Structural variants involved in high-altitude adaptation detected using single-molecule long-read sequencing

Establishing altitude-based coagulation reference ranges in Western Sichuan

The diagnosis and treatment of diseases in plateau regions should incorporate altitude, sex, and age in addition to hematological indicators from plain regions. This study analyzed coagulation results among individuals living at different altitudes in the Western Sichuan Plateaus and belonging to different sex and age groups to examine patterns of change and determine normal ranges. By comparing the changes in coagulation indicators among healthy male and female residents of different age groups (< 40 years, 40-59 years, ≥ 60 years) from Guza (1,400 m), Kangding (2,500 m), Luhuo (3,400 m), and Litang (4,100 m), we analyzed the association between coagulation indicators and altitude, age, and sex. Under low temperature, hypoxia, and other plateau environment factors, coagulation indicators varied among different altitudes, with some indicators showing specific trends of change with increasing altitude. Different sexes and age groups also exhibited specific patterns of change in coagulation results. This study clarified the patterns of change in coagulation results at four different altitudes in the Western Sichuan Plateau and the effects of sex and age on coagulation function. Normal ranges of coagulation values were determined for different sexes and age groups at different altitudes, providing a scientific basis for healthcare in this region.

Life destiny of erythrocyte in high altitude erythrocytosis: mechanisms underlying the progression from physiological (moderate) to pathological (excessive) high-altitude erythrocytosis

High-altitude polycythemia (HAPC) represents a pathological escalation of the physiological erythrocytosis induced by chronic hypoxia exposure. While moderate erythroid expansion enhances oxygen delivery, HAPC manifests as hematologic disorder characterized by hemoglobin thresholds (≥21 g/dL males; ≥19 g/dL females) and multi-organ complications including microcirculatory thrombosis, right ventricular hypertrophy, and uric acid dysmetabolism. This review critically evaluates the continuum between adaptive and maladaptive polycythemia through multiscale analysis of erythrocyte biology. We integrate genomic predisposition patterns, bone marrow erythroid kinetic studies, and peripheral erythrocyte pathophenotypes revealed by multi-omics profiling (iron-redox proteome, hypoxia-metabolome crosstalk). Current diagnostic limitations are highlighted, particularly the oversimplification of hemoglobin cutoffs that neglect transitional dynamics in erythrocyte turnover. By reconstructing the erythroid life cycle-from hypoxia-sensitive progenitor commitment to senescent cell clearance-we propose a phase transition model where cumulative epigenetic-metabolic derangements overcome homeostatic buffers, triggering pathological erythroid amplification. These insights reframe HAPC as a systems biology failure of erythroid adaptation, informing predictive biomarkers and targeted interventions to preserve hematological homeostasis in hypoxic environments.

A Segregating Structural Variant Defines Novel Venom Phenotypes in the Eastern Diamondback Rattlesnake

Of all mutational mechanisms contributing to phenotypic variation, structural variants are both among the most capable of causing major effects as well as the most technically challenging to identify. Intraspecific variation in snake venoms is widely reported, and one of the most dramatic patterns described is the parallel evolution of streamlined neurotoxic rattlesnake venoms from hemorrhagic ancestors by means of deletion of snake venom metalloproteinase (SVMP) toxins and recruitment of neurotoxic dimeric phospholipase A2 (PLA2) toxins. While generating a haplotype-resolved, chromosome-level genome assembly for the eastern diamondback rattlesnake (Crotalus adamanteus), we discovered that our genome animal was heterozygous for a ∼225 Kb deletion containing six SVMP genes, paralleling one of the two steps involved in the origin of neurotoxic rattlesnake venoms. Range-wide population-genomic analysis revealed that, although this deletion is rare overall, it is the dominant homozygous genotype near the northwestern periphery of the species' range, where this species is vulnerable to extirpation. Although major SVMP deletions have been described in at least five other rattlesnake species, C. adamanteus is unique in not additionally gaining neurotoxic PLA2s. Previous work established a superficially complementary north-south gradient in myotoxin (MYO) expression based on copy number variation with high expression in the north and low in the south, yet we found that the SVMP and MYO genotypes vary independently, giving rise to an array of diverse, novel venom phenotypes across the range. Structural variation, therefore, forms the basis for the major axes of geographic venom variation for C. adamanteus.

SVLearn: a dual-reference machine learning approach enables accurate cross-species genotyping of structural variants

Structural variations (SVs) are diverse forms of genetic alterations and drive a wide range of human diseases. Accurately genotyping SVs, particularly occurring at repetitive genomic regions, from short-read sequencing data remains challenging. Here, we introduce SVLearn, a machine-learning approach for genotyping bi-allelic SVs. It exploits a dual-reference strategy to engineer a curated set of genomic, alignment, and genotyping features based on a reference genome in concert with an allele-based alternative genome. Using 38,613 human-derived SVs, we show that SVLearn significantly outperforms four state-of-the-art tools, with precision improvements of up to 15.61% for insertions and 13.75% for deletions in repetitive regions. On two additional sets of 121,435 cattle SVs and 113,042 sheep SVs, SVLearn demonstrates a strong generalizability to cross-species genotype SVs with a weighted genotype concordance score of up to 90%. Notably, SVLearn enables accurate genotyping of SVs at low sequencing coverage, which is comparable to the accuracy at 30× coverage. Our studies suggest that SVLearn can accelerate the understanding of associations between the genome-scale, high-quality genotyped SVs and diseases across multiple species.

Calling Structural Variants with Confidence from Short-Read Data in Wild Bird Populations

Comprehensive characterization of structural variation in natural populations has only become feasible in the last decade. To investigate the population genomic nature of structural variation, reproducible and high-confidence structural variation callsets are first required. We created a population-scale reference of the genome-wide landscape of structural variation across 33 Nordic house sparrows (Passer domesticus). To produce a consensus callset across all samples using short-read data, we compare heuristic-based quality filtering and visual curation (Samplot/PlotCritic and Samplot-ML) approaches. We demonstrate that curation of structural variants is important for reducing putative false positives and that the time invested in this step outweighs the potential costs of analyzing short-read-discovered structural variation data sets that include many potential false positives. We find that even a lenient manual curation strategy (e.g. applied by a single curator) can reduce the proportion of putative false positives by up to 80%, thus enriching the proportion of high-confidence variants. Crucially, in applying a lenient manual curation strategy with a single curator, nearly all (>99%) variants rejected as putative false positives were also classified as such by a more stringent curation strategy using three additional curators. Furthermore, variants rejected by manual curation failed to reflect the expected population structure from SNPs, whereas variants passing curation did. Combining heuristic-based quality filtering with rapid manual curation of structural variants in short-read data can therefore become a time- and cost-effective first step for functional and population genomic studies requiring high-confidence structural variation callsets.

Genomic structural variation is associated with hypoxia adaptation in high-altitude zokors

Zokors, an Asiatic group of subterranean rodents, originated in lowlands and colonized high-elevational zones following the uplift of the Qinghai-Tibet plateau about 3.6 million years ago. Zokors live at high elevation in subterranean burrows and experience hypobaric hypoxia, including both hypoxia (low oxygen concentration) and hypercapnia (elevated partial pressure of CO2). Here we report a genomic analysis of six zokor species (genus Eospalax) with different elevational ranges to identify structural variants (deletions and inversions) that may have contributed to high-elevation adaptation. Based on an assembly of a chromosome-level genome of the high-elevation species, Eospalax baileyi, we identified 18 large inversions that distinguished this species from congeners native to lower elevations. Small-scale structural variants in the introns of EGLN1, HIF1A, HSF1 and SFTPD of E. baileyi were associated with the upregulated expression of those genes. A rearrangement on chromosome 1 was associated with altered chromatin accessibility, leading to modified gene expression profiles of key genes involved in the physiological response to hypoxia. Multigene families that underwent copy-number expansions in E. baileyi were enriched for autophagy, HIF1 signalling and immune response. E. baileyi show a significantly larger lung mass than those of other Eospalax species. These findings highlight the key role of structural variants underlying hypoxia adaptation of high-elevation species in Eospalax.