The " Mendelian Gene " and the " Molecular Gene " : Two Relevant Concepts of Genetic Units

International audienceWe focus here on two prevalent meanings of the word gene in research articles. On one hand, the gene, named here “molecular gene”, is a stretch of DNA that is transcribed and codes for an RNA or a polypeptide with a known or presumed function (as in “gene network'), whose exact spatial delimitation on the chromosome remains a matter of debate, especially in cases with alternative splicing, antisense transcripts, etc. On the other hand, the gene, called here “Mendelian gene”, is a segregating genetic unit which is detected through phenotypic differences associated with different alleles at the same locus (as in “gene flow”). We show that the “Mendelian gene” concept is still extensively used today in biology research and is sometimes confused with the “molecular gene”. We try here to clarify the distinction between both concepts. Efforts to delineate the beginning and the end of the DNA sequence corresponding to the “Mendelian gene” and the “molecular gene” reveal that both entities do not always match. We argue that both concepts are part of two relevant frameworks for explaining the biological world

Insights into Land Plant Evolution Garnered from the Marchantia polymorpha Genome.

The evolution of land flora transformed the terrestrial environment. Land plants evolved from an ancestral charophycean alga from which they inherited developmental, biochemical, and cell biological attributes. Additional biochemical and physiological adaptations to land, and a life cycle with an alternation between multicellular haploid and diploid generations that facilitated efficient dispersal of desiccation tolerant spores, evolved in the ancestral land plant. We analyzed the genome of the liverwort Marchantia polymorpha, a member of a basal land plant lineage. Relative to charophycean algae, land plant genomes are characterized by genes encoding novel biochemical pathways, new phytohormone signaling pathways (notably auxin), expanded repertoires of signaling pathways, and increased diversity in some transcription factor families. Compared with other sequenced land plants, M. polymorpha exhibits low genetic redundancy in most regulatory pathways, with this portion of its genome resembling that predicted for the ancestral land plant. PAPERCLIP

Insights into Land Plant Evolution Garnered from the Marchantia polymorpha Genome

The evolution of land flora transformed the terrestrial environment. Land plants evolved from an ancestral charophycean alga from which they inherited developmental, biochemical, and cell biological attributes. Additional biochemical and physiological adaptations to land, and a life cycle with an alternation between multicellular haploid and diploid generations that facilitated efficient dispersal of desiccation tolerant spores, evolved in the ancestral land plant. We analyzed the genome of the liverwort Marchantia polymorpha, a member of a basal land plant lineage. Relative to charophycean algae, land plant genomes are characterized by genes encoding novel biochemical pathways, new phytohormone signaling pathways (notably auxin), expanded repertoires of signaling pathways, and increased diversity in some transcription factor families. Compared with other sequenced land plants, M. polymorpha exhibits low genetic redundancy in most regulatory pathways, with this portion of its genome resembling that predicted for the ancestral land plant

Translational Genomics in Legumes Allowed Placing In Silico 5460 Unigenes on the Pea Functional Map and Identified Candidate Genes in Pisum sativum L.

To identify genes involved in phenotypic traits, translational genomics from highly characterized model plants to poorly characterized crop plants provides a valuable source of markers to saturate a zone of interest as well as functionally characterized candidate genes. In this paper, an integrated view of the pea genetic map was developed. A series of gene markers were mapped and their best reciprocal homologs were identified on M. truncatula, L. japonicus, soybean, and poplar pseudomolecules. Based on the syntenic relationships uncovered between pea and M. truncatula, 5460 pea Unigenes were tentatively placed on the consensus map. A new bioinformatics tool, http://www.thelegumeportal.net/pea_mtr_translational_toolkit, was developed that allows, for any gene sequence, to search its putative position on the pea consensus map and hence to search for candidate genes among neighboring Unigenes. As an example, a promising candidate gene for the hypernodulation mutation nod3 in pea was proposed based on the map position of the likely homolog of Pub1, a M. truncatula gene involved in nodulation regulation. A broader view of pea genome evolution was obtained by revealing syntenic relationships between pea and sequenced genomes. Blocks of synteny were identified which gave new insights into the evolution of chromosome structure in Papillionoids and Eudicots. The power of the translational genomics approach was underlined

Mining the genome for ‘known unknowns’

Bioinformatics is a multidisciplinary area that combines two major areas: Biology and Computer Science. It’s one of the fastest rising areas of investigation nowadays. It’s also a fundamental area for the processing of data and information from discoveries in the genetics area. One area that is prominent in the bioinformatics area is gene prediction, where various tools are available to aid researchers. Even though there are several gene prediction tools available, the most used are from several years back. They are reliable tools, but need optimization and some are not so flexible for modification. Tools created in the past years base their model on previous tools. In this dissertation work, a new model is proposed. Through ORF extraction from proteincoding sequences of a fasta-formatted file that the user inputs, these are compared to a target sequence of the user’s choice. A profile-HMM is used as the model to compare the sequences, returning a Logp value for each ORF compared with the target sequence. Match, insert and delete state probabilities were modified, to find the best scenario. The Viterbi algorithm was used to train the model, due to its speed. The results obtained were concordant with what we expected: That an ORF, which would be in the target sequence, presented a better Logp value than an ORF from a randomly selected sequence.A bioinformática é uma área multidisciplinar que combina duas áreas fundamentais: biologia e ciências da computação. É uma das áreas de investigação que mais está a crescer nos dias de hoje. É também uma área fundamental para o processamento de dados e informação na área da genética. Um ramo prominente na área da bioinformática é a predição de genes. Várias ferramentas encontram-se disponíveis para auxiliar investigadores. Estas ferramentas também se encontram disponíveis ao público em geral. Embora existam várias ferramentas, as mais utilizadas já têm muitos anos. São ferramentas fiáveis porém algumas precisam de ser otimizadas e não são muito flexíveis no que toca à sua modificação. Neste trabalho de dissertação é proposto um novo modelo. Por meio da extração de ORFs a partir de sequências de DNA que codificam para proteínas, inserido pelo usuário em formato fasta, estes são comparados com uma sequência alvo escolhida pelo utilizador. Foi utilizado um Profile-HMM como modelo para comparar as sequências, em que um valor de probabilidade logarítmica (Logp) é devolvido consoante a semelhança entre as sequências comparadas: o ORF e a sequência alvo. Quanto mais semelhantes forem as sequências comparadas, melhor será o valor da probabilidade logarítmica. Foram criados vários cenários de modo a ver qual seria a melhor forma de implementar o Profile-HMM. Nestes, os estados de correspondência, inserção e deleção foram modificados, até chegar ao melhor cenário. O algoritmo de Viterbi foi utilizado para treinar o modelo, devido à sua velocidade. Os resultados obtidos pelo modelo foram concordantes com o que esperávamos: um ORF que está presente na sequência alvo terá um valor Logp melhor que um ORF que não está presente na sequência alvo

Molecular evolution and diversification of the SMXL gene family

Strigolactones (SLs) are a relatively recent addition to the list of plant hormones that control different aspects of plant development. SL signalling is perceived by an alpha/beta hydrolase, DWARF 14 (D14). A close homolog of D14, KARRIKIN INSENSTIVE2 (KAI2), is involved in perception of an uncharacterized molecule called karrikin (KAR). Recent studies in Arabidopsis identified the SUPPRESSOR OF MAX2 1 (SMAX1) and SMAX1-LIKE 7 (SMXL7) to be potential SCF-MAX2 complex-mediated proteasome targets of KAI2 and D14, respectively. Genetic studies on SMXL7 and SMAX1 demonstrated distinct developmental roles for each, but very little is known about these repressors in terms of their sequence features. In this study, we performed an extensive comparative analysis of SMXLs and determined their phylogenetic and evolutionary history in the plant lineage. Our results show that SMXL family members can be subdivided into four distinct phylogenetic clades/classes, with an ancient SMAX1. Further, we identified the Glade-specific motifs that have evolved and that might act as determinants of SL-KAR signalling specificity. These specificities resulted from functional diversities among the clades. Our results suggest that a gradual co-evolution of SMXL members with their upstream receptors D14/KAI2 provided an increased specificity to both the SL perception and response in land plants

A Spontaneous Dominant-Negative Mutation within a 35S::AtMYB90 Transgene Inhibits Flower Pigment Production in Tobacco

In part due to the ease of visual detection of phenotypic changes, anthocyanin pigment production has long been the target of genetic and molecular research in plants. Specific members of the large family of plant myb transcription factors have been found to play critical roles in regulating expression of anthocyanin biosynthetic genes and these genes continue to serve as important tools in dissecting the molecular mechanisms of plant gene regulation.A spontaneous mutation within the coding region of an Arabidopsis 35S::AtMYB90 transgene converted the activator of plant-wide anthocyanin production to a dominant-negative allele (PG-1) that inhibits normal pigment production within tobacco petals. Sequence analysis identified a single base change that created a premature nonsense codon, truncating the encoded myb protein. The resulting mutant protein lacks 78 amino acids from the wild type C-terminus and was confirmed as the source of the white-flower phenotype. A putative tobacco homolog of AtMYB90 (NtAN2) was isolated and found to be expressed in flower petals but not leaves of all tobacco plants tested. Using transgenic tobacco constitutively expressing the NtAN2 gene confirmed the NtAN2 protein as the likely target of PG-1-based inhibition of tobacco pigment production.Messenger RNA and anthocyanin analysis of PG-1Sh transgenic lines (and PG-1Sh x purple 35S::NtAN2 seedlings) support a model in which the mutant myb transgene product acts as a competitive inhibitor of the native tobacco NtAN2 protein. This finding is important to researchers in the field of plant transcription factor analysis, representing a potential outcome for experiments analyzing in vivo protein function in test transgenic systems that over-express or mutate plant transcription factors