dataesr/scientific-paragraphs-categorization huggingface dataset:
We estimated the average recombination rate of Lacaune sheep at 1. 5 cM/Mb, identified about 50,000 crossover hotspots on the genome and found a high correlation between historical and meiotic recombination rate estimates. A genome-wide association study revealed two major loci affecting inter-individual variation in recombination rate in Lacaune, including the RNF212 and HEI10 genes and possibly 2 other loci of smaller effects including the KCNJ15 and FSHR genes. Finally, we compared our results to those obtained previously in a distantly related population of domestic sheep, the Soay. This comparison revealed that Soay and Lacaune males have a very similar distribution of recombination along the genome and that the two datasets can be combined to create more precise male meiotic recombination maps in sheep.
This study was performed in a feral population of sheep which is quite distantly related to continental populations  (Kijas et al. 2012)  and has not managed by humans for a long time. To understand how recombination patterns and genetic determinism can vary across populations, we conducted in this work a study in another sheep population, the Lacaune, from south of France. The Lacaune breed is the main dairy sheep population in France, its milk being mainly used for the production of Roquefort cheese. Starting in 2011, a large genotyping effort started in the breed to implement a genomic selection program  (Baloche et al. 2014)  , and young selection candidates are now routinely genotyped for a medium density genotyping array (about 50K SNP). This constitutes a large dataset of genotyped families that can be used to study recombination, although limited to one sex as only males were used for genomic selection in this population.
This dataset offers an opportunity to study variation in recombination and its genetic determinism between very diverged populations of the same species. Hence, a first objective of this study was to elucidate whether these two sheep populations had similar distribution of recombination on the genome and whether they shared the same genetic architecture of the trait, and in particular the same QTLs effects. The second objective of this study was to compare different approaches to study recombination from independent data in the same population. To this end, in addition to the pedigree data, we exploit a sample of 51 unrelated individuals genotyped with a high-density genotyping array (about 500K SNP). While, the family data was used to establish meiotic recombination maps, the sample of densely genotyped individuals was used to create historical recombination maps of higher resolution.
Study Population and Genotype Data In this work, we exploited two different datasets of sheep from the Lacaune breed: a pedigree dataset of 8,085 related animals genotyped with the medium density Illumina Ovine Beadchip® including 54,241 SNPs, and a diversity dataset of 70 unrelated Lacaune individuals selected as to represent population genetic diversity, genotyped with the high density Illumina Ovine Infinium® HD SNP Beadchip including  (Rochus et al. 2017; Moreno-Romieux et al. 2017)  Standard data cleaning procedures were carried out on the pedigree dataset using plink 1. 9  (Chang et al. 2015)  , excluding animals with call rates below 95% and SNPs with call freq below 98%. After quality controls we exploited genotypes at 46,813 SNPs and 5,940 meioses. For these animals, we only selected the sires which had their own sire known and at least 2 offspring and the sires which did not have their own sire known, but at least 4 offspring.
Historical recombination maps from the diversity data The diversity data contains 70 Lacaune individuals genotyped for a High Density SNP array comprising 527,823 autosomal markers  (Rochus et al. 2017). Nineteen of these individuals are FIDs in the pedigree data. To perform the LD-based analysis on individuals unrelated to the pedigree study, these individuals were therefore removed from the dataset and the subsequent analyses performed on the 51 remaining individuals. Population-scaled recombination rates were estimated using PHASE (N. Li and Stephens 2003). For computational reasons and to allow for varying effective population size along the genome, estimations were carried out in 2 Mb windows, with an additional 100 Kb on each side overlapping with neighbouring windows, to avoid border-effect in the PHASE inference.
Identification of intervals harbouring crossover hotspots Intervals that showed an outlying λ j value compared to the genome-wide distribution of λ j were considered as harbouring a crossover hotspot. Specifically, a mixture of Gaussian distribution was fitted to the genome-wide distribution of using the mclust R package (Fraley and Raftery og (λ ) l 10 j 2002) , considering that the major component of the mixture modelled the background distribution of λ j in non-hotspots intervals. From this background distribution, a p-value was computed for each interval that corresponded to the null hypothesis that it does not harbour a hotspot. Finally, hotspot harbouring intervals were defined as those for which FDR(λ j ) < 5%, estimating FDR with the  (Storey and Tibshirani 2003)  method, implemented in the R qvalue package.
Using β j ν ij this approach allows to combine in a single model LD-and pedigree-based inferences, while accounting for their respective uncertainties as we exploit posterior distribution samples. Model (4) was fitted on 20 samples of the posterior distributions of c j and for all windows of one ρ j megabase covering the genome, with an additional fixed effect for each chromosome, using the lme4 R package  (Bates et al. 2015). Windows lying less than 4 Mb from each chromosome end 10 were not used because inference on c j was possibly biased in these regions (see Results). After estimating this model, historical recombination rate estimates of HD intervals were scaled within each window by dividing them by their estimated local effective population size ( i. e. for window j ). For windows lying within 4 Mb of the chromosome ends, ( α ν ν ) exp ˆj + ˆ2j -ˆ1j historical recombination rate estimates were scaled using the genome-wide average effective population size exp( ).
Comparison with Soay sheep recombination maps and integration of the two datasets to produce new male recombination maps in Sheep In order to compare the recombination maps in Lacaune with the previously established maps in Soay sheep (Susan E. Johnston et al. 2016)  , we downloaded the raw data from the dryad data repository (doi: 10. 5061/dryad. pf4b7) and the additional information available on https://github. com/susjoh/GENETICS_2015_185553. As the approach used in (Susan E. Johnston et al. 2016)  to establish recombination maps differs from the one used here, we chose to apply the method of this study to the Soay data to perform a comparison that would not be affected by difference in methods. As the Lacaune data consist only of male meioses, we also only considered male meioses in the Soay data.
The final Soay dataset used consisted of 3,445 individuals among which were 299 male FIDs, defined as in the Lacaune analysis. After detecting crossovers with LINKPHASE, one FID exhibited a very high average number of crossover per meiosis (> 100) and was not considered in the analyses (Soay individual ID : RE4844), leaving 298 FIDs. The final dataset consisted of 88,683 crossovers in 2,609 male meiosis and was used to estimated meiotic recombination maps using the exact same approach as described above, both on intervals of one megabase and on the same intervals as the ones considered in the Lacaune meiotic maps on the medium density SNP array. Note that the Soay sheep are not necessarily polymorphic for the same markers as the Lacaune, but that our method is flexible and can nonetheless estimate recombination rates in intervals bordered by monomorphic markers: in such a case adjacent intervals will have the same estimated recombination rate.
Genome-wide Recombination Rate (GRR) The set of crossovers detected was used to estimate the genome-wide recombination rate (GRR) of each FID in the family dataset from their observed number of crossovers per meiosis, adjusting for covariates: year of birth of the parent, considered as a cofactor with 14 levels for years spanning from 1997 to 2010 and insemination month of the offspring's ewe, treated as a cofactor with 7 levels for months spanning from February to August. We used a mixed-model for estimating the population average GRR μ, covariates fixed effects β and individual breeding values u s , while controlling for non genetic individual specific effects a s : y x β e so = μ + so + a s + u s + so with , a s ~N(0,Iσ a 2 ) and , where is the number of crossovers in (0, σ ) u s ~N A s 2 (0, σ ) e so ~N I e 2 y so the meiosis between FID s and offspring o , A is the pedigree-based relationship matrix between FIDs and the line of the corresponding design matrix for observation.
Genotype Imputation Nineteen of the 345 FIDs are present in the diversity dataset of HD genotypes. For the 336 remaining FIDs, their HD genotypes at 507,784 SNPs were imputed with BimBam  (Guan and Stephens 2008; Servin and Stephens 2007)  using the 70 unrelated Lacaune individuals as a panel. To impute, BimBam uses the fastPHASE model  (Scheet and Stephens 2006)  , which relies on methods using cluster of haplotypes to estimate missing genotypes and reconstruct haplotypes from unphased SNPs of unrelated animal. BimBam was run with 10 expectation-maximization (EM) starts, each EM was run 20 steps on panel data alone, and an additional 1 step on cohort data, with a number of clusters of 15. After imputation BimBam estimates for each SNP in each individual an average number of alleles, termed mean genotype , computed from the posterior distribution of the three possible genotypes.
Single-and multi-QTLs GWAS on GRR We first tested association of individual breeding values ũ s with mean genotypes at 503,784 single SNPs imputed with BimBam. We tested these associations using the univariate mixed-model approach implemented in the Genome-wide Efficient Mixed Model Association (Gemma) software 13  (Zhou and Stephens, 2012). To accounts for polygenic effects on the trait, the centered genomic relationship matrix calculated from the mean genotypes was used. The p-values reported in the results correspond to the Wald test. To go beyond single SNP association tests, we also estimated a Bayesian sparse linear mixed-model  (Zhou, Carbonetto, and Stephens 2013)  as implemented in Gemma. This method allows to consider multiple QTLs in the model, together with polygenic effects at all SNPs.
Given that the average physical distance between SNPs on the high-density SNP array is about 5 kilobases, this procedure interrogates the probability of the presence of a QTL in overlapping windows of approximately 250 kilobases. For the univariate analysis, the False Discovery Rate was estimated using the ash package  (Stephens 2017)  and SNPs corresponding to an FDR < 10% were deemed significant and annotated. For the multivariate analysis, regions where the rolling sum of PIPs exceeded 0. 15 were further annotated. The annotation of the QTL regions consisted in extracting all genes from the Ensembl annotation v87 along with their Gene Ontology (GO) annotations and interrogated for their possible involvement in recombination.
Variant discovery in RNF212 in the Lacaune population Based on the genomic sequence and structure of the RNF212 gene annotated in Ovis orientalis (NCBI accession NW_011943327), a large set of primers were designed using PRIMER3 software (Table  S1 ) for amplification of each annotated exon and some intron part corresponding to exonic region annotated in Capra hircus (Chir_v1. 0). PCR amplification (GoTaq, Promega) with each primer pair was realized on 50ng of genomic DNA from 4 selected homozygous Lacaune animals exhibiting the GG and AA (non imputed) genotypes at the most significant SNP of the medium density SNP array of the chromosome 6 QTL (rs418933055, p-value 2. 56e-17). Each PCR product was sequenced via the BigDye Terminator v3. 1 Cycle Sequencing kit and analyzed on an ABI3730 sequencing machine (Applied Biosystems).
Estimation of historical recombination rates and identification of crossover hotspots We used a different dataset, with 51 unrelated individuals from the same Lacaune population genotyped for the Illumina HD SNP array (600K) comprising 527,823 autosomal SNPs after quality controls. Using a multipoint model for LD patterns (N. Li and Stephens 2003)  , we estimated, for each marker interval of the HD SNP array, historical recombination rates ⍴ (see Methods). Compared to meiotic maps, these estimates offer a greater precision as they in essence exploit meioses cumulated over many generations. However, the historical recombination rates obtained are scaled by the effective population size ( where Ne is the effective population size N c ρ = 4 e and c the meiotic recombination rate) which is unknown, and may vary along the genome due to evolutionary pressures, especially selection.
High-resolution recombination maps combining family and population data Having constructed recombination maps with two independent approaches and having datasets in the same population of Lacaune sheep allowed first to evaluate to which extent historical crossover hotspots explain meiotic recombination, and second to estimate the impact of evolutionary pressures on the historical recombination landscape of the Lacaune population. We present our results on these questions in turn. We studied whether variation in meiotic recombination can be attributed to the historical crossover hotspots detected from LD patterns only. For each interval between two adjacent SNPs of the medium density array, we (i) extracted the number of significant historical hotspots and (ii) calculated the historical hotspot density (in number of hotspots per unit of physical distance).
Improved male recombination maps by combining Lacaune and Soay sheep data Recently, recombination maps have been estimated in another sheep population, the Soay (Susan E. 20  Johnston et al. 2016). Soay sheep is a feral population of ancestral domestic sheep living on an island located northwest of Scotland. The Lacaune and Soay populations are genetically very distant, their genome-wide Fst, calculated using the sheephapmap data  (Kijas et al. 2012 ) , being about 0. 4. Combining our results with results from the Soay offered a rare opportunity to study the evolution of recombination over a relatively short time scale as the two populations can be considered separated at most dating back to domestication, about 10,000 years ago. The methods used in the Soay study are different from those used here, but the two datasets are similar, although the Soay data has fewer male meioses (2,604 vs.
5,940 in the present study). In order to perform a comparison that would not be affected by differences in estimation methods, we ran the method developed for the Lacaune data to estimate recombination maps on the Soay data. As the Soay study showed a clear effect of sex on recombination rates, we estimated recombination maps on male meioses only. Figure  4  presents the comparison of recombination rates between the two populations in marker intervals of the medium density SNP array. The left panel shows that the two populations exhibit very similar recombination rates (r = 0. 82, p<10 -16 ), although Soay recombination rates appear higher for low recombining intervals ( c < 1. 5 cM/Mb in gray on the figure). We explain this by the shrinkage effect of the prior, that is more pronounced in the Soay as the dataset is smaller: the right panel on Figure  4  shows that the posterior variance of the recombination rates are clearly higher in Soays for low recombining intervals while they are similar for more recombining intervals.
Overall, our results on the comparison of the recombination maps in the two populations are consistent with the two populations having the same amplitude and distribution of recombination on the genome. We therefore analyzed the two populations together to create new male recombination maps based on 302,298 crossovers detected in 8,549 meioses (Supporting file S5). Combining the two dataset together lead to a clear reduction in the posterior variance of the recombination rates, i. e. an increase in their precision (Figure  S9 ).
The most significant region was located on the distal end of chromosome 6 and corresponded to a locus frequently associated to variation in recombination rate. In our study the significant region contained 10 genes: CTBP1 , IDUA , DGKQ , GAK , CPLX1 , UVSSA , MFSD7 , PDE6B , PIGG and RNF212. For each of these genes, except RNF212 which was not annotated on the genome (see below), we extracted their gene ontology of the Ensembl v87 database, but none was clearly annotated as potentially involved in recombination. However, two genes were already reported as having a statistical association with recombination rate: CPLX1 and GAK (Augustine  Kong et al. 2014). CPLX1 has no known function that can be linked to recombination (Augustine  Kong et al. 2014)  but GAK has been shown to form a complex with the cyclin-G, which could impact recombination  (Nagel et al.
In addition, none of the SNPs located around these two candidate genes in cattle were significant in our analysis. Eleven genes were present in the region: OR10G2 , OR10G3 , TRAV5 , TRAV4 , SALL2 , METTL3 , TOX4 , RAB2B , CHD8 , SUPT16H and RPGRIP1. The study of their gene ontology, extracted from the Ensembl v87 database, revealed that none of them were associated with recombination, although SUPT16H could be involved in mitotic DSB repair  (Kari et al. 2011). However another functional candidate, CCNB1IP1 , also named HEI10 , was located between positions 23,946,971 and 23,951,850 bp, about 500 Kb from our association peak. This gene is a good functional candidate as it has been shown to interact with RNF212 : HEI10 allows to eliminate the RNF212 protein from early recombination sites and to recruit other recombination intermediates involved in crossover maturation  (Qiao et al.
Discussion In this study, we studied the distribution of recombination along the sheep genome and its relationship to historical recombination rates. We showed that contemporary patterns of recombination are highly correlated to the presence of historical hotspots. We showed that the recombination patterns along the genome are conserved between distantly related sheep populations but that their genetic determinism of genome-wide recombination rates differ. In particular, we showed that polymorphisms within the RNF212 gene are strongly associated to male recombination in Lacaune whereas this genomic region shows no association in Soay males. Hence, combining three datasets, two pedigree datasets in distantly related domestic sheep populations and a densely genotyped sample of unrelated animals, revealed that recombination rate and its genetic determinism can evolve at short time scales, as we discuss below.
Fine-scale Recombination Maps In this work, we were able to construct fine-scale genetic maps of the sheep autosomes by combining two independent inferences on recombination rate. Our study on meiotic recombination from a large pedigree dataset revealed that sheep recombination exhibits general patterns similar to other mammals  (Shifman et al. 2006; Chowdhury et al. 2009; Tortereau et al. 2012). First, sheep recombination rates were elevated at the chromosome ends, both on acrocentric and metacentric chromosomes. In the latter, our analysis revealed a clear reduction in recombination near centromeres. Second, recombination rate depended on the chromosome physical size, consistent with an obligate crossover per meiosis irrespective of the chromosome size. These patterns were consistent with those established in a very different sheep population, the Soay (Susan E.
Johnston et al. 2016)  , and indeed when re-analysing the Soay data with the same approach as used in this study, the results showed a striking similarity between recombination rates in the two populations. Hence, our results show that recombination patterns were conserved over many generations and despite the very different evolutionary histories of the two populations and clear differences in the genetic determinism of GRR in males of the two populations. This similarity allowed to combine the two datasets to create more precise male sheep recombination maps than any of the two studies taken independently. Our historical recombination maps revealed patterns of recombination at the kilobase scale, with small highly recombining intervals interspaced by more wide, low recombining regions. This result was consistent with the presence of recombination hotspots in the highly recombinant intervals.
2014 ) and bovids  (Ruiz-Herrera et al. 2017). Furthermore the variations at the major mammal recombination loci ( RNF212 , CPLX1 , REC8 or the Human inversion 17q21. 31 ) explain only 3 to 11%  (Ritz, Noor, and Singh 2017)  of the phenotypic variance among individuals. Elucidating the genetic determinism of these different processes would thus require much larger sample sizes or different experimental approaches  (Baier et al. 2014; Ruiz-Herrera et al. 2017). The combination of datasets from the Lacaune population and one from the recent study of recombination in Soay sheep (Susan E. Johnston et al. 2016 ) allowed to study the evolution of recombination at relatively short time scales. One of the most striking difference between our two studies is that the two QTLs that were detected in common had no effect in Soay males, whereas they had strong effects in Lacaune males.
Acknowledgments Institut de l'Elevage (JM. Astruc ) and breed organizations (Ovitest and  Confédération de Roquefort)  provided the SNP genotypes and pedigree information. This work was partially funded by the  BoDeliRe  grant of the  INRA Selgen Metaprogram  and by  Région Midi-Pyrénées. We are thankful to  Tom Druet ,  Laurent Duret ,  Alain Pinton  and  Pierre Sourdille  for their helpful comments on the manuscript.
Gene expression arrays (Affymetrix®) and tandem mass spectrometry (MS/MS) were then performed in parallel in SILAC-treated cells material. After confirmation of >98% marked amino-acid incorporation by mass spectrometry analysis, equal amount of proteins were mixed and trypsin-digested. Peptides were quantified and identified by nano-LC-MS/MS. (B and C) Ingenuity Pathway Analysis (IPA) software was used to examine the biological processes enriched by differentially expressed proteins (B) and differentially expressed genes (C) after BAP1 re-expression. expressing BAP1 wt , respectively. Only a diffuse signal with no stress fibers was observed in cell lines expressing either EV or BAP1 C91S (Figure  2A&2B ). Western blot analysis confirmed a 2-fold decrease N-cadherin (CDH2) expression in NCI-H226 and QR cells expressing BAP1 wt and a slight increase was observed in cells expressing catalytically dead BAP1 (Figure  2C ).
BAP1 deubiquitinase activity is associated with reduced respiratory capacities Mitochondrial dysfunction was one of the main pathways highlighted after BAP1 re-expression, and SILAC/MS revealed a high number of proteins involved in the 5 respiratory complexes with a 2-fold reduction in a BAP1 wt expression context (Figure  1B , Supplementary Figure  2B ). Of note, the change of ATP5A1, UQRC2, and SHBD protein expression could not be confirmed when using the Total OXPHOS Antibody Cocktail (data not shown). To measure active mitochondrial network content, we used the MitoTracker Red probe that accumulates in active mitochondria by recognition of depolarization in the inner mitochondria membrane. Flow cytometry analysis revealed that NCI-H226 expressing BAP1 wt has a significantly decreased number of active mitochondria (3 and 2.