Exploring the potential of incremental feature selection to improve genomic prediction accuracy.

BACKGROUND: The ever-increasing availability of high-density genomic markers in the form of single nucleotide polymorphisms (SNPs) enables genomic prediction, i.e. the inference of phenotypes based solely on genomic data, in the field of animal and plant breeding, where it has become an important tool. However, given the limited number of individuals, the abundance of variables (SNPs) can reduce the accuracy of prediction models due to overfitting or irrelevant SNPs. Feature selection can help to reduce the number of irrelevant SNPs and increase the model performance. In this study, we investigated an incremental feature selection approach based on ranking the SNPs according to the results of a genome-wide association study that we combined with random forest as a prediction model, and we applied it on several animal and plant datasets. RESULTS: Applying our approach to different datasets yielded a wide range of outcomes, i.e. from a substantial increase in prediction accuracy in a few cases to minor improvements when only a fraction of the available SNPs were used. Compared with models using all available SNPs, our approach was able to achieve comparable performances with a considerably reduced number of SNPs in several cases. Our approach showcased state-of-the-art efficiency and performance while having a faster computation time. CONCLUSIONS: The results of our study suggest that our incremental feature selection approach has the potential to improve prediction accuracy substantially. However, this gain seems to depend on the genomic data used. Even for datasets where the number of markers is smaller than the number of individuals, feature selection may still increase the performance of the genomic prediction. Our approach is implemented in R and is available at https://github.com/FelixHeinrich/GP_with_IFS/ .

Detecting Animal Contacts-A Deep Learning-Based Pig Detection and Tracking Approach for the Quantification of Social Contacts.

The identification of social interactions is of fundamental importance for animal behavioral studies, addressing numerous problems like investigating the influence of social hierarchical structures or the drivers of agonistic behavioral disorders. However, the majority of previous studies often rely on manual determination of the number and types of social encounters by direct observation which requires a large amount of personnel and economical efforts. To overcome this limitation and increase research efficiency and, thus, contribute to animal welfare in the long term, we propose in this study a framework for the automated identification of social contacts. In this framework, we apply a convolutional neural network (CNN) to detect the location and orientation of pigs within a video and track their movement trajectories over a period of time using a Kalman filter (KF) algorithm. Based on the tracking information, we automatically identify social contacts in the form of head-head and head-tail contacts. Moreover, by using the individual animal IDs, we construct a network of social contacts as the final output. We evaluated the performance of our framework based on two distinct test sets for pig detection and tracking. Consequently, we achieved a Sensitivity, Precision, and F1-score of 94.2%, 95.4%, and 95.1%, respectively, and a MOTA score of 94.4%. The findings of this study demonstrate the effectiveness of our keypoint-based tracking-by-detection strategy and can be applied to enhance animal monitoring systems.

Economic evaluation of Motor Neuron Diseases: a nationwide cross-sectional analysis in Germany.

BACKGROUND AND OBJECTIVES: Motor Neuron Diseases (MND) are rare diseases but have a high impact on affected individuals and society. This study aims to perform an economic evaluation of MND in Germany. METHODS: Primary patient-reported data were collected including individual impairment, the use of medical and non-medical resources, and self-rated Health-Related Quality of Life (HRQoL). Annual socio-economic costs per year as well as Quality-Adjusted Life Years (QALYs) were calculated. RESULTS: 404 patients with a diagnosis of Amyotrophic Lateral Sclerosis (ALS), Spinal Muscular Atrophy (SMA) or Hereditary Spastic Paraplegia (HSP) were enrolled. Total annual costs per patient were estimated at 83,060€ in ALS, 206,856€ in SMA and 27,074€ in HSP. The main cost drivers were informal care (all MND) and disease-modifying treatments (SMA). Self-reported HRQoL was best in patients with HSP (mean EuroQoL Five Dimension Five Level (EQ-5D-5L) index value 0.67) and lowest in SMA patients (mean EQ-5D-5L index value 0.39). QALYs for patients with ALS were estimated to be 1.89 QALYs, 23.08 for patients with HSP and 14.97 for patients with SMA, respectively. Cost-utilities were estimated as follows: 138,960€/QALY for ALS, 525,033€/QALY for SMA, and 49,573€/QALY for HSP. The main predictors of the high cost of illness and low HRQoL were disease progression and loss of individual autonomy. CONCLUSION: As loss of individual autonomy was the main cost predictor, therapeutic and supportive measures to maintain this autonomy may contribute to reducing high personal burden and also long-term costs, e.g., care dependency and absenteeism from work.

agReg-SNPdb-Plants: A Database of Regulatory SNPs for Agricultural Plant Species.

Single nucleotide polymorphisms (SNPs) that are located in the promoter regions of genes and affect the binding of transcription factors (TFs) are called regulatory SNPs (rSNPs). Their identification can be highly valuable for the interpretation of genome-wide association studies (GWAS), since rSNPs can reveal the biologically causative variant and decipher the regulatory mechanisms behind a phenotype. In our previous work, we presented agReg-SNPdb, a database of regulatory SNPs for agriculturally important animal species. To complement this previous work, in this study we present the extension agReg-SNPdb-Plants storing rSNPs and their predicted effects on TF-binding for 13 agriculturally important plant species and subspecies (Brassica napus, Helianthus annuus, Hordeum vulgare, Oryza glaberrima, Oryza glumipatula, Oryza sativa Indica, Oryza sativa Japonica, Solanum lycopersicum, Sorghum bicolor, Triticum aestivum, Triticum turgidum, Vitis vinifera, and Zea mays). agReg-SNPdb-Plants can be queried via a web interface that allows users to search for SNP IDs, chromosomal regions, or genes. For a comprehensive interpretation of GWAS results or larger SNP-sets, it is possible to download the whole list of SNPs and their impact on transcription factor binding sites (TFBSs) from the website chromosome-wise.

MIDESP: Mutual Information-Based Detection of Epistatic SNP Pairs for Qualitative and Quantitative Phenotypes.

The interactions between SNPs result in a complex interplay with the phenotype, known as epistasis. The knowledge of epistasis is a crucial part of understanding genetic causes of complex traits. However, due to the enormous number of SNP pairs and their complex relationship to the phenotype, identification still remains a challenging problem. Many approaches for the detection of epistasis have been developed using mutual information (MI) as an association measure. However, these methods have mainly been restricted to case-control phenotypes and are therefore of limited applicability for quantitative traits. To overcome this limitation of MI-based methods, here, we present an MI-based novel algorithm, MIDESP, to detect epistasis between SNPs for qualitative as well as quantitative phenotypes. Moreover, by incorporating a dataset-dependent correction technique, we deal with the effect of background associations in a genotypic dataset to separate correct epistatic interaction signals from those of false positive interactions resulting from the effect of single SNP×phenotype associations. To demonstrate the effectiveness of MIDESP, we apply it on two real datasets with qualitative and quantitative phenotypes, respectively. Our results suggest that by eliminating the background associations, MIDESP can identify important genes, which play essential roles for bovine tuberculosis or the egg weight of chickens.

agReg-SNPdb: A Database of Regulatory SNPs for Agricultural Animal Species.

Transcription factors (TFs) govern transcriptional gene regulation by specifically binding to short DNA motifs, known as transcription factor binding sites (TFBSs), in regulatory regions, such as promoters. Today, it is well known that single nucleotide polymorphisms (SNPs) in TFBSs can dramatically affect the level of gene expression, since they can cause a change in the binding affinity of TFs. Such SNPs, referred to as regulatory SNPs (rSNPs), have gained attention in the life sciences due to their causality for specific traits or diseases. In this study, we present agReg-SNPdb, a database comprising rSNP data of seven agricultural and domestic animal species: cattle, pig, chicken, sheep, horse, goat, and dog. To identify the rSNPs, we constructed a bioinformatics pipeline and identified a total of 10,623,512 rSNPs, which are located within TFBSs and affect the binding affinity of putative TFs. Altogether, we implemented the first systematic analysis of SNPs in promoter regions and their impact on the binding affinity of TFs for livestock and made it usable via a web interface.

A Nation-Wide, Multi-Center Study on the Quality of Life of ALS Patients in Germany.

Improving quality of life (QoL) is central to amyotrophic lateral sclerosis (ALS) treatment. This Germany-wide, multicenter cross-sectional study analyses the impact of different symptom-specific treatments and ALS variants on QoL. Health-related QoL (HRQoL) in 325 ALS patients was assessed using the Amyotrophic Lateral Sclerosis Assessment Questionnaire 5 (ALSAQ-5) and EuroQol Five Dimension Five Level Scale (EQ-5D-5L), together with disease severity (captured by the revised ALS Functional Rating Scale (ALSFRS-R)) and the current care and therapies used by our cohort. At inclusion, the mean ALSAQ-5 total score was 56.93 (max. 100, best = 0) with a better QoL associated with a less severe disease status (ß = -1.96 per increase of one point in the ALSFRS-R score, p < 0.001). "Limb-onset" ALS (lALS) was associated with a better QoL than "bulbar-onset" ALS (bALS) (mean ALSAQ-5 total score 55.46 versus 60.99, p = 0.040). Moreover, with the ALSFRS-R as a covariate, using a mobility aid (ß = -7.60, p = 0.001), being tracheostomized (ß = -14.80, p = 0.004) and using non-invasive ventilation (ß = -5.71, p = 0.030) were associated with an improved QoL, compared to those at the same disease stage who did not use these aids. In contrast, antidepressant intake (ß = 5.95, p = 0.007), and increasing age (ß = 0.18, p = 0.023) were predictors of worse QoL. Our results showed that the ALSAQ-5 was better-suited for ALS patients than the EQ-5D-5L. Further, the early and symptom-specific clinical management and supply of assistive devices can significantly improve the individual HRQoL of ALS patients. Appropriate QoL questionnaires are needed to monitor the impact of treatment to provide the best possible and individualized care.

Identifying Cattle Breed-Specific Partner Choice of Transcription Factors during the African Trypanosomiasis Disease Progression Using Bioinformatics Analysis.

African Animal Trypanosomiasis (AAT) is a disease caused by pathogenic trypanosomes which affects millions of livestock every year causing huge economic losses in agricultural production especially in sub-Saharan Africa. The disease is spread by the tsetse fly which carries the parasite in its saliva. During the disease progression, the cattle are prominently subjected to anaemia, weight loss, intermittent fever, chills, neuronal degeneration, congestive heart failure, and finally death. According to their different genetic programs governing the level of tolerance to AAT, cattle breeds are classified as either resistant or susceptible. In this study, we focus on the cattle breeds N'Dama and Boran which are known to be resistant and susceptible to trypanosomiasis, respectively. Despite the rich literature on both breeds, the gene regulatory mechanisms of the underlying biological processes for their resistance and susceptibility have not been extensively studied. To address the limited knowledge about the tissue-specific transcription factor (TF) cooperations associated with trypanosomiasis, we investigated gene expression data from these cattle breeds computationally. Consequently, we identified significant cooperative TF pairs (especially D B P - P P A R A and D B P - T H A P 1 in N'Dama and D B P - P A X 8 in Boran liver tissue) which could help understand the underlying AAT tolerance/susceptibility mechanism in both cattle breeds.

Identification of Regulatory SNPs Associated with Vicine and Convicine Content of Vicia faba Based on Genotyping by Sequencing Data Using Deep Learning.

Faba bean (Vicia faba) is a grain legume, which is globally grown for both human consumption as well as feed for livestock. Despite its agro-ecological importance the usage of Vicia faba is severely hampered by its anti-nutritive seed-compounds vicine and convicine (V+C). The genes responsible for a low V+C content have not yet been identified. In this study, we aim to computationally identify regulatory SNPs (rSNPs), i.e., SNPs in promoter regions of genes that are deemed to govern the V+C content of Vicia faba. For this purpose we first trained a deep learning model with the gene annotations of seven related species of the Leguminosae family. Applying our model, we predicted putative promoters in a partial genome of Vicia faba that we assembled from genotyping-by-sequencing (GBS) data. Exploiting the synteny between Medicago truncatula and Vicia faba, we identified two rSNPs which are statistically significantly associated with V+C content. In particular, the allele substitutions regarding these rSNPs result in dramatic changes of the binding sites of the transcription factors (TFs) MYB4, MYB61, and SQUA. The knowledge about TFs and their rSNPs may enhance our understanding of the regulatory programs controlling V+C content of Vicia faba and could provide new hypotheses for future breeding programs.

Computational identification of tissue-specific transcription factor cooperation in ten cattle tissues.

Transcription factors (TFs) are a special class of DNA-binding proteins that orchestrate gene transcription by recruiting other TFs, co-activators or co-repressors. Their combinatorial interplay in higher organisms maintains homeostasis and governs cell identity by finely controlling and regulating tissue-specific gene expression. Despite the rich literature on the importance of cooperative TFs for deciphering the mechanisms of individual regulatory programs that control tissue specificity in several organisms such as human, mouse, or Drosophila melanogaster, to date, there is still need for a comprehensive study to detect specific TF cooperations in regulatory processes of cattle tissues. To address the needs of knowledge about specific combinatorial gene regulation in cattle tissues, we made use of three publicly available RNA-seq datasets and obtained tissue-specific gene (TSG) sets for ten tissues (heart, lung, liver, kidney, duodenum, muscle tissue, adipose tissue, colon, spleen and testis). By analyzing these TSG-sets, tissue-specific TF cooperations of each tissue have been identified. The results reveal that similar to the combinatorial regulatory events of model organisms, TFs change their partners depending on their biological functions in different tissues. Particularly with regard to preferential partner choice of the transcription factors STAT3 and NR2C2, this phenomenon has been highlighted with their five different specific cooperation partners in multiple tissues. The information about cooperative TFs could be promising: i) to understand the molecular mechanisms of regulating processes; and ii) to extend the existing knowledge on the importance of single TFs in cattle tissues.

Ranking of Dystonia Severity by Pairwise Video Comparison.

BACKGROUND: Reviewers of dystonia rating scales agree on the need to assess symptoms more comprehensively. During the development of a quantitative dystonia assessment by video-perceptive computing, we devised a video-based severity ranking as a procedure to create a validation standard without the use of clinical scales. METHODS: Thirty-four patients with dystonia (17 with dystonic tremor) and 2 controls were assessed with clinical scales and video-recordings of 24 short movement tasks. Two to 4 raters compared multiple permutations of videos from 22 subjects, including 2 healthy controls, until a complete rank order was achieved. Inter-rater agreement was expressed as normalized Kendall tau distance. Spearman correlations of video rank order with clinical scales and self-rating were repeated for tremor/nontremor subgroups. RESULTS: Normalized Kendall tau distances were <0.3 for 15 items. The video rank order for sitting and head movements correlated with clinical scales for the whole group (rho 0.52-0.87) and in the subgroup without tremor. In the tremor subgroup such correlation was perceived in the 2 items involving sitting. Video rank order correlated with quality of life self-rating only in 1 item (arms held in front, palm down). CONCLUSIONS: The agreement of video rankings between raters is remarkable. The lack of correlation in the tremor subgroup in several items may be interpreted as tremor being considered in video comparisons but not in clinical scales. This supports video-based ranking as a more comprehensive rating of dystonia and as a possible validation instrument applicable in situations in which no reference standard is available.

Rapid and simple measurement of retinol in human dried whole blood spots.

We describe an improved method for the measurement of retinol in dried blood spots (DBS) on filter paper. Retinol in human DBS on filter paper was analyzed by normal phase HPLC after a simple extraction method. Retinol associated with its binding protein was eluted from the paper into aqueous solution facilitated by ultrasonic agitation. Retinol associated with retinol binding protein was denatured with acetonitrile, and then retinol was isolated in a single hexane extract and analyzed directly by HPLC. When analyzing DBS, the individual plasma volume of the spots was calculated by measuring the sodium content or by weighing the blood spots. The described method yielded low intra- and interassay variability (<6%), with sufficient sensitivity (detection limit, 0.1 micromol/L) and good recovery (97% spike). Compared with matching plasma samples, DBS retinol consistently decreased 18-23% during the 1st wk of storage. After 1 wk, retinol remained stable in the blood spots at 23 degrees C for >3 mo. In conclusion, the analysis of retinol in DBS by HPLC is comparable to retinol analysis in serum. The variability of the method was reduced by using sodium concentration to estimate sample volume. Collection of DBS for retinol analysis is appropriate under field conditions, where it is difficult to centrifuge or freeze blood samples.

Photoprotection of UV-irradiated human skin: an antioxidative combination of vitamins E and C, carotenoids, selenium and proanthocyanidins.

Endogenous antioxidants are decreased in skin and blood during UV exposure. Combined supplementation of beta-carotene, alpha-tocopherol and ascorbic acid in addition to topical sunscreens may help to lower the risk of sunburning. Acute UV erythema with sunburn reaction are the most important factors in conjunction with the cumulative life-long UV dose for inducing skin damage resulting in photoageing and precancerous and cancerous lesions. Therefore, a clinical, randomized, double-blind, parallel group, placebo-controlled study was conducted in healthy young female volunteers (skin type II) investigating the preventive, photoprotective effect of supplementation with Seresis, an antioxidative combination containing both lipid and water-soluble compounds: carotenoids (beta-carotene and lycopene), vitamins C and E, selenium and proanthocyanidins. In this study, the oral administration of Seresis appeared to be well tolerated. The preparation contains antioxidant compounds in quantities occurring at physiological levels and can therefore be used safely over a long period of time. Despite the fact that the assessment of the light sensitivity (minimal erythemal dose, chromametry) of the skin did not show any statistically significant differences between the Seresis and the placebo group, a clear statistical trend, however, could be demonstrated, i.e. Seresis was able to slow down the time of the development and grade of UVB-induced erythema. The primary efficacy parameter matrix metalloproteinases 1 (MMP-1) between treatment and placebo group following UV irradiation showed a significant difference (p < 0.05), which occurred due to the fact that after a 2-week UV irradiation, MMP-1 slightly increased (p < 0.03) in the placebo group and decreased (p < 0.044) in the treated group. The MMP-9 changes showed a clear tendency of decrease in the Seresis group (p < 1.393) and increase (p < 0.048) in the placebo group. These data emphasise that supplementation with Seresis decreases the UV-induced expression of MMP-1 and 9, which might be important in photoprotective processes. From our data, we thus finally draw the conclusion that by the combination of antioxidants, such as in the formulation of Seresis, a selective protection of the skin against irradiation can be achieved. This might be important for future recommendations for immediate suppression of the early phase of UV-induced erythema, that means pharmacological prevention of sunburn reaction as well as subsequent chronic skin damage.

Translational regulator RpL10p/Grc5p interacts physically and functionally with Sed1p, a dynamic component of the yeast cell surface.

Biogenesis of an active ribosome complement and a dynamic cell surface complement are two major determinants of cellular growth. In yeast, the 60S ribosomal subunit protein RpL10p/Grc5p functions during successive stages in ribosome biogenesis, specifically rRNA processing, nucle(ol)ar preribosomal subunit assembly, nucleo-cytoplasmic transport and cytoplasmic maturation of ribosomes. Here, we report that a two-hybrid screen identified yeast genes SED1, ACS2 and PLB3 as encoding proteins physically interacting with both ribosomal RpL10p/Grc5p and its human homologue hRpL10p/QMp. SED1 encodes a differentially expressed cell wall protein which is proposed to be first transiently secreted to the plasma membrane as a GPI (glycosylated derivative of phosphoinositol)-anchored form and to be then transferred to the glucan layer of the cell wall. Ectopic expression of SED1 rescues both the aberrant growth phenotype and the translation defect of grc5-1(ts) temperature-sensitive cells. Furthermore, we report that Sed1p associates with translating ribosomes suggesting a novel, cytoplasmic role for Sed1p. ACS2 encodes one of the two yeast acetyl-CoA synthases and represents a key enzyme in one of several metabolic routes to produce acetyl-CoA, which in turn is indispensable for lipid biosynthesis. PLB3 encodes a phospholipase, which is active in the breakdown of membrane lipids. Our results support the view that Grc5p/RpL10p links ribosome function to membrane turnover and cell surface biogenesis.