BACKGROUND
lactococcus lactis – a low-gc gram-positive model organism, found frequently in both dairy and non-dairy  <cit>  environments, has been extensively studied due to its industrial importance.
major focus of these studies has been on dairy isolates, of which the genomes of three isolates have been sequenced  <cit> .
plant isolates compared to dairy isolates show higher stress-tolerance and have more extensive fermentative abilities  <cit> .
due to their larger genetic and metabolic repertoire non-dairy isolates of l. lactis are therefore of interest in dairy food fermentation  <cit> .
strains used in dairy starter cultures have presumably evolved from plant strains, where some metabolic capabilities were lost in order to adapt to dairy environments  <cit> .
recently, the genome of ssp.
lactis strain kf <dig> was fully sequenced  <cit>  and that of strain kf <dig> was partially sequenced  <cit> .
these two plant l. lactis isolates were reported to possess many genes related to uptake of plant cell-wall degradation products such as arabinose and xylose  <cit> .
many genes present in these two isolates are new and do not have homologs in the three l. lactis strains il <dig>  mg <dig> and sk <dig> of dairy origin  <cit> .
recently, the genomes of several other l. lactis strains have also been fully sequenced  <cit> .
furthermore, many l. lactis strains were reported to have plasmids, enriching the genotypic and phenotypic repertoire of this species  <cit> .
l. lactis strains isolated from different niches have been reported to have high genomic sequence divergence  <cit> , also at the subspecies level  <cit> .
their gene content partly reflects their phenotypic properties such as niche adaptation  <cit> .
in general, genomic and phenotypic properties of strains have been studied separately  <cit> , and less frequently possible relations between genes and phenotypes have been studied  <cit> .
integrative genotype-phenotype matching would facilitate identifying genetic markers relevant for the manifestation of a phenotype.
we therefore used an iterative gene selection procedure coined phenolink  <cit>  to more accurately determine gene to phenotype relations of  <dig> l. lactis strains from  <dig> different subspecies: ssp.
lactis, ssp.
cremoris and ssp.
hordniae .
this allowed identifying novel gene-phenotype relations as well as confirming previously reported relations.
in addition to identified gene-phenotype relations, we also present a coherent dataset of genotype and phenotype data based on  <dig> experiments, which could prove to be valuable in comparative analysis of these strains.
a: in total there are  <dig> phenotyping experiments , but only  <dig> were usable in our analysis .
RESULTS
strain similarity based on phenotypes
a recent extensive genotyping study of l. lactis strains revealed that clustering based on chromosomal genes of these strains shows a high correspondence with the sub-speciation, whereas clustering using plasmid genes reflects niche-adaptation properties  <cit> .
in this study, we also analyzed these strains using only their phenotypic measurements in  <dig> experiments .
the used phenotypic metrics differ depending on the type of experiment performed.
using all phenotypic measurements in clustering could result in clusters that consist of phenotypic measurements that are in fact incomparable, for example, phenotypic readout of  <dig> in an api test indicates no growth, whereas the same value obtained in the gm <dig> medium shows growth .
from the phenotype clustering, where pre-processed phenotype data was used, we conclude that only some phenotype types partly co-cluster .
however the phenotype grouping is not very apparent from clustering phenotypic measurements only.
to this end, five categories of experiments were defined based on experiment type:  growth on sugars,  antibiotic resistance,  metal resistance,  growth on milk or polysaccharides and  remaining experiments .
visualization of links to all phenotypes creates a very large figure that is difficult to present and interpret .
since each experiment category represents a related set of experiments, each experiment category was analyzed separately.
therefore for four of the experiment categories , strains were hierarchically clustered based on their phenotypes .
based on the hierarchical clustering results, strains isolated from the same source showed different levels of phenotype similarity: growth on sugar , antibiotic resistance experiments , growth on milk and polysaccharides  and metal resistance .
phenotype-based hierarchical clustering of these strains showed that niche properties better correspond to phenotype differences of strains rather than their subspecies-level differences.
clustering provided only limited information and, thus, it can only be used as an initial screening of phenotype data.
as the focus of this study is to find relations between genes and phenotypes we applied integrative analysis of phenotype and genotype data to reveal these associations.
these are experiments of which at least a single phenotype was accurately classified; for full list of experiments and their descriptions see additional file  <dig>
genotype-phenotype matching
integrated analysis using an iterative gene selection allowed identification of gene-phenotype relations that could not be found by studying genotype and phenotype data separately.
in genotype-phenotype matching, we used the presence/absence of  <dig> ortholog groups  in  <dig> l. lactis strains  determined by comparative genome hybridization  as genotype data.
these  <dig> strains are a subset of a large representative collection of l. lactis trains that covers genotype, niche and phenotype diversity of l. lactis species  <cit> .
for phenotype data, we used phenotypic measurements of these strains in  <dig> experiments that were previously assessed in separate studies .
after pre-processing, phenotype data from  <dig> experiments was usable for genotype-phenotype matching .
only associations of genes to accurately classified phenotypes  were considered in further analysis, which resulted in  <dig> phenotypes, assessed in  <dig> different experiments.
many gene-phenotype relations were identified: a total of  <dig> ogs or on average  <dig> genes per reference strain were identified to be related to at least one of these  <dig> phenotypes.
in the present study, we focussed on gene clusters consisting of at least two phenotype-related genes that are in close genomic proximity .
transposases, integrases and phage proteins were also removed, because relations between these proteins and phenotypes are likely to be spurious.
discarding above-mentioned genes decreased the percentage of phenotype-related genes by about 50% on average.
in analyzing gene clusters, we first considered gene clusters of which their presence relates to a positive trait  and absence relates to a negative trait .
there were also many gene clusters with inverse patterns, where an absence of a gene cluster leads to a positive trait.
an inverse relationship between genes and phenotypes might indicate that in the absence of a regulator, genes previously inhibited by this particular regulator can become active, which in turn might lead to a positive trait .
in the supplementary data we provide all identified relations including inverse relations .
genes related to carbohydrate utilization
several gene clusters related to fermentation of different sugars were identified by genotype-phenotype matching.
among them were gene clusters that were previously described to be involved in carbohydrate utilization  <cit> .
for instance, the presence of a gene cluster required for arabinose utilization  <cit>  was confirmed in this study to correlate strongly with the ability to grow on arabinose .
several gene clusters were found to be related to sucrose utilization; for instance a cluster of  <dig> genes  that already was annotated as being involved in sucrose utilization   <cit> .
the other three reference strains do not grow on sucrose, and this gene cluster was absent in these strains.
these genes were also found to be inversely related to growth on lactose, where they were present in most of the strains that grew slowly on lactose and absent in most of the strains that can grow on lactose .
such a relationship suggests that most of the strains that grow well on sucrose  cannot grow or grow slowly on lactose  or vice-versa .
this also partly reflects niche adaptation of these strains, because most of the lactose-degrading strains were dairy isolates  and most of the sucrose-utilizing strains were of plant origin .
additionally, we also identified an association between sucrose fermentation and nisin production in l. lactis.
both sucrose utilization and nisin biosynthesis genes were earlier reported to be encoded on a transposon in strain nizo r <dig>  <cit> .
additionally, linkage between these phenotypes has been observed in  <dig> l. lactis strains  <cit> .
visualization of identified gene-phenotype relations revealed that sucrose-negative strains lack part or all of the genes related to nisin production.
for example, kf <dig> - a nisin non-producer strain - contains only part of the nisin gene cluster, conferring immunity but not production   <cit> .
however, we found no strong relation between growth on sucrose and presence of nisin biosynthesis genes, confirming a previous observation that the presence of nisin biosynthesis genes in a strain does not always confer its growth on sucrose  <cit> .
a large cluster of  <dig> genes  was found to be related to growth on melibiose, a plant disaccharide, but not to any of the other carbohydrates tested.
this confirms an earlier observation that strain kf <dig> can utilize this disaccharide while  <dig> other strains il <dig> , sk <dig>  and kf <dig>  strains cannot grow on melibiose  <cit> .
we also investigated whether a genomic region that encompasses these genes was deleted in melibiose-negative strains, because chromosomal deletion of a  <dig> kb region in streptococcus mutans strains leads to melibiose-negative phenotype  <cit> ; this  <dig> kb region contains orthologs of llkf_2260- <dig> of strain kf <dig>  because tiling pan-genome cgh arrays were used to identify gene occurrence in these strains, deletion of a genomic region in query strains can be determined .
therefore, we visualized a small genomic region of approximately  <dig> kb  that covers the starting position of llkf_ <dig> and the end position of llkf_ <dig> on the kf <dig> genome.
this region encompasses all these  <dig> genes and several more genes.
indeed, we also observed that this large  <dig> kb region was deleted or absent in all melibiose-negative strains from both plant and dairy origin .
probably, only  <dig> genes consecutively located in a  <dig> kb region  are necessary for growth on melibiose.
genes related to metal resistance
using genotype-phenotype matching several gene clusters were found relating to heavy metal resistance, and some of these genes are located on plasmids.
for instance, we found clusters of genes related to copper resistance; these are located on plasmids c and d in strain sk <dig> , which confirms a previous finding  <cit> .
one of these gene clusters  was previously identified to be involved in copper resistance  <cit> .
additionally, a cluster of four genes  was identified by gene-trait matching to be related to arsenite resistance , which is usually known as a plasmid-borne trait  <cit> , and two of these genes are annotated as arsenical-resistance proteins .
however, these could be plasmid genes that were transferred to the chromosome in the plasmid curing process of mg <dig>
genes related to arginine metabolism
several gene clusters were found to be relevant to arginine hydrolase activity, and therefore the ability to metabolize arginine.
a cluster of  <dig> genes  was identified to be relevant to arginine metabolism .
all  <dig> proteins are annotated as hypothetical proteins in strain il <dig> and two of them, l <dig> and l <dig>  are probably membrane proteins as they belong to a cluster of orthologous groups of proteins   <cit> , which contains membrane proteins.
a gene cluster of  <dig> mg <dig> genes was also identified to be related to arginine metabolism , and two encoded proteins, llmg_ <dig> and llmg_ <dig>  are in the same cogs with proteins l <dig> and l <dig> of strain il <dig>  the protein l <dig> belongs to a family of membrane proteins of which some are glycosyltransferase-associated proteins.
probably, at least two of these proteins, l <dig> and l <dig>  and their mg <dig> orthologs, llmg_ <dig> and llmg_ <dig>  should be re-annotated as transport proteins or maybe more specifically arginine transport proteins.
however, experimental validation is necessary.
plasmid genes related to phenotypes
plasmid genes are necessary for manifestation of some phenotypes.
for instance, it is already well-known that the lactose metabolism genes are localized on plasmid d of sk <dig>  <cit> .
indeed, we found that the presence/absence of these lactose metabolism genes  in the  <dig> strains to be highly correlated to growth on lactose .
again, there appears to be an inverse relationship with the presence of these same lactose utilization genes for no-growth on some other sugars .
thus, using plasmid genes in addition to chromosomal genes in genotype-phenotype matching allowed confirming previously known functions of some plasmid genes and identifying novel relationships between plasmid genes and some phenotypes.
partial gene-phenotype relations
for each experiment category several  partial relations between gene clusters and phenotypes, where a gene is present in only a subset of strains with a particular phenotype , were identified.
most of these gene clusters contain only two genes and were often found to be relevant to a negative trait .
as example we present partial relations between a cluster of four genes of strain mg <dig>  and arsenite resistance .
these genes were found to be relevant for strains growing at  <dig>  mm of arsenite and are present in most of the highly resistant strains.
however, some of these genes are only present in a subset of strains with no or mild resistance .
visualizing occurrence of these genes in strains revealed that they are mostly absent in strains with no arsenite resistance phenotype and mostly present in strains with mild or high arsenite resistance phenotypes .
discussion
genotype-phenotype association analysis of  <dig> l. lactis strains by integrating large genotype and phenotype data sets allowed screening of gene to phenotype relations.
only the top  <dig> genes per phenotype were selected as important , because probably most relevant genes related to a phenotype should be among these  <dig> genes and their correlated genes.
indeed, only less than 1% of phenotypes had  <dig> or more related genes in the top list.
furthermore, identified relations were visualized by integrating each gene’s occurrence with its phenotype importance, which allows a quick screening of many relations.
however, some relations could be due to an indirect effect of other factors that were not taken into account.
for example, the anti-correlation between sucrose and lactose metabolism could be a bias resulting from starter-culture selection programmes, where often bacteriocin-negative strains were selected that could have led to selection of strains that can use lactose instead of sucrose.
additionally, for some phenotypes we could not find many related genes, for example, well-known arginine-metabolism related genes were not found as relevant to metabolism of arginine.
therefore, we analyzed all ogs with gene members containing a word ‘arginine’ in their annotation and genes of the arginine deiminase pathway .
however, all these genes were either present in all or in at least  <dig> out of  <dig> strains, and such genes are removed in the pre-processing step of phenolink, because they are not capable to separate strains with different phenotypes .
we described a few examples where the annotation of genes could be refined and a few cases where new functions are suggested for genes with unknown functions.
we were able to pinpoint only a few novel relations, but analyzing all identified gene-phenotype relations in detail should allow finding even more novel relations and refining annotations of more genes.
genotype-phenotype matching allows comprehensive screening for possible relations between genes and phenotypes.
we had data for  <dig> strains and, thus, there were relatively few strains with a given phenotype and in some experiments many strains manifested the same phenotype.
therefore, few partial gene-phenotype relations were identified in this study.
more partial relations could be identified using data sets based on more l. lactis strains, which would allow finding analogous genes that have similar function but different sequences.
even with dna sequencing prices dropping, determining the gene content of dozens of strains by genome sequencing could still be costly.
pan-genome arrays allow querying occurrence of genes in multiple strains more cost-effectively, but genes absent in reference sequences and strongly divergent genes would be missed.
though the presence/absence data can be linked to phenotypes, it cannot account for effects of regulatory control or post-translational modifications.
thus putative gene-phenotype relations should be experimentally tested by high-throughput techniques such as gene expression analysis.
annotating genes of a genome is essential in understanding the genomic properties of any strain.
gene annotation is often based on sequence similarity, so mistakes in annotating a single gene could propagate to genes of different organisms through annotation by sequence similarity.
therefore identified gene-phenotype relations should be experimentally validated and linked to other information sources such as pathway information.
this would allow decreasing error propagation introduced by sequence similarity based gene function prediction approaches.
genotype-phenotype matching results show that the largest group of proteins related to phenotypes was hypothetical proteins indicating that gene annotations could still be improved for all  <dig> reference strains.
genomes of more bacterial strains are sequenced on a daily basis, which shows the critical importance of accurate gene function prediction.
identified gene-phenotype relations would allow more accurately determining functions of many genes, and hence better understanding of genotype- and phenotype-level differences among  <dig> l. lactis strains.
we provide all identified relations as well as complete genotype and phenotype data set .
this data set not only serves as a collection of leads to phenotypes, but due to large data size could also be used to test different association methods.
CONCLUSIONS
lactococcus lactis has been extensively studied due to its industrial importance.
here we provide a coherent genotype and phenotype dataset and its interpretation for the lactococcus species.
we integrated for  <dig> l. lactis strains their genotypic measurements as well as phenotypes derived from  <dig> different experiments  to identify gene-phenotype relations.
our results are publicly available  and contains many leads into lactococcus species-wide genotype-phenotype relations that can further be analysed and experimentally validated.
these relations could be used to refine functions of genes.
as new genome sequences emerge frequently, this would allow annotating gene functions for these new genomes more accurately and predicting phenotypes of new strains based on their dna sequence.

 lactococcus lactis – a low-gc gram-positive model organism, found frequently in both dairy and non-dairy environments, has been extensively studied due to its industrial importance. major focus of these studies has been on dairy isolates, of which the genomes of three isolates have been sequenced. plant isolates compared to dairy isolates show higher stress-tolerance and have more extensive fermentative abilities. due to their larger genetic and metabolic repertoire non-dairy isolates of l. lactis are therefore of interest in dairy food fermentation. strains used in dairy starter cultures have presumably evolved from plant strains, where some metabolic capabilities were lost in order to adapt to dairy environments. recently, the genome of ssp. lactis strain kf was fully sequenced and that of strain kf was partially sequenced. these two plant l. lactis isolates were reported to possess many genes related to uptake of plant cell-wall degradation products such as arabinose and xylose. many genes present in these two isolates are new and do not have homologs in the three l. lactis strains il mg and sk of dairy origin. recently, the genomes of several other l. lactis strains have also been fully sequenced. furthermore, many l. lactis strains were reported to have plasmids, enriching the genotypic and phenotypic repertoire of this species. l. lactis strains isolated from different niches have been reported to have high genomic sequence divergence, also at the subspecies level. their gene content partly reflects their phenotypic properties such as niche adaptation. in general, genomic and phenotypic properties of strains have been studied separately, and less frequently possible relations between genes and phenotypes have been studied. integrative genotype-phenotype matching would facilitate identifying genetic markers relevant for the manifestation of a phenotype. we therefore used an iterative gene selection procedure coined phenolink to more accurately determine gene to phenotype relations of l. lactis strains from different subspecies: ssp. lactis, ssp. cremoris and ssp. hordniae. this allowed identifying novel gene-phenotype relations as well as confirming previously reported relations. in addition to identified gene-phenotype relations, we also present a coherent dataset of genotype and phenotype data based on experiments, which could prove to be valuable in comparative analysis of these strains. a: in total there are phenotyping experiments, but only were usable in our analysis.  strain similarity based on phenotypes a recent extensive genotyping study of l. lactis strains revealed that clustering based on chromosomal genes of these strains shows a high correspondence with the sub-speciation, whereas clustering using plasmid genes reflects niche-adaptation properties. in this study, we also analyzed these strains using only their phenotypic measurements in experiments. the used phenotypic metrics differ depending on the type of experiment performed. using all phenotypic measurements in clustering could result in clusters that consist of phenotypic measurements that are in fact incomparable, for example, phenotypic readout of in an api test indicates no growth, whereas the same value obtained in the gm medium shows growth. from the phenotype clustering, where pre-processed phenotype data was used, we conclude that only some phenotype types partly co-cluster. however the phenotype grouping is not very apparent from clustering phenotypic measurements only. to this end, five categories of experiments were defined based on experiment type: growth on sugars, antibiotic resistance, metal resistance, growth on milk or polysaccharides and remaining experiments. visualization of links to all phenotypes creates a very large figure that is difficult to present and interpret. since each experiment category represents a related set of experiments, each experiment category was analyzed separately. therefore for four of the experiment categories, strains were hierarchically clustered based on their phenotypes. based on the hierarchical clustering results, strains isolated from the same source showed different levels of phenotype similarity: growth on sugar, antibiotic resistance experiments, growth on milk and polysaccharides and metal resistance. phenotype-based hierarchical clustering of these strains showed that niche properties better correspond to phenotype differences of strains rather than their subspecies-level differences. clustering provided only limited information and, thus, it can only be used as an initial screening of phenotype data. as the focus of this study is to find relations between genes and phenotypes we applied integrative analysis of phenotype and genotype data to reveal these associations. these are experiments of which at least a single phenotype was accurately classified; for full list of experiments and their descriptions see additional file genotype-phenotype matching integrated analysis using an iterative gene selection allowed identification of gene-phenotype relations that could not be found by studying genotype and phenotype data separately. in genotype-phenotype matching, we used the presence/absence of ortholog groups in l. lactis strains determined by comparative genome hybridization as genotype data. these strains are a subset of a large representative collection of l. lactis trains that covers genotype, niche and phenotype diversity of l. lactis species. for phenotype data, we used phenotypic measurements of these strains in experiments that were previously assessed in separate studies. after pre-processing, phenotype data from experiments was usable for genotype-phenotype matching. only associations of genes to accurately classified phenotypes were considered in further analysis, which resulted in phenotypes, assessed in different experiments. many gene-phenotype relations were identified: a total of ogs or on average genes per reference strain were identified to be related to at least one of these phenotypes. in the present study, we focussed on gene clusters consisting of at least two phenotype-related genes that are in close genomic proximity. transposases, integrases and phage proteins were also removed, because relations between these proteins and phenotypes are likely to be spurious. discarding above-mentioned genes decreased the percentage of phenotype-related genes by about 50% on average. in analyzing gene clusters, we first considered gene clusters of which their presence relates to a positive trait and absence relates to a negative trait. there were also many gene clusters with inverse patterns, where an absence of a gene cluster leads to a positive trait. an inverse relationship between genes and phenotypes might indicate that in the absence of a regulator, genes previously inhibited by this particular regulator can become active, which in turn might lead to a positive trait. in the supplementary data we provide all identified relations including inverse relations. genes related to carbohydrate utilization several gene clusters related to fermentation of different sugars were identified by genotype-phenotype matching. among them were gene clusters that were previously described to be involved in carbohydrate utilization. for instance, the presence of a gene cluster required for arabinose utilization was confirmed in this study to correlate strongly with the ability to grow on arabinose. several gene clusters were found to be related to sucrose utilization; for instance a cluster of genes that already was annotated as being involved in sucrose utilization. the other three reference strains do not grow on sucrose, and this gene cluster was absent in these strains. these genes were also found to be inversely related to growth on lactose, where they were present in most of the strains that grew slowly on lactose and absent in most of the strains that can grow on lactose. such a relationship suggests that most of the strains that grow well on sucrose cannot grow or grow slowly on lactose or vice-versa. this also partly reflects niche adaptation of these strains, because most of the lactose-degrading strains were dairy isolates and most of the sucrose-utilizing strains were of plant origin. additionally, we also identified an association between sucrose fermentation and nisin production in l. lactis. both sucrose utilization and nisin biosynthesis genes were earlier reported to be encoded on a transposon in strain nizo r. additionally, linkage between these phenotypes has been observed in l. lactis strains. visualization of identified gene-phenotype relations revealed that sucrose-negative strains lack part or all of the genes related to nisin production. for example, kf - a nisin non-producer strain - contains only part of the nisin gene cluster, conferring immunity but not production. however, we found no strong relation between growth on sucrose and presence of nisin biosynthesis genes, confirming a previous observation that the presence of nisin biosynthesis genes in a strain does not always confer its growth on sucrose. a large cluster of genes was found to be related to growth on melibiose, a plant disaccharide, but not to any of the other carbohydrates tested. this confirms an earlier observation that strain kf can utilize this disaccharide while other strains il, sk and kf strains cannot grow on melibiose. we also investigated whether a genomic region that encompasses these genes was deleted in melibiose-negative strains, because chromosomal deletion of a kb region in streptococcus mutans strains leads to melibiose-negative phenotype; this kb region contains orthologs of llkf_2260- of strain kf because tiling pan-genome cgh arrays were used to identify gene occurrence in these strains, deletion of a genomic region in query strains can be determined. therefore, we visualized a small genomic region of approximately kb that covers the starting position of llkf_ and the end position of llkf_ on the kf genome. this region encompasses all these genes and several more genes. indeed, we also observed that this large kb region was deleted or absent in all melibiose-negative strains from both plant and dairy origin. probably, only genes consecutively located in a kb region are necessary for growth on melibiose. genes related to metal resistance using genotype-phenotype matching several gene clusters were found relating to heavy metal resistance, and some of these genes are located on plasmids. for instance, we found clusters of genes related to copper resistance; these are located on plasmids c and d in strain sk, which confirms a previous finding. one of these gene clusters was previously identified to be involved in copper resistance. additionally, a cluster of four genes was identified by gene-trait matching to be related to arsenite resistance, which is usually known as a plasmid-borne trait, and two of these genes are annotated as arsenical-resistance proteins. however, these could be plasmid genes that were transferred to the chromosome in the plasmid curing process of mg genes related to arginine metabolism several gene clusters were found to be relevant to arginine hydrolase activity, and therefore the ability to metabolize arginine. a cluster of genes was identified to be relevant to arginine metabolism. all proteins are annotated as hypothetical proteins in strain il and two of them, l and l are probably membrane proteins as they belong to a cluster of orthologous groups of proteins, which contains membrane proteins. a gene cluster of mg genes was also identified to be related to arginine metabolism, and two encoded proteins, llmg_ and llmg_ are in the same cogs with proteins l and l of strain il the protein l belongs to a family of membrane proteins of which some are glycosyltransferase-associated proteins. probably, at least two of these proteins, l and l and their mg orthologs, llmg_ and llmg_ should be re-annotated as transport proteins or maybe more specifically arginine transport proteins. however, experimental validation is necessary. plasmid genes related to phenotypes plasmid genes are necessary for manifestation of some phenotypes. for instance, it is already well-known that the lactose metabolism genes are localized on plasmid d of sk. indeed, we found that the presence/absence of these lactose metabolism genes in the strains to be highly correlated to growth on lactose. again, there appears to be an inverse relationship with the presence of these same lactose utilization genes for no-growth on some other sugars. thus, using plasmid genes in addition to chromosomal genes in genotype-phenotype matching allowed confirming previously known functions of some plasmid genes and identifying novel relationships between plasmid genes and some phenotypes. partial gene-phenotype relations for each experiment category several partial relations between gene clusters and phenotypes, where a gene is present in only a subset of strains with a particular phenotype, were identified. most of these gene clusters contain only two genes and were often found to be relevant to a negative trait. as example we present partial relations between a cluster of four genes of strain mg and arsenite resistance. these genes were found to be relevant for strains growing at mm of arsenite and are present in most of the highly resistant strains. however, some of these genes are only present in a subset of strains with no or mild resistance. visualizing occurrence of these genes in strains revealed that they are mostly absent in strains with no arsenite resistance phenotype and mostly present in strains with mild or high arsenite resistance phenotypes. discussion genotype-phenotype association analysis of l. lactis strains by integrating large genotype and phenotype data sets allowed screening of gene to phenotype relations. only the top genes per phenotype were selected as important, because probably most relevant genes related to a phenotype should be among these genes and their correlated genes. indeed, only less than 1% of phenotypes had or more related genes in the top list. furthermore, identified relations were visualized by integrating each gene’s occurrence with its phenotype importance, which allows a quick screening of many relations. however, some relations could be due to an indirect effect of other factors that were not taken into account. for example, the anti-correlation between sucrose and lactose metabolism could be a bias resulting from starter-culture selection programmes, where often bacteriocin-negative strains were selected that could have led to selection of strains that can use lactose instead of sucrose. additionally, for some phenotypes we could not find many related genes, for example, well-known arginine-metabolism related genes were not found as relevant to metabolism of arginine. therefore, we analyzed all ogs with gene members containing a word ‘arginine’ in their annotation and genes of the arginine deiminase pathway. however, all these genes were either present in all or in at least out of strains, and such genes are removed in the pre-processing step of phenolink, because they are not capable to separate strains with different phenotypes. we described a few examples where the annotation of genes could be refined and a few cases where new functions are suggested for genes with unknown functions. we were able to pinpoint only a few novel relations, but analyzing all identified gene-phenotype relations in detail should allow finding even more novel relations and refining annotations of more genes. genotype-phenotype matching allows comprehensive screening for possible relations between genes and phenotypes. we had data for strains and, thus, there were relatively few strains with a given phenotype and in some experiments many strains manifested the same phenotype. therefore, few partial gene-phenotype relations were identified in this study. more partial relations could be identified using data sets based on more l. lactis strains, which would allow finding analogous genes that have similar function but different sequences. even with dna sequencing prices dropping, determining the gene content of dozens of strains by genome sequencing could still be costly. pan-genome arrays allow querying occurrence of genes in multiple strains more cost-effectively, but genes absent in reference sequences and strongly divergent genes would be missed. though the presence/absence data can be linked to phenotypes, it cannot account for effects of regulatory control or post-translational modifications. thus putative gene-phenotype relations should be experimentally tested by high-throughput techniques such as gene expression analysis. annotating genes of a genome is essential in understanding the genomic properties of any strain. gene annotation is often based on sequence similarity, so mistakes in annotating a single gene could propagate to genes of different organisms through annotation by sequence similarity. therefore identified gene-phenotype relations should be experimentally validated and linked to other information sources such as pathway information. this would allow decreasing error propagation introduced by sequence similarity based gene function prediction approaches. genotype-phenotype matching results show that the largest group of proteins related to phenotypes was hypothetical proteins indicating that gene annotations could still be improved for all reference strains. genomes of more bacterial strains are sequenced on a daily basis, which shows the critical importance of accurate gene function prediction. identified gene-phenotype relations would allow more accurately determining functions of many genes, and hence better understanding of genotype- and phenotype-level differences among l. lactis strains. we provide all identified relations as well as complete genotype and phenotype data set. this data set not only serves as a collection of leads to phenotypes, but due to large data size could also be used to test different association methods.  lactococcus lactis has been extensively studied due to its industrial importance. here we provide a coherent genotype and phenotype dataset and its interpretation for the lactococcus species. we integrated for l. lactis strains their genotypic measurements as well as phenotypes derived from different experiments to identify gene-phenotype relations. our results are publicly available and contains many leads into lactococcus species-wide genotype-phenotype relations that can further be analysed and experimentally validated. these relations could be used to refine functions of genes. as new genome sequences emerge frequently, this would allow annotating gene functions for these new genomes more accurately and predicting phenotypes of new strains based on their dna sequence. 
gene occurrence and phenotype data were used in an iterative gene selection procedure, based on the random forest algorithm, to identify genotype-phenotype relations. in addition to all gene-phenotype relations, we also provide coherent phenotype data for lactococcus strains assessed in different phenotyping experiments, which to our knowledge is the largest to date for the lactococcus lactis species. additionally, several novel gene-phenotype relations were uncovered, for instance, genes related to arsenite resistance or arginine metabolism. lactococcus lactis is used in dairy food fermentation and for the efficient production of industrially relevant enzymes. our results indicate that genotype-phenotype matching by integrating large data sets provides the possibility to identify gene-phenotype relations, possibly improve gene function annotation and identified relations can be used for screening bacterial culture collections for desired phenotypes. the genome content and different phenotypes have been determined for multiple l. lactis strains in order to understand intra-species genotype and phenotype diversity and annotate gene functions. we also identified a gene cluster related to growth on melibiose, a plant disaccharide; this cluster is present only in melibiose-positive strains and can be used as a genetic marker in trait improvement. a total of gene-phenotype relations were found, of which some confirmed known gene-phenotype relations, such as the importance of arabinose utilization genes only for strains of plant origin. in this study, we identified relations between gene presence and a collection of phenotypes across l. lactis strains of dairy and plant origin.
 lactococcus lactis is used in dairy food fermentation and for the efficient production of industrially relevant enzymes. the genome content and different phenotypes have been determined for multiple l. lactis strains in order to understand intra-species genotype and phenotype diversity and annotate gene functions. in this study, we identified relations between gene presence and a collection of phenotypes across l. lactis strains of dairy and plant origin. gene occurrence and phenotype data were used in an iterative gene selection procedure, based on the random forest algorithm, to identify genotype-phenotype relations.  a total of gene-phenotype relations were found, of which some confirmed known gene-phenotype relations, such as the importance of arabinose utilization genes only for strains of plant origin. we also identified a gene cluster related to growth on melibiose, a plant disaccharide; this cluster is present only in melibiose-positive strains and can be used as a genetic marker in trait improvement. additionally, several novel gene-phenotype relations were uncovered, for instance, genes related to arsenite resistance or arginine metabolism.  our results indicate that genotype-phenotype matching by integrating large data sets provides the possibility to identify gene-phenotype relations, possibly improve gene function annotation and identified relations can be used for screening bacterial culture collections for desired phenotypes. in addition to all gene-phenotype relations, we also provide coherent phenotype data for lactococcus strains assessed in different phenotyping experiments, which to our knowledge is the largest to date for the lactococcus lactis species. 