To understand the potential genetic basis of highland adaptation of fungal pathogenicity, we present here the ~116 Mb de novo assembled high-quality genome of Ophiocordyceps sinensis endemic to the Qinghai-Tibetan Plateau. Compared with other plain-dwelling fungi, we find about 3.4-fold inflation of the O. sinensis genome due to a rapid amplification of long terminal repeat retrotransposons that occurred ~38 million years ago in concert with the uplift of the plateau. We also observe massive removal of thousands of genes related to the transport process and energy metabolism. O. sinensis displays considerable lineage-specific expansion of gene families functionally enriched in the adaptability of low-temperature of cold tolerance, fungal pathogenicity and specialized host infection. We detect signals of positive selection for genes involved in peroxidase and hypoxia to enable its highland adaptation. Resequencing and analyzing 31 whole genomes of O. sinensis, representing nearly all of its geographic range, exhibits latitude-based population divergence and nature selection for population inhabitation towards higher altitudes on the Qinghai-Tibetan Plateau.

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BackgroundThere is little information on which pattern should be chosen to perform lymph node dissection for stage I non-small-cell lung cancer. This study aimed to develop a model for predicting lymph node metastasis using pathologic features of patients intraoperatively diagnosed as stage I non-small-cell lung cancer.MethodsWe collected pathology data from 284 patients intraoperatively diagnosed as stage I non-small-cell lung cancer who underwent lobectomy with complete lymph node dissection from 2013 through 2014, assessing various factors for an association with metastasis to lymph nodes (age, gender, pathology, tumour location, tumour differentiation, tumour size, pleural invasion, bronchus invasion, multicentric invasion and angiolymphatic invasion). After analysing these variables, we developed a multivariable logistic model to estimate risk of metastasis to lymph nodes.ResultsUnivariate logistic regression identified tumour size >2.65 cm (p < 0.001), tumour differentiation (p < 0.001), pleural invasion (p = 0.034) and bronchus invasion (p < 0.001) to be risk factors significantly associated with the presence of metastatic lymph nodes. On multivariable analysis, only tumour size >2.65 cm (p < 0.001), tumour differentiation (p = 0.006) and bronchus invasion (p = 0.017) were independent predictors for lymph node metastasis. We developed a model based on these three pathologic factors that determined that the risk of metastasis ranged from 3% to 44% for patients intraoperatively diagnosed as stage I non-small-cell lung cancer. By applying the model, we found that the values ŷ > 0.80, 0.43 < ŷ ≤ 0.80, ŷ ≤ 0.43 plus tumour size >2 cm and ŷ ≤0.43 plus tumour size ≤2 cm yielded positive lymph node metastasis predictive values of 44%, 18%, 14% and 0%, respectively.ConclusionsA non-invasive prediction model including tumour size, tumour differentiation and bronchus invasion may be useful to give thoracic surgeons recommendations on lymph node dissection for patients intraoperatively diagnosed as Stage I non-small cell lung cancer.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-017-3273-x) contains supplementary material, which is available to authorized users.

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