bluuebunny/crossref_metadata_2025_split huggingface dataset:
MiR-206 may suppress non-small lung cancer metastasis by targeting CORO1C
Authors: Liao Ming , Peng Lijun 
Published: March 2020

Abstract
Object
Non-small lung cancer (NSCLC), with a poor 5-year survival rate (16%), is the major type of lung cancer. Metastasis has been identified as the main factor that leads to NSCLC therapy failure. MiR-206 is a metastasis suppressor in many cancers, including colorectal cancer, renal cell carcinoma and breast cancer. However, the role of miR-206 in NSCLC metastasis and the underlying mechanism are still obscure.

Methods
Quantitative reverse-transcription PCR (q-RT-PCR) assay was used to detect miR-206 mRNA of NSCLC tissues and lung cancer lines. The MTT assay, scratch wound healing assay, transwell migration assay and transwell invasion assay were conducted to illuminate the effect of miR-206 on A549 cells’ proliferation, migration and invasion. Gaussia luciferase reporter assay, q-RT-PCR and western blotting assay were used to explore the underlying mechanism. Also, the A549 xenograft model was conducted to evaluate the anti-tumor effect of miR-206 in vivo.

Results
The results showed that miR-206 expression was decreased in NSCLC tissues and lung cancer cells. Further research demonstrated that miR-206 inhibited the proliferation, migration and invasion of A549 cells via negatively regulating Coronin-1C (CORO1C), and CORO1C deletion significantly rescues the miR-206 mediated inhibitory effect on A549 cells. Moreover, miR-206 exhibited a perfect anti-tumor effect in the A549 xenograft model.

Conclusion
Our study reveals that miR-206 functions as a tumor metastasis suppressor and sheds new light on the clinical significance of miR-206 in NSCLC therapy.
Identification of the ABCC4, IER3, and CBFA2T2 candidate genes for resistance to paratuberculosis from sequence-based GWAS in Holstein and Normande dairy cattle
Authors: Sanchez Marie-Pierre , Guatteo Raphaël , Davergne Aurore , Saout Judikael , Grohs Cécile , Deloche Marie-Christine , Taussat Sébastien , Fritz Sébastien , Boussaha Mekki , Blanquefort Philippe , Delafosse Arnaud , Joly Alain , Schibler Laurent , Fourichon Christine , Boichard Didier 
Published: March 2020

Abstract
Background
Bovine paratuberculosis is a contagious disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP), with adverse effects on animal welfare and serious economic consequences. Published results on host genetic resistance to MAP are inconsistent, mainly because of difficulties in characterizing the infection status of cows. The objectives of this study were to identify quantitative trait loci (QTL) for resistance to MAP in Holstein and Normande cows with an accurately defined status for MAP.

Results
From MAP-infected herds, cows without clinical signs of disease were subjected to at least four repeated serum ELISA and fecal PCR tests over time to determine both infected and non-infected statuses. Clinical cases were confirmed using PCR. Only cows that had concordant results for all tests were included in further analyses. Positive and control cows were matched within herd according to their birth date to ensure a same level of exposure to MAP. Cows with accurate phenotypes, i.e. unaffected (control) or affected (clinical or non-clinical cases), were genotyped with the Illumina BovineSNP50 BeadChip. Genotypes were imputed to whole-genome sequences using the 1000 Bull Genomes reference population (run6). A genome-wide association study (GWAS) of MAP status of 1644 Holstein and 649 Normande cows, using either two (controls versus cases) or three classes of phenotype (controls, non-clinical and clinical cases), revealed three regions, on Bos taurus (BTA) chromosomes 12, 13, and 23, presenting significant effects in Holstein cows, while only one of those was identified in Normande cows (BTA23). The most significant effect was found on BTA13, in a short 8.5-kb region. Conditional analyses revealed that only one causal variant may be responsible for the effects observed on each chromosome with the ABCC4 (BTA12), CBFA2T2 (BTA13), and IER3 (BTA23) genes as good functional candidates.

Conclusions
A sequence-based GWAS on cows for which resistance to MAP was accurately defined, was able to identify candidate variants located in genes that were functionally related to resistance to MAP; these explained up to 28% of the genetic variance of the trait. These results are very encouraging for efforts towards implementation of a breeding strategy aimed at improving resistance to paratuberculosis in Holstein cows.
AllEnricher: a comprehensive gene set function enrichment tool for both model and non-model species
Authors: Zhang Du , Hu Qi , Liu Xinxing , Zou Kai , Sarkodie Emmanuel Konadu , Liu Xueduan , Gao Fei 
Published: March 2020

Abstract
Background
Function genomic studies will generally result in lists of genes that may provide clues for exploring biological questions and discovering unanticipated functions, based on differential gene expression analysis, differential epigenomic analysis or co-expression network analysis. While tools have been developed to identify biological functions that are enriched in the genes sets, there remains a need for comprehensive tools that identify functional enrichment of genes for both model and non-model species from a different function classification perspective.

Results
We developed AllEnricher, a tool that calculates gene set function enrichment, with user-defined updatable libraries backing up for both model and non-model species as well as providing comprehensive functional interpretation from multiple dimensions, including GO, KEGG, Reactome, DO and DisGeNET.

Conclusions
AllEnricher incorporates up to date information from different public resources and provides a comprehensive resolution for biologists to make sense out of specific gene sets, making it an advanced open-source tool for gene set function analysis.
Variant effect predictions capture some aspects of deep mutational scanning experiments
Authors: Reeb Jonas , Wirth Theresa , Rost Burkhard 
Published: March 2020

Abstract
Background
Deep mutational scanning (DMS) studies exploit the mutational landscape of sequence variation by systematically and comprehensively assaying the effect of single amino acid variants (SAVs; also referred to as missense mutations, or non-synonymous Single Nucleotide Variants – missense SNVs or nsSNVs) for particular proteins. We assembled SAV annotations from 22 different DMS experiments and normalized the effect scores to evaluate variant effect prediction methods. Three trained on traditional variant effect data (PolyPhen-2, SIFT, SNAP2), a regression method optimized on DMS data (Envision), and a naïve prediction using conservation information from homologs.

Results
On a set of 32,981 SAVs, all methods captured some aspects of the experimental effect scores, albeit not the same. Traditional methods such as SNAP2 correlated slightly more with measurements and better classified binary states (effect or neutral). Envision appeared to better estimate the precise degree of effect. Most surprising was that the simple naïve conservation approach using PSI-BLAST in many cases outperformed other methods. All methods captured beneficial effects (gain-of-function) significantly worse than deleterious (loss-of-function). For the few proteins with multiple independent experimental measurements, experiments differed substantially, but agreed more with each other than with predictions.

Conclusions
DMS provides a new powerful experimental means of understanding the dynamics of the protein sequence space. As always, promising new beginnings have to overcome challenges. While our results demonstrated that DMS will be crucial to improve variant effect prediction methods, data diversity hindered simplification and generalization.
MethylNet: an automated and modular deep learning approach for DNA methylation analysis
Authors: Levy Joshua J. , Titus Alexander J. , Petersen Curtis L. , Chen Youdinghuan , Salas Lucas A. , Christensen Brock C. 
Published: March 2020

Abstract
Background
DNA methylation (DNAm) is an epigenetic regulator of gene expression programs that can be altered by environmental exposures, aging, and in pathogenesis. Traditional analyses that associate DNAm alterations with phenotypes suffer from multiple hypothesis testing and multi-collinearity due to the high-dimensional, continuous, interacting and non-linear nature of the data. Deep learning analyses have shown much promise to study disease heterogeneity. DNAm deep learning approaches have not yet been formalized into user-friendly frameworks for execution, training, and interpreting models. Here, we describe MethylNet, a DNAm deep learning method that can construct embeddings, make predictions, generate new data, and uncover unknown heterogeneity with minimal user supervision.

Results
The results of our experiments indicate that MethylNet can study cellular differences, grasp higher order information of cancer sub-types, estimate age and capture factors associated with smoking in concordance with known differences.

Conclusion
The ability of MethylNet to capture nonlinear interactions presents an opportunity for further study of unknown disease, cellular heterogeneity and aging processes.
On rare variants in principal component analysis of population stratification
Authors: Ma Shengqing , Shi Gang 
Published: March 2020

AbstractBackgroundPopulation stratification is a known confounder of genome-wide association studies, as it can lead to false positive results. Principal component analysis (PCA) method is widely applied in the analysis of population structure with common variants. However, it is still unclear about the analysis performance when rare variants are used.ResultsWe derive a mathematical expectation of the genetic relationship matrix. Variance and covariance elements of the expected matrix depend explicitly on allele frequencies of the genetic markers used in the PCA analysis. We show that inter-population variance is solely contained inKprincipal components (PCs) and mostly in the largestK-1 PCs, whereKis the number of populations in the samples. We propose FPC, ratio of the inter-population variance to the intra-population variance in theKpopulation informative PCs, andd2, sum of squared distances among populations, as measures of population divergence. We show analytically that when allele frequencies become small, the ratio FPCabates, the population distanced2decreases, and portion of variance explained by theKPCs diminishes. The results are validated in the analysis of the 1000 Genomes Project data. The ratio FPCis 93.85, population distanced2is 444.38, and variance explained by the largest five PCs is 17.09% when using with common variants with allele frequencies between 0.4 and 0.5. However, the ratio, distance and percentage decrease to 1.83, 17.83 and 0.74%, respectively, with rare variants of frequencies between 0.0001 and 0.01.ConclusionsThe PCA of population stratification performs worse with rare variants than with common ones. It is necessary to restrict the selection to only the common variants when analyzing population stratification with sequencing data.
Genome relationships and LTR-retrotransposon diversity in three cultivated Capsicum L. (Solanaceae) species
Authors: de Assis Rafael , Baba Viviane Yumi , Cintra Leonardo Adabo , Gonçalves Leandro Simões Azeredo , Rodrigues Rosana , Vanzela André Luís Laforga 
Published: March 2020

Abstract
Background
Plant genomes are rich in repetitive sequences, and transposable elements (TEs) are the most accumulated of them. This mobile fraction can be distinguished as Class I (retrotransposons) and Class II (transposons). Retrotransposons that are transposed using an intermediate RNA and that accumulate in a “copy-and-paste” manner were screened in three genomes of peppers (Solanaceae). The present study aimed to understand the genome relationships among Capsicum annuum, C. chinense, and C. baccatum, based on a comparative analysis of the function, diversity and chromosome distribution of TE lineages in the Capsicum karyotypes. Due to the great commercial importance of pepper in natura, as a spice or as an ornamental plant, these genomes have been widely sequenced, and all of the assemblies are available in the SolGenomics group. These sequences were used to compare all repetitive fractions from a cytogenomic point of view.

Results
The qualification and quantification of LTR-retrotransposons (LTR-RT) families were contrasted with molecular cytogenetic data, and the results showed a strong genome similarity between C. annuum and C. chinense as compared to C. baccatum. The Gypsy superfamily is more abundant than Copia, especially for Tekay/Del lineage members, including a high representation in C. annuum and C. chinense. On the other hand, C. baccatum accumulates more Athila/Tat sequences. The FISH results showed retrotransposons differentially scattered along chromosomes, except for CRM lineage sequences, which mainly have a proximal accumulation associated with heterochromatin bands.

Conclusions
The results confirm a close genomic relationship between C. annuum and C. chinense in comparison to C. baccatum. Centromeric GC-rich bands may be associated with the accumulation regions of CRM elements, whereas terminal and subterminal AT- and GC-rich bands do not correspond to the accumulation of the retrotransposons in the three Capsicum species tested.
ITR-Seq, a next-generation sequencing assay, identifies genome-wide DNA editing sites in vivo following adeno-associated viral vector-mediated genome editing
Authors: Breton Camilo , Clark Peter M. , Wang Lili , Greig Jenny A. , Wilson James M. 
Published: March 2020

Abstract
Background
Identifying nuclease-induced double-stranded breaks in DNA on a genome-wide scale is critical for assessing the safety and efficacy of genome editing therapies. We previously demonstrated that after administering adeno-associated viral (AAV) vector-mediated genome-editing strategies in vivo, vector sequences integrated into the host organism’s genomic DNA at double-stranded breaks. Thus, identifying the genomic location of inserted AAV sequences would enable us to identify DSB events, mainly derived from the nuclease on- and off-target activity.

Results
Here, we developed a next-generation sequencing assay that detects insertions of specific AAV vector sequences called inverted terminal repeats (ITRs). This assay, ITR-Seq, enables us to identify off-target nuclease activity in vivo. Using ITR-Seq, we analyzed liver DNA samples of rhesus macaques treated with AAV vectors expressing a meganuclease. We found dose-dependent off-target activity and reductions in off-target events induced by further meganuclease development. In mice, we identified the genomic locations of ITR integration after treatment with Cas9 nucleases and their corresponding single-guide RNAs.

Conclusions
In sum, ITR-Seq is a powerful method for identifying off-target sequences induced by AAV vector-delivered genome-editing nucleases. ITR-Seq will help us understand the specificity and efficacy of different genome-editing nucleases in animal models and clinical studies. This information can help enhance the safety profile of gene-editing therapies.
Genetic dissection of grain water content and dehydration rate related to mechanical harvest in maize
Authors: Liu Jianju , Yu Hui , Liu Yuanliang , Deng Suining , Liu Qingcai , Liu Baoshen , Xu Mingliang 
Published: March 2020

AbstractBackgroundThe low grain water content (GWC) at harvest is a prerequisite to mechanical harvesting in maize, or otherwise would cause massive broken kernels and increase drying costs. The GWC at harvest in turn depends on GWC at the physiological maturity (PM) stage and grain dehydration rate (GDR). Both GWC and GDR are very complex traits, governed by multiple quantitative trait loci (QTL) and easily influenced by environmental conditions. So far, a number of experiments have been conducted to reveal numbers of GWC and GDR QTL, however, very few QTL have been confirmed, and no QTL has been fine-mapped or even been cloned.ResultsWe demonstrated that GWCs after PM were positively correlated with GWC at PM, whereas negatively with GDRs after PM. With a recombinant inbred line (RIL) population, we identified totally 31 QTL related to GWC and 17 QTL related to GDR in three field trials. Seven GWC QTL were consistently detected in at least two of the three field trials, each of which could explain 6.92–24.78% of the total GWC variation. Similarly, one GDR QTL was consistently detected, accounting for 9.44–14.46% of the total GDR variation. Three major GWC QTL were found to overlap with three GDR QTL in bins 1.05/06, 2.06/07, and 3.05, respectively. One of the consistent GWC QTL, namelyqGwc1.1, was fine-mapped from a 27.22 Mb to a 2.05 Mb region by using recombinant-derived progeny test. TheqGwc1.1acted in a semi-dominant manner to reduce GWC by 1.49–3.31%.ConclusionsA number of consistent GWC and GDR QTL have been identified, and one of them, QTL-qGwc1.1, was successfully refined into a 2.05 Mb region. Hence, it is realistic to clone the genes underlying the GWC and GDR QTL and to make use of them in breeding of maize varieties with low GWC at harvest.
The association between anthropometric measures of adiposity and the progression of carotid atherosclerosis
Authors: Imahori Yume , Mathiesen Ellisiv B. , Morgan Katy E. , Frost Chris , Hughes Alun D. , Hopstock Laila A. , Johnsen Stein Harald , Emaus Nina , Leon David A. 
Published: March 2020

Abstract
Background
Few reports are available on the contribution of general and abdominal obesity to the progression of carotid atherosclerosis in late adulthood. This study investigated the impact of four simple anthropometric measures of general and abdominal obesity on the progression of carotid atherosclerosis and the extent to which the association between adiposity and the progression of plaque burden is mediated by cardiometabolic markers.

Methods
Four thousand three hundred forty-five adults (median age 60) from the population-based Tromsø Study were followed over 7 years from the first carotid ultrasound screening to the next. The progression of carotid atherosclerosis was measured in three ways: incidence of plaques in previously plaque-free participants; change in the number of plaques; and total plaque area (TPA). We used generalised linear models to investigate the association between each adiposity measure – body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) – and each outcome. Models were adjusted for potential confounders (age, sex, smoking, education, physical activity). The pathways through which any associations observed might operate were investigated by further adjusting for cardiometabolic mediators (systolic blood pressure, cholesterol, and HbA1c).

Results
There was little evidence that adiposity was related to the formation of new plaques during follow-up. However, abdominal adiposity was associated with TPA progression. WHtR showed the largest effect size (mean change in TPA per one standard deviation (SD) increase in WHtR of 0.665 mm2, 95% confidence interval 0.198, 1.133) while BMI showed the smallest. Effect sizes were substantially reduced after the adjustment for potential mediators.

Conclusions
Abdominal obesity indirectly measured with WC seems more strongly associated with the progression of TPA than general obesity. These associations appear to be largely mediated by known cardiometabolic markers.
A framework for extending trial design to facilitate missing data sensitivity analyses
Authors: Mason Alexina J. , Grieve Richard D. , Richards-Belle Alvin , Mouncey Paul R. , Harrison David A. , Carpenter James R. 
Published: March 2020

AbstractBackgroundMissing data are an inevitable challenge in Randomised Controlled Trials (RCTs), particularly those with Patient Reported Outcome Measures. Methodological guidance suggests that to avoid incorrect conclusions, studies should undertake sensitivity analyses which recognise that data may be ‘missing not at random’ (MNAR). A recommended approach is to elicit expert opinion about the likely outcome differences for those with missing versus observed data. However, few published trials plan and undertake these elicitation exercises, and so lack the external information required for these sensitivity analyses. The aim of this paper is to provide a framework that anticipates and allows for MNAR data in the design and analysis of clinical trials.MethodsWe developed a framework for performing and using expert elicitation to frame sensitivity analysis in RCTs with missing outcome data. The framework includes the following steps: first defining the scope of the elicitation exercise, second developing the elicitation tool, third eliciting expert opinion about the missing outcomes, fourth evaluating the elicitation results, and fifth analysing the trial data. We provide guidance on key practical challenges that arise when adopting this approach in trials: the criteria for identifying relevant experts, the outcome scale for presenting data to experts, the appropriate representation of expert opinion, and the evaluation of the elicitation results.The framework was developed within the POPPI trial, which investigated whether a preventive, complex psychological intervention, commenced early in ICU, would reduce the development of patient-reported post-traumatic stress disorder symptom severity, and improve health-related quality of life. We illustrate the key aspects of the proposed framework using the POPPI trial.ResultsFor the POPPI trial, 113 experts were identified with potentially suitable knowledge and asked to participate in the elicitation exercise. The 113 experts provided 59 usable elicitation questionnaires. The sensitivity analysis found that the results from the primary analysis were robust to alternative MNAR mechanisms.ConclusionsFuture studies can adopt this framework to embed expert elicitation within the design of clinical trials. This will provide the information required for MNAR sensitivity analyses that examine the robustness of the trial conclusions to alternative, but realistic assumptions about the missing data.