:D Genetic Preservation :D - Breeding

[acespicoli]

https://www.icmag.com/members/djzed.11016/#recent-content

@pipeline

DJ Short and Legends Seeds

• Flo »»» Floral Line F2 x Floral Line F2 F5,6

The Seedsman was a f7 from the orig parental line

 

[pipeline]

Cool, thank you! Does Dutch Passion offer Blueberry in regular seeds? Website says regular is out of stock, but most of their stock in other varieties is auto or fem.

Will look into Flo. Thanks for sharing that Potcast, and DJShort's screen name. I am following him now!

 

[acespicoli]

Flo is a Sativa/Indica cross (60% Sativa / 40% Indica) with very Sativa phenotypic characteristics that also matures very early. The large, tight, spear-shaped buds are made up of small, densely packed purple calyxes. The plants are taller and like to branch out.

Indoors the buds are fully mature by the end of their sixth week. Outdoors the plant is a super producer when multi-harvested over a period of time. The first buds are ripe around the third week of September. About every ten days after that, new buds form and can be harvested through the end of November, if the plant can be kept alive that long. Therefore, Flo is ideal for greenhouse production.

The motivational high produced by the Flo is quite unique; the flavor is like Nepalese Temple Hash. A most pleasant and enjoyable experience. Rated #1 strain at Cannabis Cup `96 by Cannabis Canada Magazine.

 

[acespicoli]

Cool, thank you! Does Dutch Passion offer Blueberry in regular seeds? Website says regular is out of stock, but most of their stock in other varieties is auto or fem.

Will look into Flo. Thanks for sharing that Potcast, and DJShort's screen name. I am following him now!

Read his ic info the thread on parental plants!
Not sure what DP has but id prefer the reg as well. in usa multiverse has seeds from dp
dude over there is cool!

I like tivas up motivational vibe, the dj strains are tasty!
One of the prettiest strains imo, bb nice nugs
I would def do the flo again, let me know if you find some regs
Compare some notes on those
Didnt you find some Purple Thai some where OPT

 

[acespicoli]

The non-recreational hemp (Cannabis sativa L.) industry, particularly the cannabidiol sector, is expanding rapidly. Commercial growers and researchers are shifting to sterile triploids to avoid pollen contamination from male hemp plants grown nearby. As such, producers need reliable and efficient methods to clonally propagate industrial hemp on a large scale. Hemp is propagated either by seed (Potter, 2009), by stem cuttings (Caplan, 2018), or in vitro (Lata et al., 2017).

 

[pipeline]

Yeah Seth who goes by the screen name Socioecologist owns Oregon cbd I think it was. He was talking about this project a couple years ago. He was doing some serious breeding programs to achieve these breeding goals first. I think the sterile plants is one he was working on, also he developed hemp with 0% THC. Will have to look up the thread. I think he's no longer a member though.

 

[acespicoli]

 

[acespicoli]

Cannabis gets its high-inducing power from ancient viruses​

A new genome map reveals that the genes for THC and CBD production probably came from viral DNA.


By Neel V. Patel | Published Nov 30, 2018 6:00 PM EST

• Health

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There are a variety of reasons why us humans enjoy cannabis, but they typically boil down to one of two things: THC (tetrahydrocannabinol), the psychoactive component, that gets you high as a bird; and CBD (cannabidiol), predominantly sought after for its medicinal effects in treating conditions like epilepsy, and potentially other health benefits. As it turns out, you can thank millions of years ago viruses for gifting cannabis the ability to produce these two chemicals.


In the latest issue of Genome Research, a group of North American scientists have, for the first time ever, published a full map of the cannabis genome. Among the myriad of interesting insights to glean from the chart is the finding that the genes that encode for THC and CBD production evolved thanks to bits of DNA introduced by viruses that infected the plant and successfully colonized its genome millions of years ago.


Other new insights from the map include the discovery of the gene responsible for CBC (cannabichromene—one of the cannabinoids found in marijuana) production, the differentiation of hemp and marijuana (the former produces mainly CBD, while the latter is full of THC), and clues into what might make different cannabis more potent and robust than others.


“One of the problems with breeding in cannabis has been the resources associated with looking at the genome,” says Todd Michael, the Director of Informatics at the J. Craig Venter Institute in La Jolla, California, who was not involved with the study. A lot of the work thus far has sort of involved a trial-and-error process of breeding random strains with one-another, without much knowledge of what particular genetic traits will transfer. “A resource like a genetic map is really like the starting point for high quality breeding, for any plant” says Michael. “All really important crops need these.”


But in the past, obstacles have plagued the development of such a map for cannabis. Legislation has barred researchers from readily studying and experimenting with the plant, even in controlled laboratory settings. On top of that, it’s inherently difficult to map the cannabis genome, thanks to its relatively large size. The larger the genome, the harder it is to categorize, which is why it took so long for scientists to map and make sense of the human genome. The difficulty in sequencing and assembling the cannabis genome was compounded by the viral elements. See, both THC and CBD are made by synthase genes that are found on the same chromosome. But those synthase genes are swarmed by garbled chunks of DNA called retrotransposons, which came from—you guessed it—viruses. Over time, those millions of infectious DNA elements multiplied and spread throughout the genome. The THC and CBD synthase genes are firmly nested in those elements.


It seems the THC and CBD synthase genes came from a single gene, and the viral retrotransposons, as they jumped around and expanded, drove the mutation of the synthase gene sequences in different cannabis strains, spurring the divergence of the gene into THCA (producing THC) in marijuana, and CBDA (producing CBD) in hemp. Michael suggests the transposable elements may have been capable of carrying and moving the synthase gene around itself as they jumped throughout the genome.


The team behind the paper previously published a draft of the genome in 2011, although it was too fragmented to show where specific genes were located on chromosomes. Another genetics firm revealed a cannabis genome map in February, but have not yet published the findings.


According to Michael, having the genome finally fully mapped is going to be “revolutionary” for the cannabis industry. Industry experts will have a much easier time pinpointing what traits to select for in order to yield strains that are easier and faster to grow. But besides turning cannabis into a better growing crop, the genome map should also having significant impacts on fine tuning a strain’s ability to produce THC, CBD, and the hundreds of other cannabinoids specific to cannabis.


“Having a genetic map combined with a high quality genome could possibly enable scientists to target specific pathways, especially for people interested in the psychoactive components of cannabis,” says Michael. For example, you could modify the terpene profile in cannabis to modulate the high you get from the plant. You could also change what sort of smells the plant produces. Armed with the map of the genome, researchers could even use a tool like CRISPR to directly edit those features at the genetic level.


While the role of ancient viral elements in the evolutionary history of THC and CBD production is a neat insight, to most scientists, it’s not all that surprising. “In general, this is basically how plants evolve,” says Michael. “I’m not really sure why the media has picked up on this so aggressively.” Researchers have long known that retrotransposons have viral origins. “We know that genome size in plants is almost 100 percent due to the expansion of retrotransposons. This isn’t anything new. And we know they play a large role in the evolution of plants.”


Instead, Michael argues the more critical insights from the paper have to do with illustrating what genes may or may not be active, since that will give researchers a better understanding of what points are worth tinkering around with and what areas ought to be avoided.


Michael is particularly excited about the future of high-CBD products as a substitute for opioids. “We’ve got a huge opioid epidemic,” he says, “and it’s been shown that CBD, and THC, can play a role in managing pain.”


Ultimately, the new genome map is sure to spur a host of new work in recreational and medicinal cannabis applications. “There is a lot of great work that’s coming out,” says Michael. “In the next year we’re going to see a lot of really fantastic things in cannabis genomics.”

Cannabis gets its high-inducing power from ancient viruses - Google Search

 

[pipeline]

DJ Short Seeds - Blue V-2 (16 reg seeds) - Great Lakes Genetics

DJ Short Seeds - Blue V-2. Genetics: Flo TF x Thai-side FL/FK. Seeds in pack: 16 regs

www.greatlakesgenetics.com

 

[pipeline]

The Pot Cast

A Cannabis podcast for budding enthusiasts. Long-form cannabis content focusing on breeding, growing, history and culture. [email protected]

soundcloud.com

The Potcast Episode 94 Kevin Jordey Pt1 interview discusses is experience working with Phyllos and inside information about their company.

Available only to Patreon Subscribers now--Recently Released by @Heavy Dayze

 

[acespicoli]

Cannabis is a
Dioecious, Obligate Outcrosser,
Cannabis sativa L. (hemp, marijuana) produces male and female inflorescences on different plants (dioecious) and therefore the plants are obligatory out-crossers.

Heterozygous,
having two different alleles of a particular gene or genes.
"the genetic study showed two heterozygous variants"

Have questions???

Statistical genetic considerations for maintaining germ plasm collections
J. Crossa , C. M. Hernandez , P. Bretting , S. A. Eberhart , S. Taba
Theor Appl Genet (1993) 86:673-678
DOI: 10.1007/BF00222655
Theor Appl Genet

• 
  
• 
  

. 1993 Jul;86(6):673-8.
doi: 10.1007/BF00222655.

Statistical genetic considerations for maintaining germ plasm collections​

J Crossa 1 , C M Hernandez, P Bretting, S A Eberhart, S Taba
Affiliations

• PMID: 24193775
• DOI: 10.1007/BF00222655

Abstract​

One objective of the regeneration of genetic populations is to maintain at least one copy of each allele present in the original population. Genetic diversity within populations depends on the number and frequency of alleles across all loci. The objectives of this study on outbreeding crops are: (1) to use probability models to determine optimal sample sizes for the regeneration for a number of alleles at independent loci; and (2) to examine theoretical considerations in choosing core subsets of a collection. If we assume that k-1 alleles occur at an identical low frequency of p0 and that the k(th) allele occurs at a frequency of 1-[(k-1)p0], for loci with two, three, or four alleles, each with a p0 of 0.05, 89-110 additional individuals are required if at least one allele at each of 10 loci is to be retained with a 90% probability; if 100 loci are involved, 134-155 individuals are required. For two, three, or four alleles, when p0 is 0.03 at each of 10 loci, the sample size required to include at least one of the alleles from each class in each locus is 150-186 individuals; if 100 loci are involved, 75 additional individuals are required. Sample sizes of 160-210 plants are required to capture alleles at frequencies of 0.05 or higher in each of 150 loci, with a 90-95% probability. For rare alleles widespread throughout the collection, most alleles with frequencies of 0.03 and 0.05 per locus will be included in a core subset of 25-100 accessions.



Methodologies for estimating the sample size required for genetic conservation of outbreeding crops.
Crossa, J.
Theoretical and Applied Genetics, 77(2). (1989).
doi:10.1007/bf00266180

Summary​

The main purpose of germplasm banks is to preserve the genetic variability existing in crop species. The effectiveness of the regeneration of collections stored in gene banks is affected by factors such as sample size, random genetic drift, and seed viability. The objective of this paper is to review probability models and population genetics theory to determine the choice of sample size used for seed regeneration. A number of conclusions can be drawn from the results. First, the size of the sample depends largely on the frequency of the least common allele or genotype. Genotypes or alleles occurring at frequencies of more than 10% can be preserved with a sample size of 40 individuals. A sample size of 100 individuals will preserve genotypes (alleles) that occur at frequencies of 5%. If the frequency of rare genotypes (alleles) drops below 5%, larger sample sizes are required. A second conclusion is that for two, three, and four alleles per locus the sample size required to include a copy of each allele depends more on the frequency of the rare allele or alleles than on the number. Samples of 300 to 400 are required to preserve alleles that are present at a frequency of 1%. Third, if seed is bulked, the expected number of parents involved in any sample drawn from the bulk will be less than the number of parents included in the bulk. Fourth, to maintain a rate of breeding (F) of 1 %, the effective population size (N e) should be at least 150 for three alleles, and 300 for four alleles. Fifth, equalizing the reproductive output of each family to two progeny doubles the effective size of the population. Based on the results presented here, a practical option is considered for regenerating maize seed in a program constrained by limited funds.

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Three hundred ten alleles were identified, and the major allele frequency ranged from 0.26 to 0.85 (average: 0.56)

Genetic Diversity and Population Structure of Cannabis Based on the Genome-Wide Development of Simple Sequence Repeat Markers - PMC

Cannabis has been used as a source of nutrition, medicine, and fiber. However, lack of genomic simple sequence repeat (SSR) markers had limited the genetic research on Cannabis species. In the present study, 92,409 motifs were identified, and 63,707 ...

www.ncbi.nlm.nih.gov

 

[dogzter]

Odd how with all the "knowledge" written and theories bandied about until they became facts we still don't have any actual stable "strains".

 

[acespicoli]

Results​

Development of the SSRs Based on Genomic Data​

A total of 92,409 SSR motifs were detected, and 63,699 (63.70%) pairs of SSR primers were developed. The most abundant SSR motifs were generally detected on chromosome 5 (12,099), whereas chromosome 10 showed the lowest number of SSR motifs (5277). The maximum ratio of SSR primers was 71.49% on chromosome 4, and the minimal ratio was 66.46% on chromosome 10. Chromosome 10 not only produced the lowest number of primers, but also had the lowest ratio; this was expected considering that chromosome 10 is a sex chromosome and contains less genetic information and variation than the other chromosomes (Table 1).
TABLE 1

Table 1. Number of motifs and SSR primers.

The dinucleotide SSR motifs were the most abundant type of repeats (82,859), followed by the trinucleotide, tetranucleotide, pentanucleotide, and hexanucleotide SSR motifs. According to the length of the genomic SSRs based on the number of repeat units (Table 2), the most abundant type of repeats was six, accounting for 42,305 (36.60%), followed by seven, five, eight, and nine repeat units. Only 6808 units presented more than 14 repeats (5.89%). The five, six, and seven repeat units accounted for 70.46% of the total repeat units, which could explain the predominant diversity of SSR repeat unit types. The number of primers developed based on each motif type was as follows: dinucleotide, 56,406 (68.07%); trinucleotide, 20,709 (71.94%); tetranucleotide, 1896 (62.10%); pentanucleotide, 356 (66.54%); and hexanucleotide, 289 (83.29%). Interestingly, the hexanucleotide motif type was the least common motif type, but it accounted for the highest percentage of the SSR primers developed, possibly caused by a complex of hexanucleotide type.
TABLE 2

Table 2. Frequency of SSR motifs of genome-SSRs in hemp.

Among the 92,409 SSR motifs, 572 motif types were identified, namely di- (12), tri- (60), tetra- (122), penta- (187), and hexa- (191) types. The number of SSR motifs within each motif sequence type was as follows: di- (6904.9), tri- (496.3), tetra- (25), penta- (2.9), and hexa- (1.8) (Table 3). The di- type was the most abundant, and the hexa- type was the least abundant. The most abundant type of repeat motif was AT/TA, accounting for 48,353 of the repeats (41.84%), followed by CT/AG, GA/TC, and AAT/ATT; the other SSR motifs types (18,522) accounted for 16.03% of the repeats (Figure 1).
TABLE 3

Table 3. Number of SSR motifs.

FIGURE 1

Figure 1. Frequency distribution of cannabis genome-SSRs based on motif numbers.

According to the percentage of SSR primers on the 10 chromosomes, chromosome 5 produced the most abundant primers, and chromosome 10 produced the fewest. The results are consistent with the number of SSR motifs on each chromosome, and the percentages of the SSR primers were consistent with each other. A high number of motifs were associated with a high percentage of SSR primers across all chromosomes.

Genomic SSRs and Phenotypic Markers​

Overall Genetic Diversity​

Eighty pairs of markers were randomly selected to evaluate the quality of the SSR markers across the 12 Cannabis varieties. A total of 11 pairs of markers from these 80 pairs failed to generate amplicons. Among the 69 pairs (86.25%) that generated amplicons, 59 (73.59%) showed polymorphisms that produced 72 loci. In addition, 13 pairs of primers produced 2 loci, and the remaining 10 markers had no polymorphisms. The 72 loci and the 3 phenotypic markers were then used to analyze the 199 germplasm resources and evaluate their population structure and genetic diversity.
PowerMarker and POPGENE analyses revealed that the Na ranged from 2 to 8 (average: 4.13), PIC ranged from 0.25 to 0.79 (average: 0.50), and I ranged from 0.50 to 1.78 (average: 1.01). The expected heterozygosity ranged from 0.28 to 0.81 (average: 0.56), Ne ranged from 1.38 to 5.32 (average: 2.50), and H ranged from 0.28 to 0.82 (average: 0.56) (Table 4). Considering two germplasm resources as a variety pair, the maximum genetic distance (1.0229) among the 19,701 pairs was observed between varieties 13 and 102, both from Gansu, China. The minimal genetic distance (0.2107) was observed between varieties 90 and 89, from Inner Mongolia and Heilongjiang, China, respectively.
TABLE 4

Table 4. Characterization of 72 loci and 3 phenotypes.

Genetic Diversity Among Germplasms From Different Regions​

Genetic diversity was also analyzed among 30 local cultivars and 109 wild Cannabis germplasm resources. The results show that the MAF, Na, Ne, I, H, PIC, and He were lower in local cultivars than in wild accessions; that is, the genetic diversity of wild accessions was higher than that of the domesticated accessions. The maximum Na value, 3.96, was recorded in wild accessions, and the minimum value, 3.4667, was recorded in the domesticated accessions. The difference between the maximum and minimum values of the other indexes was not very significant. We also analyzed 135 accessions from China and 64 accessions from abroad. The results show that Na was higher in Chinese accessions, and there were minimal differences in the other indexes between accessions from China and from other countries. In summary, domesticated accessions did not significantly differ from wild germplasms in China. The accessions from China did not significantly differ from foreign accessions although the Chinese accessions harbored more alleles than the foreign accessions.
The germplasms could be divided into nine regions, and the genetic diversity of germplasms among the nine regions was marginal (Table 5). The Na value was the highest for samples from Northeast China (3.79) and the lowest for samples from “other” (2.89). The largest value of MAF was found for samples from other, and the smallest was found for samples from Southwest China. Values of H, He, and PIC for the samples from the nine regions showed no differences; I was greatest in Northeast China and smallest in other; and Ne ranged from 2.18 (others) to 2.43 (Southwest China). In summary, there were no significant differences for the seven indexes among the samples from the nine regions. Samples from the other regions had the largest value of MAF and the lowest Na, H, PIC, I, and Ne.
TABLE 5

Table 5. Genetic diversity of hemp with different geographic origins.

Genetic Distance and Genetic Consistency​

The magnitude of genetic distance reveals the genetic similarity among different groups. The genetic distance of germplasm resources ranged from 0.2107 to 1.0229. The average genetic distance was 0.4792, indicating a relatively low genetic variation among the 199 Cannabis germplasms. The pairwise genetic distances were usually 0.4–0.6 within each population (Figure 2). The percentage of germplasms showing a genetic distance greater than 0.5 was the highest in the case of samples from Northwest China (44%), indicating that the accessions in this region were less related to one another than those from other regions. Samples from mid-eastern China showed the lowest ratio of germplasms with a genetic distance greater than 0.5 (11%); the average ratio of the germplasms from the nine regions that showed a genetic distance greater than 0.5 was 30%. Further, the average ratio of all germplasms that showed a genetic distance greater than 0.5 except those from mid-eastern China were above 20%, indicating that Cannabis accessions from these regions were closely related.
FIGURE 2

Figure 2. The genetic ratio of each region.

The genetic distance between the samples from the various regions ranged from 0.0199 (between Northwest and Northeast China) to 0.1325 (between North China and other) (Table 6). The average genetic distance was 0.063, suggesting a relatively small genetic variation in accessions among the nine regions. Interestingly, there were two pairs with a genetic distance exceeding 0.100 among the 36 region pairs examined (between samples from North China and other, and between those from mid-eastern China and other). Moreover, the results indicate that samples from the region other did not show close relatedness to the samples from the remaining eight regions. The genetic consistency between the region pairs ranged from 0.8759 (between samples from North China and other) to 0.9803 (between samples from mid-eastern and Northwest China). The genetic consistency between samples from North China and other and between samples from mid-eastern China and other was below 0.900. In summary, genetic distances for all samples were below 0.2, and genetic consistency values were all above 0.8, demonstrating a close relatedness among the germplasms from the nine regions.
TABLE 6

Table 6. Genetic distances and genetic consistency analysis.

The average gene flow among all Cannabis accessions was 5.0974, and the mean fixation index (Fst) was 0.0468. High Nm and low Fst values indicate high levels of migration (Bossart and Pashley Prowell, 1998), which might be responsible for the small degree of variation observed within the 199 germplasm resources.

The Microsatellite Bottleneck Event​

A bottleneck signature was detected for samples from all nine populations following their analysis using the IAM and TPM (with SMM = 30%) except for the samples from the region others (P = 0.0970), suggesting that a recent bottleneck event had occurred in all populations. However, all nine populations were found to show mutation-drift equilibrium following analysis using the SMM (Table 7). In the allele frequency distribution test, the samples from the regions mid-eastern China, North China, and other showed a shift in allele frequency distribution, presenting a shifted shape. The other populations showed no shift in allele distribution, maintaining a normal L-shape.
TABLE 7

Table 7. Microsatellite bottleneck events.

Cluster Analysis​

Germplasm Cluster Analysis​

Based on the genetic distances, all germplasm resources analyzed were divided into three classes using PowerMarker (Figure 3). The first class contained 119 germplasm resources, including those from Europe and America (21), Southwest China (22), Northeast China (23), Middle China (14), Northwest China (14), Asia (14), Mid-eastern China (6), North China (4), and other (1). The second class contained 28 germplasm resources from Southwest China (4), Middle China (6), Northeast China (6), Mid-eastern China (1), Northwest China (6), North China (1), Europe and America (1), and Asia (3) (and none from the group other). The third class consisted of 51 germplasm resources from Southwest China (5), Middle China (4), Northeast China (10), Mid-eastern China (3), Northwest China (4), North China (2), Europe and America (10), Asia (8), and others (5). Thus, the majority of germplasm resources from Southwest, Middle, and Mid-eastern China were clustered in the first class, and most of the germplasm resources from the others region were clustered in the third class. Germplasm resources from different regions were clustered into the same class in agreement with the genetic distance and genetic consistency values. The analysis indicates that the Cannabis germplasm resources have a similar genetic background.
FIGURE 3

Figure 3. Cluster analysis results for the 199 hemp materials based on SSR and phenotypic markers.

Cluster Analysis of Different Regions​

A phylogenetic tree based on Nei’s genetic distance was constructed (Figure 4). Arabic numbers are assigned to the nodes in the clustering map. At node 15, the nine regions are clustered into four groups (from top to bottom). Group I is further divided into four subgroups, namely A, B, C, and D, comprising six regions, whereas Groups II, III, and IV each contain only one region. Furthermore, Europe and America as well as Asia are clustered in Group I, indicating that the samples from the first two regions are closely related to those from almost all Chinese regions. At node 14, the nine regions are separated into five groups; subgroup D is integrated into Group II, and Groups III, IV, and V contain only one region each. At node 12, the nine regions are categorized into five groups (from top to bottom): Group I contains four regions; Group II contains two regions; and Groups III, IV, and V contain one region each. These results reveal that the germplasm resources from China are not clustered within a certain group and that there is no direct correlation between region and affiliation. Subgroup D is categorized into one independent group at nodes 11, 12, and 14. In general, the analysis of region clusters based on genetic distance and diversity indexes reflects the geographical origin of the germplasms.
FIGURE 4

Figure 4. Dendrogram of the cluster analysis for the nine regions.

Population Structure of Cannabis Germplasms​

The structure of Cannabis germplasm resource genotypes was analyzed based on the likelihood of data [LnP(D)]. The germplasm resources were randomly integrated into groups (K) to assess the variant frequency of each group, and the individual germplasms were reintegrated into groups based on the estimated frequencies (Evanno et al., 2005). The number of subgroups varies with the LnP(D) values. The curve occurs between K = 1 and K = 2, and all the values are at their maximum when K = 2 (Figure 5), i.e., when the germplasm resources are divided into two subgroups (Figure 6), including 99 and 100 genotypes, which accounts for 49.60% and 50.40% of the germplasm resources, respectively. The first subgroup includes accessions from Southwest China (18), Europe and America (27), Asia (22), and all the germplasms in the set others (6). The second subgroup includes those from Southwest China (13), Middle China (18), Northeast China (28), and Northwest China (24). The structure of each subgroup varies except that accessions from the others region are not included in the second subgroup. The first subgroup is generally composed of accessions from abroad, and the accessions in the second subgroup are all from China. The cluster analysis reveals that the genotypes in both subgroups are variable, but almost all genotypes show the same general trend.
FIGURE 5

Figure 5. Graphical representation of the population structure. (A) K-values for different numbers of populations assumed (K) in the STRUCTURE analysis. (B) The median and variation of the estimated probability value for each K-value. (C) Evanno table output.

FIGURE 6

Figure 6. Population structure of the 199 hemp germplasm resources based on the SSR and the phenotypic markers.

Discussion​

Various types of molecular markers are used to assess the genetic diversity of Cannabis, such as ribosomal DNA, inter-simple sequence repeats (ISSRs), sequence characterized amplified regions, random amplified polymorphic DNA (RAPD), and amplified fragment length polymorphism (AFLP). In one study, 10 pairs of AFLP primers are validated to identify illicit Cannabis cultivars (Datwyler and Weiblen, 2006). Other studies use RAPD markers to identify prefloral hemp (Shao et al., 2003) and the RAPD marker OPA8 that generates specific 400-bp bands in male but not in female plants (Mandolino et al., 1999). A genetic diversity analysis of 27 Chinese hemp cultivars using ISSR markers reveals that the accessions can be classified into five categories (Zhang et al., 2014).
SSR markers are based on microsatellites and are considered the most efficient and abundant molecular markers with a high ratio of genome coverage. They are highly reproducible and can be used to study codominant inheritance (Chen et al., 2019). Moreover, SSR polymorphisms are employed to identify and characterize germplasm resources in terms of affiliation (Tuler et al., 2015), and the development and characterization of genomic SSRs in hemp are important to enable genetic research and marker-assisted selection. Because SSR markers have a higher number of polymorphisms than other molecular markers, they are popular and ideal for analyzing population structure and genetic diversity and identifying fiber crop varieties (Zhang et al., 2015a, b; Saha et al., 2017, 2019). In previous research, EST-SSR development was conducted, and 4577 potential SSR motifs were identified for Cannabis (Gao et al., 2014).
Genomic SSRs have the advantages of a higher number of polymorphisms and higher stability than EST-SSR markers (Ding et al., 2017). Thus, SSR markers in Cannabis can be valuable in future research. In the present study, 92,409 SSR motifs are detected in the Cannabis genome, from which 63,707 pairs of SSR primers are developed, meaning 63.7% of motifs with developed primers. The most abundant sequence motif is of the dinucleotide type (56,406), and the most abundant repeat motif is AT/TA (41.84%). These results differ from those of previous studies, which report that the trinucleotide AAG/CTT and dinucleotide AG/CT are the most common types in EST-SSR (Alghanim and Almirall, 2003; Gao et al., 2014). The most abundant motifs are detected on chromosome 5, suggesting this chromosome may have abundant genetic information and several potentially modified loci. Among the 80 pairs of genomic SSRs, 59 have validated polymorphisms. This information is valuable for the development of Cannabis fingerprints to aid in cultivar identification. Knowledge of the genetic diversity and population structure of crop germplasm resources could accelerate genetic research and the development of new plant varieties. Thus, the results obtained herein may also aid in conserving and utilizing specific high-quality germplasm resources.
Cannabis shows higher genetic diversity than annual wind-pollinated and gravity-dispersed weedy plants (Lynch et al., 2016). Historically, Cannabis germplasm resources around the world are limited. In the 1970s, because of the hallucinogenic effects of Cannabis, the United States prohibited Cannabis planting, and other countries followed. However, in the 1990s, scientists determined that Cannabis had positive treatment effects on various diseases, and Cannabis farming was accepted worldwide (Chandra et al., 2017). However, the ban on Cannabis farming for several years affected global germplasm resource collection and our knowledge of its genetic structure and diversity.
In a previous study, the genetic diversity and DNA fingerprinting of jute was analyzed by 28 pairs of SSR primers, a total of 184 polymorphic loci were identified, and the DNA fingerprinting of 58 jute accessions was based on SSR markers (Zhang et al., 2015a). The genetic differentiation and population structure of 93 fiber flax accessions were evaluated based on genome-wide regulatory gene-derived SSRs and all accessions separated into two subpopulations: Indian and global (Saha et al., 2019). In the present study, PIC values > 0.5 indicate that the locus is highly informative, 0.25 < PIC < 0.5 represent moderate polymorphisms, and PIC values < 0.25 mean a low rate of polymorphism (Jensen et al., 2011). Because PIC ranges from 0.25 to 0.78 (mean: 0.50), Cannabis germplasm resources are considered to have a high degree of polymorphism. The values are lower than those of the Kenyan common bean (Phaseolus vulgaris L.) (Valentini et al., 2018), Indian garlic (Allium sativum L.) (Kumar et al., 2019), and ramie (Boehmeria nivea L.) (Feng et al., 2018) and higher than those of tea plants (Camellia sinensis L.) (Ori et al., 2017), corn (Zea mays L.) (Zhang et al., 2017), and sesame (Sesamum indicum L.) (Yue et al., 2012). In addition, the PIC values of the domesticated, wild, and Chinese and foreign accessions range from 0.25 to 0.50, indicating that the germplasm resources in these regions have moderate polymorphism, and the results are consistent among the nine populations. The He of the accessions from the nine regions is around 0.55; when combined with the MAF (0.6), this indicates that the alleles are uniformly distributed across the populations. The I is around 0.9, which reveals that Cannabis has a highly stable genetic structure. The values of I, Ne, MAF, He, and H among the 199 germplasm resources from the nine regions range between 0.93 and 1.01, 2.35 and 2.50, 0.58 and 0.56, 0.55 and 0.56, and 0.53 and 0.56, respectively. The observed and effective numbers of alleles differ among the populations except for the samples from the other region; those from the other regions have an uneven distribution of alleles. The accessions show a stable genetic structure and moderate genetic diversity. Compared with the He value of 0.49 and I value of 0.32 reported previously (Gao et al., 2014), the accessions in the present study show high genetic diversity. The similarity between the populations analyzed with regard to genetic diversity is confirmed to be a result of a genetic bottleneck event. Following analysis using the IAM, the nine populations do not show mutation-drift equilibrium, suggesting a substantial erosion of genetic diversity among the populations.
In the present study, the germplasm resources are clustered in three groups, and each group includes samples from most, if not all, of the nine regions. In a previous report, 115 Cannabis accessions are divided into four groups, and the genetic diversity between Northern China and Europe is higher than that between groups containing accessions from China only (Gao et al., 2014). Thus, Cannabis germplasms cannot always be clearly distinguished based on geography although geographic origin could aid in domesticating certain varieties and introducing new ones. LnP(D) varies with the number of subgroups, but there is no obvious inflection point in the curve. The population structure analysis and mathematical model application divide the 199 germplasm resources into two subgroups in a population with a single structure.
Cannabis is believed to have originated in China, central Asia, and the northwest Himalayas (Hillig, 2005). The genetic structure of marijuana and hemp are significantly different (Sawler et al., 2015). Genetic differentiation varies with genetic frequency as well as with genetic drift and heterozygosity. The fixation index expresses the degree of genetic differentiation in the population at four levels: little (0 < Fst < 0.05), moderate (0.05 < Fst < 0.15), large genetic (when 0.15 < Fst < 0.25), and very large genetic differentiation (0.25 < Fst < 1) (Wright, 1965). The 199 germplasm resources show little genetic differentiation with an Fst value of 0.0468. Gene flow is a vital index to detect genetic leakage and assess genetic differentiation. When the gene flow (Nm) is >1, the population is able to efficiently prevent the genetic differentiation caused by genetic drift; otherwise, genetic differentiation is inevitable (Wright, 1965; Golenberg, 1987). Gene flow in the present study is 5.0974, indicating that Cannabis germplasm resources around the world frequently undergo gene exchange, which efficiently reduces the genetic differentiation caused by genetic drift. Accordingly, the genetic distance among the nine regions is low, which is consistent with the results of a previous review (Chandra et al., 2017). However, this genetic distance shows large variation. There is no difference among the cultivars and wild Cannabis varieties in China or between the Chinese and foreign Cannabis germplasms, but this result is not consistent with the findings of previous reports (Lynch et al., 2016). The genetic consistency of the germplasms analyzed herein is higher than 0.9, suggesting that the accessions from all nine regions have a relatively high kinship.
Because CBD and THC are unique to Cannabis, they are used as phenotypic markers in the present study (Piomelli and Russo, 2016). CBD and THC show therapeutic potential for many diseases (Galasso et al., 2016). To classify Cannabis varieties, the most accepted standard is a level of 0.3% for THC and 0.5% for CBD. When the THC content is >0.3% and the CBD content is <0.5%, the Cannabis is considered to be of the drug type; when the THC content is <0.3% and the CBD content is <0.5%, the Cannabis is of the fiber type; and when the THC content is <0.3% and the CBD content is >0.5%, it is considered to be of the medicinal type (Small and Beckstend, 1973; Small and Cronquist, 1976). In the present study, the contents of CBD in the 199 Cannabis accessions ranges from 0.00% to 0.93% (average: 0.15%), and the THC contents range from 0.00% to 0.75% (average: 0.18%). The variable coefficients are large for the CBD and THC contents at 108% and 82.6%, respectively. However, based on their THC and CBD contents, 33 accessions are of the drug type, 135 of the fiber type, 7 of the medicinal type, and 24 have inadequate data for classification.
Overall, the genetic diversity and population structure analyses presented herein provide a basis for the further investigation of Cannabis species by quantitative trait loci mapping, association analysis, and molecular-assisted breeding. Our findings can also further the exchange of Cannabis germplasms among different areas in China and the introduction of new Cannabis varieties from abroad.

Data Availability Statement​

All datasets generated for this study are included in the article/Supplementary Material.

Author Contributions​

LZ, DL, and DP designed the experiments. SH, JL, and AC provided the research materials. AB and CuZ performed polyacrylamide gel electrophoresis and data analysis. GP, LC, ChZ, and HT measured the contents of CBD, THC, and CBDA. JZ and JY wrote the manuscript.

Funding​

This research was mainly supported by the China Agriculture Research System for Bast and Leaf Fiber Crops (CARS-16-E-02); China Agriculture Technology Research System and Agricultural Science and Technology Innovation Program (ASTIP-IBFC03); and National Natural Science Foundation of China (Grant No. 31871674).

Conflict of Interest​

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Supplementary Material​

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fgene.2020.00958/full#supplementary-material

Footnotes​

1. ^ http://pgrc.ipk-gatersleben.de/misa/
2. ^ http://taylor0.biology.ucla.edu/structureHarvester/#

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Keywords: Cannabis, genetic diversity, population structure, simple sequence repeat, cluster analysis
Citation: Zhang J, Yan J, Huang S, Pan G, Chang L, Li J, Zhang C, Tang H, Chen A, Peng D, Biswas A, Zhang C, Zhao L and Li D (2020) Genetic Diversity and Population Structure of Cannabis Based on the Genome-Wide Development of Simple Sequence Repeat Markers. Front. Genet. 11:958. doi: 10.3389/fgene.2020.00958
Received: 17 March 2020; Accepted: 30 July 2020;
Published: 11 September 2020.
Edited by:
Liwu Zhang, Fujian Agriculture and Forestry University, China
Reviewed by:
Dipnarayan Saha, Central Research Institute for Jute and Allied Fibres, Indian Council of Agricultural Research, India
Salih Kafkas, Çukurova University, Turkey
Copyright © 2020 Zhang, Yan, Huang, Pan, Chang, Li, Zhang, Tang, Chen, Peng, Biswas, Zhang, Zhao and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Jiangjiang Zhang, [email protected]; Lining Zhao, [email protected]; Defang Li, [email protected]
†These authors have contributed equally to this work

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.



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Odd how with all the "knowledge" written and theories bandied about until they became facts we still don't have any actual stable "strains".

Polymorphism (biology) - Wikipedia

en.wikipedia.org

 

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Large-scale whole-genome resequencing unravels the domestication history of Cannabis sativa​

• July 2021
• Science Advances 7(29)

DOI:10.1126/sciadv.abg2286

Fig. 1. Population structure of Cannabis accessions.

(A) Geographic distribution (i.e., sampling sites of feral plants or country of origin of landraces and cultivars) of the
samples analyzed in this study. Color codes correspond to the four groups obtained in the phylogenetic analysis and shapes indicate domestication types. The two empty
red squares symbolize drug-type cultivars obtained from commercial stores located in Europe and the United States. For sample codes, see table S1.

(B) Maximum likelihood
phylogenetic tree based on single-nucleotide polymorphisms (SNPs) at fourfold degenerate sites, using H. lupulus as outgroup. Bootstrap values for major clades are shown.

(C) Bayesian model–based clustering analysis with different number of groups (K = 2 to 4). Each vertical bar represents one Cannabis accession, and the x axis shows the
four groups. Each color represents one putative ancestral background, and the y axis quantifies ancestry membership.

(D) Nucleotide diversity and population divergence
across the four groups. Values in parentheses represent measures of nucleotide diversity () for the group, and values between pairs indicate population divergence (FST).

(E) Principal component analysis (PCA) with the first two principal components, based on genome-wide SNP data. Colors correspond to the phylogenetic tree grouping


We show that C. sativa was first domesticated in early Neolithic times in East Asia and that all current hemp and drug cultivars diverged from an ancestral gene pool currently represented by feral plants and landraces in China. -Basal Cannabis

 

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​

Released 1985 via Nevilles seed catalog

This wild Sativa variety is used to make some of the world's finest hash. Unfortunately very little sinsemilla is grown in Nepal, but even the seeded buds were very powerful. Stress is often applied to the plants in the belief that the resulting crop will be more potent. The stem is split and a mixture of garlic and ginger is placed in the incision. Another grower assured me that using a cobra head is even more effective. Superstition or not, the Nepalese grow very potent weed. The effect after smoking can best be described as overpowering, trippy and very long lasting. It left me speechless on more than one occasion.

Flowers early September
Heights of 16 feet are easily reached in good conditions.
The yield is said to be up to 2kg for a well developed plant.

 

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Frontiers | Discovery and Genetic Mapping of PM1, a Powdery Mildew Resistance Gene in Cannabis sativa L.

Powdery mildew is among the most common diseases of both hemp- and marijuana-type cultivated Cannabis sativa. Despite its prevalence, no documented studies h...

www.frontiersin.org

Despite a wide range of diseases reported on C. sativa, we have not been able to identify any functionally documented R genes of any kind in this species. In this paper, we describe a naturally occurring powdery mildew R gene that was discovered by screening a Pacific Northwest germplasm collection. This gene, first observed in experimental line “PNW39,” confers complete resistance to a Washington State isolate of G. ambrosiae and was inherited in a dominant, single-gene fashion in two independent genetic backgrounds. Using a recently developed 40K SNP array, we successfully mapped the R gene in an F1 population and validated a qPCR-based marker for use in breeding and selection. SNP genotyping also allowed for the creation of a high-density linkage map to determine the relationship among markers physically located on the same chromosome. The results are reported herein.

Materials and Methods​

Plant Material​

Resistance to powdery mildew was first observed in photoperiod-sensitive experimental line “PNW39” after being grown in a greenhouse setting with high disease pressure. Two independent mapping populations were subsequently developed using parental material consisting of “PNW39,” susceptible and photoperiod-sensitive cultivar “Jumping Jack,” and a susceptible and photoperiod-insensitive recombinant inbred family “Dwy1337.” For the first population, feminized pollen from susceptible cultivar “Jumping Jack” was crossed to the female parent “PNW39.” The second population was developed by exposing female parent “PNW39” to an open pollination of multiple individuals from the “Dwy1337” family. At least 100 viable seeds were collected from each independent cross. Currently, the most prevalent accessions of C. sativa are highly heterozygous due to its natural preference for outcrossing and acute inbreeding depression (Onofri and Mandolino, 2017). Thus, the F1 families resulting from these hybridizations were genetically heterogeneous and allowed for linkage mapping of simple to moderately complex traits.

Critical+ 2.0 (Dinafem) :: Cannabis Strain Info :: SeedFinder.eu

Independent, standardized information about Dinafem cannabis-strain Critical+ 2.0! Find phenotypes, comments + detailed profiles, flowering-time, THC-Content, images, prices & stores, extended family-tree & lineages, crossings & hybrids, grow-journals, direct-comparisons, medicinal properties...

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[acespicoli]

Mold Resistant Strains To Grow Easily | Grove Bags

15 mold-resistant strains exist and cultivating strains that are resistant to molds is a great start to protecting your harvest.

grovebags.com

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12. The Purps​

High Times Top Ten List. It’s a strain that’s easy to grow because it can adapt to fluctuations in humidity.
It is highly resistant to molds

13. Purest Indica (NL0)​

These marijuana seeds are more resistant to mold formation, which is music to the ears of a cannabis grower.Northern Light marijuana strain is great for mold resistance, therefore rendering it a great strain for long-term use and storage.

14. Purple Kush​

This marijuana strain is also naturally resistant to powdery mildew, mold, and other pests that may interfere with its growth cycle and progress as a plant. It tends to thrive ideally as an indoor plant, as this climate and condition allows the strain to be better controlled when it comes. to humidity and temperature throughout the cycle.

 

[acespicoli]

The poet Samuel Taylor Coleridge​

In Köhln, a town of monks and bones,
And pavements fang’d with murderous stones
And rags, and hags, and hideous wenches ;
I counted two and seventy stenches,
All well defined, and several stinks!
Ye Nymphs that reign o’er sewers and sinks,
The river Rhine, it is well known,
Doth wash your city of Cologne ;
But tell me, Nymphs, what power divine
Shall henceforth wash the river Rhine?​

Historically and in literature sulfur is also called brimstone,[5] which means "burning stone".

Many sulfur compounds are odoriferous, and the smells of odorized natural gas, skunk scent, bad breath, grapefruit, and garlic are due to organosulfur compounds. Hydrogen sulfide gives the characteristic odor to rotting eggs and other biological processes.




Sweet;
Floral; Nectar; Rose; Jasmine; Vanilla; Cherry Blossom; Apricot Tree; Orange Blossom; Lilac; Violet; Fruity; Berry; Raspberry; Strawberry; Blackberry; Blueberry; Cranberry; Tropical; Passion Fruit; Pineapple; Cantaloupe; Mango; Kiwi; Banana; Coconut; Grape; Apricot; Cherry; Plum; Peach; Apple; Pear; Sugar; Honey; Bubble Gum; Cookie Dough; Peanutbutter; Butterscotch; Chocolate; Marshmallow; Whipped Cream; Licorice;

Sour;
Citrus; Lemon; Sweet Lemon; Lime; Lemon Grass; Grapefruit; Orange; Blood Orange; Tangerine; Dairy; Butter; Cheese; Hot Milk; Sour Cream; Acidic; Spicy; Hot; Mustard; Teriyaki; Curry; Chili; Tabasco; Soy Sauce; BBQ Sauce; Mint; Spearmint; Herbs; Ginger; Pepper; Cinnamon; Sage; Basilicum; Thyme; Dill; Saffron; Cloves; Parsley; Fennel; Sandalwood; Cedarwood; Pine; Maple; Hashish;


Bitter;
Nuts; Fresh Nuts; Macadamia; Walnut; Hazelnut; Tonsil; Rosted Nuts; Pistachio; Sesame; Peanut; Chestnut; Chemical; Coughsyrup; Medicine; Metal; Poison; Glue; Diesel; Tar; Organic; Cucumber; Chives; Tee; Cocoa; Coffee; Tobacco; Onion; Garlic; Vinegar; Salty; Microbiological; Rot; Earth; Musky; Mold; Sweat; Charcoal; Wood; Alcohol; Chalk; Soda; Leather

Grapefruit (Clone Only Strains) :: Cannabis Strain Info :: SeedFinder.eu

Independent, standardized information about Clone Only Strains cannabis-strain Grapefruit! Find phenotypes, comments + detailed profiles, flowering-time, THC-Content, images, prices & stores, extended family-tree & lineages, crossings & hybrids, grow-journals, direct-comparisons, medicinal...

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Not all organic sulfur compounds smell unpleasant at all concentrations: the sulfur-containing monoterpenoid grapefruit mercaptan in small concentrations is the characteristic scent of grapefruit, but has a generic thiol odor at larger concentrations.

Garlic Bud (The Seed Bank) :: Cannabis Strain Info :: SeedFinder.eu

Independent, standardized information about The Seed Bank cannabis-strain Garlic Bud! Find phenotypes, comments + detailed profiles, flowering-time, THC-Content, images, prices & stores, extended family-tree & lineages, crossings & hybrids, grow-journals, direct-comparisons, medicinal...

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White Widow (De Sjamaan) :: Cannabis Strain Info :: SeedFinder.eu

Independent, standardized information about De Sjamaan cannabis-strain White Widow! Find phenotypes, comments + detailed profiles, flowering-time, THC-Content, images, prices & stores, extended family-tree & lineages, crossings & hybrids, grow-journals, direct-comparisons, medicinal properties...

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Trainwreck (Clone Only Strains) :: Cannabis Strain Info :: SeedFinder.eu

Independent, standardized information about Clone Only Strains cannabis-strain Trainwreck! Find phenotypes, comments + detailed profiles, flowering-time, THC-Content, images, prices & stores, extended family-tree & lineages, crossings & hybrids, grow-journals, direct-comparisons, medicinal...

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Taste :: All "Leather" medical marijuana strains. (P91) :: SeedFinder.eu

Here you can find the varieties of cannabis which were tagged by our users with certain characteristics in terms of Taste (Leather). :: P91

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Viking (Unknown or Legendary) :: Cannabis Strain Info :: SeedFinder.eu

Independent, standardized information about Unknown or Legendary cannabis-strain Viking! Find phenotypes, comments + detailed profiles, flowering-time, THC-Content, images, prices & stores, extended family-tree & lineages, crossings & hybrids, grow-journals, direct-comparisons, medicinal...

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Maple Leaf Indica; Super Skunk; Legends Ultimate Indica;
P91 »»» Thailand x {Thailand x (Thailand x Afghanistan)} "The Cube"

Onion; Garlic; Musky; Sweat; Rot; Leather

Nordle (Mr Nice Seedbank) :: Cannabis Strain Info :: SeedFinder.eu

Independent, standardized information about Mr Nice Seedbank cannabis-strain Nordle! Find phenotypes, comments + detailed profiles, flowering-time, THC-Content, images, prices & stores, extended family-tree & lineages, crossings & hybrids, grow-journals, direct-comparisons, medicinal properties...

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Naturally occurring organosulfur compounds​

Not all organosulfur compounds are foul-smelling pollutants. Penicillin and cephalosporin are life-saving antibiotics, derived from fungi. Gliotoxin is a sulfur-containing mycotoxin produced by several species of fungi under investigation as an antiviral agent. Compounds like allicin and ajoene are responsible for the odor of garlic, and lenthionine contributes to the flavor of shiitake mushrooms. Volatile organosulfur compounds also contribute subtle flavor characteristics to wine, nuts, cheddar cheese, chocolate, coffee, and tropical fruit flavors.[32] Many of these natural products also have important medicinal properties such as preventing platelet aggregation or fighting cancer.

In pollution​

Most organic sulfur compounds in the environment are naturally occurring, as a consequence of the fact that sulfur is essential for life and two amino acids (cysteine and methionine) contain this element.

Some organosulfur compounds in the environment, are generated as minor by-products of industrial processes such as the manufacture of plastics and tires.

Selected smell-producing processes are organosulfur compounds produced by the coking of coal designed to drive out sulfurous compounds and other volatile impurities in order to produce 'clean carbon' (coke), which is primarily used for steel production.

In fossil fuels​

Odours occur as well in chemical processing of coal or crude oil into precursor chemicals (feedstocks) for downstream industrial uses (e.g. plastics or pharmaceutical production) and the ubiquitous needs of petroleum distillation for gasolines, diesel, and other grades of fuel oils production.

Organosulfur compounds might be understood as aromatic contaminants that need to be removed from natural gas before commercial uses, from exhaust stacks and exhaust vents before discharge. In this latter context, organosulfur compounds may be said to account for the pollutants in sulfurous acid rain, or equivalently, said to be pollutants within most common fossil fuels, especially coal.

The most common organosulfur compound present in all petroleum fractions is thiophene (C4H4S), a cyclic and aromatic liquid. In addition, the heavy fractions of oil contain benzothiophene (C8H6S, thianaphtene) and dibenzothiophene. Most of the last compounds are solids and smell like naphthalene. Many methylated, dimethyl, diethyl benzothiophene derivatives are present in diesel and fuel oils which make fuel oils very difficult to clean.

All these heterocyclic sulfides account for 200–500 ppm of natural fuel, the heavily substituted dibenzothiophenes remain after HDS and account for 10–20 ppm. These molecules are also found in coals and they must be eliminated before consumption.

Reduced molybdenum together with nickel is currently used to eliminate thiophenes from petroleum (HDS) due to its great affinity towards sulfur. In addition tungsten together with nickel and cobalt is used for hydrodesulfurization (HDS) in large refineries. The adsorption mechanism of thiophene to transition metals is proposed to occur through the π system, where the organosulfur compound lies almost parallel to the metal surface. Many researchers focus their efforts in optimizing the oxidation state of the transition metals for HDS, like Cu(I) and Ag(II) which together with Pd(0) have proven to be more specific for π bonding with thiophenes of all kinds.

Basis for odor​

Humans and other animals have an exquisitely sensitive sense of smell toward the odor of low-valent organosulfur compounds such as thiols, sulfides, and disulfides. Malodorous volatile thiols are protein-degradation products found in putrid food, so sensitive identification of these compounds is crucial to avoiding intoxication. Low-valent volatile sulfur compounds are also found in areas where oxygen levels in the air are low, posing a risk of suffocation. It has been found that copper is required for the highly sensitive detection of certain volatile thiols and related organosulfur compounds by olfactory receptors in mice. Whether humans, too, require copper for sensitive detection of thiols is not yet known.[33]

Organosulfur chemistry - Wikipedia

en.wikipedia.org

Organosulfur chemistry is the study of the properties and synthesis of organosulfur compounds, which are organic compounds that contain sulfur.[1] They are often associated with foul odors, but many of the sweetest compounds known are organosulfur derivatives, e.g., saccharin. Nature is abound with organosulfur compounds—sulfur is vital for life. Of the 20 common amino acids, two (cysteine and methionine) are organosulfur compounds, and the antibiotics penicillin and sulfa drugs both contain sulfur. While sulfur-containing antibiotics save many lives, sulfur mustard is a deadly chemical warfare agent. Fossil fuels, coal, petroleum, and natural gas, which are derived from ancient organisms, necessarily contain organosulfur compounds, the removal of which is a major focus of oil refineries.

Sulfur shares the chalcogen group with oxygen, selenium, and tellurium, and it is expected that organosulfur compounds have similarities with carbon–oxygen, carbon–selenium, and carbon–tellurium compounds.

A classical chemical test for the detection of sulfur compounds is the Carius halogen method.

Thiol - Wikipedia

en.wikipedia.org

Odor​

Many thiols have strong odors resembling that of garlic. The odors of thiols, particularly those of low molecular weight, are often strong and repulsive. The spray of skunks consists mainly of low-molecular-weight thiols and derivatives.[11][12][13][14][15] These compounds are detectable by the human nose at concentrations of only 10 parts per billion.[16] Human sweat contains (R)/(S)-3-methyl-3-mercapto-1-ol (MSH), detectable at 2 parts per billion and having a fruity, onion-like odor. (Methylthio)methanethiol (MeSCH2SH; MTMT) is a strong-smelling volatile thiol, also detectable at parts per billion levels, found in male mouse urine. Lawrence C. Katz and co-workers showed that MTMT functioned as a semiochemical, activating certain mouse olfactory sensory neurons, attracting female mice.[17] Copper has been shown to be required by a specific mouse olfactory receptor, MOR244-3, which is highly responsive to MTMT as well as to various other thiols and related compounds.[18] A human olfactory receptor, OR2T11, has been identified which, in the presence of copper, is highly responsive to the gas odorants (see below) ethanethiol and t-butyl mercaptan as well as other low molecular weight thiols, including allyl mercaptan found in human garlic breath, and the strong-smelling cyclic sulfide thietane.[19]

Thiols are also responsible for a class of wine faults caused by an unintended reaction between sulfur and yeast and the "skunky" odor of beer that has been exposed to ultraviolet light.

Not all thiols have unpleasant odors. For example, furan-2-ylmethanethiol contributes to the aroma of roasted coffee, whereas grapefruit mercaptan, a monoterpenoid thiol, is responsible for the characteristic scent of grapefruit. The effect of the latter compound is present only at low concentrations. The pure mercaptan has an unpleasant odor.

In the United States, natural gas distributors were required to add thiols, originally ethanethiol, to natural gas (which is naturally odorless) after the deadly New London School explosion in New London, Texas, in 1937. Many gas distributors were odorizing gas prior to this event. Most currently-used gas odorants contain mixtures of mercaptans and sulfides, with t-butyl mercaptan as the main odor constituent in natural gas and ethanethiol in liquefied petroleum gas (LPG, propane).[20] In situations where thiols are used in commercial industry, such as liquid petroleum gas tankers and bulk handling systems, an oxidizing catalyst is used to destroy the odor. A copper-based oxidation catalyst neutralizes the volatile thiols and transforms them into inert products.

Allicin - Wikipedia

en.wikipedia.org

Allicin is an organosulfur compound obtained from garlic.[1] When fresh garlic is chopped or crushed, the enzyme alliinase converts alliin into allicin, which is responsible for the aroma of fresh garlic.[2] Allicin is unstable and quickly changes into a series of other sulfur-containing compounds such as diallyl disulfide.[3] Allicin is an antifeedant, i.e. the defense mechanism against attacks by pests on the garlic plant.[4]

Allicin is an oily, slightly yellow liquid that gives garlic its distinctive odor. It is a thioester of sulfenic acid. It is also known as allyl thiosulfinate.[5] Its biological activity can be attributed to both its antioxidant activity and its reaction with thiol-containing proteins.[6]

Ethanethiol - Wikipedia

en.wikipedia.org

Odor​

Ethanethiol has a strongly disagreeable odor that humans can detect in minute concentrations. The threshold for human detection is as low as one part in 2.8 billion parts of air (0.36 parts per billion). Its odor resembles that of leeks, onions, durian or cooked cabbage.[9]

Employees of the Union Oil Company of California reported first in 1938 that turkey vultures would gather at the site of any gas leak. After finding that this was caused by traces of ethanethiol in the gas it was decided to boost the amount of ethanethiol in the gas, to make detection of leaks easier. [10][11]

Skunk - Wikipedia

en.wikipedia.org

These glands produce the skunk's spray, which is a mixture of sulfur-containing chemicals such as thiols (traditionally called mercaptans), which have an offensive odor.

Navarretia squarrosa - Wikipedia

en.wikipedia.org

California Western Railroad - Wikipedia

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The 'brussels sprouts' gene: TAS2R38 | Anna Perman's Genetic Spaghetti

As the annual sprout-eating ritual approaches, Anna Perman explains why you either love them or hate them

www.theguardian.com

There is one gene controlling taste sensitivity that scientists have characterised in a lot of detail – the catchily named TAS2R38 gene. This gene makes a protein that interlocks with a chemical called PTC (phenylthiocarbamide) and gives the taste sensation of bitterness.

PTC isn't usually found in the human diet, but it is very similar to chemicals found in brassicas such as brussels sprouts and cabbages. Because of this, scientists have suggested that the ability to taste or not taste PTC might explain why some people hate sprouts, and some people love them.

Phenylthiocarbamide - Wikipedia

en.wikipedia.org

Thiourea - Wikipedia

en.wikipedia.org

Musk - Wikipedia

en.wikipedia.org

Sesquiterpene - Wikipedia

en.wikipedia.org

A recent study conducted in the Cosmics Leaving Outdoor Droplets large cloud chamber at CERN, has identified sesquiterpenes — gaseous hydrocarbons that are released by plants — as potentially playing a major role in cloud formation in relatively pristine regions of the atmosphere.[2]