A sharp decline in the availability of arable land and sufficient supply of irrigation water along with a continuous steep increase in food demands have exerted a pressure on farmers to produce more with fewer resources. A viable solution to release this pressure is to speed up the plant breeding process by employing biotechnology in breeding programs. The majority of biotechnological applications rely on information generated from various -omic technologies. The latest outstanding improvements in proteomic platforms and many other but related advances in plant biotechnology techniques offer various new ways to encourage the usage of these technologies by plant scientists for crop improvement programs. A combinatorial approach of accelerated gene discovery through genomics, proteomics, and other associated -omic branches of biotechnology, as an applied approach, is proving to be an effective way to speed up the crop improvement programs worldwide. In the near future, swift improvements in -omic databases are becoming critical and demand immediate attention for the effective utilization of these techniques to produce next-generation crops for the progressive farmers. Here, we have reviewed the recent advances in proteomics, as tools of biotechnology, which are offering great promise and leading the path toward crop improvement for sustainable agriculture.
Both social environment and genetic factors are critical for smoking initiation and nicotine addiction. We reported that rats developed conditioned flavor (i.e., taste and odor) aversion to intravenously self-administered (IVSA) nicotine, and that social learning promoted nicotine IVSA with flavor cues. We thus tested the hypothesis that socially acquired nicotine IVSA is a heritable trait by using female rats of six inbred strains and six F1 hybrids. Each strain was tested for 10 daily IVSA sessions. We found that the intake of nicotine (15 and 30 μg/kg/inf) varied among these strains by 33.7-56.6-fold. The heritability of nicotine intake was estimated to be 0.54-0.65. Further, there was a strong correlation in nicotine intake (R(2) = 0.85, p < 0.0001) between the two nicotine doses. Another cohort of rats was given three daily IVSA sessions followed by five sessions that tested conditioned flavor aversion. Nicotine intake was highly correlated with the extinction of the conditioned aversion (R(2) = 0.58, p < 0.005). These data showed that nicotine intake in the socially acquired nicotine self-administration model is controlled by genetic factors and that the role of social learning is likely in facilitating the extinction of conditioned aversive response to nicotine.
Sustainable agriculture in response to increasing demands for food depends on development of high-yielding crops with high nutritional value that require minimal intervention during growth. To date, the focus has been on changing plants by introducing genes that impart new properties, which the plants and their ancestors never possessed. By contrast, we suggest another potentially beneficial and perhaps less controversial strategy that modern plant biotechnology may adopt. This approach, which broadens earlier approaches to reverse breeding, aims to furnish crops with lost properties that their ancestors once possessed in order to tolerate adverse environmental conditions. What molecular techniques are available for implementing such rewilding? Are the strategies legally, socially, economically, and ethically feasible? These are the questions addressed in this review.
Genomic evaluations often use as pseudo-phenotypes corrected means of progeny performances, like daughter yield deviations (DYD) in dairy species. In horse breeding, own performances are also available and performances from others relatives (as half sibs) may play an important part in the estimated breeding values (EBV) because the number of progeny remains low, even for stallions. The first step for genomic selection in horses is therefore to generate pseudo-phenotypes for genomic analysis when parental or own information is considered. This work presents an easy method to compute deregressed EBVs from regular pedigree-based genetic evaluations (EBVs, reliabilities) to be used in genomic evaluations. The proposed methodology builds deregressed proofs so that they combine own performances (from genotyped individuals) and performances of relatives (outside of the genotyped sample). An application to show jumping horse data is presented. A sample of 908 stallions specialized in show jumping (71% Selle français (SF), 17% Foreign sport horses (FH), 13% Anglo Arab(AA)) were genotyped. Genotyping was performed using the Illumina Equine SNP50 BeadChip and after quality tests, 44444 SNP were retained. Two methods were used for genomic evaluation: GBLUP and Bayes Cπ, and 6 validation data sets were compared, chosen according to breeds SF+FH+AA or SF+FH, family structure (more than 3 half sibs), reliability of sires (>0.97) or sons (>0.72). In spite of a favorable genetic structure (linkage disequilibrium equal to 0.24 at 50Kbp), results showed low advantage of genomic evaluation. On the validation sample SF+FH+AA, the correlation between deregressed proofs and GBLUP or BayesCπ predictions was: 0.39, 0.37, 0.51 according to the different validation data sets compared to 0.36, 0.33, 0.53 obtained with BLUP predictions. Correlations were much lower on the SF+FH sample. Research is pursued in order to understand this low advantage of genomic selection and to improve the methodology for genomic evaluation in this context, less favorable than dairy cattle breeding.
Gene-environment interactions have an important role in the development of psychiatric disorders. To generate and validate a new substrain of rats with signs related to schizophrenia, we used selective breeding after postweaning social isolation and chronic ketamine treatment through several generations of animals and compared the subsequent strain to naive rats that were not genetically manipulated. We further investigated whether social isolation and ketamine treatment augmented the appearance of schizophrenic-like signs in these rats. Four experimental groups were studied (n=6-15 rats/group): naive rats without any treatment (NaNo); naive rats with postweaning social isolation and ketamine treatment (NaTr); 15(th) generation of selectively bred animals without any treatment (SelNo) or selectively bred rats with both isolation and ketamine treatment (SelTr). The startle reaction, tail-flick and novel object recognition tests were used to classify the animals into low- or high-risk for schizophrenia. Reduced pain sensitivity, higher degree of the startle reaction, disturbed prepulse inhibition, altered motor activity and decreased differentiation index in the memory test were observed in the 15(th) generation of the substrain, along with enhanced grooming behavior. Five functional indices (TF latency, startle reaction, prepulse inhibition, differentiation index, and grooming activity) were rated from 0 - 2, and the analysis of the summarized score revealed that the NaNo group had the lowest overall indication of schizophrenic-like signs, while the SelTr animals scored the highest, suggesting that both heritable and environmental factors were important in the generation of the behavioral alterations. We assume that further breeding after this complex treatment may lead to a valid and reliable animal model of schizophrenia.
With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize recombinant inbred line population (n=167) across 16 developmental stages using the automatic phenotyping platform. QTL mapping with a high-density genetic linkage map, including 2496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits and 988 QTLs have been identified for all investigated traits, including 3 QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction.
Deleterious alleles have long been proposed to play an important role in patterning phenotypic variation and are central to commonly held ideas explaining the hybrid vigor observed in the offspring of a cross between two inbred parents. We test these ideas using evolutionary measures of sequence conservation to ask whether incorporating information about putatively deleterious alleles can inform genomic selection (GS) models and improve phenotypic prediction. We measured a number of agronomic traits in both the inbred parents and hybrids of an elite maize partial diallel population and re-sequenced the parents of the population. Inbred elite maize lines vary for more than 350,000 putatively deleterious sites, but show a lower burden of such sites than a comparable set of traditional landraces. Our modeling reveals widespread evidence for incomplete dominance at these loci, and supports theoretical models that more damaging variants are usually more recessive. We identify haplotype blocks using an identity-by-decent (IBD) analysis and perform genomic prediction analyses in which we weigh blocks on the basis of complementation for segregating putatively deleterious variants. Cross-validation results show that incorporating sequence conservation in genomic selection improves prediction accuracy for grain yield and other fitness-related traits as well as heterosis for those traits. Our results provide empirical support for an important role for incomplete dominance of deleterious alleles in explaining heterosis and demonstrate the utility of incorporating functional annotation in phenotypic prediction and plant breeding.
Domesticated apple (Malus × domestica Borkh) is a popular temperate fruit with high nutrient levels and diverse flavors. In 2012, global apple production accounted for at least one tenth of all harvested fruits. A high-quality apple genome assembly is crucial for the selection and breeding of new cultivars. Currently, a single reference genome is available for apple, assembled from 16.9 × genome coverage short reads via Sanger and 454 sequencing technologies. Although a useful resource, this assembly covers only ~89 % of the non-repetitive portion of the genome, and has a relatively short (16.7 kb) contig N50 length. These downsides make it difficult to apply this reference in transcriptive or whole-genome re-sequencing analyses.
Pedigree or purebred dogs are often stated to have high prevalence of disorders which are commonly assumed to be a consequence of inbreeding and selection for exaggerated features. However, few studies empirically report and rank the prevalence of disorders across breeds although such data are of critical importance in the prioritisation of multiple health concerns, and to provide a baseline against which to explore changes over time. This paper reports an owner survey that gathered disorder information on Kennel Club registered pedigree dogs, regardless of whether these disorders received veterinary care. This study aimed to determine the prevalence of disorders among pedigree dogs overall and, where possible, determine any variation among breeds.
Genetic diversity of cultivated wheat was markedly reduced, first, during domestication and, second, since the onset of modern elite breeding. There is an increasing demand for utilizing genetic resources to increase genetic diversity and, simultaneously, to improve agronomic performance of cultivated wheat. To locate favorable effects of exotic wheat alleles, we developed the tri-parental wheat population SW84. The population was derived from crossing the hexaploid spring wheat cultivars Triso and Devon with one synthetic exotic donor accession, Syn084L, followed by two rounds of backcrossing and three rounds of selfing. SW84 consists of 359 BC2F4 lines, split into two families, D84 (Devon*Syn084L) and T84 (Triso*Syn084L).