Idiopathic Subglottic Stenosis Is Associated With More Frequent and Abnormal Squamous Metaplasia.

OBJECTIVES: Gain insights into the pathophysiology of idiopathic subglottic stenosis (iSGS) by investigating differences in transcriptome of subglottic mucosal tissue between patients with iSGS and controls, and between tracheal and subglottic tissue within patients. METHODS: RNA sequencing was conducted on biopsied mucosal samples collected from subglottic and tracheal (in-patient control) regions in iSGS patients, and from subglottis in controls. The gene expression differences were validated on a protein level by (1) staining the tissue samples obtained from a second cohort of patients and controls; and (2) in vitro functional assays using primary subglottic epithelial cells from both iSGS patients and healthy donors. RESULTS: We found 7 upregulated genes in the subglottic region of iSGS patients relative to both the tracheal mucosa and subglottic region of controls. A gene ontology enrichment analysis found that the epithelial cell differentiation and cornification pathways are significant, involving specifically 3 of the genes: involucrin (IVL), small proline rich protein 1B (SPRR1B), and keratin 16 (KRT16). Involvement of these pathways suggests squamous metaplasia of the epithelium. Histological analyses of epithelium in subglottic mucosal biopsies revealed squamous metaplasia in 41% of the samples from iSGS patients and in 25% from controls. Immunohistochemical evaluation of the samples presented with squamous epithelium revealed increased expression of the protein encoded by SPRR1B, hyperproliferative basal cells, shedding of apical layers, and accompanying lesions in iSGS compared to CTRL. Cultured primary subglottic epithelial cells from iSGS patients had higher proliferation rates compared to healthy donors and squamous metaplastic differentiation formed thinner epithelia with increased expression proteins encoded by INV, SPRR1B, and KRT16, suggesting intrinsic dysfunction of basal cells in iSGS. CONCLUSIONS: Abnormal squamous differentiation of epithelial cells may contribute to the pathogenesis of iSGS. Patients having metaplastic epithelial phenotype may be sensitive to drugs that reverse it to a normal phenotype.

Sex differences in early and term placenta are conserved in adult tissues.

BACKGROUND: Pregnancy complications vary based on the fetus's genetic sex, which may, in part, be modulated by the placenta. Furthermore, developmental differences early in life can have lifelong health outcomes. Yet, sex differences in gene expression within the placenta at different timepoints throughout pregnancy and comparisons to adult tissues remains poorly characterized. METHODS: Here, we collect and characterize sex differences in gene expression in term placentas (≥ 36.6 weeks; 23 male XY and 27 female XX). These are compared with sex differences in previously collected first trimester placenta samples and 42 non-reproductive adult tissues from GTEx. RESULTS: We identify 268 and 53 sex-differentially expressed genes in the uncomplicated late first trimester and term placentas, respectively. Of the 53 sex-differentially expressed genes observed in the term placentas, 31 are also sex-differentially expressed genes in the late first trimester placentas. Furthermore, sex differences in gene expression in term placentas are highly correlated with sex differences in the late first trimester placentas. We found that sex-differential gene expression in the term placenta is significantly correlated with sex differences in gene expression in 42 non-reproductive adult tissues (correlation coefficient ranged from 0.892 to 0.957), with the highest correlation in brain tissues. Sex differences in gene expression were largely driven by gene expression on the sex chromosomes. We further show that some gametologous genes (genes with functional copies on X and Y) will have different inferred sex differences if the X-linked gene expression in females is compared to the sum of the X-linked and Y-linked gene expression in males. CONCLUSIONS: We find that sex differences in gene expression are conserved in late first trimester and term placentas and that these sex differences are conserved in adult tissues. We demonstrate that there are sex differences associated with innate immune response in late first trimester placentas but there is no significant difference in gene expression of innate immune genes between sexes in healthy full-term placentas. Finally, sex differences are predominantly driven by expression from sex-linked genes.

Erratum: X chromosome inactivation in the human placenta is patchy and distinct from adult tissues.

[This corrects the article DOI: 10.1016/j.xhgg.2022.100121.].

X chromosome inactivation in the human placenta is patchy and distinct from adult tissues.

In humans, one of the X chromosomes in genetic females is inactivated by a process called X chromosome inactivation (XCI). Variation in XCI across the placenta may contribute to observed sex differences and variability in pregnancy outcomes. However, XCI has predominantly been studied in human adult tissues. Here, we sequenced and analyzed DNA and RNA from two locations from 30 full-term pregnancies. Implementing an allele-specific approach to examine XCI, we report evidence that XCI in the human placenta is patchy, with large patches of either maternal or paternal X chromosomes inactivated. Further, using similar measurements, we show that this is in contrast to adult tissues, which generally exhibit mosaic X inactivation, where bulk samples exhibit both maternal and paternal X chromosome expression. Further, by comparing skewed samples in placenta and adult tissues, we identify genes that are uniquely inactivated or expressed in the placenta compared with adult tissues, highlighting the need for tissue-specific maps of XCI.

Unique evolutionary trajectories of breast cancers with distinct genomic and spatial heterogeneity.

Breast cancers exhibit intratumoral heterogeneity associated with disease progression and therapeutic resistance. To define the sources and the extent of heterogeneity, we performed an in-depth analysis of the genomic architecture of three chemoradiation-naïve breast cancers with well-defined clinical features including variable ER, PR, ERBB2 receptor expression and two distinct pathogenic BRCA2mut genotypes. The latter included a germ line carrier and a patient with a somatic variant. In each case we combined DNA content-based flow cytometry with whole exome sequencing and genome wide copy number variant (CNV) analysis of distinct populations sorted from multiple (4-18) mapped biopsies within the tumors and involved lymph nodes. Interrogating flow-sorted tumor populations from each biopsy provided an objective method to distinguish fixed and variable genomic lesions in each tumor. Notably we show that tumors exploit CNVs to fix mutations and deletions in distinct populations throughout each tumor. The identification of fixed genomic lesions that are shared or unique within each tumor, has broad implications for the study of tumor heterogeneity including the presence of tumor markers and therapeutic targets, and of candidate neoepitopes in breast and other solid tumors that can advance more effective treatment and clinical management of patients with disease.

Identification and characterization of constrained non-exonic bases lacking predictive epigenomic and transcription factor binding annotations.

Annotations of evolutionary sequence constraint based on multi-species genome alignments and genome-wide maps of epigenomic marks and transcription factor binding provide important complementary information for understanding the human genome and genetic variation. Here we developed the Constrained Non-Exonic Predictor (CNEP) to quantify the evidence of each base in the genome being in an evolutionarily constrained non-exonic element from an input of over 60,000 epigenomic and transcription factor binding features. We find that the CNEP score outperforms baseline and related existing scores at predicting evolutionarily constrained non-exonic bases from such data. However, a subset of them are still not well predicted by CNEP. We developed a complementary Conservation Signature Score by CNEP (CSS-CNEP) that is predictive of those bases. We further characterize the nature of constrained non-exonic bases with low CNEP scores using additional types of information. CNEP and CSS-CNEP are resources for analyzing constrained non-exonic bases in the genome.

Unique genomic and neoepitope landscapes across tumors: a study across time, tissues, and space within a single lynch syndrome patient.

Lynch syndrome (LS) arises in patients with pathogenic germline variants in DNA mismatch repair genes. LS is the most common inherited cancer predisposition condition and confers an elevated lifetime risk of multiple cancers notably colorectal and endometrial carcinomas. A distinguishing feature of LS associated tumors is accumulation of variants targeting microsatellite repeats and the potential for high tumor specific neoepitope levels. Recurrent somatic variants targeting a small subset of genes have been identified in tumors with microsatellite instability. Notably these include frameshifts that can activate immune responses and provide vaccine targets to affect the lifetime cancer risk associated with LS. However the presence and persistence of targeted neoepitopes across multiple tumors in single LS patients has not been rigorously studied. Here we profiled the genomic landscapes of five distinct treatment naïve tumors, a papillary transitional cell renal cell carcinoma, a duodenal carcinoma, two metachronous colorectal carcinomas, and multi-regional sampling in a triple-negative breast tumor, arising in a LS patient over 10 years. Our analyses suggest each tumor evolves a unique complement of variants and that vaccines based on potential neoepitopes from one tissue may not be effective across all tumors that can arise during the lifetime of LS patients.

Neoantigen Fitness Model Predicts Lower Immune Recognition of Cutaneous Squamous Cell Carcinomas Than Actinic Keratoses.

A low percentage of actinic keratoses progress to develop into cutaneous squamous cell carcinoma. The immune mechanisms that successfully control or eliminate the majority of actinic keratoses and the mechanisms of immune escape by invasive squamous cell carcinoma are not well-understood. Here, we took a systematic approach to evaluate the neoantigens present in actinic keratosis and cutaneous squamous cell carcinoma specimens. We compared the number of mutations, the number of neoantigens predicted to bind MHC class I, and the number of neoantigens that are predicted to bind MHC class I and be recognized by a T cell receptor in actinic keratoses and cutaneous squamous cell carcinomas. We also considered the relative binding strengths to both MHC class I and the T cell receptor in a fitness cost model that allows for a comparison of the immune recognition potential of the neoantigens in actinic keratosis and cutaneous squamous cell carcinoma samples. The fitness cost was subsequently adjusted by the expression rates of the neoantigens to examine the role of neoantigen expression in tumor immune evasion. Our analyses indicate that, while the number of mutations and neoantigens are not significantly different between actinic keratoses and cutaneous squamous cell carcinomas, the predicted immune recognition of the neoantigen with the highest expression-adjusted fitness cost is lower for cutaneous squamous cell carcinomas compared with actinic keratoses. These findings suggest a role for the down-regulation of expression of highly immunogenic neoantigens in the immune escape of cutaneous squamous cell carcinomas. Furthermore, these findings highlight the importance of incorporating additional factors, such as the quality and expression of the neoantigens, rather than focusing solely on tumor mutational burden, in assessing immune recognition potential.

Identifying, understanding, and correcting technical artifacts on the sex chromosomes in next-generation sequencing data.

BACKGROUND: Mammalian X and Y chromosomes share a common evolutionary origin and retain regions of high sequence similarity. Similar sequence content can confound the mapping of short next-generation sequencing reads to a reference genome. It is therefore possible that the presence of both sex chromosomes in a reference genome can cause technical artifacts in genomic data and affect downstream analyses and applications. Understanding this problem is critical for medical genomics and population genomic inference. RESULTS: Here, we characterize how sequence homology can affect analyses on the sex chromosomes and present XYalign, a new tool that (1) facilitates the inference of sex chromosome complement from next-generation sequencing data; (2) corrects erroneous read mapping on the sex chromosomes; and (3) tabulates and visualizes important metrics for quality control such as mapping quality, sequencing depth, and allele balance. We find that sequence homology affects read mapping on the sex chromosomes and this has downstream effects on variant calling. However, we show that XYalign can correct mismapping, resulting in more accurate variant calling. We also show how metrics output by XYalign can be used to identify XX and XY individuals across diverse sequencing experiments, including low- and high-coverage whole-genome sequencing, and exome sequencing. Finally, we discuss how the flexibility of the XYalign framework can be leveraged for other uses including the identification of aneuploidy on the autosomes. XYalign is available open source under the GNU General Public License (version 3). CONCLUSIONS: Sex chromsome sequence homology causes the mismapping of short reads, which in turn affects downstream analyses. XYalign provides a reproducible framework to correct mismapping and improve variant calling on the sex chromsomes.

Complex patterns of sex-biased demography in canines.

The demographic history of dogs is complex, involving multiple bottlenecks, admixture events and artificial selection. However, existing genetic studies have not explored variance in the number of reproducing males and females, and whether it has changed across evolutionary time. While male-biased mating practices, such as male-biased migration and multiple paternity, have been observed in wolves, recent breeding practices could have led to female-biased mating patterns in breed dogs. For example, breed dogs are thought to have experienced a popular sire effect, where a small number of males father many offspring with a large number of females. Here we use genetic variation data to test how widespread sex-biased mating practices in canines are during different evolutionary time points. Using whole-genome sequence data from 33 dogs and wolves, we show that patterns of diversity on the X chromosome and autosomes are consistent with a higher number of reproducing males than females over ancient evolutionary history in both dogs and wolves, suggesting that mating practices did not change during early dog domestication. By contrast, since breed formation, we found evidence for a larger number of reproducing females than males in breed dogs, consistent with the popular sire effect. Our results confirm that canine demography has been complex, with opposing sex-biased processes occurring throughout their history. The signatures observed in genetic data are consistent with documented sex-biased mating practices in both the wild and domesticated populations, suggesting that these mating practices are pervasive.

Comparison of Single Genome and Allele Frequency Data Reveals Discordant Demographic Histories.

Inference of demographic history from genetic data is a primary goal of population genetics of model and nonmodel organisms. Whole genome-based approaches such as the pairwise/multiple sequentially Markovian coalescent methods use genomic data from one to four individuals to infer the demographic history of an entire population, while site frequency spectrum (SFS)-based methods use the distribution of allele frequencies in a sample to reconstruct the same historical events. Although both methods are extensively used in empirical studies and perform well on data simulated under simple models, there have been only limited comparisons of them in more complex and realistic settings. Here we use published demographic models based on data from three human populations (Yoruba, descendants of northwest-Europeans, and Han Chinese) as an empirical test case to study the behavior of both inference procedures. We find that several of the demographic histories inferred by the whole genome-based methods do not predict the genome-wide distribution of heterozygosity, nor do they predict the empirical SFS. However, using simulated data, we also find that the whole genome methods can reconstruct the complex demographic models inferred by SFS-based methods, suggesting that the discordant patterns of genetic variation are not attributable to a lack of statistical power, but may reflect unmodeled complexities in the underlying demography. More generally, our findings indicate that demographic inference from a small number of genomes, routine in genomic studies of nonmodel organisms, should be interpreted cautiously, as these models cannot recapitulate other summaries of the data.

Determining the Effect of Natural Selection on Linked Neutral Divergence across Species.

A major goal in evolutionary biology is to understand how natural selection has shaped patterns of genetic variation across genomes. Studies in a variety of species have shown that neutral genetic diversity (intra-species differences) has been reduced at sites linked to those under direct selection. However, the effect of linked selection on neutral sequence divergence (inter-species differences) remains ambiguous. While empirical studies have reported correlations between divergence and recombination, which is interpreted as evidence for natural selection reducing linked neutral divergence, theory argues otherwise, especially for species that have diverged long ago. Here we address these outstanding issues by examining whether natural selection can affect divergence between both closely and distantly related species. We show that neutral divergence between closely related species (e.g. human-primate) is negatively correlated with functional content and positively correlated with human recombination rate. We also find that neutral divergence between distantly related species (e.g. human-rodent) is negatively correlated with functional content and positively correlated with estimates of background selection from primates. These patterns persist after accounting for the confounding factors of hypermutable CpG sites, GC content, and biased gene conversion. Coalescent models indicate that even when the contribution of ancestral polymorphism to divergence is small, background selection in the ancestral population can still explain a large proportion of the variance in divergence across the genome, generating the observed correlations. Our findings reveal that, contrary to previous intuition, natural selection can indirectly affect linked neutral divergence between both closely and distantly related species. Though we cannot formally exclude the possibility that the direct effects of purifying selection drive some of these patterns, such a scenario would be possible only if more of the genome is under purifying selection than currently believed. Our work has implications for understanding the evolution of genomes and interpreting patterns of genetic variation.