Tuesday, November 14, 2006

On the Genetic efficiency of in situ conservation of germplasm

K K Vinod

In situ conservation, is the continuation of this traditional method of informal breeding that dis­tinguishes in situ from ex situ conservation on farms and in gardens. However, many developed countries now have legislation protecting plant breeders' rights, which effectively prevents the continuation of traditional agriculture and therefore in situ conservation of crop species. This section therefore applies to in situ conservation of wild species, and of crop spe­cies only in those countries where legislation permits.

Sites for inclusion in a network for in situ conservation must be chosen to maximize the diversity that can be maintained. This is similar in principle to choosing sites for collection to maximize diversity collected.

Sites should cover the entire ecological range of the species, with a bias towards its centre(s) of diversity and the ecological extremes of its distri­bution. There should be a stratified distribution of sites with several levels of clustering: each site should be large enough to encompass a cluster of several genetic populations; each site should be part of a cluster of several nearby sites, close enough for occasional gene flow between sites as a result of rare long-distance dispersal events; each cluster of sites should be part of a larger cluster; and so on to encompass the entire range of the spe­cies. Such stratification will serve a dual purpose of: (i) optimizing gene flow within and between populations; and (ii) encompassing the maxi­mum possible range of types of diversity. Within the general stratification, sites and clusters should be chosen to maximize diversity of environments and therefore of selection pressures within and between sites and clusters. As always, of course, diversity of selection pressures is taken to include artificial as well as natural selection, with diversity associated with varia­tion in local preferences and farmers' concepts of quality and agronomic value.

The shape of sites and clusters also needs consideration. For example, linear habitats may be useful to increase connectivity between clusters with minimal increase in areas of the region set aside for conservation. For rare species, there may be a need to create new popula­tions at sites with sufficient connectivity to existing populations to prevent loss of diversity through inbreeding.

Additional measures can be taken to increase biodiversity within the selected network of conservation sites, essentially by increasing the diver­sity of environments and selection pressures within and between sites.

For crop species, farmers can be actively encouraged to value the dis­tinctiveness of the traditional farming practices of the region; and the local customer community can be actively encouraged to value the distinctive­ness of local traditions and their consequent demands on local farmers. Important traditional farming practices can include factors such as con­scious selection by the farmer for genetic variation within and between varieties for tolerance to disease, drought, heat, etc. These traditions are based on utilizing high diversity to provide low-cost, sustainable, low-risk protection from environmental stresses and hazards. That is, they benefit not only conservation of biodiversity but also the farm economy.

For wild and some crop species, there can also be opportunities for increasing diversity by appropriately diverse management. Emphasis is on diverse management, as many management procedures, especially mech­anized ones, tend to reduce diversity. For example, cutting, liming, fertil­ization and control of weeds, pathogens and pests are usually applied uniformly across entire sites; in so doing they reduce environmental diver­sity and therefore the diversity of selection pressures and biodiversity at the scale of the site. If such procedures are also applied consistently from year to year, there will also be less temporal variation in selection pres­sures, again reducing biodiversity at the scale of the field. In contrast, management by grazing imposes cutting, trampling and fertilization that is spatially and temporally variable - to an extent that depends on the grazing behaviour of the selected herbivore.

Similarly, diversity of management should be encouraged at larger scales, including landscape and regional. The principal problem here relates to how to construct and implement a conservation policy. For example, a management policy may be implemented that maximizes bio­diversity within a field; but if that same policy is applied to all sites, the same range of biodiversity will be promoted at all sites, reducing biodiver­sity at the larger landscape and regional scales. If the policy is to be cen­trally established and imposed, it may be economically impossible to incorporate the larger-scale variation in management necessary to max­imize biodiversity at landscape and regional levels. A decentralized system is likely to be preferable, especially to incorporate regional varia­tions in traditions.

We have seen that biodiversity is a scale-dependent phenomenon and that for its efficient conservation we need to include all scales from a few square centimetres to thousands of square kilometres. We have also shown that the distribution of genetic diversity of any spe­cies depends on its life cycle and consequent evolutionary characteristics. Efficient conservation depends on having a good knowledge of population structure and the life cycle characteristics that determine this - dispersal profiles, breeding system and longevity. The same principles apply not only to wild species but also to crop species, the major difference being that crop species have dispersal profiles determined largely by the farmer and mar­ket, and are subject to artificial selection by the farmer as well as natural selection.


Forman, R.T.T. (1995) Land Mosaics: the Ecology of Landscapes and Regions.Cambridge University Press, Cambridge.

Sunday, July 16, 2006

On the Genetic Efficiency of ex situ germplam conservation

K K Vinod

When we plan for an expedition for germplasm collection from a region following objectives are need to be set.

1. Acquire the maximum genetic diversity of targeted taxa within the region, within the constraints of limited available resources.

2. Acquire germplasm with the maximum novelty value with respect to a collection already held ex situ; i.e. the greatest number and diversity of genes and genotypes that have not previously been collected.

3. Combat genetic erosion.

4. Acquire genes or genotypes most likely to benefit a particular breeding or research objective.

5. Acquire germplasm for analysis of agro-ecogeographic patterns of the distribution of biodiversity.

In the case of first objective, limiting resources vary from expedition to expedition, and may be time (time to travel to a site, time to collect overall site data, time to collect each seed or plant at a site, speed of returning live plants to base); space available in the collecting vehicle; or labour and facilities to process samples at base. Resource limitations influence optimal collecting strategy in a way that depends on population structure.

For the objective 2 above, except that additional information is needed on the diversity and origins of the pre-existing collection.

Where the primary objective is to combat genetic erosion (objective 3 above), sampling strategy can and should still be designed to satisfy objec­tive 1. However, painstaking planning to maximize the diversity collected may be counterproductive where the rate of erosion is so high that diver­sity is lost whilst planning is in progress. In these circumstances, speed of undertaking a collecting expedition is of overriding importance.

Objective 4, a breeder-driven collection to support a particular breed­ing objective, requires a totally different sampling strategy, to locate par­ticular genes rather than maximize diversity of genes. Nevertheless, knowledge of evolutionary patterns can aid identification of sites most likely to contain the desired genes or genotypes.

Objective 5, collection for agro-ecogeographic analysis, requires yet another strategy, namely an appropriately randomized sampling proce­dure. This fact is not sufficiently recognized, as many published analyses are based on collections made for conservation or breeding purposes. Yet any sampling strategy that aims to maximize diversity or to target specific genes can generate incorrect and misleading estimates of components of variance. For example, suppose two collections are undertaken in two dif­ferent regions, both with a sampling strategy to maximize the diversity sampled within each region. A comparison of both collections will then incorrectly suggest that there is less difference between them and more variation within each region than is really the case.

A specific example of an erroneous conclusion may be the widely accepted latitudinal cline in genetic diversity of Trifolium repens across Europe, according to which southern populations are believed to be highly diverse and northern ones uniform. This is likely to be spurious, and at least partly a consequence of collections being specifically targeted at well-managed pastures in the north but at highly diverse habitats in the south. A northern collection targeted at diverse hab­itats contained as much diversity as southern populations (Hamilton, 1980).

Appropriate randomization for agro-ecogeographic analyses need not mean full randomization. Collecting for maximum diversity can be com­patible and even beneficial to agro-ecogeographic analysis. Seeking to col­lect maximum genetic diversity by targeting maximum environmental diversity improves the sensitivity of analysis of the relationship between genetic diversity and environmental diversity. This of course requires col­lection of all relevant environmental data so that they can be incorporated as independent variables in statistical analysis.

Collections targeting spatial scale of biodiversity and overall distribution of sites

The general scaling properties of biodiversity have two imme­diate implications. First, it is important to cover as large an area as pos­sible. Second, adjacent sites should not be further apart than the genetic patch size, since increasing the geographical distance beyond this does not increase the expected genetic distance between two populations. For this purpose, genetic patch size should be measured using neutral genes, to provide a general baseline sampling strategy that is not influenced by any particular pattern of environmental diversity

At the lower end of the scale, the genetic neighbourhood area defines the minimum possible scale for taking distinct population samples, at least of the seed population. At smaller scales mating is random and Hardy-Weinberg equilibrium is expected, with no possibility of division into genetically distinct subpopulations. This applies only to seeds: the population of adult plants may show genetic subdivision at smaller scales if the environment is heterogeneous at smaller scales, imposing smaller scale heterogeneity of pressures within the genetic neighbourhood. Thus there may be merit in finer-scale sampling of adult populations than seed populations.

However, the genetic neighbourhood area of most wild plant species is remarkably small, far smaller than the unit regarded as one population by the collector. For the insect-pollinated self-incompatible perennial Trifolium repens the reproductive genetic neighbourhood area is 2m2; for the wind-pollinated self-incompatible per­ennial Lolium perenne it is 8.4 m2. In practice, therefore, each sample of a wild population in an ex situ collection almost invariably comprises genotypes from what were originally numerous dis­tinct genetic populations.

The genetic neighbourhood area of crop plants is closely related to the type of farming. In primitive farming communities it is generally much smaller than for modern agriculture. Farmers in such communities usually maintain and select their own seed, with limited 'dispersal' (by seed exchange) between isolated communities or even between farmers within communities. It is essential, when collecting, to determine what are the local customs in relation to seed selection and exchange, especially (i) whether a formal centralized system exists for exchanging seed, or whether exchange is informal and centralized through the market, or informal and localized to individual farmer-farmer interactions; and (ii) how much farmers rely on their own farm-saved seed, and if so whether they consciously make their own selections. Only with such local knowledge can the collector judge the probable scale of distribution of diversity.

Collections targeting by habitat and adaptation to environment

Targeting the maximum diversity of habitats for collection will maximize the diversity of genes contributing to adaptation to the selection pres­sures imposed in the environments sampled. It will also maximize diver­sity of genes closely linked to the adaptive genes and of pleiotropic characters. It will have no effect on the diversity of genes that are neutral for the particular environmental diversity sampled - this includes not only genes that appear neutral with respect to all known selection pres­sures, but also genes that are non-neutral for different types of environ­mental diversity.

Effective environmental targeting in this manner depends on the col­lector having good knowledge of environmental diversity in the region, and of the distribution of the target taxa in relation to environmental diver­sity. Much of the planning phase of a collection should be devoted to iden­tifying contrasting environments, using as many sources of information as possible, preferably in map form: not only conventional geographical maps, but also maps of surface geology, soil, temperature, rainfall, vegeta­tion and land use. Much additional information is not available in map form, and may not be readily available prior to the expedition, being in the knowledge domain of local extension scientists and farmers. Relevant local knowledge covers not only natural variation between fields but also diver­sity in farmer-selection pressures resulting from variation in crop usage and variation in preferred crop characteristics.

Collections targeting centres of diversity

It is now widely accepted that evolution does not progress at a uniform rate, but involves periods of relative stability interspersed with periods of rapid change. Exactly how and how much the rate of evolution changes is still the subject of debate. Nevertheless, for most species and genera it is possible to identify centres of diversity, associated with a phase of rapid diversification at some stage in their evolutionary history.

Centres of diversity are most strongly developed for crop species, leading to the famous pioneering work of Vavilov (1951). These centres are associated with early agricultural developments. They are attributed to disruptive selection caused by the simultaneous action of natural selection for fitness and artificial selection for agronomic value, combined with diverse artificial selections applied by different farmers in different envi­ronments, and with introgression between conspecific crop and wild rela­tive.

By definition, a collecting expedition will obtain the greatest diversity if it is located within the centre of diversity of the target taxa. The content of ex situ collections should therefore contain a bias in favour of popula­tions from the centre of diversity.

Sampling targeting environmental heterogeneity: stratified sampling

The environment is a multidimensional entity. Genetic adaptation to environment is correspondingly multidimensional. Different environmen­tal variables show different patterns of variation in space and time. Therefore genetic variation for adaptation to different environmental vari­ables also shows different patterns. For example, Hamilton (1980) collected Trifolium repens from an area of high diversity of soils and grass­land management but uniform climate. Relative to the global diversity pre­sent in the entire gene pool of T. repens, genetic diversity between populations was high for vegetative and morphological characteristics important for adaptation to soils and management but low for time of flowering. More generally, it may be, for example, that populations from adjacent fields differ mainly in genes affecting response to management; ones from nearby fields differ mainly in genes for response to aspect; ones further apart differ mainly in genes for response to soils; ones from differ­ent altitudes differ mainly for response to temperature; ones from differ­ent villages for local human preferences; ones from different latitudes for response to day length; and so on.

Given this situation, a stratified sampling strategy will not just max­imize the genetic diversity collected; it will maximize the diversity of dif­ferent types of genetic diversity collected. A particular advantage of stratified sampling is that it does not depend on prior knowledge of the different scales of heterogeneity of different envi­ronmental attributes. Although such knowledge helps, nevertheless the fact that different environmental variables show different scales of hetero­geneity is itself sufficient to make a stratified sampling procedure more efficient in obtaining qualitatively different types of genetic diversity.

For some purposes, the stratification of sampling procedure should be extended to sampling individuals within sites, at least for natural popula­tions. Certainly this will maximize within-accession diversity sampled from such populations. For example: sampling several individuals from a single genetic population will sample diversity in genes that are truly polymorphic at the genetic population level; sampling from different quadrats within a field will acquire diversity in genes responsible for micro scale adaptation to patchiness of the vegetation, soil characteristics, and microflora, microtopography, etc.; and samples from the boundaries of the field are more likely to contain immigrant genes from nearby, differ­ently adapted populations.

Stratification of sampling procedure within a population is rarely appropriate for crop populations and market populations. Even for natural populations it may not always be appro­priate. In particular, by maximizing within-population variance, a stratified sampling procedure will invalidate agro-ecogeographical comparison of dif­ferent populations. If this is important, a random sampling procedure is more appropriate, unless the individual plants are maintained separately.

For species where it is difficult, or even impossible as routine practice, to distinguish plants from each other - as with most perennial herbaceous species communities - it may be impossible to take a truly random sam­ple. In these species, only inflorescences, or leaves, or some other part of the plant, can be sampled at random. This inevitably introduces a size bias into the sample in favour of those plants with the most inflorescences, leaves, etc.

Sampling targeting breeding system and adjustment of sampling procedures

The breeding system has a major influence on the distribution of genetic diversity. A number of mechanisms operate to fix par­ticular variants in lines: inbreeding fixes it through homozygosity; apo­mixis fixes variants even in heterozygotes; some complex chromosome linkages, like those in Oenothera, operate to minimize recombination. All these cases reduce within-population variance, so that a correspondingly increased proportion of the total gene pool is represented by variation between populations. In contrast, outbreeders show higher within-population variance. Sampling procedures must be adjusted corres­pondingly, to take relatively few individuals from many populations of inbreeding, apomictic and similar species, and many individuals from each of fewer populations of outbreeding species (Marshall and Brown, 1975).

Vegetative propagation (by stolons, bulbs, rhizomes, etc.) is function­ally equivalent to apomixis in that it can generate numerous genetically identical plants. However, vegetative propagation is often associated with outbreeding, generating a complex two-level population structure. There is high genetic variance among the individuals originating by sexual reproduction through different zygotes, and zero genetic variance (ignor­ing somatic mutations) among the vegetative progeny derived solely by mitotic division from a single zygote.

In many such vegetatively reproduced species it is impossible to know at a glance whether two plants are derived from the same or from differ­ent zygotes. In these species the two-level population structure can present very considerable problems for collection for efficient conservation. The commonest approach is to ensure a large enough distance between sam­pled individuals so as to be reasonably confident that they are genetically distinct. However, a single clone of even small herbaceous species can cover hundreds or thousands of square metres. The distance between adjacent samples therefore has to be undesir­ably large, in that it eliminates sampling the genetic diversity that is expressed at smaller scales. For many species there is no satisfactory reso­lution to this problem, as the only resolution may be intensive sampling followed by genetic fingerprinting to determine the genotypic composition of the population sample, which of course is unjustifiably labour intensive.

Populations of these species often show a highly skewed distribution of physical size of genotypes, with a few large genotypes and many small ones (Hamilton et al., 1996). When population sam­ples are based on a random selection of inflorescences or leaves, the sam­ple will be strongly biased in favour of the few large genotypes.

Collections targeting temporal scale of biodiversity

Little attention has been paid to the temporal scale of biodiversity for con­servation purposes. Whilst the importance of cyclic fluctuations, chaotic changes and continuous directional shifts are all well acknowledged and documented, it has rarely if ever been considered justifiable for conserva­tion purposes to return to the same sites for repeat collections. The only common reason for returning to a site or region is to test specific hypothe­ses, for example to test the extent of genetic erosion.


Hamilton, N.R.S. and Chorlton, KH.C. (1995) Collecting vegetative material of forage grasses and legumes. In: Guarino, L, Ramanatha Rao, V and Reid, R. (eds) Collecting Plant Genetic Diversity: Technical Guidelines. CAB International, Wallingford, UK, pp. 467-484.

Hamilton, N.R.S., Jones, D., Cresswell, A. and Fothergill, M. (1996) Genetic diversity and sustainability of clover-based pastures: 2. Size hierarchies and sampling bias. In: Younie, D. (ed.) Legumes in Sustainable Farming Systems. Symposium of the British Grassland Society, Aberdeen. pp. 179-180.

Marshall, D.R and Brown, AH.D. (1975) Optimum sampling strategies in genetic conservation. In: Frankel, O.H. and Hawkes, J.G. (eds) Crop Genetic Resources for Today and Tomorrow. Cambridge University Press, Cambridge, pp. 53-80.

Vavilov, N.I. (1951) The origin, variation, immunity and breeding of cultivated plants (translated by KS. Chester). Chronica Botanica 13, 1-366.

Sunday, June 25, 2006

Characterization of variability and population structure

K K Vinod

The state of variability within and between populations can be determined by application of both biometrical and molecular procedures. Whilst the former can describe a population in terms of means and variances and the underlying mode of gene action, if an appropriate biometrical design is applied as part of the characterization of a population (Kearsey, 1993), it is only the procedures of molecular genetics which allow a measure of population structure at the level of the gene and genome to be gained. Various molecular tools are available for the characterization of popula­tions. The most widely used to date is electrophoresis of isozymes, but direct DNA methods, including restric­tion fragment length polymorphisms (RFLPs), randomly amplified poly­morphic DNA and amplified fragment length polymorphism (AFLP), are now being exploited. The application of these procedures allows several different parameters of variability within and between populations to be determined. These include the percentage of polymorphic loci, average and effective numbers of alleles per locus, heterogeneity and heterozy­gosity indices and the various measures based upon the F statistics of Wright (1965).

More recently the application of DNA-based technologies, particularly 'fingerprinting', has provided a wealth of infor­mation on the diversity of wild populations and the relatedness of cultivars. For wild species these techniques have been applied to answer­ing specific questions particularly in relation to breeding systems. A com­parison of Plantago spp. using RFLP analysis revealed by the M13 probe showed that the inbreeding P. major possessed little variation within pop­ulations but marked differentiation between populations whilst the out­breeding P. lanceolata possessed high variability within populations but only moderate variability between populations. Similarly, in an analysis of cultivar differentiation in three species of Bermuda grass (Cynodon), using DNA amplification fingerprinting (DAF), were able to distinguish some closely related cultivars. On the basis of this technique's discriminatory power they recommend that it be used as a method for seed certification and registration purposes. These are just two examples of the many that have been carried out on a wide range of species exploiting the 'fingerprinting' capacity of the molecular methods.

In the majority of applications of these DNA-based technologies com­parisons are based upon statistical analyses of the number of 'bands shared'. Such a procedure can be fraught with problems both on a techni­cal and a genetic level. Some of the technical problems and other sources of error which can be encountered in the preparation, running and read­ing of gels have been considered by Weising et al. (1995), who emphasize the need for technical care and caution in scoring closely spaced bands. In addition there is also the question as to whether two DNA fragments which migrate to a common position on a gel are homologous. This may only be ascertained by extraction of the bands and comparative cross-­hybridization. In RAPD analysis of the Lolium/ Festuca complex of species it was found that four out of six amplification products were homologous when tested by Southern hybridization. Although this is a small sample and ranged across genetically diverse species, it does emphasize the need for caution in assuming homology.

The use of individual isozyme loci and similar genetic markers, as measures of variability, is limited in that they give no indication of the genomic associations that are of importance in the maintenance of co-­adapted gene complexes. It is only by looking at combinations of markers that such information can be ascertained. In Avena spp. and Hordeum spp., for example, Allard and his coworkers (Allard, 1990; Allard et al., 1993) have shown by comparisons involving up to 14 discrete loci that popula­tions are made up of individuals containing differing multilocus assem­blages of favourable epistatic combinations of alleles. These have arisen by rare outcrossing followed by inbreeding to near homozygosity. In A. hir­tula, for example, a majority of Spanish populations were found to be poly­morphic for different multilocus genotypes, which suggests that 'interactions at the interplant level may contribute to adaptive significance' (Allard et al., 1993). In addition, in this species, polyploidy is present which, in its own right, can lead to a greater allelic diversity and potential for differing multilocus associations. Here again the breeding system rein­forces the stabilization of such associations by restricting the degree of recombination that takes place.

The current procedures using molecular markers for assessing popula­tion differentiation consider both expressed and non-expressed parts of the genome. Given the ease with which genetic maps may now be con­structed, it seems likely that, in future, measures of population differentia­tion will take into account genome organization and will target those regions of interest. Already this problem is being addressed as a means of determining identity by descent as part of the statutory procedures in determining 'essential derivation' of cultivars (Dillmann et al., 1995).

Recent developments in QTL analysis of crop plants in defined popu­lations, such as F2s and recombinant inbred lines, are now bringing together the power of genome analysis at the molecular level and biomet­rical procedures which will eventually allow a more detailed understand­ing of the genetic architecture of traits of both agronomic interest and of importance to evolutionary fitness.
These various studies of population structure provide an insight into the manner in which variability is distributed within a species and some of the factors controlling that pattern. From a conservation aspect it is now neces­sary to consider how these mechanisms interact to determine the spatial dis­tribution of variability and their implications for collection and conservation.


Allard, R.W. (1990) Future directions in plant population genetics. In: Brown, AH.D., Clegg, M.T, Kahler, A.L and Weir B.S. (eds) Plant Population Genetics, Breeding, and Genetic Resources. Sinauer Associates, Sunderland, MA, pp. 43-63.

Allard, R.W., Garcia, P., Saenz-de-Miera, L.E. and Perez de la Vega, M. (1993) Evolution of multilocus genetic structure in Avena hirtula and Avena barbata. Genetics 135, 1124-1139.

Dillmann, C, Charcosset, A, Bar-Hen, A, Goffinet, B., Smith, J.S., Datte, Y. and Guiard, J. (1995) The estimation of molecular genetic distance in maize for DUS and ED protocols: optimisation of the information and new approaches of kinship. BMT /3/6. UPOV; Working Group on Biochemical and Molecular Techniques and DNA Profiling in Particular. Upov, Geneva, pp. 2-27.

Kearsey, M.J. (1993) Biometrical genetics in breeding. In: Hayward, M.D., Bosemark, N.O. and Romagosa, I. (eds) Plant Breeding: Principles and Prospects. Chapman & Hall, London, pp. 163-183.

Weising, K., Nybom, H., Wolff, K and Meyer, W. (1995) DNA Fingerprinting in Plants and Fungi. CRC Press, Boca Raton, FL, 322 pp.

Wright, S. (1965) The interpretation of population structure by F statistics with special regard to system of mating. Evolution 19, 395-420. 

Wednesday, June 21, 2006

Genetic makeup and variability

K K Vinod

The genetic structure of a population determines its capacity for response to selection, both natural and artificial, and as such is of primary consid­eration in the formulation of strategies for the collection and conservation of biodiversity. The structure of the population is controlled by several fac­tors such as its life form, breeding system and effective population size. These factors, which often reflect past selection pressures, all influence the nature and maintenance of genetic variation both within and between populations and in some cases may themselves be subject to genetic deter­mination. In the conservation of biodiversity it is the underlying genetic control of variability that is of major importance in determining appropri­ate strategies.

The phenotype of an organism is controlled by a multitude of genes which act both individually and in concert upon the various stages of develop­ment and are influenced to varying degrees by the environment. Their action leads, in the majority of cases, to a quantitative expression of growth forms which are continuously distributed in nature. The genetic control of these quantitative traits is by sets of genes (polygenes or quantitative trait loci) each of small effect; although these may be difficult to identify individually, they are inherited in a Mendelian manner and show all the properties of major genes, i.e. linkage, dominance, epistasis and the effects of ploidy. The study of such traits has in the past required the application of biometrical procedures utilizing means and variances, but develop­ments in molecular techniques for genome analysis and genetic mapping offer the prospect of more precise identification of single quantitative trait loci.

The behaviour of genes determining quantitative traits in a population is the same as that of major genes. If random mating is the mode of repro­duction, at a single locus level the individual genotypes are to be found in the Hardy-Weinberg proportions, p2:2pq:q2, where p and q represent the diallelic frequencies. When extended over many loci it can be seen that the extreme homozygous classes and thus phenotypes are rare in the popula­tion. These genotypes, which represent free variability and are directly fix­able by selection, have the capacity by hybridization and segregation to create all intermediate genotypic classes. In doing so, the majority of individuals produced will be of differing homozygous/het­erozygous genotypic combinations and, as such, will give rise to interme­diate phenotypes. These differing genotypic classes again have the potential, by hybridization and segregation, to release variation. Here, however, this hidden variability is in two states, the homozygotic and het­erozygotic (Mather, 1973). As the number of genes controlling a trait increases, the proportion of variability exposed to the rigours of selection in the homozygous state will decrease.

The mode of gene action will also influence the state and proportion of exposed variability. The effects of dominance will be two-fold depend­ing on the direction of dominance at the individual loci concerned. Firstly, if all dominant alleles are acting in the same direction the effect will be to reduce the number of phenotypic classes observed as the heterozygous classes will be indistinguishable from the dominant homozygotes. As a consequence, selection will be more difficult as potential variability will still be present in the heterozygotes and can only be revealed by progeny testing. The distribution of individuals will be very much skewed in the direction of the dominant expression. Secondly, if dominance is ambidirec­tional, the effect will be to increase the proportion of intermediate pheno­types in the distribution and with it the release of variability and the potential for response to selection. Nonallelic interaction will to some extent reinforce the effects of dominance in leading to a reduction in class frequencies and the mean expression of a trait in a population.

The evolution of the genetic architecture of a trait is governed by the components of the genetic system (Darlington, 1958), namely the creation of new variation by mutation, recombination and the breeding system. These, when coupled with selection and/ or genetic drift, are the major determinants controlling the manner in which variability is organized within a population.

Genetic variation due to mutation

Mutational change at the DNA level of the genome is the basis of new variation and can take several forms such as base pair deletion, duplica­tion or rearrangement. Its effect may be detectable at the molecular level, as for example in the changes that lead to differing forms of an enzyme (allozyme), which in most cases would be neutral in its action, or it may have a gross effect on the phenotype such as in flower form or colour. Most mutational changes are considered to be deleterious in that they generally disrupt the hitherto integrated structure of the gene. However, some may be advantageous, with their subsequent survival and spread in the population being dependent on such factors as selective advantage, population size and genetic drift. If the mutation is recessive, as in most cases, its frequency in the homozygous state will initially be very rare in outbreeding species, hence the likelihood of exposure to the rigours of selection is very low. However, mutations that affect the breeding system can be at an immediate advantage. The occurrence of a mutant incompat­ibility allele in a single-locus gametophytic system, such as occurs in Trifolium repens, would be advantageous in that it is directly exposed in the haploid phase in the pollen grain and can be effective in promoting fertilization. In that it provides a further option for cross-pollination to occur its survival in the population/ species is ensured. This may well account for the very high number of incompatibility alleles that can be found in species with gametophytic systems.

Adaptive change may arise in a population through alterations at the chromosomal level. This may take the form of structural or numerical change such as gross deletions, inversions, interchanges, aneuploidy and polyploidy. The mechanisms and origin of these types of change are well documented (Darlington, 1956). It is their influence on the maintenance and release of variability and the opportunity they provide for new adap­tive forms to arise which are of importance from a conservation aspect. Polyploidy, for example, which may arise by the direct doubling of a chro­mosome set or be coupled with wide hybridization, is well known as a mechanism for maintaining heterozygous combinations of genes (Stebbins, 1950).

Genetic variation due to recombination

The role of recombination in controlling the release and distribution of variation within a population is of fundamental concern in the develop­ment of strategies for the conservation of genetic resources. It has long been established that the mechanisms controlling chromosome pairing, and the frequency and position of crossing over in the genome are under genetic control. The evolution of the Ph (pairing) gene on chromosome 5B of wheat has led to the regu­lar diploid pairing that takes place, and with it the stability and fertility of a diploid as opposed to the instability and sterility of an allopolyploid. Selection, irrespective of whether it be natural or artificial, can lead to marked differences in the rate of recombination between populations. In the outbreeding species Lolium perenne and Festuca pratensis bred cultivars have a higher chiasma frequency than their wild counterparts. This has arisen as a correlated response to selection for varia­bility by the breeder. Similarly the presence of B chromosomes can influ­ence chiasma frequency. The fine-scale collinearity of cereal and grass genomes should enable strategies to be developed for the positional cloning of the gene(s) controlling chromosome pairing in wheat and the forage grasses, opening up the prospect of genetically manipulating the processes of recombination at will and, with it, the range of variation that may be extracted from a population.

Genetic variation due to selection, drift and gene flow

The differentiation of populations depends on the three processes of selec­tion, drift and gene flow. The forces of selection, reflecting the environmen­tal pressures acting upon the population, are instrumental in defining the underlying genetic structure. The differing modes which it may take, such as stabilizing, disruptive or directional, each have their own effect upon the subsequent gene action and organization of the variation (Mather, 1973). Random drift, particularly in small populations, can lead to arbit­rary fixation of genes. The immigration of new genes from distinctive neighbouring subpopulations can increase the extent of both selective response and drift by introducing new alleles; or it can reduce it by repeatedly introducing genes adapted to a different microenvironment and by so doing retard micro-adaptation to local patches. In addition, life form and the persistence of seed banks may all influence the capacity for selection to lead to local adaptation.

Variability in breeding systems

The flow of variability within a species is dependent on its mode of repro­duction. Sexual species, which may be either inbreeders or out-breeders, have the capacity for recombination and as a consequence variability may be exposed to selection. Asexual forms, which reproduce either by apo­mixis or vegetative means, maintain a uniform genotype, which may be well adapted to present selective forces, but lack the ability to respond to changing conditions. The breeding system is often under genetic control and may be associated with specific life forms. Inbreeding, which is pre­dominantly found in annual life forms, often at the limits of a species dis­tribution (Stebbins, 1950), is generally achieved by mechanisms that ensure self-pollination. Pollen may be shed within closed florets (cleistogamy), as in wheat and barley, or flowers may open and be receptive when anther dehiscence occurs (chasmogamy), as in tomato. Although these mecha­nisms are under precise genetic control, breakdown may occur, allowing outcrossing to take place. In barley, for example, Allard and Hansche (1965) showed that up to 1% outcrossing may be found under some envi­ronmental conditions. Novel recombinants will appear offering scope for further selection and evolutionary change.

Outbreeding is generally found in the more perennial species and is often promoted by one or more genetically controlled mechanisms. These may range from timing differences in anther dehiscence and the receptiv­ity of the stigma through to precisely controlled incompatibility systems. The consequence of such processes is the mainten­ance of a high level of heterozygosity within the individual and variability both between individuals within the population and between populations. This aspect of population structure will be considered in more detail in a later section.

The apomictic mode of reproduction, which involves the production of seed by asexual means, is found in many genera, predominantly of the Gramineae and Rosaceae. It is generally associated with polyploidy and can be obligate or facultative. In those cases where sexual relatives are to be found, which allow genetic analysis, it has been shown to be under simple genetic control. For example, in Panicum maximum it appears to be under the control of a single dominant gene whilst in Citrus several genes are involved. Apomixis has the attribute of maintaining well-adapted combinations of genes together but has the disadvantage that there is no flow of variability and as such the species may well be at an evolutionary dead end (Stebbins, 1950).

Truly vegetative reproduction is rare but like apomixis can lead to the widespread distribution of a species. Spartina anglica is now to be found all around the shores of Great Britain having spread from its origins in Southampton Water by the continual breakup of its rhizomes. It is a repro­ductive mode that is often exploited by humans to maintain and distribute a crop species, as in the potato.

Each of these reproductive modes can be under genetic control and thus subjected to the forces of natural selection in the same manner as the genes responsible for other traits of adaptive significance. An insight into their effect on the state of variability and structure of populations can be obtained from the numerous studies of molecular markers in plant popu­lations.


Allard, R.W. and Hansche, P. E. (1965) Population and biometrical genetics in plant breeding. In: Geerts, S.J. (ed.) Genetics Today, vol. 3, Proceedings of XIth International Congress of Genetics, The Hague, Netherlands, 1963. Pergamon Press, Oxford, pp. 665-668.

Darlington, C.D. (1956) Chromosome Botany. Allen & Unwin, London, 186 pp.

Darlington, C.D. (1958) The Evolution of Genetic Systems. Oliver & Boyd, London, 265 pp.

Mather, K. (1973) Genetical Structure of Populations. Chapman & Hall, London, 197pp.

Stebbins, G.L (1950) Variation and Evolution in Plants. Columbia University Press, New York.

Wednesday, April 12, 2006

Conservation of plant genetic resources


Maintenance of biodiversity is an essential prerequisite for the continued production of new cultivars of current crops, for the development and exploitation of newer crops.

In situ conservation is the conservation in any habitat where the germplasm normally occurs, not only in natural habitats, but also in farms, gardens and other man-made habitats of relevant germplasm. Ex situ conservation on the other hand refers to any collection maintained outside the normal habitat of the germplasm including seed collections and in vitro tissue cul­ture, and also living collections in botanic gardens and collections of spe­cies with recalcitrant seed.

The objective of in situ conservation, at least for agricultural purposes, is to conserve the maximum possible number of alleles and/ or maximum possible diversity of genotypes whilst permitting continued evolution. This is of importance in generating new genes or genotypes, particularly: (i) in response to changing environments, e.g. genes for resistance to newly evolved strains of pathogens; and (ii) by continued selection of landraces by farmers or gardeners (at least where law still permits). Additional ben­efits include conservation of much more biodiversity - entire ecosystems - than just the targeted crop germplasm. Against this is the disadvantage that the germplasm cannot be efficiently utilized because characterized genotypes cannot be readily tracked.

The objective of ex situ conservation is to maintain a collection contain­ing as many alleles as possible, and/ or as diverse a range of gene combina­tions (i.e. genotypes) as possible, in a form that can be readily utilized for breeding and research. For efficient utilization, genetic variation within the collection must be appropriately characterized. For efficient conservation, ideally the collection should be as small as possible commensurate with conserving maximum diversity. In practice, in the face of rapid genetic ero­sion it is often necessary to collect germplasm before it can be ascertained that it contains genes or genotypes not already present in the collection: most collections are therefore considerably larger than strictly necessary for the diversity they contain.

There are three groups of implica­tions for efficient conservation.

First, efficient collection of diverse germplasm for ex situ conserva­tion depends on having good knowledge of the spatial distribution of genetic diversity. Inevitably it is not possible to know the exact location of every genotype. Instead, a good understanding of the factors that control the distribution of genetic diversity is necessary to devise a collecting strat­egy that maximizes the diversity sampled.

Second, in addition to efficient construction of an ex situ collection, effi­cient maintenance of the same also depends on good understanding of the factors that control the distribution of genetic diversity - in this case to control the genetic shifts that occur whenever a population is sampled, subsampled or regenerated.

Third, efficient in situ conservation depends on good knowledge of the distribution of genetic diversity in space and time, and of the factors that control its distribution. In particular, an in situ conservation area must have a size, heterogeneity and structure that maximize genetic variance maintained by evolution.

The efficient achievement of both the primary objectives requires a knowledge of the genetic nature of variability, population structure, the distribution of diver­sity and the factors that control them.

Tuesday, February 28, 2006

Some sugarcane facts…………

K K Vinod

Sugarcane (Saccharum officinarum) falls under the family Graminae, is known to be under cultivation in India from the Vedic times. India is considered to be one of the centres of diversity for Saccharum and allied genera. Sugarcane is one of the important agro-industrial crops in the country. Sugarcane is grown in India in 3.8 million hectares, producing 300 million tonnes of cane at approximately 71 tonne/ha of cane yield. The country produces about 20 million tonnes of sugar through 470 sugar mills spread all over the country giving employment to around 20 million people directly or indirectly. Of the total sugarcane production, about 60 per cent is utilised by the white sugar industry and the rest for gur, khandsari, seed, chewing etc. India is the highest producer of sugar in the world at present, however, the demand for sugar for internal consumption is growing due to the increased per capita consumption and the increase in population size. The increased requirement of sugar has to be met mostly through increased production per hectare since there is no possibility of further increase in the area under sugarcane due to competition from other crops, urbanisation etc.

The theoretical maximum yield of cane has been estimated to be 339.42 tonnes per hectare on the basis of the efficiency (3.6%) of use of total incident solar radiation. The world’s highest recorded yield is reported to be 255 tonnes per hectare. Recently, farmers in Gujarat are reported to have achieved yields as high as 340 tonnes per hectare. Compared to these yield levels, the national average is around 71 tonnes with the yields in various states ranging from 46 tonnes in Bihar to 113 tonnes in Tamil Nadu. Thus there is ample scope for improvement of cane and sugar productivity in the country.

The Genus Saccharum and the ‘Saccharum Complex’

Sugarcane belongs to the family Graminae in the genus Saccharum, a member of the tribe Andropogoneae abundant in tropical and subtropical regions. The term ‘Saccharum complex’ was used by Mukherjee (1957) to denote that the genera Saccharum, Erianthus (sect. Ripidium), Sclerostachya and Narenga constituted a closely related interbreeding group involved in the origin of sugarcane, to which Daniels et al. (1975) added the genus Miscanthus sect Diandra Keng (Table). The taxonomy, evolution, distribution and characteristics of genera in the Saccharum complex and the species of the genus Saccharum have been reviewed by Daniels and Roach (1987). Salient features of the Saccharum species and of the allied genera relevant to their use in pre-breeding are outlined.

Species of Saccharum complex

Chromosome numbers (2n)
Saccharum spontaneum
40, 48, 56, 64, 80, 128
S. officinarum
S. barberi
S. sinense
111 - 120
S. robustum
60, 80
S. edule
60, 80
Narenga phorphyrocoma
Sclerostachya fusca
Erianthus spp.
20, 30, 40, 60
Miscanthus spp.
30, 40

S. officinarum L., an octaploid, 2n = 80, indigenous to New Guinea, has provided the genetic background and the sucrose genes of modern sugarcane hybrids. Clones of S. officinarum have thick stalks, high juice purity, low fibre and starch content, low vigour and adaptability to environmental stresses, and they are susceptible to diseases.

S. spontaneum L., 2n = 40-128, is distributed widely from New Guinea, the Mediterranean to Africa. Clones of S. spontaneum are highly polymorphic from bushy types to tall stalks with low sucrose and high fibre content. They played an important role in providing disease resistance and vigour to modern hybrids.

Saccharum robustum Brandes and Jesweit ex Grassl., indigenous to New Guinea, has stalks of up to 10 m high which are hard, woody and pithy with little juice. Five groups are recognized with two cytotypes 2n = 60 and 2n = 80 (Price, 1965). This species contributed towards the evolution of some Hawaiian varieties.

Saccharum barberi Jesw. and Saccharum sinense Roxb., 2n = 81-124, presumably evolved in Northern India and China, are characterized by thin to medium stalks, low sucrose, high fibre and tolerance to stress conditions. They are of limited fertility and their use in breeding is restricted. Molecular studies have confirmed that both S. barberi and S. sinense possess S. officinarum and S. spontaneum genomes.

The genus Erianthus Michx Sect. Ripidium Henrard, 2n = 20-60, is distributed in India, South­east Asia to Japan, Indonesia and New Guinea. Seven species are described. Clones of Erianthus are highly vigorous, tall with slender stalks of good diameter and display disease resistance, excellent ratooning ability and drought tolerance.

The genus Miscanthus Anderss., 2n = 38-114, is distributed from Tahiti through Eastern Indonesia, Indo­China to northern China, Siberia and Japan. The species vary from small wiry­leafed types to taller ones, occurring from sea level in Indonesia to 3300m in Taiwan. Four sections have been described with prominent species.

Saccharum has also been successfully crossed with Sorghum and Zea mays. Several earlier reports of hybridisation during the 1930s with bamboo, Sorghum etc. could not be substantiated.

Nobilisation of cane

Sugarcane (Saccharum spp.) is one of the crops for which interspecific hybridization has provided a major breakthrough in its improvement. Modern commercial sugarcane varieties (Saccharum hybrids, 2n=100-130) are derived from interspecific hybridization. Nobilisation refers to the crossing of the wild cane, S. spontaneum, to the noble cane S. officinarum, and further backcrossing of progenies to the latter, and includes the planned introgression of the other Saccharum species and related genera into the noble cane. Initial work on hybridisation and selection were restricted to intercrossing the S. officinarum clones (both typical and atypical) and limited success was obtained through intervarietal crosses, but improved vigour and resistance to many diseases became possible only after inter specific crosses were attempted. Kobus in 1897 crossed a S. barberi clone ‘Chunnee’ with S. officinarum and by backcrossing the progeny to the S. officinarum for dilution of the traits from the barberi clone obtained ‘sereh’ disease resistant varieties. This led to increased interest in interspecific hybrids were renewed.

In India, Barber in 1912 crossed ‘Vellai’ a S. officinarum clone with a S. spontaneum clone (2n = 64 ) found locally and obtained several promising clones starting with Co 205 which became the first interspecific hybrid to become a commercial success in India. Co 205 replaced the officinarum and the barberi varieties in cultivation in North India, on account of its hardiness and ability to withstand abiotic stresses better. In addition to introducing disease resistance in the noble background, nobilisation produced unexpected gains in general vigour, increased cane and sugar yields, adaptability to stress conditions and ratooning ability. The early success of interspecific hybridization led to the intercrossing of other species to produce tri­species hybrids that proved very successful in subtropical areas in India. Subsequently clones of S. barberi were nobilised to produce clones which were intercrossed to S. spontaneum clones. Some of these early trispecific hybrids became commercially successful in subtropics and in several other countries as well. Though earlier attempt for sugarcane breeding was to improve the yield, however, the quality of the cane was also given equal importance owing to industrial relevance of the cane produced.


Daniels, J. and Roach, T. (1987) Taxonomy and evolution. In: Sugarcane Improvement Through Breeding. Heinz, D.J. (ed.) Elsevier, Amsterdam, pp. 7-84.

Daniels, J., Smith, P., Paton, N. and Williams, C.A. (1975) The origin of the genus Saccharum. Sugarcane Breeders Newsletter 36, 24-39.

Mukherjee, S.K. (1957) Origin and distribution of Saccharum. Botanical Gazette 119, 55-61.