Sheep farming is a major source of meat in Morocco and plays a key role in the country’s agriculture. This study aims at characterizing the whole-genome diversity and demographic history of the main Moroccan sheep breeds, as well as to identify selection signatures within and between breeds. Whole genome data from 87 individuals representing the five predominant local breeds were used to estimate their level of neutral genetic diversity and to infer the variation of their effective population size over time. In addition, we used two methods to detect selection signatures: either for detecting selective sweeps within each breed separately or by detecting differentially selected regions by contrasting different breeds. We identified hundreds of genomic regions putatively under selection, which related to several biological terms involved in local adaptation or the expression of zootechnical performances such as Growth, UV protection, Cell maturation or Feeding behavior. The results of this study revealed selection signatures in genes that have an important role in traits of interest and increased our understanding of how genetic diversity is distributed in these local breeds. Thus, Moroccan local sheep breeds exhibit both a high genetic diversity and a large set of adaptive variations, and therefore, represent a valuable genetic resource for the conservation of sheep in the context of climate change. Sheep were among the first domesticated animals about 11,000 years B.P . They arTechnological advances during the last decade have made it possible to produce and process Whole Genome data for hundreds of individuals . SimilarIn Morocco, sheep are marked by a high global genetic diversity indicating a high adaptive potential . The maiSheep farming in Morocco plays an important economic and sociological role. It is practiced all over the country where it is often one of the main sources of farmers’ income. Thus, sheep are bred under various environmental conditions and anthropogenic pressures. One of the main threats to these breeds is the unsupervised crossing practiced by farmers under increasing economic pressure as recently demonstrated by The Moroccan sheep population is made up of about 1% of exogenous breeds and 99% of local breeds , among wMany characteristics that condition the fitness of livestock are associated with the production performances. Thus, the identification of signatures of selection is a valuable approach to identify the genes and polymorphisms underlying the phenotypic variation of these traits that are subjected to both anthropogenic selection  and natuIn this context, this study aims at characterizing the main five Moroccan breeds by describing their genomic diversity, inferring their demographic history and identifying shared and breed-specific selective sweeps using whole genome data. The data obtained enabled us to distinguish genomic regions putatively involved in local adaptation from those more directly related to anthropogenic pressures and associated to breed-specific zootechnical performances.We sampled 87 unrelated sheep representatives of the geographic distribution of five local Moroccan breeds  were collected either from captive or recently hunted animals, and from frozen samples available at the Iranian Department of Environment. These worldwide sheep (n = 20) and Asiatic mouflons (n = 13) were previously used in Additionally, a worldwide breed panel consisting of 20 sheep representing 20 different worldwide breeds was provided by the International Sheep Genome Consortium. The panel represents sheep from Asia, Africa Australia, America and Europe . SimilarAs described by The Gaussian model was applied to the full data set, generating a VQSLOD (log odds ratio of being a true variant). Sites were filtered out if VQSLOD < cutoff value. The cutoff value was set for each population by the following: Minimum VQSLOD = {the median value of VQSLOD for training set variants}—3 * {the median absolute deviation VQSLOD of training set variants}. Measures of the transition/transversion ratio of SNPs suggest that this chosen cutoff criterion gives the best balance between selectivity and sensitivity.Genotypes were improved and phased by Beagle 4 , and then filtered out where the genotype probability calculated by Beagle was <0.95. The resulting dataset was constituted of 47,622,950 variants.ST index (We used vcftools  to estimST index  using thr), while assuming a fixed and pre-defined per generation per site mutation rate (μ). In order to compare the demographic history Moroccan sheep with the main worldwide breeds/populations, we included, in the analysis, genomic data of the worldwide sheep and Asiatic mouflons. The latters represent the closest wild descents of the species from which the current domestic sheep (O. aries) diverged since their domestication. The worldwide breeds were subjected to the improvement of their production performances by intensive selection  approach implemented in PopSizeABC  to estimelection .−9 to 13e−9 with an approximation of r = 10.65e−9, and then empirical data for each population. The minor allele count threshold (mac) for the Allele Frequency Spectrum (AFS) and Identity By State (IBS) statistics computation was set for each population to about 5% × N (where N is the number of samples) and the minor allele count threshold for LD statistics computation (mac_ld) was set to about 20% × N as recommended by We estimated the recombination rate by using a uniform prior interval from 8eTo identify selective sweeps, we have defined an integrated framework based on two complementary approaches as proposed in hard sweeps) as described by Ovis to produce SNPs. Those ancestral alleles were added to the input VCF files using an in-house shell script. Afterwards, five different datasets representing whole genome variants with a total of polymorphic 31,442,046 SNPs  of each of the five breeds were extracted using vcftools . It was used to detect selection signatures by differentiating haplotypes among hierarchically structured populations, as described by B- The second approach to detect selective sweeps was a combination of the FLK  and hapFOvis Orientalis (included as outgroup) were combined using the option “-T CombineVariants” of GATK  were established and used for the Gene Ontology (GO) enrichment analyses. Similarly, outlier genomic regions were constituted of 50 kb segments surrounding outlier SNPs. GO enrichment analyses were performed using GOwinda  in orderHo) in the five breeds was 0.28 on average, varying from 0.22 in Dman to 0.35 in Beni Guil , calculated over the 87 Moroccan sheep was 0.29. The Dman and Sardi breeds showed close π values of 0.247 and 0.25, respectively. Timahdite, Ouled Jellal and Beni Guil showed slightly higher π values of 0.274, 0.32 and 0.346, respectively .The number of breed-specific SNPs strongly varied among breeds, from 341 k and 460 k in Beni Guil and Ouled Jellal, respectively, to 1.6 and 1.78 M in Sardi and Dman, respectively .ST was low, from 0 between Beni Guil and both Dman and Ouled Jellal to 0.004 between Sardi and both Dman and Ouled Jellal , Timahdite is closely grouped with Sardi and Dman, Beni Guil is the most divergent, with rather long branches, among the Moroccan breeds. As expected, wilds were distant from all domestic breeds.Ne in the recent past. Conversely, in cosmopolitan sheep, the bottleneck was first less pronounced but during the last 1 K years, the Ne regularly decreased until about 300 at present. However, we do not exclude that using a pool of individuals representing several breeds may impact the accuracy of the estimates.The PopsizeABC analysis highlighted that before 10,000 years ago, the estimated effective population size (Ne) was similar in all populations . Then, tThe analysis of the whole genome variants of the 87 Moroccan sheep belonging to five breeds, detected selection signatures both within FreqHMM,  and betwWe identified 182,337 SNPs in 364 genomic regions  under seHMGA2 (3 SNPs), RCOR1 (9 SNPs) and SBF2 (4 SNPs).Regarding the shared selection signatures, we noticed that Dman share more SNPs/genes under selection with Sardi and Timahdite  and haplotype local tree (hapFLK scores). This selective sweep was associated with the genes RXFP2 and ENSOARG00000011616. The other strongest selective sweeps were related to 1) the region located on Chr14: 13,329,709-14,250,423 differentiating Sardi and associated to 8 genes; 2) the region located on Chr19: 2,143,797-2,261,064 differentiating Sardi and Beni Guil from the other breeds and associated with intergenic SNPs; 3) the region located on Chr16: 34,551,942-34,646,856 differentiating Timahdite and associated with intergenic SNPs; 4) the region located on Chr2: 84,619,111-84,759,276 differentiating Timahdite and associated to the BNC2 gene and some intergenic SNPs  in order to be sufficiently conservative. The whole process identified 8,887 SNPs in 27 different regions, of which 4,131 were associated with 20 genes and 4,756 were intergenic. Among the all outliers we identified 3,908 SNPs as top candidates with an 10−12 . They weter-plot  where Dmter-plot  where Dmnic SNPs .HMGA2, RCOR1 and SBF2.When combining both approaches, from a total of 31,721,507 analyzed SNPs, we identified as putatively under selection 46,799 variants associated with 155 genes in Sardi, 37,511 SNPs associated with 138 genes in Timahdite, 59,351 variants associated with 206 genes in Dman, 56,995 associated with 186 genes in the Beni Guil breed and 53,990 variants associated with 189 genes in Ouled Jellal. The Venn diagrams in The selection signatures detected by both methods  allowed identifying a total of 7,735 GO categories enriched in genes under selection , based oF = 0.1). FST values showed no clear differentiation between Moroccan breeds with an average of ∼0.002. These FST values are lower than those found in Welsh local sheep  and globally lower than the values reported for Iranian sheep breeds  and Welsal sheep  but stilal sheep , which wBased on nucleotide diversity (π), we found that Dman was the most diversified of the Moroccan breeds. This could be explained by a lower intensity of selection, a higher founder population and wider breeding area for this breed. The slightly higher inbreeding in Dman would be explained by its sub-structuration in isolated Oases that leads to the mating of closely related individuals and by the longstanding use reproductive rams . HoweverOvis Orientalis  are very high when compared to what is reported in the literature for sheep . This would illustrate the important role of regulation in the realization of biological processes and the expression of traits as reported by HMGA2, RCOR1 and SBF2) are generally involved in cellular functioning. The expression of HMGA2 is strongly associated with body size and growth in mice, humans and dogs  specific to one or a few breeds. Several GO Terms were enriched in genes putatively selected ; they weMC1R gene, which is candidate in the Sardi breed, has been associated with a large panel of skin or coat colors . Another candidate specific of Sardi is SLC9A3. The deficiency of this gene causes severe obstructive azoospermia and infertility in male mice  exclusively in the Beni Guil breed. It has been associated with meat and carcass traits in pigs  found in Ouled Jellal was involved in protecting against UV-induced damages (The  damages  and was  damages . Mutatio damages . in fact damages .MITF) is a selected gene in both Beni Guil, Dman, Sardi and Timahdite. It is a basic transcription factor which regulates the differentiation and development of melanocytes and pigment cell-specific transcription of the melanogenesis enzyme genes (Besides specific-breed candidates, the Microphthalmia-associated transcription factor (me genes . This geme genes . We coulWe characterized the neutral diversity, demographic history and selection signatures using whole genome variants in the five main sheep breeds from Morocco. Globally, these five breeds are not very genetically differentiated, but they show a high number of specific variants and very high effective population sizes unlike cosmopolitan breeds. This illustrates that Moroccan indigenous breeds are highly diversified and have thus the potential to develop key adaptive characteristics to face upcoming climate changes. This makes them valuable resources for conservation and future preservation of sheep even at the worldwide scale.Investigations on selection signatures provided valuable insights about genes and biological processes targeted by selection, which are essentially involved in pigmentation, zootechnical performance, adaptation and reproduction traits. Many genomic regions highlighted here need further investigations to decipher their specific roles in the expression of phenotypes specific to the studied breeds. However, the outlier genomic variants identified here represent valuable candidates and should be conserved in priority when conceiving the upcoming genomic breeding programs. Those programs have to consider improving production as well as adaptation traits while maintaining the diversity of these local sheep breeds.


Uniparentally-inherited markers on mitochondrial DNA (mtDNA) and the non-recombining regions of the Y chromosome (NRY), have been used for the past 30 years to investigate the history of humans from a maternal and paternal perspective. Researchers have preferred mtDNA due to its abundance in the cells, and comparatively high substitution rate. Conversely, the NRY is less susceptible to back mutations and saturation, and is potentially more informative than mtDNA owing to its longer sequence length. However, due to comparatively poor NRY coverage via shotgun sequencing, and the relatively low and biased representation of Y-chromosome variants on capture assays such as the 1240 k, ancient DNA studies often fail to utilize the unique perspective that the NRY can yield. Here we introduce a new DNA enrichment assay, coined YMCA (Y-mappable capture assay), that targets the "mappable" regions of the NRY. We show that compared to low-coverage shotgun sequencing and 1240 k capture, YMCA significantly improves the mean coverage and number of sites covered on the NRY, increasing the number of Y-haplogroup informative SNPs, and allowing for the identification of previously undiscovered variants. To illustrate the power of YMCA, we show that the analysis of ancient Y-chromosome lineages can help to resolve Y-chromosomal haplogroups. As a case study, we focus on H2, a haplogroup associated with a critical event in European human history: the Neolithic transition. By disentangling the evolutionary history of this haplogroup, we further elucidate the two separate paths by which early farmers expanded from Anatolia and the Near East to western Europe. Since the seminal studies of the 1980s4, and prior to the genomic era, much of the genetic history of humankind and the peopling of the world was inferred from uniparentally inherited mtDNA and NRY7.Uniparentally inherited markers such as mtDNA and the NRY are an attractive source of information about the demographic history of a population due to the fact that their history can be represented by a simple evolutionary tree8, mtDNA has been particularly well-studied, yielding an inexpensive and yet reliable source of information about the genetic variability of a population10.Due to the high copy number of mtDNA in the cells (Ingman and Gyllensten 2001), the short genome length (< 17 kb), and the relatively high substitution rate11, e.g. 8, e.g. 12. However, the greater genome length of the NRY, compared to the mtDNA, means that from these substitution rates, and for a single lineage, we still expect to observe a point mutation approximately every ~ 108 to ~ 123 years for the NRY, compared to between ~ 3094 and 4440 years for the entire mitogenome. Consequently, the NRY can contain more information about the paternal demographic history of a population and can be informative about male-biased population demographic changes, such as through male-driven migration15 or patrilocality16, so seeking insights into the paternal history of a population can be of critical importance.Conversely, the mappable portion  of the NRY is much longer  and presents only as single-copy in the cells of male individuals. The evolutionary substitution rate (in substitutions per site per year) was estimated to be up to two orders of magnitude lower for the NRY20 that were otherwise impossible to recover from human genetic data of modern-day populations. Studies of the uniparentally inherited markers of ancient individuals have also yielded otherwise undetectable results, e.g. the loss of European mtDNA diversity following the repeopling of Europe after the last glacial maximum10, or the decrease in and partial replacement of diversity of hunter-gatherer Y-chromosome lineages in eastern and central Europe following the Neolithic expansion24, followed by the loss of diversity of Neolithic Y-chromosomes lineages with the arrival of Steppe-like ancestry at the beginning of the 3rd millennium BCE20.When studying the demographic history of humans, aDNA has been shown to be an irreplaceable source of information. aDNA studies have revealed large-scale population movements and genetic turnover events in Western Eurasia26. The Y chromosome makes up < 2% of the total DNA in male cells, meaning that if researchers wish to use shotgun (SG) sequencing to adequately cover enough informative sites on the single-copy NRY, then, even for samples with good DNA preservation, a substantial sequencing effort is required.Researchers using aDNA data usually encounter problems related to sample quality, specifically a decrease of endogenous human DNA due to post-mortem DNA decay and environmental contamination28. One such popular assay is the 1240 k assay, which targets ~ 1.24 M ancestry-informative sites on the human genome, of which ~ 32 k represent a selection of known variants on the Y chromosome 28. Of note, the commercially available version  contains an additional 46 k Y-chromosomal SNPs identified by ISOGG to be variable in extant males.The development of targeted capture assays has allowed aDNA researchers to enrich specific sites and regions of the genome for sequencing, vastly improving the yield of human endogenous DNA from ancient sampleshttps://isogg.org/tree; https://www.yfull.com), allows for basic Y haplogroup (YHG) assignments, but is heavily biased towards modern-day diversity and certain geographic regions. As a consequence, depending on the representation of particular Y-SNPs on the 1240 k assay, the resulting YHG assignments can be of low and uneven resolution, while the targeted approach does not allow for the detection of hidden and/or potentially extinct lineages in the human past.This relatively low number of targeted Y-SNPs, compared to the number of currently known, informative Y-SNPs , and we show that the remaining ~ 1.5 Mb in our target regions still yield reliably mapped sites , a tiled capture-assay for NRY sequence data that targets regions of the NRY for which short reads, typical in ancient DNA samples, are reliably mapped to the human genome, as defined by Poznik et al.Here we show that YMCA significantly improves the relative coverage of NRY sites when compared to shotgun sequencing, allowing for the enrichment of NRY sites for the same sequencing effort. We also show that YMCA significantly outperforms 1240 k SNP assay sequencing in two ways. Empirically, we show that YMCA improves the number of NRY sites that are covered. We also show, by considering the targeted NRY sites as defined by the associated bed files, and if we were to sequence a sample with high complexity to exhaustion, that YMCA has an improved potential resolution for Y-haplogroup assignment and the discovery of new diagnostic SNPs when compared to 1240 k assay sequencing.We highlight the improved performance obtained via YMCA by analysing the Y-chromosomal haplogroup H2 (H-P96), a low-frequency YHG that is associated with early farmers during the Neolithic transition in Western Eurasia. We curated a data set of 46 previously published individuals (45 ancient and 1 modern), and 49 newly YMCA-sequenced individuals . We show that our current understanding of H2, which is based largely on modern H2 samples (n = 20), is inconsistent with the ancient diversity of our H2 individuals. In resolving this ancient haplogroup, we can show two distinct migration paths along the Mediterranean and Danube for Neolithic groups from Anatolia to Western Europe, ultimately resulting in the Mediterranean-derived groups also reaching Britain and Ireland.To evaluate the performance of our new NRY-Capture assay (YMCA), we calculated the empirical fold-increase in endogenous human DNA for a range of samples with varying levels of preservation. We chose samples from the same site  to avoid the effects of too many environmental variables, for which we had shotgun, 1240 k capture and YMCA sequence data , and that the number of ISOGG SNPs covered and the endogenous DNA percentage for 1240 k sequencing were uncorrelated (p = 0.1825) indicating that our results are not dependent on the relative abundance of retrievable human DNA in the sample. Hence, we found that, although the SNPs covered on the Y chromosome are an added bonus when using the 1240 k assay, as it is primarily used for analysing the autosomal genome of male and female individuals, YMCA is clearly a significant improvement if researchers wish to efficiently and thoroughly investigate the non-recombining portion of the Y chromosome.We then compared the percentage of haplogroup-informative SNPs on the ISOGG SNP list v14.8, that are also included in the 1240 k assay, and YMCA, according to their respective bed files. This comparison will be particularly powerful as YMCA and the 1240 k assay are based on the same technology, and captured via identical lab protocols. The 1240 k assay targets 24.44% of the currently listed ISOGG SNPs, whereas the YMCA targets 90.01% . However, if one is to include a window of 120 bp around each SNP again, then the 1240 k assay potentially targets ~ 3,953 k sites or 37.82% of the number of sites one can potentially analyse using our YMCA. Hence, YMCA is a predictably better tool for exploring the NRY for new ancestry informative SNPs.We were also interested in comparing the potential resolution to which YHG assignments can be made, given the available ISOGG SNPs targeted by YMCA and 1240 k. We also found that the resolution of a YHG call cannot be improved, even when including a 120 bp tiling window around the ~ 32 k Y-SNPs of the 1240 k assay, according to the ISOGG SNPs occurring in the respective bed files. This holds true both for dominant YHGs today and in particular for those that are associated with known ancient populations, but that have significantly reduced in frequency in modern populations, and which are not well covered for diagnostic SNPs on the 1240 k assay.17, and the Neolithic expansion-associated G-Z3820232 and H-P96, for which the Y-SNPs of the 1240 k assay target 0.8%, 0% and 13% of the associated ISOGG SNPs, respectively . If we include a 120 bp window, then these percentages increase to a more respectable 32.5%, 31.2% and 36.2%, which are still much lower than the 89.6%, 90.6% and 95.2% of SNPs targeted by YMCA  of the relevant diagnostic SNPs covered, compared to 92% for YMCA.We often observe low resolution in haplogroups such as the early hunter-gatherer haplogroup C-V20To summarize, YMCA enriches the relative proportion of reads mapping to the NRY, when compared to shotgun sequencing and the 1240 k assay. YMCA also targets more than 2.5 times as many sites on the NRY than the 1240 k assay, allowing for the detection of new diagnostic SNPs. Critically, however, YMCA targets SNPs which are already known to be informative, but the 1240 k assay cannot target.Through routine application of SG sequencing for sample screening, followed by 1240 k capture for suitable samples in our lab, we were able to explore the performance of the new YMCA on a range of YHG in ancient male individuals. Here, we showcase an example of YHG H-P96, for which the resolution of the evolutionary tree is still unclear due to the scarcity of data and low frequency in modern-day populations. Judging from our current ancient DNA record, it appears that YHG H was more common in the past, in particular among males that were associated with the spread of farming across Western Eurasia during the Neolithisation. As a result, we can show that aDNA research, and in particular high-resolution typing of YHG, can help elucidate the evolutionary relationship of Y chromosome lineages past and present.34. Three subsequent sub-haplogroups, H1 (H-M69), H2 (H-P96) and H3 (H-Z5857), appear to have quickly formed over the following 4000 years. H1 and H3 have estimated formation times of ~ 44.3 kya, however, H2 is estimated to have formed slightly earlier at ~ 45.6 kya [https://www.yfull.com].The YHG H (H-L901) is thought to have formed in South Asia approximately ~ 48 kya35, but in extremely low frequencies in Europe, with H1 only being found associated with the spread of the Romani people ~ 900 ya. Conversely, H2 has been present in Western Eurasia since at least 10 kya36, and is strongly linked with the spread of agriculture38, but is found at no higher than 0.2% frequency in modern-day western European populations. In contrast, H2 was more common in Neolithic groups, and has been found to have constituted between 1.5 and 9% of the observed Y haplogroups, with the exception of the highly related individuals from Rivollat et al. 2020, for which H2 was ~ 30%41.Haplogroups H1 and H3 are still found in frequencies as high as 20% in South Asia19, and although H2 was never found in particularly high frequencies among Neolithic individuals, we expect that its diversity was also greatly reduced, and many sub-lineages were potentially lost altogether.With the arrival of Steppe-related ancestry ~ 5 kya, incoming YHGs such as R1a and R1b would largely replace many of the older, “Neolithic” YHGs, such as G2, T1a, and H237, it is precisely the low frequency of H2 which is of interest here. The relative scarcity of H2 individuals, especially compared to the relatively high frequency of the accompanying G2a individuals, allows us to better track the ‘genealogical history’ and thus potential dispersal routes as we would expect a stronger effect of lineage sorting and therefore a higher chance of observing geographic patterns. In this particular case, we could trace expanding Neolithic farmers from Anatolia to Western Europe through the use of unique markers associated with H2 individuals and test whether we can genetically discern the proposed so-called “Danubian or inland'' and “Mediterranean'' routes of the Neolithic expansion42, which had recently also found support by genomic signals from the nuclear genome38.To test whether our YMCA could improve the haplotyping quality to a point which would allow us to also draw phylogeographic inferences, we made use of newly collated collection of prehistoric ancient human DNA data and selected individuals, who were tentatively assigned to YHG H2. We generated new data for n = 49 individuals, and merged this with n = 46 published Y-chromosomal genomes , and, in many cases, inconsistent with a tree-like history for almost all of the published and unpublished ancient samples. In all but one case that we found that H2 individuals carry a mixture of derived SNPs from two bifurcated clades in the current ISSOG topology, such as from H2a1 and H2b1. Encouraged by the performance of the YMCA presented above, we thus analysed further H2 individuals in an attempt to resolve the branching pattern of this lineage.For a non-recombining portion of DNA, the evolutionary history is expected to follow a tree-like structure, and therefore hybrids of sibling haplogroups  are impossible. To try and find a better resolved evolutionary history for these individuals, we constructed a maximum likelihood (ML) phylogenetic tree using IQ-TREE see “”. We ideBased on our extended set of diagnostic SNPs, we were able to assign n = 58 of our individuals to either one of these two sub-clades, or  H2* (due to low coverage), even for those who did not meet minimum coverage requirements to be included in the ML tree, which also provides bootstrap support for individual clades Fig. A. Finall45 could potentially explain this single geographically outlying observation.When we plotted all of the samples in our study on a map of Europe, a phylogeographic pattern clearly emerged . Our estimated TMRCA for H2 was ~ 24.1 kya, which is slightly older than the current estimate of ~ 17.1 kya, and which could be explained by our extremely limited access (only one) to high-coverage modern H2 samples, as well as our increased number of ancient samples (https://www.yfull.com).Due to the incomplete and varying coverage of our ancient samples, we were unable to produce a reliable, calibrated tree for divergence time estimates using the radiocarbon dates of ancient samples as tip dates. Instead we estimated the time since the most recent common ancestor (TMRCA) for each pair of individuals to investigate the split times for our newly identified H2 clades see “. First, We found that the estimated TMRCA for H2d and H2m was ~ 15.4 kya. We also found that H2m and H2d had estimated TMRCAs of ~ 11.8 and ~ 11.9 kya .The analysis of the Y-chromosomal history of populations can be of significant importance to the understanding of population histories. To this end we advocate for the adoption of targeted sequencing strategies for ancient Y-chromosomal sequence data. Our focused study highlighted the improved coverage and number of SNPs that are attainable when using YMCA, when compared to SG or 1240 k sequencing, for the same amount of sequencing effort, accounting for endogenous human DNA content.Targeted endogenous human DNA enrichment is of critical importance to overcome poor sample preservation in ancient DNA studies. We have shown that the Y-SNPs of the 1240 k assay ascertained from modern-day males simply do not cover enough of the diagnostic SNPs on the NRY for reliable Y-haplogroup assignment, especially in the case of haplogroups that predate modern diversity, highlighting a need for targeting contiguous regions in favour of an updated “Y-chromosome SNP panel”. YMCA can be applied to the same libraries that are used for other captures and require no additional extractions or library preparations. While it is certainly possible to combine YMCA with other captures assays (which we have not attempted), we argue that a bespoke YMCA of selected male samples in a directed study might outweigh that of a routine combined application  with additional sequencing effort.We were also able to show, through a deeper analysis of H2 (H-P96), that the current understanding of ancient H2 diversity is incompatible with a tree-like history (which must be true for NRY history), and that a resolution of this diversity leads to further support for the two paths of the Neolithic expansion from the Near East into Europe; an observation that would not have been possible without the improved resolution offered by YMCA. We foresee future applications in the study of Y-chromosomal sub-structure in Eurasian hunter-gatherers  or to better characterise the R1a/R1b diversification of Bronze Age Western Eurasia, Central and South Asia.49.Note that for Y-haplogroup assignment, tree building and SNP identification, we use a mix of shotgun, 1240 k, and YMCA capture sequencing runs. However, to estimate the TMRCA, we use only shotgun and YMCA data as they do not target known segregating sites (which would upwardly bias the substitution rate for samples with 1240 k capture compared to those with shotgun and YMCA data only). Previously published samples were selected from published data with “H2” designated for Y haplogroupsmale source, it would be readily noticeable in bam pileups as derived alleles for another haplogroup, which means these samples would not have been identified as H2, and hence would not be in the study.To screen our samples for contamination, we consider the heterozygosity for sites on the NRY as our in-house samples are all merged and filtered for sites on the Y-chromosome only. We measured heterozygosity (the proportion of sites with more one than one type of base read per site) for a pileup of the quality filtered reads. We found that 47 of our 49 samples had less than 0.1%, with the remaining 2 samples 1% and 1.85% heterozygous sites. However, we were also confident in the quality of our samples as H2 is a very rare modern haplogroup, with only 19 individuals being downstream of H2-P96 on YFull at the time of this publication. Hence, if any of our samples had been contaminated by a pileup function in the Rsamtools library for the R statistical software package. We then filter this pileup of SNPs found on the ISOGG list (https://isogg.org/tree), and then for each SNP we calculate and record the number of derived and ancestral SNP calls, the form of the ancestral and derived SNPs, and the difference . Note that a positive difference indicates evidence for the ancestral form of the associated ISOGG SNP, and a negative difference indicates the converse. Recording the form of the called SNPs (i.e. C to T or G to A transitions), allows us to identify where DNA damage could have caused us to infer false calls.To assign Y haplogroups to samples we follow a partially-automated process. We begin by taking trimmed, merged, deduplicated, quality-filtered bam files, and, for each bam file, creating a pileup of every site that was covered using the We return two CSVs: one CSV of only ISOGG SNPs with positive differences , and a second CSV of all SNPs (negative or positive) allowing us to double check potentially spurious SNPs . This second CSV also allows us to discover when some SNPs are derived and some are ancestral for the same branch, indicating a transitional form of the basal haplogroup.Finally, in cases where we are uncertain of the dependability of a call (say a C to T transition with only one read), we also manually inspect where the site falls on the associated read(s), placing increased trust in SNP calls originating further from the terminal ends of a read.When comparing the empirical performance of our Y-capture assay to both shotgun and 1240 k sequencing, we took libraries for which shotgun, 1240 k and Y-capture sequencing had all been performed. All samples were prepared and analysed using the same methods and parameters values as for the main data set.To compare the theoretical performance of YMCA against the 1240 k assay, we downloaded the ISOGG SNP list v15.64. We then took the bed files for the NRY and 1240 k assay, and found which sites overlapped with the SNP son the ISOGG SNP list.When comparing empirical data performance for shotgun, 1240 k and YMCA data, we included only samples that had shotgun endogenous DNA greater than 0.1 %, had sequencing results for shotgun, 1240 k and YMCA sequencing, and then normalized the number of SNPs covered by the number of reads mapping to the human reference (hs37d5) after quality filtering. We did this to avoid any potential bias from sample quality or sequencing effort.We began by taking pileups of each bam file, and performing the following quality filters for calling a consensus alignment; for each sequence we considered only sites for which we had at least two reads, with a minimum allele frequency less than 10%, and called the majority allele. We then took the aligned consensus sequences, and kept only samples for which at least 1100 segregating sites were covered, and then filtered sites for which more than at least one sample was covered. We selected a lower bound of 1100 segregating sites by varying this value, and inspecting bootstrap node support values. A minimum bootstrap support for major cladal splits of 80% was required.50 from Y-haplogroups A, H1, H2 and H3, as well as one ancient H1 sample46 as outgroups.We also included high-coverage samples from the 1000 Genomes Project51 and selected the transversion model (TVM) as it had the minimum Bayesian information criterion value. We found a maximum likelihood tree using IQ-TREE v.1.5.552.We performed DNA substitution model selection using ModelFinderSupplementary Information 1.Supplementary Information 2.


Rhizoctonia solani relies on the continuous identification of resistance genes to allow their integration into new and modern cultivars. Better control of the disease may thus be achieved by a combination of tolerant or resistant cultivars selected based on molecular markers such as SNPs. The utility of one such marker, RsBv1 , located in an ADP-ribosylation factor and associated with Rhizoctonia resistance resulting from validation of three geographically diverse plant materials is reported.Sustainable breeding of sugar beet against Rhizoctonia solani, causing Rhizoctonia crown and root rot, is a major risk to sugar beet (Beta vulgaris L.) cultivation. The development of resistant varieties accelerated by marker-assisted selection is a priority of breeding programs. We report the identification of a single-nucleotide polymorphism (SNP) marker linked to Rhizoctonia resistance using restriction site-associated DNA (RAD) sequencing of two geographically discrete sets of plant materials with different degrees of resistance/susceptibility to enable a wider selection of superior genotypes. The variant calling pipeline utilized SAMtools for variant calling and the resulting raw SNPs from RAD sequencing  were able to explain 13.40% and 25.45% of the phenotypic variation in the two sets of material from different sources of origin, respectively. An association analysis was carried out independently on both the datasets and mutually occurring significant SNPs were filtered depending on their contribution to the phenotype using principal component analysis (PCA) biplots. To provide a ready-to-use marker for the breeding community, a systematic molecular validation of significant SNPs distributed across the genome was undertaken to combine high-resolution melting, Sanger sequencing, and rhAmp SNP genotyping. We report that RsBv1 located on Chromosome 6  is significantly associated with Rhizoctonia resistance (p < 0.01) and able to explain 10% of the phenotypic disease variance. The related SNP assay is thus ready for marker-assisted selection in sugar beet breeding for Rhizoctonia resistance. Rhizoctonia solani which is recurrent and perennial in all sugar beet production areas and causes the typical root and crown rot. Symptoms can range from localized brown to black lesions on the root surface to complete rotting of the root. Symptoms are also characterized by sudden wilting of the leaves and black lesions on the petioles attaching to the crown area. The extent of the damage it causes and the yield losses vary in sugar beet farms and are considerable and dramatic [Sugar beet cultivation, contributing to ~20% of the world’s sugar production, is distressed by different pathogens. One such fungal pathogen is the soil-borne fungus, dramatic ,2,3,4. Sdramatic ,2,3.R. solani was initiated and substantial improvements in Rhizoctonia resistance were achieved with germplasm releases FC701 and FC702 [R. solani. Yet another accession, FC 712 (Reg. no. GP-97) was registered in 1985 as a source of resistance to R. solani [Rhizoctonia resistance [Rhizoctonia resistant lines in sugar beet [Rhizoctonia solani was shown [One of the most direct and economical management strategies is breeding varieties for genetic resistance. Growers are strongly advised to control the disease by combining agronomic measures such as long crop rotations  and using resistant varieties adapted to the production areas ,5. In thnd FC702 ,7,8. In nd FC702 . These t. solani . Along wsistance . Consequgar beet ,16,17,18gar beet . Newly, gar beet . Althouggar beet  have beeas shown . This clRhizoctonia resistance. Single nucleotide polymorphisms (SNPs) identified through DNA sequencing are the most robust and abundant co-dominant markers for mapping genes affecting traits of interest in crop plants [Rhizoctonia resistance in sugar beet germplasm. The increasing use of affordable and high-throughput technologies such as next-generation sequencing (NGS) allows the discovery of panels of SNPs appropriate for the identification of allelic combinations linked to agronomic traits that are functionally advantageous in breeding programs [The development of disease resistance-linked markers can substantially aid the breeding programs for p plants ,25. SNP programs ,27. Partprograms . While tprograms ,30.Rhizoctonia resistance tested in several international sugar beet germplasm. Firstly, we carried out restriction site-associated DNA (RAD) sequencing on geographically diverse breeding materials, from Iran and Germany, with different degrees of resistance/susceptibility. Subsequently, a joint bioinformatics analysis of the sequencing data along with efficient bioinformatics pipelines resulted in the identification of contributing loci distributed across the sugar beet genome. Finally, a wide molecular validation strategy on diverse plant material was used for cross-validation of the identified SNPs in many individual sugar beet plants and worldwide reference Rhizoctonia-resistant cultivars. Our marker assay resulted in the development of RsBv1 for marker-assisted breeding programs of disease resistance and cultivar release.In this study, we report the discovery and validation of useful SNP associated with The plant material provided by the Sugar Beet Seed Institute (SBSI), Iran, comprised 42 S1 (self-pollinated), 27 pollinator lines, 18 three-way cross hybrids, and 5 single-cross hybrids . This geRhizoctonia resistance/susceptibility. Ten lines including the five highest resistance and five highest susceptible lines of this breeding material were sequenced using RAD sequencing.The second germplasm tested was plant material provided by Strube Research, Germany, and comprised a collection of 62 breeding lines with a broad genetic diversity in terms of Rhizoctonia were provided by the SBSI, Iran. These were used for rhAmp genotyping of RsBv1. Melindia , Moliere , and Octopus  provided by COPROB, Italy were used as resistant checks. A CMS line and an O-type from susceptible background provided by the Department of Agronomy, Animals, Natural Resources and Environment (DAFNAE), Padova University, Italy, used for screening through HRM and Sanger sequencing and rhAmp validation of RsBv1. Three plants per line, for a total of 186 plants belonging to the 62 breeding lines of Strube Research, were randomly selected for rhAmp validation of RsBv1.The plant material provided by USDA consisted of a highly resistant check (FC709-2), a moderately resistant check (FC703), and a susceptible check (FC901/C817). The rating for symptoms (Ruppel score between 0 and 7) was determined based on field experiments of three replicated plots consisting of 8 plants each from the year 2018. The phenotyping data are also shared in Rhizoctonia inocula were prepared from a highly aggressive isolate of R. solani (AG-2-2-IIIB (R9)). The isolate selected for this study was provided by SBSI. An inoculum of the fungus R. solani was developed by growing strain R9 on corn grains for 3 weeks at 25 °C. Seven weeks after sowing, inoculation of plants was performed through the addition of six infested corn grains to the soil around the plant crown area following a previously described method [Rhizoctonia symptoms was performed for each plant. The commercial hybrids Jolgeh introduced by SBSI, Iran, and Kermit  were used as susceptible and resistant checks, respectively. Rating disease symptoms on the roots were performed following a nine-class disease scale [The experimental site was located at the Hamedan Agricultural and Natural Resources and Education Centre, Hamedan, Iran and the field trials were carried out in the year 2017–2018. Seeds of each genotype were directly sown in two 2-m long rows. The soil texture was sandy loam enriched. Fertilizer requirement was determined based on soil analysis. Weed control was performed manually and no herbicide was used. Plants in each plot were thinned down to 20 plants in each row at the four to the six-leaf stage of sugar beet growth. d method . In the Rhizoctonia inocula were prepared from a highly aggressive isolate of R. solani  developed on barley grains. Eight weeks after sowing, inoculation of plants was performed through the addition of infested barley grains to the soil around the plant crown area following an internal protocol. The experiment was set up as an incomplete randomized block design with two susceptible and two resistant checks included. A total of 3370 plants were tested in two greenhouses on seven tables and 168 trays each consisting of 20 plants where at least one check was included in the tray. The experiment was conducted in summer under controlled conditions with the following parameters: day temperature: 24 °C, night temperature: 20 °C, air humidity: 80%, air humidity during inoculation: 100%, photoperiod 6:00 to 22:00, light intensity: 15,000 lux). No fungicides were applied. Rating disease symptoms occurred two weeks after inoculation on the roots of single plants based on the percentage of infected roots. The scoring scale was adopted from a recently published study [Rhizoctonia scoring were calculated for each line with a mixed linear model to correct the effects from greenhouses, tables, and trays. The means for percentage infection were then converted to the ten-class disease scale [A collection of 62 lines chosen from the O-type and pollinator breeding programs of Strube Research were phenotyped in a greenhouse using 50 plants per line in summer 2019. ed study . AdjusteLeaves from plant materials listed in p < 0.05) was selected as preliminary candidates. The genotype matrix of 0 , 1 , 2  was analyzed to assess the contributions of the selected SNPs in the separation of phenotypes using PCA biplots. They were developed using the FactoMineR package in R [Variant calling was performed individually on the two datasets from SBSI and Strube Research and adapted from the earlier published method . The pipage in R  and furtFlanking sequences of 150 bp around the target SNP were extracted using the bedtools getfasta tool (version 2.28.0). The list of sequences was given as input to the stand-alone version of the Primer3 software (version 4.0) to design primers with suitable amplicon lengths. The HRM analyses were carried out in 384 well plates on the QuantStudio 12K Flex . Reactions were carried out according to a previously described method . The melFlanking sequences of 250 bp around the target SNP were extracted using the bedtools getfasta tool (version 2.28.0). The list of sequences was given as input to the stand-alone version of the Primer3 software (version 4.0) to design primers with suitable amplicon lengths. The reaction setup and PCR cycling conditions were adopted from an earlier study from our lab . The ampValidated SNPs from Sanger sequencing were used to design rhAmp assays . Sequences of the SNP are presented in For the germplasm from Strube, Germany, the distribution of disease scores of two-three randomly chosen plants from 46 parental lines are shown in p < 0.05). A total of 297 significant SNPs mutually occurring between the two datasets (Iran and Germany) are shown using circular Manhattan in The total number of raw SNPs upon mapping to EL10 reference genome were 15,988 and 24,439 for the SBSI and Strube Research germplasms, respectively. The association analysis resulted in the selection of candidate SNPs differing significantly in their allelic status and discriminating the sample groups . For two different vectors (a sample and a SNP), samples in each direction from the origin have positive interactions for SNPs in the same direction. Samples present in the opposite directions of SNPs have negative interactions for those SNPs. Thus, the influences are larger when a sample or SNP is farthest from the origin. Similarly, samples near the origin have the smallest influences from all SNPs and likewise for SNPs present near the origin.The contributions of the individuals (sequenced samples of SBSI and Strube Research) and variables (significant SNPs) are shown in A subset of SNP candidates was studied for its contribution in discriminating resistance/susceptible phenotypes from the bioinformatics analysis that were subsequently screened using high-resolution melting (HRM) analysis. Rhizoctonia resistant phenotype, a genotyping assay was developed to screen larger germplasm from other sources.Sanger sequencing of the promising SNP candidates from preliminary validation based on HRM, incorporating all tested checks from USDA with biological replicates resulted in the confirmation of RsBv1 being able to distinguish the two groups. The resistant material was predominantly showed the C allele in the homozygous form whereas the susceptible material had the T allele in the homozygous form at position 9,000,093 bp on chromosome 6 . To furtRhizoctonia resistance allowed us to correlate the marker genotypes obtained for 157 plants from 62 breeding lines with their disease scores obtained from the adjusted means of the percentage of infection . From the adjusted R2 of the model, the marker RsBv1 explained 10.99% of the phenotypic variation. As the heterozygous group was small (only six cases), we also did a t-test for the adjusted means between C and T (excluding the heterozygous genotypes), which showed a significant difference (p < 0.01). Both these results indicated that the marker is significantly associated with Rhizoctonia.Additionally, a generalized linear model which was run to see the association between the adjusted means and the marker genotypes showed that the marker is significantly associated with We further compared the marker genotypes with the phenotypic bioassay data and the genetic background of the tested lines. Among the 62 tested lines, the marker genotypes of 35 lines fit their bioassay data and genetic background while the marker genotypes of 16 lines did not fit for their bioassay data and/or genetic background. Eleven lines were unknown because they either lacked an SNP call or genetic background. Therefore, the matching correction rate predicted by the marker RsBv1 was calculated as 35/(35 + 16) × 100 = 68.6%.Rhizoctonia resistance was further confirmed on additional germplasm from USDA and SBSI (p < 0.05). Thus, Rhizoctonia resistance could be linked to the higher frequency of the C allele in the RsBv1 position.The association of RsBv1 with and SBSI . The bolRhizoctonia solani, the most severe soil-borne disease of sugar beet is complex due to the interplay between several host-pathogen factors and the environment. It is therefore possible that different genes confer resistance in diverse germplasm due to genetic heterogeneity. The quantitative nature of resistance with additive effects of both major and minor genes has been shown in other crops [Rhizoctonia infection.The genetic basis of resistance to er crops . Thus, tRhizoctonia resistance using two sets of geographically diverse germplasm from Iran and Germany (206 plants from 32 genotypes) to initiate the identification of SNP markers using RAD-seq. One of the foremost factors determining the success of marker discovery and association study is the plant material and the phenotyping variation. Here, although we used geographically diverse germplasm, a priorly established phenotyping method formed the basis for the study . It is worth mentioning that the strain for inoculation (AG-2-2-IIIB), growth cycle, and scoring based on the percentage of infected roots were comparable among the locations  genes that reduced susceptibility to fungal pathogens [to R. solani infection in wheat, ADP-ribosylation factor emerged as one of the targets [Analysis of genomic context of the identified RsBv1 showed that it is located in an intron of the gene coding for ADP-ribosylation factor 2 . ADP-ribathogens . In yet  targets . While t targets .Rhizoctonia resistance as a panel.One of the fundamental goals of breeding programs is the development of robust markers for marker-assisted selection and the release of resistant cultivars. The RsBv1 marker identified and largely validated in this study allows for rapid screening of multiple genotypes providing alternatives to labor-intensive phenotyping methods. The utility of one such valuable and robust marker was demonstrated through validation on diverse germplasm with both quantitative and qualitative phenotypes and using multiple SNP detection technologies providing an advantage to breeders interested to incorporate molecular selection tools. In addition, the association study resulted in the identification of key SNPs due to the sequencing of geographically diverse germplasm. Each or all of these candidate SNPs reported in this study can be used in the wide screening of


Shiraia. NO donor sodium nitroprusside (SNP) was used as a chemical elicitor to promote hypocrellin biosynthesis in Shiraia mycelium cultures.Nitric oxide (NO) is a ubiquitous signaling mediator in various physiological processes. However, there are less reports concerning the effects of NO on fungal secondary metabolites. Hypocrellins are effective anticancer photodynamic therapy (PDT) agents from fungal perylenequinone pigments of 2−) and hydrogen peroxide (H2O2). Gene ontology (GO) analysis revealed that SNP treatment could up-regulate biosynthetic genes for hypocrellins and activate the transporter protein major facilitator superfamily (MFS) for the exudation. Moreover, SNP treatment increased the proportion of total unsaturated fatty acids in the hypha membranes and enhanced membrane permeability. Our results indicated both cellular biosynthesis of HA and its secretion could contribute to HA production induced by SNP.SNP application at 0.01–0.20 mM was found to stimulate significantly fungal production of perylenequinones including hypocrellin A (HA) and elsinochrome A (EA). SNP application could not only enhance HA content by 178.96% in mycelia, but also stimulate its efflux to the medium. After 4 days of SNP application at 0.02 mM, the highest total production (110.34 mg/L) of HA was achieved without any growth suppression. SNP released NO in mycelia and acted as a pro-oxidant, thereby up-regulating the gene expression and activity of reactive oxygen species (ROS) generating NADPH oxidase (NOX) and antioxidant enzymes, leading to the increased levels of superoxide anion (OThe results of this study provide a valuable strategy for large-scale hypocrellin production and can facilitate further understanding and exploration of NO signaling in the biosynthesis of the important fungal metabolites.The online version contains supplementary material available at 10.1186/s12934-021-01581-8. Shiraia bambusicola P. Hennings is a bambusicolous fungus parasitized on bamboo tender twigs and its fruiting bodies have been used in traditional Chinese medicine to stimulate blood circulation, relieve expectoration, cure rheumarthritis and relax muscle rigidity [Shiraia fungi, have being developed as new non-porphyrin and reactive oxygen species (ROS)-generating photosensitizers in photodynamic therapy (PDT) for clinical application of anti-microbes, -cancers and -viruses [Shiraia mycelium culture has become a promising production process of this new PDT agent [Aspergillus niger at 50 µg/mL [S. bambusicola was also observed in extractive culture of Shiraia by Triton X-100 [rigidity , 2. Hypo-viruses , 3, 4. D-viruses , ShiraiaDT agent . More prDT agent , and appDT agent , 9 or abDT agent , 11. Nit50 µg/mL  and a fu50 µg/mL . The endon X-100 .Echinacea purpurea roots [Artemisia annua hairy roots [Taxus yunnanensis cells [Coniothyrium minitans [Colletotrichum coccodes conidia were significantly inhibited by SNP at 100 µM [A. nidulans, suggesting a positive regulator of NO on fungal sexual development [Inonotus obliquus with Phellinus morii and triggered the biosynthetical pathway of phenylpropanoids, leading to an increased production of styrylpyrone derivatives [Ganoderma lucidum [S. bambusicola treated by fungal elicitors [Shiraia hypocrellin biosynthesis. We also investigated the relationship between NO and elicitation responses including ROS generation, the activation of antioxidant defenses and hypocrellin production in Shiraia mycelium cultures. In this study, de novo transcriptome sequencing for Shiraia sp. S9 was performed for better understanding the NO regulation on hypocrellin biosynthesis. This study presented a novel elicitor of hypocrellin production and shed light on the relational roles of NO on the biosynthesis of secondary metabolites.NO is an important regulatory molecule in mammals . Recentlea roots , artemisry roots , and taxis cells . Howeverminitans . Wang ant 100 µM . A NO-reelopment . Zhao etivatives . SNP at  lucidum . Althouglicitors , 12 and licitors , the reglicitors , 25 and licitors , 26, we Shiraia mycelia, whereas the relative fluorescent ration was markedly decreased by NO scavenger 2-(4-carboxyphenyl)-4, 4, 5, 5-tetramethylimidazoline-1-oxyl-3-oxide (cPTIO), indicating the release of NO in hyphae  in -DA in ShShiraia [As HA is a major bioactive hypocrellin constituent in Shiraia , we optiShiraia sp. S9 after SNP treatment, RNA-Seq experiment was subsequently performed. There were altogether 84,275 unigenes assembled with an average length of 1,011.81 bp (base pairs) and an N50 of 5,399 bp , conidial yellow pigment biosynthesis polyketide synthase , hydroxyindole-O-methyltransferase , FAD dependent oxidoreductase , phenol hydroxylase , cytochrome P450 CYP2 subfamily , fasciclin  , ABC superfamily , secondary metabolites biosynthesis, transport and catabolism  (Table MFS (TRINITY_DN33647_c1_g1_i8) from 2.40- to 7.31-fold was confirmed by qRT-PCR , followed by C3H (12 DEGs), and MYB (11 DEGs)  and diphenyleneiodonium (DPI), an inhibitor of ROS generating enzyme NADPH oxidase (NOX) for 30 min prior to SNP application, the relative intensities of fluorescence in mycelia exhibited much more notable reduction of 72.39% and 72.14%  in mycelia was induced rapidly around 30 min of SNP treatment, reaching a highest value of 6.47 µmol/g FW (fresh weight) with time up to day 7, which was 59.14% higher than that of control  concentration were consistent with O2− production. The generation of H2O2 was strikingly increased from 9.12 to 11.75 µmol/g FW after 2–4-day treatment of SNP and then decreased on day 7–9, but it was still higher than those of the control group , ‘oxidoreductase activity’ GO:0016491), ‘electron carrier activity’ (GO:0009055) and ‘oxidoreductase activity, acting on paired donors, with incorporation or reduction of molecular oxygen’ GO:0016705) items , methylation, decarboxylation and reduction by O-methyltransferase (Omef), monooxygenase/hydroxylase (Mono/Hyd) and multicopper oxidase (MCO), and then the core structure formation via the cooperation of fasciclin (Fas), laccase and berberine bridge enzyme (BBE) [SbaPKS indicated its essential role in the hypocrellin biosynthesis of Shiraia sp. SUPER-H168 [SbaPKS also had a moderating effect on the transcriptional expression of its adjacent genes FAD, Omef, Mono and MCO in the gene cluster. Overexpression of Hyd gene in S. bambusicola S4201 resulted in ultra-higher production of HA (1180.1 mg/L) [Hyd (59.35-fold) and PKS (14.59-fold) genes 2Cys6 (or C6 zinc) binuclear cluster DNA-binding domain is located in the hypocrellin gene cluster. However, zftf is not the differentially expressed gene induced by SNP treatment  , 43, 44.PER-H168 . SbaPKS .1 mg/L) . Most ofCercospora fungi for the auto-resistance [MFS) were up-regulated significantly  (2.40- to 7.31-folds) after SNP application  for hypocrellin production was obtained from fresh Shiraia fruit-body in our previous work [The strain ous work . The strous work . The seeSNP  was dissolved in deionized water at 0.50 mM as a stock solution and filtered through a sieve (Ø0.22 μm) before use. To determine the optimal dosage of SNP for hypocrellin production, different dosages (0.01–1.00 mM) of SNP were added into the cultural broth on day 3. To confirm the effect of the addition time, 0.02 mM SNP was added into the mycelium culture on day 1–5 respectively.Shiraia sp. S9 mycelia, the NO-specific fluorescent probe DAF-2-DA  was applied [The medium pH of the cultural broth was detected with pH Meter , and the residual glucose in cultural broth was measured using anthrone-sulfuric acid method . To dete applied . After 3 applied . After 2Shiraia sp. S9 during the solid medium culture, the colony diameter was measured in triplicates (3 objects in a replicate). Photos were taken on day 6. To investigate the influence of SNP on fungal development, the 8-day-old colony was eluted with 10-mL deionized water. Subsequently, the fungal morphological characteristics were observed and photographed by a light microscope . To observe the influence of SNP on fungal growth during the submerged culture, SNP at 0.10 mM was added into the cultural broth on day 3. The mycelia were harvested and dried to constant weight at 60 °C to assess fungal biomass. The fungal pellets were viewed and photographed under a stereoscopic microscope . Pellet diameters were measured in triplicates (50 pellets per replicate).To analyze the effect of SNP (0.01–1.00 mM) on growth and morphological changes of The membrane permeabilization of hyphal cell was detected by SYTOX Green dye, a high-affinity nucleic acid stain fluorescent probe  . After 5The components of mycelial fatty acids were extracted and analyzed via the protocols given in our previous report . The det2O2 and O2− in the mycelia were assayed as previously described [The ROS generation in hyphal cell was detected by DCFH-DA  probe, which could penetrate the cell membrane freely . After 2escribed , 55. Theescribed –58.To study the effects of ROS signal during the culture of S9 strain by SNP, Vc and DPI were used as ROS scavenger and NOX inhibitor, respectively. The concentrations of ROS scavenger and NOX inhibitor used in this work were chosen based on previous research . Vc  database with a cut off E value of ≤ 1e−5. The raw RNA-seq data have been submitted to NCBI’s Gene Expression Omnibus (GEO) repository under accession number SRR7293200-7293205. In our study, we calculated the relative expression levels of genes via the fragments per kilobase per million reads (FPKM) method described by Mortazavi et al. [p value < 0.05.In this study, six samples with or without SNP treatment were obtained from three biological replicates (independent experiments) to establish cDNA libraries. Then, the HiSeq X Ten platform  was applied to sequence above cDNA libraries. The raw reads were cleaned and assembled according to our previous report . All unii et al. . Meanwhi−△△CT method described in detail by Zhang et al. [Total RNA was extracted using RNAprep pure Plant Kit  according to the instruction. The primer sequences of 18S ribosomal RNA  and selected unigenes from NCBI database of SRR7293200-7,293,205 and PRJNA323638 were listed in Additional file t-test was applied for the comparison of the means between two groups. One-way analysis of variance (ANOVA) test was used for the comparison of the means among multiple groups. p < 0.05 is considered statistically significant.Data analyses were carried out using Microsoft Excel and expressed as Mean ± Standard Deviation (SD). Student's Additional file 1: Table S1. Illumina RNA-Seq reads and de novo assembly statistics of Shiraia sp. S9 by SNP. Table S2. Summary statistics of unigene annotation numbers of Shiraia sp. S9 by SNP. Table S9. Primers and relevant information of reference and target genes. F: forward primer, R: reverse primer. Figure S1. Effect of SNP at 0.10 mM on the growth and development of Shiraia sp. S9 in submerged culture. Time profiles of fungal biomass (A) and average pellet diameters (B) during the production culture. Figure S2. Time profiles of pH (A) and residual sugar (B) in Shiraia sp. S9 submerged cultures with the addition of SNP at 0.10 mM. Figure S3. Chromatograms of PQs in mycelium of Shiraia sp. S9 treated by SNP (0.10 mM) on day 3 and cultivated for 8 days. Figure S4. Effect of SNP concentration on (A) hyphal growth, (B) HA content in mycelium and (C) the released HA in cultural broth of Shiraia sp. S9. The strain was treated by SNP (0.01–1.00 mM) on day 3. Figure S5. Effect of SNP addition time on (A) hyphal growth, (B) HA content in mycelium and (C) the released HA in cultural broth of Shiraia sp. S9. SNP (0.02 mM) was added on different cultural time (1–5 d). Figure S6. The length distribution of unigenes of Shiraia sp. S9 by SNP. Figure S7. Heat map of DEGs summary of Shiraia sp. S9 by SNP. The up/down-regulated DEGs were detected by comparing RNA-Seq data of the unigenes of case group to control group . Figure S8. The cellular component (CC), biological process (BP) and molecular function (MF) of gene ontology (GO) categories of the DEGs in Shiraia sp. S9 under SNP treatment at 0.02 mM. The arrow represents the time of SNP addition. Values are mean ± SD from three independent experiments (**p < 0.01 vs. control). Different letters above the bars mean significant differences (p < 0.05).Additional file 2: Table S3. Annotation of DEGs using NR, SWISS-Prot, KEGG, KOG and GO databases and their fold change with SNP treatment. Table S4. GO enrichment of Shiraia sp. S9 with SNP treatment. Table S5. Differentially expressed genes (DEGs) involved in hypocrellin biosynthesis of Shiraia sp. S9 under SNP treatment. Table S6. Differentially expressed genes (DEGs) involved in hypocrellin transport of Shiraia sp. S9 under SNP treatment. Table S7. Annotation of transcription factors in Shiraia sp. S9. Table S8. Differentially expressed genes (DEGs) involved in transcription factors of Shiraia sp. S9 under SNP treatment.


Anthocyanin biosynthesis is one of the most studied pathways in plants due to the important ecological role played by these compounds and the potential health benefits of anthocyanin consumption. Given the interest in identifying new genetic factors underlying anthocyanin content we studied a diverse collection of diploid potatoes by combining a genome-wide association study and pathway-based analyses. By using an expanded SNP dataset, we identified candidate genes that had not been associated with anthocyanin variation in potatoes, namely a Myb transcription factor, a Leucoanthocyanidin dioxygenase gene and a vacuolar membrane protein. Importantly, a genomic region in chromosome 10 harbored the SNPs with strongest associations with anthocyanin content in GWAS. Some of these SNPs were associated with multiple anthocyanin compounds and therefore could underline the existence of pleiotropic genes or anthocyanin biosynthetic clusters. We identified multiple anthocyanin homologs in this genomic region, including four transcription factors and five enzymes that could be governing anthocyanin variation. For instance, a SNP linked to the phenylalanine ammonia-lyase gene, encoding the first enzyme in the phenylpropanoid biosynthetic pathway, was associated with all of the five anthocyanins measured. Finally, we combined a pathway analysis and GWAS of other agronomic traits to identify pathways related to anthocyanin biosynthesis in potatoes. We found that methionine metabolism and the production of sugars and hydroxycinnamic acids are genetically correlated to anthocyanin biosynthesis. The results contribute to the understanding of anthocyanins regulation in potatoes and can be used in future breeding programs focused on nutraceutical food. Solanum tuberosum L.) is the main non-cereal food consumed worldwide [S. tuberosum L. species, the Group Phureja is composed of diploid potatoes (2n = 2x = 24) with short-day adaptation and a lack of tuber dormancy that are widely grown by local farmers in the Andes mountains range of South America. Landraces from the Andes were the first domesticated potatoes and the main origin of cultivars, developed after the colonization of America and grown in most of the rest of the world today [Potato , P (purple) and D/I (developer or inhibitor) loci, which map to chromosomes 2, 11, and 10, respectively [R and P loci govern red and violet pigmentation in tubers while D/I is responsible for the intensity of pigmentation [R and P loci code for two enzymes of flavonoid biosynthesis, DFR [I corresponded to a regulatory gene encoding the TF R2R3 MYB, which has a high similarity with the product of the Petunia hybrida AN2 on chromosome 10 [StAN1, StMYBA1 and StMYB113) [StJAF13 and StbHLH1) [StWD40) [In potatoes the synthesis of anthocyanins was initially described as being controlled by the ectively –30. R anentation –30. Latesis, DFR  and F3’5sis, DFR , which aosome 10 . This geosome 10 . Recentlosome 10 , 34, 35 tMYB113) , 21, 36 StbHLH1)  and one [StWD40) .The pattern of anthocyanin composition across tissues and genotypes is controlled by multiple genes , 19. GenPrevious genetic studies of anthocyanin pigmentation in potato tubers conducted using biparental populations of potato identified a small number of QTL which explained from 8% to 11% of the phenotypic variation , 51, 52.Solanum tuberosum Group Phureja from the Universidad Nacional de Colombia (CCC) was employed for the GWAS using information partially published in previous studies [The Working Collection of Potato Breeding Program of  studies . Briefly studies .In order to do functional analyses, we expanded the SNP matrix used to run the GWAS in previous studies . The ori® [2) by using TASSEL software [The GWAS was conducted for each anthocyanin compound using a compression mixed linear model (CMLM)  applied ® . The pri® . The Ben®  using a software .prior biological information about the biosynthesis of anthocyanins to pre-select a subset of candidate genes. We searched in the literature for structural and regulatory genes involved in anthocyanin production in the Solanaceae family. We made use of a study that identified flavonoid orthologs in multiple Solanaceae species [https://www.ncbi.nlm.nih.gov/), KEGG (https://www.genome.jp/kegg/), Spud (http://solanaceae.plantbiology.msu.edu/), and BioCyc (https://biocyc.org/) genomic databases. In order to identify homologs of these anthocyanin genes in the potato genome we performed a BLASTx (v2.6.0) [−20. We then retrieved SNPs located ± 100 Kb of these genes and ran again the GWAS with this subset of SNPs. We used a relatively large window of 100 Kb in order to get multiple SNPs associated with the genes. The p-values within each gene were recalculated with the new subset of SNP markers and inputted to corrected for multiple testing using the approach reported by Benjamini and Hochberg [p-value value among all SNPs mapped to a gene as the p-value of the gene [We used  species . We also(v2.6.0)  of the s(v2.6.0) , 64 and Hochberg , based othe gene , 66. Thehttps://phytozome.jgi.doe.gov/pz/portal.html#!info?alias=Org_Stuberosum) and KEGG (https://www.genome.jp/kegg/pathway).We used the PAST software  to condup-value < 0.05 were selected based on thresholds set for gene association and effect values of the genes.SNPs were assigned to genes based on LD information and a distance of 1,500 bp from the tagSNP . StatistWe used the TASSEL software to conduct a phylogenetic tree of the populations using the Neighbor Joining algorithm and two inputs: (1) All SNPs used in GWAS and (2) significant SNPs from Chromosome 10. We also used Tassel to conduct principal components analysis (PCA) using the covariance option and the same sets of SNPs.TASSEL was used to calculate the Tajima D statistic using the sliding window option . SNPs falling in the upper and lower 1% percentiles of the distribution were considered candidates for balancing and positive selection respectively .Phytophtora infestans [The potato population used in our study has also been rated for other agricultural and nutritional important traits like macronutrients , sugars nfestans . We wereIn this study we exploited previous research on the Work Collection of Potato Breeding Program from Colombia  to underChloroplast threonine deaminase 1 (PGSC0003DMG400017604) and the STS14 (PGSC0003DMG400017597) genes. Chloroplast threonine deaminases are the first enzymes in the biosynthesis of the amino acid isoleucine but also mediate plant defenses against pathogens and herbivores [Our results confirmed the significant SNPs reported by Parra-Galindo  and idenrbivores . STS14 brbivores  AlthoughLeucoanthocyanidin dioxygenase gene ; a position on Chromosome 1 located in a R2R3-MYB transcription factor ; and a SNP on chromosome 6 linked to the Vacuolar membrane protein . Firstly, LDOX enzyme, also known as anthocyanidin synthase, catalyzes the conversion of leucoanthocyanidins to anthocyanidins, the precursors of anthocyanins [LDOX genes are located on QTL for anthocyanin variation in Chromosomes 8 and 9. However, there are no reports of anthocyanin QTL in the genomic region of Chromosome 11 containing the LDOX gene reported in our study. Secondly, R2-R3 MYB transcription factors showing homology with Petunia AN2 gene (Borevitz2000) regulate anthocyanin biosynthesis in dicotyledonous plants [StAN1, StAN2 and StFlAN2. The Myb12 TF detected in this study has not been linked to anthocyanin production in potatoes but it´s orthologs regulate anthocyanin production in other plants like Arabidopsis thaliana [Vacuolar membrane protein PEP3 is an interesting candidate because this gene is involved in vacuole organization [We highlight three newly detected associations from our expanded SNP set involving polymorphisms located within putative anthocyanin biosynthetic genes ; a SNP oocyanins . Previouocyanins , 75 founs plants –80. A nus plants , 37, incthaliana , apple [thaliana , lily [8thaliana , 84, andthaliana . FinallyBy expanding the number of genetic markers evaluated in this potato population and analyzing the function of genes underneath the most associated markers from GWAS we were able to identify potential determinants of anthocyanin variation in potatoes that were not detected in previous studies. Given that causal genes might be in the vicinity of significant SNPs we searched for anthocyanin homologs in broader QTL regions.anthocyanin homologs ; leucoanthocyanidin dioxygenase (LDOX); cinnamoyl-coA reductases (CCR1); 4-coumarate: CoA ligase (4CL1); 1-O-acylglucose:anthocyanin-O-acyltransferase enzyme (CtSCPLAT1); and chalcone synthase enzyme (CHS) [CHS enzymes located within anthocyanin QTL have been identified in tomato  [Seven structural genes showed significant associations in this analysis . In Fig me (CHS) . CCR is me (CHS)  and downme (CHS) . The 4-cme (CHS)  while thme (CHS) . CHS enz, TCHS2)  and pota, TCHS2) . Finally, TCHS2) .phenylalanine ammonia-lyase homolog (PGSC0003DMG400031365) in chromosome 10 is particularly interesting because it is linked to the most significant SNPs that display associations to the five anthocyanins measured. The association of a PAL homolog to all anthocyanins makes sense biochemically because the PAL enzyme catalyzes the first reaction in the phenylpropanoid biosynthetic pathway [A. thaliana, mutations in the two isoforms of PAL gene cause a reduced production of all anthocyanins [PAL genes but only the homolog identified in our study has been previously associated with variation in anthocyanin content. For instance, Liu and colleagues [A  pathway , which l pathway –95. For ocyanins . Within lleagues  found thlleagues .PAL gene, in a region of 4 Mb in the extreme of Chromosome 10 . These SNPs were linked to anthocyanin regulatory genes, namely StFlAN2 (PGSC0003DMG400019217) and WRKY 13 (PGSC0003DMG400010987) (PhAN2). On the other hand, WRKY 13 is orthologous with TRANSPARENT TESTA GLABRA 2 from Arabidopsis and PhPH3 from petunia, which control the transcription of structural genes responsible for anthocyanin biosynthesis as well as ion pumps that determine the pH of vacuoles, where anthocyanins are stored [StFlAN2), a BHLH TF (JAF13) and a WRKY TF (WRKY 13). Furthermore, the orthologs of these genes interact to control anthocyanin production and storage in other plant species [Importantly, eight significant SNP markers were located near the 0010987) . It was e stored : a MYB T species . These rMany of the QTL identified in studies of anthocyanin variation simultaneously govern variation in multiple anthocyanin compounds , 76, 99.PAL gene, four putative 7-O-linked N-acetylglucosamine transferases, an oxidoreductase, a WRKY transcription factor, and at least three Myb transcription factors . This indicates that recombination is not reduced at this site and that different significant SNPs from GWAs are located within different haplotypes   .It is likely that the genetic basis of anthocyanin variation differs across individuals from our panel. To evaluate whether potatoes with high anthocyanin content shared alleles at the loci governing anthocyanin variation, we analyzed the genomic variation of significant SNPs from GWAS using phylogenetic and multivariate analyses. We found that the genotypes at significant SNPs from Chromosome 10 do not fully separate plants with high and low anthocyanin content , S2 Fig.PAL gene catalyzes the first step in the phenylpropanoid pathway and therefore could be a pleiotropic gene whose expression or/and sequence affects the production of anthocyanins located downstream in the biosynthetic pathway. Intriguingly, PAL is located nearby three pleiotropic transcription factors that govern the production of multiple anthocyanins StAN1, StAN2 StflAN2. Another candidate from Chromosome 10 that could pleiotropically control multiple anthocyanins is the WRKY 13 TF [Pleiotropy and genetic clustering are common genomic patterns in specialized metabolism –105. BotKY 13 TF . It shouPAL gene [The clustering of genes from the same route has been reported in many specialized metabolism pathways and it is proposed as a mechanism to synchronize gene expression or to maintain favorable allelic combinations in the face of recombination , 104. DePAL gene  as well PAL gene  and MYB PAL gene , 64, 110PAL gene , which sPAL gene  and tomaPAL gene , perhapsPhylogenetic analyses of the genomic region containing this group of anthocyanin genes suggest that multiple alleles or allelic combinations were involved in the creation of potato landraces with high anthocyanin content. Interestingly, a study of historical European samples shows a drastic reduction of genetic diversity and negative values of Tajima´s D in this genomic region . The aut also has been associated with anthocyanin production in fruits [We found an enrichment of genes involved in biosynthesis of methionine and sugars and the degradation of spermidine and spermine. An association between the biosynthesis of the amino acid methionine and anthocyanin has been previously reported in many plants –117. Forn fruits . Stimulan fruits , 121. Thn fruits . Finallyn fruits , is derin fruits , 124. PaPAL gene. We also found significant correlations between the levels of anthocyanins with tuber content of HCAs . This correlation is not surprising given that HCAs are chemically conjugated to anthocyanins and anthocyanin-linked HCAs are frequently reported in red skin or flesh of potato tubers [We analyzed phenotypic variation for multiple agronomically important traits to identify pathways associated with anthocyanin production. We first evaluated pairwise correlations  between o tubers , 126.P. infestans and sugars content. We also identified positions in chromosomes 1, 2, and 6 governing simultaneously anthocyanins and other traits  from a GWAS are plotted against physical position (DM_v4.04_pseudomolecules) on each of 12 chromosomes.(TIF)Click here for additional data file.S2 FigPrincipal components analysis of all SNPs used in the GWAS. The color of each dot indicates the total anthocyanin content (arithmetic sum of the five anthocyanins) for each plant.(PDF)Click here for additional data file.S1 TableFor each polymorphic site we present the diploid genotype of the 96 accessions used.(XLSX)Click here for additional data file.S2 TableAnalyses were run with GAPIT using an array of 47,298 SNP markers.(TXT)Click here for additional data file.S3 TableCalculated with Tassel for the 47,298 SNP markers evaluated in 96 potato genotypes.(TXT)Click here for additional data file.S4 TablePutative anthocyanin genes retrieved from the literature.(XLSX)Click here for additional data file.S5 TableGWAS was run using only SNPs mapped within ± 100 Kb of 108 anthocyanin homologs.(XLSX)Click here for additional data file.S6 TableGenome-wide association of 5 anthocyanin compounds in SNPs located nearby a pre-selected set of 108 candidate genes.(XLSX)Click here for additional data file.S7 TableFor each marker we calculated the maximum distance in bp to markers associated with a minimum correlation (r2) of 0.8.(XLSX)Click here for additional data file.S8 TableResults from the PAST software using GWAS results and gene annotation from the PotatoCyc and KEGG databases.(XLSX)Click here for additional data file.S9 TablePairwise correlation between traits previously evaluated in this population, namely anthocyanin, macronutrients, sugars, Hydroxycinnamic acids (HCAs), and resistance to late blight.(TXT)Click here for additional data file.S10 TableNumber and density of anthocyanin homologs across non-overlapping 1 Mb intervals.(TXT)Click here for additional data file.S11 TableTASSEL was used to calculate Tajima’s D statistic as well as genetic diversity (pi and theta) using a sliding window . SNPs falling in the upper and lower 1% percentiles of the distribution were considered candidates for balancing and positive selection respectively.(TXT)Click here for additional data file.


The pleiotropic SNPs/haplotypes, overlapping genes , and homozygous/biallelic SNPs and transcription factors (HTH myb-type and BHLH) hold great potential for improving wheat yield potential on sodic-dispersive soils.−2. These SNPs correspond to HTH myb-type and BHLH transcription factors, brassinosteroid signalling pathway, kinase activity, ATP and chitin binding activity. These resources are valuable in haplotype-based breeding and genome editing to improve yield potential on sodic-dispersive soils.Sodic-dispersive soils have multiple subsoil constraints including poor soil structure, alkaline pH and subsoil toxic elemental ion concentration, affecting growth and development in wheat. Tolerance is required at all developmental stages to enhance wheat yield potential on such soils. An in-depth investigation of genome-wide associations was conducted using a field phenotypic data of 206 diverse Focused Identification of Germplasm Strategy (FIGS) wheat lines for two consecutive years from different sodic and non-sodic plots and the exome targeted genotyping by sequencing (tGBS) assay. A total of 39 quantitative trait SNPs (QTSs), including 18 haplotypes were identified on chromosome 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 5A, 5D, 6B, 7A, 7B, 7D for yield and yield-components tolerance. Among these, three QTSs had common associations for multiple traits, indicating pleiotropism and four QTSs had close associations for multiple traits, within 32.38 Mb. The overlapping metal ion binding  and photosynthesis genes and transcription factors  identified are known to be highly regulated during germination, maximum stem elongation, anthesis, and grain development stages. The homozygous/biallelic SNPs having allele frequency above 30% were identified for yield and crop establishment/plants mThe online version contains supplementary material available at 10.1007/s00122-021-04021-8. Wheat is one of the most important cereals in human diets and plays a significant role in feeding global population, which is expected to increase by 30%  soils are common in the Australian agricultural landscapes and wheat growing regions around the world. Recent estimates show about 8–10% soils in Western Australian grain belt to be dispersive leading to heavy losses in production and grower income , NDVI values (N), heads m−2 (HM), grains head−1 (GH), 1000 grain-weight (TGW), and harvest index (HI) on sodic and non-sodic soils in FIGS wheat set, (2) conduct GWAS to identify significant and pleiotropic quantitative trait SNPs (QTSs) and haplotypes, contributing to tolerance to sodic-dispersive soils, and (3) identify tolerance associated candidate genes and their functional characterisation, transcription factors and expression status at various wheat developmental stages. The significant and pleiotropic QTSs and haplotypes involved in multi-trait expression and overall grain development will provide information about collaborative gene-networks and genetic mechanisms involved in tolerance on sodic dispersive soils in wheat, which can be deployed in breeding programs and/or genome editing.Focused Identification of Germplasm Strategy (FIGS) is an effective tool to discover new genes for useful traits in crop plants. It uses machine-learning algorithms to match geographic and agro-climatic characteristics of the site of original collection with target trait to identify desirable genes and alleles (FIGS-ICARDA The study employed a set of 206 diverse hexaploid wheat lines (Table S1), comprising 190 FIGS lines from 24 countries and 16 Australian check cultivars. These wheat lines from around the world are tolerant to subsoil challenges such as high salinity and pH. Majority of FIGS lines are land races, selected based on the prevalence of subsoil constraints in their place of origin and thus reflect natural selection under target environments , Western Australia, for two years (2018 and 2019). The sodic and non-sodic sites in both years were within 1 km to ensure uniform climatic conditions  for the comparison. The soil type of sodic belongs to clays and shallow loamy duplexes, while the non-sodic site was a deep sandy duplex. Soil analysis for the natural fertility and macro- and micro-nutrients content of both sites from 0–10, 10–30 and 30–70 cm depth is presented in Table −2 (PM) was measured at five-leafed stage (Zadoks GS 13). GreenSeeker NDVI  values (N) were taken at booting stage (Zadoks GS 49). The instrument was manually held 25 cm above the crop canopy, and each plot NDVI value was averaged over 20 data points. At physiological maturity (Zadoks GS 94), shoot biomass samples from a sub-set of plots (1 m2 of 4 × 1.5 m2) were collected and dried in an air-forced dryer at 60 °C for 48 h and weighed to estimate biomass per m2. These samples were used to assess yield components: heads m−2 (HM), grains head−1 (GH), thousand grain-weight (TGW), and harvest index (HI). Grain yield (YD) was measured by combine-harvesting the entire experimental plot. Phenotypic data analyses were done using the ASReml-R package (R Core Team 2) was calculated following Bonneau et al.  assay designed to target SNPs evenly distributed across the genome (every ~ 1 Mb) using exome SNP identified from the globally diverse hexaploid wheat collection described in He et al.. Paired-GWAS was performed on wheat association panel using phenotypic data collected from two years (2018 and 2019). PCA and kinship analysis was conducted using inbuilt R functions under Genome Association and Prediction Integrated Tool (GAPIT) version 3. The scree plot was used to determine optimum number of principal components (PCs) (Bayesian information criterion) in Q model and kinship heatmap was used to analyze genetic correlation among 206 diverse FIGS wheat lines (Wang and Zhang R2) between SNP marker pairs and the graphical representation of R2/linkage disequilibrium (LD) against genetic distance (Mb) between the markers was produced using GAPIT package in R.LD among pairs of SNP markers within and across the three wheat genomes  was estimated as a squared allele frequency correlation  SNP hit, LD analysis was performed on every chromosome where significant quantitative trait SNPs (QTSs) were detected. False discovery rate (FDR) correction (q < 0.10) was performed using Benjamini–Hochberg method to select significant SNPs  as the  y-axis.Association mapping was performed using TASSEL v5  on respective chromosome were searched using BLASTN program, against the Ensembl Plants  and UniParc (https://www.uniprot.org/uniparc/) to obtain more information including protein domain, family, molecular and biological functions of the potential candidate genes. Further, the key features of the domain and InterPro annotation were searched in pfam and Prosite to check the characteristics of the protein. Additionally, alternative splicing variants, variant consequence and SIFT score for the identified genes were determined. The gene ontology (GO) and gene expression levels at various developmental stage were obtained from QuickGo and gene expression atlas, respectively.The SNP position on the reference genome was combined with the chromosome number to identify genes and gene ontology associated with sodic-dispersive tolerance. The overlapping genes or genes found close to the significant targeted SNPs (2) from the mixed models are presented in Table S2. Data for HM, GH and TGW for 2018 trial are not available. Comparison of the magnitudes of genetic variances at the two soil types (S2non-sodic vs. S2sodic) revealed a greater variation in YD, TGW and HI at the sodic site. Within-year variance comparison for PM and HM showed opposite trends in both years albeit in opposite order; the variance of PM was less than HM on non-sodic than sodic site in 2018 and the vice versa in 2019. Correlation coefficients between trial sites were high and positive for all traits in both years. Moderate to high broad-sense H2 was estimated for YD, N, and PM for both the years. However, H2 was low for HM, GM, TGW and HI. The plot of sodic blups against non-sodic blups was used to determine ICT for each trait. The slope b in Table S2 was used to calculate ICTs for each trait.The soil test comparison of sodic and non-sodic sites revealed higher levels of exchangeable cations on sodic site including toxic levels of boron (B), manganese (Mn) and sodium (Na) and favourable levels of nutrients–potassium (K), calcium (Ca) and magnesium (Mg) Table . HoweverThe genetic diversity based in 206 FIGS wheat lines from 24 countries is shown in radial dendrogram Fig. a. The whR2 = 1.0), followed by genomes D (R2 = 0.96) and A (R2 = 0.78). In the present t-GBS assay, D genome (17%) had the lowest number of SNPs followed by genomes A (38.1%) and B (44.8%) (Table S3). The LD decay was rapid in A genome, followed by B and D genome.The analysis of linkage disequilibrium (LD) showed that the LD decayed with the genetic distance in A, B and D genomes Fig. . The aveP < 0.005) for each SNP, using F test for the null hypothesis that a SNP has no effect on the measured trait. Plots of the negative logarithmic estimates of the observed against expected p values (Q-Q plots) showed that the MLM with (Q + K) matrix represented a good model fit and accounted for relatedness between wheat lines, minimising false positives and improving the marker-trait associations estimates . The scree plot generated by plotting the percentage of variances explained by optimal number of PCs from GAPIT  associated with ICTs of YD, PM, N, HM, GH, TGW, and HI, respectively. The significant threshold was then adjusted by setting the P ≤ 0.005 and q < 0.10. The cut-off threshold p values for the traits with FDR correction were YD – 2.9E-03; PM – 1.1E-03; N – 2.2E-03; HM – 5.2E-04; GH – 1.3E-03; TGW – 8.4E-04; HI – 2.6E-03. This reduced the number of significantly associated SNPs to 21 for YD ICT, 18 for PM ICT, 5 for N ICT, 5 for HM ICT, 7 for GH ICT, 5 for TGW ICT, and 12 for HI ICT (Table S4).The MLM analysis generated a significance value , Indel, favourable alleles, and their effect identified for two years are presented in Table 10(P) value above 2.5 and PVE% in range of 17.8–4.1. Five haplotypes, having more than one SNP within 200 bp on respective chromosome were detected for YD4 (1B): 94,828,187–94,828,277, YD5 (1B): 411,775,338–411,775,423, YD7 (3B): 817,580,012–817,580,066, YD9 (5A): 613,704,427–614,358,933, and YD10 (7B): 148,015,309–148,015,372. The QTSs for YD1 and YD7 are homozygous biallelic and the genotypic effects on yield ICT are presented in Fig. The association analysis for YD ICT revealed strong associations Table  on chrom10(P) value above 3.0 and PVE% in the range of 39.1–8.0. Four haplotypes were detected on QTSs PM2 (1B): 53,737,652–53,737,716, PM4 (2A): 63,307,274–63,307,383, PM5 (3A): 502,921,633–502,921,779, and PM10 (7D): 566,251,264–566,251,365. Two QTSs PM4 (2A) and PM7 (6B) had significant impact on wheat establishment on sodic-dispersive soil with PVE% of 24.2 and 37.6, respectively. The QTSs PM1, PM3 and PM7 are homozygous biallelic having higher additive effect for wheat establishment  value above 2.5 and PVE% in the range of 9.1–7.2. A haplotype was detected on chromosome 7A at QTS N4 (7A): 696,574,393–696,574,479. The QTS N3 on chromosome 6B at 694,681,316 had minor allele frequency of 0.47 with PVE% of 8.5 and this QTS corresponds to a gene TraesCS6B02G426300, having photoreceptor activity, highly expressed during stem elongation and flowering stage.The association analysis for PM ICT revealed ten QTSs on chromosomes 1A, 1B, 1D, 2A, 3A, 3B, 6B, 7B and 7D, with − log10(P) value above 2.5 and PVE% in the range of 9.6–3.1. A haplotype was identified for HM ICT on chromosome 1D (HM1). This haplotype has five SNPs between 356,142,294 and 356,142,422, which is within 128 bp with a minor allele frequency of 0.45 and PVE% of 9.6. This genomic region overlaps with the gene TraesCS1D02G262200, involved in metal ion binding and transcription regulation, and is highly expressed during germination, flower opening stage and maximum stem elongation. Three haplotypes were identified for GH ICT on chromosome 2B, 2D and 5D. The haplotype on chromosome 2B overlaps with the gene TraesCS2B02G067500, which is pleiotropic for YD and HI and encodes for dirigent protein, highly expressed during stem elongation. Likewise, four QTSs were identified for TGW ICT on chromosome 1A, 3B and 6B. The QTS TGW3 on chromosome 6B at 638,828,274 corresponds to a gene TraesCS6B02G366100 which has two splice variants and is involved in RNA polymerase II cis-regulatory sequence specific binding. This gene is highly regulated 14 days after anthesis. The haplotype QTSs TGW4: 640,352,471–640,352,516, is 1.52 Mb apart from TGW3: 638,828,274 on same chromosome 6B. Seven QTSs were identified for HI ICT on chromosome 1A, 2B, 5D, 6B, and 7A. The haplotypes were identified on chromosome 2B , 5D , 6B , and 7A . The overlapping genes on chromosome 1A, 6B, and 7A have metal ion and nucleic acid binding and translation activity and these genes are highly expressed during anthesis, post-anthesis and maximum stem length. The gene TraesCS7A02G213400 caused missense mutation with a deleterious SIFT score of 0.01, inducing an amino acid change from valine to methionine. Most of the QTSs identified for TGW and HI ICT had rare variants MAF < 0.05  confirmed the suitability of testing conditions for phenotypic differentiation of tested germplasm. The opposite trend of within-year variance comparison between the two sites for PM and HM (comparison available only in 2019), aligned with the concept of compensation for yield components in setting sink size  Table . These rPhytohormones, protein kinase and chitin-binding activities play a significant role in alleviating stress in sodic-dispersive soils. The present association study revealed significant additive effects with greater phenotypic variance (PV) for the QTS corresponding to phytohormones, kinase and chitin binding activities Table . The QTSThe sodic-dispersive sub-soils have high levels of exchangeable boron and manganese cations Table . The metPlant-specific transcription factors play a critical role in plant growth and development. The metal ion binding genes identified for QTSs HM1 and HI7 encodes for PHD-type domain protein and Dof-type domain proteins, respectively, which has transcriptional regulatory activities for plant growth and development  are plant-specific blue copper proteins involved in electron transport  with greater additive effects explaining large phenotypic variance (PVE% > 10) were identified which may contribute significantly to the yield and wheat establishments on sodic-dispersive soils. The in silico gene expression analyses revealed that genes are highly expressed during germination, stem elongation, anthesis, and grain development and are involved in metal ion exclusion, photosynthesis, and transcription regulation. The pleiotropic SNPs, haplotypes, transcription factors and overlapping genes identified in the present study provide new potential targets for genetic improvement of wheat on sodic-dispersive soils.In most crop genomes, the exome corresponds to only 1–2% of the entire genome. The gene-associated t-GBS platform had SNPs tagging key trait loci in A, B and D genomes of wheat. The array served as an invaluable resource for inferring significant and pleiotropic QTSs, transcription factors, homozygous/biallelic SNPs with significant additive effects contributing to the trait expression, overlapping genes with expression status at various wheat developmental stages, and haplotype diversity in a globally diverse wheat germplasm. The common and distinct haplotype detected for several agronomic trait expression could simplify study of the genetic basis of complex tolerance expression to sodic-dispersive soils. It can be noted that most of the candidate genes identified for yield and yield-components have higher expressions during germination and early growth stages and these SNPs can be deployed in crop improvement programs. The significant homozygous biallelic codominant markers reported in the present study can be potentially converted to KASP markers for high throughput marker-assisted selection, reducing time, cost, and error rates. Alternatively, CRISPR base-editing tool can be used to bring about favourable allele editing, improving the tolerance and yield potential on sodic-dispersive soils.Supplementary file1 (XLSX 14 KB)Supplementary file2 (DOCX 104 KB)Below is the link to the electronic supplementary material.