No SNPs were found to be in common across PGP traits. The number of favorable alleles possessed by each inbred line for PGP35°C, PGP45°C, and the PGP ratio ranged between 4 and 10, 3–13 and 5–13, respectively. In contrast, the number of negative alleles for these traits ranged between 2 and 8, 3–13 and 3–13, respectively. Genetic mapping of yield  and flowering time  in 275 lines revealed five common SNPs: three shared for AWP−1 between normal and heat stress conditions, one for ASI between conditions, and one SNP, CM007648.1-86615409, was associated with both ASI and AWP−1. Variety selection can be performed based on these favorable alleles for various traits. These marker trait associations identified in the diversity panel can be utilized in breeding programs to improve heat stress tolerance in maize.Global environmental changes with more extreme episodes of heat waves are major threats to agricultural productivity. Heat stress in spring affects the reproductive stage of maize, resulting in tassel blast, pollen abortion, poor pollination, reduced seed set, barren ears and ultimately yield loss. As an aneamophelous crop, maize has a propensity for pollen abortion under heat stress conditions. To overcome the existing challenges of heat stress and pollen abortion, this study utilized a broad genetic base of maize germplasm to identify superior alleles to be utilized in breeding programs. A panel of 375 inbred lines was morpho-physiologically screened under normal and heat stress conditions in two locations across two consecutive planting seasons, 2017 and 2018. The exposure of pollen to high temperature showed drastic decline in pollen germination percentage. The average pollen germination percentage (PGP) at 35 and 45°C was 40.3% and 9.7%, respectively, an average decline of 30.6%. A subset of 275 inbred lines were sequenced using tunable genotyping by sequencing, resulting in 170,098 single nucleotide polymorphisms (SNPs) after filtration. Genome wide association of PGP in a subset of 122 inbred lines resulted in ten SNPs associated with PGP35°C ( Global maize production exceeds 1,108 million tons, making it one of the most widely grown cereal crops around the world . Maize pMaize plants are particularly sensitive to heat stress at the flowering stage, causing more yield reduction than during the grain filling stage. . The repThe genome wide association study (GWAS) has emerged as a powerful approach for identifying genes underlying complex morphological traits , in whicThe objectives of this study were: 1) evaluation of a maize diversity panel consisting of exotic and indigenous maize inbred lines for heat stress tolerance, considering pollen viability, yield, and ASI as the target traits, and 2) identification of marker-trait associations and quantification of their effect on the traits.A maize diversity panel composed of 375 diverse inbred lines was used for this study. The diversity panel includes 103 exotic lines, 283 indigenous lines, and three check cultivars: Haq Nawaz Gold, FH-1898, and CML161. The diversity panel was formulated by collection of diverse maize genotypes from exotic sources  and from plant genetic resources (PGRI), NARC, Pakistan. The details of the diversity panel are given in Two different sowing dates were used so that the flowering periods would be synchronized to both a normal temperature and a heat stress temperature in each year. Significant temperature differences at flowering time were observed in normal and stressed sowing trials. The normal sowing trials flowered during the end of May, and temperatures at the flowering stage (VT) were in the range of 29–35°C. The stressed sowing trials flowered during early to mid-July, and the temperatures at VT stage were in the range of 38–45°C.Seeds were hand sown in single row plots of length 4 m using a dibbler at a depth of 3 cm. Row to row distance was maintained at 75 cm while plant to plant distance was maintained at 25 cm such that each plot contained 16 plants, and fertilizer was applied at the rate of 200:100:100 NPK. Manual thinning and weeding operations were performed to retain optimum plant numbers and weed control in the experiments. The same experimental plots were used for both years in both locations.−1) were collected from 5 plants for each of the 375 varieties. At tasseling (VT) stage, DTA, DTS and ASI were recorded, while yield was measured at the R6 stage. Assessment of pollen germination was carried out on a subset of 122 lines using pollen germination media (PGM) proposed by Phenotypic data of various agronomic traits were collected according to published maize descriptors . To asse2G and phenotypic variance σ2P, and Broad-sense heritability was calculated using formula H2 = σ2G/σ2P. Field experiment data was analyzed as a randomized design in R software  . Mean sqsoftware .Zea mays AGPv4 reference genome after de-barcoding and trimming of reads. SNP calling was conducted using only those reads that aligned to a single location in the reference genome. Initially, nearly 2.7 million SNPs were identified, with a mean missing data rate per SNP site of 64%. From these, a high-quality set of 496,740 SNPs in which each marker was genotyped in at least 50% of the samples was generated and referred to hereafter as MCR50 SNPs. Each of these SNPs were supported on average by 20 tGBS reads per SNP per genotyped sample. Finally, imputation was performed on the MCR50 SNPs using BeagleV4.1 (Genotypic data of 275 maize accessions were generated by Freedom Markers from fresh tissue via tunable genotyping by sequencing  with theagleV4.1  with 50 agleV4.1 .Population structure and kinship matrices of the sets of 122 (for pollen traits) and 275 (for other traits) maize accessions were generated within the rMVP program  in R sofp-values for marker-trait associations were produced to assess model fit and select the appropriate number of principle components for each trait. Bonferroni corrections at 0.05 yielded a significance threshold of 2.94 × 10−7 . Because Bonferroni can be overly stringent due to linkage, all SNPs with p-values lower than 10−5 are reported here as potential associations as a hypothesis-generating approach.Phenotypic data of all accessions were checked for outliers, and all high-quality data was used for association studies. The FarmCPU algorithm  within t−1, DTA, DTS, and ASI was 37.5 g, 62.5, 64.6, and 2.9 days, respectively, which were significantly reduced to 35.5 g, 47.4, 50, and 2.4 days under heat stress , DTA (r = 0.49) and DTS (r = 0.14), but PGP at 45°C showed negative correlation with AWP−1 (r = −0.3), DTA (r = −0.07) and DTS (r = −0.1). On the other hand, DTA and DTS showed negative correlation with yield under heat stress conditions, at (r = −0.64) and (r = −0.76), respectively  with SNP CM007650.1-89641171 located on chromosome 1 shown in No common association of SNPs were found for the PGP traits under study. SNP CM007650.1-89641171 located on 89.64 MB position of chromosome 1 showed the highest (0.25) R−1 . Fourteen SNPs located on chromosomes 2 (4), 3 (1), 4 (3), 5 (1), 8 (4), and 10 (1) showed significant association with AWP−1 at NARC in 2018 on planting date 1. Similarly, 4 SNPs located on chromosomes 1 (1), 2 (1), and 10 (2), and 5 SNPs located on chromosomes 1 (1), 3 (1), 6 (2), and 8 (1) were found to be associated with AWP−1 at Peshawar in 2017 date 1 and 2018 date 1, respectively. Four SNPs located on chromosomes 1 (3) and 8 (1), and 9 SNPs located on chromosomes 1 (2), 3 (1), 4 (1), 6 (2), 8 (1), 9 (1), and 10 (1) showed association with AWP−1 at Peshawar in 2017 date 2 and 2018 date 2, respectively. Out of 59 SNPs, 18 were highly significant (p ≤ 10−6)  .p ≤ 10−6) , 67 SNPs were associated . Two SNP ≤ 10−6) .The number of favorable alleles for PGP traits in each inbred line was investigated. For PGP35°C, this number ranged between 6 and 95 favorable alleles for each inbred line . SimilarAgro-morphological screening showed that the diversity panel behaved differently under normal and heat stress conditions. The main trait under study was pollen viability, and as expected, it was adversely affected by heat stress. The pollen viability was estimated in terms of pollen germination percentage (PGP). At 35°C the mean value of PGP was 40.30% with minimum PGP 0% and maximum PGP 93.70%, which was significantly reduced by 9.70% mean value and 0 and 57% minimum and maximum PGP respectively at 45°C. This is due to the fact that pollen germination of maize is hindered above 38°C −1 was the key indicator of plant response to heat stress in terms of major economic return. The mean AWP−1 was 37.5 g under normal conditions which was reduced to 35.50 g under heat stress conditions. Another important observation was that many of the inbred lines in the diversity panel produced baren plants under heat stress conditions. This is due to the fact that even a small increase (1.5°C) in temperature has a very significant negative effect on crop yield  has a negative effect on light capture, harvest index, grain and biomass yield. At flowering, heat stress causes more yield reduction as compared to the grain filling stage .−1 with DTA (r = 0.96) and DTS (r = 0.52), and negative correlation with PGP 45°C (r = -0.3). DTA (r = 0.9) and DTS (r = 0.93) have high correlation with ASI under heat stress. PGP 35°C showed positive correlation with AWP−1 (r = 0.54), DTA (r = 0.49), and DTS (r = 0.14), and negative correlation with ASI (r = −0.09) under normal sowing conditions. The correlation analysis suggests that the traits under study might be influenced by the same genomic regions. Our studies are in coherence with previous studies (−1) than PGP under heat stress. It is interesting that the association of DTA and DTS with yield (AWP−1) reverses directions under normal and heat stress conditions, perhaps emphasizing the importance of developmental stage on the impact of extreme weather conditions.Broad-sense heritability estimates were moderate for traits under normal sowing trials, but were significantly reduced under heat stress conditions. This might be due to the fact that inbred lines were influenced by the adverse environment and affected the expression of traits. Our results were strongly in agreement with  studies . Further−5 as candidates for future studies. Though this portion of the experiment was conducted on a reduced subset of 122 diverse inbred lines, 29 putative SNPs were found to be associated with the target traits at this significance level. Several studies have reported the association of traits with SNPs in maize using GWAS analysis , and 35 under heat stress conditions (date 2). Most of the SNPs that were identified were unique to a specific location and year, once again emphasizing the role of the environment and highlighting the need for validation of significant loci prior to their application in a breeding program.GWAS of AWP−1 in more than one condition, validating our results. In each case, these SNPs were associated with AWP−1 at Peshawar in 2017 on both date 1 and 2:- SNP CM007647.1-19525844 on chromosome 1 at 19.5 MB- SNP CM007650.1-26720973 on chromosome 3 at 26.7 MB- SNP CM000786.4-148468397 on chromosome 10 at 148.5 MBIn this study, three SNPs were identified as associated with AWPThough these SNPs were specific to location and year, they significantly impacted yield in both the normal and heat stress planting dates, indicating an overall contribution to fitness in that environment as opposed to a mechanism of heat stress tolerance specifically.−1, most SNPs identified were associated with only one environment. However, one SNP, CM007647.1-258148529 on chromosome 1 at 258 MB was found to be commonly associated with ASI at Peshawar in 2018 at both sowing dates, validating its association with ASI.Association studies of ASI at two locations, years, and sowing dates identified a total of 67 SNPs distributed across nine chromosomes. Under normal sowing conditions, 30 MTAs were identified, while 37 SNPs showed significant association with ASI under heat stress conditions. Distribution of these traits across locations, years, and chromosomes are in Finally, one SNP, CM007648.1-86615409 on chromosome 2 at 86.6 MB was found to be associated with two different traits: ASI at Peshawar in 2018, and AWP-1 at NARC in 2017, both under heat stress conditions. This locus may be of interest to pursue in future studies or for breeding heat tolerant varieties, as it was validated across traits, locations, and years as significantly impacting both yield and ASI in heat stress conditions specifically.The results indicate that different regions on chromosomes are responsible for the expression of various traits under study. This might be due to a difference in gene regulatory mechanisms under heat stress conditions compared to normal conditions, or perhaps different subsets of a greater regulatory network become critical in different specific environments. It is also possible that a more powerful experiment  may have identified additional shared loci. Still, SNPs were identified as significantly associated with the traits of interest, and a subset were validated. Based on these associations, candidate genes can also be identified and investigated for their roles in stress signaling. In previous studies, 206 significant SNPs were found associated with 115 candidate genes for drought tolerance and related traits . Sixty-sTo understand the effect of combined favorable and unfavorable alleles on PGP35°C, PGP45°C, and PGP Ratio, the number of increasing effect alleles were investigated. Alleles corresponding to higher average PGP were considered favorable alleles, and those corresponding to lower average PGP were considered unfavorable alleles. The number of PGP 35°C increasing effect alleles ranged from 4 to 10, and the number of PGP 35°C decreasing effect alleles ranged between 2 and 8, Identification of maize genomic regions responsible for better crop performance under heat stress conditions is essential for the selection of inbred lines and development of heat tolerant hybrids. In this study, pollen viablility is considered as a major factor, reponsible for yield losses under heat stress conditions. Importantly, the exotic genotypes were not very adaptive, and the local germplasm showed resiliance aginst heat stress conditions. There was significant reduction in PGP from 40.30% at 35°C to 9.70% at 45°C. This reduction in PGP showed negative correlation with yield contributing traits as well. GWAS indicated 14 significant SNPs associated with PGP35°C, PGP45°C and PGP ratio. Further work in identification of candidate genes using these significant SNPs is required to fully elucidate the role of these genomic regions in heat stress tolerance.


Bemisia tabaci is a key pest of horticultural, fibre and ornamental crops, primarily as a vector of plant viruses. This whitefly is considered as a complex of morphologically indistinguishable species that differ in several biological traits. In Italy, the Mediterranean (MED) and Middle East–Asia Minor 1 (MEAM1) species are known to be present in southern regions as well as in Sicily and Sardinia, where they have been responsible for economically important yield losses to horticultural crops since the 1990s. Recent reports of infestations in some areas of central Italy prompted a reassessment of the species distribution in the country, and several sites have been inspected at different central and southern regions and in the main islands. The survey confirmed that B. tabaci is nowadays established in central Italy even at more northern latitudes than those noticed before, with MED that is clearly prevailing on MEAM1 species throughout the country. The extensive presence of B. tabaci in Italy causes new concerns for the growing number of horticultural and ornamental productive sites that are potentially endangered by whitefly-transmitted viruses. The prevalence of the MED species is even more worrying for its ability to rapidly develop insecticide resistances.Bemisia tabaci is a key pest of horticultural, fibre and ornamental crops worldwide, primarily as a vector of plant viruses. In Italy, B. tabaci has established since the 1980s–1990s in southern regions as well as in Sicily and Sardinia. Recent reports of infestations in some areas of central Italy prompted a new survey to assess the whitefly distribution in the country as well as to update the species and haplotype composition of the populations present in southern Italy and in the main islands. The survey confirmed that B. tabaci is nowadays established in central Italy even at more northern latitudes than those noticed before. Most of the specimens collected throughout the country belonged to the Mediterranean (MED) species. The MEDQ1 and Q2 haplogroups were prevailing in open-field and greenhouse cultivations, respectively, except in Sardinia where only Q1 specimens were found on a wide range of crops and weeds. Population genetics analyses showed that several MEDQ1 haplotypes currently occur in Italy and their distribution is unrelated to evident temporal and geographic trends, except for a new genetic variant which seems to have originated in Sardinia. The MED species is known to better adapt to insecticide treatments and high temperatures, and its northward spread in Italy may have been favoured by the intensive agricultural practices and steady increase in both winter and summer temperatures occurring in the last few decades. The extensive presence of B. tabaci in Italy proves that a strict surveillance for possible new outbreaks of whitefly-transmitted viruses should be addressed to a range of sites that are expanding northwards. Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is a global pest that is responsible for economically important losses to horticultural, fibre and ornamental crops worldwide. Both direct and indirect damages are ascribable to the sap-sucking behaviour of B. tabaci, such as a reduction in the plant vigour, the abundant excretion of honeydew that favours the development of sooty moulds, and the transmission of hundreds of plant viruses mostly belonging to the genus Begomovirus (family Geminiviridae) [viridae) ,2.B. tabaci is considered a complex of at least 40 morphologically indistinguishable species [cytochrome oxidase subunit 1 (COI) sequence variability [Nowadays,  species ,6,7,8,9.iability ,10,11, biability ,13,14, tiability ,16, inseiability ,18, invaiability ,20 and viability , with moiability . Most ofiability . Althougiability ,25. For iability ,18,26, wiability ,28,29. Tiability ,32,33,34The successful adaptation of MEAM1 and MED to environmental and farming conditions has likely been supported by their genetic plasticity. Indeed, high genetic variability has been found at the intra-specific level and led to the definition of several COI haplotypes . Within B. tabaci became an important agricultural pest since the 1990s mainly in association with disease outbreaks caused by two whitefly-transmitted begomoviruses, tomato yellow leaf curl virus (TYLCV) and tomato yellow leaf curl Sardinia virus (TYLCSV) [In Italy, (TYLCSV) ,49. Both(TYLCSV) ,50,51. M(TYLCSV) ,32,52,53(TYLCSV) . Along w(TYLCSV) , this co(TYLCSV) .B. tabaci in Italy has been for a long time restricted to the southern regions and the main islands Sicily and Sardinia. A recent study provided evidence of the establishment of whitefly populations also in central Italy, where the presence of B. tabaci was thought to be only occasional. Single and mixed populations of MED and MEAM1 were found in different horticultural areas of the Latium region, suggesting that the steady increase in the temperature which has occurred in the Mediterranean basin in the last decade may have favoured a northward spread of the species [B. tabaci in the nearby regions of central Italy that have similar climatic and cultural conditions as well as for the introduction in free areas of whitefly-transmitted viruses, specially the emergent begomovirus tomato leaf curl New Delhi virus (ToLCNDV). This study presents the results of a recent survey carried out in different regions of central Italy to assess the current distribution of B. tabaci in the country. The study also includes further samplings in southern Italy as well as in Sicily and Sardinia to update the species and haplotype composition of the whitefly populations in Italy.The presence of  species . This fiB. tabaci were collected at different localities in Tuscany, Marche, Latium and Molise regions in central Italy, in Campania and Calabria regions in southern Italy and in the main islands Sicily and Sardinia .Samples of Sardinia . The surB. tabaci collected at different sites on different host plants and at a different time. The DNA of two to ten B. tabaci specimens per collection sample was extracted and tested for the identification of the B. tabaci species and haplotypes.Each collection sample consisted of 5–50 individuals of B. tabaci using the Xpert directXtract Lysis Buffer . Each whitefly was ground in 50 µL of reaction mixture  and the DNA was extracted following the manufacturer’s instructions.The DNA was extracted from single individuals of B. tabaci cryptic species as well as the MED Q1 and Q2 haplogroups was carried out by means of the PCR-RFLP assay suggested by [2, 0.5 µM of each primer and 1 µL of DNA. The thermo-cycling conditions consisted of an initial denaturation cycle at 94 °C for 5 min, 35 cycles at 95 °C for 30 s, 45 °C for 45 s and 72 °C for 1 min and a final cycle at 72 °C for 10 min. The amplified DNA was analyzed by electrophoresis onto a 1% (w/v) agarose gel and then digested with the restriction enzyme ApoI according to the manufacturer’s instructions . The restriction fragments were separated by electrophoresis onto 2% (w/v) 1 × TBE agarose gels  at 70 V for 2 h and stained with ethidium bromide.The identification of ested by . The disested by . The PCR® Ultra-0.5 Centrifuge Filter Devices  and sequenced in both directions. The sequences were assembled using MEGA (version X) [MEAM1 and MED specimens representative of each sampling area were selected, and their COI amplicons were purified through Amiconrsion X)  and depoBemisia afer was used as an outgroup (GenBank accession number: GU220055).Phylogenetic analyses were conducted using MEGA. The COI sequences were aligned by MUSCLE together with sequences that have been chosen in GenBank to be representative of the worldwide MEAM1 and MED haplotypes. A maximum-likelihood (ML) consensus tree was generated from 1000 bootstrap replicates. The Tamura–Nei model with five gamma distribution categories (TN93 + G) was the best-fit model selected according to BIC and AIC criteria using Model Selection analysis as implemented by MEGA. The COI sequence of Fs) and Tajima’s (D) tests. The geographic structure of the MEDQ1 haplotypes was assessed by Median Joining networks (MJN) [The COI sequences of MED specimens were analysed in the DnaSP package v. 6.12.03  to estimks (MJN)  that werks (MJN) . The resks (MJN)  and Campks (MJN)  were incB. tabaci were collected in all the inspected localities in central and southern Italy as well as in the main islands  was also inspected, providing evidence of the presence of B. tabaci sequences worldwide . A possible structure of the MEDQ1 populations was inferred by grouping the sequences by region of origin in a haplotype network analysis. The 13 MEDQ1 haplotypes were arranged in a star-like network made of six main groups  that did not correspond to such high levels of nucleotide diversity per site (π = 0.004 ± 0.0004 SD), suggesting that this genetic variability is poorly fixed in the MEDQ1 populations. The neutrality test did not provide evidence of any demographic trends, since both Fu’s and Tajima’s tests had negative but not significant values . The result is still a star-like network with no evident evolutive genetic trends. The network is made of six main haplotype groups that overlapped the geographical groups B and shoBemisia tabaci has become a paradigm for both invasiveness and genetic variability in several countries worldwide, and in Italy as well. After the first introductions in the 1980s–1990s [B. tabaci rapidly established at a high density level in Sicily, Sardinia and southern Italy and then progressively moved northwards. The spread in new areas occurred together with a genetic change of B. tabaci populations that gradually shifted from MEAM1 to MED cryptic species. This study provides evidence that the whitefly is nowadays established in central Italy and that the MEAM1 species occurs at very low levels, confirming that in Italy the geographic and genetic status of B. tabaci are still changing.In agriculture, species invasions are among the drivers for changes in natural equilibria and have often been a major threat for crop production and management. The principal characteristic of an invading species is its ability to adapt rapidly to environmental changes, and such adaptation has often genetic bases. 0s–1990s ,62, popuB. tabaci in central Italy, after its first occurrence in Latium in 2016 [B. tabaci species under temperature changes have proved that global climate warming would expand the northern boundaries of the open-field populations in Europe [The main aim of the study was to extend the search for  in 2016 . The new in 2016 . Similar in 2016 ,56. The n Europe ,64.Both MEDQ1 and MEDQ2 mitochondrial variants were found in single or mixed populations in central and southern continental Italy. Most of the specimens collected in greenhouse crops belonged to MEDQ2 (87.6%), whereas MEDQ1 was prevailing in open-field cultivations and weeds (60%). These rates confirmed the previous observations conducted in southern Italy as well as in other Mediterranean countries that MEDQ2 is most adapted to protected conditions ,54. IndeS. melongena, Solanum nigrum and Brassica oleracea, that have been suggested as preferred hosts of MEDQ2 [A different scenario was observed in Sardinia, where only the MEDQ1 mitochondrial group was found. This suggests that the MED specimens previously found in Sardinia since the late 1990s together with MEAM1 ,50 belonof MEDQ2 ,54. We cAmong the four mitochondrial variants that have been identified within MED cryptic species so far, Q1 shows the highest level of genetic variability and includes several haplotypes worldwide ,35,39,66B. tabaci might also depend on the phenotype of inherited bacterial endosymbionts, which are known to enhance insecticide susceptibility [B. tabaci in this country.In general, the absence of both temporal and geographic genetic structures suggests that the MEDQ1 haplotypes in Italy have neutrally evolved in the last few years, and they have likely originated from multiple introductions independently occurring at different sites and times rather than from selection events. The absence of selection also implies that all the MEDQ1 haplotypes are potentially able to adapt to different conditions and would establish even further north as soon as the climatic conditions will become favourable. The invasiveness of a particular genotype of tibility , facilittibility  or confetibility . The endtibility . The furB. tabaci populations in Italy and states that this pest is now established at latitudes where it was previously unnoticed or thought to be only occasional. This extensive presence causes new concerns for a wider number of horticultural and ornamental productive sites that are potentially endangered by B. tabaci-transmitted viruses. The fact that MED is prevailing over MEAM1 species should alarm even more, not only for its higher insecticide resistance but also because it has been suggested that MED can be more efficient than MEAM1 in begomovirus transmission [B. tabaci populations have been established over the years [B. tabaci in regions of central Italy makes the introduction of begomoviruses also possible in further horticultural areas with important economic consequences. This has already occurred within the Latium region, where the ToLCNDV outbreaks, initially restricted to the Agro Pontino area, also occurred in the northern area of Agro Romano [B. tabaci populations had recently been noticed [B. tabaci-transmitted viruses should be addressed to a range of sites that are expanding northwards. In the same range, all the integrated management strategies should be adopted to keep B. tabaci under control even where the whitefly is not regarded as a harmful pest yet.This study defines a new map of the smission ,71. Currsmission ,73. Thussmission ,75. In the years ,50,56. Fo Romano  where B.


Meat quality is an important trait for pig-breeding programs aiming to meet consumers’ demands. Geneticists must improve meat quality based on their understanding of the underlying genetic mechanisms. Previous studies showed that most meat-quality indicators were low-to-moderate heritability traits; therefore, improving meat quality using conventional techniques remains a challenge. Here, we performed a genome-wide association study of meat-quality traits using the GeneSeek Porcine SNP50K BeadChip in 582 crossbred Duroc × (Landrace × Yorkshire) commercial pigs . Meat conductivity, marbling score, moisture, meat color, pH, and intramuscular fat (IMF) content were investigated. The genome-wide association study was performed using both fixed and random model Circulating Probability Unification (FarmCPU) and a mixed linear model (MLM) with the rMVP software. The genomic heritability of the studied traits ranged from 0.13 ± 0.07 to 0.55 ± 0.08 for conductivity and meat color, respectively. Thirty-two single-nucleotide polymorphisms (SNPs) were identified for meat quality in the crossbred pigs using both FarmCPU and MLM. Among the detected SNPs, five, nine, seven, four, six, and five were significantly associated with conductivity, IMF, marbling score, meat color, moisture, and pH, respectively. Several candidate genes for meat quality were identified in the detected genomic regions. These findings will contribute to the ongoing improvement of meat quality, meeting consumer demands and improving the economic outlook for the swine industry. Meat quality, a comprehensive indicator that includes moisture, intramuscular fat (IMF), pH, meat color, water-holding capacity, marbling, and tenderness , is amonRN, RKAG3, RYR1, PHKG1, MC4R, and insulin-like growth factor 2 (IGF2) are the major genes reported to affect meat-quality traits  associated with drip loss and pH (ubiquitin-specific peptidase 43 (USP43) associated with five meat-quality traits, including IMF, marbling, moisture, meat color, and color score  pigs [D (LY)] for their high feed-utilization rates and large eye muscle area, while meat quality is often neglected. Meat-quality traits are difficult to measure and cannot be assessed without slaughter, which greatly increases the difficulty and cost of breeding programs selecting for meat quality. In the present study, a GWAS was conducted using the Porcine SNP50 Genotyping BeadChip to identify QTLs for meat-quality traits in a crossbred D (LY) porcine population. This study was conducted to identify candidate genes and potential breeding markers and more deeply investigate the genetic architecture of meat-quality traits.All experimental animals were handled in accordance with the guidelines of the Institutional Animal Care and Use Committee of Foshan University. The Institutional Animal Care and Use Committee of Foshan University approved this study.We collected 582 D (LY) commercial pigs  from two farms (Fengda and Xinglin) of Guangxi Yangxiang Co., Ltd. These pigs were offspring of 45 boars and 96 sows. The pigs were reared under the same management conditions and similar environments, with automatic water and free food intake  of the United States. All meat-quality measurements were taken on the left side of the carcass. Meat color was measured as follows: (1) grayish white , (2) mild gray , (3) normal bright red, (4) slightly dark red , and (5) dark purple . Marbling score was assessed from 1 to 5. Both measurements were assessed subjectively via the longissimus muscle (LM) according to the NPPC. pH was measured via the LM using a Delta 320 pH meter  45 min after slaughter. IMF was determined from the thoracic lumbar LM via Soxhlet petroleum-ether extraction. Moisture was analyzed via the thoracic lumbar LM by routine oven drying. Conductivity was measured via the dorsal LM between the 13th and 14th ribs using the LF-STAR conductivity meter . Meat color, pH, marbling score, and conductivity were measured in triplicate for each sample, and the average of the three measurements was used.P > 10–4 were retained. All markers located on sex chromosomes or in unmapped regions were excluded. Missing genotypes were imputed using the Beagle software . DNA quality was assessed by measuring the light absorption ratios (A260/280 and A260/230) at ≥40 ng/μl. Genomic DNA was genotyped on the GeneSeek Porcine 50K SNP Beadchip . Quality control of the SNP data was conducted using PLINK software . Brieflysoftware . After qGenomic heritability of the meat-quality traits was calculated by dividing the genetic variance by the sum of the genetic and residual variances using the hiblup package . The mody is the vector of phenotypic values; b is a vector of fixed effects, including sex, farm of origin, and batch containing the year-season effect; and u represents breeding values. X and Z were design matrices for b and u, respectively; e represents the residual error vector. In this study, G is the genomic relationship matrix   and mixey is the vector of phenotypic values; T is a matrix of fixed effects, including sex, farm of origin, batch containing the year-season effect, and the top three principal components with the corresponding effect, wi; Pj is the genotype matrix of j pseudo quantitative trait nucleotides (QTNs), which was used as the fixed effects; and qj is the corresponding effect. mk is a vector of genotypes for the kth marker to be tested, and hk is the corresponding effect. e is the residual effect vector with distribution, where y is the vector of the phenotypic values of meat quality; u is the genetic effects defined by K is the kinship matrix defined by pseudo QTNs, and e is the residual effect vector.where The MLM can be written as follows:y is the vector of phenotypes of each D (LY) pig, a is the vector of the same fixed effects as those in the FarmCPU model, b is the vector of the SNP substitution effects, and c is the vector of random additive genetic effects with G is the genomic relationship matrix, and W, Z, and S are the incidence matrices for b, a, and c, respectively. Because the Bonferroni correction was too strict, the genome-wide significant thresholds were set as p < 1/N, where N was the number of SNPs tested in the analyses as per previous studies , meat color and moisture , and marbling score and IMF . Moisture was significantly negatively correlated with IMF , pH , and marbling score .Thirty-two SNPs were identified as significant for the traits investigated –6. AmongP-value, whether the SNP is located on or flanking the gene, and distance between the flanking genes and significant SNPs. Three significant SNPs were located within a 0.20-Mb segment (from 56.34 to 56.54 Mb) on SSC15. Among them, the two most significant, ALGA0085588 and ALGA0085585, were located within HERC2 and 93.3 kb upstream from HERC2, respectively, and were detected by both the MLM and FarmCPU. ALGA0085594 was also located within HERC2 via the FarmCPU method. These three significant SNPs on SSC15 were in a 534-kb haplotype block  were located within an intron of NMT1 on SSC12 and DENND2A and KDM7A on SSC18, respectively.The FarmCPU identified four significant SNPs associated with meat color ; the MLMNDFIP2.The FarmCPU identified two significant SNPs associated with moisture; the MLM identified no significant SNPs associated with moisture . Figure ETV5, a protein-coding gene.Five significant SNPs on SSC1 and SSC13 were significantly associated with pH . Among tMC4R, IGF2, ADRB3, and ATP1A2, heavily affected meat quality . Thus, the correlation between traits might explain the pleiotropic effects in some regions.Notably, in addition to duplicating the QTL for meat quality found in a previous GWAS, we identified four novel QTLs. These four novel QTLs were located on a 0.20-Mb region (56.34–56.54 Mb) significantly associated with conductivity on SSC15, a 0.39-Mb region (9.19–9.58 Mb) significantly associated with meat color on SSC18, a 0.04-Mb region (0.56–0.60 Mb) significantly associated with pH on SSC1, and a 4.25-Mb region (52.26–56.51 Mb) on SSC1. Additionally, a 2.59-Mb region (51.89–49.30 Mb) on SSC11 was identified as being significantly associated with marbling and moisture, containing the significant SNPs WU_10.2_11_53938211 at 49.30 Mb for marbling, and WU_10.2_11_56636318 at 51.89 Mb and ALGA0062389 at 51.83 Mb for moisture. The results showed that some chromosomal regions might have diverse effects on meat-quality traits. Moreover, similar to the results of HECT and RLD domain-containing E3 ubiquitin protein ligase 2 (HERC2). ALGA0085594 was also located within HERC2. Previous research found that ATP1A2 was strongly associated with muscle electrical conductivity because it encoded a subunit of the Na+/K+-ATPase responsible for maintaining an electrochemical gradient across the plasma membrane , another candidate gene for conductivity, was located 0.1 Mb from the significant SNP, DRGA0006706, a protein-coding gene whose gene ontology annotations indicate that it is related to cytosolic metabolic processes (We identified five significant SNPs as being significantly associated with conductivity. Two of these (ALGA0085585 and ALGA0085588) were identified by the FarmCPU and MLM and were located near membrane . Furtherrcentage . The funrocesses  and calcrocesses .roundabout guidance receptor 2 (ROBO2) of the ROBO family. Some researchers showed that ROBO2 was involved in fat metabolism, especially in fatty acid composition and includes C18:3IMF (transmembrane protein 236 (TMEM236). No research has found TMEM236 to be involved in fat metabolism, but its related genes, transmembrane protein 120A (TMEM120A) and transmembrane protein 120B (TMEM120B), affect adipocyte differentiation and metabolism in mice and are highly expressed in fat (transmembrane protein 60 (TMEM60) is another homologous gene associated with marbling fat in cattle , located 0.14 Mb from SNP WU_10.2_12_33077453, is involved in regulating fat androstenone levels , respectively, were first associated with meat color. The related genes, solute carrier family 15 member 4 (SLC15A4) and solute carrier family 25 member 17 (SLC25A17), participate in regulating pork quality. Researchers reported that the SLC15A4 c.658AA genotype had better water-holding capacity and reduced color b∗ and color L∗ , which plays a role in regulating voltage-gated calcium channels during neurotransmitter and insulin release in humans, was located 17.4 kb of ALGA0003423 on SSC1. This gene might regulate glycogen metabolism through insulin, thus affecting pork pH values. Furthermore, insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2), another candidate gene for pH, encodes a protein that binds the 5′-untranslated region of IGF2 mRNA and regulates its translation. It plays an important role in glycogen metabolism, and variation of this gene has been associated with susceptibility to diabetes  and Dark-Firm-Dry (DFD) production. Studies have suggested that mulation  and decrmulation . Regulatdiabetes . Thus, RMany factors affect the validity of GWAS results. Population stratification is an important factor that can lead to false positives . Many stWe conducted a GWAS for meat-quality traits in 582 D (LY) pigs using both FarmCPU and MLM. Thirty-two significant SNPs and several subsequent candidate genes were identified as being associated with meat-quality traits. The biological functions of the candidate genes aligned well with regulating the corresponding meat-quality traits. Furthermore, the FarmCPU worked well in identifying candidate genes, particularly for complex meat-quality traits. Overall, the significant SNPs and candidate genes identified herein may benefit pig-breeding programs and contribute to further improving meat quality.https://figshare.com/s/7c316a6828f238 af0f12).In present study, the SNP genotype data was deposited in the Figshare Repository (The animal study was reviewed and approved by the Institutional Animal Care and Use Committee of Foshan University. Written informed consent was obtained from the owners for the participation of their animals in this study.YZ developed the experimental design. GG was in charge of the experiment execution and data collection and wrote the manuscript. GG and NG processed the data and performed the statistical analysis. All authors made the final revisions, were involved in developing, writing, and commenting on the manuscript, and read and approved the final manuscript.NG, SL, LZ, WJ, and YZ were employed by the company Guangxi Yangxiang Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Salmo trutta L.) populations have been restocked during recent decades to satisfy angling demand and counterbalance the decline of wild populations. Millions of fertile brown trout individuals were released into Mediterranean and Atlantic rivers from hatcheries with homogeneous central European stocks. Consequently, many native gene pools have become endangered by introgressive hybridization with those hatchery stocks. Different genetic tools have been used to identify and evaluate the degree of introgression starting from pure native and restocking reference populations . However, due to the high genetic structuring of brown trout, the definition of the "native pool" is hard to achieve. Additionally, although the LDH-C* locus is useful for determining the introgression degree at the population level, its consistency at individual level is far from being accurate, especially after several generations were since releases. Accordingly, the development of a more powerful and cost-effective tool is essential for an appropriate monitoring to recover brown-trout-native gene pools. Here, we used the 2b restriction site-associated DNA sequencing (2b-RADseq) and Stacks 2 with a reference genome to identify single-nucleotide polymorphisms (SNPs) diagnostic for hatchery-native fish discrimination in the Atlantic and Mediterranean drainages of the Iberian Peninsula. A final set of 20 SNPs was validated in a MassARRAY® System genotyping by contrasting data with the whole SNP dataset using samples with different degree of introgression from those previously recorded. Heterogeneous introgression impact was confirmed among and within river basins, and was the highest in the Mediterranean Slope. The SNP tool reported here should be assessed in a broader sample scenario in Southern Europe considering its potential for monitoring recovery plans.Brown trout ( S. trutta) is a cold-water fish, living in well-oxygenated swift streams, brooks, rivers, and lakes. After the smoltification process, anadromous forms migrate to the sea to feed , foraging close to the coast, not far from the mouth of natal rivers [Brown trout  ‘intic role ,39,40,41tic role ,41,42,43tic role ,21,23,44tic role ,23,39,44Although restocking practices with allochthonous stocks have mostly been discarded ,39,44,45Next-generation sequencing (NGS) techniques enable the achievement of genome-wide data collections in a much faster and cost-effective way , fuelingLDH-C* and microsatellite genotypes).In this study, the 2b-RADseq genotyping-by-sequencing (GBS) methodology  was usedS. trutta, including the four main mitochondrial DNA (mtDNA) lineages in the Atlantic  and Mediterranean  drainages  taking the brown trout genome as reference   with sliference  t,66 tS. tference , (5) ≤3 species   in wild locations using the BA14 hatchery as reference. This made it possible to look for diagnostic loci differentiating hatchery and native individuals from the Iberian Peninsula. A total of 244 individuals coming from 13 wild locations from both the Atlantic and Mediterranean slopes were analyzed. First, using all specimens , we determined the minimal K value where all hatchery specimens were clustered together and separated from the wild samples. The lowest qH detected among BA14 individuals was used as a threshold to identify pure fish for further analyses. Then, from the STRUCTURE analyses of wild locations (see below), all individuals were classified into three categories: (1) hatchery individuals (qH > 0.95), admixed (qH between 0.05 and 0.95), and (3) native individuals (qH < 0.05). Next, for each wild location, an admixture model with two origins was performed , where hatchery individuals were forced to be non-admixed , following an incomplete, frequently used baseline method [The Bayesian clustering method implemented in STRUCTURE 2.3.4  using R e method . Due to e method ). Ten ine method . A burn-e method .qH > 0.05). SNPs were classified according to genetic differentiation . Later, for each location, three additional STRUCTURE analyses were run (for K = 2) with three different subsets of physical, unlinked SNPs: FST > 0.95, FST > 0.99 and FST = 1.00  and results were compared with those obtained using the whole SNP dataset. The matching ratio of fish classified as native, admixed and hatchery with each subset of SNPs regarding the whole SNP dataset information was used to establish their performance for the classification of fish. Annotation of the SNPs selected was performed with the Ensembl Variant Effect Predictor 104 software . Tests on  betweenre .To validate 2b-RAD genotyping, we used the MassARRAY technology on the 81 control individuals (16 hatchery + 65 native) derived from different locations of the Mediterranean and Atlantic slopes. In brief, the protocol consists of a two-step reaction: The first involves the amplification by polymerase chain reaction (PCR) of an amplicon, including the selected SNP, and the second involves a mini-sequencing reaction using an internal primer adjacent to the SNP, which extends the primer with a dideoxinucleotide complementary to the SNP variant . FlankinLDH-C* locus were used to check the performance of the new tool [qH) at individuals and locations was estimated in the eleven locations by using previous hatchery and native controls as references and keeping the same above-described parameters for STRUCTURE software. Correlations between the different estimators of hatchery ancestry using different molecular makers  were performed with R.Secondly, the 241 individuals from eleven locations , with prnew tool . For thinew tool ,44. HatcThe number of AlfI RAD-loci identified in the brown trout genome was 557,761, representing ~0.8% of the total genome assembly. Sixteen individuals with less than 0.9 M aligned reads were removed (see qH > 0.05). Accordingly, this location was not used to identify diagnostic allele variants between native and hatchery fish. One individual from FE, three from LE, two from BL , suggesting random mating and the admixture of hatchery variants into the wild after several generations since the start of releases (data not shown). All of the SNPs used were ranked by FST  to select those with the highest diagnostic power (FST > 0.95) between these two groups. The number of SNPs with FST > 0.95, FST > 0.99 and FST = 1.00 were 214, 38 and nine, respectively (ST = 1.00). Discordances mainly occurred in locations with an average hatchery ancestry (qH) > 0.05, especially at the CE location.Using the whole SNP dataset, a total of 34 individuals of hatchery ancestry with the aforementioned threshold were identified in the wild locations studied. Of all individuals captured at VI, CH, AG1, OM, P2 and P3, TE04 and TE14 were native, while 14 out of the 18 individuals from QB14 showed different degrees of hatchery ancestry , five fectively . These 2ectively , mostly ectively . In 10 oqH close to 0.05, the threshold established to distinguish between native and admixed individuals. Thus, while five individuals were considered admixed (qH between 0.05–0.95) using the whole panel, only one was identified with the 214 and 38 SNP panels, while none were identified with the total of nine diagnostic SNPs panels. Some discordances at other locations were also explained by this fact . Despite the misclassification of a few individuals, the estimated qH for all wild individuals (N = 244) from the different SNP panels was significantly correlated with the whole dataset .Agreement with the whole SNP dataset at CE was slightly lower than 80% with all the three SNP panels . In thisST > 0.95) were revised to check for the lack of polymorphisms and multiple possible alignments along the genomes to avoid interference with primers annealing for the MassARRAY genotyping technology. A total of 39 SNPs fulfilled this criterion, becoming potential candidates to be included in the MassARRAY analysis. Among them, 20 SNPs located in 18 different brown trout chromosomes, far away when mapping in the same chromosome, were compatible for a single multiplex reaction for MassARRAY genotyping, thus being suitable for a cost-effective evaluation of hatchery ancestry (LDH-C* markers.Adjacent genomic regions (±100 bp) to the 214 selected SNPs  showed a very poor genotyping performance and was discarded for further analyses , being much lower with microsatellites . The lower correlation with microsatellites was mainly due to the ME16 and GRE17 locations (p < 0.001). At the individual level, the correlation with estimates was worse between SNPs and LDH-C*90, but significant . The correlation between SNPs and microsatellites with all locations was lower  than when the ME16 and GRE17 locations were removed, as outlined above .The hatchery impact in the 11 new locations estimated as the average location . All loclocation , and theocations . When boAs a result of the evolutionary processes associated with the Pleistocene glaciations, the brown trout is most likely the vertebrate species with the highest population genetic structuring throughout Europe; several of its long-time diverging lineages were previously described ,4,87,88.LDH-C*. The use of a high number of SNPs distributed across the whole brown trout genome, and the availability of a reference hatchery sample from Bagà to estimate the genetic incidence of restocking across the Iberian populations in the Atlantic and Mediterranean slopes, rendered similar values at population level. Our results corroborated a higher impact in Mediterranean-flowing rivers, as previously reported [LDH-C* results at population level, the use of LDH-C* genotypes were less accurate to typify individuals in introgressed populations since, for instance, 50% of the F2 from a native x hatchery cross are expected to be homozygotes for the native LDH-C*100 or *90 alleles, despite their 50% average hatchery genomic background. Furthermore, with only this locus, some approaches  were impossible to achieve. The SNPs detected in this research allowed for a more accurate classification of individuals by hatchery ancestry using the probability of membership assignment with STRUCTURE, as previously reported [qH threshold was more restrictive than those previously used for the species [Scophthalmus maximus; [To counterbalance brown trout population declines, Mediterranean river basins were extensively restocked during the 20th and at the beginning of the 21st centuries, using non-indigenous hatchery stocks from North Atlantic basins ,44,98,99reported , and a dreported ). Despitreported . Our con species  and othemaximus; ) to idenST > 0.95) between hatchery and native fish, irrespective of their lineage, as previously described for the LDH-C* locus. The efficiency of these markers, as well of their two subsets, were composed by SNPs with a progressively higher diagnostic power (from FST > 0.99 (38 SNPs) to FST = 1.00 (9 SNPs)) to relatively determine native, hatchery and admixed fish with conclusions from the whole SNPs dataset. The discrepancies were related to individuals with a hatchery impact (qH) close to the threshold used in the classification, which were very frequent in CE location. Furthermore, because introgression is not homogeneous across the genome [qH estimate affecting individuals’ classification.Notably, the 214 SNPs identified here showed an almost full divergence  [In any case, the MassARRAY tool using 19 SNPs successfully determined the hatchery impact across 11 Mediterranean locations  without previous 2b-RAD information. The MassARRAY approach is a more complete and cost-effective way to determine hatchery impact and identify native brown trout in Mediterranean rivers, compared to using 2b-RADseq or other RADseq methods, which are economically unfeasible for the monitoring of wild populations. In our laboratories, without taking into account DNA extraction, the current price of RE digestion for . (2001)  would be. (2001) ,106,107.. (2001) ).The present results support the usefulness of the SNP MassARRAY tool developed here for the estimation of stocking from a large sample of individuals covering the Iberian Peninsula. However, because AD and ME trout lineages are distributed throughout the Mediterranean basin, our tool could also be useful for studying other Mediterranean trout populations outside of Iberian rivers. Furthermore, in case additional markers are needed, there is a larger diagnostic SNP catalog that can be included in this tool or in a brown trout, high-density array. In addition, this study highlights the usefulness of RAD-seq strategies to provide such a volume of genomic data that many objectives can be covered.


Aspergillus fumigatus is a ubiquitous saprophytic mold that can cause a range of clinical syndromes, from allergic reactions to invasive infections. Amphotericin B (AMB) is a polyene antifungal drug that has been used to treat a broad range of systemic mycoses since 1958, including as a primary treatment option against invasive aspergillosis in regions with high rates (≥10%) of environmental triazole resistance. However, cases of AMB-resistant A. fumigatus strains have been increasingly documented over the years, and high resistance rates were recently reported in Brazil and Canada. The objective of this study is to identify candidate mutations associated with AMB susceptibility using a genome-wide association analysis of natural strains, and to further investigate a subset of the mutations in their putative associations with differences in AMB minimum inhibitory concentration (MIC) and in growths at different AMB concentrations through the analysis of progeny from a laboratory genetic cross. Together, our results identified a total of 34 candidate single-nucleotide polymorphisms (SNPs) associated with AMB MIC differences—comprising 18 intergenic variants, 14 missense variants, one synonymous variant, and one non-coding transcript variant. Importantly, progeny from the genetic cross allowed us to identify putative SNP–SNP interactions impacting progeny growth at different AMB concentrations. Aspergillus is one of the most well-studied fungal genera due to their medical, environmental, commercial, and industrial importance. Aspergillus species are ubiquitous in nature and can survive in a broad range of environmental conditions. Although there are over 350 identified Aspergillus species, only a few are pathogenic to humans [Aspergillus fumigatus is the most common cause of human Aspergillus infections, responsible for more than 90% of aspergillosis [A. fumigatus varies among countries and patient groups [A. fumigatus allow the mold to be an efficient and widespread pathogen, resulting in the ubiquitous presence of up to tens of thousands of conidia/m3 of air [A. fumigatus can germinate, invade tissues through filamentous growth, and disseminate inside the host; resulting in the most severe presentation of aspergillosis, invasive aspergillosis [The fungal genus o humans . Among tgillosis . Howevert groups . Multipl3 of air . In hostgillosis . It is egillosis . Howevergillosis ,8.A. fumigatus strains have been identified in six of the seven continents, with the presence of triazole-resistant strains reaching 80% in certain geographic and ecological populations [A. fumigatus, including the ecological source , underlying patient conditions, and agriculture fungicide use [A. fumigatus isolates have a high mortality rate, at ~88% [For the treatment of aspergillosis, triazole drugs are recommended as first-line therapy. However, triazole-resistant ulations ,20,21,22cide use ,23. In acide use , 7.6%  greater than or equal to 2 mg/L. A study in Campinas, Brazil reported AMB resistance (MIC ≥ 2 mg/L) prevalence rates of 27% for A. fumigatus isolates and 43% in patients [A. fumigatus have mostly come from studies on human pathogenic and non-pathogenic yeasts. In studies of drug resistance among human fungal pathogens, species often differ in their intrinsic drug susceptibility patterns, and possess species-specific mechanisms for drug resistance. Thus, it is important to understand the mechanisms of resistance for individual species. Currently, there is little information available about the mechanism(s) of AMB resistance in A. fumigatus, and mutations that confer resistance remain largely unexplored.Despite over 60 years of clinical use, AMB is still widely used in medical therapy due to its broad spectrum of activity . Furtherpatients . A high patients . At presA. fumigatus isolate genomes with known AMB MIC values, in order to examine non-synonymous mutations in 22 genes of interest potentially associated with AMB susceptibility. We also conducted a genome-wide association study (GWAS) on the clade level using 33 strains [A. fumigatus by conducting a GWAS using a larger sample set of 98 A. fumigatus strains. A subset of these identified mutations was then examined for their associations with specific AMB MIC values and growths at different AMB concentrations among progeny strains from a defined genetic cross. Specifically, we mated two AMB-resistant strains, CM11 (MIC = 8 mg/L) from Hamilton, Ontario and the supermater AFB62-1 (MIC = 4 mg/L), which were known to differ at five SNPs identified as associated with AMB susceptibility in GWAS. The progeny strains were used to examine the contributions of these SNP sites to the observed differences in AMB MIC values and in fungal growths at different AMB concentrations. To help readers follow the paper, we have listed the common acronyms and abbreviations used throughout in In our recent paper, we investigated 71  strains . Those 2 strains . In thatA. fumigatus whole-genome sequences were used in this study, of which 86 sequences were downloaded from the National Center for Biotechnology Information (NCBI) Sequence Read Archive and the remaining 12 sequences were obtained from our previous study [A total of 98 us study . The strA. fumigatus reference genome Af293 (GenBank accession GCA_000002655.1) via the BWA-MEM algorithm v0.7.17 [Sequence mapping, assembly and variant calling were performed using the same pipeline reported in our previous study for triazole GWAS . Briefly v0.7.17 . The Mar v0.7.17  and vari v0.7.17  to remov v0.7.17 . Variant v0.7.17 . p-values and all 277,669 SNP sites from the soft-filtered file were then used to identify highly linked (R2 > 0.85) SNPs of interest.Association analysis was performed in TASSEL 5 by implementing the mixed linear model approach, which handles both fixed and random effects in the model. The analysis included a population structure defined by 5 principal component vectors, determined based on the scree plot, and a kinship matrix calculated using the Identity by State (Centered IBS) method to account for cryptic relatedness as a random effect . To avoiA. fumigatus strains, CM11 and AFB62-1. CM11 had an AMB MIC of 8 mg/L and, to our knowledge, this is the highest reported AMB MIC in A. fumigatus. CM11 has the MAT1-2 mating type. AFB62-1 had an AMB MIC of 4 mg/L and is the designated supermater with mating type MAT1-1, capable of mating with many strains of MAT1-2 mating type to complete the sexual cycle in a relatively short period of time [A genetic cross was created between two  of time .A. fumigatus cleistothecia was conducted using a modified protocol from Ashton and Dyer [3 CFU/mL using TWEEN 20. The solutions underwent heat treatment at 70 °C for 1 h to kill any remaining conidia, then 100 μL of the ascospore suspension was plated on malt agar plates and incubated at 30 °C for 2 to 3 days. After incubation, single ascospore-derived colonies were picked using a sterile loop and each was transferred to new medium for phenotypic and genotypic analyses, as described below.The mating and harvesting of and Dyer . The cro5 to 5 × 106 CFU/mL. Spore suspensions were placed into 96-well microtiter plates containing varying concentrations of AMB and incubated at 35 °C for 48 h. The AMB concentrations tested were 0 mg/L, 0.25 mg/L, 0.5 mg/L, 1 mg/L, 2 mg/L, 4 mg/L, 8 mg/L, and 16 mg/L. Candida parapsilosis (ATCC 22019) and Candida krusei (ATCC 6258) were used as quality controls. The AMB MIC of all progeny and parental strains were determined based on the procedures as recommended by M38-A2. In addition, the amount of growth at each drug concentration for all strains was measured spectrophotometrically at 530 nm. The ratio of fungal growth for strains at various AMB concentrations was calculated by comparing the optical density measurements at 530 nm (OD530) at the start of incubation (0 h) and at the end of incubation (48 h). The value difference between the two time points compared to the positive control (0 mg/L AMB) was taken as the rate of fungal growth over this time period for each AMB concentration. Antifungal susceptibility testing was performed with three replicates. Outlying absorbance values were assessed and removed using a Dixon’s Q-test (α = 0.1). The mean value of three technical repeats was taken to determine the rate of fungal growth for each strain at each AMB concentration. The in vitro susceptibility of all sexual progeny and the two parental strains was determined using the M38-A2 guideline of the Clinical and Laboratory Standards Institute (CLSI) . Brieflyg rpm for 10 min and the supernatant was discarded. The cells were resuspended in 0.5 mL of protoplasting buffer and incubated at 37 °C for 2 h. The solutions were then centrifuged at 5000× g rpm for 10 min. The supernatant was poured out and 0.5 mL of lysing buffer was added in. The mixture was vortexed and incubated at 65 °C for 30 min, and 500 µL of chloroform/isoamyl alcohol (24:1) and 125 µL of 7.5 M ammonium acetate was added to each sample. The tubes were vortexed and centrifuged at 13,000× g rpm for 15 min, or until the upper layer was clear; 500 µL from this clear layer was added to 550 µL of ice-cold isopropyl alcohol. The tubes were mixed by inversion, centrifuged at 13,000× g rpm for 2 min, and the remaining supernatant was discarded. DNA pellets were washed using 50 µL of 70% ethanol for 2 min, dried overnight, and resuspended in 60 µL of 1× TE buffer. DNA extraction of the progeny and parental strains was performed using a modified protocol described by Xu and colleagues . ConidiaThe progeny genotypes at five SNP sites were determined using polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) (PCR-RFLP). The details for the five SNPs can be found below in the Results section. Among the five SNP sites, four were located on chromosome 5 and one on chromosome 6. Primers flanking the SNP sites were designed using the whole-genome sequences of CM11 and AFB62-1. PCR amplification was conducted using a SimpliAmp Thermal Cycler and PCR products were checked using 1% agarose gels. Restriction digests that distinguish nucleotide bases at the five SNP sites between the two parents were performed on all progeny strains, following the manufacturer’s instructions . The digested products were run on 2% agarose gels at 80 V for 1.5 h. Progeny with a PCR-RFLP pattern identical to one of the two parents at each locus were scored as having the allele (nucleotide) of the specific parent at the specific SNP position. Information on the primer sequences, PCR amplification conditions, and restriction enzymes can be found in p-values showed no genomic inflation (A genome-wide association study (GWAS) was conducted to determine candidate mutations associated with AMB susceptibility using a total of 98 A. fumigatus whole-genome sequences and their corresponding AMB MIC values. The results of the GWAS are presented in a Manhattan plot . The quanflation . p-values were further examined. Among these 20 SNPs, 13 (65%) were located in intergenic regions, 6 (30%) were missense variants and 1 (5%) was a synonymous variant  SNPs of interest. From this analysis, 24 highly linked variants were found , tcsB (n = 4), mpkC (n = 2), catA (n = 2), fos1 (n = 1), and mpkB (n = 1). These SNP sites were also examined in our current study using the expanded 98-strain sample set and via Fisher’s exact tests using a Bonferroni-corrected p-value significance threshold. The results of these tests are shown in In our previous GWAS of AMB resistance, a total of 71 A. fumigatus strains were analyzed. Through the use of Fisher’s exact tests, 12 missense variants were found to be significantly associated with AMB resistance using an uncorrected  of 0.05 . These 1−3 (0.05/36), 8 of the 24 highly linked SNPs identified in the current analyses were significantly associated with AMB resistance , mpkC (n = 2 SNPs), and catA (n = 1 SNP)  MIC breakpoint of >1 mg/L was used to define AMB-resistant A. fumigatus strains . From thsistance . Among t_5G00710 . The Fis_5G00710 . These s= 1 SNP) .To further confirm the genetic association between the candidate mutations of interest identified above with AMB susceptibility, we investigated the genotype–phenotype associations among progeny strains of the mating cross. From the mating cross between CM11 and AFB62-1, we obtained 143 meiotic progenies. The AMB MIC values for the 143 progeny strains and the two parental strains are listed in In addition to MIC values, the growth of the progeny strains in various concentrations of AMB was also determined as another quantitative measure of AMB susceptibility. The amounts of fungal growth for the 143 progeny strains and parental strains in the varying concentrations of AMB  were measured using spectrophotometry . The disThe growth data shown in At each AMB concentration, Welch’s t-tests were also conducted on the progeny strains to compare the ratio of fungal growth and AMB MIC values . p < 0.05) between MIC groups were present at AMB concentrations of 0.25 mg/L, 1.00 mg/L and 2.00 mg/L , no statistically significant differences were observed between the MIC groups in their frequencies of inherited alleles at any of the five SNPs  was found at an AMB concentration of 0.25 mg/L for SNP site 5. Specifically, progeny that inherited the CM11 allele at SNP 5 showed statistically significantly higher fungal growth than progeny that inherited the AFB62-1 allele   and the pairwise SNP combinations. No statistically significant difference was found between the genotype groups in their AMB MIC values using the Bonferroni-corrected 0.05/10) .t-tests were again conducted using the pairwise genotype combinations to compare the ratios of fungal growth in varying AMB concentrations  strains inherited all three genotypes from AFB62-1, 67 (46.85%) strains inherited all three genotypes from CM11, and 12 (8.39%) strains had recombinations present at these three sites . Using tThe additional analyses of SNP 5 and Group A found statistically significant differences present at AMB concentrations of 0.25 mg/L, 0.50 mg/L and 1.00 mg/L A. At theTogether, both the pairwise SNP–SNP interaction analyses and the linked SNP analyses revealed that many recombinant genotypes at these five SNP sites showed greater growths than either parental genotype. The results are consistent with the two parental strains having different genetic mechanisms controlling AMB susceptibility, and suggest that AMB susceptibility is a quantitative and multigenic trait.A. fumigatus. The GWAS was conducted using 98 A. fumigatus whole-genome sequences from strains across nine countries with reported AMB MIC values ranging from 0.06 to 8 mg/L. From the GWAS analysis, among the top 20 SNPs, 6 were missense variants. The six missense variants were located in six genes. The highest scoring missense variant was found in AFUA_4G12480, which encodes for an asparagine synthase that converts aspartate to asparagine in an ATP-dependent reaction [AFUA_6G12420, a putative SprT family metallopeptidase. The next two missense variants were found in the uncharacterized proteins AFUA_6G12460 and AFUA_3G00600. The remaining two variants were found in putative oxidoreductases: a missense variant in AFUA_3G00620, encoding a putative zinc-containing alcohol dehydrogenase, and in AFUA_7G01050, encoding for a putative salicylate hydroxylase. These two enzymes are involved in the oxidation-reduction process, a process relevant to AMB resistance in A. fumigatus. For example, AMB exposure has been reported to induce the production and accumulation of intracellular reactive oxygen species (ROS) in A. fumigatus, thereby resulting in oxidative damage [A. fumigatus when exposed to oxygen-limiting environments, which then triggers the oxidative stress response [Aspergillus nidulans was found to be associated with terbinafine resistance [A. fumigatus [In this study, our combined GWAS and genetic crossing approaches revealed that multiple genes contribute to differences in AMB MICs and in fungal growths among strains at different AMB concentrations in reaction . The sece damage . Alcohole damage . Alcohole damage . Howeverresponse . In addiresponse . Meanwhiresponse . Overexpsistance . Howeverumigatus . Both teumigatus . Therefop-value ranking results, even when using the same input file. This was seen in a recent A. fumigatus study that compared overlapping SNPs between software TASSEL and RoadTrips [A. fumigatus strains, with quality control threshold criteria of an MAF of 0.05, a quality score of 20, the removal of indels and excluding genotypes called below 95% across all individuals. Our results revealed that with a LOD score > 2.4, 36 and 57 SNPs were found by TASSEL and PLINK, respectively. Among these SNPs, 18 were found overlapping between the two softwares. However, a greater overlap in the number of significant SNPs was found between these two approaches for triazole resistance in A. fumigatus [Surprisingly, we found no overlap in the top 20 SNPs identified based on GWAS between our previous study  and the oadTrips . Here, wumigatus . Specifiumigatus . Since T2 > 0.85) variants among the 98 strains. Fisher’s exact tests identified 8 of the 24 SNPs to be significantly associated with AMB resistance  permease, respectively. These intergenic variants could impact the gene expressions of the surrounding genes and targeted RT-qPCR analyses could help confirm their effects [AFUA_5G00710, which encoded for a putative GABA permease, and the other was found in AFUA_5G09220, encoding a BEACH (Beige and Chediak-Higashi) domain protein. The final SNP was a non-coding transcript variant in AFUA_5G09320, which encodes for a putative signal transduction protein (Syg1) with plasma membrane localization. The non-coding mutation can also impact gene expression or function if located in elements such as enhancers, silencers, promoters or other regulatory roles.Linkage disequilibrium analysis, conducted on the top 20 SNPs and the 277,669 SNPs of the soft-filtered VCF file, identified an additional 24 highly linked . These six missense variants were in the three genes tcsB (n = 3), mpkC (n = 2), and catA (n = 1). The Bonferroni-corrected p-value was used here to reduce the number of false-positive SNPs. However, if the p-value threshold of 0.05 was used in the current study, four additional SNPs, including those of erg3, would remain significantly associated with AMB resistance (tcsB and mpkC are involved in the high-osmolarity glycerol (HOG) mitogen-activated protein kinase (MAPK) signaling pathway, encoding for a sensor histidine kinase and mitogen-activated protein kinase, respectively [catA, which encodes for a catalase, was also included due to its role in the ROS-detoxifying system [Fisher’s exact tests were also performed on the 12 missense variants that were found in our previous study to be significantly associated with AMB resistance using a significance threshold  of 0.05 . Among tsistance . As ment0−3 0.05/. These s0−3 0.05/. These sA. fumigatus in varying AMB concentrations. Specifically, our results suggest that parental strains CM11 and AFB62-1 differ at multiple loci that contribute to fungal growth differences in varying AMB concentrations, with strain CM11 having advantageous alleles (those contributing to greater growth) at some loci and strain AFB62-1 possessing advantageous alleles at other loci. Since A. fumigatus is a haploid, mating between these two parental strains followed by sexual recombination would generate some progeny with more or fewer advantageous allele combinations than either parental strain. Here, we focused on experimentally investigating the effects of five of the top SNPs identified above on AMB susceptibility and fungal growths under various AMB concentrations using the cross between CM11 and AFB62-1. As described in In this study, a genetic cross was conducted between CM11 and AFB62-1 to generate 143 progeny strains. The result of this cross showed a wide variation in progeny growth values in varying AMB concentrations, with many progeny strains exhibiting transgressive phenotypes, with growths being either two standard deviations higher than the fast-growing parental strain or two standard deviations lower than the slow-growing parental strain. The results here are consistent with multiple quantitative trait loci influencing the growths of AFUA_5G00700 and AFUA_5G00710, which encode for an uncharacterized protein and a putative GABA permease, respectively. GABA permeases serve as gamma-aminobutyrate transporter proteins and are involved in the utilization of GABA as a nitrogen and carbon source [AFUA_5G09190 and AFUA_5G09200. The gene AFUA_5G09190 encodes a putative ABC bile acid transporter, part of the ABC transporter superfamily with many members involved in antifungal drug resistance, while AFUA_5G09200 encodes a putative ubiquitin conjugating enzyme, UbcC. Ubiquitin conjugating enzymes are responsible for the ubiquitination or ubiquitin-like modification of proteins, which plays a role in many biological processes [AFUA_5G09220, a BEACH domain protein sequence. Their exact biological function remains largely unknown; however, BEACH domain proteins have been implicated in membrane dynamics, vesicular transport, and receptor signaling [AFUA_5G09320, encoding a putative signal transduction protein (Syg1) with plasma membrane localization. Although the protein’s function is not clear, Syg1 is predicted to be involved in phosphate homeostasis and to mediate phosphate export due to its similarity to the mammalian phosphate exporter Xpr1 [AFUA_6G07160 and AFUA_6G07170, encoding for a putative IZH family channel protein (Izh3) and an uncharacterized protein, respectively. The IZH family consists of membrane proteins involved in zinc homeostasis [Saccharomyces cerevisiae, izh3 deletion mutants were more resistant to AMB than the wild-type strain [Among these five SNP sites, SNP 1 was an intergenic variant between n source . SNP 2 wrocesses . The nexignaling . SNP 4 wter Xpr1 . The fineostasis . These geostasis . Interese strain . Furthere strain .A. fumigatus. However, we would like to note that the two parental strains used to construct our genetic cross were chosen for their specific traits, such as being different at several SNPs easily distinguished by PCR-RFLP, available in our strain collection, capable of efficient mating and sexual spore production, and both having high AMB MIC. While these features allowed us to identify several of the interesting phenomena reported here, including the multigenic nature of AMB susceptibility and the two parental strains having different AMB resistance mutations, other types of crosses such as those involving a high AMB MIC parent and a low AMB MIC parent may generate broader phenotypic categories among progenies, and enable the mapping and confirmation of additional SNPs associated with AMB resistance. Our study here showed that genetic cross can be an effective approach for investigating the effects of candidate SNPs, as revealed by the GWAS on AMB susceptibility in A. fumigatus strains  into resistant and susceptible categories have changed over time for several antifungal drugs; therefore, rather than restricting our analysis to the predominant binary classification threshold, analyzing MIC differences enabled us to reveal the polygenic aspect of AMB susceptibility using the GWAS and laboratory cross. In addition, with quantitative fungal growths within hosts being an important clinical consideration, variations among strains in terms of their growth abilities, with and without antifungal drugs, should be more frequently analyzed. Our analyses of A. fumigatus growths here identified mutations and SNP–SNP interactions significantly associated with fungal growth inhibition at various AMB concentrations, which were not found to be significant when using MIC value differences.At present, most studies of antifungal drug resistance classify strains into binary categories: resistant vs. susceptible. In this study, we have focused on the quantitative nature of both AMB MIC values and fungal growths at different AMB concentrations. As shown here, we believe analyzing quantitative variation is crucial for understanding the complexities of antifungal drug resistance. The MIC breakpoints used to define and separate A. fumigatus. However, other genomic features not analyzed here, such as the copy number variation of genes and the presence of mycoviruses, may also influence AMB susceptibility (and other phenotypes) in this species. For example, the tandem duplication of a 34 bp or a 46 bp sequence in the promoter region of cyp51a is associated with an elevated MIC to triazole antifungals in A. fumigatus [Aspergillus fungi, and some of them are known to impact phenotypes in these fungal species [A. fumigatus strain IFM 41362 had reduced tolerance to hypoxic, nitrosative, oxidative, and osmotic stresses. Furthermore, the virus-infected strain IFM 41362 had lower virulence than the virus-free strain of the same genotype in a mouse infection model [A. fumigatus has not been systematically investigated, given their impacts on stress responses, it is possible that these viruses could contribute to AMB susceptibility differences in A. fumigatus. In our study, the distributions of mycoviruses among the genome-sequenced strains analyzed here are unknown, and thus their relationships to AMB susceptibility could not be analyzed. Because most known mycoviruses in Aspergillus fungi are RNA viruses [A. fumigatus.In this research, our focus was on the relationship between genomic SNPs and AMB susceptibility in umigatus . Copy nu species ,66,67. FA. fumigatus, and for further functional analysis. Furthermore, these candidates can help to accelerate the selection of prospective gene markers for AMB resistance screening in A. fumigatus. The development and clinical applications of molecular markers such as those identified here into rapid diagnostic kits could significantly shorten the time for drug-resistance identification, facilitate targeted treatment at early stages of infection, and reduce mobility and mortality caused by A. fumigatus and other fungal pathogens.In recent years, advancements in medical technology and the increased usage of immunosuppressive agents have led to an expanding population of immunocompromised hosts, as well as a rising incidence of invasive mycoses such as aspergillosis. With the recommendation for a shift to AMB use in first-line invasive aspergillosis treatment where triazole resistance rates exceed 10%, the emerging problem of widespread AMB resistance and reports of high resistance rates—27% in Campinas, Brazil and 96.4% in Hamilton, Canada—are becoming a major public health concern ,34,35. T


The common carp, one of the most important food and ornamental allo-tetraploid fish, encodes two fads2 genes (fads2a and fads2b). The PUFA contents among common carp individuals were numerous, suggesting that there might exist polymorphisms in fads2a and fads2b. However, selective breeding of common carp with high PUFA contents was hindered due to a lack of effective molecular markers. This study investigated the contents of PUFAs in common carp and identified polymorphisms in the CDS regions of fads2a and fads2b. The association study identified three cSNPs associated with the PUFA contents and suggested that fads2b might be the major gene responding for common carp PUFA contents. These cSNPs would be potential markers for future selection to improve the PUFA contents in common carp.Fishes are the major dietary source of polyunsaturated fatty acids (PUFAs) for humans. The limited availability of PUFAs derived from fish represents a critical bottleneck in food production systems, one that numerous research institutions and aqua-feed companies in this field are trying to overcome. This problem could be minimized by select-bred fish to be capable of more effectively producing endogenous PUFAs. Fatty acid desaturase 2 (fads2) is one of the rate-limiting enzymes in PUFAs biosynthesis. Compared with the diploid fish encoding one fads2, the allo-tetraploid common carp, one most important food fish, encodes two fads2 genes (fads2a and fads2b). The associations between the contents of different PUFAs and the polymorphisms of fads2a and fads2b have not been studied. The contents of 12 PUFAs in common carp individuals were measured, and the polymorphisms in the coding sequences of fads2a and fads2b were screened. We identified five coding single nucleotide polymorphisms (cSNPs) in fads2a and eleven cSNPs in fads2b. Using the mixed linear model and analysis of variance, a synonymous fads2a cSNP was significantly associated with the content of C20:3n-6. One non-synonymous fads2b cSNP (fads2b.751) and one synonymous fads2b cSNP (fads2b.1197) were associated with the contents of seven PUFAs and the contents of six PUFAs, respectively. The heterozygous genotypes in both loci were associated with higher contents than the homozygous genotypes. The fads2b.751 genotype explained more phenotype variation than the fads2b.1197 genotype. These two SNPs were distributed in one haplotype block and associated with the contents of five common PUFAs. These results suggested that fads2b might be the major gene responding to common carp PUFA contents and that fads.751 might be the main effect SNP. These cSNPs would be potential markers for future selection to improve the PUFA contents in common carp.Fatty acid desaturase 2 ( Fish provide polyunsaturated fatty acids (PUFAs) for human. PUFAs are necessary for important biological functions in human, such as regulating lipid metabolism, stimulating growth and development, exerting anticancer and antiaging effects, enforcing immune-regulation, promoting cardiovascular health, and aiding weight loss ,2,3. PUFfads2), an endoplasmic reticulum membrane-bound enzyme, introduces cis double bonds into fatty acyl chains at specific sites of PUFAs [fads2 gene, comparative analysis revealed that mutations in the protein sequences affect the substrate specificity  and conversion efficiency [fads2 in human, mammals, and fish [Biosynthesis of PUFAs in fish involves desaturation and elongation of the precursor C18 FA ,6. The fof PUFAs ,8,9. Thificiency ,12,13,14and fish ,18,19,20Cyprinus carpio) is cultured commercially worldwide, generating numerous geographical populations. Domestication has also accelerated the phenotypic diversity of the common carp [fads2 gene than most diploid freshwater fish. Two fad cDNAs, fads2a and fads2b, were previously identified [fads2a and fads2b. Indeed, in common carp var. Jian, one intronic SNP in fads2a and one intronic SNP in fads2b were identified [The common carp . Before collecting the tissues, all fishes were euthanized in MS222 solution.To increase the diversities of HUFA contents, in 2018, we collected the juvenile common carp including the var. Huanghe , the var. Furui (FRC), and the var. Jian  . The samfads2a and fads2b in common carp (GenBank accessions: MK852165 and MK852166), gene-specific primers were designed to amplify the complete coding sequence (CDS) regions of these two genes . The concentration of RNA was determined using the NanoDrop 2000 spectrophotometer , and its quality was determined by 1% agarose gel electrophoresis. Next, 1 µg RNA was reverse transcribed to cDNA using the SuperScript III RNase H-Reverse Transcriptase Kit  with oligo-dT. Based on the reference full-length sequence of wo genes . 2, 0.2 mM of each dNTP, 15 pmol of each primer, and 0.3 U of Taq polymerase . The following thermal profile was applied: 5 min at 94 °C, 40 cycles of 30 s at 94 °C, 30 s at the annealing temperature of 56/62 °C , all of the amplified sequences were aligned to fads2a and fads2b using blastn. For one sequence expected to be from fads2a, if it had a higher alignment score for fads2b than fads2a, then this sequence should be aligned to fads2b to call for SNPs. The same operation was performed on all sequences expected from fads2b. To detect SNPs and to perform genotyping in each sample, the sequences were aligned to their corresponding reference genes in the novoSNP software [Since software  with thefads2a and fads2b. The genetic distances were estimated using Principle Component analysis (PCA) in the Tassel 5.0 software [We investigated the genetic distances and structures among three varieties with all retained genotypes in software . The firsoftware . K was ssoftware . fads2a genotype information), it was retained in the downstream analysis. The polymorphism information content (PIC) for each retained SNP locus was estimated using PICcalc 0.6 [As three varieties were grouped together in the PCA analysis and had similar structures, we combined these varieties into one population. The observed heterozygosity (Ho), expected heterozygosity (He), genotype frequency, and allele frequency in the population were calculated using the Genepop software . If the calc 0.6 . The effFAs in each individual muscle were transformed into fatty acid methyl esters (FAMEs). FAMEs were prepared, extracted, and purified by thin-layer chromatography following Li et al.’s strategy . The typBefore the following association study, we first examine whether there existed significant differences in the PUFA types and contents among three varieties. With the contents of 12 PUFAs, the distances measured by the PCA analysis were estimated with Tassel 5.0. The Spearman correlation coefficient of the contents of any two PUFAs in all individuals was calculated using the R ‘cor.test’ function. Using the TBtools software , we clusAssociations between the contents of each PUFA and the genotypes were studied using the mixed linear model (MLM) and the analysis of variance (ANOVA), respectively. The MLM model, including the PCA and the kinship matrix, which is MLM (PCA + K), was applied into the association study with Tassel 5. This method was widely used in the association study between the polymorphisms in candidate genes and phenotypes ,37,38. Tp values were corrected using the false discovery rate (FDR) method for multiple hypothesis testing.For each SNP locus, we grouped the individuals on the basis of their genotypes. Then, we performed pairwise group comparison with ANOVA to estimate whether there existed significant content difference in each PUFA between the two groups. All p value < 0.05 in the MLM method and a FDR-corrected p value < 0.05 in the ANOVA. In each gene, the pairwise linkage disequilibrium (LD) between any two SNPs was measured by D’ calculated with PLINK v1.90 [As for each PUFA, one SNP locus was considered significantly associated with the content if it had a NK v1.90  and visuNK v1.90 . The hapfads2a and fads2b were highly similar, with a nucleotide identity of 89.86% and a protein identity of 92.06%. The fads2a CDS spanned 12 exons, and the fads2b CDS covered 12 exons. For fads2a, base contents of A, G, C, and T in the sequence were 25.0%, 26.2%, 24.6%, and 24.2%, respectively; the A + T content (49.2%) was lower than the G + C content (50.8%). For fads2b, the average A, G, C, and T base contents in amplified sequences were 25.4%, 26.1%, 24.5%, and 24%, respectively; the A + T content (49.4%) was lower than the G + C content (50.6%). All of these data suggest high similarity between the CDS of these two genes. After amplification and validating the real source genes, we successfully sequenced the entire CDS of fads2a in 122 individuals and the entire CDS of fads2b in 237 individuals. The CDS sequences of fads2a cSNPs and 27 fads2b cSNPs . Ho in fads2a ranged from 0.1 to 0.51 and He ranged from 0.09 to 0.4. PIC analysis indicated that the fads2a.288 locus displayed a low polymorphism level (PIC < 0.1) compared with the other four loci. Among the fads2b cSNPs, Ho ranged from 0.02 to 0.38 and He ranged from 0.07 to 0.49. Two loci displayed low polymorphism levels (PIC < 0.1) compared with the remaining nine loci. All fads2a cSNPs and fads2b cSNPs significantly deviated from the Hardy–Weinberg equilibrium .The minor allele frequencies (MAF) of p value < 0.05, We obtained the contents of 12 PUFAs in 269 common carp samples . PCA anaA correlation matrix of pairwise content comparisons between two PUFAs  exhibitefads2a cSNPs, only one synonymous cSNP (fads2a.624) was found to be significantly associated with the content of C20:3n-6 by both MLM  and ANOVA , resulting in the conversion of valine to isoleucine, was associated with the contents of four n-3 PUFAs  and three n-6 PUFAs . In this locus, two genotypes including the homozygous genotype (GG) and the heterozygous genotype (AG) were observed while the homozygous genotype of AA was not identified. Interestingly, in all observed associated PUFAs, the individuals with the heterozygous genotype had significantly higher contents than those with the homozygous genotype (Among 11 genotype B–H. The The other cSNP (fads2b.1197) was synonymous and associated with the contents of three n-3 PUFAs  and three n-6 PUFAs . In this locus, two genotypes including the homozygous genotype (CC) and the heterozygous genotype (CT) were observed while the homozygous genotype of TT was not identified. Likewise, in all observed associated PUFAs, the individuals with the heterozygous genotype had significant higher contents than those with the homozygous genotype I–N. The fads2b CDS  were associated with both cSNPs. Two haplotype blocks were identified in the ds2b CDS . The fadThe limited availability of PUFAs derived from fish represents the critical bottleneck in food production systems, one that numerous research institutions and aqua-feed companies in this field are trying to overcome. Increasing PUFA in fish may have important impacts on human heath, especially in a context where the traditional sources of PUFA, wild fish, and fish oils, are limited by the stagnation of fisheries. Although producing aquaculture fish with more PUFA could be achieved by feeding different fish ingredients ,42, thisfads2 gene is a rate-limiting enzyme catalyzing the desaturation of PUCAs, and the overexpression of salmon fads2 gene in zebrafish could improve PUFA contents [fads2 genes were identified in the common carp and had differential expression patterns during the development from embryo to larval [fads2a/fads2b and the PUFA contents. The PUFA content diversities in common carp suggest the possible existence of SNPs in fads2a/fads2b. Since the genic regions of fads2a and fads2b were longer than 11,500 bp [fads2a and fads2b. The lower amplification efficiency of fads2a than fads2b was possibly due to the low gene expression of fads2a in liver. The contents . Two fado larval . Our stu1,500 bp , it is lfads2a and fads2b, and the PUFA content diversities. It is still unknown which gene makes more contributions to the PUFA biosynthesis. More associated PUFAs and higher explained percentage of phenotypic variations in fads2b than fads2a suggest that fads2b might be the major effect gene for PUFA biosynthesis. More functional studies on these two genes are required for further validation [Although under long-term selection  common carp acquired genetic diversity and phenotypic diversity, the three varieties studied had no significant differences in the genetic diversities of these two genes and the PUFA content diversities. Three varieties of common carp were grouped into one population to increase the sample size, the genetic diversities of lidation ,13,15,16fads2b cSNP might improve desaturase efficiency on the n-3 and n-6 substrates, leading to higher PUFA contents. We also observed one synonymous cSNP associated with the PUFA contents. One possible reason is the tight linkage between the non-synonymous cSNP and the synonymous cSNP, and the synonymous cSNP is a possible biomarker representing the non-synonymous cSNP. The other possible reason is that the synonymous cSNP might affect the DNA methylation level of fads2b. In humans, the DNA methylation level in the fads1/2/3 gene cluster was linked with genetic variants and desaturase activities and thus affected fads2 gene expression [fads2b CDS region using the method described by Gardiner-Garden and Frommer (1987) with the parameters of GC content over 50% and of the observed/expected ratio over 60% [fads2b DNA methylation level and then its expression requires future study. The non-synonymous pression ,45. We pover 60% . The synfads2b might increase the desaturase activity. Steer et al. [fads2 in humans to be increasingly capable of synthesizing docosahexaenoic acid from alpha-linolenic acid, thereby suggesting that heterozygotes can achieve nutritional adequacy. We observed the eterozygote advantage with the PUFA contents. The heterozygote advantage was widely observed in the economic traits including the growth rates . In two r et al.  reportedfads2a and fads2b associated with the PUFA contents. These cSNPs will be applied into future marker-assisted selective breeding of common carp to improve PUFA contents. The question of whether there exist polymorphisms in the promoters, miRNA binding sites, and other functional elements of fads2a and fads2b will be studied in the future. We identified cSNPs in fads2a and fads2b in common carp and found higher polymorphisms in fads2b than fads2a. We identified the contents of 12 PUFAs in common carp muscle, which exhibited diversities among individuals. The association studies between the polymorphisms of these two genes and the PUFA contents in common carp identified three cSNPs linked to the PUFA contents. The gene fads2b might be the major gene responding for common carp PUFA contents, and fads.751 might be the main effect SNP. Taken together, our findings highlight the importance of polymorphisms in fads2a and fads2b, critical to the biosynthesis of n-6 and n-3 PUFA levels in common carp. These cSNPs would be potential markers for future selection to improve PUFA contents in common carp.We detected many polymorphisms in the coding regions of