Building genomes to understand biology.

Genetic manipulation is one of the central strategies that biologists use to investigate the molecular underpinnings of life and its diversity. Thus, advances in genetic manipulation usually lead to a deeper understanding of biological systems. During the last decade, the construction of chromosomes, known as synthetic genomics, has emerged as a novel approach to genetic manipulation. By facilitating complex modifications to chromosome content and structure, synthetic genomics opens new opportunities for studying biology through genetic manipulation. Here, we discuss different classes of genetic manipulation that are enabled by synthetic genomics, as well as biological problems they each can help solve.

"Lessons from the extremes: Epigenetic and genetic regulation in point monocentromere and holocentromere establishment on artificial chromosomes".

The formation of de novo centromeres on artificial chromosomes in humans (HACs) and fission yeast (SpYACs) has provided much insights to the epigenetic and genetic control on regional centromere establishment and maintenance. Similarly, the use of artificial chromosomes in point centromeric budding yeast Saccharomyces cerevisiae (ScYACs) and holocentric Caenorhabditis elegans (WACs) has revealed epigenetic regulation in the originally thought purely genetically-determined point centromeres and some centromeric DNA sequence features in holocentromeres, respectively. These relatively extreme and less characterized centromere organizations, on the endogenous chromosomes and artificial chromosomes, will be discussed and compared to the more well-studied regional centromere systems. This review will highlight some of the common epigenetic and genetic features in different centromere architectures, including the presence of the centromeric histone H3 variant, CENP-A or CenH3, centromeric and pericentric transcription, AT-richness and repetitiveness of centromeric DNA sequences.

Rapid and Efficient CRISPR/Cas9-Based Mating-Type Switching of Saccharomyces cerevisiae.

Rapid and highly efficient mating-type switching of Saccharomyces cerevisiae enables a wide variety of genetic manipulations, such as the construction of strains, for instance, isogenic haploid pairs of both mating-types, diploids and polyploids. We used the CRISPR/Cas9 system to generate a double-strand break at the MAT locus and, in a single cotransformation, both haploid and diploid cells were switched to the specified mating-type at ∼80% efficiency. The mating-type of strains carrying either rod or ring chromosome III were switched, including those lacking HMLα and HMRa cryptic mating loci. Furthermore, we transplanted the synthetic yeast chromosome V to build a haploid polysynthetic chromosome strain by using this method together with an endoreduplication intercross strategy. The CRISPR/Cas9 mating-type switching method will be useful in building the complete synthetic yeast (Sc2.0) genome. Importantly, it is a generally useful method to build polyploids of a defined genotype and generally expedites strain construction, for example, in the construction of fully a/a/α/α isogenic tetraploids.

Representing genetic variation with synthetic DNA standards.

The identification of genetic variation with next-generation sequencing is confounded by the complexity of the human genome sequence and by biases that arise during library preparation, sequencing and analysis. We have developed a set of synthetic DNA standards, termed 'sequins', that emulate human genetic features and constitute qualitative and quantitative spike-in controls for genome sequencing. Sequencing reads derived from sequins align exclusively to an artificial in silico reference chromosome, rather than the human reference genome, which allows them them to be partitioned for parallel analysis. Here we use this approach to represent common and clinically relevant genetic variation, ranging from single nucleotide variants to large structural rearrangements and copy-number variation. We validate the design and performance of sequin standards by comparison to examples in the NA12878 reference genome, and we demonstrate their utility during the detection and quantification of variants. We provide sequins as a standardized, quantitative resource against which human genetic variation can be measured and diagnostic performance assessed.

Minichromosomes and artificial chromosomes in Arabidopsis.

Minichromosomes have been extensively used as tools for revealing the functional structures of eukaryotic chromosomes. However, the definition of a minichromosome is still ambiguous. Based on previous reports on various eukaryotes, minichromosomes are defined here to be chromosomes that are smaller than one third the size of the smallest chromosome in the given species. In Arabidopsis thaliana, therefore, chromosomes <8.5 Mb in length are classified as minichromosomes, although to date only six different minichromosomes have been found or created, probably due to their extremely small sizes that limit detection. Minichromosomes vary from 1.7 to 8.4 Mb in length and are much shorter than authentic chromosomes (25.3 to 38.0 Mb). Linear and circular minichromosomes have been identified, and both types are maintained as experimental lines. Most of the circular, ring-shaped minichromosomes in Arabidopsis are relatively stable at mitosis and transmissible to the next generation, regardless of the centromere form (dicentric or monocentric). Recently, a ring minichromosome was artificially generated by a combination of the Cre/LoxP and Ac/Ds systems. This artificial ring chromosome, AtARC1, has several advantages over the previously reported minichromosomes as a chromosome vector; therefore, this method of generating artificial ring chromosomes is expected to be improved for application to other plant species including important crops.

Alteration of chromosome numbers by generation of minichromosomes -- is there a lower limit of chromosome size for stable segregation?

Practical applications of minichromosomes, generated by de novo composition or by truncation of natural chromosomes, rely on stable transmission of these chromosomes. Functional centromeres, telomeres and replication origins are recognized as prerequisites for minichromosome stability. However, it is not yet clear whether, and if yes, to what degree the chromatin content has a qualitative or quantitative impact on stable chromosome transmission. A small translocation chromosome, which arose after X-irradiation of a reconstructed field bean karyotype, comprised approximately 5% of the haploid metaphase complement and was found to consist of three pieces of duplicated chromatin and a wild-type centromere. This chromosome was stably transmitted through all meristematic and pollen grain mitoses but was frequently lost during meiosis (66% loss in hemizygous and 33% in homozygous condition). This minichromosome was only a little smaller than stably segregating translocation chromosomes (comprising approximately 6% of the genome) of a euploid field bean karyotype. The duplications specific for this minichromosome did not influence meiotic segregation when associated with non-duplicated chromatin of other chromosomes. In comparison with minichromosomes of other species, the possibility of a lower size limit for a stable chromosome transmission must therefore be considered which might be based, for instance, on insufficient lateral support of centromeres or on insufficient bivalent stability due to the incapability of chiasma formation.

An assessment of gene prediction accuracy in large DNA sequences.

One of the first useful products from the human genome will be a set of predicted genes. Besides its intrinsic scientific interest, the accuracy and completeness of this data set is of considerable importance for human health and medicine. Though progress has been made on computational gene identification in terms of both methods and accuracy evaluation measures, most of the sequence sets in which the programs are tested are short genomic sequences, and there is concern that these accuracy measures may not extrapolate well to larger, more challenging data sets. Given the absence of experimentally verified large genomic data sets, we constructed a semiartificial test set comprising a number of short single-gene genomic sequences with randomly generated intergenic regions. This test set, which should still present an easier problem than real human genomic sequence, mimics the approximately 200kb long BACs being sequenced. In our experiments with these longer genomic sequences, the accuracy of GENSCAN, one of the most accurate ab initio gene prediction programs, dropped significantly, although its sensitivity remained high. Conversely, the accuracy of similarity-based programs, such as GENEWISE, PROCRUSTES, and BLASTX was not affected significantly by the presence of random intergenic sequence, but depended on the strength of the similarity to the protein homolog. As expected, the accuracy dropped if the models were built using more distant homologs, and we were able to quantitatively estimate this decline. However, the specificities of these techniques are still rather good even when the similarity is weak, which is a desirable characteristic for driving expensive follow-up experiments. Our experiments suggest that though gene prediction will improve with every new protein that is discovered and through improvements in the current set of tools, we still have a long way to go before we can decipher the precise exonic structure of every gene in the human genome using purely computational methodology.