Oryza rufipogon is the wild progenitor of cultivated rice Oryza sativa and exhibits high levels of genetic diversity across its distribution, making it a useful resource for the identification of abiotic stress–tolerant varieties and genes that could limit future climate-changed–induced yield losses. To investigate local adaptation in O. rufipogon, we analyzed single nucleotide polymorphism (SNP) data from a panel of 286 samples located across a diverse range of climates. Environmental association analysis (EAA), a genome-wide association study (GWAS)-based method, was used and revealed 15 regions of the genome significantly associated with various climate factors. Genes within these environmentally associated regions have putative functions in abiotic stress response, phytohormone signaling, and the control of flowering time. This provides an insight into potential local adaptation in O. rufipogon and reveals possible locally adaptive genes that may provide opportunities for breeding novel rice varieties with climate change–resilient phenotypes. Domestication and selective breeding are necessary to produce high crop yields; however, crops tend to have a restricted genetic diversity when compared to their wild relatives . The redOryza sativa L.) provides food for approximately 3.5 billion people, accounting for an estimated 50% of the caloric intake of half a billion people living in poverty in Asia  mapping (High genetic diversity is a main characteristic of crop wild relatives (Hordeum vulgare subsp. spontaneum (K. Koch) Thell; Glycine soja Siebold & Zucc; Applications of EAA to investigate local adaptation and identify genetic variation associated with environmental conditions have been demonstrated in a few crop wild relatives, for example the wild progenitors of barley [O. rufipogon with a view to investigating the genetic basis of local adaptations associated with aspects of the abiotic environment, with potential for rice breeding for future or more varied climates. We analyzed genome-wide SNP data from a subset of the wild O. rufipogon accessions sequenced by In this study, we investigate local adaptation in O. rufipogon sensu lato accessions (i.e. including samples referable to O. nivara) located in the OryzaGenome database release 1.0 (O. sativa reference genome (IRGSP 4.0) with Smalt (v 0.4), keeping uniquely mapping reads with >96% identity, and identified by the Ssaha Pileup package (v 0.5), removing low-quality bases. Missing genotypes were imputed using a k-nearest neighbor imputation method with a reported accuracy of approximately 98% . Nineteen bioclimatic variables  were reduced to a single variable to limiting the effects of multiple testing. Therefore, 13 environmental variables were analyzed here.Composite climate variables, principal component 1 (PC1) and PC2, were derived from the climatic data via principal component analysis (PCA) on all climate variables using the RStudio core stats function “princomp” with parameters cor and scores enabled. The first and second principal component values were then extracted. Correlations between variables at each sample location were analyzed with Spearman's rank correlation and visualized using the R package “ggcorrplot” . Based oSNP data from the 286 accessions were processed in RStudio version 3.6.0. Missing data were recoded from “-” to “N”, and the data set was converted to “HapMap” style. SNPs were allocated IDs, e.g. ORRUF01_00001445T:A, detailing the species (ORRUF), chromosome (01), the location within the chromosome (00001445), and the reference/SNP base present (T:A).On average, accessions were missing 6.78% of SNPs after imputation, with a maximum of 13% missing data; therefore, no further accessions were removed from the analysis because of missing data, resulting in a SNP count of 2,463,549. The proportion of missing data for each SNP ranged from 0 to 77.3%, and SNPs with greater than 20% missing data were removed, in line with previous studies  program GAPIT3 .SNPs significantly associated with the climate variables are often clustered into regions due to LD, including putatively neutral SNPs that are in close proximity to a selectively advantageous SNP variant. Regions were identified based on the 0.05 FDR-corrected Gene ontology (GO) term enrichment analysis was carried out on the genes present in the genomic regions identified from the EAA using AgriGO V2.0 .ρ ≤ −0.8; ρ ≥ 0.8) were reduced to a single variable for the EAA, resulting in analysis of 13 variables.The climate variables comprise 19 bioclimatic variables and elevation. Across the sample locations, average annual temperature (BIO1) ranges from 21.4°C to 28.1°C, generally decreasing with latitude . Annual Composite variables were derived from the climate data using PCA, and the first and second PCs were used in the EAA. The greatest loadings for PC1 include BIO1, 4, 9, 11, 14, and 17 , which aPrevious population structure analyses on the SNP data set using neighbor-joining method revealed 3 genetic groups, Or-I, II, and III .The EAA was run using GAPIT, based on 1,898,737 SNPs across 286 individuals. Overall, 8 of 13 variables produced significant associations . VariablRegions (R) were named by chromosome and then sequentially if more than 1 region was present on a chromosome. In total, 15 regions across 9 of the 12 chromosomes were identified, with each passing at least the FDR threshold and most passing the more stringent Bonferroni threshold . Two of The size of each significant region varied considerably, from a single significantly associated SNP to large regions of over 100 kb containing several significant SNPs after FDR correction. This could be a result of differences in sequence coverage or imputation in these regions, degree of LD, or the presence of multiple genes that are associated with the environmental variables.Overall, 86 genes were present within or close to (within 10 kb) the 15 genomic regions . SeveralThree environmentally associated regions were detected in chromosome 1. R1.1 was associated with the precipitation of the driest month, another (R1.2) shows association with precipitation of the wettest month, and the third (R1.3) is in association with the warmest month.PYRICULARIA ORYZAE RESISTANCE T  and a metallothionein gene  ca. 2-kb downstream of this region. R1.2 is ca. 6 kb from a sulfate transporter , which has previously been shown to be upregulated in drought and salinity stresses  is located downstream of this region and is predicted to function in the biosynthesis of ascorbic acid  gene OsFBOX84; LOC_Os02g21110), which is differentially expressed under light and dark conditions , which is located 1.9-kb upstream of the single significant SNP in this region.The final 2 regions in chromosome 2 are associated with temperature of the wettest quarter and mean diurnal range, respectively. R2.2 contains an uncharacterized gene encoding an expressed protein (LOC_Os02g35860), and R2.3 has a terpene synthase gene, ent-isokaur-15-ene synthase .In chromosome 3, a single significant SNP peak was detected and associated with the mean temperature of the wettest quarter (BIO8). This SNP is near a gene encoding an ethylene receptor, R5.1 is associated with the precipitation of the driest month (BIO14), PC1, annual temperature, and temperature seasonality. This region contains a single gene encoding an expressed protein (LOC_Os05g27680) and a transposon protein.O-fucosyltransferase (LOC_Os06g13215), and R6.2, associated with the mean temperature of the wettest quarter (BIO8), is close to a predicted MADS-box transcription factor (LOC_Os06g40609) and an ESCRT-III complex SNF7 component (LOC_Os06g40620).In chromosome 6, 2 significant regions were detected. R6.1, associated with the precipitation of the wettest month (BIO13), contains a predicted growth regulator, OsGHD7-like; LOC_Os07g15770), reactive oxygen species (ROS) antioxidant activity (LOC_Os07g15670), and leaf and spikelet development . OsGhd7 is linked to adaptation of rice to higher latitudes (Ghd7 associated with BIO5 is found in accessions located in environments with high maximum temperatures (R7.1 was found to be associated with the maximum temperature of the warmest month (BIO5). This large 147-kb region contains 26 genes, 22 of which are genes of unknown function or transposons. Genes with functional annotations include genes putatively related to flowering time , with the SNP allele present in accessions found in climates with relatively low precipitation in their wettest month. OsGAD1 has high sequence similarity to AtGAD1 , which is implicated in the response to heat, drought, and hypoxia stresses, through production of GABA (R8.1 is associated with precipitation of the wettest month (BIO13) and contains a glutamate decarboxylase  and mRNA adenosine methylase 4 . Although the function of these proteins in rice is largely unknown, expression of OsUBC10 is upregulated by the phytohormone abscisic acid (ABA)  near genes encoding ubiquitin-conjugating enzyme 10 .In chromosome 12, there are 2 significant regions both associated with BIO14. R12.1 consists of 3 genes with unknown functions, and R12.2 does not contain any genes within 10 kb. The closest gene is 11.2-kb downstream and is predicted to encode a 9-Overall, a large proportion of the environmentally associated SNPs were near genes with unknown functions, highlighting the importance of gene annotation in model systems. Despite this, 8 of the 15 regions identified contain genes with putative functions linked to response to abiotic/biotic conditions or hormone signaling. This included genes known to be regulated by or implicated in ethylene and ABA signaling and the GABA shunt pathway. Genes functioning in response to temperature, drought, UV, and hypoxia were present in several of the significant regions. While there was no significant enrichment of GO terms, this may indicate that the various adaptations are controlled by a range of processes.O. rufipogon. Genes predicted to be in close proximity to these markers were identified and their biological functions were analyzed bioinformatically. This has allowed us to detect genomic regions potentially involved in the local adaptation of O. rufipogon and to highlight genes and mechanisms predicted to contribute to response to environmental conditions.The aim of the analysis was to identify genetic markers associated with variation in environmental conditions across the native range of O. rufipogon, which found that the variables annual temperature, temperature seasonality, and mean annual radiation were the main factors contributing to variation in climate across the population  are often associated with non-functional Ghd7 variants (One of the candidate genes in a region associated with temperature variables encodes the heading date gene Ghd7 could alter flowering time, functioning to escape high temperature stress. Lifecycle shifts for stress avoidance are known to occur in Arabidopsis thaliana in response to a broad range of abiotic and biotic factors (Avena barbata Pott ex Link (OsGhd7 is also responsive to other stress conditions (In our analysis, populations with the nonreference allele were from locations with high maximum temperatures. Because high temperature stress during reproductive stages causes sterility (at least in domesticated rice;  factors  and in t ex Link . OsGhd7 OsGhd7, mentioned before, is repressed by ABA and jasmonic acid (ERS1 is a predicted negative regulator of ethylene signaling, influences root length in O. sativa (Some of the EAA candidate genes are associated with phytohormones, which are often involved in stress response and developmental processes, for example ABA . OsGhd7,O. sativa, UBC10 expression is increased in response to ABA (Finally, the ubiquitin-conjugating enzyme UBC10 is associated with precipitation of the driest month and quarter. UBCs are involved in the ubiquitination of target proteins  and can O. sativa identified large transcriptional changes in root and shoot tissue between drought and control conditions (OsMT2a, a cytochrome p450, an expressed protein and GAD1. In addition to differential expression under drought, 2 genes are induced under other stress conditions too; OsMT2a expression is induced by heat shock (SULTR3;6 is responsive to salinity stresses (O. rufipogon.Some of the EAA candidate genes have possible functions in response to various abiotic stresses. A previous drought study in GAD1 encodes an enzyme in the GABA-shunt pathway and was detected in association with precipitation. The GABA-shunt pathway is branched from the TCA cycle and is thought to function to support the respiratory metabolic system, as well as during stress responses by promoting seedling growth (GAD1 in O. sativa is upregulated during heat (g growth , a mechag growth . GAD1 inFBOX84, predominantly associated with temperature variables in our EAA, is downregulated in white light compared to dark conditions, but not for other stresses (Finally, O. rufipogon accessions with greater than 9× sequencing depth (O. rufipogon that are missing from our analysis, although this can occur even within species (O. rufipogon SNP data set has previously been successfully analyzed using GWAS for traits such as tiller angle (It should be noted that GWAS-based methods have reduced detection power when analyzing complex traits as these are likely controlled by multiple additive loci with weak effects. Although the number of accessions is reasonably high in this study, the SNP sequence data are limited by low coverage, which would have provided less detection power in certain regions. This would especially occur if these regions are characterized by higher recombination rates breaking up the association between SNP alleles and causative genes. Due to the low coverage, the SNP data do not include heterozygous sites, which will be present in a wild species such as this, and so missing possible associations. The proportion of heterozygous sites has previously been calculated to range between 0.1 and 5.4% for 5 Ghd7, a gene known to be involved in local adaptation, and maximum temperature in the EAA (see The EAA only detects associated genomic loci and is unable to detect transcriptional responses to the environment. Related to this, LD can result in the causative gene being distant from a significantly associated SNP, adding to the challenge of confidently selecting candidate genes. LD decays relatively quickly in rice, dropping to half at around 20 kb ( EAA see  providesThe absence of significant GO terms may be explained by LD; only a single gene may be causative in each environmentally associated region, but our GO analysis necessarily included all genes in EAA regions. In addition, for a significant portion of the associated genes, the annotations were weak; hence, some adaptively important genes may have been uncovered but remain with unknown function. Regardless of this limitation, associated regions could be used in marker-assisted selective breeding.O. rufipogon EAA revealed 15 regions of the genome associated with environmental variables and are predicted to contain several genes with functions potentially associated with abiotic stress, flowering, developmental processes, and hormone signaling. The investigation looks at the association between environmental conditions and genetic variation and consequently focuses on the abiotic component of local adaptation. Therefore, additional genomic regions may be detected in association with biotic factors. Although requiring confirmatory analysis, these loci provide significant potential for adaptive variation in the wild progenitor of one of the world's most widely grown crops. Going forward, alleles at these genes have the potential for being incorporated into breeding programs to ensure rice adaptation for a future climate.Taking these caveats into account, the jkad194_Supplementary_DataClick here for additional data file.


Ghir_A09G002730 and Ghir_D03G009280) within qGR-A09-1 and qGI/GP/GR-D03-3 were associated with vigor-related traits, and Ghir_A09G002730 was found to be involved in artificial selection during cotton breeding by population genetic analysis. Thus, understanding the genetic mechanisms underlying seed vigor-related traits in cotton could help increase the efficiency of direct seeding by molecular marker-assisted selection breeding.Seed vigor (SV) is a crucial trait determining the quality of crop seeds. Currently, over 80% of China’s cotton-planting area is in Xinjiang Province, where a fully mechanized planting model is adopted, accounting for more than 90% of the total fiber production. Therefore, identifying SV-related loci and genes is crucial for improving cotton yield in Xinjiang. In this study, three seed vigor-related traits, including germination potential, germination rate, and germination index, were investigated across three environments in a panel of 355 diverse accessions based on 2,261,854 high-quality single-nucleotide polymorphisms (SNPs). A total of 26 significant SNPs were detected and divided into six quantitative trait locus regions, including 121 predicted candidate genes. By combining gene expression, gene annotation, and haplotype analysis, two novel candidate genes ( Gossypium hirsutum L.) is one of the world’s most important cash crops and a major source of natural fibers, accounting for more than 95% of global cotton production  have a strong effect on seed germination  and abscisic acid (ABA) have been reported to be essential for the regulation of seed germination —for exammination . When plmination . Low levmination —for exam content . The relbidopsis , wheat , 28 SV-related QTLs were identified by a SNP genotyping array, and one major QTL (11.2q1stGC) explaining 19.9% of the phenotypic variation (PV) was flanked by SNP_11_27994133 on chromosome 11  related to GR were identified by 122 backcross inbred lines, and the phenotypic variation explained (PVE) by qLTG-3-1 was 35.0%  responsible for seed germination was detected through a GWAS panel in upland cotton by using whole-genome resequencing  for SV-related traits were further identified by a GWAS panel, laying the foundation for understanding the genetic mechanism underlying SV and providing potential information for applying these potential elite loci for marker-assisted selection (MAS) in cotton breeding.To date, many quantitative traits have been reported in cotton, such as fiber quality traits , early mThe 355 upland cotton germplasm resources collected by laboratories worldwide represent a natural population. Previous studies focused on early maturity , fiber qThe phenotyping of SV-related traits was carried out by the sandponic method based on previously described methods . Cotton https://github.com/broadinstitute/picard) was used to sort the BAM file and mark duplicate reads; (5) The ‘HaplotypeCaller’ module of GATK (version: 4.2.6.1) was used to identify variant sites and perform SNP filtering with the following conditions: ‘QUAL <30, DP <1,340, DP >10,050, QD <2.0, MQ <35, FS >70, SOR >3, MQRankSum <-12.5, and ReadPosRankSum <-4.0’; (6) The SNP clusters with at least three SNPs detected within a 10-base window were removed; (7) SNPs within five base pairs of an InDel were filtered out by BCFtools software (version: 0.1.19-44428cd) (The resequencing data (PRJNA389777) of the 355 upland cotton germplasms used in this study were reported in a previous study . The Ill44428cd) ; and (8)44428cd) .P <1 × 10-6 was used as the threshold to detect significant SNP loci. Additionally, the PVE by each marker was calculated as previously reported (π)a value was calculated using VCFtools based on the release years  and geographical distribution  of the 355 accessions. The packages ‘CMplot’ (https://github.com/YinLiLin/CMplot), ‘LDheatmap’  and executed by vcf2gwas software (version: 0.8.7) . P <1 × reported . The nucheatmap’ , and ‘ggheatmap’  in R sofhttps://www.cottongen.org/). Then, local BLAST software was used to compare the protein sequence of the candidate gene with the Arabidopsis protein database (https://www.arabidopsis.org) to obtain the homologous sequence, and the criterion was set to less than E-60  and SYBR with three biological repeats. The public RNA-seq data (PRJNA248163) including SRR1695160, SRR1695161, and SRR1695162 were downloaded from NCBI (https://www.ncbi.nlm.nih.gov/bioproject/). The Illumina Hiseq2000 platform was used to perform RNA sequencing on ‘TM1’ seeds soaked in water for 0, 5, and 10 h, and the paired-end clean reads length was more than 100 bp. The gene expression values were normalized by the average expression levels (log2) based on transcripts per million values. The clustered heat map was drawn by the R package ‘pheatmap’ (Based on the ‘TM-1’ reference genome (HAU_v1.1) , the genhan E-60 . The expheatmap’ .Resequencing of the natural population libraries by the Illumina HiSeq 4000 platform with 150 bp paired-end reads, as described in previous reports , yieldedP < 0.001)  of natural population accessions were measured in three environments. The values followed a normal distribution for the GI and GP but showed a skewed distribution for GR based on Shapiro–Wilk tests (10(p) values was from 6.00 to 8.27. Furthermore, 26 stable SNPs were identified in a minimum of two environments  or two traits, which were declared as six stable QTLs, focusing on chromosomes A09, A10, and D03. Notably, a QTL region (qGR-A09-1) located on chromosome A09 showed a strong SNP cluster associated with GR, which had a PVE of 6.76–8.56% and -log10(P) ranging from 6.19 to 7.74. qGP-A10-1 on chromosome A10 had only one SNP that explained 8.15% of the observed PVE, with a LOD score of 7.39. Four QTLs on chromosome D03  were identified in two, three, three, and four environments, explaining 6.61–7.39%, 6.72–7.79%, 6.65–8.43%, and 6.61–8.90% of the observed PVE, respectively. Interestingly, a stable QTL (qGI/GP/GR-D03-3) region was revealed on chromosome D03 from 31.68 to 32.61 Mb and was flanked by regions associated with the GI, GP, and GR in the E1, E3, and BLUP environments. Thus, the QTLs qGR-A09-1 and qGI/GP/GR-D03-3 could be treated as major QTLs for further dissection.A total of 292 significant SNPs for three SV-related traits were identified on 11 chromosomes using the linear mixed model S3. OnlyqGR-A09-1, exhibited a significant SNP cluster  occupying a physical region of 0.2 Mb on chromosome A09   superfamily protein family and has higher expression levels during the seed germination stage from 0 to 10 h than other genes (Ghir_A09G002730 had higher expression levels in the accessions (‘Liaomian27’ and ‘Xinluzhong35’) carrying the AA allele than in accessions (‘PB12-1-8’ and ‘Xiazao2’) with GG allele during the seed germination stage  in Arabidopsis  were measured for seeds collected from three locations: E1, E2, and E3. Among them, GR and GP did not show an absolute normal distribution, which was also found in previous studies , indicatGhir_A09G002650 was annotated on chromosome A09, belonging to the GA-regulated family of proteins and encoding a protein containing the GASA domain, which is most closely related to the known homolog GASA14 in Arabidopsis. GASA14 regulates the increase in plant growth through GA induction and DELLA-dependent signal transduction, which could increase resistance to abiotic stress by reducing the accumulation of ROS  and chromosome D03 (qGI/GP/GR-D03-3)  Figure 3rocesses . We alsomination . FurtherGhir_A09G002730 and Ghir_D03G009280 caught our attention based on gene expression (RNA-seq and qRT-PCR), gene annotation, and haplotype analysis, which may play a key role in regulating the germination of cotton seeds. These results will enhance our understanding of the molecular–genetic regulation of SV in cotton.In the present study, there was a total of 121 predicted candidate genes within six stable QTL regions. Furthermore, https://www.ncbi.nlm.nih.gov/bioproject/).The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: The resequencing data (PRJNA389777) of the 355 upland cotton germplasms used in this study. For RNA-seq data: The public RNA-seq data (PRJNA248163) including SRR1695160, SRR1695161, and SRR1695162 were downloaded from the NCBI (LL: Conceptualization, Software, Visualization, Writing – original draft, Writing – review & editing. YH: Data curation, Formal Analysis, Investigation, Software, Visualization, Writing – original draft. YW: Methodology, Writing – review & editing. YY: Writing – original draft. RL: Software, Visualization, Writing – review & editing. JW: Visualization, Writing – review & editing. MY: Methodology, Supervision, Writing – review & editing. SZ: Conceptualization, Investigation, Software, Writing – review & editing. FZ: Writing – review & editing. JH: Conceptualization, Writing – review & editing. SY: Conceptualization, Writing – review & editing. ZF: Conceptualization, Investigation, Supervision, Writing – review & editing.


This study concerns evaluation of the possible negative effects of power plants as one of the most important objects generating environmental pollution in aquatic ecosystems. We attempted to research the intraspecific genetic diversity of a naturally distributed fish species, Eurasian perch, based on a comparison of its mitochondrial DNA sequences. To distinguish naturally occurring mutagenesis from DNA changes caused by thermal or chemical pollution, the molecular data representing patterns of perch populations inhabiting hydro-systems profoundly affected by power plants and non-affected perch populations were collected and analysed. The obtained results indicate that most genetic differences among perch populations representing a large geographic area that encompasses territories from the Baltic Sea to Ukraine could be explained by historical and ongoing natural processes instead of pollution from power plants.ATP6 region in the adaptability and microevolution of Perca fluviatilis within phylogeographic and anthropogenic contexts. We sequenced a 627 bp fragment encompassing the ATP6 region and used it for genetic analysis of 193 perch caught in Latvia, Lithuania, Belarus, and Ukraine, representing natural and anthropogenically impacted populations. We evaluated patterns of intraspecific genetic diversity in the ATP6 region and phylogeographic trends within the studied area compared with previously established D-loop trends. Evaluation of ATP6 coding sequence variability revealed that among 13 newly detected haplotypes, only two were caused by non-synonymous substitutions of amino acids of the protein. PCoA revealed three genetic groups (I–III) based on the ATP6 region that encompassed four previously described genetic groups established based on the mtDNA D-loop. The two mtDNA regions (D-loop and ATP6) have microevolved at least partially independently. Prolonged anthropogenic impacts may generate new point mutations at the ATP6 locus, but this phenomenon could be mainly concealed by natural selection and reparation processes.The intraspecific genetic diversity of freshwater fish inhabiting hydro-systems of the macrogeographic area spreading from the Black to Baltic Seas requires comprehensive investigation from fundamental and practical perspectives. The current study focused on the involvement of the mtDNA  The 21st century is the peak of the Anthropocene, as all terrestrial and aquatic ecosystems in the world are directly or indirectly affected by various human activities ,4. ThereWhile NPPs are generally considered to be a relatively safe option for generating electricity , technogGlobal freshwater ecosystems and their biodiversity are susceptible to anthropogenic impacts that are not limited to NPP and TPP activities, which affect aquatic abiotic, biotic, and genetic resources ,21,22. TFreshwater ecosystems spreading between the Black and Baltic Sea Regions require special attention, as the ChNPP is located close to the border between Ukraine and Belarus, and this power plant was set approximately at the midpoint between these seas ,40. PopuPerca fluviatilis L.) currently occupies a wide natural range that encompasses European  and Asian  areas [cytb, 16S RNA, and cytochrome oxidase subunit I (COI), have been included in comprehensive studies [Eurasian perch (a) areas . In addia) areas ,45 can ba) areas . Perch aa) areas . In genea) areas . Thus faa) areas ,48, DNA a) areas ,51,52,53a) areas ,55, randa) areas , amplifia) areas , major ha) areas ,59, intea) areas , and inta) areas  moleculaa) areas ,61,62,63a) areas ,64,65,66 studies ,67. More studies . The mat studies  of perch studies , like th studies . In addi studies ,72,73,74 studies . IntraspATP6) and ATP synthase F0 subunit 8 (ATP8) loci are the most rapidly evolving and adaptable loci among mtDNA genes [ATP6 marker for freshwater fish species in Europe based on data from intraspecific genetic research. Based on data reported by Vasemägi et al. [ATP6 gene variability is quite similar to that of other coding mtDNA regions. However, to date, ATP6 has not been used specifically for comprehensive research on intraspecific variability of perch populations in Europe and Asia.In some fish species, the ATP synthase F0 subunit 6  or as reduced genetic diversity of the studied fish populations in particular locations (H2).The present study presents trends of the genetic structure and phylogeographic relationships among the studied Eurasian perch populations inhabiting hydro-systems of Lithuania, Latvia, Belarus, and Ukraine. We generated these results using the mtDNA Samples of perch were delivered to the Laboratory of Molecular Ecology, Nature Research Centre  by hydrobiologists and fishermen. A total of 193 perch  were investigated during the current study; the sex and precise age of the individuals were not determined. A detailed list of samples collected from Lithuania, Latvia, Belarus, and Ukraine is shown in This study also focused on the anthropogenic context, especially effects associated with NPP and TPP activities. It should be noted that all of the collected perch samples could be considered to be affected by different doses of radionuclides due to radioactive contamination of freshwater ecosystems in the studied area after the ChNPP accident in 1986. Based on the available data , the LitTo sum up, the most representative samples (n = 19–30) were obtained from Lakes Cirīšu and Engure in Latvia, the Mozyr area in Belarus, and Lake Drūkšiai and the Neris River in Lithuania , includiATP6 fragments were amplified with the help of newly designed primers: ATP-PCR-F (5′-CCCTAACGAGCCTACATCCC-3′) and ATP-PCR-R (5′-TGTAAGAGGTCAAGGGCTGG-3′). Briefly, available perch mtDNA sequences deposited in GenBank were retrieved and aligned, and conservative fragments with unchanging nucleotide positions suitable for primer design were chosen using Primer3 program [The genomic DNA of perch was extracted from frozen or ethanol-preserved muscle or fin clips following the universal and rapid salt-extraction method  with sli program . 4)2SO4, 2.5 μL of 25 mM MgCl2, 2.5 μL of dNTP Mix (2 mM), 0.2 μL of 5 U/μL 500 U Taq DNA polymerase , 1 μL of each primer, 10.3 μL of water, and 5 μL of template DNA. Amplification started with an initial denaturation for 2 min at 95 °C; followed by 35 cycles of 30 s at 94 °C, 45 s at 52 °C, and 45 s at 72 °C; and a final elongation for 5 min at 72 °C. The PCR products were purified with the help of ExoI and FastAP enzymes  and sequenced directly using the Big-Dye® Terminator v3.1 Cycle Sequencing Kit and a 3500 Genetic Analyzer . Most polymerase chain reactions (PCRs) were performed in a total volume of 25 μL, consisting of 5 μL of perch genomic DNA, 12.5 μL of DreamTaq DNA polymerase mix , 5.5 μL of nuclease-free water, and 1 μL of each primer. The other PCRs were performed in a total volume of 25 µL, including 2.5 μL of 10 ×Taq buffer with (NHATP6 region sequences—a 627 base pair (bp) fragment representing nucleotides 1–589 of ATP6 and nucleotides 589–627 of cytochrome c oxidase subunit III (cox3)—were analysed to define different haplotypes using FaBox v. 1.5 [ATP6 region haplotypes were deposited in GenBank under accession numbers OQ676936–OQ676948. The ClustalW algorithm [ATP6 region nucleotide sequences into amino acids. The Hasegawa–Kishino–Yano (HKY) evolutionary nucleotide substitution model [Perca flavescens Mitchill) was selected as the outgroup sequence from GenBank. The haplotype network was created using the median joining (MJ) method implemented in NETWORK 10.2.0.0 software [ST values were calculated using Arlequin v. 3.5.2.2 [ST values was tested by 10,000 permutations at the 95% confidence level. Principal coordinates analysis (PCoA) using Nei’s genetic distance [Truncated x v. 1.5 . Notablylgorithm  implemenlgorithm  was usedon model  appearedsoftware . Relatedsoftware ; nucleotsoftware ; and selsoftware . To eval 3.5.2.2 . The staATP6 and D-loop regions were evaluated by comparing sequences of perch individuals collected from Lakes Cirīšu and Engure in Latvia and Lake Drūkšiai in Lithuania. This endeavour used the ATP6 region data collected in this study and the mtDNA D-loop data obtained from a previous study [Trends of genetic variability based on the us study . Specifius study . For extThis study also used data reported by Ragauskas et al.  for the ATP6 region  and in cox3 at position 607 (G→C in haplotype D3). The ML dendrogram also supported the separation of four haplogroups , 28 (14.51%), 46 (23.83%), and 32 (16.58%) sequences, respectively . We deteBased on PCoA, the first and second principal components explained 68.8% and 25.2% of the genetic variation, respectively, and three genetic perch groups could be defined by this analysis . The firThe calculated parameters of genetic variability—h, K, S, and π—in different perch samples are presented in ST values ranged from −0.077 to 0.900 (ST < 0.05); however, there were also samples that showed marked genetic differences from one another (ΦST > 0.25). Aside from the Meleshkovichi River channel sample, we found the most significant ΦST value  by comparing the Curonian Lagoon and Lake Žeimenys samples. This result supported the PCoA result, as the distance between these two samples was the largest based on the first principal component  that acted as a stop codon before the 13 codons that represented part of the cox3 gene  and cox3  partial sequences (ATP6 region haplotypes could be detected outside the studied macrogeographic area. These two unique ATP6 region haplotypes were represented by two specimens from China (AP005995 and MZ461595) and the perch mtDNA genome from Hungary (KM410088), which could be distinguished from haplotype A by two and four point mutations, respectively. Even so, there were no additional non-synonymous substitutions.The analysed 627 bp ox3 gene . The firequences . NucleotATP6 region as well as those without the cox3 gene fragment are presented in The calculated dS/dN ratios for groups I, II, and III using the entire ATP6 partial sequence that for the entire studied ATP6 region. This indicated stronger effects of purifying selection in the studied part of the ATP6 gene than in the cox3 gene. The lowest ω values in the ATP6 region and partial ATP6 sequence occurred in genetic group II, which included the majority of studied individuals (n = 101) and dominated the eastern Lithuanian and Latvian territories. Conversely, we detected carriers of haplotypes D1 and D3 that had non-synonymous substitutions between geographically distant territories (Ukraine and Lithuania). This could imply that natural selection might have had different effects on perch populations inhabiting northern parts compared to those in warmer parts of Europe.All ω values were below 1 and generally indicated the effect of relaxed purifying selection. We observed a lower total dS/dN ratio for the ATP6 and D-loop sequencing data of the same individuals are presented in The Both mtDNA regions indicated that there were fewer haplotypes and haplogroups detected in the studied Belarussian perch populations than in the Latvian and Lithuanian perch populations . ATP6 marker were lower  than those calculated using the D-loop region  among the Lithuanian, Latvian, Belarussian, and Ukrainian samples  eastern part (Lakes Cirīšu and Sventes) of this country and the western part of Lithuania. The lowest diversity based on both markers was in the Meleshkovichi River channel sample. In Lithuania, the Elektrėnai Reservoir and Lake Plateliai could be indicated as hot and cold spots, respectively, as D-loop variability was highest and lowest, respectively, in these two samples. Interestingly, Lake Plateliai is more elevated (>140 m) than the surrounding western region near the Baltic Sea (0–10 m). Based on the ATP6 region, the Desna River in Ukraine was a hot spot. When combining all Ukrainian samples, the h value (0.786 ± 0.113) was still higher than that of the combined Belarussian samples (0.611 ± 0.046)  . Convers± 0.046)  with simATP6 region (ranging from 0 to 0.004). The Desna River sample had the highest value for the ATP6 region. When combining the Ukrainian samples, the obtained value was still the highest (0.00325 ± 0.00055) (0.00055) . Based oATP6 genetic groups    showed aand III) . The obtand III) , had no of perch . ATP6 to study perch population genetics, including phylogeography and possible changes in genetic variation of perch populations related to anthropogenic activities in Europe. Our work provides new specific knowledge of the genetic variability of perch based on a mtDNA molecular marker that includes the majority of the ATP6 gene and part of the cox3 gene. We emphasised evaluating the possible effects of natural selection and trends of species genetic variation within a macrogeographic area encompassing the Black and Baltic Sea Regions. Different mtDNA regions as well as other types of molecular markers and their combinations, including the entire mtDNA genome, have different potentials to reflect distinct historic events as well as microevolution see . TherefoATP6 in natural fish populations has been determined both interspecifically [ATP6 region has been affected by relaxed purifying selection, and the purifying effect on the ATP6 sequence was more pronounced compared to that on the entire studied mtDNA fragment. Consequently, in this regard, our results are similar to those reported by Deng et al. [Ammodytes personatus Girard) for which ω ranged from 0.0167 (lineage B) to 0.0384 (lineage A). Pichaud et al. [nd4) gene and variations representing adaptability of this gene, was highly affected by warmer temperatures. Our results   between representatives of the three distinct groups. Consequently, based on molecular data obtained using the ATP6 marker, the established groups I and II indicated an obvious qualitative genetic difference between perch inhabiting the Nemunas and Neris River hydro-systems   showed aand III) . It is iand III) . The samand III) . Most pa-systems , respect-systems . Therefo-systems . The resependent . In futuy et al.  found the D-loop . Other pe D-loop . Perch pATP6 overlapped with most of the perch phylogeographic trends in Eurasia determined by sequencing other mtDNA regions [We can conclude that the newly determined trends indicated by  regions ,38,41,62 regions . Finally regions ,37,41,97Because of the recent challenges of the 21st century—such as the brutal war initiated by Russia in Ukrainian territory causing an economic and humanitarian crisis—the risk of radiocontamination is increasing, mainly due to NPPs located in the war zone  . In addiATP6 gene in microevolution [ATP6 region. Several generations have passed since the anthropogenic activities increased in the studied location, which could have concealed the increase in new point mutations. A similar trend was observed in previous research with perch using the mtDNA D-loop region [ATP6 region because of specific anthropogenic activities, such as contamination of the environment by radionuclides, and could be detected in specimens of perch affected by anthropogenic activities , but subsequent natural selection or reparation processes could eliminate new mutants from the population. The findings suggest that neither hypothesis H1 nor H2 could not be outright rejected, especially using more sensitive methods. However, their confirmation was not likely because the obtained results could be better explained by the perch phylogeographic trends observed in Lithuania, Latvia, and Belarus  was better explained by isolation over time rather than anthropogenic activities caused by FNPP operation for more than two decades. On the other hand, MHC class IIβ genes experienced strong natural selection effects within the artificial cooler of the FNPP. Similar studies devoted to evaluating the anthropogenic impact of different NPPs on the genomes of fish located in brackish and freshwater ecosystems are required. It is also reasonable to consider expanded research of transcriptomic profiles of the affected and intact perch populations, as it has been shown that messenger RNA (mRNA) changes could appear due to attempts to domesticate wild perch [To detect other possible, subtler transformations of genetic variability, such as changes in haplotype frequencies over different timescales of NPP exploitation, temporal samples should be studied ,103. In ld perch . In addild perch .ATP6 genetic diversity within the studied macrogeographic area. Thus far, ATP6 intraspecific research of various freshwater fish species in Europe is extremely limited [Single molecular markers, including whole mtDNA molecules, have a one locus limitation but are still useful as a first research step. Notably, the trends of genetic diversity revealed in the current work strongly support previous findings based on mtDNA-based analyses, and the results reported by Toomey et al.  based on limited . Compreh limited ,66, gene limited  variabil limited ,16,99, eATP6 region haplotypes in the studied macrogeographic area  represented by different compositions of A, B, C, and D haplogroups specifically distributed in the studied area. Of note, the Lithuanian and Latvian perch populations could be discriminated from those inhabiting the heterogenous hydro-systems of eastern Belarus and Ukraine. Microevolution of the mtDNA ATP6 and D-loop regions has been at least partially independent. Although the current study provides the most recent data and trends od the genetic and protein variability of perch based on the ATP6 region, our hypotheses H1 and H2 regarding the impact of anthropogenic activities on the genetic structure of perch remain to be comprehensively tested. As the next major step, we recommend performing genomic and transcriptomic investigations of perch populations affected by NPPs or TPPs, as research within the anthropogenic context requires applying the most sensitive methods.The first comprehensive attempt to reveal major patterns and trends of the intraspecific genetic diversity of


Many viruses activate cellular autophagy in infected cells to facilitate their replication. Recently, we identified an interferon (IFN)-stimulated gene (ISG) Tudor domain containing 7 (TDRD7), which inhibits viral replication by blocking autophagy pathway. Here, we present a molecular mechanism for TDRD7 action and its relative contribution to protection against viral pathogenesis. TDRD7 inhibited the activation of adenosine monophosphate (AMP)-activated protein kinase (AMPK), a kinase required for initiating autophagy. Mechanistically, TDRD7 interacted directly with AMPK in the cytosolic compartment. Domain-mapping analyses revealed C-terminal Tudor domain of TDRD7 interacted with auto-inhibitory domain of AMPK. Deletion of Tudor domains abolished anti-AMPK and antiviral activities of TDRD7. We evaluated physiological relevance of TDRD7 function against viral replication using newly engineered TDRD7 knockout mice and the derived primary cells. TDRD7 knockout primary cells displayed increased AMPK activation, which led to a higher viral load. Subsequently, TDRD7 knockout mice showed enhanced susceptibility upon intranasal Sendai virus infection. Therefore, our study revealed a new antiviral function of IFN, mediated by TDRD7-AMPK, inhibiting viral replication and pathogenesis.Virus infection triggers induction of interferon (IFN)-stimulated genes (ISGs), which ironically inhibit viruses themselves. We identified Tudor domain-containing 7 (TDRD7) as a novel antiviral ISG, which inhibits viral replication by interfering with autophagy pathway. Here, we present a molecular basis for autophagy inhibitory function of TDRD7. TDRD7 interacted with adenosine monophosphate (AMP)-activated protein kinase (AMPK), the kinase that initiates autophagy, to inhibit its activation. We identified domains required for the interaction; deleting AMPK-interacting domain blocked antiAMPK and antiviral activities of TDRD7. We used primary cells and mice to evaluate the TDRD7-AMPK antiviral pathway. TDRD7-deficient primary mouse cells exhibited enhanced AMPK activation and viral replication. Finally, TDRD7 knockout mice showed increased susceptibility to respiratory virus infection. Therefore, our study revealed a new antiviral pathway of IFN and its contribution to host response. Our results have therapeutic potential; a TDRD7-derived peptide may be an effective AMPK inhibitor with application as antiviral agent. Virus infection causes rapid activation of pattern recognition receptors (PRRs), e.g., TLR, RLR, cGAS, and STING, which sense viral nucleic acids and trigger intracellular signaling pathways –3. PRRAutophagy is initiated by activation of adenosine monophosphate (AMP)-activated protein kinase (AMPK), a Ser/Thr kinase. Low cellular ATP levels lead to increased AMP, which activates AMPK triggering, in addition to autophagy, an array of downstream signaling pathways, e.g., mTOR, SIRT1, and GLUT –13. Ma2+ levels, which are associated with nutrient deprivation, cellular stress, and viral infection. In addition to direct activation, AMPK can be activated by pharmaceuticals and chemical agents. Metformin, an antidiabetic compound currently used on patients, activates AMPK by increasing cellular AMP levels. AMPK can be activated noncanonically by DNA damage or reactive oxygen species (ROS), which are not associated with increase in AMP or Ca2+ levels. In addition, A-769662, identified using a high throughput screen, binds AMPK directly to activate it. AICAR, a chemical agent, upon cellular uptake, produces an AMP analog that activates AMPK. Among kinases known to phosphorylate AMPK, liver kinase B1 (LKB1) is the most well-studied. LKB1 gets recruited to the AMPK-activating complex in presence of increased cellular AMP  and regulatory (β and γ) subunits and is activated during energy-deprived cellular conditions , 13. AMPular AMP . In presular AMP . Activat172 (pAMPK) in TDRD7 knockout cells, was inhibited by restoration of TDRD7 expression  using co-IP, which revealed that ΔOST mutant interacted with AMPK (3) or Tud-2 and Tud-3 together (ΔTud2+3), however, blocked AMPK interaction  and Tudor (∆Tud)] domains . We valiith AMPK . Deletioeraction , indicateraction . Therefoeraction . Recombiith AMPK . These rWe next mapped TDRD7-interacting domain of AMPK by deleting its critical functional domains, as shown in To determine whether TDRD7:AMPK interaction is responsible for TDRD7-mediated inhibition of AMPK, we expressed Wt TDRD7 (AMPK interacting) and ΔTud mutant (AMPK noninteracting) in TDRD7 KO human cells at similar protein levels . In contIn previous studies, we demonstrated that antiviral function of TDRD7 depends on its antiAMPK activity; AMPK inhibitor alleviates the antiviral activity of TDRD7 . To invefl/fl) mice with CreCMV deleter mice -Tdrd7  staining revealed increased immune cell infiltration in Tdrd7Δ/Δ lungs, compared to Tdrd7fl/fl control ; TDRD7 KO HT1080 cells and L929 cells expressing Tdrd7-specific shRNA were described previously  and SeV 52 VR-105) strains (Charles River) and HSV-1 KOS strain , and the5 strainseviously .For analyses of AMPK activation through serum starvation, the cells were washed with and incubated in serum-free DMEM for 4 h or the time period indicated in figure legends or treated with 500 µM of AICAR for 2 h. The cells were harvested, and pAMPK was analyzed by immunoblot.Immunoblot analyses were performed using previously described procedures , 42. BriEscherichia coli BL-21 strain using the previously described procedure  and AMPK (doubly-tagged with His and HA) proteins were purified from rocedure .in vitro interaction, bacterially purified TDRD7 and AMPK proteins were incubated at 37°C for 2 h, and co-IP assays were performed. For co-IP of endogenous TDRD7 and AMPK proteins, mouse liver homogenates were prepared in lysis buffer and immunoprecipitated by anti-AMPK antibody followed by immunoblot with anti-TDRD7 antibody.Co-immunoprecipitation assays were performed by co-transfection of epitope (HA or His)-tagged AMPK and V5-tagged TDRD7 constructs for 24 h followed by lysis in 3-[4-(2-hydroxyethyl)piperazin-1-yl]propane-1-sulfonic acid (EPPS) buffer containing protease inhibitors by repetitive freeze-thaw cycles, and lysates were immunoprecipitated with anti-V5-agarose beads or pulled down with Ni-NTA-agarose beads overnight at 4°C. Beads were washed twice with EPPS buffer and once with RIPA buffer, and bound proteins and eluates were analyzed by immunoblot. For The AMPK three-dimensional structure was modeled on template 6C9J, and the TDRD7 structure was built on template 5m9n.2 based on sequence homology using SWISS-MODEL because there was no structure available for full-length TDRD7. The templates were selected based on the close sequence similarity and were used for docking analysis. The 3D model structure of the AMPK:TDRD7 complex was predicted using Z-DOCK. The auto-inhibitory domain of AMPK and Tudor domain of TDRD7 were used for binding, and non-interacting residues were blocked in the input for predictions from Z-DOCK. The top 10 predictions were analyzed, and the most likely conformation was selected based on the binding affinity and optimal binding arrangement as a representative.Cytosolic, nuclear, and mitochondrial fractions from transfected cells were isolated as described previously using the Mitochondria Isolation Kit (Pierce Biotechnology), following the manufacturer’s instructions . IsolateCTAAGGGCTGTCCTGCAGTC; Tdrd7-rev, AGAGTTGCCTTTGGCTTT; SeV P-fwd, CAAAAGTGAGGGCGAAGGAGAA; SeV P-rev, CGCCCAGATCCTGAGATACAGA; SeV genome-fwd, ACTGGTCCGGATAAGAAGGC; SeV genome-rev, AGTTCCTGATCAGACCCGTG; 18S-fwd, ATTGACGGAAGGGCACCACCAG; 18S-rev, CAAATCGCTCCACCAACTAAGAACG.Total RNA was isolated using Trizol extraction, and cDNA was prepared using ImProm-II Reverse Transcription Kit (Promega). For qRT-PCR, 0.5 ng of cDNA was analyzed using Radiant SYBR Green reagent  on Roche Light Cycler. Expression levels of the mRNAs were normalized to 18S rRNA. For the qRT-PCR analyses of the respective genes, the following primers were used: Tdrd7-fwd, HEK293T cells were transfected with TDRD7 Wt or mutants; 24 h later, the cells were infected with SeV (Cantell) at an MOI of 10. After 16 h, cells were harvested, fixed with 1% paraformaldehyde in PBS for 10 min, permeabilized with 0.1% (wt/vol) Triton X-100, and incubated with an anti-SeV polyclonal antibody and an Alexa Fluor conjugated secondary antibody. Cells were analyzed on BD Canto (flow cytometer) using Flow Jo. The relative infectivity in each condition was normalized to EV to obtain percent infection.HEK293T cells were grown on coverslips and transfected with HA-AMPK and V5-TDRD7. Twenty-four hours post-transfection, the cells were fixed in 4% paraformaldehyde and permeabilized in 0.2% Triton X-100 and immunostaining by anti-HA and anti-V5 antibodies followed by Alexa Fluor-conjugated secondary antibody. Objects were mounted on slides using VectaShield/DAPI and analyzed by confocal microscopy. For studying interaction of endogenous proteins, HT1080 cells were grown on coverslips and immuno-stained with anti-TDRD7 and anti-AMPK antibodies, followed by Alexa Fluor-conjugated secondary antibodies. Images were further processed and analyzed using Adobe Photoshop software. Multiple culture fields were analyzed to select representative images. For the proximal ligation assay, the immunostained (with anti-HA and anti-V5 antibodies) cells were used for duolink assay  using manufacturer’s instructions and as described previously .fl/fl mice were custom generated by Cyagen Inc, using the design of the target allele indicated in fl/fl mice were crossed with CreCMV mice (from JAX) to obtain the Tdrd7Δ/Δ mice and used for our studies. The genotyping of the mice was performed using the following primers: P1, GTGCTGAATGCCTGAAAGATGATG; P2, CTCATTGTTTTATGTTGTGCGGAC; and P3, CAACACAGGCCATACATGAACAGAG  or one-way analysis of variance (ANOVA) (for comparing more than two groups), based on the number of sets for comparison. P < 0.05 was considered statistically significant. The results presented here are representatives of three or more independent experiments.Statistical analyses were performed using GraphPad Prism 9 software or Microsoft Excel for Windows 10. The


RXFP2, as a gene under strong selective pressure in the GUA population likely owing to human-driven  pressure. Findings from this study provide insight into the genetic mechanisms associated with resilience traits in livestock.The Creole cattle from Guadeloupe (GUA) are well adapted to the tropical environment. Its admixed genome likely played an important role in such adaptation. Here, we sought to detect genomic signatures of selection in the GUA genome. For this purpose, we sequenced 23 GUA individuals and combined our data with sequenced genomes of 99 animals representative of European, African and indicine groups. We detect 17,228,983 single nucleotide polymorphisms (SNPs) in the GUA genome, providing the most detailed exploration, to date, of patterns of genetic variation in this breed. We confirm the higher level of African and indicine ancestries, compared to the European ancestry and we highlight the African origin of indicine ancestry in the GUA genome. We identify five strong candidate regions showing an excess of indicine ancestry and consistently supported across the different detection methods. These regions encompass genes with adaptive roles in relation to immunity, thermotolerance and physical activity. We confirmed a previously identified horn-related gene,  Subsequently, between the sixteenth and eighteenth centuries, West African cattle are thought to have entered the Caribbean and Brazil, presumably as a consequence of slave trade routes3. Genetic evidence also points to a West African influence on Creole cattle5. Around the middle of the nineteenth century, several other European cattle breeds were brought in large numbers to the Americas. Later on, during the beginning of the twentieth century, Bos indicus were imported from India to improve the adaptability of local populations in tropical areas of the Americas through extensive crossbreeding6.One of the major consequences of long-distance human migrations is the displacement of domestic animals into new environments, thus putting a strong selective pressure on the genome of these animals over a brief period. One example is the introduction of cattle to the western hemisphere. New World Creole cattle were first brought from the Iberian Peninsula by Spanish colonists since the second expedition of Christopher Columbus in the late fifteenth century. Creole cattle breeds have then undergone a rapid expansion throughout the American continent7. The GUA population is well adapted to tropical environment and to the conditions of the local production systems characterized by nutrient-poor pastures. This is exemplified by low feed requirement, heat tolerance and by the ability to make use of poor-quality forage efficiently to have an acceptable body weight gain8. The GUA population also appears particularly resistant to local parasitic and infectious diseases9.The Creole cattle in the Guadeloupe island (GUA) is an admixed breed. Published estimates of ancestry proportions of this population indicate 26%, 36% and 38% of European taurine (EUT), African taurine (AFT) and indicine (IND) ancestries in the GUA genome, respectively12. These studies benefited from ongoing advancements in genomic technology and the development of improved statistical and computational methods to identify signatures of selection in cattle genome, that is genomic regions that appear to be shaped by selection.Elucidating the genetic architecture of adaptation is becoming an increasingly relevant topic in animal genetics. Indeed, it is expected that innovative breeding schemes will include heritable resilience biomarkers to overcome the foreseeable adverse impacts of climate change characterized by increasing temperatures, the expansion into new areas of invasive parasites and possibly the degradation of forage production and quality. An increasingly number of studies have addressed the effect of admixture and introgression in cattle adaptation to new environmental challengesOwing to its three-way admixture and its long-term isolation under extreme environmental conditions, the genome of the Creole cattle from Guadeloupe offers a unique opportunity to study admixture-enabled adaptation.13. The results from these studies point to candidate regions linked to various molecular processes underlying tropical adaptation including slick hair coat, DNA repair processes6, immune response and adaptation to warm conditions in male and female reproductive functions13.There are only a few studies that aimed at detecting selection signatures in Creole cattle7. To expand our understanding of the genomic architecture of local adaptation in this population, we leverage whole-genome sequence data from 23 GUA animals and genomes of 99 cattle individuals from various origins. Our objective was to use high-resolution genomic data and consistency of signals among different methods based on the excess of haplotype homozygosity, differences in allele frequencies and excess ⁄ deficiency of local ancestry to identify new, strong candidate regions under selection in the GUA genome.A previous study provided a first insight into footprints of selection in GUA cattle using the Illumina BovineSNP50 chip assayBos Taurus reference genome (ARS-UCD1.2) with an average alignment rate of 95.7% (ranging between 94.93 and 96.51%) and an average depth of 16.35   which is consistent with their three-way admixture. African taurine has the lowest diversity (median = 6.28 × 10−4)  Fig. ” section−4) Fig. a. Additi−4) Fig. b.Figure A total of 12 ROH islands located on chromosomes 1, 5, 6, 7, 10, 11, 12 and 19 were identified in the GUA genome. Among the detected ROH islands, the strongest pattern was observed on BTA11 , BTA05  and BTA12  with an overlapping ROH region present in 47%, 41% and 41% of the samples, respectively  grouped individuals in clusters according to their populations of origin Fig. b. The fings Fig. c. When Kngs Fig. . Likewisngs Fig. .Pairwise Fst values obtained with Genepop corroborated the genetic proximity within AFI populations (0.016 < Fst < 0.044) and between these latter and GUA (0.049 < Fst < 0.062) while Fst estimates between GUA and AMASI breeds were almost two times greater (Fst > 0.1). Moderate values of Fst are observed between GUA and EUT breeds with a South European origin  (0.0691 < Fst < 0.0799)  were in clade with the Asian zebu (BRA and SAHW). TreeMix shows GUA strongly introgressed with the African taurine Muturu (MUTU) and the East African zebu, Barka. A third edge originating more basally in the phylogenetic network was also placed towards GUA. High levels of admixture are shown between African taurine (MUTU and Ndama) and African zebu (BOR and BUT)  based on the decay of haplotype homozygosity as a function of recombination distance. Candidate regions were defined by groups of at least five outlier SNPs exceeding the significance threshold of − log10  = 6. The rationale is that selective sweeps tend to produce clusters of extreme scores across the sweep region, while under a neutral model, extreme scores are scattered more uniformly15. Rsb and Cross-population Extended Haplotype Homozygosity (XP-EHH) statistics were computed at each SNP. Haplotypes estimated in each population were pooled, for each autosome, according to their group of origin . In total, 14, 102 and 44 haplotypes were thus considered representative of AFT, EUT and IND ancestries, respectively. Rsb detected 6, 11 and 8 regions putatively under selection for GUA/AFT, GUA/EUT and GUA/IND comparisons, respectively  > 11) fell within GIMAP genes. On chromosome 5 the highest signal fell 16 Kb upstream NKG2-A/NKG2-B type II integral membrane protein. Overall, 17 candidate regions were identified by at least two EHH-based tests , BTA05 (at position: 47–47.5 Mb), BTA06 (at position: 69–69.5 Mb), BTA12 (at position: 29–30 Mb) and BTA13 (at position: 63.5–64 Mb) were identified in the EUT versus GUA comparison. The first four candidate regions overlapped with areas harbouring a sudden increase in indicine allele dosage  located 250 Kb upstream the highest signal. In candidate region on chromosome 12, the three SNPs of highest significance  < 10.4) are less than 80 Kb upstream of relaxin family peptide receptor 2 (RXFP2). On chromosome 13, the cluster of the four most significant outlier SNPs is less than 100 Kb upstream the ASIP gene.We also tested for signals of selection using the composite likelihood ratio implemented in SweeD software to detect patterns of site frequency spectrum in the GUA population. We found that all five candidate regions had the highest CLR values in their respective chromosomes  similarly reported a high proportion of African mtDNA haplotypes in twenty-five GUA individuals4. Interestingly, the aforementioned study included Creole samples from Antigua and St. Lucia, two Guadeloupe’s neighbouring regions and found that mtDNA pools of these samples are predominantly European, with very low African mtDNA admixture proportions. Moreover, when using microsatellite data, the authors of the study reported that the Guadeloupe cattle was the only population to exhibit West African–specific alleles4. This further confirms the uniqueness of this population with respect to the other Creole breeds even those found in neighbouring regions and which are expected to have a similar genetic history.In this paper, we present a characterization of the first complete genome sequence of the Creole cattle from Guadeloupe. In line with previous reportseds Fig. c leadingeds Fig. . More paeds Fig. b,c. Prev19 and is recognizable in our phylogenetic network where migration edges are placed between African taurine (MUTU and Ndama) and African zebu (BOR and BUT)  around 1000 years ago, reaching the Lake Chad Basin 500 years later20. Clearly, estimating with high accuracy the origin of African indicine ancestry in the GUA genome would require using additional cattle populations from western Africa and the Sahel region.The lower genetic differentiation and a closer position in PCA analysis between GUA and East African zebu compared to Indian zebu and the migration edge placed by TreeMix between GUA and the East African Zebu Barka, all suggest that the indicine ancestry in the GUA genome has an African origin. African indicine ancestry in the GUA genome could be inherited via west African taurine which also carries an indicine component in their genome stemming from past admixture events between migrating populations of East African zebu and local taurine cattle in West Africa. This admixture was previously reported7.To identify footprints of selection in the genome of GUA cattle, we used pools of individuals haplotypes belonging to contemporary populations sampled from geographical locations remote from each other, as proxies for their assumed ancestral counterparts. In this regard, EUT ancestry was represented by breeds from France, Spain as well as Criollo populations which were shown to be genetically close to the former breeds  reflecting primarily ongoing selection, Rsb and XP-EHH, having the most power to detect completed selection after fixation of the advantageous allele22.As a first step, we applied two types of complementary EHH-based statistics, the integrated Haplotype Homozygosity Score . Infectious pathogens are among the strongest selective forces that shape the genome of several mammalian species such as human26.Two candidate regions on chromosomes 4 (position: 113–113.5 Mb) and 5 (position: 99–99.5 Mb) were jointly identified by the two types of approaches. Additionally, we observe that the candidate region on chromosome 4 is also under selection in AFT since it has a negative 27. Limiting the number of spurious signals that can arise owing to various confounding factors such as the marker discovery process and/or population demographics is the main challenge in genome-wide scans aiming at the detection of selective sweeps. In the present study every attempt has been made to reduce the number of false-positive signals while focusing on candidate regions under selection in the GUA genome. First, the use of whole genome sequencing should reduce SNP ascertainment bias afflicting commercial genotyping arrays. Avoiding SNP ascertainment bias is critical for accurate population genetic analyses because levels of variability, distribution of allele frequencies, and levels of linkage disequilibrium will all be strongly affected by such ascertainment schemes29. Second, in our EHH-based tests, we relied on consistency of signals over regions, that is taking clustering of highly significative outliers as evidence for selection. Third, and most importantly, we considered that selection signals that are consistently supported across different statistical tests are less likely to be false-positives. Indeed, although these tests are designed to detect selective sweeps that vary in terms of type, age and strength of selection events, selection signals supported across different methodologies can increase power, reduce sensitivity to confounding factors (which are unlikely to affect different methods in a similar manner) and increase precision of the detection of the selective sweep30. Here, we used various methods based on excess of haplotype homozygosity, deformation of the allele frequency spectrum, excess of differentiation in allelic frequencies between the GUA population and proxies of its ancestral populations and reduction in genetic diversity around the selected region to identify reliable selection signatures in the genome of GUA. Fourth, we relied on the identification of excess/deficiency of local ancestry in the GUA genome to further confirm selection signals revealed by the various tests we used. The rationale is that, under a recent admixture scenario followed by a strong selection, we expect a parallel increase in local ancestry proportions in the regions surrounding the beneficial variants. We found evidence of congruent signals between methods for five candidate regions on chromosomes 2, 5, 6, 12 and 13, all of them identified in the GUA versus EUT comparison. These five regions exhibit a sudden increase in indicine ancestry , we detected 278 regions of which 13 reported in Gautier and Naves 2011 (out of 16 candidate regions)  gene, previously identified by Gautier & Naves 2011. RXFP2 is a gene with a pleiotropic effect. It affects both inguinoscrotal testis descent39 and horn size in wild bighorn40 and domestic sheep42. The use of horns is likely part of a thermoregulatory mechanism in several pecoran species. Indeed, since the core of the horn is part of the sinus, horns may contribute to nasal heat exchange, a mechanism that considerably reduces water loss through cooling of the air during exhalation43. Another explanation to the selection pressure exerted on RXFP2 is that Creole bulls were traditionally used for sugarcane cart pulling and cattle cart race competition, with a yoke attached to the horns. This has probably led to the development of a stronger horn base7. Creole cattle have been historically selected for draught works in sugarcane plantation. They are known to have a better endurance in long-term effort than crossbreed or exotic breeds44. Accordingly, we found that the strongest evidence of selective pressure on chromosomes 2 co-localizes with EIF4E2. In human cells under hypoxia, eIF4E2 plays a fundamental role in protein synthesis. This gene substitutes its homologue, eIF4E and forms a complex with the oxygen-regulated hypoxia-inducible factor 2α45. EIF4E2 was among the candidate genes that were shown to be under positive selection in Fu Zhong buffalo characterized by strong muscles and able to endure the strength to pull a plough through muddy rice paddies46. We also identified another gene, OCIAD1, as a good candidate for mitochondrial adaptation during exercise. OCIAD1 lies within a 3-Mb region which is among the top 1% regions with the highest indicine ancestry and is located in the vicinity of our candidate region on BTA06. The region encompassing this gene is detected by Rsb and XP-EHH tests when relaxing the p value threshold to 10−5. Almost ~ 11% of the 220 SNPs contained in this region (66.5–68 Mb) exceed the significance threshold (data not shown). Importantly, the two variants with the highest p value in this region are located 16 Kb upstream OCIAD1 which encodes a mitochondrial inner membrane protein that regulates mitochondrial Complex III assembly in cells47. The latter is among the complexes that play a key role in electron transport and proton gradient production, precisely across the inner mitochondrial membrane48. Proton gradient provides the energy necessary for the production of ATP whose demand increases in the muscle with exercise intensity49. Selection for draught traits in the GUA population thus seems to have provoked responses in a diversity of pathways involving at least EIF4E2, OCIAD1 and RXFP2 genes. Such selective pressure promoted the fixation of beneficial alleles from an indicine origin that allowed GUA individuals to cope with withstanding hours of high intensities of physical activity.Our results demonstrate that the Creole cattle from Guadeloupe which are usually exposed to long periods of direct, intense sunlight either during grazing or during ploughing, possess signatures of putative selection within or around genes associated with thermo-tolerance. Aside from In this study, we have generated for the first time a catalogue of genetic variants found in the Creole cattle from Guadeloupe. We were able to show that GUA adaptation to local environment occurred mainly through its indicine component. We also demonstrate that pathogenic environment, thermotolerance and physical stamina are important drivers of local adaptation in Creole cattle. Overall, our results provide clues for understanding the adaptive admixture in the Creole cattle from Guadeloupe thus contributing to the emerging picture of the genes and pathways associated with traits resilience in livestock species. Our study may represent a starting point for a targeted and sustainable genetic breeding improvement of Creole cattle.Blood collection was done according to good practices recommended for identification of sires for paternity checking in France. Semen was collected for the main purpose of insemination, according to relevant technical guidelines for semen collection and preparation. This study was approved by the scientific committee of the Metaprogramme SELGEN of INRA, which afforded a grant to the project TROCADERO. The study is in accordance with ARRIVE guidelines.Twenty-three Creole bulls representative of the INRA nucleus in Guadeloupe were selected for the purpose of this study. INRA experimental nucleus was created in 1980 from local animals chosen according to their phenotype. New local sires are regularly introduced in the nucleus as a part of a conservation program aiming to avoid loss of variation in the GUA population. Ten out of the twenty-three individuals of the present study are sons of founder sires of the experimental flock while the remaining thirteen animals are unrelated sires  chosen from the local stock of Guadeloupe before introduction to the INRA nucleus. The animals selected for the purpose of this study are among the most frequently used in artificial insemination.Genomic DNA was extracted from whole-blood and semen samples collected between 1995 and 2015. Four Colombian individuals belonging to the IMAGE project  were also included in the study. Paired-end libraries with insert size of 500 bp were constructed for each individual and sequenced using the HiSeq 3000 platform (Illumina) in the Genome et Transcriptome (GeT) GénoToul platform , following the manufacturer’s protocol.50. Quality control of raw sequence reads was performed using the fastQC software v.0.11.7 (http://www.bioinformatics.bbsrc.ac.uk/projects/fastqc/). Trimmomatic-0.3651 was used to remove Illumina adapter sequences, low-quality bases and artefact sequences. Filtered sequences were then mapped against the bovine reference genome (ARS-UCD1.2) using the Burrows-Wheeler Alignment tool (bwa mem v.0.7.17)52 with default parameters. The resulting SAM files were then converted to BAM format, sorted, and indexed using SAMtools53. Potential PCR duplicates were removed using the MarkDuplicates tool from Picard version 1.88 (http://broadinstitute.github.io/picard). Only properly reads with a mapping quality of at least 30 were kept. Prior to variant discovery, local realignment was performed using two GATK  version-3.8-1-0-gf15c1c3ef modules, RealignerTargetCreator and IndelRealigner. GVCF files were then created for each sample using the GATK HaplotypeCaller module. Single nucleotide polymorphisms (SNPs) and small insertions and deletions (indels) were subsequently called for all samples using the GATK GenotypeGVCFs tool. VCFtools v.0.1.17 software was used to filter out indels, multiallelic SNPs and variants that (1) displayed a minor allele frequency (MAF) < 0.1; (2) have missing genotype rates > 0.1; (3) did not pass Hardy–Weinberg equilibrium (HWE) test (p < 0.01) and (4) have a quality score (– minQ option) below 100. The selected variants were subsequently annotated using the SnpEff annotation software54.Genotype data were generated following the 1000 Bull Genomes Project Run 8 guidelinep value HWE = 0.01 and minQ = 100) to build these two databases which resulted in 16,360,962 and 8,955,346 high-quality SNPs for the public and the 1000 Bull Genomes genotyping data, respectively. All three databases were combined into a single one containing 5,316,956 common snps. Nucleotide diversity (Π) at a whole-genome scale was estimated in sliding windows of 1 Mb using VCFtools considering the following breed groupings: AFI (N = 11) and AFT (N = 7) and the each of the following breeds separately: Aubrac , Charolais , Holstein , Limousin , Montbeliarde . In Π computation, we selected 10 GUA individuals among the least related. This was done to have sample groups with similar size (for a matter of comparison).We downloaded publicly available genomes of of 41 individuals including 12 AFI, 10 AFT, 7 Australian-American indicine (AMI), 4 Asian indicine (ASI), 4 European taurine breeds from Spain (IBER) and 4 LIMO individuals (representative of Criollo (CRIO) cattle)  was estimated using Genepop 4.6 software59 for populations represented by more than one animal. The four Spanish individuals were considered as one population as well as the four Colombian animals. Next, we performed local ancestry assignment across the GUA genome using the Efficient Local Ancestry Inference (ELAI) algorithm60 under a three-way admixture model using AMASI and AFI populations as proxies for indicine ancestry, Muturu and Ndama as proxies for AFT ancestry, the French and the Spanish breeds as proxies for EUT ancestry. ELAI uses a two-layer hidden Markov model to detect the structure of haplotypes for unrelated individuals. The algorithm models two scales of linkage disequilibrium (one within a group of haplotypes and one between groups) and provides a map, for each admixed individual, showing the probability, for each SNP, to descend from each one of the ancestral populations. ELAI analysis was conducted across 19 GUA genomes by setting the parameters -mg (number of generations) to 70, -s (EM steps) to 30, -C (upper clusters) to 3, and -c (lower clusters) to 15.We performed a principle component analysis (PCA) using the adegenet R package61. To run TreeMix, we considered the 17 populations with more than two individuals. We built a maximum likelihood tree using blocks of 30,000 SNPs with no migration events allowed. Then, we built a phylogenetic tree of these populations and started adding migration events (modelled as edges) sequentially to the phylogenetic model. The migration edges were added until 99.79% of the variance in ancestry between populations was explained by the model.The patterns of population splits and mixtures were inferred using TreeMixRuns of homozygosity (ROHs) were identified in sliding windows of 100 SNPs using PLINK and the 1,064,342 SNPs that passed quality control filtering. ROH were detected within the following five breed groupings: Creole cattle from Guadeloupe (GUA), African Taurine (AFT) : Muturu and Ndama, Africain Indicine (AFI) : BOR, BUT and BARK, European Taurine (EUT) : IBER (represented by the four Spanish breeds), AUB, CHA, BAQ, LIM, MON, HOL, LIMO, COL (represented by the four Colombian breeds) and American-Australian and Asian Indicine (AMASI) : BRA, GIR, NEL, HAR and SAHW. The following parameters were used to define a ROH: (1) homozyg-snp (minimum number of SNPs that a ROH is required to have): 100. (2) homozyg-density (required minimum density to consider a ROH): 50. (3) homozyg-gap (length in Kb between two SNPs in order to be considered in two different segments): 1000 (4) homozyg-window-het : 3 (5) homozyg-window-missing : 5. The –homozyg-group option implemented in PLINK was used to assess ROH islands shared among GUA individuals. These were defined as the homozygous segments shared by at least 30% of the samples.iHS)15, Rsb22 and cross population extended haplotype homozygosity (XP-EHH)21 scans were performed using the rehh package62. In iHS computation, the information on the ancestral and derived allele state is needed for each SNP because this statistic is based on the ratio of the extended haplotype homozygosity (EHH) associated to each allele. In our analysis, the ancestral allele was inferred as the most common allele within our dataset. iHS scores for each SNP were transformed into two-sided p values: piHS = − log10[1 − 2|Φ(iHS) − 0.5|]. Rsb and XP-EHH analyses were performed for each of the three pairwise comparisons: GUA versus AFT, GUA versus EUT  and GUA versus IND (AMASI and AFI populations). Haplotype phasing was performed using fastPHASE 1.463. Since fastPHASE is based on haplotype clusters, whose size should be set a priori, we used the toolkit implemented in imputeqc R package64 to estimate the optimal number of haplotype clusters (K) needed for haplotype phasing. Imputeqc package has been designed to assess the imputation quality and/or to choose the model parameters for imputation. In the present study, we found that K = 20 provided the best imputation quality (for 5% of masked data). Therefore, we used this value to run fastPHASE. Considering that Rsb and XP-EHH values are normally distributed, a Z-test was applied to identify significant SNPs under selection. Two-sided p values were derived as pRsb = − log10[1 − 2|Φ(Rsb) − 0.5|] and pXP-EHH = − log10[1 − 2|Φ(XP-EHH) − 0.5|] where Φ (x) represents the Gaussian cumulative distribution function. For all three EHH-based tests, the maximum allowed gap between two SNPs was set to 500 Kb. We used sliding nonoverlapping 500-Kb windows to perform selection signature detection. A window is classified as putatively under selection when it contains at least 5 markers exceeding the significance threshold of − log10  = 6. Positive XP-EHH and Rsb values indicate longer haplotypes in the target population (i.e. GUA) therefore suggesting that selection occurred in the GUA population.Prior to selection signature analysis, we performed a more stringent LD-based pruning with the ‘-indep-pairwise 20 4 0.4’ option of PLINK which resulted in 433,408 SNPs. Integrated haplotype score  in nonoverlapping 500-kb windows along the chromosomes containing the relevant regions. The software detects Site Frequency Spectrum (SFS) patterns generated by complete selective sweeps.Regions putatively under selection in the GUA genome, identified by at least two EHH-based tests and experiencing a sudden increase in one of the three ancestries of GUA compared to the average level on their respective chromosomes were considered as relevant. We employed additional approaches to further confirm these relevant candidate regions. First, Fst and nucleotide diversity were calculated for nonoverlapping 50-Kb windows across the genome using VCFtools. Highly differentiated windows with at least 4 SNPs between GUA and each of its three ancestries were identified. We checked if our candidate regions were among the top 1% windows and if these regions present specific patterns of nucleotide diversity compared to the neighboring regions. Next, we used SweeD v4.0.0 softwareWe collected information through a literature search to discuss the biological implications of our findings with regard to the candidate genes located in the relevant genomic regions known to be involved in phenotypic variation of adaptive traits.Supplementary Information.


Ne) was estimated using SMC++. The genetic characteristics of PRS were analyzed by integrated haplotype score (iHS) and fixation index (FST). The result showed that r2 of PRS was 0.233 ± 0.280 in the range of 0–10 Kb and decreased with increasing distances. SMC++ tested that the Ne of PRS remained at 236.99 in recent generations. 184 genes were screened out under iHS 1% threshold, and 1148 genes were screened out with FST under the 5% threshold, and 29 genes were obtained from the intersection of the two gene sets. In this study, the genetic characteristics of PRS and QR were compared by ovine genome chip, and the related excellent genes were searched, providing reference for the protection of sheep germplasm resources and molecular breeding in a desert environment.Extreme environmental conditions are a major challenge for livestock production. Changes in climate conditions, especially those that lead to extreme weather, can reduce livestock production. The screening of genes and molecular markers is of great significance to explore the genetic mechanism of sheep prolificacy traits in Taklimakan Desert environment. We selected healthy adult Pishan Red Sheep (PRS) and Qira Black Sheep (QR) which live in Taklimakan Desert environment, collected blood from jugular vein, extracted DNA, and prepared Illumina Ovine SNP50 chip. For PRS, linkage disequilibrium (LD) was calculated using the ovine SNP50 Beadchip and the effective population size ( Sheep is one of the earliest domesticated animals in the world, and also one of the most successful animals domesticated by human beings in the Neolithic age. After long-term domestication and different environments, sheep have great changes in morphology, physiology and behavior. Pishan Red sheep (PRS) living in the Taklimakan Desert is characterized by perennial estrus and multiple fetuses after long-term selection by nature and people. In addition to its high-quality production traits, PRS is also a rare breed of sheep because its origin is on the southern edge of the Taklimakan Desert and north of the Karakoram Mountains . Pishan Ne)  can improve the accuracy of genomic association analysis and predict marker regions . LD decaNe) . Ne and pulation . Therefopulation , pigs  is used to measure the degree of population differentiation, indicating that there are obvious allele frequency differences between populations  under relevant survival background as research objects. Genetic basis of PRS was analyzed based on LD and This work was conducted in accordance with the specifications of the Ethics Committee of Tarim University of Science and Technology (SYXK 2020-009).33 PRS (polyembryony) and 40 QR (singleton pregnancy) were randomly selected from Pishan County and Cele County in Hetian region and all of them were healthy adult sheep with no genetic relationship. Blood samples were collected from the jugular vein and DNA was extracted with a DNA kit . The samples were sent to Beijing Compass Agritechnology Co., Ltd. to prepare the Illumina Ovine SNP50 Beadchip (The number of SNPs in this chip is 50 k). The validation samples were 130 PRS (first lambing) from Pishan Farm, with the same feeding conditions, 1.5–2.5 years old, no relationship.p values Genome Studio software was used to process the preliminary data results and obtain the VCF files. Plink  softwarer2 is more capable of objectively reflecting the LD between different loci, it was adopted in this study as the LD measurement standard. The LD values ranged from 0 to 1. As the LD level increased with the value of r2, the linkage degree increased. The calculation formula of r2 is as follows (r2 mean) of alleles was calculated to measure the level of linkage disequilibrium (LD) using PopLDdecay V3.41 . The VCF2Dis v1.09 (https://github.com/BGI-shenzhen/VCF2Dis) was used to calculate the P distance matrix, and then the NJ-tree was constructed by ATGC:FastME (http://www.atgc-montpellier.fr/fastme) program. Genetic admixture calculations were performed using Admixture  using MingPCACluster  and OMIM database (http://www.ncbi.nlm.nih.gov/omim). The g:Profiler (https://biit.cs.ut.ee/gprofiler/gost) was used for autosomal enrichment of candidate genes for GO and Reactome/KEGG pathway analysis.The iHS results and FecB locus of the BMPR1B gene in 130 PRS was amplified by PCR according to the primers shown in The Genotypic quality control was conducted on the SNPs of the 33 PRS and 40 QR used in the experiment. After the unqualified SNPs were removed, there were 49,219 informative SNPs in the PRS and QR population.r2 decreased with increasing physical distance , the difference was 0.082, much larger than the average r2 value between other adjacent distance regions. When the distance increased to 50–100 Kb, the r2 value was lower than 0.1, indicating that the LD was weak.When LD was calculated, the distance between markers was set in the 0–1 Mb  autosomal range . The avedistance . When thNe of PRS were estimated .The t window , and a tt window . A totalt window , scuh asABCA4, ARL4C, and PARP14 can affect the function of ion channels. Genes SOX2, DAB1, and COL5A2 regulate cell differentiation. 29 genes were obtained by the intersection of the results of FST and IHS, and after pathway enrichment, these genes were found to be related to GnRH signalingpathway, Ovarian steroidogenesis and Estrogen signaling pathway . The number of lambs of the B+ genotype was significantly higher than that of the ++ genotype (p < 0.05). It was shown in the χ2 test that the PRS reached Hardy-Weinberg equilibrium at the FecB locus.After 1.5% agarose gel electrophoresis, the PCR products were found to conform to the expected size, indicating that the target fragment was successfully amplified . The seqThe Pishan Red sheep is a newly discovered local sheep group known for its stress resistance, perennial estrus, and high fecundity. Understanding the breed characteristics and evolutionary history of PRS will help to further strengthen the conservation and utilization of its genetic resources. PCA, N-J tree and Admixture suggest that PRS and QR could be subdivided into two genetic clusters, and have similar ancestral components.r2 we calculated for PRS was close to that of other sheep breeds and species. In Iranian Zandi sheep, the average r2 for the pairwise space of 0–10 Kb was 0.26 , consistent with previous reports in sheep    . Moreoveng type) . As seenNe of 236.99 of PRS 50 generations ago was similar to that of Chinese Merino sheep . In terms of immunity, HERC2 and USP10 can promote the activation of the ATR-CHK1 pathway, triggering cell cycle checkpoints  metabolism (R-MMU-2046105), ty acids , which ackpoints . PAALD iocytosis . KIF2A, cell DNA . GPRIN3 poptosis . In termem cells . EVC canogenesis . GABRB1 lligence .TLR5 can effectively alleviate the stimulation caused by radiation  is a large family of paracrine cells that can regulate follicular development and oocyte maturation. lization . FGF10 w ability . FGF10 cst stage . In embrst cells . FGF10 collicles , which i quality .HAS1, HAS2, and HAS3). HAS2 is so critical to development that the HAS2-HA system is considered an essential HAS-HA system. HAS2 is responsible for the rapid hyaluronic acid synthesis in cumulus-oocyte complexes and granulosa cells. In the dominant follicles of mammals, most of the hyaluronic acid is secreted by cumulus cells and is also present in the follicular fluid. HAS2 plays a vital physiological role in oocyte maturation, ovulation, in vivo fertilization, and early embryonic development , also called hyaluronate or hyaluronan, is an essential extracellular matrix component widely available in various mammalian tissues . HA is selopment . C11orf7lization . Progest pathway . These gFecB gene is the most studied gene and can significantly affect the ovulation number and lambing number of sheep breeds. The B+ genotype exists among multiple sheep breeds in Xinjiang, China, including Duolang and Hotan sheep. The number of lambs of the B+ genotype was significantly higher than that of the ++ genotype. We detected FecB in 130 leather-red sheep and found three genotypes: BB, B+, and ++. The average number of lambs born in the BB genotype was the highest, followed by the B+ and ++ genotypes, indicating that the FecB gene is an effective gene for improving the fecality of PRS.The number of lambs is a complex character affected by many factors, among which heredity is the main factor. The Ne were at a relatively low level, suggesting that we should take reasonable protection measures to increase the PRS population. Genomic selection signal analysis and population validation showed that FecB could be used as a molecular breeding marker for multiple fetal lines of PRS in desert environments.In the extreme environment of the desert, PRS has formed the characteristics of perennial estrus, multiple pregnancies, and adequate resistance to stress. The LD decay rate of the PRS was faster, and LD and the