Integration of molecular and physiological models to explain time of anthesis in wheat

Background and Aims

A model to predict anthesis time of a wheat plant from environmental and genetic information requires integration of current concepts in physiological and molecular biology. This paper describes the structure of an integrated model and quantifies its response mechanisms.

Methods

Literature was reviewed to formulate the components of the model. Detailed re-analysis of physiological observations are utilized from a previous publication by the second two authors. In this approach measurements of leaf number and leaf and primordia appearance of near isogenic lines of spring and winter wheat grown for different durations in different temperature and photoperiod conditions are used to quantify mechanisms and parameters to predict time of anthesis.

Key Results

The model predicts the time of anthesis from the length of sequential phases: 1, embryo development; 2, dormant; 3, imbibed/emerging; 4, vegetative; 5, early reproductive; 6, pseudo-stem extension; and 7, ear development. Phase 4 ends with vernalization saturation (VS), Phase 5 with terminal spikelet (TS) and Phase 6 with flag leaf ligule appearance (FL). The durations of Phases 4 and 5 are linked to the expression of Vrn genes and are calculated in relation to change in Haun stage (HS) to account for the effects of temperature per se. Vrn1 must be expressed to sufficient levels for VS to occur. Vrn1 expression occurs at a base rate of 0·08/HS in winter ‘Batten’ and 0·17/HS in spring ‘Batten’ during Phases 1, 3 and 4. Low temperatures promote expression of Vrn1 and accelerate progress toward VS. Our hypothesis is that a repressor, Vrn4, must first be downregulated for this to occur. Rates of Vrn4 downregulation and Vrn1 upregulation have the same exponential response to temperature, but Vrn4 is quickly upregulated again at high temperatures, meaning short exposure to low temperature has no impact on the time of VS. VS occurs when Vrn1 reaches a relative expression of 0·76 and Vrn3 expression begins. However, Vrn2 represses Vrn3 expression so Vrn1 must be further upregulated to repress Vrn2 and enable Vrn3 expression. As a result, the target for Vrn1 to trigger VS was 0·76 in 8-h photoperiods (Pp) and increased at 0·026/HS under 16-h Pp as levels of Vrn2 increased. This provides a mechanism to model short-day vernalization. Vrn3 is expressed in Phase 5 (following VS), and apparent rates of Vrn3 expression increased from 0·15/HS at 8-h Pp to 0·33/HS at 16-h Pp. The final number of leaves is calculated as a function of the HS at which TS occurred (TS^HS): 2·86 + 1·1 × TS^HS. The duration of Phase 6 is then dependent on the number of leaves left to emerge and how quickly they emerge.

Conclusions

The analysis integrates molecular biology and crop physiology concepts into a model framework that links different developmental genes to quantitative predictions of wheat anthesis time in different field situations.     

Variation in breeding success among reintroduced island populations of South Island Saddlebacks Philesturnus carunculatus carunculatus

South Island Saddlebacks Philesturnus carunculatus carunculatus were once found throughout the South Island of New Zealand, but by the early 1960s were confined to the island of Big South Cape, in the extreme south of the country. All subsequent reintroduced populations of South Island Saddlebacks are derived from 36 surviving birds from this relict population. The aim of this study was to compare the breeding success of three recently reintroduced populations of Saddlebacks relative to their distance from, and habitat similarity to, the relict population. The three study islands show a latitudinal cline with Ulva, Breaksea and Motuara Islands located 60, 190 and 810 km north of Big South Cape, respectively. Saddlebacks on Ulva and Breaksea appeared to prefer to establish breeding territories in coastal scrub, the dominant habitat feature of Big South Cape. The area of coastal scrub habitat was much smaller on Motuara, where breeding territories were instead scattered through broadleaf forest habitat. Nesting success, calculated using Mayfield's method, was significantly greater on Ulva (73%) than on Breaksea (32%) or Motuara (19%) owing primarily to higher egg fertility and hatching success. Although egg failure rates were highest on Motuara, the island least similar to Big South Cape, they were also relatively high on Breaksea where the habitat was similar to Ulva and Big South Cape. Therefore, the results only partially support the hypothesis that nesting success should decrease with increasing habitat difference associated with increasing latitudinal distance from the source population. The data from this 1-year study lay the groundwork for examining further hypotheses on the effects of reintroducing endangered species outside their contemporary range, but within their historical range.     

Using co-occurrence network structure to extract synonymous gene and protein names from MEDLINE abstracts

Background  

Text-mining can assist biomedical researchers in reducing information overload by extracting useful knowledge from large collections of text. We developed a novel text-mining method based on analyzing the network structure created by symbol co-occurrences as a way to extend the capabilities of knowledge extraction. The method was applied to the task of automatic gene and protein name synonym extraction.