dataesr/scientific-paragraphs-categorization huggingface dataset:
Genetic diseases have been historically segregated into rare Mendelian disorders and common complex conditions. Large-scale studies using genome sequencing are eroding this distinction and are gradually unmasking the underlying complexity of human traits. Here, we analysed data from the Genomics England 100,000 Genomes Project and from a cohort of 1313 individuals with albinism aiming to gain insights into the genetic architecture of this archetypal rare disorder. We investigated the contribution of protein-coding and regulatory variants both rare and common. We focused on TYR, the gene encoding tyrosinase, and found that a high-frequency promoter variant, TYR c. -301C>T [rs4547091], modulates the penetrance of a prevalent, albinism-associated missense change, TYR c. 1205G>A (p. Arg402Gln) [rs1126809].
T here is abundant evidence supporting the view that rare genetic diseases are caused by rare, high-impact variants in individual genes  1, 2. However, for most known rare disorders, it is not possible to identify such pathogenic changes in every affected proband, leaving significant diagnostic and knowledge gaps  [3] [4] [5]. In recent years, the emergence of comprehensive rare disease and population-based resources that link genomic and phenotypic data (e. g. UK Biobank  6  , Genomics England 100,000 Genomes Project  7  ) has offered unprecedented opportunities for genetic discovery  [8] [9] [10] [11] [12] [13]. Through integrative analysis of these datasets, we can now achieve line-of-sight for uncovering complex molecular explanations in people with rare disorders who have hitherto remained undiagnosable.
Results and Discussion A cohort of 1208 people with albinism underwent testing of ≤19 albinism-related genes; these individuals were not known to be related and had predominantly European ancestries (Supplementary Data 1). A further 105 probands with albinism were identified in the Genomics England 100,000 Genomes Project dataset  7. A 'control' cohort of 29,497 unrelated individuals that had no recorded diagnosis or features of albinism was also identified in this resource (Fig. 1 , Supplementary Table  1 , Methods). To gain insights into the contribution of common variants to the genetic architecture of albinism, we studied the impact of protein-coding changes that have minor allele frequency [MAF] ≥ 1% and are predicted by a computational algorithm to be functionally relevant (CADD score  22 ≥ 20).
For TYR, two such variants were identified: c. 575C>A (p. Ser192Tyr) [rs1042602] and c. 1205G>A (p. Arg402Gln) [rs1126809]. Multiple associations have been recorded for these two changes including with skin/ hair pigmentation (for both variants), macular thickness (for c. 575 C>A) and iris colour (for c. 1205G>A)  23. Furthermore, each of these changes has been shown to decrease tyrosinase activity in vitro  [24] [25] [26]. Importantly, there is evidence suggesting that c. 1205G>A is acting as a 'hypomorphic' variant, causing a mild form of albinism when in compound heterozygous state with a complete loss-of-function TYR change  27. It is also noted that the MAF of this variant in European populations is around 27% and that multiple unaffected homozygous individuals have been reported (including > 2000 people in the control subset of the Genome Aggregation Database [gnomAD] v2.
Fig. 1  Outline of the case-control study design. A case-control analysis was performed to gain insights into the contribution of protein-coding and regulatory variation (at the common and rare ends of the allele-frequency spectrum) in albinism. The majority of participants in the 'case' cohort (1208/1313) were identified through the database of the University Hospital of Bordeaux Molecular Genetics Laboratory, France. All these probands had at least one key ocular feature of albinism, i. e. nystagmus or prominent foveal hypoplasia. The remaining 105/1313 cases were identified through the Genomics England 100,000 Genomes Project dataset and had a diagnosis of albinism or a phenotype deemed consistent with partial/ocular albinism. The 'control' cohort included 29,497 unrelated individuals from the Genomics England 100,000 Genomes Project dataset, none of whom had a recorded diagnosis of albinism.
Genotypes that include selected TYR haplotypes in homozygous state were studied. Haplotypes of interest were defined as those formed by combinations of TYR variants that are predicted to be functionally relevant; three variants met the pre-determined criteria set for regulatory (TYR c. -301C>T) and common protein-coding (TYR c. 575C>A and c. 1205G>A) variants. The associated haplotypic blocks were analysed further using logistic regression (see Methods). 100K_GP Genomics England 100,000 Genomes Project, eQTLs expression quantitative trait loci, MAF minor allele frequency, CADD Combined Annotation Dependent Depletion score, HGMD Human Gene Mutation Database v2021. 2. TYR variant numbering is based on the transcript with the following identifiers: NM_000372. 5 and ENST00000263321. 6. We used Firth regression analysis  32, 33  to study how TYR haplotypes affect the risk of albinism (i.
e. the probability of having a diagnosis of albinism). This increasingly recognised logistic regression approach has been designed to handle small, imbalanced datasets (which are common in studies of rare conditions) and allows for adjustment of key covariates (which is not possible in contingency table methods) (Fig. 1 , Methods). The results are shown in Fig. 2b  and in Supplementary Table  2. This analysis identified a number of pertinent points that are discussed below. We found that the penetrance of the 'hypomorphic' TYR c. 1205G>A variant  27  is modulated by the TYR c. -301C>T promoter change. When c. 1205G>A is encountered in a homozygous state and in combination with the c. -301C allele of the promoter variant (which reduces TYR expression), the risk of albinism is high (OR > 24; see [C;A;A] and [C;C;A] in Fig.
A log 10 scale with 1 as the reference point is used; it is noted that an odds ratio >1 suggests an increased risk while an odds ratio <1 suggests a decreased risk. Further information including numerical data can be found in Supplementary Table  2. c Distribution of visual acuity measurements in UK Biobank participants carrying selected TYR haplotypes in homozygous state. Vision near 0. 0 LogMAR is considered normal while vision >0. 5 LogMAR is considered moderate/severe visual impairment. The Kruskal-Wallis p value was 8 × 10 -11. Further information including numerical data can be found in Supplementary Table  4. Table  5 ). We expect that future studies analysing visual function and ocular structure in this group of homozygous individuals will provide key insights into the elusive link between RPE melanin synthesis and visual system organisation  39.
Furthermore, we anticipate that the study of cellular models specific to these homozygous cases (e. g. human induced pluripotent stem cell-derived RPE) will advance our understanding of the molecular pathology of albinism. Lastly, we quantified the risk of albinism associated with combinations of rare and common variants. For each study participant, we estimated two key contributors to an individual's risk. First, we counted the number of rare, presumed Mendelian variants in albinism-related genes; single nucleotide variants that have MAF < 1% and are labelled as disease-causing (DM) in the Human Gene Mutation Database (HGMD) v2021. 2  40 were considered. Subsequently, we counted the number of common 'risk genotypes' in TYR (i. e. c. -301C, c. 575A and/or c. 1205A). We found that the presence of >4 common TYR risk genotypes confers an increased risk of albinism even in the absence of a rare, HGMD-listed variant (OR > 3.
Cohort characteristics and genotyping University Hospital of Bordeaux albinism cohort. Individuals with albinism were identified through the database of the University Hospital of Bordeaux Molecular Genetics Laboratory, France. This is a national reference laboratory that has been performing genetic testing for albinism since 2003 and has been receiving samples from individuals predominantly based in France (or French-administered overseas territories). Information on the dermatological and ophthalmological phenotypes was available for all affected individuals and each of these cases had at least one of the key ocular features of albinism, i. e. nystagmus or absence of a foveal pit (prominent foveal hypoplasia). No pre-screening based on genotype was undertaken and only individuals who were not knowingly related were included.
Genetic testing, bioinformatic analyses, and clinical interpretation were performed as previously described  17, 27. Briefly, most participants had gene-panel testing of 19 genes associated with albinism (TYR, OCA2, TYRP1, SLC45A2, SLC24A5, C10ORF11, GPR143, HPS 1 to 10, LYST, SLC38A8) using IonTorrent platforms. High-resolution array-CGH (comparative genomic hybridisation) was also used to detect copy number variants in these 19 genes. All genetic changes of interest were confirmed with an alternative method (e. g. Sanger sequencing or quantitative PCR). Clinical interpretation of variants was performed using criteria consistent with the 2015 American College of Medical Genetics and Genomics best practice guidelines  44. Generally, variants with MAF ≥ 1% in large publicly available datasets (e.
g. gnomAD  28  ) were considered unlikely to be disease-causing. We note that the genetic findings in a subset of this cohort (70%; 845/1208) have been partly reported in a previous publication by our group  17  (see Supplementary Data 1 for further information). Due to the limited number of genes screened in this cohort, it was not possible to reliably assess genetic ancestry and to objectively assign individuals to ancestry groups. Attempting to mitigate this, we processed available data on self-identified ethnicity that were collected through questionnaires. Responses were inspected and stratification into five broad continental groups (European, African, Admixed American, East Asian, South Asian) was performed. Genomics England 100,000 Genomes Project cohort. Clinical and genomic data from the Genomics England 100,000 Genomes Project were accessed through a secure Research Environment that is available to registered users.
This dataset was collected as part of a national genome sequencing initiative  45. Enrolment was coordinated by Genomics England Limited and participants were recruited mainly at National Health Service (NHS) Hospitals in the UK  7. Clinical information was recorded in Human Phenotype Ontology (HPO)  46  terms and International Classification of Diseases (ICD) codes. Genome sequencing was performed in DNA samples from 78,195 individuals using Illumina HiSeq X systems (150 base-pair paired-end format). Reads were aligned using the iSAAC Aligner v03. 16. 02. 19 and small variants were called using Starling v2. 4. 7  47. Aggregation of single-sample gVCFs was performed using the Illumina software gVCF genotyper v2019. 02. 29; normalisation/decomposition was implemented by vt version 0. 57721  48.
Data from the 1000 Genomes Project (phase 3) dataset  45  were used and five broad super-populations were projected (European, African, Admixed American, East Asian, South Asian) (further information on this can be found online at https://research-help. genomicsengland. co. uk/display/GERE/Ancestry +inference). We focused on a pre-determined subset of the Genomics England 100,000 Genomes Project dataset that includes only unrelated probands (n = 29,602). 105 of these individuals had a diagnosis of albinism, i. e. the ICD-10 term 'Albinism' [E70. 3] and/or the HPO terms 'Albinism' [HP:0001022], 'Partial albinism' [HP:0007443] or 'Ocular albinism' [HP:0001107] were assigned. Together with the University Hospital of Bordeaux cases, these 105 probands formed the 'case' cohort (for the albinism risk analysis).
The remaining 29,497 probands had no recorded diagnosis or phenotypic features of albinism and formed the 'control' cohort. We note that in-depth ophthalmic phenotyping was not routinely undertaken in Genomics England 100,000 Genomes Project participants. Thus, we cannot be certain that a small number of individuals with mild/subclinical forms of albinism has not been included in the control cohort. Identifying functional regulatory and protein-coding variants Regulatory variants. Focusing on TYR, we identified changes that are likely to have an impact on gene regulation by selecting variants that: • are known TYR eQTLs. • alter TYR cis-regulatory elements, including the promoter of the gene. To identify eQTLs, we inspected the eQTL catalogue  51  and used data from the Genotype-Tissue Expression v8  52  and Eye Genotype Expression 53 projects.
To identify regulatory elements, we used the ENCODE 3 (ENCyclopedia Of DNA Elements phase 3) dataset; the SCREEN (Search Candidate cis-Regulatory Elements by ENCODE) v10 interface was utilised to query this resource for regions flagged as candidate cis-regulatory elements (see https://screen. encodeproject. org/ for further information and definitions)  29. Additional putative regulatory elements were identified by inspecting chromatin accessibility peaks in RPE samples in DESCARTES (the Developmental Single-Cell Atlas of Gene Regulation and Expression)  54  and through an extensive search of the biomedical literature (e. g. 30  ). All these queries were conducted in January 2021. Common protein-coding variants. Focusing on TYR, we identified common changes that are likely to have an impact on protein function by selecting variants that: • have a CADD PHRED-scaled score ≥20.
2. • are included in the following HGMD v2021. 2 'mutation type' categories: missense/nonsense, splicing, small deletions, small insertions or small indels; gross deletions, gross insertions/duplications and complex rearrangements were not analysed. • have 'total' MAF < 1% in gnomAD v2. 1. 1  28. Case-control analysis to estimate albinism risk. The effect of homozygosity for selected TYR haplotypes (formed by one common regulatory change, c. -301C>T, and two common protein-coding variants, c. 575C>A and c. 1205G>A) on albinism risk (i. e. the probability of receiving a diagnosis of albinism) was estimated using data from the University Hospital of Bordeaux albinism cohort and the Genomics England 100,000 Genomes Project dataset. A case-control analysis of a binary trait (presence/absence of albinism) was conducted assuming a recessive model.
Notably, only 24 UK Biobank participants are assigned a diagnosis of albinism (data field 41270; ICD-10 term 'Albinism' [E70. 3]) of which only 7 had visual acuity measurements and none had OCT imaging; 19 additional individuals had a diagnosis of albinism in their primary care record data (resource 591). Given that reduced visual acuity and increased central retinal thickness (due to underdevelopment of the fovea) are two hallmark features of albinism, we decded to investigate the impact of TYR risk haplotypes on these quantitative endophenotypes. First, genotyping array data were used to obtain genotypes for TYR c. 575C>A [rs1042602] and TYR c. 1205G>A [rs1126809] (data field 22418 including information from the Applied Biosystems UK Biobank Axiom Array containing 825,927 markers). In contrast to these two changes, the TYR c.
-301C>T [rs4547091] variant was not directly captured by the array. However, high-quality (>99. 9%) imputation data on this promoter change were available (data field 22828). Subsequently, we calculated the mean of the right and left LogMAR visual acuity for each UK Biobank volunteer (data fields 5201 and 5208, 'instance 0' datasets). These visual acuity measurements were subsequently used to compare visual performance between groups of people with different homozygous haplotype combinations. As the obtained distributions deviated from normality (Fig. 2c ), the Kruskal-Wallis test was used. Pair-wise comparisons were performed and the p values were adjusted using the Benjamini-Hochberg method (Supplementary Table  4 ). To obtain central foveal thickness measurements from UK Biobank OCT images, we calculated the mean of the right and left central retinal thickness (defined as the average distance between the hyperreflective bands corresponding to the RPE and the internal limiting membrane, across the central 1 mm diameter circle of the ETDRS grid) for each UK Biobank volunteer  51.
Acknowledgements We acknowledge the following sources of funding: the  Wellcome Trust  ( 224643/Z/21/Z , Clinical  Research Career Development Fellowship  to P. I. S. ;  200990/Z/16/Z ,  Transforming Genetic Medicine Initiative  to G. C. B. ); the  UK National Institute for Health Research (NIHR) Clinical Lecturer Programme  ( CL-2017-06-001  to P. I. S. );  Retina UK and Fight for Sight  ( GR586 ,  RP Genome Project-UK Inherited Retinal Disease Consortium  to G. C. B. );  Christopher Green  (D. J. G. ); the  French Albinism Association (Genespoir)  and the  French National Research Agency (Agence Nationale de la Recherche ;  ANR-21-CE17-0041-01  to B. A. ). The  UK Biobank Eye and Vision Consortium  is supported by funding from the  NIHR Biomedical Research Centre at Moorfields Eye Hospital  and  UCL Institute of Ophthalmology , the  Alcon Foundation  and the  Desmond Foundation.
[-301C;575A;1205A] or the TYR c. [-301C;575 C;1205A] haplotype (15% in heterozygous state ['TYR heterozygous haplotype' category]; 3% in homozygous state ['TYR homozygous haplotype' category]). Further information including a list of all molecular diagnoses can be found in Supplementary Data 1. a Presence of each of the following TYR variants in one allele was considered as one common risk genotype: c. -301C [rs4547091]; c. 575C>A (p. Ser192Tyr) [rs1042602]; c. 1205G>A (p. Arg402Gln) [rs1126809]. TYR variant numbering is based on the transcript with the following identifiers: NM_000372. 5 and ENST00000263321. 6. b Autosomal albinism-related genes were inspected and each heterozygous protein-coding change with a minor allele frequency <1% and a 'disease-causing' (DM) label in the Human Gene Mutation Database (HGMD) v2021.
The article presents a proteomic dataset generated by a comparative analysis, using gel-free nanoLC-MS/MS, of the cellular proteome of Lactobacillus delbrueckii subsp. bulgaricus , a yogurt starter, when cultivated in soy milk versus in cow milk. The CIRM-BIA1592 strain was cultivated in the aqueous phase of soy milk, or of cow milk. Whole-cell proteins were extracted, trypsinolyzed and analyzed by nano LC-MS/MS, prior to identification and to classification by function using the X!Tandem pipeline software and the proteomic data from NCBI. nlm. nigh. gov. Quantification of the proteins was moreover performed to evidence changes in their expression, depending on the culture medium. Data are available via Pro-teomeXchange with the identifier PXD033905 ( http://www. proteomexchange. org/ ). This article is related to the research article entitled "The stressing life of Lactobacillus delbrueckii subsp.
Data Description This article presents a dataset generated during a comparison of the cellular proteome of the yogurt starter Lactobacillus delbrueckii subsp. bulgaricus cultivated in (1) cow milk environment and (2) soy milk environment. The list of all the cellular proteins that were identified in this study is provided in a table entitled "protein_quantification_results. csv" available via Pro-teomeXchange with the identifier PXD033905. Project Name: Data from a proteomic comparative analysis highlight differential adaptation of Lactobacillus delbrueckii subsp. bulgaricus to cow milk versus to soy milk environments. Project accession: PXD033905. The abundance ratios of the differentially expressed proteins, displaying a significantly different abundance when bacteria were cultivated in soy versus in cow milk environment, classified in different COG categories, are published in the following article:  [1].
The stressing life of Lactobacillus delbrueckii subsp. bulgaricus in soy milk. Food Microbiol 106:104042. https: //doi. org/10. 1016/j. fm. 2022. 104042. For each biological and each technical replicate, a raw data file is presented in the deposited dataset as mentioned above. This article presents data from the research article entitled "The stressing life of Lactobacillus delbrueckii subsp. bulgaricus in soy milk". The cellular proteome, according to the growth medium, reveals major induction of stress proteins, in the soy environment.
Spectra of eluted peptides were recorded in full MS mode, selected between 250-20 0 0 m/z, with a resolution of 70,0 0 0 at m/z 200. Identification of proteins was as previously described  [7]  , peptides being identified using the X!Tandem pipeline software (Langella et al. , 2017), querying the proteome of L. delbrueckii subsp. bulgaricus (proteome UP0 0 0 0 01259 downloaded from uniprot. org). Protein quantification was as described  [7]  , each peptide being quantified using the Mass-ChroQ software prior to data treatment and statistical analysis under the R software (R 3. 2. 2, Project for statistical computing) using the specific R package called 'MassChroqR'. Variance analysis was performed on proteins with a minimum peak ratio of 1. 5 for peak counting analysis. We considered significantly different proteins with an adjusted p -value < 0.
05. Proteins with a significant ( p < 0. 05, ANOVA) change in expression of ≥ 2-fold (log2 ratio ≥ 1. 5) were considered differentially expressed. We generated a volcano plot to illustrate differentially expressed proteins in L. delbrueckii subsp. bulgaricus. Functional annotation and Clusters of Orthologous Groups (COGs) were done with eggNOG-mapper v2 web tool (Huerta-Cepas et al. , 2017, 2019). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE  [8]  partner repository with the dataset identifier PXD033905.
Acknowledgments N. Illikoud  and  F. Rosa do Carmo  are recipients of post-doctoral fellowships from the  French FUI  ( Fond Unique Interministériel) program ,  N °25 , ProBioVeg. This study is part of the  PhD  project of  F. Canon  funded by the  French National Research Institute for Agriculture, Food and Environment (INRAE)  and the Brittany region. The authors offer their thanks to  Victoria Chuat , from  CIRM-BIA , for storing, checking and maintaining the bacterial strains.
Data identification and screening The AGrum database (IDDN. FR. 001. 510032. 000. R. C. 2011. 000. 1 0300) aggregates publications from 1970 to 2019 based on in vivo trials studying FA intake, dairy performance and milk FA profiles of cows in response to dietary strategies such as lipid supplementation (saturated or unsaturated FA as seed, oil, fat or free FA), forage type, and forage-to-concentrate ratio. Statistical unit of the AGrum database is the published mean of an experimental treatment within a trial. To study the relationships between input flows of LA and ALA (i. e. , ingested, duodenal, or absorbed flows of LA and ALA), BW and milk LA and ALA secretion flows, all flows were expressed in a common unit (g/d). We screened the AGrum database (Fig. 1 ) to select papers enabling the calculation of both LA or ALA intake and LA or ALA secretion into milk and reporting BW.
Data eligibility and inclusion In order to study accurate flows of EFA, treatments providing an estimate of DM intake (DMI) with no direct measurement (trials at pasture) were removed from the database. Treatments including post-ruminal infusions of lipids or FA were excluded, as the infused FA escaped ruminal biohydrogenation (RBH). We also removed any treatments that included factors known to decrease RBH of unsaturated FA, such as additives protecting FA against microbial activity (Fig. 1 ). Diets using tannins were therefore removed, as tannins have been shown to alter the bacteria of the rumen microbiota and globally the RBH of FA  (Vasta et al. , 2019). Treatments containing ionophore antibiotics, such as monensin, were also excluded as they have been associated with a limitation of the complete RBH of unsaturated FA  (AlZahal et al.