Extravillous trophoblast cell lineage development is associated with active remodeling of the chromatin landscape.

The extravillous trophoblast cell lineage is a key feature of placentation and successful pregnancy. Knowledge of transcriptional regulation driving extravillous trophoblast cell development is limited. Here, we map the transcriptome and epigenome landscape as well as chromatin interactions of human trophoblast stem cells and their transition into extravillous trophoblast cells. We show that integrating chromatin accessibility, long-range chromatin interactions, transcriptomic, and transcription factor binding motif enrichment enables identification of transcription factors and regulatory mechanisms critical for extravillous trophoblast cell development. We elucidate functional roles for TFAP2C, SNAI1, and EPAS1 in the regulation of extravillous trophoblast cell development. EPAS1 is identified as an upstream regulator of key extravillous trophoblast cell transcription factors, including ASCL2 and SNAI1 and together with its target genes, is linked to pregnancy loss and birth weight. Collectively, we reveal activation of a dynamic regulatory network and provide a framework for understanding extravillous trophoblast cell specification in trophoblast cell lineage development and human placentation.

Direct haplotype-resolved 5-base HiFi sequencing for genome-wide profiling of hypermethylation outliers in a rare disease cohort.

Long-read HiFi genome sequencing allows for accurate detection and direct phasing of single nucleotide variants, indels, and structural variants. Recent algorithmic development enables simultaneous detection of CpG methylation for analysis of regulatory element activity directly in HiFi reads. We present a comprehensive haplotype resolved 5-base HiFi genome sequencing dataset from a rare disease cohort of 276 samples in 152 families to identify rare (~0.5%) hypermethylation events. We find that 80% of these events are allele-specific and predicted to cause loss of regulatory element activity. We demonstrate heritability of extreme hypermethylation including rare cis variants associated with short (~200 bp) and large hypermethylation events (>1 kb), respectively. We identify repeat expansions in proximal promoters predicting allelic gene silencing via hypermethylation and demonstrate allelic transcriptional events downstream. On average 30-40 rare hypermethylation tiles overlap rare disease genes per patient, providing indications for variation prioritization including a previously undiagnosed pathogenic allele in DIP2B causing global developmental delay. We propose that use of HiFi genome sequencing in unsolved rare disease cases will allow detection of unconventional diseases alleles due to loss of regulatory element activity.

DNA Methylation Near CPT1A and Changes in Triglyceride-rich Lipoproteins in Response to Weight-loss Diet Interventions.

CONTEXT: Carnitine palmitoyltransferase-1A, encoded by the CPT1A gene, plays a key role in the oxidation of long-chain fatty acids in the mitochondria and may be important in triglyceride metabolism. Previous work has shown that high fat intake was negatively associated with CPT1A methylation and positively associated with CPT1A expression. OBJECTIVE: We aim to investigate the association of DNA methylation (DNAm) at the CPT1A gene with reductions in triglycerides and triglyceride-rich lipoproteins (TRLs) in response to weight-loss diet interventions. METHODS: The current study included 538 White participants, who were randomly assigned to 1 of 4 diets varying in macronutrient components. We defined the regional DNAm at CPT1A as the average methylation level over CpGs within 500 bp of the 3 triglyceride-related DNAm sites. RESULTS: Dietary fat intake significantly modified the association between baseline DNAm at CPT1A and 2-year changes in total plasma triglycerides, independent of concurrent weight loss. Among participants assigned to a low-fat diet, a higher regional DNAm level at CPT1A was associated with a greater reduction in total plasma triglycerides at 2 years (P = .01), compared with those assigned to a high-fat diet (P = .64) (P interaction = .018). Further investigation on lipids and apolipoproteins in very low-density lipoprotein (VLDL) revealed similar interaction patterns for 2-year changes in VLDL-triglycerides, VLDL-cholesterol, and VLDL-apolipoprotein B (P interaction = .009, .002, and .016, respectively), but not for VLDL-apoC-III (P interaction = .36). CONCLUSION: Participants with a higher regional DNAm level at CPT1A benefit more in long-term improvement in triglycerides, particularly in the TRLs and related apolipoproteins when consuming a low-fat weight-loss diet.

Blood DNA methylation at TXNIP and glycemic changes in response to weight-loss diet interventions: the POUNDS lost trial.

BACKGROUND: Thioredoxin Interacting Protein (TXNIP) functions as a master regulator for glucose homeostasis. Hypomethylation at the 5'-cytosine-phosphate-guanine-3' (CpG) site cg19693031 of TXNIP has been consistently related to islet dysfunction, hyperglycemia, and type 2 diabetes. DNA methylation (DNAm) may reveal the missing mechanistic link between obesity and type 2 diabetes. We hypothesize that baseline DNAm level at TXNIP in blood may be associated with glycemic traits and their changes in response to weight-loss diet interventions. METHODS: We included 639 adult participants with overweight or obesity, who participated in a 2-year randomized weight-loss diet intervention. Baseline blood DNAm levels were profiled by high-resolution methylC-capture sequencing. We defined the regional DNAm level of TXNIP as the average methylation level over CpGs within 500 bp of cg19693031. Generalized linear regression models were used for main analyses. RESULTS: We found that higher regional DNAm at TXNIP was significantly correlated with lower fasting glucose, HbA1c, and Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) at baseline (P < 0.05 for all). Significant interactions were observed between dietary protein intake and DNAm on changes in insulin (P-interaction = 0.007) and HOMA-IR (P-interaction = 0.009) at 6 months. In participants with the highest tertile of regional DNAm at TXNIP, average protein (15%) intake was associated with a greater reduction in insulin (ß: -0.14; 95% CI: -0.24, -0.03; P = 0.011) and HOMA-IR (ß: -0.15; 95% CI: -0.26, -0.03; P = 0.014) than high protein (25%) intake, whereas no significant associations were found in those with the lower tertiles (P > 0.05). The interaction was attenuated to be non-significant at 2 years, presumably related to decreasing adherence to the diet intervention. CONCLUSIONS: Our data indicate that higher regional DNAm level at TXNIP was significantly associated with better fasting glucose, HbA1c, and HOMA-IR; and people with higher regional DNAm levels benefited more in insulin and HOMA-IR improvement by taking the average-protein weight-loss diet.

Immune cell residency in the nasal mucosa may partially explain respiratory disease severity across the age range.

Previous studies focusing on the age disparity in COVID-19 severity have suggested that younger individuals mount a more robust innate immune response in the nasal mucosa after infection with SARS-CoV-2. However, it is unclear if this reflects increased immune activation or increased immune residence in the nasal mucosa. We hypothesized that immune residency in the nasal mucosa of healthy individuals may differ across the age range. We applied single-cell RNA-sequencing and measured the cellular composition and transcriptional profile of the nasal mucosa in 35 SARS-CoV-2 negative children and adults, ranging in age from 4 months to 65 years. We analyzed in total of ~ 30,000 immune and epithelial cells and found that age and immune cell proportion in the nasal mucosa are inversely correlated, with little evidence for structural changes in the transcriptional state of a given cell type across the age range. Orthogonal validation by epigenome sequencing indicate that it is especially cells of the innate immune system that underlie the age-association. Additionally, we characterize the predominate immune cell type in the nasal mucosa: a resident T cell like population with potent antiviral properties. These results demonstrate fundamental changes in the immune cell makeup of the uninfected nasal mucosa over the lifespan. The resource we generate here is an asset for future studies focusing on respiratory infection and immunization strategies.

High-resolution epigenome analysis in nasal samples derived from children with respiratory viral infections reveals striking changes upon SARS-CoV-2 infection.

Background: DNA methylation patterns of the human genome can be modified by environmental stimuli and provide dense information on gene regulatory circuitries. We studied genome-wide DNA methylation in nasal samples from infants (<6 months) applying whole-genome bisulfite sequencing (WGBS) to characterize epigenome response to 10 different respiratory viral infections including SARS-CoV-2. Results: We identified virus-specific differentially methylated regions (vDMR) with human metapneumovirus (hMPV) and SARS-CoV-2 followed by Influenza B (Flu B) causing the weakest vs. strongest epigenome response with 496 vs. 78541 and 14361 vDMR, respectively. We found a strong replication rate of FluB (52%) and SARS-CoV-2 (42%) vDMR in independent samples indicating robust epigenome perturbation upon infection. Among the FluB and SARS-CoV-2 vDMRs, around 70% were hypomethylated and significantly enriched among epithelial cell-specific regulatory elements whereas the hypermethylated vDMRs for these viruses mapped more frequently to immune cell regulatory elements, especially those of the myeloid lineage. The hypermethylated vDMRs were also enriched among genes and genetic loci in monocyte activation pathways and monocyte count. Finally, we perform single-cell RNA-sequencing characterization of nasal mucosa in response to these two viruses to functionally analyze the epigenome perturbations. Which supports the trends we identified in methylation data and highlights and important role for monocytes. Conclusions: All together, we find evidence indicating genetic predisposition to innate immune response upon a respiratory viral infection. Our genome-wide monitoring of infant viral response provides first catalogue of associated host regulatory elements. Assessing epigenetic variation in individual patients may reveal evidence for viral triggers of childhood disease.

Quantitative Genetic Mapping and Genome Assembly in the Lesser Wax Moth Achroia grisella.

Specific characteristics of the male Achroia grisella acoustic mating signal determine a male's attractiveness toward females. These features are genetically variable in populations, and mapping experiments have been used to identify loci contributing to song variation, and understand the evolutionary forces acting on this important sexual trait. Here we built on this foundation and carried out QTL (Quantitative Trait Locus) mapping using >1,000 recombinant individuals, genotyping this large cohort at thousands of sequence-based markers covering the entire collection of 30 A. grisella chromosomes. This dense marker set, coupled with our development of an annotated, draft genome of A. grisella, allowed us to link >3,000 genome scaffolds, >10,000 predicted genes, and close to 275Mb of genome sequence to chromosomes. Our QTL mapping confirmed a fraction of the QTL identified in a previous study, and additionally revealed novel loci. Collectively, QTL explained only small fractions of the phenotypic variance, suggesting many more causative factors remain below the detection threshold of our study. A surprising, and ultimately challenging feature of our study was the low level of intrachromosomal recombination present in our mapping population. This led to difficulty ordering markers along linkage groups, necessitating a chromosome-by-chromosome mapping approach, rather than true interval mapping, and precluded confident ordering/orienting of scaffolds along each chromosome. Nonetheless, our study increased the genomic resources available for the A. grisella system. Enabled by ever more powerful technologies, future investigators will be able to leverage our data to provide more detailed genetic dissection of male song variation in A. grisella.

The Genome of Drosophila innubila Reveals Lineage-Specific Patterns of Selection in Immune Genes.

Pathogenic microbes can exert extraordinary evolutionary pressure on their hosts. They can spread rapidly and sicken or even kill their host to promote their own proliferation. Because of this strong selective pressure, immune genes are some of the fastest evolving genes across metazoans, as highlighted in mammals and insects. Drosophila melanogaster serves as a powerful model for studying host/pathogen evolution. While Drosophila melanogaster are frequently exposed to various pathogens, little is known about D. melanogaster's ecology, or if they are representative of other Drosophila species in terms of pathogen pressure. Here, we characterize the genome of Drosophila innubila, a mushroom-feeding species highly diverged from D. melanogaster and investigate the evolution of the immune system. We find substantial differences in the rates of evolution of immune pathways between D. innubila and D. melanogaster. Contrasting what was previously found for D. melanogaster, we find little evidence of rapid evolution of the antiviral RNAi genes and high rates of evolution in the Toll pathway. This suggests that, while immune genes tend to be rapidly evolving in most species, the specific genes that are fastest evolving may depend either on the pathogens faced by the host and/or divergence in the basic architecture of the host's immune system.

The genetic breakdown of sporophytic self-incompatibility in Tolpis coronopifolia (Asteraceae).

Angiosperm diversity has been shaped by mating system evolution, with the most common transition from outcrossing to self-fertilizing. To investigate the genetic basis of this transition, we performed crosses between two species endemic to the Canary Islands, the self-compatible (SC) species Tolpis coronopifolia and its self-incompatible (SI) relative Tolpis santosii. We scored self-compatibility as self-seed set of recombinant plants within two F2 populations. To map and genetically characterize the breakdown of SI, we built a draft genome sequence of T. coronopifolia, genotyped F2 plants using multiplexed shotgun genotyping (MSG), and located MSG markers to the genome sequence. We identified a single quantitative trait locus (QTL) that explains nearly all variation in self-seed set in both F2 populations. To identify putative causal genetic variants within the QTL, we performed transcriptome sequencing on mature floral tissue from both SI and SC species, constructed a transcriptome for each species, and then located each predicted transcript to the T. coronopifolia genome sequence. We annotated each predicted gene within the QTL and found two strong candidates for SI breakdown. Each gene has a coding sequence insertion/deletion mutation within the SC species that produces a truncated protein. Homologs of each gene have been implicated in pollen development, pollen germination, and pollen tube growth in other species.

A high-resolution genetic map of yellow monkeyflower identifies chemical defense QTLs and recombination rate variation.

Genotyping-by-sequencing methods have vastly improved the resolution and accuracy of genetic linkage maps by increasing both the number of marker loci as well as the number of individuals genotyped at these loci. Using restriction-associated DNA sequencing, we construct a dense linkage map for a panel of recombinant inbred lines derived from a cross between divergent ecotypes of Mimulus guttatus. We used this map to estimate recombination rate across the genome and to identify quantitative trait loci for the production of several secondary compounds (PPGs) of the phenylpropanoid pathway implicated in defense against herbivores. Levels of different PPGs are correlated across recombinant inbred lines suggesting joint regulation of the phenylpropanoid pathway. However, the three quantitative trait loci identified in this study each act on a distinct PPG. Finally, we map three putative genomic inversions differentiating the two parental populations, including a previously characterized inversion that contributes to life-history differences between the annual/perennial ecotypes.

The genomic signal of partial sweeps in Mimulus guttatus.

The molecular signature of selection depends strongly on whether new mutations are immediately favorable and sweep to fixation (hard sweeps) as opposed to when selection acts on segregating variation (soft sweeps). The prediction of reduced sequence variation around selected polymorphisms is much stronger for hard than soft sweeps, particularly when considering quantitative traits where sweeps are likely to be incomplete. Here, we directly investigate the genomic signal of soft sweeps within an artificial selection experiment on Mimulus guttatus. We first develop a statistical method based on Fisher's angular transformation of allele frequencies to identify selected loci. Application of this method identifies about 400 significant windows, but no fixed differences between phenotypically divergent populations. With two notable exceptions, we find a modest average effect of partial sweeps on the amount of molecular variation. The first exception is a polymorphic inversion on chromosome 6. The increase of the derived haplotype has a broad genomic effect due to recombination suppression coupled with substantial initial haplotype structure within the population. Second, we found significant increases in nucleotide variation around selected loci in the population evolving larger flowers. This suggests that "high" alleles for flower size were initially less frequent than "low" alleles. This result is consistent with prior studies of M. guttatus and illustrates how molecular evolution can depend on the allele frequency spectrum at quantitative trait loci.