Phillip Jackson

The role of physiological understanding in plant breeding; from a breeding perspective

Abstract The role of physiological understanding in improving the efficiency of breeding programs is examined largely from the perspective of conventional breeding programs. Impact of physiological research to date on breeding programs, and the nature of that research, was assessed from (i) responses to a questionnaire distributed to plant breeders and physiologists, and (ii) a survey of literature abstracts. Ways to better utilise physiological understanding for improving breeding programs are suggested, together with possible constraints to delivering beneficial outcomes. Responses from the questionnaire indicated a general view that the contribution by crop physiology to date has been modest. However, most of those surveyed expected the contribution to be larger in the next 20 years. Some constraints to progress perceived by breeders and physiologists were highlighted. The survey of literature abstracts indicated that from a plant breeding perspective, much physiological research is not progressing further than making suggestions about possible approaches to selection. There was limited evidence in the literature of objective comparison of such suggestions with existing methodology, or of development and application of these within active breeding programs. It is argued in this paper that the development of outputs from physiological research for breeding requires a good understanding of the breeding program(s) being serviced and factors affecting its performance. Simple quantitative genetic models, or at least the ideas they represent, should be considered in conducting physiological research and in envisaging and evaluating outputs. The key steps of a generalised breeding program are outlined, and the potential pathways for physiological understanding to impact on these steps are discussed. Impact on breeding programs may arise through (i) better choice of environments in which to conduct selection trials, (ii) identification of selection criteria and traits for focused introgression programs, and (iii) identifying traits for indirect selection criteria as an adjunct to criteria already used. While many breeders and physiologists apparently recognise that physiological understanding may have a major role in the first area, there appears to be relatively little research activity targeting this issue, and a corresponding bias, arguably unjustified, toward examining traits for indirect selection. Furthermore, research on traits aimed at crop improvement is often deficient because key genetic parameters, such as genetic variation in relevant breeding populations and genetic (as opposed to phenotypic) correlations with yield or other characters of economic importance, are not properly considered in the research. Some areas requiring special attention for successfully interfacing physiology research with breeding are discussed. These include (i) the need to work with relevant genetic populations, (ii) close integration of the physiological research with an active breeding program, and (iii) the dangers of a pre-defined or narrow focus in the physiological research.

A combination of AFLP and SSR markers provides extensive map coverage and identification of homo(eo)logous linkage groups in a sugarcane cultivar

Sugarcane varieties are complex polyploids carrying in excess of 100 chromosomes and are derived from interspecific hybridisation between the domesticated Saccharum officinarum and the wild relative S. spontaneum. A map was constructed in , an Australian cultivar, from a segregating F1 population, using 40 amplified fragment length polymorphism (AFLP) primer combinations, five randomly amplified DNA fingerprints (RAF) primers and 72 simple sequence repeat (SSR) primers. Using these PCR-based marker systems, we generated 1,365 polymorphic markers, of which 967 (71%) were single-dose (SD) markers. Of these SD 967 markers, 910 were distributed on 116 linkage groups (LGs) with a total map length of 9,058.3 cM. Genome organisation was significantly greater than observed in previously reported maps for Saccharum spp. With the addition of 123 double-dose markers, 36 (3:1) segregating markers and a further five SD markers, 1,074 markers were mapped onto 136 LGs. Repulsion phase linkage detected preferential pairing for 40 LGs, which formed 11 LG pairs and three multi-chromosome pairing groups. Using SSRs, double-dose markers and repulsion phase linkage, we succeeded in forming 127 of the 136 LGs into eight homo(eo)logy groups (HG). Two HGs were each represented by two sets of LGs. These sets of LGs potentially correspond to S. officinarum chromosomes, with each set aligning to either end of one or two larger LGs. The larger chromosomes in the two HGs potentially correspond to S. spontaneum chromosomes. This suggestion is consistent with the different basic chromosome number of the two species that are hybridised to form sugarcane cultivars, S. spontaneum (x=8) and S. officinarum (x=10), and illustrates the structural relationship between the genomes of these two species. The discrepancy of coverage between HGs highlights the difficulty in mapping large parts of the genome.

Associations between DNA markers and resistance to diseases in sugarcane and effects of population substructure.

Association between markers and sugarcane diseases were investigated in a collection of 154 sugarcane clones, consisting of important ancestors or parents, and cultivars. 1,068 polymorphic AFLP and 141 SRR markers were scored across all clones. Data on the four most important diseases in the Australian sugarcane industry were obtained; these diseases being pachymetra root rot (Pachymetra chaunorhiza B.J. Croft & M.W. Dick), leaf scald (Xanthomonas albilineans Dowson), Fiji leaf gall (Fiji disease virus), and smut (Ustilago scitaminea H. & P. Sydow). By a simple regression analysis, association between markers and diseases could be readily detected. However, many of these associations were due to the effects of embedded population structure and random effects. After taking population structure into account, we found that 59% of the phenotypic variation in smut resistance ratings could be accounted for by 11 markers, 32% of variation for leaf scald and pachymetra root rot rating by 4 markers, and 26% of Fiji leaf gall by 5 markers. The results suggest that marker–trait associations can be readily detected in populations generated from modern sugarcane breeding programs. This may be due to special features of past sugarcane breeding programs leading to persistent linkage disequilibrium in modern parental populations.

Quantitative trait loci identified for sugar related traits in a sugarcane (Saccharum spp.) cultivar × Saccharum officinarum population

AbstractThe identification of markers linked to quantitative trait loci (QTLs) for increased sugar accumulation could improve the effectiveness of current breeding strategies in sugarcane. Progeny from a cross between a high sucrose producing cultivar, (denotes Australian plant breeding rights), and a Saccharum officinarum clone, IJ76-514 were grown in two field experiments in different years, and evaluated in the early and mid-season phases of crop maturity, to identify robust QTLs in affecting sucrose content in cane. Using an extensive genetic map constructed for with over 1,000 AFLP and SSR markers, a total of 37 QTLs were identified for brix and pol of which, 16 were detected in both experiments. Of these 37 QTL, 30 were clustered into 12 genomic regions in six of the eight homo(eo)logous groups. Each QTL explained from 3 to 9% of the phenotypic variation observed. Both positive and negative effects were identified and the location of the QTLs on linkage groups belonging to the same homo(eo)logy group suggested that a number of the QTLs were allelic forms of the same genes. Of the 37 QTLs identified, the majority were significant in both early and mature cane, but 8 were identified as early specific QTLs and 9 as mature cane QTLs. In total, 97 interactions were significant (P<10−5) and these were localised to 32 genomic regions of which 6 were detected with both years’ data. Models including all the QTLs explained from 37 to 66% of the total phenotypic variation, depending on the trait. The results will be subsequently applied in marker assisted breeding.

Diversity Arrays Technology effectively reveals DNA polymorphism in a large and complex genome of sugarcane

Diversity Arrays Technology (DArT) provides whole genome profiling for hundreds to thousands of polymorphic markers in a single assay using a high-throughput microarray platform. The presented work aimed to establish DArT genotyping for the genetically challenging genome of sugarcane. Due to the genome complexity of this sugar-producing crop of high economic importance, an application of DArT genotyping to this species required extensive testing and optimization. As the method of genome complexity reduction determines the efficiency of polymorphism identification in DArT, various approaches and several methods were tested, in order to establish the most optimal. The sugarcane DArT markers generated with these established methods identified high genetic differentiation of sugarcane ancestral species from modern cultivars, in agreement with the data available for other types of molecular markers for this crop. The majority of sugarcane DArT markers segregated in a Mendelian fashion and were readily incorporated into the framework genetic map. As the DArT markers are sequence-ready genomic clones, we sequenced 384 clones and found that one-third of sequenced markers came from the transcribed portion of the sugarcane genome. The presented results further validate the potential of DArT technology in providing cost-effective genetic profiles for plants, irrespective of their genome complexity, for effective applications in molecular-assisted breeding, diversity analysis or genetic identity testing.

Construction of a genetic linkage map for Saccharum officinarum incorporating both simplex and duplex markers to increase genome coverage

Saccharum officinarum L. is an octoploid with 80 chromosomes and a basic chromosome number of x = 10. It has high stem sucrose and contributes 80% of the chromosomes to the interspecific sugarcane cultivars that are grown commercially for sucrose. A genetic linkage map was developed for S. officinarum (clone IJ76-514) using a segregating population generated from a cross between Q165 (a commercial sugarcane cultivar) and IJ76-514. In total, 40 AFLP and 72 SSR primer pairs were screened across the population, revealing 595 polymorphic bands inherited from IJ76-514. These 595 markers displayed a frequency distribution different from all other sugarcane genetic maps produced, with only 40% being simplex markers (segregated 1:1). Of these 240 simplex markers, 178 were distributed on 47 linkage groups (LGs) and 62 remained unlinked. With the addition of 234 duplex markers and 80 biparental simplex markers (segregating 3:1), 534 markers formed 123 LGs. Using the multi-allelic SSR markers, repulsion phase linkage, and alignment with the Q165 linkage map, 105 of the 123 LGs could be grouped into 10 homology groups (HGs). These 10 HGs were further assigned to the 8 HGs observed in cultivated sugarcane and S. spontaneum. Analysis of repulsion phase linkage indicated that IJ76-514 is neither a complete autopolyploid nor an allopolyploid. Detection of 28 repulsion linkages that occurred between 6 pairs of LGs located in 4 HGs suggested the occurrence of limited preferential chromosome pairing in this species.

Effects of tissue culture, biolistic transformation, and introduction of PPO and SPS gene constructs on performance of sugarcane clones in the field

Stably transformed sugarcane plants were produced by the biolistic introduction of DNA into tissue-cultured cells. Constructs containing genes in sense and antisense orientation of polyphenol oxidase and sense orientation of sucrose phosphate synthase were used in the transformations. Regenerated plants were grown in a series of field experiments that incorporated commercial varieties, including Q117, from which the transgenic clones were derived and plants regenerated from tissue culture but not subjected to biolistic bombardment. In all experiments, the mean yield of transgenic sugarcane was lower than commercial varieties and the transgenic clones often exhibited lower sugar content, although individual transgenic clones in some experiments were not significantly different from Q117. Those plants regenerated from tissue culture but not bombarded were intermediate in their yield, and more clones were equivalent to Q117 in agronomic performance. Transformed plants produced by the bombardment of callus performed poorly but the results from the tissue-cultured controls indicated that not all of this could be due to somaclonal variation. Some aspect(s) of the process of transformation itself was deleterious and in most cases more significant than the effects due to tissue culture. Of the transgenic clones grown at Ayr, Queensland, 1.6% were equivalent to Q117 in sugar content and yield, suggesting that large numbers of transgenic clones would have to be generated using the current method in order to allow for selection of clones with acceptable agronomic performance.

Comparative genetics in sugarcane enables structured map enhancement and validation of marker-trait associations

As sugarcane is a complex polyaneuploid with many chromosomes, large numbers of markers are required to generate genetic maps with reasonable levels of genome coverage. Comparative mapping was investigated as an approach for both quantitative trait loci (QTL) validation and genetic map enhancement in sugarcane. More than 1000 SSR and AFLP markers were scored in a bi-parental Australian sugarcane population (Q3) that was segregating widely for sugar content-related traits. Two maps were constructed, one for each parent. The Q117 (female) and MQ77-340 (male) maps each contained almost 400 markers distributed onto approximately 100 linkage groups (LGs), of which nearly half could be assigned to homology groups (HGs) on the basis of SSRs. Then, using common SSR and AFLP markers, the two Q3 parental maps were aligned with the maps of the French cultivar, R570, and of the Australian cultivar, Q165A (A denotes variety covered by Australian plant breeding rights). As a result of comparative mapping, all ten HGs in the Q117 map, and all eleven HGs in the MQ77-340 map could be re-assigned to seven of the expected eight sugarcane HGs, revealing that one sugarcane HG was not covered at all in either Q3 parental map, and that other HGs were poorly represented. QTL analysis in the Q3 population identified approximately 75 marker-trait associations (MTAs) from approximately 18 chromosomal regions or putative QTL in each map for three sugar content-related traits. QTL location appeared to be consistent between the 4 maps; two of the eight HGs were observed to contain MTAs for brix in two or three maps, strongly suggesting the location of sugar content-related trait loci in these HGs.

Sugarcane for water-limited environments. Genetic variation in cane yield and sugar content in response to water stress

Water limitation is a major production constraint for sugarcane worldwide. However, to date, there has been little investigation of patterns of genetic variation in the response to water stress in sugarcane. Field experiments were conducted over 3 years under fully irrigated and managed water stress conditions at two locations in Northern Queensland in Australia. Eighty-nine genetically diverse clones were evaluated for their yield performance and sugar attributes. Water stress treatments reduced cane yield [tonnes of cane per hectare (TCH)] and total dry matter (TDM) by 17-52% and 20-56%, respectively, compared with irrigated treatments in the same experiments. Nevertheless, there was little genotype×environment interaction variation for TCH, TDM, or commercial cane sugar (CCS), and hence high genetic correlations between the irrigated and water stress treatments across environments. Both commercial and unselected clones performed poorly under severe stress environments, while the commercial clones outperformed the unselected clones under mild and moderate stress conditions. The results presented here highlight the contribution of intrinsic potential yields (yield under well-irrigated conditions) of some selected and unselected clones to maintain relatively high productivity in a range of moderate stress conditions imposed. The physiological basis for the high genetic correlations is at present unclear, but some explanations are hypothesized. The choice of stress levels in selection trials would not appear to be a critical issue for sugarcane breeding programmes, at least for the early phases of selection, where similar ranking clones across a range of moderate water stresses may be expected.

Simultaneously accounting for population structure, genotype by environment interaction, and spatial variation in marker–trait associations in sugarcaneThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

Few association mapping studies have simultaneously accounted for population structure, genotype by environment interaction (GEI), and spatial variation. In this sugarcane association mapping study we tested models accounting for these factors and identified the impact that each model component had on the list of markers declared as being significantly associated with traits. About 480 genotypes were evaluated for cane yield and sugar content at three sites and scored with DArT markers. A mixed model was applied in analysis of the data to simultaneously account for the impacts of population structure, GEI, and spatial variation within a trial. Two forms of the DArT marker data were used in the analysis: the standard discrete data (0, 1) and a continuous DArT score, which is related to the marker dosage. A large number of markers were significantly associated with cane yield and sugar content. However, failure to account for population structure, GEI, and (or) spatial variation produced both type I and type II errors, which on the one hand substantially inflated the number of significant markers identified (especially true for failing to account for GEI) and on the other hand resulted in failure to detect markers that could be associated with cane yield or sugar content (especially when failing to account for population structure). We concluded that association mapping based on trials from one site or analysis that failed to account for GEI would produce many trial-specific associated markers that would have low value in breeding programs.