Beyond missing heritability: prediction of complex traits

Despite rapid advances in genomic technology, our ability to account for phenotypic variation using genetic information remains limited for many traits. This has unfortunately resulted in limited application of genetic data towards preventive and personalized medicine, one of the primary impetuses of genome-wide association studies. Recently, a large proportion of the "missing heritability" for human height was statistically explained by modeling thousands of single nucleotide polymorphisms concurrently. However, it is currently unclear how gains in explained genetic variance will translate to the prediction of yet-to-be observed phenotypes. Using data from the Framingham Heart Study, we explore the genomic prediction of human height in training and validation samples while varying the statistical approach used, the number of SNPs included in the model, the validation scheme, and the number of subjects used to train the model. In our training datasets, we are able to explain a large proportion of the variation in height (h(2) up to 0.83, R(2) up to 0.96). However, the proportion of variance accounted for in validation samples is much smaller (ranging from 0.15 to 0.36 depending on the degree of familial information used in the training dataset). While such R(2) values vastly exceed what has been previously reported using a reduced number of pre-selected markers (<0.10), given the heritability of the trait (～ 0.80), substantial room for improvement remains.     

Non-linear models based on simple topological indices to identify RNase III protein members

Alignment-free classifiers are especially useful in the functional classification of protein classes with variable homology and different domain structures. Thus, the Topological Indices to BioPolymers (TI2BioP) methodology (Agüero-Chapin et al., 2010) inspired in both the TOPS-MODE and the MARCH-INSIDE methodologies allows the calculation of simple topological indices (TIs) as alignment-free classifiers. These indices were derived from the clustering of the amino acids into four classes of hydrophobicity and polarity revealing higher sequence-order information beyond the amino acid composition level. The predictability power of such TIs was evaluated for the first time on the RNase III family, due to the high diversity of its members (primary sequence and domain organization). Three non-linear models were developed for RNase III class prediction: Decision Tree Model (DTM), Artificial Neural Networks (ANN)-model and Hidden Markov Model (HMM). The first two are alignment-free approaches, using TIs as input predictors. Their performances were compared with a non-classical HMM, modified according to our amino acid clustering strategy. The alignment-free models showed similar performances on the training and the test sets reaching values above 90% in the overall classification. The non-classical HMM showed the highest rate in the classification with values above 95% in training and 100% in test. Although the higher accuracy of the HMM, the DTM showed simplicity for the RNase III classification with low computational cost. Such simplicity was evaluated in respect to HMM and ANN models for the functional annotation of a new bacterial RNase III class member, isolated and annotated by our group.     

QTL Mapping of Agronomic Waterlogging Tolerance Using Recombinant Inbred Lines Derived from Tropical Maize (Zea mays L) Germplasm

Waterlogging is an important abiotic stress constraint that causes significant yield losses in maize grown throughout south and south-east Asia due to erratic rainfall patterns. The most economic option to offset the damage caused by waterlogging is to genetically incorporate tolerance in cultivars that are grown widely in the target agro-ecologies. We assessed the genetic variation in a population of recombinant inbred lines (RILs) derived from crossing a waterlogging tolerant line (CAWL-46-3-1) to an elite but sensitive line (CML311-2-1-3) and observed significant range of variation for grain yield (GY) under waterlogging stress along with a number of other secondary traits such as brace roots (BR), chlorophyll content (SPAD), % stem and root lodging (S&RL) among the RILs. Significant positive correlation of GY with BR and SPAD and negative correlation with S&RL indicated the potential use of these secondary traits in selection indices under waterlogged conditions. RILs were genotyped with 331 polymorphic single nucleotide polymorphism (SNP) markers using KASP (Kompetitive Allele Specific PCR) Platform. QTL mapping revealed five QTL on chromosomes 1, 3, 5, 7 and 10, which together explained approximately 30% of phenotypic variance for GY based on evaluation of RIL families under waterlogged conditions, with effects ranging from 520 to 640 kg/ha for individual genomic regions. 13 QTL were identified for various secondary traits associated with waterlogging tolerance, each individually explaining from 3 to 14% of phenotypic variance. Of the 22 candidate genes with known functional domains identified within the physical intervals delimited by the flanking markers of the QTL influencing GY and other secondary traits, six have previously been demonstrated to be associated with anaerobic responses in either maize or other model species. A pair of flanking SNP markers has been identified for each of the QTL and high throughput marker assays were developed to facilitate rapid introgression of waterlogging tolerance in tropical maize breeding programs.     

Biodiversity and Land uses at a regional scale: Is agriculture the biggest threat for reptile assemblages?

The human exploitation of land resources (land use) has been considered the major factor responsible for changes in biodiversity within terrestrial ecosystems given that it affects directly the distribution of the fauna. Reptiles are known to be particularly sensitive to habitat change due to their ecological constraints. Here, the impact of land use on reptile diversity was analysed, choosing Catalonia (NE Iberia) as a case study. This region provides a suitable scenario for such a biogeographical study since it harbours: 1) a rich reptile fauna; 2) a highly diverse environment showing strong variation in those variables usually shaping reptile distributions; and 3) good species distribution data. Potential species richness was calculated, using ecological modelling techniques (Ecological Niche Factor Analysis – ENFA). The subtraction of the observed from the potential species richness was the dependent variable in a backwards multiple linear regression, using land use variables. Agriculture was the land use with the strongest relation with the non-fulfilment of the potential species richness, indicating a trend towards a deficit of biodiversity. Deciduous forest was the only land use negatively related with the subtracted species richness. Results indicate a clear relationship between land use and biodiversity at a mesoscale. This finding represents an important baseline for conservation guidelines within the habitat change framework because it has been achieved at the same spatial scale of chorological studies and management policies.     

Proteogenomic analysis of polymorphisms and gene annotation divergences in prokaryotes using a clustered mass spectrometry-friendly database

Precise annotation of genes or open reading frames is still a difficult task that results in divergence even for data generated from the same genomic sequence. This has an impact in further proteomic studies, and also compromises the characterization of clinical isolates with many specific genetic variations that may not be represented in the selected database. We recently developed software called multistrain mass spectrometry prokaryotic database builder (MSMSpdbb) that can merge protein databases from several sources and be applied on any prokaryotic organism, in a proteomic-friendly approach. We generated a database for the Mycobacterium tuberculosis complex (using three strains of Mycobacterium bovis and five of M. tuberculosis), and analyzed data collected from two laboratory strains and two clinical isolates of M. tuberculosis. We identified 2561 proteins, of which 24 were present in M. tuberculosis H37Rv samples, but not annotated in the M. tuberculosis H37Rv genome. We were also able to identify 280 nonsynonymous single amino acid polymorphisms and confirm 367 translational start sites. As a proof of concept we applied the database to whole-genome DNA sequencing data of one of the clinical isolates, which allowed the validation of 116 predicted single amino acid polymorphisms and the annotation of 131 N-terminal start sites. Moreover we identified regions not present in the original M. tuberculosis H37Rv sequence, indicating strain divergence or errors in the reference sequence. In conclusion, we demonstrated the potential of using a merged database to better characterize laboratory or clinical bacterial strains.     

Cell type-specific proteasomal processing of HIV-1 Gag-p24 results in an altered epitope repertoire

Proteasomes are critical for the processing of antigens for presentation through the major histocompatibility complex (MHC) class I pathway. HIV-1 Gag protein is a component of several experimental HIV-1 vaccines. Therefore, understanding the processing of HIV-1 Gag protein and the resulting epitope repertoire is essential. Purified proteasomes from mature dendritic cells (DC) and activated CD4(+) T cells from the same volunteer were used to cleave full-length Gag-p24 protein, and the resulting peptide fragments were identified by mass spectrometry. Distinct proteasomal degradation patterns and peptide fragments were unique to either mature DC or activated CD4(+) T cells. Almost half of the peptides generated were cell type specific. Two additional differences were observed in the peptides identified from the two cell types. These were in the HLA-B35-Px epitope and the HLA-B27-KK10 epitope. These epitopes have been linked to HIV-1 disease progression. Our results suggest that the source of generation of precursor MHC class I epitopes may be a critical factor for the induction of relevant epitope-specific cytotoxic T cells.     

Rewatering plants after a long water-deficit treatment reveals that leaf epidermal cells retain their ability to expand after the leaf has apparently reached its final size

Background and Aims: Leaves expand during a given period of time until they reachtheir final size and form, which is called determinate growth.Duration of leaf expansion is stable when expressed in thermal-timeand in the absence of stress, and consequently it is often proposedthat it is controlled by a robust programme at the plant scale.The usual hypothesis is that growth cessation occurs when cellexpansion becomes limited by an irreversible tightening of cellwall, and that leaf size is fixed once cell expansion ceases.The objective of this paper was to test whether leaf expansioncould be restored by rewatering plants after a long soil water-deficitperiod. Methods: Four experiments were performed on two different species (Arabidopsisthaliana and Helianthus annuus) in which the area of leavesthat had apparently reached their final size was measured uponreversal of water stresses of different intensities and durations. Key Results: Re-growth of leaves that had apparently reached their finalsize occurred in both species, and its magnitude depended onlyon the time elapsed from growth cessation to rewatering. Leafarea increased up to 186% in A. thaliana and up to 88% in H.annuus after rewatering, with respect to the leaves of plantsthat remained under water deficit. Re-growth was accounted forby cell expansion. Increase in leaf area represented actualgrowth and not only a reversible change due to increased turgor. Conclusions: After the leaf has ceased to grow, leaf cells retain their abilityto expand for several days before leaf size becomes fixed. Aresponse window was identified in both species, during whichthe extent of leaf area recovery decreased with time after the‘initial’ leaf growth cessation. These results suggestthat re-growth after rewatering of leaves having apparentlyattained their final size could be a generalized phenomenon,at least in dicotyledonous plants.     

StCDPK1 is expressed in potato stolon tips and is induced by high sucrose concentration

StCDPK1 encodes a calcium-dependent protein kinase (CDPK) from Solanum tuberosum, which is transiently induced upon tuberization in swelling stolons. In situ hybridization determined that StCDPK1 mRNA is localized in the apical dome of tuberizing stolon tips, close to the region where sucrose was reported to accumulate. The expression of StCDPK1, and other tuber-specific genes was enhanced when in vitro-cultured potato plants were transferred to high sucrose or high sorbitol containing media. Glucose, fructose or a mixture of both showed no effect on CDPK expression. Okadaic acid blocked sucrose-inducible gene expression, suggesting that phosphatases from the PP1/PP2A family could also participate in the regulation of StCDPK1 and other tuberization-related genes.     

Phosphotransbutyrylase Expression in Bacillus megaterium

The molecular analysis of a genomic region of B. megaterium revealed the presence of a gene coding for the enzyme phosphotransbutyrylase (Ptb). The enzyme activity was measured throughout the different phases of growth in B. megaterium, and its activity was found to be maximal in the late exponential growth phase. The branched amino acids isoleucine and valine activated Ptb expression. Ptb_Bm was capable of using butyryl-CoA and 2-methyl-propionyl CoA as substrates. Act_Bm, a sigma⁵⁴ regulator from B. megaterium whose gene is situated upstream from the ptb gene, activated its expression. Received: 14 September 2000 / Accepted: 13 October 2000