What is the relationship between r/K strategy and filial infanticides?

In other words, is the frequency of killing one's own offspring among species dependent on their location on the r/K strategy spectrum?

From what I can tell there isn't any work done on this specific form of infanticide. Here is a review on the subject Here

My assessment would lead me to believe the more r selected a species is the more likely infanticide (if it happens at all) done by the individual would be toward kin. This would probably be due to a need for resources.

One thing to recall though is that this actually violates a basic inference from natural selection. Fitness is measured by how much of your alleles you contribute to the next generation. If you are eating your own offspring you are effectively reducing your fitness. The individual may however increase their long term fitness by doing this.

A possible way to locate a species that might do this would be one that sexually matures later in life but has a relatively long reproductive life with the higher number of offspring being produced in the later age groups. Finding some life history on some K selected species might help you find what you are looking for.

I'm sorry that I can't better answer your question. and for the spelling and grammar. cheers,

I think there is.

We know that each and every organism has sufficient resources provided by Nature for its survival.

Lets do a case study.

Let us say a population of 10 foxes lives in a jungle (whose biodiversity is undisturbed by any Non-Natural factors ).So, this particular jungle is well equipped to ensure the survival of 10 foxes.

Now, if we by any means alter the r-value - what we are actually doing is disturbing the initially stable number of organisms present in the jungle at different tropic levels. That can occur by altering any little characteristic because all are interdependent by food webs and chains.

For eg, if the number of plants drops due to say fertility problems of the soil, then the number of herbivores would also drop (As herbivores' only source of food are plants). This would result in competition between the carnivores for food as carnivores feed upon herbivores, whose population are dropping due to lack of sufficient food.

Competition is a type of relationship from which no one benefits.Its kinda like war- There shall be a winner but there shall be no side that doesn't suffer losses.

So, back to the situation, competition among carnivores here let's say the foxes would increase day by day as the number of plants drops. So, foxes would resort to killing their own species so as to decrease the number of organisms vying for the same food i.e here herbivores.

You know what prevails the most in nature is - The Survival of the fittest.

So, who do you think would be killed first ?

The one who has had experiences in fighting for food and such stuff or the one who is an infant i.e has not yet experienced the dynamics of the intraspecific competition

Its also worth mentioning here that of all the types of competition, Intraspecific competition is the most brutal as here organism compete for the same resources.

So, I think lesser the r-value of a location, more shall be the chances of filial infanticide.

PS: Note that I used the word chance because we can't predict 90 % of the natural things with certainty.We can make our best guesses. Say here, we don't take into account the protective nature of animals towards their offsprings.So animals are fiercely protective towards their own offsprings that they shall sacrifice themselves first while some eat their own offsprings first.

The cheetah mom is a hard-working single mother, who raises two and eight cubs at a time. In addition to feeding and teaching them, she protects them from lions, hyenas, and other predators. To keep her litter safe, the mother cheetah moves her cubs to a new location every few days.

Insects, fish, amphibians, reptiles, and birds also have been implicated in killing, and sometimes devouring, the young of their own kind.

The best example that I think I could give to you is Cannibalism. We say that Humans are the most self-conscious beings.So, if they can resort to killing their own species for a) food b) money (female infanticide) , then why can't animals who have supposedly lesser consciousness of their actions than humans

Inheritance of evolved glyphosate resistance in Conyza canadensis (L.) Cronq.

N-(phosphonomethyl)glycine (glyphosate) resistance was previously reported in a horseweed [Conyza (=Erigeron) canadensis (L.) Cronq.] population from Houston, DE (P R 0 ). Recurrent selection was performed on P R 0 , since the population was composed of susceptible (5%) and resistant (95%) phenotypes. After two cycles of selection at 2.0 kg ae glyphosate ha −1 , similar glyphosate rates that reduced plant growth by 50%, glyphosate rates that inflicted 50% mortality in the population, and accumulations of half of the maximum detectable shikimic acid concentration were observed between the parental P R 0 and the first (RS1) and second (RS2) recurrent generations. In addition, RS1 and RS2 did not segregate for resistance to glyphosate. This suggested that the RS2 population comprised a near-homozygous, glyphosate-resistant line. Whole-plant rate responses estimated a fourfold resistance increase to glyphosate between RS2 and either a pristine Ames, IA (P P 0 ) or a susceptible C. canadensis population from Georgetown, DE (P S 0 ). The genetics of glyphosate resistance in C. canadensis was investigated by performing reciprocal crosses between RS2 and either the P P 0 or P S 0 populations. Evaluations of the first (F1) and second (F2) filial generations suggested that glyphosate resistance was governed by an incompletely dominant, single-locus gene (R allele) located in the nuclear genome. The proposed genetic model was confirmed by back-crosses of the F1 to plants that arose from achenes of the original RS2, P P 0 , or P S 0 parents. The autogamous nature of C. canadensis, the simple inheritance model of glyphosate resistance, and the fact that heterozygous genotypes (F1) survived glyphosate rates well above those recommended by the manufacturer, predicted a rapid increase in frequency of the R allele under continuous glyphosate selection. The impact of genetics on C. canadensis resistance management is discussed.

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Climate scenarios suggest that the increased CO2 levels in the atmosphere and associated warming will increase precipitation in the northern hemisphere (Dore, 2005 ). For northern Scandinavia, precipitation is predicted to increase by a maximum of 21% compared to the current average (Meier, 2006 ). As a result the discharge of freshwater, and thereby nutrient load to the coastal zone, will increase.

The current view is that increased discharge of nitrogen and phosphorus promotes phytoplankton productivity and therefore eutrophication in the coastal zone (Larsson et al., 1985 Smith, 2006 Finkel et al., 2010 ). This is based on the fact that most studies implicate phosphorus and nitrogen as the major limiting nutrients of phytoplankton biomass production (Rabalais et al., 2002 ). Consequently, increased fresh water discharge should result in elevated primary production and high food web efficiency, and so in greater fish and shellfish production (Nixon, 1988 ).

However, Howarth et al. ( 2000 ), contrastingly reported higher primary production during dry than wet years in the Hudson estuary, suggesting weaker stratification and light penetration to be the main cause. Also, organic carbon is typically discharged at higher levels simultaneously with nitrogen and phosphorus, potentially exerting several negative effects on phytoplankton productivity (Hessen et al., 2010 ). In accordance with this, estuaries worldwide are often reported as net-heterotrophic, suggesting that externally supplied organic carbon is an important driver of coastal metabolism (Kemp et al., 1997 Sandberg et al., 2004 ). Dissolved organic carbon may support bacterioplankton biomass production, resulting in increased competition for mineral nutrients with phytoplankton (Pengerud et al., 1987 Thingstad et al., 2008 Barrera-Alba et al., 2009 ). Increased freshwater discharge may further influence stratification of the water column, affecting the vertical distribution of phytoplankton and their effective light climate (Cole et al., 1992 Howarth et al., 2000 Jager et al., 2008 ). Furthermore, an increase in humic and suspended substances may reduce light climate and, in conjunction with reduced salinity, may change the taxonomic composition of resident communities (Gasiunaite et al., 2005 Hessen et al., 2010 ).

Marine productivity and transfer efficiency in the coastal food web are important to understand in view of changing freshwater discharge, as they may influence the functionality of the coastal ecosystem. Whether larger phytoplankton or small bacterioplankton dominate the biomass at the food web base will influence the food web efficiency, defined as fish production per unit of primary production (Nixon, 1988 Rand & Stewart, 1998 Berglund et al., 2007 ). If the net effect of increased freshwater discharge is higher primary production of larger phytoplankton in the coastal zone, this may lead to increased production of fish and shellfish (Finkel et al., 2010 ). In contrast, the large influence of riverine dissolved and suspended organic matter in the coastal zone can both reduce primary production and promote a microbial food web structure with poor transfer efficiency of organic carbon to fish and shellfish (Sandberg et al., 2004 Berglund et al., 2007 ). To properly manage coastal resources and mitigate future effects of climate change, a better understanding of the net effect of increased freshwater discharge on an ecosystem scale is therefore required.

Taken together, it is difficult to predict the net outcome of increased river discharge for coastal productivity and the balance between auto- and heterotrophic processes, or to simulate it in controlled laboratory experiments. In this study, we therefore investigated the influence of a relatively moderate, but climatologically relevant, change in freshwater discharge on the ratio of bacterial to phytoplankton biomass production in full-scale coastal ecosystems over several years. This was used as a proxy for the relative importance of microbial production, and thereby losses from fish production and sedimentation.

Three different coastal sea areas were included, providing varying riverine load, morphology, productivity level and hydrography. In addition, long-term effects were examined by using a 13 year data set. The advantage of this strategy was that it addressed many of the composite effects of increased freshwater discharge on hydrography, chemistry, and biology in the coastal zone. Long-term field data sets also encompass effects on larger and more relevant time scales than can be achieved in controlled experimental systems, an important aspect in assessing climate-driven environmental change.

Neanderthals, Inbreeding, r/K Selection Theory and Eurasian Birthrates

(Note, 6/24/17: Rushton’s r/K selection in applications to human races is dead. It’s been dead for almost 30 years after and ecologist critiqued his method and use of ecological theory in application to human races. Now, that doesn’t meant that everything written below—or even on my whole blog—is fully wrong, just that the attempted explanation is wrong. It still holds that Eurasians have worse fitness than Africans, which is partly due to deleterious Neanderthal variants, however, r/K theory does not explain it.)

Science Daily reported last week that Neanderthals left humans a genetic burden, which is having less offspring. Of course, these deleterious alleles only introgressed into non-African populations due to Africans not leaving Africa. This manifests itself today in birth rates within countries and between them based on the ethnic/racial mix. And (not) coincidentally, the areas with the highest rate of children are in sub-Saharan Africa.

The Neanderthals existed in small bands, so inbreeding was common. Due to this inbreeding, Neanderthals were more homogenous than we are today. When humans migrated out of Africa, they encountered the inbred Neanderthals who they interbred with. Harmful genetic variants acquired from Neanderthals are shown to reduce the fitness of populations with certain deleterious alleles. There are of course tradeoffs with everything in life. Increased intelligence and being better able to weather the Ice Age, among numerous other factors, were positive things gained from interbreeding with Neanderthals. Negative effects were the acquisition of deleterious alleles which still persist today in non-African hominids. These deleterious alleles decreased biological fitness which manifests itself in the birthrate of Eurasian populations throughout the world (the Germann and Japanese birthrate is 1.3 for reference).

Harris and Nielson also hypothesize that since Neanderthals existed in small bands that natural selection was less effective, allowing for weakly harmful mutations to pass on and not get weeded out over the generations. However, when introduced back into humans these effects become lost over time due to a large population with natural selection selecting against the deleterious Neanderthal alleles. Using a computer program, Harris and Nielson quantify how much of a negative effect the Neanderthal genome had on modern populations. The conclusion of the results was that Neanderthals are 40 percent LESS genetically fit than modern humans.

The researchers’ simulations also suggest that humans and Neanderthals mated more freely, which leads more credence to the idea that Neanderthals got absorbed into the Homo Sapien population and not mostly killed off. The estimation for Neanderthal DNA in modern hominids from the simulation was around 10 percent, which then continued to drop as the Neanderthal-Homo Sapiens hybrids interbred with those who hardly had any Neanderthal DNA. More evidence also shows that the percentage of Neanderthal DNA was higher in the past in Eurasians as well. Which makes sense since Asians have on average 20 percent more Neanderthal DNA than Europeans due to a second interbreeding event.

However, Harris and Nielson end up concluding that non-Africans historically had a 1 percent loss in biological fitness due to Neanderthal genetics. Moreover, a better immune system came from Neanderthal genetics. Skin color is another trait inherited from Neanderthals as well.

Along with the acquisition of deleterious Neanderthal alleles, early Eurasians also encountered the same environment as the Neanderthals. Those selection pressures, along with interbreeding due to small bands lead to a decrease in the number of children had. Fewer children are easier to care for as well as show more attention to. All of these variables in that environment lead to fewer children produced. It’s a better evolutionary strategy to have fewer children in more northerly climes than in more southerly ones due to the differing selection pressures. Environmental effects are also one reason why birthrates are lower for populations that evolved in northerly climes (Neanderthals and post-OoA hominids). Harsh winters lead to a decreased population size, as evidenced by the Inuit and Eskimoes, which their low population size didn’t allow for selection for high IQ despite having the same brain size as East Asians.

I couldn’t help but think that, yet again, for the second time in two weeks, one of JP Rushton’s theories was confirmed. This confirms one of the many variables of Rushton’s r/K Selection Theory. Just like I covered how Piantadosi and Kidd corroborated Rushton’s theory of brain size and earlier child birth. Neanderthals had bigger brains than we do today, and knowing what we know about the correlation between IQ, brain size and early childbirth, I would assume that Neanderthals also had earlier childbirths as well,.

Along with these deleterious gene variants from Neanderthals, other variables that contribute to the decline in Eurasian populations also include higher IQ as well, as JP Rushton says, is an extreme way to have control over their environment and individuality. These traits are seen in higher IQ populations in comparison to lower IQ populations. We could also make the inference that since Eurasian children have bigger heads, that multiple childbirths would be taxing on the Eurasian woman’s birth canal while it would be less taxing on the African woman’s.

This study also shows that Neanderthals also had less offspring due to being more intelligent. They had bigger brains than we do today, and since we know that higher IQ is correlated with fewer children conceived, we can say that they were pretty damn smart (they buried their dead 50,000 years ago. There was also a recent discovery of a 176,500-year-old Neanderthal constructions in a French cave). A main cause for the current trend in birthrates in Eurasian populations is due interbreeding with Neanderthals. These events also attributed more to the decline of the Neanderthals.

Deleterious Neanderthal alleles are yet another reason for lower Eurasian birthrates, which shows = that the current trend currently happening in the world with these populations is natural and evolutionarily based. I’ve said a few times that by showing positive things to women on television will increase the white birth rate, with Rushton cites National Socialist Germany as one example. By showing women happy with children, this lead to a massive boom in the German population. To ameliorate the effects of low natural birth rates, these positive things need to be shown on television to women to start to reverse the effects of low natural childbirths.

It’s been a great month for Rushton’s theories, with two of them being corroborated in one month. It’s only a matter of time before the denial of human nature is completely discarded from modern science. As the data piles up on human genetic diversity we will not be able to deny these clearly evident factors any longer.

What is the relationship between r/K strategy and filial infanticides? - Biology

KEYWORDS: evolution, fitness variation, genetic systems, NATURAL SELECTION

The idea that sex functions to provide variation for natural selection to act upon was first advocated by August Weismann and it has dominated much discussion on the evolution of sex and recombination since then. The goal of this paper is to further extend this hypothesis and to assess its place in a larger body of theory on the evolution of sex and recombination. A simple generic model is developed to show how fitness variation and covariation interact with selection for recombination and illustrate some important implications of the hypothesis: (1) the advantage of sex and recombination can accrue both to reproductively isolated populations and to modifiers segregating within populations, but the former will be much larger than the latter (2) forces of degradation that are correlated across loci within an individual can reduce or reverse selection for increased recombination and (3) crossing-over (which can occur at different places in different meioses) will create more variability than having multiple chromosomes and so will have more influence on the efficacy of selection. Several long-term selection experiments support Weismann's hypothesis, including those showing a greater response to selection in populations with higher rates of recombination and higher rates of recombination evolving as a correlated response to selection for some other character. Weismann's hypothesis is also consistent with the sporadic distribution of obligate asexuality, which indicates that clones have a higher rate of extinction than sexuals. Weismann's hypothesis is then discussed in light of other patterns in the distribution of sexuality versus asexuality. To account for variation in the frequency of obligate asexuality in different taxa, a simple model is developed in which this frequency is a function of three parameters: the rate of clonal origin, the initial fitness of clones when they arise, and the rate at which that fitness declines over time. Variation in all three parameters is likely to be important in explaining the distribution of obligate asexuality. Facultative asexuality also exists, and for this to be stable it seems there must be ecological differences between the sexual and asexual propagules as well as genetic differences. Finally, the timing of sex in cyclical parthenogens is most likely set to minimize the opportunity costs of sex. None of these patterns contradict Weismann's hypothesis, but they do show that many additional principles unrelated to the function of sex are required to fully explain its distribution. Weismann's hypothesis is also consistent with what we know about the mechanics and molecular genetics of recombination, in particular the tendency for chromatids to recombine with a homolog rather than a sister chromatid at meiosis, which is opposite to what they do during mitosis. However, molecular genetic studies have shown that cis-acting sites at which recombination is initiated are lost by gene conversion as a result, a factor that can be expected to affect many fine details in the evolution of recombination. In summary, although Weismann's hypothesis must be considered the leading candidate for the function of sex and recombination, nevertheless, many additional principles are needed to fully account for their evolution.


Highly significant 46 microsatellites were discovered in association with FUI, LP, FS, FL, BW, MIC, FE, PH and FU. Two-thirds of these significantly associated loci were scattered on D sub-genome, especially those of related to FS, FL and FU. Also the pleiotropic effects of NAU2631, CM45 and GH501 loci on FUI, FS, FL and FE were detected. A set of 96 exclusively favorable alleles were discovered primarily associated with BW, FL, FE and MIC mainly harbored by F1s from C tester (A971 Bt). To grab prominent improvement in mentioned influenced fiber quality and yield traits, we suggest the A971 Bt cotton cultivar as fundamental element in succeeding AM population development procedure to eliminate deleterious alleles residing at corresponding loci of superior alleles. The output of this study can be helpful for plant breeders and researchers working to improve the yield and quality attributes of cotton for the efficient utilization of hybrid vigor.


Tick-borne diseases comprise a complex epidemiological and ecological network that connects the vectors, pathogens, and a group of host species. The aim of this study was to identify bacteria from the genus Rickettsia associated with ixodid ticks infesting camels and cows in Egypt. Ticks were collected from 6 different localities: Qina, Giza, Qalet El Nakhl, New Valley, El Arish, and Minufia, from July to October 2008. Species were identified using PCR, followed by sequencing. The gltA and rOmpA genes were used for the initial detection of Rickettsia spp. Further characterization of positive samples utilized primers targeting rOmpB, sca4, and intergenic spacers (mppA-purC, dksA-xerC, and rpmE-tRNA fMet ). Cows were infested with Hyalomma anatolicum excavatum and Boophilus annulatus. Camels were infested with Hyalomma dromedarii, H. impeltatum, and H. marginatum marginatum. Approximately 57.1% of H. dromedarii ticks collected from Qalet El Nakhl were infected with Rickettsia africae, exhibiting 99.1–100% identity to reference strains. Within H. impeltatum, 26.7% and 73.3% of ticks from El Arish were infected with R. africae and R. aeschlimannii, with 98.3–100% and 97.9–100% identity, respectively. Furthermore, 33.3% of H. marginatum marginatum ticks in Qalet El Nakhl were infected with the same two species as H. impeltatum, demonstrating 99.1–100% and 99.3–100% identity, respectively. By comparing percent identities and phylogenetic relationships, R. africae is identified for the first time in Egypt, in addition to R. aeschlimannii, which exhibits 100% identity with the Stavropol strain in GenBank. In conclusion, the obtained data underscore the medical and veterinary importance of tick-borne rickettsioses, which necessitate further investigation by authorities in Egypt. Moreover, additional characterization of these rickettsial isolates should be performed to designate their strains, using a polyphasic strategy combining genotypic and phenotypic tests, to facilitate their deposition in the rickettsial collection of the WHO and/or ATCC.

Sub-lethal effects of lufenuron exposure on spotted bollworm Earias vittella (Fab): key biological traits and detoxification enzymes activity

Spotted bollworm, Earias vittella, is one of the most serious and devastating insect pests of vegetables and cotton. Currently, insecticides are necessary for its control in nearly all crop systems. In this paper, we evaluate the sub-lethal effects of lufenuron on biological traits and activity of detoxification enzymes: cytochrome P450 monooxygenases, esterase, and glutathione S-transeferase (GST) in second instar larvae of E. vittella. Results showed that sub-lethal concentrations (LC15 and LC40 of lufenuron), prolonged larval period (at LC40 = 13.86 ± 1.22 day, LC15 = 13.14 ± 1.15 day, control = 12.28 ± 0.7), pupal duration (LC40 = 11.1 ± day, LC15 = 11.8 ± 0.28 day, control = 9.40 ± 0.52), and extended mean generation time (LC40 = 27.3 ± 0.43 LC15 = 29.0 ± 1.19 day, control = 26.0 ± 0.65). Sub-lethal exposure significantly prolonged the pre-adult stage, decreased pupal weight, and reduced adult longevity in the parent (F0) and F1 generation. Moreover, the fecundity and egg viability were significantly lowered in parental and F1 generations at both sub-lethal concentrations compared to the control. While no significant effects were noted on reproductive parameters such as the intrinsic rate of increase (r), finite rate of increase (λ), and net reproduction rate (R0) of F1 generation when compared to the control. Only mean generation time (T) in F1 at LC15 was significantly longer compared to the LC40 and control (LC40 = 3.79 ± 0.37, LC15 = 32.28 ± 1.55 day, control = 29.79 ± 0.55). Comparatively, the activities of cytochrome P450 monooxygenases and esterase were higher than GST in treated populations. The increase in resistance development against insecticides may possibly because of elevated activity of detoxification enzymes. These results provide useful information for monitoring resistance in integrated pest management (IPM) programs for E. vittella.

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Genome sequencing and assembly

With a total of 121.8× sequence data, the R. sativus genome was assembled using ≥500-bp and ≥2-kb scaffolds (Table 1). In total, 40,123 scaffolds ≥500 bp were generated spanning 383.3 Mb (N50: 138.17 kb, longest size: 1.31 Mb, average size: 9.55 kb), while 8686 scaffolds ≥2 kb were generated spanning 353.77 Mb (N50 158.63 Kb, longest size: 1.31 Mb, average size: 40.73 kb). The scaffolds ≥500 bp corresponded to 72,909 contigs with N50 of 7.12 kb, whereas the scaffolds ≥2 kb corresponded to 41,473 contigs with N50 of 8.15 kb. The quality of the scaffolds was evaluated by mapping onto the genome of 17,181 mRNA sequences from a wide variety of R. sativus cultivars (Supplementary Tables S1 and S2). The scaffolds and contigs were deposited at the DDBJ (DNA Data Bank of Japan) under accession numbers DF196826–DF236948 and BAOO01000001–BAOO01072909, respectively. We used flow cytometry to estimate the genome size of R. sativus (Supplementary Table S3) and the estimated 574 Mb genome size was similar to previous results by Johnston et al. 10 . Based on the estimated genome size, the ≥500-bp and ≥2-kb scaffolds covered approximately 67% and 63%, respectively, of the entire genome.

Repetitive sequences

In total, 140.48 Mb repetitive sequences were detected for the scaffolds ≥500 bp in the radish genome (Table 2) and 4978 unique sequences were found in scaffolds ≥2 kb. The frequency and classes of repeat sequences in R. sativus (36.61%) were similar to that in B. rapa (39.51%).

Gene models

In total, 64,657 R. sativus gene models were predicted (Table 1). Comparison with the gene models of B. rapa 3 showed a shorter average gene locus length (1724 bp in radish and 2015 bp in B. rapa) and a longer mean exon length (266 bp in radish and 233 bp in B. rapa).

To complement the annotation of the genome sequence, gene models were mapped to the longest 53,846 open reading frame (ORF) sequences from the mRNAs of young leaves (Supplementary Table S4). In total, 3650 (6.8%) gene models had no ORF hit sequences, 22,949 gene models had more than 50% coverage, 9755 gene models had more than 90% coverage and 5554 gene models had 100% coverage (Supplementary Table S5).

In total, 54,132 gene models by BLASTp and 56,539 gene models by InterProScan have been characterised in terms of protein domain or functional sites, including 31,921 gene models with Gene Ontology (GO) classification. The paths of extracted GO IDs from the top node were searched and the classification of the 2 nd node of paths is shown in Supplementary Table S6 together with the results of similar analyses for A. thaliana 11 and B. rapa 3 .

The numbers of specific and common gene families among A. thaliana 11 , Arabidopsis lyrata 12 (excluding chloroplast and mitochondrial genes), B. rapa 3 , Carica papaya 13 and R. sativus are shown as Venn diagrams in Supplementary Fig. S1. Among 200,700 protein sequences, 135,065 genes (67.3%) were clustered into 25,813 orthologous groups (Supplementary Table S7) and 6304 genes were clustered into 1272 R. sativus-specific clusters.

Phylogenetic analysis

The lineages of A. thaliana, A. lyrata and related families diverged from a common ancestor at 5 13,14 , 10 3 and 13 3 million years ago (Mya), respectively, while the whole genome triplication (WGT) in Brassica occurred about 28.3–15.6 Mya 3 and 5–9 Mya 3 . We applied OrthoMCL to the clustered and aligned gene models of A. lyrata, A. thaliana, B. rapa, C. papaya and Oryza sativa as reported by Wang et al. 3 , as well as R. sativus and then selected a “single copy gene” set. Based on the lineage I phylogenetic divergence of A. thaliana, which occurred about 13 Mya, the divergence between R. sativus and B. rapa was estimated at 16.7 Mya (95PD: 22.4–12.4 Mya), much earlier than that between A. thaliana and A. lyrata around 13 Mya (95PD: 17.4–9.7 Mya Fig. 1). The branch era between Arabidopsis and the Brassica–Raphanus clade was 38.8 Mya (95PD: 51.8–29.1 Mya) and the branch era between the Brassica–Raphanus clade and C. papaya was 104.2 Mya (95PD: 139.1–78.1 Mya Supplementary Fig. S2).

Phylogenetic tree of R. sativus, A. thaliana, A. lyrata, B. rapa and C. papaya.

The blue line represents the 95% probability density (95PD) of ages for all nodes in the tree the green line represents the most recent common ancestor (95PD: 50.7–43.2–36.6 Mya) of the Arabidopsis–Brassica clade the orange line represents the whole genome triplication (95PD: 28.3–22.5–15.6 Mya) in the Brassiceae crown group (centre of the bold character is the average). The geologic timescale below the phylogenetic tree is based on the International Chronostratigraphic Chart (v2013). Photographs were taken by Y. Mitsui.

Genome structure

In total, 1384 markers were mapped onto the pseudomolecules and spanned 179.8 Mb (137.2 Mb without gap) (Supplementary Table S8). The syntenic blocks for R. sativus vs. A. thaliana (Fig. 2a, Supplementary Fig. S3a), R. sativus vs. B. rapa (Fig. 2b, Supplementary Fig. S3b) and R. sativus vs. R. sativus (Supplementary Fig. 3c) were analysed using BLASTp and represented as “ABC” blocks 2 . The syntenic blocks for each linkage group are shown in Supplementary Fig. 4a and 4b. Based on the genome assembly, relatively large synteny blocks were observed between A. thaliana and R. sativus. Regarding the “A” block, large blocks were identified in LN7 and LN9 and small blocks in LN2, LN3, LN4, LN6 and LN8. Large “F” blocks exist in LN2 and LN3 (2 blocks) and small blocks in LN1 and LN8. Large “U” blocks exist in LN4, LN5 and LN7 and small blocks are found in LN1 and LN2. Large “R” blocks exist in LN1 and LN8 and small blocks in LN4, LN5 and LN6. “F” and “U” blocks had three synteny blocks and the blocks were recognised from self-syntenic blocks. WGT has been observed in B. rapa 3 and synteny analysis has shown that partial WGT may also have occurred in R. sativus.

Syntenic relationships between A. thaliana and R. sativus (a) and between B. rapa and R. sativus (b) based on the ABC genomic blocks.

The left arc represents A. thaliana and the right arc shows the line chart for repeat density. Red: retrotransposon, blue: DNA transposon, green: other repeat sequences.

Radish Genome Database

All sequencing data can be accessed at with BLAST and GBrowse functions.

RNA-seq and gene clustering analyses

The process of radish tuberous root development and cell proliferating patterns are shown in Fig. 3a. Radish tuber initiated at about 14 DAG and tuberisation occurred mainly by supplementation of proliferated cells from root vascular cambium (root vc) to xylem parenchyma (root xp) tissues. In root xp, enlargement of parenchyma cells was observed and cell proliferation occurred around vessels. Using the same radish strain used for genome sequencing, the global gene expression patterns in root and leaf tissues of key developmental stages were analysed. Using a single-end sequencing platform (Illumina, San Diego, CA, USA), an average of 2995 (SD: 645) million reads with 88% Q30 bases were generated from 14 cDNA libraries (Supplementary Table S9).

The process of root tuberisaiton of R. sativus var.hortensis cv. Aokubi and gene expression patterns at key developmental stages and tissues.

(a) Root thickening and cell proliferating processes in 7, 14, 20, 40 and 60 days after germination (DAG) roots. Changes in root diameter, growth rate and cell number in xylem parenchyma tissue of 7–90 DAG roots are presented. Bar = SD. Letters represent significant differences among growing stages (ANOVA post hoc Tukey HSD, P < 0.01).Transverse section of roots are shown px: primary xylem, sx: secondary xylem, co: root cortex, ep: epidermis, xp: xylem parenchyma, vc: root vascular cambium, en: endodermis, ve: vessel. (b) Number of differentially expressed genes (DEGs) in 7, 14, 20, 40 and 60 DAG roots and tissues. (c) Significantly enriched GO categories for upregulated genes in each developmental stage and tissue. The top three categories of biological process (BP), cellular component (CC) and molecular function (MF) are shown. (d) Significantly enriched KEGG pathways for upregulated genes in each developmental stage and tissue. The top three pathways are shown. Photographs were taken by Y. Mitsui.

The majority of DEGs were found between early seedling roots (7 DAG roots) and the roots at the primary thickening stages (14 and 20 DAG roots) and also between cell proliferating tissues (root vc and root xp) and cortex tissue of 40 and 60 DAG roots (Fig. 3b). The data sets from early seedling to primary growth stage (7, 14 and 20 DAG roots) and from root vc, xp and cortex tissues in the secondary growth stage (40 and 60 DAG root tissues) were grouped together to detect DEGs. ANOVA tests detected 4260 and 4526 DEGs in 7, 14 and 20 DAG roots and 40 and 60 DAG root tissues, respectively. We also detected 10,468 DEGs in 7, 14, 20, 40 and 60 DAG leaf samples.

In each of the three data sets of the DEGs, cluster analysis was performed using self-organising maps (SOMs) to identify classes of genes with similar temporal changes. The DEGs of 7, 14 and 20 DAG roots, 1538 genes in 7 DAG roots (Cluster 6), 1035 genes in 14 and 20 DAG roots (Cluster 7) and 1539 genes in 20 DAG roots (Cluster 1) were clustered as overexpressed genes (Supplementary Fig. S5). In the DEGs of 40 and 60 DAG root tissues, the clusters of 877 genes in the 40 DAG root vc and xp (Cluster 7), 1187 genes in 60 DAG root vc and xp (Cluster 1) and 1498 genes in 40 and 60 DAG root cortex (Clusters 6 and 9) were detected (Supplementary Fig. S6). The thickening tissues (root vc and xp) showed similar gene expression patterns. In the DEGs of 7, 14, 20, 40 and 60 DAG leaves, we found that the gene clusters were associated with specific developmental stages (Supplementary Fig. S7).

Gene functions and pathways involving tuberous root formation and development

Based on GO annotations, 40,705 of 65,457 Raphanus gene models were assigned GO terms. Statistical analysis revealed significantly enriched functional gene groups in each of the gene sets clustered as particular developmental stages and tissues (Fig. 3c, Supplementary Table S10). Genes related to stress and stimulus responses, transport and membrane activities were most significantly enriched in the cluster of genes upregulated at the early seedling stage of the root and leaf. In the cluster of genes upregulated in roots of the primary thickening stages, genes related to ribosomal activity, structural molecule activity and translation were most significantly enriched. In the cluster of genes upregulated in the root tissues (root vc and xp) of secondary thickening stages, genes related to membrane activities, transcription and cell development were particularly enriched, while genes related to stress and stimulus response, transport and membrane activities were most significantly enriched in the cluster of genes upregulated in root cortex tissue, similar to early seedling stage roots.

In total, 142 KEGG (Kyoto Encyclopaedia of Genes and Genomes) pathways including 13,795 genes were found in the Raphanus gene models. The significantly enriched KEGG pathways in each of the DEG clusters are shown in Fig. 3d and Supplementary Table S11. In thickening roots and cell proliferating tissues, the starch and sucrose metabolism pathway was particularly enriched. In the leaves in root thickening stages, pathways related to photosynthetic activities were activated. In root cortex tissue, the phenylpropanoid biosynthetic pathway that synthesises lignin was most significantly enriched.

Sucrose metabolism is considered important for the development of a plant sink organ. Thus, spatial and temporal changes in the expression of sucrose metabolism genes in radish sink and source tissues were analysed (Supplementary Fig. 8). The sucrose transporter genes (SUTs and SUCs) that function in cell-to-cell and long-distance distribution of sucrose throughout the plant showed relatively high expression rates in early seedling roots and leaves. The expression of genes encoding sucrose invertases, which function in sucrose cleavage, was relatively low. Among them, the cell wall invertase genes (CWIs) were expressed at a low level during all developmental stages. The expression of cytoplasmic invertase genes (CINs) increased only in the young seedling roots. We did not identify any vacuolar invertase genes (VINs) in the radish genome. Sucrose synthases (SUSs), the other enzymes involved in sucrose cleavage, showed markedly increased expression in tuberising roots and tissues. Two homologous genes of SUS1 were present and one showed particularly high expression in radish tuber, whereas these genes were expressed at low levels in the roots and leaves of early seedling stages. In the leaves of root thickening stages, the expression of SUS genes was limited. Additional RT-qPCR experiments confirmed that SUS1 genes were specifically expressed in tuberising roots and tissues and the expression levels of SUS1a were dozens of times higher than those in non-tuberising roots (Supplementary Fig. S9).

Glucosinolate biosynthesis and myrosinase genes

We investigated the genes involved in radish glucosinolate biosynthesis and degradation using radish genome information and transcriptome analysis. A core pathway of glucosinolates (GSLs) biosynthesis has been well examined and the genes have been identified in A. thaliana 16,17 . The R. sativus genome contained the majority of GLS biosynthesis-related genes (GLS genes), whereas no orthologue in the genome was observed for 10 GLS genes encoding amino acid side-chain elongation genes (MAM3, IPMI-SSU3 and IPMIDH3), core structure formation genes (CYP79F2), side-chain modification genes (CYP81F1, FMOGS-OX3, FMOGS-OX4, AOP2 and AOP3) and a transcription factor gene (MYB76) (Fig. 4, Supplementary Table S12). However, 8 genes are absent (IPMI-SSU3, IPMIDH3, CYP79F2, FMOGS-OX1, FMOGS-OX3, FMOGS-OX4, AOP3 and MYB76) in the related B. rapa genome 16 . Thus, genes that are not contained in both genomes may be lost in ancestors of R. sativus and B. rapa, or may be specific to Arabidopsis and its relatives.

Glucosinolate biosynthesis and degradation genes in R. sativus.

(a) Glucosinolate biosynthesis and degradation pathway. The number of genes in the genome is noted in brackets. Orthologues identified in R. sativus are marked in blue colour. The absence genes in the genome are marked in red. (b) Comparison of transcriptional profiles for glucosinolate biosynthesis and degradation genes. Heat maps show log2-scaled reads per kilobase per million reads (RPKM) for biosynthetic genes.

In radish roots, the tip and outer zone including peel are known to be a pungent region and isothiocyanates and glucosinolates are dominantly detected in this region 19,20 . Our transcriptional profiling has shown that numerous GSL genes were strongly expressed in root tip, cortex and vc corresponding to the pungent region in the root (Fig. 4b and Supplementary Fig. S10). Moreover, GSL genes were expressed in younger developmental stages (14 and 20 DAG), which generally showed a high accumulation of GSLs 20 (Fig. 4b and Supplementary Fig. S11). In this manner, GSL gene expression showed spatial and temporal correlations with GSL accumulation and pungency. These results indicated that the expression of GSL genes plays an important role in GSL accumulation and pungency and that their expression was coordinately regulated in radish roots. MYB28, MYB29, MYB76 and R2R3-type MYB family transcription factors have been reported to regulate the expression level of GSL genes in A. thaliana 21,22 . Based on transcriptome profiles, expression of the radish gene encoding a protein homologous to the Arabidopsis MYB29 protein showed correlations with GSL gene expression (Fig. 4b and Supplementary Fig. S12) and MYB28 showed relatively high expression in pungent tissues (Fig. 4b). These results indicate that the core glucosinolate biosynthesis pathway and the regulation mechanisms are conserved in Brassicales.

Eleven myrosinase encoding genes were identified in the radish genome. The number of myrosinase genes is distinctly large in the Brassicae and Raphanus genus in the order Brassicales. The myrosinase genes are also expressed in pungent regions of the root and middle developmental stages and were correlated with the presence of isothiocyanates (Fig. 4b and Supplementary Figs S13, S14). These findings demonstrated that transcriptional regulation of glucosinolate biosynthesis and myrosinase genes is important for determining the pungency level in radish roots.

Additional RT-qPCR experiments of four genes, MYB28, BCAT4, CYP79F1 and TGG1-3 (TGG1C), showed that these pungency-related genes were highly expressed in pungent tissues (Supplementary Fig. S15).


Estimation of genome size

The relative genome size of R. sativus was analysed using flow cytometry. The leaf samples were chopped finely using a razor blade and incubated on a petri dish containing extraction buffer. After 3 minutes, the resulting extract was passed through a CellTrics filter with 30-μm mesh. For propidium iodide (PI) staining of nuclear DNA, the CyStain PI plant DNA absolute quantitation reagent KIT05-5022 (Partec Inc., Franklin Park, IL, USA) was added to four times its volume and incubated for more than 1 hour before measurement. The relative fluorescence of total DNA was measured using the Partec CyFlow ploidy analyser (Green laser). Genomic DNA extracted from A. thaliana was similarly analysed using flow cytometry for comparison. Genome size was estimated based on the pro rata allocation between the median peak position of A. thaliana and R. sativus.

Sequencing and assembly

Genome sequencing was performed using R. sativus var. hortensis cv. Aokubi doubled haploid (DH) line provided by Sakata Seed Co. (Yokohama, Japan). High-quality nuclear DNA with reduced organellar DNA was extracted from leaves of 20-day-old seedlings using a protocol modified from Paterson et al. 56 . We prepared approximately 70-Gb sequences including paired end (PE) sequences with insert lengths of 300𠂛p and 500𠂛p using the Illumina Hiseq 2000 at the Nodai Genome Research Centre, Tokyo University of Agriculture. Long-jumping-distance (LJD) library sequences with insert lengths of 8 kb, 20 kb and 40 kb were generated using the Illumina Hiseq 2000 at Operon Biotechnologies, Inc. (Huntsville, AL, USA). In addition, about 5-Gb single end sequences (SE) were analysed using the Roche 454 FLX Titanium at the Agrogenomics Research Centre, NIAS (National Institute of Agrobiological Sciences). Flow cytometry analysis resulted in 574 Mb corresponding to 122× genome coverage (Supplementary Table S13). The sequence data were deposited at the DDBJ (DNA Data Bank of Japan) as BioProject ID PRJDB707.

The SE, PE and 8-kb insert LJD sequence reads were filtered for duplicated sequences, trimmed by Quality Value (QV) and assembled separately using Newbler (GS-Assembler version 2.7, Roche/454, Branford, CT, USA), Ray (version 2.0.0) 57 and CLC genomics workbench (version 5.5.1, CLC bio, Aarhus, Denmark). Based on subsequent evaluation of the results from these assemblers (Supplementary Table S14), we adopted the genome assembly generated by Newbler. Moreover, we removed organelle sequences from more than 500-bp contigs by BLASTn using the B. rapa ( <"type":"entrez-nucleotide","attrs":<"text":"JF920285.1","term_id":"335354838","term_text":"JF920285.1">> JF920285.1) and R. sativus ( <"type":"entrez-nucleotide","attrs":<"text":"AB694744.1","term_id":"400278294","term_text":"AB694744.1">> AB694744.1) mitochondrial sequences, and B. rapa ( <"type":"entrez-nucleotide","attrs":<"text":"DQ231548.1","term_id":"85816402","term_text":"DQ231548.1">> DQ231548.1) and A. thaliana ( <"type":"entrez-nucleotide","attrs":<"text":"AP000423.1","term_id":"5881673","term_text":"AP000423.1">> AP000423.1) chloroplast sequences were used as queries. The vector sequences were checked by BLASTn with pBACe3.6 ( <"type":"entrez-nucleotide","attrs":<"text":"U80929.2","term_id":"4878025","term_text":"U80929.2">> U80929.2) as the query. Subsequently, using the contigs and mate-pair (MP) sequences, scaffold sequences were built using SSPACE (version 2.0) 58 (Supplementary Table S14).

Evaluation of scaffolds

The quality of the scaffolds was evaluated by mapping a total of 17,181 mRNA sequences of R. sativus available at the NCBI (National Centre for Biotechnology Information) UniGene ( onto the genome using BLAT 59 .

Repetitive sequences

Scaffolds Ϣ kb were analysed using REPET 60 ,61 . The copy number of repeat sequences for scaffolds 𾔀𠂛p was determined using RepeatMasker ( (Supplementary Table S15).

Gene prediction and annotation

Gene models were generated using the gene prediction programme Augustus 62 with Arabidopsis parameters. To complement the annotation of the genome sequence, we constructed a full-length cDNA library under the same conditions as the genomic DNA used for sequencing. mRNAs were assembled using Trinity 63 to build contigs. The longest 53,846 ORF sequences were extracted from the contigs using EMBOSS 64 .

The gene models were processed by BLASTp 65 with the NCBI nr database and by InterProScan 66 . The paths of extracted GO IDs from the top node were searched, along with the classification of the 2 nd node together with the results of similar analysis for A. thaliana 11 and B. rapa 3 . The numbers of specific and common gene families among A. thaliana, A. lyrata 12 (excluding chloroplast and mitochondrial genes), B. rapa, C. papaya 12 and R. sativus are shown as a Venn diagram.

Orthologous genes

Using the CD-HIT 67 with -c 0.9 -n 5, we removed highly similar paralogous genes. After a BLASTp run with an all-against-all option, the BLAST results were fed into the stand alone OrthoMCL 68 programme using a default MCL inflation parameter of 1.5.

Phylogenetic analysis

We clustered the gene models of A. lyrata, A. thaliana, B. rapa, C. papaya, O. sativa and R. sativus using OrthoMCL (inflation factor 1.5) and selected “single copy gene” sets. The gene sets that perfectly matched with gene models assembled from the R. sativus transcriptome were selected. The branch era of each gene set was estimated using Baseml 69 (HKY85, ncatG =𠂕) and Multidivtime 70 . Before estimation of branch era, a topology of the evolutionary tree was prespecified using Clustal W2 71 and MrBayes 72 as required when using Multidivtime. To clarify the overall pattern of selected gene sets, four-fold degenerate sites were extracted for the 720 gene sets, and each gene set was aligned using Clustal Omega 73 .

The scatterplot (Supplementary Fig. S2) shows a normal distribution with minimal bias. We checked specific genes in the clustered gene set with the annotated GO of A. thaliana 74 , but could not confirm specific genes. Based on these results, we constructed a phylogenetic tree using all 720 gene sets. Due to limitations of the Multidivtime programme, each of the 30 gene sets was aligned using Clustal Omega, and 24 aligned sequences were drawn using Mutidivtime. In Fig. 2 , we adopted the calibration time of 13 Mya for the A. thalianaA. lyrata clade 23 .

Analysis of linkage groups

We constructed a linkage map with a total of 1384 markers (Supplementary Table S16) including 630 markers from the Kazusa DNA laboratory 75 , 746 markers from Tohoku University 25 and 8 markers from Chonnam National University 76 . If the assigned linkage number and direction differed from the Kazusa and Tohoku linkage maps, we used the Kazusa linkage map information, which was published previously 75 . Both markers were coordinated with A. thaliana (Supplementary Table S17).

The linkage map was used for mapping scaffolds onto linkage groups. The Kazusa markers, which consist of expressed sequence tags (ESTs) and primer sequences, were used to search for EST sequences and scaffolds by BLAT 59 . The Tohoku markers consist of primers and probes. We searched for these three sequences and scaffolds using BLAST, and 446 markers were selected with three whole sets and one error. The Korea markers consist of ESTs and primer sequences. We searched for EST sequences and/or primer sequences and scaffolds using BLAST. These three sets of markers were merged, and 1039 markers (including derivative markers) were mapped onto the scaffolds.

Syntenic analysis

The homology between A. thaliana and R. sativus was analysed using BLASTp with an e-value 1.0e-5. After filtering BLAST results using MCScan version 0.8 77 with Match_Size 40, the syntenic relationship was analysed using the Circos viewer version circus-0.63-4 78 . A similar analysis was performed for B. rapa vs. R. sativus and R. sativus vs. R. sativus.

Preparing RNA-seq samples

Seeds of the Japanese radish cultivar 𠆊okubi’ used in the genome study were sown in the experimental field of Tokyo University of Agriculture, Faculty of Agriculture, at the normal sowing time in this region (31 August 2012). Samples of roots and leaves from three seedlings at each developmental stage (7, 14, 20, 40 and 60 DAG) were collected. In radish tuberous roots, the upper part originates from the hypocotyl where lateral roots are not present and the lower part consists of true root tissue where lateral roots developed. We collected samples from the border of hypocotyl and true root tissues and immediately transferred the samples into RNAlater® solution (Qiagen, Hilden, Germany) for RNA extraction.

Total RNA was isolated from each sample using the NucleoSpin RNA Plant Kit (Macherey-Nagel, Düren, Germany). RNA quality and quantity were assessed on a 2100 Bioanalyser using the RNA 6000 Nano Kit (Agilent technologies, Palo Alto, CA, USA). Using equal volumes of total RNA from each sample, cDNA libraries were prepared using an mRNA-Seq Sample Preparation Kit (Illumina) according to the manufacturer's instructions. Illumina RNA sequencing using the Hiseq 2000 platform was performed at the Nodai Genome Research Centre (NRGC, Tokyo, Japan) in accordance with the manufacturer’s instructions.

RNA-seq analysis

RNA-seq raw reads were imported into the CLC genomic workbench, and the reads were trimmed using default parameters. The 64,657 Augustus gene model 66 was used as a reference sequence for mapping. The trimmed reads sets obtained from the cDNA libraries were mapped to reference sequences using default parameters. The reads mapped as paired reads were used for calculating gene expression values. The expression level for each transcript was calculated the using the reads per kilobase per million reads (RPKM) method. The BLAST2GO suite was used for GO and KEGG pathway analysis.

Detecting differentially expressed genes and cluster analysis

DEGS were detected between all pairs of libraries using a t-test and among the libraries grouping key developmental stages and tissues by ANOVA using a Benjamini and Hochberg false discovery rate (FDR)-adjusted significance level of π.05, a fold change of Ϣ and a minimum RPKM difference of 㸐. DEGs were clustered using a SOM algorithm and Genesis software ( A Euclidean distance metric was used and nine (3 ×𠂓) clusters were generated, which were visually inspected for similarity and differences among the gene expression profiles. Clusters were merged if they shared a similar expression profile.

Gene ontology and pathway analyses

The curated clusters of genes from SOM analysis were further investigated and mapped to significant ontologies and pathways to analyse their biological function. The Blast2GO programme was used to obtain GO annotation of the unigenes based on BLASTp hits against the NCBI Nr database with an e-value threshold of 㰐 𢄥 . Each cluster of annotated genes was mapped to the KEGG pathway database and the gene number was calculated for every KEGG pathway. Then, Fisher’s exact test was used to match the significantly enriched KEGG pathway in the DEG clusters to the genomic background.


To validate some candidate genes involved in sucrose metabolism and pungency biosynthesis, RT-qPCR experiments were conducted using LightCycler® 480 SYBR Green I Master (Roche) according to the manufacturer’s instructions, with 1 μM primers in a 10 μL final volume. Primer information is presented in Supplementary Table S18. Conditions for the amplification were as follows: a 10 min incubation at 95 ଌ, followed by 45 cycles (95 ଌ for 10 s 60 ଌ for 10 s 72 ଌ for 10 s) with a single fluorescent reading taken at the end of each cycle. All the runs were completed with a melt curve analysis to confirm the specificity of amplification and lack of primer dimers. Cp (second derivative method) values were used to estimate expression levels. The expression levels were adjusted by two housekeeping genes (Actin 79 and Calmodulin 7:CAM7).

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