SummaryLactococcus lactis produces lactic acid and is widely used in the manufacturing of various fermented dairy products. However, the species is also frequently isolated from non‐dairy niches, such as fermented plant material. Recently, these non‐dairy strains have gained increasing interest, as they have been described to possess flavour‐forming activities that are rarely found in dairy isolates and have diverse metabolic properties. We performed an extensive whole‐genome diversity analysis on 39 L. lactis strains, isolated from dairy and plant sources. Comparative genome hybridization analysis with multi‐strain microarrays was used to assess presence or absence of genes and gene clusters in these strains, relative to all L. lactis sequences in public databases, whereby chromosomal and plasmid‐encoded genes were computationally analysed separately. Nearly 3900 chromosomal orthologous groups (chrOGs) were defined on basis of four sequenced chromosomes of L. lactis strains (IL1403, KF147, SK11, MG1363). Of these, 1268 chrOGs are present in at least 35 strains and represent the presently known core genome of L. lactis, and 72 chrOGs appear to be unique for L. lactis. Nearly 600 and 400 chrOGs were found to be specific for either the subspecies lactis or subspecies cremoris respectively. Strain variability was found in presence or absence of gene clusters related to growth on plant substrates, such as genes involved in the consumption of arabinose, xylan, α‐galactosides and galacturonate. Further niche‐specific differences were found in gene clusters for exopolysaccharides biosynthesis, stress response (iron transport, osmotolerance) and bacterial defence mechanisms (nisin biosynthesis). Strain variability of functions encoded on known plasmids included proteolysis, lactose fermentation, citrate uptake, metal ion resistance and exopolysaccharides biosynthesis. The present study supports the view of L. lactis as a species with a very flexible genome.

Most common diseases are complex, involving multiple genetic and environmental factors and their interactions. In the past decade, genome-wide association studies (GWAS) have successfully identified thousands of genetic variants underlying susceptibility to complex diseases. However, the results from these studies often do not provide evidence on how the variants affect downstream pathways and lead to the disease. Therefore, in the post-GWAS era the greatest challenge lies in combining GWAS findings with additional molecular data to functionally characterize the associations. The advances in various ~omics techniques have made it possible to investigate the effect of risk variants on intermediate molecular levels, such as gene expression, methylation, protein abundance or metabolite levels. As disease aetiology is complex, no single molecular analysis is expected to fully unravel the disease mechanism. Multiple molecular levels can interact and also show plasticity in different physiological conditions, cell types and disease stages. There is therefore a great need for new integrative approaches that can combine data from different molecular levels and can help construct the causal inference from genotype to phenotype. Systems genetics is such an approach; it is used to study genetic effects within the larger scope of systems biology by integrating genotype information with various ~omics datasets as well as with environmental and physiological variables. In this review, we describe this approach and discuss how it can help us unravel the molecular mechanisms through which genetic variation causes disease. This article is part of a Special Issue entitled: From Genome to Function.

We identified an lncRNA that can play an important regulatory role in liver function and provide new insights into the regulation of hepatocyte viability in NASH. (Hepatology 2017;66:794-808).