27 resultados para Genetic Analyses

em eResearch Archive - Queensland Department of Agriculture


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The introgression of domestic dog genes into dingo populations threatens the genetic integrity of 'pure' dingoes. However, dingo conservation efforts are hampered by difficulties in distinguishing between dingoes and hybrids in the field. This study evaluates consistency in the status of hybridisation (i.e. dingo, hybrid or dog) assigned by genetic analyses, skull morphology and visual assessments. Of the 56 south-east Queensland animals sampled, 39 (69.6%) were assigned the same status by all three methods, 10 (17.9%) by genetic and skull methods, four (7.1%) by genetic and visual methods; and two (3.6%) by skull and visual methods. Pair-wise comparisons identified a significant relationship between genetic and skull methods, but not between either of these and visual methods. Results from surveying 13 experienced wild dog managers showed that hybrids were more easily identified by visual characters than were dingoes. A more reliable visual assessment can be developed through determining the relationship between (1) genetics and phenotype by sampling wild dog populations and (2) the expression of visual characteristics from different proportions and breeds of domestic dog genes by breeding trials. Culling obvious hybrids based on visual characteristics, such as sable and patchy coat colours, should slow the process of hybridisation.

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Coastal seagrass habitats in tropical and subtropical regions support aggregations of resident green turtles (Chelonia mydas) from several genetically distinct breeding populations. Migration of individuals to their respective dispersed breeding sites provides a complex pattern of migratory connectivity among nesting and feeding habitats of this species. An understanding of this pattern is important in regions where the persistence of populations is under threat from anthropogenic impacts. The present study uses mitochondrial DNA and mixed-stock analyses to assess the connectivity among seven feeding grounds across the north Australian coast and adjacent areas and 17 genetically distinct breeding populations from the Indo-Pacific region. It was hypothesised that large and geographically proximate breeding populations would dominate at nearby feeding grounds. As expected, each sampled feeding area appears to support multiple breeding populations, with two aggregations dominated by a local breeding population. Geographic distance between breeding and feeding habitat strongly influenced whether a breeding population contributed to a feeding ground (wi = 0.654); however, neither distance nor size of a breeding population was a good predictor of the extent of their contribution. The differential proportional contributions suggest the impact of anthropogenic mortality at feeding grounds should be assessed on a case-by-case basis.

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The common blacktip shark (Carcharhinus limbatus) and the Australian blacktip shark (C. tilstoni) are morphologically similar species that co-occur in subtropical and tropical Australia. In striking contrast to what has been previously reported, we demonstrate that the common blacktip shark is not rare in northern Australia but occurs in approximately equal frequencies with the Australian blacktip shark. Management of shark resources in northern Australia needs to take account of this new information. Species identification was performed using nucleotide sequences of the control, NADH dehydrogenase subunit 4 (ND4) and cytochrome oxidase I (COI) regions in the mitochondrial genome. The proportion of overall genetic variation (FST) between the two species was small (0.042, P < 0.01) based on allele frequencies at five microsatellite loci. We confirm that a third blacktip species (C. amblyrhynchoides, graceful shark) is closely related to C. tilstoni and C. limbatus and can be distinguished from them on the basis of mtDNA sequences from two gene regions. The Australian blacktip shark (C. tilstoni) was not encountered among 20 samples from central Indonesia that were later confirmed to be common blacktip and graceful sharks. Fisheries regulators urgently need new information on life history, population structure and morphological characters for species identification of blacktip shark species in Australia.

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Twelve microsatellite DNA markers were isolated in the spot-tail shark (Carcharhinus sorrah) and nine were isolated in Australian black-tip shark (Carcharhinus tilstoni). These loci plus 18 others developed for sharks from the genera Negaprion, Ginglymostoma, Carcharodon and Isurus were tested for amplification success on four species of Carcharhinus (including C. sorrah and C. tilstoni) and four other species representing three diverse families. Cross-amplification was most common within families. Five loci were subsequently tested for polymorphism on 50 C. sorrah and 60 C. tilstoni. The number of alleles per locus was two to 24 and the average heterozygosity was 0.54 (range 0.16-0.87) for C. sorrah and 0.64 (range 0.44-0.78) for C. tilstoni. These loci may be useful tools for genetic analyses of the Carcharhinidae.

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A total of 2115 heifers from two tropical genotypes (1007 Brahman and 1108 Tropical Composite) raised in four locations in northern Australia were ovarian-scanned every 4-6 weeks to determine the age at the first-observed corpus luteum (CL) and this was used to de. ne the age at puberty for each heifer. Other traits recorded at each time of ovarian scanning were liveweight, fat depths and body condition score. Reproductive tract size was measured close to the start of the first joining period. Results showed significant effects of location and birth month on the age at first CL and associated puberty traits. Genotypes did not differ significantly for the age or weight at first CL; however, Brahman were fatter at first CL and had a small reproductive tract size compared with that of Tropical Composite. Genetic analyses estimated the age at first CL to be moderately to highly heritable for Brahman (0.57) and Tropical Composite (0.52). The associated traits were also moderately heritable, except for reproductive tract size in Brahmans (0.03) and for Tropical Composite, the presence of an observed CL on the scanning day closest to the start of joining (0.07). Genetic correlations among puberty traits were mostly moderate to high and generally larger in magnitude for Brahman than for Tropical Composite. Genetic correlations between the age at CL and heifer- and steer-production traits showed important genotype differences. For Tropical Composite, the age at CL was negatively correlated with the heifer growth rate in their first postweaning wet season (-0.40) and carcass marbling score (-0.49), but was positively correlated with carcass P8 fat depth (0.43). For Brahman, the age at CL was moderately negatively genetically correlated with heifer measures of bodyweight, fatness, body condition score and IGF-I, in both their first postweaning wet and second dry seasons, but was positively correlated with the dry-season growth rate. For Brahman, genetic correlations between the age at CL and steer traits showed possible antagonisms with feedlot residual feed intake (-0.60) and meat colour (0.73). Selection can be used to change the heifer age at puberty in both genotypes, with few major antagonisms with steer- and heifer- production traits.

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The white-spotted eagle ray Aetobatus narinari is a species complex that occurs circumglobally throughout warm-temperate waters. Aetobatus narinari is semi-pelagic and large (up to 300 cm disc width), suggesting high dispersal capabilities and gene flow on a wide spatial scale. Sequence data from two mitochondrial genes, cytochrome b (cytb) and NADH dehydrogenase subunit 4 (ND4), were used to determine the genetic variability within and among 18 sampling locations in the central Indo-Pacific biogeographical region. Populations in the Indo-Pacific were highly genetically structured with c. 70% of the total genetic variation found among three geographical regions (East China Sea, Southeast Asia and Australia). FST was 0.64 for cytb and 0.53 for ND4, with φST values being even larger, that is, 0.78 for cytb and 0.65 for ND4. This high-level genetic partitioning provides strong evidence against extensive gene flow in A. narinari. The degree of genetic population structuring in the Indo-Pacific was similar to that found on a global scale. Global FST was 0.63 for cytb and 0.57 for ND4, and global φST values were 0.94 for cytb and 0.82 for ND4. This suggests that the A. narinari complex may be more speciose than the two or three species proposed to date. Further sampling and genetic analyses are likely to uncover the ‘evolutionarily significant’ and ‘management’ units that are critical to determine the susceptibilities of individual populations to regional fishing pressures and to provide advice on management options. Network analyses showed a close genetic relationship between haplotypes from the central Indo-Pacific and South Africa, providing support for a proposed dispersal pathway from the possible centre of origin of the A. narinari species complex in the Indo-Pacific into the Atlantic Ocean.

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The requirement for Queensland, Northern Territory and Western Australian jurisdictions to ensure sustainable harvest of fish resources and their optimal use relies on robust information on the resource status. For grey mackerel (Scomberomorus semifasciatus) fisheries, each of these jurisdictions has their own management regime in their corresponding waters. The lack of information on stock structure of grey mackerel, however, means that the appropriate spatial scale of management is not known. As well, fishers require assurance of future sustainability to encourage investment and long-term involvement in a fishery that supplies lucrative overseas markets. These management and fisher-unfriendly circumstances must be viewed in the context of recent 3-fold increases in catches of grey mackerel along the Queensland east coast, combined with significant and increasing catches in other parts of the species' northern Australian range. Establishing the stock structure of grey mackerel would also immensely improve the relevance of resource assessments for fishery management of grey mackerel across northern Australia. This highlighted the urgent need for stock structure information for this species. The impetus for this project came from the strategic recommendations of the FRDC review by Ward and Rogers (2003), "Northern mackerel (Scombridae: Scomberomorus): current and future research needs" (Project No. 2002/096), which promoted the urgency for information on the stock structure of grey mackerel. In following these recommendations this project adopted a multi-technique and phased sampling approach as carried out by Buckworth et al (2007), who examined the stock structure of Spanish mackerel, Scomberomorus commerson, across northern Australia. The project objectives were to determine the stock structure of grey mackerel across their northern Australian range, and use this information to define management units and their appropriate spatial scales. We used multiple techniques concurrently to determine the stock structure of grey mackerel. These techniques were: genetic analyses (mitochondrial DNA and microsatellite DNA), otolith (ear bones) isotope ratios, parasite abundances, and growth parameters. The advantage of using this type of multi-technique approach was that each of the different methods is informative about the fish’s life history at different spatial and temporal scales. Genetics can inform about the evolutionary patterns as well as rates of mixing of fish from adjacent areas, while parasites and otolith microchemistry are directly influenced by the environment and so will inform about the patterns of movement during the fishes lifetime. Growth patterns are influenced by both genetic and environmental factors. Due to these differences the use of these techniques concurrently increases the likelihood of detecting different stocks where they exist. We adopted a phased sampling approach whereby sampling was carried out at broad spatial scales in the first year: east coast, eastern Gulf of Carpentaria (GoC), western GoC, and the NW Northern Territory (NW NT). By comparing the fish samples from each of these locations, and using each of the techniques, we tested the null hypothesis that grey mackerel were comprised of a single homogeneous population across northern Australia. Having rejected the null hypothesis we re-sampled the 1st year locations to test for temporal stability in stock structure, and to assess stock structure at finer spatial scales. This included increased spatial coverage on the east coast, the GoC, and WA. From genetic approaches we determined that there at least four genetic stocks of grey mackerel across northern Australia: WA, NW NT (Timor/Arafura), the GoC and the east Grey mackerel management units in northern Australia ix coast. All markers revealed concordant patterns showing WA and NW NT to be clearly divergent stocks. The mtDNA D-loop fragment appeared to have more power to resolve stock boundaries because it was able to show that the GoC and east coast QLD stocks were genetically differentiated. Patterns of stock structure on a finer scale, or where stock boundaries are located, were less clear. From otolith stable isotope analyses four major groups of S. semifasciatus were identified: WA, NT/GoC, northern east coast and central east coast. Differences in the isotopic composition of whole otoliths indicate that these groups must have spent their life history in different locations. The magnitude of the difference between the groups suggests a prolonged separation period at least equal to the fish’s life span. The parasite abundance analyses, although did not include samples from WA, suggest the existence of at least four stocks of grey mackerel in northern Australia: NW NT, the GoC, northern east coast and central east coast. Grey mackerel parasite fauna on the east coast suggests a separation somewhere between Townsville and Mackay. The NW NT region also appears to comprise a separate stock while within the GoC there exists a high degree of variability in parasite faunas among the regions sampled. This may be due to 1. natural variation within the GoC and there is one grey mackerel stock, or 2. the existence of multiple localised adult sub-stocks (metapopulations) within the GoC. Growth parameter comparisons were only possible from four major locations and identified the NW NT, the GoC, and the east coast as having different population growth characteristics. Through the use of multiple techniques, and by integrating the results from each, we were able to determine that there exist at least five stocks of grey mackerel across northern Australia, with some likelihood of additional stock structuring within the GoC. The major management units determined from this study therefore were Western Australia, NW Northern Territory (Timor/Arafura), the Gulf of Carpentaria, northern east Queensland coast and central east Queensland coast. The management implications of these results indicate the possible need for management of grey mackerel fisheries in Australia to be carried out on regional scales finer than are currently in place. In some regions the spatial scales of management might continue as is currently (e.g. WA), while in other regions, such as the GoC and the east coast, managers should at least monitor fisheries on a more local scale dictated by fishing effort and assess accordingly. Stock assessments should also consider the stock divisions identified, particularly on the east coast and for the GoC, and use life history parameters particular to each stock. We also emphasise that where we have not identified different stocks does not preclude the possibility of the occurrence of further stock division. Further, this study did not, nor did it set out to, assess the status of each of the stocks identified. This we identify as a high priority action for research and development of grey mackerel fisheries, as well as a management strategy evaluation that incorporates the conclusions of this work. Until such time that these priorities are addressed, management of grey mackerel fisheries should be cognisant of these uncertainties, particularly for the GoC and the Queensland east coast.

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Turnip mosaic virus (TuMV) is a potyvirus that is transmitted by aphids and infects a wide range of plant species. We investigated the evolution of this pathogen by collecting 32 isolates of TuMV, mostly from Brassicaceae plants, in Australia and New Zealand. We performed a variety of sequence-based phylogenetic and population genetic analyses of the complete genomic sequences and of three non-recombinogenic regions of those sequences. The substitution rates, divergence times and phylogeographical patterns of the virus populations were estimated. Six inter- and seven intralineage recombination-type patterns were found in the genomes of the Australian and New Zealand isolates, and all were novel. Only one recombination-type pattern has been found in both countries. The Australian and New Zealand populations were genetically different, and were different from the European and Asian populations. Our Bayesian coalescent analyses, based on a combination of novel and published sequence data from three nonrecombinogenic protein-encoding regions, showed that TuMV probably started to migrate from Europe to Australia and New Zealand more than 80 years ago, and that distinct populations arose as a result of evolutionary drivers such as recombination. The basal-B2 subpopulation in Australia and New Zealand seems to be older than those of the world-B2 and -B3 populations. To our knowledge, our study presents the first population genetic analysis of TuMV in Australia and New Zealand. We have shown that the time of migration of TuMV correlates well with the establishment of agriculture and migration of Europeans to these countries.

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Analyses of variance and co variance were carried out on the activities of three lysosomal enzymes in mononuclear blood cells from Brahman cattle. These were hexosaminidase (HEX), beta-D-galacto-sidase (GAL) and acid alpha-glucosidase (GLU) which had been measured in blood mononuclear cells from 1752 cattle from 6 herds in a Pompe's disease control programme. Herd of origin and date of bleeding significantly affected the level of activity of all enzymes. In addition, HEX and GAL were affected by age and HEX by the sex of the animal bled. Estimates of heritability from sire variances were 0.29:t 0.09 for HEX, 0.31 :t 0.09 for GAL and 0.44:t 0.09 for GLU. Genetic correlations between all enzymes were positive. The data indicate the existence of a major gene causing Pompe's disease and responsible for 16% of the genetic variation in GLU. One standard deviation of selection differential for high GLU should almost eliminate Pompe's disease from the population. The effi-ciency of selection would be aided by estimating the breeding value for GLU using measurements of HEX and GLU and taking account of an animal's sex, age, date of bleeding and herd of origin.

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Pineapple mealybug wilt-associated virus 1 (PMWaV-1), 2 (PMWaV-2) and -3 (PMWaV-3) have been detected in Australian commercial pineapple crops, along with a previously undescribed ampelovirus, for which the name Pineapple mealybug wilt-associated virus 5 (PMWaV-5) is proposed. Partial sequences extending from open reading frame 1b through to the heat shock protein homologue were obtained for PMWaV-1, -3 and -5. Phylogenetic analyses of selected regions of these sequences indicated that PMWaV-5 is a distinct species and most closely related to PMWaV-1. The amino acid sequence variation observed in the RNA-dependent RNA polymerase region of PMWaV-1 isolates was 95.8–98.4% and of PMWaV-3 isolates was 92.2–99.5%. In surveys of mealybug wilt disease (MWD) affected crops, none of the four viruses was clearly associated with the disease at all survey sites. A statistically significant association (P < 0.001) between the presence of PMWaV-2 and symptoms was observed at one survey site (site 3), but the virus was at a low incidence at the remaining three survey sites. By contrast, although PMWaV-1 and -3 were equally distributed between symptomless and MWD-affected plants at site 3, there was a statistically significant (P < 0.001) association between each of these two viruses and MWD at sites 1 and 4. At site 2, there was a statistically significant (P < 0.001) association only between PMWaV-3 and MWD. PMWaV-1 was the most commonly found of the four viruses and conversely PMWaV-5 was only occasionally found. Australian isolates of PMWaV-1, -2 and -3 were transmitted by the mealybug species Dysmicoccus brevipes.

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This study compares estimates of the census size of the spawning population with genetic estimates of effective current and long-term population size for an abundant and commercially important marine invertebrate, the brown tiger prawn (Penaeus esculentus). Our aim was to focus on the relationship between genetic effective and census size that may provide a source of information for viability analyses of naturally occurring populations. Samples were taken in 2001, 2002 and 2003 from a population on the east coast of Australia and temporal allelic variation was measured at eight polymorphic microsatellite loci. Moments-based and maximum-likelihood estimates of current genetic effective population size ranged from 797 to 1304. The mean long-term genetic effective population size was 9968. Although small for a large population, the effective population size estimates were above the threshold where genetic diversity is lost at neutral alleles through drift or inbreeding. Simulation studies correctly predicted that under these experimental conditions the genetic estimates would have non-infinite upper confidence limits and revealed they might be overestimates of the true size. We also show that estimates of mortality and variance in family size may be derived from data on average fecundity, current genetic effective and census spawning population size, assuming effective population size is equivalent to the number of breeders. This work confirms that it is feasible to obtain accurate estimates of current genetic effective population size for abundant Type III species using existing genetic marker technology.

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Ecological and genetic studies of marine turtles generally support the hypothesis of natal homing, but leave open the question of the geographical scale of genetic exchange and the capacity of turtles to shift breeding sites. Here we combine analyses of mitochondrial DNA (mtDNA) variation and recapture data to assess the geographical scale of individual breeding populations and the distribution of such populations through Australasia. We conducted multiscale assessments of mtDNA variation among 714 samples from 27 green turtle rookeries and of adult female dispersal among nesting sites in eastern Australia. Many of these rookeries are on shelves that were flooded by rising sea levels less than 10 000 years (c. 450 generations) ago. Analyses of sequence variation among the mtDNA control region revealed 25 haplotypes, and their frequency distributions indicated 17 genetically distinct breeding stocks (Management Units) consisting either of individual rookeries or groups of rookeries in general that are separated by more than 500 km. The population structure inferred from mtDNA was consistent with the scale of movements observed in long-term mark-recapture studies of east Australian rookeries. Phylogenetic analysis of the haplotypes revealed five clades with significant partitioning of sequence diversity (Φ = 68.4) between Pacific Ocean and Southeast Asian/Indian Ocean rookeries. Isolation by distance was indicated for rookeries separated by up to 2000 km but explained only 12% of the genetic structure. The emerging general picture is one of dynamic population structure influenced by the capacity of females to relocate among proximal breeding sites, although this may be conditional on large population sizes as existed historically across this region.

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The genetic population structure of red snapper Lutjanus malabaricus and Lutjanus erythropterus in eastern Indonesia and northern Australia was investigated by allozyme electrophoresis and sequence variation in the control region of mtDNA. Samples were collected from eight sites in Indonesia and four sites in northern Australia for both species. A total of 13 allozyme loci were scored. More variable loci were observed in L. malabaricus than in L. erythropterus. Sequence variation in the control region (left domain) of the mitochondrial genome was assessed by RFLP and direct sequencing. MtDNA haplotype diversity was high (L. erythropterus, 0.95 and L. malabaricus, 0.97), as was intraspecific sequence divergence, (L. erythropterus, 0.0-12.5% and L. malabaricus, 0.0-9.5%). The pattern of mtDNA haplotype frequencies grouped both species into two broad fisheries stocks with a genetic boundary either between Kupang and Sape (L. malabaricus) or between Kupang and Australian Timor Sea (L. erythropertus). The allozyme analyses revealed similar boundaries for L. erythropterus. Seven allozymes stocks compared to two mtDNA stocks of L. malabaricus including Ambon, which was not sampled with mtDNA, however, were reported. Possible reasons for differences in discrimination between the methods include: i) increased power of multiple allozyme loci over the single mtDNA locus, ii) insufficient gene sampling in the mtDNA control region and iii) relative evolutionary dynamics of nuclear (allozyme loci) and mitochondrial DNA in these taxa. Allozyme and haplotype data did not distinguish separate stocks among the four Australian locations nor the central Indonesian (Bali and Sape locations) for both L. malabaricus and L. erythropterus.

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The sequential nature of gel-based marker systems entails low throughput and high costs per assay. Commonly used marker systems such as SSR and SNP are also dependent on sequence information. These limitations result in high cost per data point and significantly limit the capacity of breeding programs to obtain sufficient return on investment to justify the routine use of marker-assisted breeding for many traits and particularly quantitative traits. Diversity Arrays Technology (DArT™) is a cost effective hybridisation-based marker technology that offers a high multiplexing level while being independent of sequence information. This technology offers sorghum breeding programs an alternative approach to whole-genome profiling. We report on the development, application, mapping and utility of DArT™ markers for sorghum germplasm. Results: A genotyping array was developed representing approximately 12,000 genomic clones using PstI+BanII complexity with a subset of clones obtained through the suppression subtractive hybridisation (SSH) method. The genotyping array was used to analyse a diverse set of sorghum genotypes and screening a Recombinant Inbred Lines (RIL) mapping population. Over 500 markers detected variation among 90 accessions used in a diversity analysis. Cluster analysis discriminated well between all 90 genotypes. To confirm that the sorghum DArT markers behave in a Mendelian manner, we constructed a genetic linkage map for a cross between R931945-2-2 and IS 8525 integrating DArT and other marker types. In total, 596 markers could be placed on the integrated linkage map, which spanned 1431.6 cM. The genetic linkage map had an average marker density of 1/2.39 cM, with an average DArT marker density of 1/3.9 cM. Conclusion: We have successfully developed DArT markers for Sorghum bicolor and have demonstrated that DArT provides high quality markers that can be used for diversity analyses and to construct medium-density genetic linkage maps. The high number of DArT markers generated in a single assay not only provides a precise estimate of genetic relationships among genotypes, but also their even distribution over the genome offers real advantages for a range of molecular breeding and genomics applications.

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The objective of this study was to examine genetic changes in reproduction traits in sows (total number born (TNB), number born alive (NBA), average piglet birth weight (ABW) and number of piglets weaned (NW), body weight prior to mating (MW), gestation length (GL) and daily food intake during lactation (DFI)) in lines of Large White pigs divergently selected over 4 years for high and low post-weaning growth rate on a restricted ration. Heritabilities and repeatabilities of the reproduction traits were also determined. The analyses were carried out on 913 litter records using average information-restricted maximum likelihood method applied to single trait animal models. Estimates of heritability for most traits were small, except for ABW (0·33) and MW (0·35). Estimates of repeatability were slightly higher than those of heritability for TNB, NBA and NW, but they were almost identical for ABW, MW, GL and DFI. After 4 years of selection, the high growth line sows had significantly heavier body weight prior to mating and produced significantly more piglets born alive with heavier average birth weight than the low line sows. There were, however, no statistical differences between the selected lines in TNB or NW. The lower food intake of high relative to low line sows during lactation was not significant, indicating that daily food intake differences found between grower pigs in the high and low lines (2·71 v. 2·76 kg/day, s.e.d. 0·024) on ad libitum feeding were not fully expressed in lactating sows. It is concluded that selection for growth rate on the restricted ration resulted in beneficial effects on important measures of reproductive performance of the sows.