyi), an endemic species on the Qinghai-Tibet Plateau (QTP). Whole-genome resequencing of 58 sampled individuals from 15 populations was performed to identify the drivers of intraspecific divergence and explore the potential roles of genes under selection. Our analyses resolved three groups, with major intergroup admixture occurring in regions of group contact. Divergence probably occurred during the Pleistocene as a result of glacial climatic oscillations, Yadong-Gulu rift, and geothermal fields differentiation, while complex gene flow between group pairs reflected a unique intraspecific divergence pattern on the QTP. Intergroup fixed loci involved selected genes functionally related to divergence and local adaptation, especially adaptation to hot spring microenvironments in different geothermal fields. Analysis of structural variants, genetic diversity, inbreeding, and genetic load indicated that the hot-spring snake population has declined to a low level with decreased diversity, which is important for the conservation management of this endangered species. Our study demonstrated that the integration of demographic history, gene flow, genomic divergence genes, and other information is necessary to distinguish the evolutionary processes involved in speciation.

A chromosome-level genome assembly for Erianthus fulvus provides insights into its biofuel potential and facilitates breeding for improvement of sugarcane

Erianthus produces substantial biomass, exhibits a good Brix value, and shows wide environmental adaptability, making it a potential biofuel plant. In contrast to closely related sorghum and sugarcane, Erianthus can grow in degraded soils, thus releasing pressure on agricultural lands used for biofuel production. However, the lack of genomic resources for Erianthus hinders its genetic improvement, thus limiting its potential for biofuel production. In the present study, we generated a chromosome-scale reference genome for Erianthus fulvus Nees. The genome size estimated by flow cytometry was 937 Mb, and the assembled genome size was 902 Mb, covering 96.26% of the estimated genome size. A total of 35 065 protein-coding genes were predicted, and 67.89% of the genome was found to be repetitive. A recent whole-genome duplication occurred approximately 74.10 million years ago in the E. fulvus genome. Phylogenetic analysis showed that E. fulvus is evolutionarily closer to S. spontaneum and diverged after S. bicolor. Three of the 10 chromosomes of E. fulvus formed through rearrangements of ancestral chromosomes. Phylogenetic reconstruction of the Saccharum complex revealed a polyphyletic origin of the complex and a sister relationship of E. fulvus with Saccharum sp., excluding S. arundinaceum. On the basis of the four amino acid residues that provide substrate specificity, the E. fulvus SWEET proteins were classified as mono- and disaccharide sugar transporters. Ortho-QTL genes identified for 10 biofuel-related traits may aid in the rapid screening of E. fulvus populations to enhance breeding programs for improved biofuel production. The results of this study provide valuable insights for breeding programs aimed at improving biofuel production in E. fulvus and enhancing sugarcane introgression programs.

Spontaneous immortalization of chicken fibroblasts generates stable, high-yield cell lines for serum-free production of cultured meat

Cellular agriculture could meet growing demand for animal products, but yields are typically low and regulatory bodies restrict genetic modification for cultured meat production. Here we demonstrate the spontaneous immortalization and genetic stability of fibroblasts derived from several chicken breeds. Cell lines were adapted to grow as single-cell suspensions using serum-free culture medium, reaching densities of 108 × 10⁶ cells per ml in continuous culture, corresponding to yields of 36% w/v. We show that lecithin activates peroxisome proliferator-activated receptor gamma (PPARγ), inducing adipogenesis in immortalized fibroblasts. Blending cultured adipocyte-like cells with extruded soy protein, formed chicken strips in which texture was supported by animal and plant proteins while aroma and flavour were driven by cultured animal fat. Visual and sensory analysis graded the product 4.5/5.0, with 85% of participants extremely likely to replace their food choice with this cultured meat product. Immortalization without genetic modification and high-yield manufacturing are critical for the market realization of cultured meat.

Insertion of a TRIM-like sequence in MdFLS2-1 promoter is associated with its allele-specific expression in response to Alternaria alternata in apple

Alternaria blotch disease, caused by Alternaria alternata apple pathotype (AAAP), is one of the major fungal diseases in apple. Early field observations revealed, the anther-derived homozygote Hanfu line (HFTH1) was highly susceptible to AAAP, whereas Hanfu (HF) exhibited resistance to AAAP. To understand the molecular mechanisms underlying the difference in sensitivity of HF and HFTH1 to AAAP, we performed allele-specific expression (ASE) analysis and comparative transcriptomic analysis before and after AAAP inoculation. We reported an important immune gene, namely, MdFLS2, which displayed strong ASE in HF with much lower expression levels of HFTH1-derived alleles. Transient overexpression of the dominant allele of MdFLS2-1 from HF in GL-3 apple leaves could enhance resistance to AAAP and induce expression of genes related to salicylic acid pathway. In addition, MdFLS2-1 was identified with an insertion of an 85-bp terminal-repeat retrotransposon in miniature (TRIM) element-like sequence in the upstream region of the nonreference allele. In contrast, only one terminal direct repeat (TDR) from TRIM-like sequence was present in the upstream region of the HFTH1-derived allele MdFLS2-2. Furthermore, the results of luciferase and β-glucuronidase reporter assays demonstrated that the intact TRIM-like sequence has enhancer activity. This suggested that insertion of the TRIM-like sequence regulates the expression level of the allele of MdFLS2, in turn, affecting the sensitivity of HF and HFTH1 to AAAP.

Intra- and Interspecies RNA-Seq Based Variants in the Lactation Process of Ruminants

The RNA-Seq data provides new opportunities for the detection of transcriptome variants' single nucleotide polymorphisms (SNPs) in various species and tissues. Herein, milk samples from two sheep breeds and two cow breeds were utilized to characterize the genetic variation in the coding regions in three stages (before-peak (BP), peak (P), and after-peak (AP)) of the lactation process. In sheep breeds Assaf and Churra, 100,462 and 97,768, 65,996 and 62,161, and 78,656 and 39,245 variants were observed for BP, P, and AP lactation stages, respectively. The number of specific variants was 59,798 and 76,419, 11,483 and 49,210, and 104,033 and 320,817 in cow breeds Jersy and Kashmiri, respectively, for BP, P, and AP stages. Via the transcriptome analysis of variation in regions containing QTL for fat, protein percentages, and milk yield, we detected a number of pathways and genes harboring mutations that could influence milk production attributes. Many SNPs detected here can be regarded as appropriate markers for custom SNP arrays or genotyping platforms to conduct association analyses among commercial populations. The results of this study offer new insights into milk production genetic mechanisms in cow and sheep breeds, which can contribute to designing suitable breeding systems for optimal milk production.

Applying multi-omics data to study the genetic background of bovine respiratory disease infection in feedlot crossbred cattle

Bovine respiratory disease (BRD) is the most common and costly infectious disease affecting the wellbeing and productivity of beef cattle in North America. BRD is a complex disease whose development is dependent on environmental factors and host genetics. Due to the polymicrobial nature of BRD, our understanding of the genetic and molecular mechanisms underlying the disease is still limited. This knowledge would augment the development of better genetic/genomic selection strategies and more accurate diagnostic tools to reduce BRD prevalence. Therefore, this study aimed to utilize multi-omics data (genomics, transcriptomics, and metabolomics) analyses to study the genetic and molecular mechanisms of BRD infection. Blood samples of 143 cattle (80 BRD; 63 non-BRD animals) were collected for genotyping, RNA sequencing, and metabolite profiling. Firstly, a genome-wide association study (GWAS) was performed for BRD susceptibility using 207,038 SNPs. Two SNPs (Chr5:25858264 and BovineHD1800016801) were identified as associated (p-value <1 × 10^-5) with BRD susceptibility. Secondly, differential gene expression between BRD and non-BRD animals was studied. At the significance threshold used (log₂FC>2, logCPM>2, and FDR<0.01), 101 differentially expressed (DE) genes were identified. These DE genes significantly (p-value <0.05) enriched several immune responses related functions such as inflammatory response. Additionally, we performed expression quantitative trait loci (eQTL) analysis and identified 420 cis-eQTLs and 144 trans-eQTLs significantly (FDR <0.05) associated with the expression of DE genes. Interestingly, eQTL results indicated the most significant SNP (Chr5:25858264) identified via GWAS was a cis-eQTL for DE gene GPR84. This analysis also demonstrated that an important SNP (rs209419196) located in the promoter region of the DE gene BPI significantly influenced the expression of this gene. Finally, the abundance of 31 metabolites was significantly (FDR <0.05) different between BRD and non-BRD animals, and 17 of them showed correlations with multiple DE genes, which shed light on the interactions between immune response and metabolism. This study identified associations between genome, transcriptome, metabolome, and BRD phenotype of feedlot crossbred cattle. The findings may be useful for the development of genomic selection strategies for BRD susceptibility, and for the development of new diagnostic and therapeutic tools.

Evolution of weedy giant ragweed (Ambrosia trifida): Multiple origins and gene expression variability facilitates weediness

Agricultural weeds may originate from wild populations, but the origination patterns and genetics underlying this transition remain largely unknown. Analysis of weedy-wild paired populations from independent locations may provide evidence to identify key genetic variation contributing to this adaptive shift. We performed genetic variation and expression analyses on transcriptome data from 67 giant ragweed samples collected from different locations in Ohio, Iowa, and Minnesota and found geographically separated weedy populations likely originated independently from their adjacent wild populations, but subsequent spreading of weedy populations also occurred locally. By using eight closely related weedy-wild paired populations, we identified thousands of unique transcripts in weedy populations that reflect shared or specific functions corresponding, respectively, to both convergently evolved and population-specific weediness processes. In addition, differential expression of specific groups of genes was detected between weedy and wild giant ragweed populations using gene expression diversity and gene co-expression network analyses. Our study suggests an integrated route of weedy giant ragweed origination, consisting of independent origination combined with the subsequent spreading of certain weedy populations, and provides several lines of evidence to support the hypothesis that gene expression variability plays a key role in the evolution of weedy species.

Molecular insights into high-altitude adaption and acclimatisation of Aporrectodea caliginosa

A megabase genome assembly for Aporrectodea caliginosa is presented with transcriptomic and SNP-based evidence for acclimatisation and adaption to extreme weather conditions found at high altitude.

Here, we explore the high-altitude adaptions and acclimatisation of Aporrectodea caliginosa. Population diversity is assessed through mitochondrial barcoding, identifying closely related populations across the island of Pico (Azores). We present the first megabase N50 assembly size (1.2 Mbp) genome for A. caliginosa. High- and low-altitude populations were exposed experimentally to a range of oxygen and temperature conditions, simulating altitudinal conditions, and the transcriptomic responses explored. SNP densities are assessed to identify signatures of selective pressure and their link to differentially expressed genes. The high-altitude A. caliginosa population had lower differential expression and fewer co-expressed genes between conditions, indicating a more condition-refined epigenetic response. Genes identified as under adaptive pressure through F_st and nucleotide diversity in the high-altitude population clustered around the differentially expressed an upstream environmental response control gene, HMGB1. The high-altitude population of A. caliginosa indicated adaption and acclimatisation to high-altitude conditions and suggested resilience to extreme weather events. This mechanistic understanding could help offer a strategy in further identifying other species capable of maintaining soil fertility in extreme environments.

EfGD: the Erianthus fulvus genome database

Erianthus fulvus (TaxID: 154759) is a valuable germplasm resource in sugarcane breeding and research and has excellent agronomic traits, such as drought resistance, cold resistance, barren tolerance and high brix. With a stable chromosome number (2n = 20) and a small genome (0.9 Gb), it is an ideal candidate for research on sugarcane. Next-generation sequencing technology has enabled a growing number of studies to focus on genomics. Due to the large amount of omics data available, a centralized platform is necessary for ensuring the consistency, independence and maintainability of these large-scale datasets through storage, analysis and integration. Here, we present a comprehensive database for the E. fulvus genome, EfGD. By using the new high-quality reference genome and its annotations, the EfGD provides the largest whole-genome sequencing reference dataset for E. fulvus, which archives 27 165 protein-coding genes and 55 564 488 SNPs from 202 newly resequenced genomes. Furthermore, we created a user-friendly graphical interface for visualizing genomic diversity, population structure and evolution and provided other tools on an open platform.

Database URL: https://efgenome.ynau.edu.cn

Integrative Analysis Between Genome-Wide Association Study and Expression Quantitative Trait Loci Reveals Bovine Muscle Gene Expression Regulatory Polymorphisms Associated With Intramuscular Fat and Backfat Thickness

Understanding the architecture of gene expression is fundamental to unravel the molecular mechanisms regulating complex traits in bovine, such as intramuscular fat content (IMF) and backfat thickness (BFT). These traits are economically important for the beef industry since they affect carcass and meat quality. Our main goal was to identify gene expression regulatory polymorphisms within genomic regions (QTL) associated with IMF and BFT in Nellore cattle. For that, we used RNA-Seq data from 193 Nellore steers to perform SNP calling analysis. Then, we combined the RNA-Seq SNP and a high-density SNP panel to obtain a new dataset for further genome-wide association analysis (GWAS), totaling 534,928 SNPs. GWAS was performed using the Bayes B model. Twenty-one relevant QTL were associated with our target traits. The expression quantitative trait loci (eQTL) analysis was performed using Matrix eQTL with the complete SNP dataset and 12,991 genes, revealing a total of 71,033 cis and 36,497 trans-eQTL (FDR &lt; 0.05). Intersecting with QTL for IMF, we found 231 eQTL regulating the expression levels of 117 genes. Within those eQTL, three predicted deleterious SNPs were identified. We also identified 109 eQTL associated with BFT and affecting the expression of 54 genes. This study revealed genomic regions and regulatory SNPs associated with fat deposition in Nellore cattle. We highlight the transcription factors FOXP4, FOXO3, ZSCAN2, and EBF4, involved in lipid metabolism-related pathways. These results helped us to improve our knowledge about the genetic architecture behind important traits in cattle.

Genetic basis investigation of wattle phenotype in goat using genome-wide sequence data

In domestic goats, wattles often appear in even numbers, mostly on the neck and a few under the ear. Goat wattle is composed of ectopic cartilage tissue covered by skin and was reported as a dominant inheritance. Thirty-eight goats from two Southwest Chinese breeds were studied to elucidate the genetic basis of wattle phenotype in goat. Their genomes were sequenced for wide-genome selective sweep analysis (WGSA) and a genome-wide association study (GWAS). The WGSA results revealed 500 candidate genes identified by fixation index and π ratio and 261 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enriched with 195 genes and 38 significantly enriched KEGG items. In particular, three chondrogenesis-related pathways (Wnt, Hippo and MAPK signaling pathways) were found. Among the 500 genes, 474 were enriched to 2855 Gene Ontology items, and four (BMP2, BMP4, RARA and MSX1) were annotated in the regulation and development of chondrogenesis. Four chondrogenesis-related genes (GREM1, NEDD4, ATG7 and ITGA1) were identified from 519 single-nucleotide polymorphisms (SNPs) with a GWAS above the threshold. Six and 11 SNPs on chromosome 10 are located on GREM1 and NEDD4 respectively, and the highest numbers of SNPs on chromosomes 20 and 22 are located on ITGA1 and ATG7 respectively. All of these genes are related to cartilage development. This study identified a series of genes related to chondroplasia by GWAS and WGSA and presented the possibility that wattle inheritance may be influenced by multiple genes. This work provides a new theoretical understanding of the hereditary basis of wattle phenotype.

Characterization of Potential Molecular Markers in Lac Insect Kerria lacca (Kerr) Responsible for Lac Production

Kerria lacca (Kerr) is an important lac insect extensively used in industrial products in the form of resin, wax and dye. The scarce knowledge on molecular markers for K. lacca is a barrier in elucidating genetic information. Our study identified a total of 16,921 single-nucleotide polymorphisms (SNPs), and 6231 insertions and deletions (InDels)-of which, intergenic variation accounted for 41.22% and 56.30%, and exonic variation accounted for 39.10% and 17.46%, of SNPs and InDels, respectively. Observation of SNPs suggested that nucleotide substitution frequency and transition to transversion (Ts/Tv) ratio were highest at the late adult stage, 3.97, compared to at the other stages, with a genome-wide Ts/Tv ratio of 2.95. The maximum number of SNPs, 2853 (16.86%), was identified in chromosome 8, while the lowest, 1126 (6.65%), was identified in chromosome 7. The maximum and minimum numbers of InDels were located on chromosome 1 and 7, with 834 (13.38%) and 519 (8.33%), respectively. Annotation showed that highest numbers of exonic and intergenic SNPs were present at the late adult stage, whereas the maximum number of InDels was found at the larval stage. On the basis of gene function, 47 gene variations were screened and 23 candidate genes were identified in associations with lac production. Concluding work will enhance knowledge on molecular markers to facilitate an increase in lac production in K. lacca as well as other lac insects.

Novel homozygous nonsense mutation of MLIP and compensatory alternative splicing

Despite the growing accessibility of clinical sequencing, functional interpretation of variants remains a major hurdle to molecular diagnostics of Mendelian diseases. We aimed to describe a new adult-onset myopathy with muscle weakness and hyperCKemia caused by a nonsense variant in muscular LMNA-interacting protein (MLIP). Following RNA-sequencing, differential expression analysis uncovered a significant downregulation of this gene, which had a surprisingly mild effect on MLIP protein expression. RT-PCR and long-read sequencing (LRS) both support an important transcriptome shift in the patient, where decreased MLIP levels are seemingly due to nonsense-mediated decay of transcripts containing the exon 5 mutation. Moreover, a compensatory mechanism upregulates the functionally lacking isoforms and generates novel transcripts. These results support the recently discovered clinical implications of MLIP variants in myopathies, highlighting for the first time its relevance in adult-onset cases. These results also underline the power of LRS as a tool for the functional assessment of variants of unknown significance (VUS), as well as the definition of accurate isoform profile annotations in a tissue-specific manner.

Targeted RNAseq Improves Clinical Diagnosis of Very Early-Onset Pediatric Immune Dysregulation

Despite increased use of whole exome sequencing (WES) for the clinical analysis of rare disease, overall diagnostic yield for most disorders hovers around 30%. Previous studies of mRNA have succeeded in increasing diagnoses for clearly defined disorders of monogenic inheritance. We asked if targeted RNA sequencing could provide similar benefits for primary immunodeficiencies (PIDs) and very early-onset inflammatory bowel disease (VEOIBD), both of which are difficult to diagnose due to high heterogeneity and variable severity. We performed targeted RNA sequencing of a panel of 260 immune-related genes for a cohort of 13 patients (seven suspected PID cases and six VEOIBD) and analyzed variants, splicing, and exon usage. Exonic variants were identified in seven cases, some of which had been previously prioritized by exome sequencing. For four cases, allele specific expression or lack thereof provided additional insights into possible disease mechanisms. In addition, we identified five instances of aberrant splicing associated with four variants. Three of these variants had been previously classified as benign in ClinVar based on population frequency. Digenic or oligogenic inheritance is suggested for at least two patients. In addition to validating the use of targeted RNA sequencing, our results show that rare disease research will benefit from incorporating contributing genetic factors into the diagnostic approach.

Investigating underlying human immunity genes, implicated diseases and their relationship to COVID-19

Aim: A human immunogenetics variation study was conducted in samples collected from diverse COVID-19 populations. Materials & methods: Whole-genome and whole-exome sequencing (WGS/WES), data processing, analysis and visualization pipeline were applied to identify variants associated with genes of interest. Results: A total of 2886 mutations were found across the entire set of 13 genomes. Functional annotation of the gene variants revealed mutation type and protein change. Many variants were found to be biologically implicated in COVID-19. The involvement of these genes was also found in multiple other diseases. Conclusion: The analysis determined that ACE2, TMPRSS4, TMPRSS2, SLC6A20 and FYCOI had functional implications and TMPRSS4 was the gene most altered in virally infected patients.

The quest to establish an understanding of the genetics underlying COVID-19 is a central focus of life sciences today. COVID-19 is triggered by SARS-CoV-2, a single-stranded RNA respiratory virus. Several clinical-genomics studies have emerged positing different human gene mutations occurring due to COVID-19. A global analysis of these genes was conducted targeting major components of the immune system to identify possible variations likely to be involved in COVID-19 predisposition. Gene-variant analysis was performed on whole-genome sequencing samples collected from diverse populations. ACE2, TMPRSS4, TMPRSS2, SLC6A20 and FYCOI were found to have functional implications and TMPRSS4 may have a role in the severity of clinical manifestations of COVID-19.

Cardiac chamber-specific genetic alterations suggest candidate genes and pathways implicating the left ventricle in the pathogenesis of atrial fibrillation

It is believed that the atria play a predominant role in the initiation and maintenance of atrial fibrillation (AF), while the role of left ventricular dysfunction in the pathophysiology remains enigmatic. We sought to dissect chamber specificity of AF-associated transcriptional changes using RNA-sequencing. We performed intra- and inter-chamber differential expression analyses comparing AF against sinus rhythm to identify genes specifically dysregulated in human left atria, right atria, and left ventricle (LV), and integrated known AF genetic associations with expression quantitative trait loci datasets to inform the potential for disease causal contributions within each chamber. Inter-chamber patterns changed drastically. Vast AF-associated transcriptional changes specific to LV, enriched for biological pathway terms implicating mitochondrial function, developmental processes and immunity, were supported at the genetic level, but no major enrichments for candidate genes specific to the atria were found. Our observations suggest an active role of the LV in the pathogenesis of AF.

Comparison of seven SNP calling pipelines for the next-generation sequencing data of chickens

Single nucleotide polymorphisms (SNPs) are widely used in genome-wide association studies and population genetics analyses. Next-generation sequencing (NGS) has become convenient, and many SNP-calling pipelines have been developed for human NGS data. We took advantage of a gap knowledge in selecting the appropriated SNP calling pipeline to handle with high-throughput NGS data. To fill this gap, we studied and compared seven SNP calling pipelines, which include 16GT, genome analysis toolkit (GATK), Bcftools-single (Bcftools single sample mode), Bcftools-multiple (Bcftools multiple sample mode), VarScan2-single (VarScan2 single sample mode), VarScan2-multiple (VarScan2 multiple sample mode) and Freebayes pipelines, using 96 NGS data with the different depth gradients of approximately 5X, 10X, 20X, 30X, 40X, and 50X coverage from 16 Rhode Island Red chickens. The sixteen chickens were also genotyped with a 50K SNP array, and the sensitivity and specificity of each pipeline were assessed by comparison to the results of SNP arrays. For each pipeline, except Freebayes, the number of detected SNPs increased as the input read depth increased. In comparison with other pipelines, 16GT, followed by Bcftools-multiple, obtained the most SNPs when the input coverage exceeded 10X, and Bcftools-multiple obtained the most when the input was 5X and 10X. The sensitivity and specificity of each pipeline increased with increasing input. Bcftools-multiple had the highest sensitivity numerically when the input ranged from 5X to 30X, and 16GT showed the highest sensitivity when the input was 40X and 50X. Bcftools-multiple also had the highest specificity, followed by GATK, at almost all input levels. For most calling pipelines, there were no obvious changes in SNP numbers, sensitivities or specificities beyond 20X. In conclusion, (1) if only SNPs were detected, the sequencing depth did not need to exceed 20X; (2) the Bcftools-multiple may be the best choice for detecting SNPs from chicken NGS data, but for a single sample or sequencing depth greater than 20X, 16GT was recommended. Our findings provide a reference for researchers to select suitable pipelines to obtain SNPs from the NGS data of chickens or nonhuman animals.

Population-level genome-wide STR discovery and validation for population structure and genetic diversity assessment of Plasmodium species

Short tandem repeats (STRs) are highly informative genetic markers that have been used extensively in population genetics analysis. They are an important source of genetic diversity and can also have functional impact. Despite the availability of bioinformatic methods that permit large-scale genome-wide genotyping of STRs from whole genome sequencing data, they have not previously been applied to sequencing data from large collections of malaria parasite field samples. Here, we have genotyped STRs using HipSTR in more than 3,000 Plasmodium falciparum and 174 Plasmodium vivax published whole-genome sequence data from samples collected across the globe. High levels of noise and variability in the resultant callset necessitated the development of a novel method for quality control of STR genotype calls. A set of high-quality STR loci (6,768 from P. falciparum and 3,496 from P. vivax) were used to study Plasmodium genetic diversity, population structures and genomic signatures of selection and these were compared to genome-wide single nucleotide polymorphism (SNP) genotyping data. In addition, the genome-wide information about genetic variation and other characteristics of STRs in P. falciparum and P. vivax have been available in an interactive web-based R Shiny application PlasmoSTR (https://github.com/bahlolab/PlasmoSTR).

Variant Calling from RNA-seq Data Using the GATK Joint Genotyping Workflow

The Genome Analysis Toolkit (GATK) developed at the Broad Institute provides state-of-the-art pipelines for germline and somatic variant discovery and genotyping. Unfortunately, the fully validated GATK pipeline for calling variant on RNAseq data is a Per-sample workflow that does not include the recent improvements seen in modern workflows, especially the possibility to perform joint genotyping analysis. Here, we describe how modern GATK commands from distinct workflows can be combined to call variants on RNAseq samples. We provide a detailed tutorial that starts with raw RNAseq reads and ends with filtered variants, of which some were shown to be associated with bovine paratuberculosis.

Prospects and challenges of cancer systems medicine: from genes to disease networks

It is becoming evident that holistic perspectives toward cancer are crucial in deciphering the overwhelming complexity of tumors. Single-layer analysis of genome-wide data has greatly contributed to our understanding of cellular systems and their perturbations. However, fundamental gaps in our knowledge persist and hamper the design of effective interventions. It is becoming more apparent than ever, that cancer should not only be viewed as a disease of the genome but as a disease of the cellular system. Integrative multilayer approaches are emerging as vigorous assets in our endeavors to achieve systemic views on cancer biology. Herein, we provide a comprehensive review of the approaches, methods and technologies that can serve to achieve systemic perspectives of cancer. We start with genome-wide single-layer approaches of omics analyses of cellular systems and move on to multilayer integrative approaches in which in-depth descriptions of proteogenomics and network-based data analysis are provided. Proteogenomics is a remarkable example of how the integration of multiple levels of information can reduce our blind spots and increase the accuracy and reliability of our interpretations and network-based data analysis is a major approach for data interpretation and a robust scaffold for data integration and modeling. Overall, this review aims to increase cross-field awareness of the approaches and challenges regarding the omics-based study of cancer and to facilitate the necessary shift toward holistic approaches.

JWES: a new pipeline for whole genome/exome sequence data processing, management, and gene-variant discovery, annotation, prediction, and genotyping

Whole genome and exome sequencing (WGS/WES) are the most popular next‐generation sequencing (NGS) methodologies and are at present often used to detect rare and common genetic variants of clinical significance. We emphasize that automated sequence data processing, management, and visualization should be an indispensable component of modern WGS and WES data analysis for sequence assembly, variant detection (SNPs, SVs), imputation, and resolution of haplotypes. In this manuscript, we present a newly developed findable, accessible, interoperable, and reusable (FAIR) bioinformatics‐genomics pipeline Java based Whole Genome/Exome Sequence Data Processing Pipeline (JWES) for efficient variant discovery and interpretation, and big data modeling and visualization. JWES is a cross‐platform, user‐friendly, product line application, that entails three modules: (a) data processing, (b) storage, and (c) visualization. The data processing module performs a series of different tasks for variant calling, the data storage module efficiently manages high‐volume gene‐variant data, and the data visualization module supports variant data interpretation with Circos graphs. The performance of JWES was tested and validated in‐house with different experiments, using Microsoft Windows, macOS Big Sur, and UNIX operating systems. JWES is an open‐source and freely available pipeline, allowing scientists to take full advantage of all the computing resources available, without requiring much computer science knowledge. We have successfully applied JWES for processing, management, and gene‐variant discovery, annotation, prediction, and genotyping of WGS and WES data to analyze variable complex disorders. In summary, we report the performance of JWES with some reproducible case studies, using open access and in‐house generated, high‐quality datasets.

Identification of cancer-related mutations in human pluripotent stem cells using RNA-seq analysis

Human pluripotent stem cells (hPSCs) are known to acquire genetic aberrations during in vitro propagation. In addition to recurrent chromosomal aberrations, it has recently been shown that these cells also gain point mutations in cancer-related genes, predominantly in TP53. The need for routine quality control of hPSCs is critical for both basic research and clinical applications. Here we discuss the relevance of detecting mutations for various hPSCs applications, and present a detailed protocol to identify cancer-related point mutations using data from RNA sequencing, an assay commonly performed during the growth and differentiation of hPSCs. In this protocol, we describe how to process and align the sequencing data, analyze it and conservatively interpret the results in order to generate an accurate estimation of mutations in tumor-related genes. This pipeline is designed to work in high throughput and is available as a software container at https://github.com/elyadlezmi/RNA2CM . The protocol requires minimal command-line skills and can be carried out in 1-2 d.

Genomics pipelines to investigate susceptibility in whole genome and exome sequenced data for variant discovery, annotation, prediction and genotyping

Over the last few decades, genomics is leading toward audacious future, and has been changing our views about conducting biomedical research, studying diseases, and understanding diversity in our society across the human species. The whole genome and exome sequencing (WGS/WES) are two of the most popular next-generation sequencing (NGS) methodologies that are currently being used to detect genetic variations of clinical significance. Investigating WGS/WES data for the variant discovery and genotyping is based on the nexus of different data analytic applications. Although several bioinformatics applications have been developed, and many of those are freely available and published. Timely finding and interpreting genetic variants are still challenging tasks among diagnostic laboratories and clinicians. In this study, we are interested in understanding, evaluating, and reporting the current state of solutions available to process the NGS data of variable lengths and types for the identification of variants, alleles, and haplotypes. Residing within the scope, we consulted high quality peer reviewed literature published in last 10 years. We were focused on the standalone and networked bioinformatics applications proposed to efficiently process WGS and WES data, and support downstream analysis for gene-variant discovery, annotation, prediction, and interpretation. We have discussed our findings in this manuscript, which include but not are limited to the set of operations, workflow, data handling, involved tools, technologies and algorithms and limitations of the assessed applications.

Whole genome sequencing of nearly isogenic WMI and WLI inbred rats identifies genes potentially involved in depression and stress reactivity

The WMI and WLI inbred rats were generated from the stress-prone, and not yet fully inbred, Wistar Kyoto (WKY) strain. These were selected using bi-directional selection for immobility in the forced swim test and were then sib-mated for over 38 generations. Despite the low level of genetic diversity among WKY progenitors, the WMI substrain is significantly more vulnerable to stress relative to the counter-selected WLI strain. Here we quantify numbers and classes of genomic sequence variants distinguishing these substrains with the long term goal of uncovering functional and behavioral polymorphism that modulate sensitivity to stress and depression-like phenotypes. DNA from WLI and WMI was sequenced using Illumina xTen, IonTorrent, and 10X Chromium linked-read platforms to obtain a combined coverage of ~ 100X for each strain. We identified 4,296 high quality homozygous SNPs and indels between the WMI and WLI. We detected high impact variants in genes previously implicated in depression (e.g. Gnat2), depression-like behavior (e.g. Prlr, Nlrp1a), other psychiatric disease (e.g. Pou6f2, Kdm5a, Reep3, Wdfy3), and responses to psychological stressors (e.g. Pigr). High coverage sequencing data confirm that the two substrains are nearly coisogenic. Nonetheless, the small number of sequence variants contributes to numerous well characterized differences including depression-like behavior, stress reactivity, and addiction related phenotypes. These selected substrains are an ideal resource for forward and reverse genetic studies using a reduced complexity cross.

PACAP Induces Light Aversion in Mice by an Inheritable Mechanism Independent of CGRP

The neuropeptides CGRP (calcitonin gene-related peptide) and PACAP (pituitary adenylate cyclase-activating polypeptide) have emerged as mediators of migraine, yet the potential overlap of their mechanisms remains unknown. Infusion of PACAP, like CGRP, can cause migraine in people, and both peptides share similar vasodilatory and nociceptive functions. In this study, we have used light aversion in mice as a surrogate for migraine-like photophobia to compare CGRP and PACAP and ask whether CGRP or PACAP actions were dependent on each other. Similar to CGRP, PACAP induced light aversion in outbred CD-1 mice. The light aversion was accompanied by increased resting in the dark, but not anxiety in a light-independent open field assay. Unexpectedly, about one-third of the CD-1 mice did not respond to PACAP, which was not seen with CGRP. The responder and nonresponder phenotypes were stable, inheritable, and not sex linked, although there was a trend for greater responses among male mice. RNA-sequencing analysis of trigeminal ganglia yielded hierarchical clustering of responder and nonresponder mice and revealed a number of candidate genes, including greater expression of the Trpc5 and Kcnk12 ion channels and glycoprotein hormones and receptors in a subset of male responder mice. Importantly, an anti-PACAP monoclonal antibody could block PACAP-induced light aversion but not CGRP-induced light aversion. Conversely, an anti-CGRP antibody could not block PACAP-induced light aversion. Thus, we propose that CGRP and PACAP act by independent convergent pathways that cause a migraine-like symptom in mice.SIGNIFICANCE STATEMENT The relationship between the neuropeptides CGRP (calcitonin gene-related peptide) and PACAP (pituitary adenylate cyclase-activating polypeptide) in migraine is relevant given that both peptides can induce migraine in people, yet to date only drugs that target CGRP are available. Using an outbred strain of mice, we were able to show that most, but not all, mice respond to PACAP in a preclinical photophobia assay. Our finding that CGRP and PACAP monoclonal antibodies do not cross-inhibit the other peptide indicates that CGRP and PACAP actions are independent and suggests that PACAP-targeted drugs may be effective in patients who do not respond to CGRP-based therapeutics.